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  1. {
  2. "cells": [
  3. {
  4. "cell_type": "code",
  5. "execution_count": 1,
  6. "metadata": {
  7. "collapsed": false
  8. },
  9. "outputs": [
  10. {
  11. "data": {
  12. "text/html": [
  13. "<script>jQuery(function() {if (jQuery(\"body.notebook_app\").length == 0) { jQuery(\".input_area\").toggle(); jQuery(\".prompt\").toggle();}});</script>"
  14. ]
  15. },
  16. "metadata": {},
  17. "output_type": "display_data"
  18. },
  19. {
  20. "data": {
  21. "text/html": [
  22. "<button onclick=\"jQuery('.input_area').toggle(); jQuery('.prompt').toggle();\">Toggle code</button>"
  23. ]
  24. },
  25. "metadata": {},
  26. "output_type": "display_data"
  27. }
  28. ],
  29. "source": [
  30. "import IPython.core.display as di\n",
  31. "\n",
  32. "# This line will hide code by default when the notebook is exported as HTML\n",
  33. "di.display_html('<script>jQuery(function() {if (jQuery(\"body.notebook_app\").length == 0) { jQuery(\".input_area\").toggle(); jQuery(\".prompt\").toggle();}});</script>', raw=True)\n",
  34. "\n",
  35. "# This line will add a button to toggle visibility of code blocks, for use with the HTML export version\n",
  36. "di.display_html('''<button onclick=\"jQuery('.input_area').toggle(); jQuery('.prompt').toggle();\">Toggle code</button>''', raw=True)"
  37. ]
  38. },
  39. {
  40. "cell_type": "code",
  41. "execution_count": 2,
  42. "metadata": {
  43. "collapsed": true
  44. },
  45. "outputs": [],
  46. "source": [
  47. "from IPython.display import display, HTML\n",
  48. "from itertools import combinations, product"
  49. ]
  50. },
  51. {
  52. "cell_type": "code",
  53. "execution_count": 3,
  54. "metadata": {
  55. "collapsed": false
  56. },
  57. "outputs": [],
  58. "source": [
  59. "from jarvis.brain.utility.data_preparation import (get_metrics_single_date, get_metrics_date_range)\n",
  60. "import numpy as np\n",
  61. "import pandas as pd\n",
  62. "from sklearn import tree\n",
  63. "import pydotplus\n",
  64. "global_metrics = ['ga_cpt', 'fb_spend', 'ga_transactions', 'ga_revenue']\n",
  65. "goal_metric = 'ga_cpt'"
  66. ]
  67. },
  68. {
  69. "cell_type": "code",
  70. "execution_count": 7,
  71. "metadata": {
  72. "collapsed": false
  73. },
  74. "outputs": [],
  75. "source": [
  76. "start = '2017-02-21'\n",
  77. "end = '2017-03-21'\n",
  78. "df = get_metrics_date_range(119, 'ad', start, end, global_metrics, custom_tags=True, active=False)"
  79. ]
  80. },
  81. {
  82. "cell_type": "code",
  83. "execution_count": 8,
  84. "metadata": {
  85. "collapsed": false
  86. },
  87. "outputs": [],
  88. "source": [
  89. "df= df[df['App Type'] == 'Web']"
  90. ]
  91. },
  92. {
  93. "cell_type": "code",
  94. "execution_count": 65,
  95. "metadata": {
  96. "collapsed": true
  97. },
  98. "outputs": [],
  99. "source": [
  100. "excluded_tags = ['Campaigns', 'ad_id', 'Image', 'Adsets', 'start_date', '_id', 'Ads',\n",
  101. " 'end_date', 'Active Ads Count in Adset', 'Active Adsets Count in Campaign', 'Labels', 'audience type', 'audience category', 'Product Set',\n",
  102. " 'Prominent Text', 'Dominant Color', 'DominantColor', 'ProminentText', 'NumberofFaces', 'Number of Faces', 'Sale', 'name', 'Carousel Count']\n",
  103. "\n",
  104. "user_tags = ['Current Adsets', 'AdsetStrategy']\n",
  105. "excluded_tags = excluded_tags + user_tags"
  106. ]
  107. },
  108. {
  109. "cell_type": "code",
  110. "execution_count": 66,
  111. "metadata": {
  112. "collapsed": true
  113. },
  114. "outputs": [],
  115. "source": [
  116. "def exclude_single_dominant_tag(tags, df):\n",
  117. " all_tags = []\n",
  118. " total_spend = df.fb_spend.sum()\n",
  119. " for tag in tags:\n",
  120. " grp = df.groupby(tag).sum()\n",
  121. " grp['prop'] = grp.fb_spend / total_spend\n",
  122. " if pd.np.max(grp['prop']) > 0.95:\n",
  123. " print(tag)\n",
  124. " continue\n",
  125. " all_tags.append(tag)\n",
  126. " return all_tags\n",
  127. "def clean_tags(df, excluded_tags, global_metrics):\n",
  128. " all_tags = list(set(df.columns) - set(global_metrics) - set(excluded_tags))\n",
  129. " all_tags = [tag for tag in all_tags if len(df[df[tag] != 'None'][tag].unique()) > 1]\n",
  130. " all_tags = [tag for tag in all_tags if df[tag].count() > 0.25*len(df)]\n",
  131. " all_tags = exclude_single_dominant_tag(all_tags, df) \n",
  132. " return all_tags"
  133. ]
  134. },
  135. {
  136. "cell_type": "code",
  137. "execution_count": 67,
  138. "metadata": {
  139. "collapsed": false
  140. },
  141. "outputs": [
  142. {
  143. "name": "stdout",
  144. "output_type": "stream",
  145. "text": [
  146. "User OS\n",
  147. "Behaviors\n"
  148. ]
  149. }
  150. ],
  151. "source": [
  152. "all_tags = clean_tags(df, excluded_tags, global_metrics)"
  153. ]
  154. },
  155. {
  156. "cell_type": "markdown",
  157. "metadata": {},
  158. "source": [
  159. "### Tags after cleanup"
  160. ]
  161. },
  162. {
  163. "cell_type": "code",
  164. "execution_count": 68,
  165. "metadata": {
  166. "collapsed": false
  167. },
  168. "outputs": [
  169. {
  170. "data": {
  171. "text/plain": [
  172. "['Gender',\n",
  173. " 'Lookalike Types',\n",
  174. " 'Optimization Goal',\n",
  175. " 'Landing Pages',\n",
  176. " 'Audience Types',\n",
  177. " 'Audience Strategy',\n",
  178. " 'strategy',\n",
  179. " 'Campaign Objective',\n",
  180. " 'Device Platforms',\n",
  181. " 'Facebook Positions',\n",
  182. " 'Billing Event',\n",
  183. " 'Age Range',\n",
  184. " 'Publisher Platforms',\n",
  185. " 'Ad Format',\n",
  186. " 'Interests',\n",
  187. " 'Locations',\n",
  188. " 'Ad Type',\n",
  189. " 'Custom Audiences']"
  190. ]
  191. },
  192. "execution_count": 68,
  193. "metadata": {},
  194. "output_type": "execute_result"
  195. }
  196. ],
  197. "source": [
  198. "all_tags"
  199. ]
  200. },
  201. {
  202. "cell_type": "code",
  203. "execution_count": 69,
  204. "metadata": {
  205. "collapsed": true
  206. },
  207. "outputs": [],
  208. "source": [
  209. "df_org = df.copy()"
  210. ]
  211. },
  212. {
  213. "cell_type": "code",
  214. "execution_count": 70,
  215. "metadata": {
  216. "collapsed": false
  217. },
  218. "outputs": [],
  219. "source": [
  220. "df = df_org[df_org['App Type'] == 'Web']"
  221. ]
  222. },
  223. {
  224. "cell_type": "code",
  225. "execution_count": 71,
  226. "metadata": {
  227. "collapsed": true
  228. },
  229. "outputs": [],
  230. "source": [
  231. "df_global = df.copy()"
  232. ]
  233. },
  234. {
  235. "cell_type": "code",
  236. "execution_count": 72,
  237. "metadata": {
  238. "collapsed": false
  239. },
  240. "outputs": [],
  241. "source": [
  242. "total_spend = df_global.fb_spend.sum()"
  243. ]
  244. },
  245. {
  246. "cell_type": "code",
  247. "execution_count": 73,
  248. "metadata": {
  249. "collapsed": false
  250. },
  251. "outputs": [],
  252. "source": [
  253. "tag_scores = {}\n",
  254. "for tag in all_tags:\n",
  255. " temp = df.groupby([tag]).sum()\n",
  256. " temp['prop'] = temp['fb_spend'] / total_spend\n",
  257. " tag_scores[tag] = temp[temp.index != 'None']['prop'].mean()"
  258. ]
  259. },
  260. {
  261. "cell_type": "markdown",
  262. "metadata": {},
  263. "source": [
  264. "### Scores"
  265. ]
  266. },
  267. {
  268. "cell_type": "code",
  269. "execution_count": 74,
  270. "metadata": {
  271. "collapsed": false
  272. },
  273. "outputs": [
  274. {
  275. "data": {
  276. "text/plain": [
  277. "[('Interests', 0.012374212466183188),\n",
  278. " ('Landing Pages', 0.016936776591743516),\n",
  279. " ('Custom Audiences', 0.02514431012335517),\n",
  280. " ('Lookalike Types', 0.0362420481952802),\n",
  281. " ('Age Range', 0.07142857142857138),\n",
  282. " ('Audience Types', 0.12491133392877621),\n",
  283. " ('strategy', 0.15954100510681227),\n",
  284. " ('Facebook Positions', 0.1636805829167642),\n",
  285. " ('Locations', 0.16666666666666677),\n",
  286. " ('Publisher Platforms', 0.20000000000000004),\n",
  287. " ('Optimization Goal', 0.24999999999999986),\n",
  288. " ('Campaign Objective', 0.25),\n",
  289. " ('Audience Strategy', 0.33333333333333326),\n",
  290. " ('Gender', 0.33333333333333326),\n",
  291. " ('Device Platforms', 0.3333333333333334),\n",
  292. " ('Ad Type', 0.33333333333333387),\n",
  293. " ('Ad Format', 0.33333333333333387),\n",
  294. " ('Billing Event', 0.4999999999999997)]"
  295. ]
  296. },
  297. "execution_count": 74,
  298. "metadata": {},
  299. "output_type": "execute_result"
  300. }
  301. ],
  302. "source": [
  303. "import operator\n",
  304. "sorted(tag_scores.items(), key=operator.itemgetter(1))"
  305. ]
  306. },
  307. {
  308. "cell_type": "code",
  309. "execution_count": 75,
  310. "metadata": {
  311. "collapsed": false
  312. },
  313. "outputs": [],
  314. "source": [
  315. "score_df = pd.DataFrame().from_dict(tag_scores, orient='index')\n",
  316. "score_df = score_df.rename(columns = {0:'score'})"
  317. ]
  318. },
  319. {
  320. "cell_type": "code",
  321. "execution_count": 76,
  322. "metadata": {
  323. "collapsed": true
  324. },
  325. "outputs": [],
  326. "source": [
  327. "score_df = score_df[pd.notnull(score_df['score'])]"
  328. ]
  329. },
  330. {
  331. "cell_type": "code",
  332. "execution_count": 77,
  333. "metadata": {
  334. "collapsed": true
  335. },
  336. "outputs": [],
  337. "source": [
  338. "num_levels = 4"
  339. ]
  340. },
  341. {
  342. "cell_type": "code",
  343. "execution_count": 78,
  344. "metadata": {
  345. "collapsed": false
  346. },
  347. "outputs": [],
  348. "source": [
  349. "from sklearn.cluster import KMeans\n",
  350. "from sklearn import preprocessing\n",
  351. "\n",
  352. "train = score_df[pd.notnull(score_df['score'])].values\n",
  353. "train = preprocessing.scale(train)\n",
  354. "kmeans_model = KMeans(n_clusters=num_levels, random_state=1).fit(train)"
  355. ]
  356. },
  357. {
  358. "cell_type": "code",
  359. "execution_count": 79,
  360. "metadata": {
  361. "collapsed": false
  362. },
  363. "outputs": [],
  364. "source": [
  365. "score_df['level'] = kmeans_model.labels_"
  366. ]
  367. },
  368. {
  369. "cell_type": "code",
  370. "execution_count": 80,
  371. "metadata": {
  372. "collapsed": false
  373. },
  374. "outputs": [],
  375. "source": [
  376. "score_levels = {}\n",
  377. "for level in range(num_levels):\n",
  378. " score_levels[level] = score_df[score_df['level'] == level]['score'].mean()\n",
  379. "\n",
  380. "levels = sorted(score_levels.items(), key=operator.itemgetter(1), reverse=True)"
  381. ]
  382. },
  383. {
  384. "cell_type": "code",
  385. "execution_count": 81,
  386. "metadata": {
  387. "collapsed": false
  388. },
  389. "outputs": [],
  390. "source": [
  391. "global_tag_list = [score_df[score_df['level']==levels[level][0]].index.tolist() for level in range(num_levels)]"
  392. ]
  393. },
  394. {
  395. "cell_type": "markdown",
  396. "metadata": {},
  397. "source": [
  398. "### Tag levels"
  399. ]
  400. },
  401. {
  402. "cell_type": "code",
  403. "execution_count": 82,
  404. "metadata": {
  405. "collapsed": false
  406. },
  407. "outputs": [
  408. {
  409. "name": "stdout",
  410. "output_type": "stream",
  411. "text": [
  412. "Level 1: ['Billing Event']\n",
  413. "Level 2: ['Audience Strategy', 'Gender', 'Optimization Goal', 'Ad Type', 'Ad Format', 'Device Platforms', 'Campaign Objective']\n",
  414. "Level 3: ['Facebook Positions', 'Publisher Platforms', 'strategy', 'Locations', 'Audience Types']\n",
  415. "Level 4: ['Lookalike Types', 'Interests', 'Landing Pages', 'Custom Audiences', 'Age Range']\n"
  416. ]
  417. }
  418. ],
  419. "source": [
  420. "for level in range(num_levels):\n",
  421. " print('Level {0}:'.format(level + 1) , global_tag_list[level])"
  422. ]
  423. },
  424. {
  425. "cell_type": "code",
  426. "execution_count": 83,
  427. "metadata": {
  428. "collapsed": true
  429. },
  430. "outputs": [],
  431. "source": [
  432. "# global_tag_list = ['Campaign Objective']"
  433. ]
  434. },
  435. {
  436. "cell_type": "code",
  437. "execution_count": 84,
  438. "metadata": {
  439. "collapsed": true
  440. },
  441. "outputs": [],
  442. "source": [
  443. "aggregations = {'fb_spend': pd.np.sum,\n",
  444. " 'ga_transactions': pd.np.sum,\n",
  445. " 'ga_revenue': pd.np.sum,\n",
  446. " }"
  447. ]
  448. },
  449. {
  450. "cell_type": "code",
  451. "execution_count": 85,
  452. "metadata": {
  453. "collapsed": false
  454. },
  455. "outputs": [],
  456. "source": [
  457. "overall = df_global['fb_spend'].sum() / df_global['ga_transactions'].sum()"
  458. ]
  459. },
  460. {
  461. "cell_type": "code",
  462. "execution_count": 86,
  463. "metadata": {
  464. "collapsed": false
  465. },
  466. "outputs": [],
  467. "source": [
  468. "df_global['ga_cpt'] = df_global['fb_spend'] / df_global['ga_transactions']\n",
  469. "df_global.replace([pd.np.inf, -pd.np.inf, float('inf')], 0, inplace=True)"
  470. ]
  471. },
  472. {
  473. "cell_type": "code",
  474. "execution_count": 87,
  475. "metadata": {
  476. "collapsed": true
  477. },
  478. "outputs": [],
  479. "source": [
  480. "overall_dev = df_global.ga_cpt.std()"
  481. ]
  482. },
  483. {
  484. "cell_type": "code",
  485. "execution_count": 88,
  486. "metadata": {
  487. "collapsed": false
  488. },
  489. "outputs": [],
  490. "source": [
  491. "P = pd.np.percentile(df_global.fb_spend, [10, 100])"
  492. ]
  493. },
  494. {
  495. "cell_type": "code",
  496. "execution_count": 89,
  497. "metadata": {
  498. "collapsed": false
  499. },
  500. "outputs": [],
  501. "source": [
  502. "df_global_true = df_global.copy()"
  503. ]
  504. },
  505. {
  506. "cell_type": "code",
  507. "execution_count": 90,
  508. "metadata": {
  509. "collapsed": true
  510. },
  511. "outputs": [],
  512. "source": [
  513. "df_global = df_global#[(df_global.fb_spend >= P[0]) & (df_global.fb_spend <= P[1])]"
  514. ]
  515. },
  516. {
  517. "cell_type": "code",
  518. "execution_count": 91,
  519. "metadata": {
  520. "collapsed": true
  521. },
  522. "outputs": [],
  523. "source": [
  524. "df_global = df_global[df_global.ga_cpt > 0]"
  525. ]
  526. },
  527. {
  528. "cell_type": "code",
  529. "execution_count": 98,
  530. "metadata": {
  531. "collapsed": false
  532. },
  533. "outputs": [],
  534. "source": [
  535. "def process_paths(df, tag_list_obj):\n",
  536. " \n",
  537. " \n",
  538. " def recurse_paths(tag_list, tag_list_old, tag_values_old):\n",
  539. " if len(tag_list):\n",
  540. " tag_level = tag_list.pop(0)\n",
  541. "\n",
  542. " tags = []\n",
  543. " if isinstance(tag_level, list):\n",
  544. " tags = tags + tag_level\n",
  545. " else:\n",
  546. " tags = tags + [tag_level]\n",
  547. " \n",
  548. " if len(tag_list_old):\n",
  549. " old = df.groupby(tag_list_old).agg(aggregations)\n",
  550. " old['ga_cpt'] = old['fb_spend'] / old['ga_transactions']\n",
  551. " old_cpt = old.loc[tag_values_old]['ga_cpt']\n",
  552. " old_spend = old.loc[tag_values_old]['fb_spend']\n",
  553. " else:\n",
  554. " old = df\n",
  555. " old_cpt = old.fb_spend.sum() / old.ga_transactions.sum()\n",
  556. " old_spend = old.fb_spend.sum()\n",
  557. "\n",
  558. " premature = True\n",
  559. " for tag in tags:\n",
  560. " new_tag_list = tag_list_old + [tag]\n",
  561. "\n",
  562. " new = df.groupby(new_tag_list).agg(aggregations)\n",
  563. " new['ga_cpt'] = new['fb_spend'] / new['ga_transactions']\n",
  564. " prop = new['fb_spend'] / old_spend\n",
  565. " \n",
  566. " if pd.np.max(prop) > 0.95:\n",
  567. " continue\n",
  568. " \n",
  569. " tag_values = set([val[-1] if isinstance(val, tuple) else val for val in new.index.values.tolist()] )\n",
  570. "\n",
  571. " if (tag_values == ['None']):\n",
  572. " continue\n",
  573. "\n",
  574. " for value in tag_values:\n",
  575. " if value == 'None':\n",
  576. " continue\n",
  577. " new_tag_value = tag_values_old + (value,)\n",
  578. " try:\n",
  579. " new.loc[new_tag_value]\n",
  580. " except:\n",
  581. " continue\n",
  582. " if True:#(new.loc[new_tag_value].fb_spend >= P[0]) & (new.loc[new_tag_value].fb_spend <= P[1]):\n",
  583. " value_df = new.loc[new_tag_value]\n",
  584. " bad_condition = (((value_df.fb_spend / value_df.ga_transactions) - old_cpt) / old_cpt ) > 0.2\n",
  585. " good_condition = (((value_df.fb_spend / value_df.ga_transactions) - old_cpt) / old_cpt )< -0.2\n",
  586. " if bad_condition:\n",
  587. " bad[new_tag_value] = {'cpt': value_df.fb_spend / value_df.ga_transactions,\n",
  588. " 'spend_prop': value_df.fb_spend*100 / df_global.fb_spend.sum(),\n",
  589. " 'tag_list': new_tag_list}\n",
  590. " \n",
  591. " if good_condition:\n",
  592. " good[new_tag_value] = {'cpt': value_df.fb_spend / value_df.ga_transactions,\n",
  593. " 'spend_prop': value_df.fb_spend*100 / df_global.fb_spend.sum(),\n",
  594. " 'tag_list': new_tag_list} \n",
  595. " \n",
  596. " premature = False\n",
  597. " recurse_paths(tag_list[:], new_tag_list[:], new_tag_value[:])\n",
  598. " \n",
  599. " if premature and len(tag_list):\n",
  600. " recurse_paths(tag_list[:], tag_list_old, tag_values_old)\n",
  601. " \n",
  602. " recurse_paths(tag_list_obj, [], ())"
  603. ]
  604. },
  605. {
  606. "cell_type": "code",
  607. "execution_count": 99,
  608. "metadata": {
  609. "collapsed": true
  610. },
  611. "outputs": [],
  612. "source": [
  613. "bad = {}\n",
  614. "good = {}"
  615. ]
  616. },
  617. {
  618. "cell_type": "code",
  619. "execution_count": 100,
  620. "metadata": {
  621. "collapsed": false
  622. },
  623. "outputs": [],
  624. "source": [
  625. "tag_list = global_tag_list\n",
  626. "process_paths(df_global, tag_list[:])\n",
  627. "bad_raw = bad.copy()\n",
  628. "good_raw = good.copy()"
  629. ]
  630. },
  631. {
  632. "cell_type": "code",
  633. "execution_count": 61,
  634. "metadata": {
  635. "collapsed": false
  636. },
  637. "outputs": [],
  638. "source": [
  639. "def get_filtered_paths(paths):\n",
  640. " filtered_paths = {key: value for (key, value) in paths.items() if value['spend_prop'] > 2}\n",
  641. "\n",
  642. " processed_paths = {}\n",
  643. " for key, value in filtered_paths.items():\n",
  644. " l = list(key)\n",
  645. " none_list = ['-']*len(tag_list)\n",
  646. " none_list[:len(l)] = l\n",
  647. " if len(none_list) > 1:\n",
  648. " new_key = tuple(none_list)\n",
  649. " else:\n",
  650. " new_key = none_list[0]\n",
  651. "\n",
  652. " if tuple(value['tag_list']) in processed_paths:\n",
  653. " processed_paths[tuple(value['tag_list'])][new_key] = {metric: val for metric, val in value.items() if metric != 'tag_list'}\n",
  654. " else:\n",
  655. " processed_paths[tuple(value['tag_list'])] = {}\n",
  656. " processed_paths[tuple(value['tag_list'])][new_key] = {metric: val for metric, val in value.items() if metric != 'tag_list'}\n",
  657. "\n",
  658. " impact_values = {}\n",
  659. " for key, value in processed_paths.items():\n",
  660. " out_df = pd.DataFrame().from_dict(value, orient='index')\n",
  661. " impact = out_df.cpt.mean()*out_df.spend_prop.mean()\n",
  662. " impact_values[key] = impact\n",
  663. "\n",
  664. " impacts = sorted(impact_values.items(), key=operator.itemgetter(1), reverse=True)\n",
  665. " \n",
  666. " return processed_paths, impacts"
  667. ]
  668. },
  669. {
  670. "cell_type": "code",
  671. "execution_count": 62,
  672. "metadata": {
  673. "collapsed": true
  674. },
  675. "outputs": [],
  676. "source": [
  677. "def display_df(paths, impacts_list, num=10, level=[4]):\n",
  678. " impacts_list = [val for val in impacts_list if len(val) in level]\n",
  679. " for key, value in paths.items():\n",
  680. " if key in impacts_list[:num]:\n",
  681. " b = pd.DataFrame().from_dict(value, orient='index')\n",
  682. " none_list = ['-']*len(tag_list)\n",
  683. " l = list(key)\n",
  684. " if len(l) in level:\n",
  685. " none_list[:len(l)] = l\n",
  686. "\n",
  687. " b.index = b.index.set_names(none_list)\n",
  688. "\n",
  689. " display(b)"
  690. ]
  691. },
  692. {
  693. "cell_type": "markdown",
  694. "metadata": {},
  695. "source": [
  696. "### Bad paths"
  697. ]
  698. },
  699. {
  700. "cell_type": "code",
  701. "execution_count": 63,
  702. "metadata": {
  703. "collapsed": false
  704. },
  705. "outputs": [
  706. {
  707. "data": {
  708. "text/html": [
  709. "<div>\n",
  710. "<table border=\"1\" class=\"dataframe\">\n",
  711. " <thead>\n",
  712. " <tr style=\"text-align: right;\">\n",
  713. " <th></th>\n",
  714. " <th></th>\n",
  715. " <th></th>\n",
  716. " <th></th>\n",
  717. " <th>spend_prop</th>\n",
  718. " <th>cpt</th>\n",
  719. " </tr>\n",
  720. " <tr>\n",
  721. " <th>Billing Event</th>\n",
  722. " <th>Campaign Objective</th>\n",
  723. " <th>Publisher Platforms</th>\n",
  724. " <th>Age Range</th>\n",
  725. " <th></th>\n",
  726. " <th></th>\n",
  727. " </tr>\n",
  728. " </thead>\n",
  729. " <tbody>\n",
  730. " <tr>\n",
  731. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  732. " <th rowspan=\"2\" valign=\"top\">Conversions</th>\n",
  733. " <th rowspan=\"2\" valign=\"top\">audience_network or facebook</th>\n",
  734. " <th>18-35</th>\n",
  735. " <td>3.725390</td>\n",
  736. " <td>2119.010761</td>\n",
  737. " </tr>\n",
  738. " <tr>\n",
  739. " <th>23-38</th>\n",
  740. " <td>3.084434</td>\n",
  741. " <td>1855.262874</td>\n",
  742. " </tr>\n",
  743. " </tbody>\n",
  744. "</table>\n",
  745. "</div>"
  746. ],
  747. "text/plain": [
  748. " spend_prop \\\n",
  749. "Billing Event Campaign Objective Publisher Platforms Age Range \n",
  750. "Impressions Conversions audience_network or facebook 18-35 3.725390 \n",
  751. " 23-38 3.084434 \n",
  752. "\n",
  753. " cpt \n",
  754. "Billing Event Campaign Objective Publisher Platforms Age Range \n",
  755. "Impressions Conversions audience_network or facebook 18-35 2119.010761 \n",
  756. " 23-38 1855.262874 "
  757. ]
  758. },
  759. "metadata": {},
  760. "output_type": "display_data"
  761. },
  762. {
  763. "data": {
  764. "text/html": [
  765. "<div>\n",
  766. "<table border=\"1\" class=\"dataframe\">\n",
  767. " <thead>\n",
  768. " <tr style=\"text-align: right;\">\n",
  769. " <th></th>\n",
  770. " <th></th>\n",
  771. " <th></th>\n",
  772. " <th></th>\n",
  773. " <th>spend_prop</th>\n",
  774. " <th>cpt</th>\n",
  775. " </tr>\n",
  776. " <tr>\n",
  777. " <th>Billing Event</th>\n",
  778. " <th>Audience Strategy</th>\n",
  779. " <th>Publisher Platforms</th>\n",
  780. " <th>Landing Pages</th>\n",
  781. " <th></th>\n",
  782. " <th></th>\n",
  783. " </tr>\n",
  784. " </thead>\n",
  785. " <tbody>\n",
  786. " <tr>\n",
  787. " <th rowspan=\"3\" valign=\"top\">Impressions</th>\n",
  788. " <th rowspan=\"3\" valign=\"top\">Prospecting</th>\n",
  789. " <th rowspan=\"3\" valign=\"top\">audience_network or facebook</th>\n",
  790. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  791. " <td>3.241590</td>\n",
  792. " <td>2094.220494</td>\n",
  793. " </tr>\n",
  794. " <tr>\n",
  795. " <th>www.koovs.com/women/tags/holi-promo</th>\n",
  796. " <td>2.145768</td>\n",
  797. " <td>1935.994483</td>\n",
  798. " </tr>\n",
  799. " <tr>\n",
  800. " <th>www.koovs.com/women/tags/spring-into-march</th>\n",
  801. " <td>3.115504</td>\n",
  802. " <td>1940.878333</td>\n",
  803. " </tr>\n",
  804. " </tbody>\n",
  805. "</table>\n",
  806. "</div>"
  807. ],
  808. "text/plain": [
  809. " spend_prop \\\n",
  810. "Billing Event Audience Strategy Publisher Platforms Landing Pages \n",
  811. "Impressions Prospecting audience_network or facebook www.koovs.com/women/dresses, www.koovs.com/wome... 3.241590 \n",
  812. " www.koovs.com/women/tags/holi-promo 2.145768 \n",
  813. " www.koovs.com/women/tags/spring-into-march 3.115504 \n",
  814. "\n",
  815. " cpt \n",
  816. "Billing Event Audience Strategy Publisher Platforms Landing Pages \n",
  817. "Impressions Prospecting audience_network or facebook www.koovs.com/women/dresses, www.koovs.com/wome... 2094.220494 \n",
  818. " www.koovs.com/women/tags/holi-promo 1935.994483 \n",
  819. " www.koovs.com/women/tags/spring-into-march 1940.878333 "
  820. ]
  821. },
  822. "metadata": {},
  823. "output_type": "display_data"
  824. },
  825. {
  826. "data": {
  827. "text/html": [
  828. "<div>\n",
  829. "<table border=\"1\" class=\"dataframe\">\n",
  830. " <thead>\n",
  831. " <tr style=\"text-align: right;\">\n",
  832. " <th></th>\n",
  833. " <th></th>\n",
  834. " <th></th>\n",
  835. " <th></th>\n",
  836. " <th>spend_prop</th>\n",
  837. " <th>cpt</th>\n",
  838. " </tr>\n",
  839. " <tr>\n",
  840. " <th>Billing Event</th>\n",
  841. " <th>Gender</th>\n",
  842. " <th>Locations</th>\n",
  843. " <th>Age Range</th>\n",
  844. " <th></th>\n",
  845. " <th></th>\n",
  846. " </tr>\n",
  847. " </thead>\n",
  848. " <tbody>\n",
  849. " <tr>\n",
  850. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  851. " <th rowspan=\"2\" valign=\"top\">Female</th>\n",
  852. " <th rowspan=\"2\" valign=\"top\">IN</th>\n",
  853. " <th>18-35</th>\n",
  854. " <td>5.339884</td>\n",
  855. " <td>1826.373791</td>\n",
  856. " </tr>\n",
  857. " <tr>\n",
  858. " <th>23-38</th>\n",
  859. " <td>3.084434</td>\n",
  860. " <td>1855.262874</td>\n",
  861. " </tr>\n",
  862. " </tbody>\n",
  863. "</table>\n",
  864. "</div>"
  865. ],
  866. "text/plain": [
  867. " spend_prop cpt\n",
  868. "Billing Event Gender Locations Age Range \n",
  869. "Impressions Female IN 18-35 5.339884 1826.373791\n",
  870. " 23-38 3.084434 1855.262874"
  871. ]
  872. },
  873. "metadata": {},
  874. "output_type": "display_data"
  875. },
  876. {
  877. "data": {
  878. "text/html": [
  879. "<div>\n",
  880. "<table border=\"1\" class=\"dataframe\">\n",
  881. " <thead>\n",
  882. " <tr style=\"text-align: right;\">\n",
  883. " <th></th>\n",
  884. " <th></th>\n",
  885. " <th></th>\n",
  886. " <th></th>\n",
  887. " <th>spend_prop</th>\n",
  888. " <th>cpt</th>\n",
  889. " </tr>\n",
  890. " <tr>\n",
  891. " <th>Billing Event</th>\n",
  892. " <th>Gender</th>\n",
  893. " <th>Publisher Platforms</th>\n",
  894. " <th>Age Range</th>\n",
  895. " <th></th>\n",
  896. " <th></th>\n",
  897. " </tr>\n",
  898. " </thead>\n",
  899. " <tbody>\n",
  900. " <tr>\n",
  901. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  902. " <th rowspan=\"2\" valign=\"top\">Female</th>\n",
  903. " <th rowspan=\"2\" valign=\"top\">audience_network or facebook</th>\n",
  904. " <th>18-35</th>\n",
  905. " <td>3.725390</td>\n",
  906. " <td>2119.010761</td>\n",
  907. " </tr>\n",
  908. " <tr>\n",
  909. " <th>23-38</th>\n",
  910. " <td>3.084434</td>\n",
  911. " <td>1855.262874</td>\n",
  912. " </tr>\n",
  913. " </tbody>\n",
  914. "</table>\n",
  915. "</div>"
  916. ],
  917. "text/plain": [
  918. " spend_prop \\\n",
  919. "Billing Event Gender Publisher Platforms Age Range \n",
  920. "Impressions Female audience_network or facebook 18-35 3.725390 \n",
  921. " 23-38 3.084434 \n",
  922. "\n",
  923. " cpt \n",
  924. "Billing Event Gender Publisher Platforms Age Range \n",
  925. "Impressions Female audience_network or facebook 18-35 2119.010761 \n",
  926. " 23-38 1855.262874 "
  927. ]
  928. },
  929. "metadata": {},
  930. "output_type": "display_data"
  931. },
  932. {
  933. "data": {
  934. "text/html": [
  935. "<div>\n",
  936. "<table border=\"1\" class=\"dataframe\">\n",
  937. " <thead>\n",
  938. " <tr style=\"text-align: right;\">\n",
  939. " <th></th>\n",
  940. " <th></th>\n",
  941. " <th></th>\n",
  942. " <th></th>\n",
  943. " <th>spend_prop</th>\n",
  944. " <th>cpt</th>\n",
  945. " </tr>\n",
  946. " <tr>\n",
  947. " <th>Billing Event</th>\n",
  948. " <th>Campaign Objective</th>\n",
  949. " <th>Locations</th>\n",
  950. " <th>Interests</th>\n",
  951. " <th></th>\n",
  952. " <th></th>\n",
  953. " </tr>\n",
  954. " </thead>\n",
  955. " <tbody>\n",
  956. " <tr>\n",
  957. " <th rowspan=\"4\" valign=\"top\">Impressions</th>\n",
  958. " <th rowspan=\"4\" valign=\"top\">Conversions</th>\n",
  959. " <th rowspan=\"4\" valign=\"top\">IN</th>\n",
  960. " <th>Allen Solly or Formal wear or Mango (clothing) or Others or Startup company or Startups</th>\n",
  961. " <td>3.084434</td>\n",
  962. " <td>1855.262874</td>\n",
  963. " </tr>\n",
  964. " <tr>\n",
  965. " <th>Amazon.com or Flipkart</th>\n",
  966. " <td>2.510142</td>\n",
  967. " <td>2478.401698</td>\n",
  968. " </tr>\n",
  969. " <tr>\n",
  970. " <th>Ballet or Bars or Concerts or Dancehalls or Dresses or Others</th>\n",
  971. " <td>3.539806</td>\n",
  972. " <td>2081.319326</td>\n",
  973. " </tr>\n",
  974. " <tr>\n",
  975. " <th>Shoes</th>\n",
  976. " <td>3.843959</td>\n",
  977. " <td>1991.620990</td>\n",
  978. " </tr>\n",
  979. " </tbody>\n",
  980. "</table>\n",
  981. "</div>"
  982. ],
  983. "text/plain": [
  984. " spend_prop \\\n",
  985. "Billing Event Campaign Objective Locations Interests \n",
  986. "Impressions Conversions IN Allen Solly or Formal wear or Mango (clothing) ... 3.084434 \n",
  987. " Amazon.com or Flipkart 2.510142 \n",
  988. " Ballet or Bars or Concerts or Dancehalls or Dre... 3.539806 \n",
  989. " Shoes 3.843959 \n",
  990. "\n",
  991. " cpt \n",
  992. "Billing Event Campaign Objective Locations Interests \n",
  993. "Impressions Conversions IN Allen Solly or Formal wear or Mango (clothing) ... 1855.262874 \n",
  994. " Amazon.com or Flipkart 2478.401698 \n",
  995. " Ballet or Bars or Concerts or Dancehalls or Dre... 2081.319326 \n",
  996. " Shoes 1991.620990 "
  997. ]
  998. },
  999. "metadata": {},
  1000. "output_type": "display_data"
  1001. },
  1002. {
  1003. "data": {
  1004. "text/html": [
  1005. "<div>\n",
  1006. "<table border=\"1\" class=\"dataframe\">\n",
  1007. " <thead>\n",
  1008. " <tr style=\"text-align: right;\">\n",
  1009. " <th></th>\n",
  1010. " <th></th>\n",
  1011. " <th></th>\n",
  1012. " <th></th>\n",
  1013. " <th>spend_prop</th>\n",
  1014. " <th>cpt</th>\n",
  1015. " </tr>\n",
  1016. " <tr>\n",
  1017. " <th>Billing Event</th>\n",
  1018. " <th>Campaign Objective</th>\n",
  1019. " <th>Facebook Positions</th>\n",
  1020. " <th>Landing Pages</th>\n",
  1021. " <th></th>\n",
  1022. " <th></th>\n",
  1023. " </tr>\n",
  1024. " </thead>\n",
  1025. " <tbody>\n",
  1026. " <tr>\n",
  1027. " <th>Impressions</th>\n",
  1028. " <th>Conversions</th>\n",
  1029. " <th>feed</th>\n",
  1030. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  1031. " <td>2.058482</td>\n",
  1032. " <td>1923.571964</td>\n",
  1033. " </tr>\n",
  1034. " </tbody>\n",
  1035. "</table>\n",
  1036. "</div>"
  1037. ],
  1038. "text/plain": [
  1039. " spend_prop \\\n",
  1040. "Billing Event Campaign Objective Facebook Positions Landing Pages \n",
  1041. "Impressions Conversions feed www.koovs.com/women/dresses, www.koovs.com/wome... 2.058482 \n",
  1042. "\n",
  1043. " cpt \n",
  1044. "Billing Event Campaign Objective Facebook Positions Landing Pages \n",
  1045. "Impressions Conversions feed www.koovs.com/women/dresses, www.koovs.com/wome... 1923.571964 "
  1046. ]
  1047. },
  1048. "metadata": {},
  1049. "output_type": "display_data"
  1050. },
  1051. {
  1052. "data": {
  1053. "text/html": [
  1054. "<div>\n",
  1055. "<table border=\"1\" class=\"dataframe\">\n",
  1056. " <thead>\n",
  1057. " <tr style=\"text-align: right;\">\n",
  1058. " <th></th>\n",
  1059. " <th></th>\n",
  1060. " <th></th>\n",
  1061. " <th></th>\n",
  1062. " <th>spend_prop</th>\n",
  1063. " <th>cpt</th>\n",
  1064. " </tr>\n",
  1065. " <tr>\n",
  1066. " <th>Billing Event</th>\n",
  1067. " <th>Ad Format</th>\n",
  1068. " <th>strategy</th>\n",
  1069. " <th>Landing Pages</th>\n",
  1070. " <th></th>\n",
  1071. " <th></th>\n",
  1072. " </tr>\n",
  1073. " </thead>\n",
  1074. " <tbody>\n",
  1075. " <tr>\n",
  1076. " <th>Impressions</th>\n",
  1077. " <th>Image</th>\n",
  1078. " <th>conversions</th>\n",
  1079. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  1080. " <td>2.03591</td>\n",
  1081. " <td>2048.823077</td>\n",
  1082. " </tr>\n",
  1083. " </tbody>\n",
  1084. "</table>\n",
  1085. "</div>"
  1086. ],
  1087. "text/plain": [
  1088. " spend_prop \\\n",
  1089. "Billing Event Ad Format strategy Landing Pages \n",
  1090. "Impressions Image conversions www.koovs.com/women/dresses, www.koovs.com/wome... 2.03591 \n",
  1091. "\n",
  1092. " cpt \n",
  1093. "Billing Event Ad Format strategy Landing Pages \n",
  1094. "Impressions Image conversions www.koovs.com/women/dresses, www.koovs.com/wome... 2048.823077 "
  1095. ]
  1096. },
  1097. "metadata": {},
  1098. "output_type": "display_data"
  1099. },
  1100. {
  1101. "data": {
  1102. "text/html": [
  1103. "<div>\n",
  1104. "<table border=\"1\" class=\"dataframe\">\n",
  1105. " <thead>\n",
  1106. " <tr style=\"text-align: right;\">\n",
  1107. " <th></th>\n",
  1108. " <th></th>\n",
  1109. " <th></th>\n",
  1110. " <th></th>\n",
  1111. " <th>spend_prop</th>\n",
  1112. " <th>cpt</th>\n",
  1113. " </tr>\n",
  1114. " <tr>\n",
  1115. " <th>Billing Event</th>\n",
  1116. " <th>Ad Type</th>\n",
  1117. " <th>strategy</th>\n",
  1118. " <th>Interests</th>\n",
  1119. " <th></th>\n",
  1120. " <th></th>\n",
  1121. " </tr>\n",
  1122. " </thead>\n",
  1123. " <tbody>\n",
  1124. " <tr>\n",
  1125. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  1126. " <th rowspan=\"2\" valign=\"top\">Carousel</th>\n",
  1127. " <th rowspan=\"2\" valign=\"top\">conversions</th>\n",
  1128. " <th>Clothing or Coupons or Discount stores or Fashion accessories or Footwear or Others</th>\n",
  1129. " <td>2.633819</td>\n",
  1130. " <td>1914.268194</td>\n",
  1131. " </tr>\n",
  1132. " <tr>\n",
  1133. " <th>Shoes</th>\n",
  1134. " <td>3.843959</td>\n",
  1135. " <td>1991.620990</td>\n",
  1136. " </tr>\n",
  1137. " </tbody>\n",
  1138. "</table>\n",
  1139. "</div>"
  1140. ],
  1141. "text/plain": [
  1142. " spend_prop \\\n",
  1143. "Billing Event Ad Type strategy Interests \n",
  1144. "Impressions Carousel conversions Clothing or Coupons or Discount stores or Fashi... 2.633819 \n",
  1145. " Shoes 3.843959 \n",
  1146. "\n",
  1147. " cpt \n",
  1148. "Billing Event Ad Type strategy Interests \n",
  1149. "Impressions Carousel conversions Clothing or Coupons or Discount stores or Fashi... 1914.268194 \n",
  1150. " Shoes 1991.620990 "
  1151. ]
  1152. },
  1153. "metadata": {},
  1154. "output_type": "display_data"
  1155. },
  1156. {
  1157. "data": {
  1158. "text/html": [
  1159. "<div>\n",
  1160. "<table border=\"1\" class=\"dataframe\">\n",
  1161. " <thead>\n",
  1162. " <tr style=\"text-align: right;\">\n",
  1163. " <th></th>\n",
  1164. " <th></th>\n",
  1165. " <th></th>\n",
  1166. " <th></th>\n",
  1167. " <th>spend_prop</th>\n",
  1168. " <th>cpt</th>\n",
  1169. " </tr>\n",
  1170. " <tr>\n",
  1171. " <th>Billing Event</th>\n",
  1172. " <th>Ad Format</th>\n",
  1173. " <th>Publisher Platforms</th>\n",
  1174. " <th>Age Range</th>\n",
  1175. " <th></th>\n",
  1176. " <th></th>\n",
  1177. " </tr>\n",
  1178. " </thead>\n",
  1179. " <tbody>\n",
  1180. " <tr>\n",
  1181. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  1182. " <th rowspan=\"2\" valign=\"top\">Image</th>\n",
  1183. " <th rowspan=\"2\" valign=\"top\">audience_network or facebook</th>\n",
  1184. " <th>18-35</th>\n",
  1185. " <td>3.725390</td>\n",
  1186. " <td>2119.010761</td>\n",
  1187. " </tr>\n",
  1188. " <tr>\n",
  1189. " <th>23-38</th>\n",
  1190. " <td>3.084434</td>\n",
  1191. " <td>1855.262874</td>\n",
  1192. " </tr>\n",
  1193. " </tbody>\n",
  1194. "</table>\n",
  1195. "</div>"
  1196. ],
  1197. "text/plain": [
  1198. " spend_prop \\\n",
  1199. "Billing Event Ad Format Publisher Platforms Age Range \n",
  1200. "Impressions Image audience_network or facebook 18-35 3.725390 \n",
  1201. " 23-38 3.084434 \n",
  1202. "\n",
  1203. " cpt \n",
  1204. "Billing Event Ad Format Publisher Platforms Age Range \n",
  1205. "Impressions Image audience_network or facebook 18-35 2119.010761 \n",
  1206. " 23-38 1855.262874 "
  1207. ]
  1208. },
  1209. "metadata": {},
  1210. "output_type": "display_data"
  1211. },
  1212. {
  1213. "data": {
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  1217. " <thead>\n",
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  1219. " <th></th>\n",
  1220. " <th></th>\n",
  1221. " <th></th>\n",
  1222. " <th></th>\n",
  1223. " <th>spend_prop</th>\n",
  1224. " <th>cpt</th>\n",
  1225. " </tr>\n",
  1226. " <tr>\n",
  1227. " <th>Billing Event</th>\n",
  1228. " <th>Ad Format</th>\n",
  1229. " <th>Facebook Positions</th>\n",
  1230. " <th>Landing Pages</th>\n",
  1231. " <th></th>\n",
  1232. " <th></th>\n",
  1233. " </tr>\n",
  1234. " </thead>\n",
  1235. " <tbody>\n",
  1236. " <tr>\n",
  1237. " <th>Impressions</th>\n",
  1238. " <th>Image</th>\n",
  1239. " <th>feed</th>\n",
  1240. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  1241. " <td>2.058482</td>\n",
  1242. " <td>1923.571964</td>\n",
  1243. " </tr>\n",
  1244. " </tbody>\n",
  1245. "</table>\n",
  1246. "</div>"
  1247. ],
  1248. "text/plain": [
  1249. " spend_prop \\\n",
  1250. "Billing Event Ad Format Facebook Positions Landing Pages \n",
  1251. "Impressions Image feed www.koovs.com/women/dresses, www.koovs.com/wome... 2.058482 \n",
  1252. "\n",
  1253. " cpt \n",
  1254. "Billing Event Ad Format Facebook Positions Landing Pages \n",
  1255. "Impressions Image feed www.koovs.com/women/dresses, www.koovs.com/wome... 1923.571964 "
  1256. ]
  1257. },
  1258. "metadata": {},
  1259. "output_type": "display_data"
  1260. },
  1261. {
  1262. "data": {
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  1265. "<table border=\"1\" class=\"dataframe\">\n",
  1266. " <thead>\n",
  1267. " <tr style=\"text-align: right;\">\n",
  1268. " <th></th>\n",
  1269. " <th></th>\n",
  1270. " <th></th>\n",
  1271. " <th></th>\n",
  1272. " <th>spend_prop</th>\n",
  1273. " <th>cpt</th>\n",
  1274. " </tr>\n",
  1275. " <tr>\n",
  1276. " <th>Billing Event</th>\n",
  1277. " <th>Audience Strategy</th>\n",
  1278. " <th>strategy</th>\n",
  1279. " <th>Interests</th>\n",
  1280. " <th></th>\n",
  1281. " <th></th>\n",
  1282. " </tr>\n",
  1283. " </thead>\n",
  1284. " <tbody>\n",
  1285. " <tr>\n",
  1286. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  1287. " <th rowspan=\"2\" valign=\"top\">Prospecting</th>\n",
  1288. " <th rowspan=\"2\" valign=\"top\">conversions</th>\n",
  1289. " <th>Clothing or Coupons or Discount stores or Fashion accessories or Footwear or Others</th>\n",
  1290. " <td>2.633819</td>\n",
  1291. " <td>1914.268194</td>\n",
  1292. " </tr>\n",
  1293. " <tr>\n",
  1294. " <th>Shoes</th>\n",
  1295. " <td>3.843959</td>\n",
  1296. " <td>1991.620990</td>\n",
  1297. " </tr>\n",
  1298. " </tbody>\n",
  1299. "</table>\n",
  1300. "</div>"
  1301. ],
  1302. "text/plain": [
  1303. " spend_prop \\\n",
  1304. "Billing Event Audience Strategy strategy Interests \n",
  1305. "Impressions Prospecting conversions Clothing or Coupons or Discount stores or Fashi... 2.633819 \n",
  1306. " Shoes 3.843959 \n",
  1307. "\n",
  1308. " cpt \n",
  1309. "Billing Event Audience Strategy strategy Interests \n",
  1310. "Impressions Prospecting conversions Clothing or Coupons or Discount stores or Fashi... 1914.268194 \n",
  1311. " Shoes 1991.620990 "
  1312. ]
  1313. },
  1314. "metadata": {},
  1315. "output_type": "display_data"
  1316. },
  1317. {
  1318. "data": {
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  1322. " <thead>\n",
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  1324. " <th></th>\n",
  1325. " <th></th>\n",
  1326. " <th></th>\n",
  1327. " <th></th>\n",
  1328. " <th>spend_prop</th>\n",
  1329. " <th>cpt</th>\n",
  1330. " </tr>\n",
  1331. " <tr>\n",
  1332. " <th>Billing Event</th>\n",
  1333. " <th>Gender</th>\n",
  1334. " <th>strategy</th>\n",
  1335. " <th>Landing Pages</th>\n",
  1336. " <th></th>\n",
  1337. " <th></th>\n",
  1338. " </tr>\n",
  1339. " </thead>\n",
  1340. " <tbody>\n",
  1341. " <tr>\n",
  1342. " <th>Impressions</th>\n",
  1343. " <th>Female</th>\n",
  1344. " <th>conversions</th>\n",
  1345. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  1346. " <td>2.03591</td>\n",
  1347. " <td>2048.823077</td>\n",
  1348. " </tr>\n",
  1349. " </tbody>\n",
  1350. "</table>\n",
  1351. "</div>"
  1352. ],
  1353. "text/plain": [
  1354. " spend_prop \\\n",
  1355. "Billing Event Gender strategy Landing Pages \n",
  1356. "Impressions Female conversions www.koovs.com/women/dresses, www.koovs.com/wome... 2.03591 \n",
  1357. "\n",
  1358. " cpt \n",
  1359. "Billing Event Gender strategy Landing Pages \n",
  1360. "Impressions Female conversions www.koovs.com/women/dresses, www.koovs.com/wome... 2048.823077 "
  1361. ]
  1362. },
  1363. "metadata": {},
  1364. "output_type": "display_data"
  1365. },
  1366. {
  1367. "data": {
  1368. "text/html": [
  1369. "<div>\n",
  1370. "<table border=\"1\" class=\"dataframe\">\n",
  1371. " <thead>\n",
  1372. " <tr style=\"text-align: right;\">\n",
  1373. " <th></th>\n",
  1374. " <th></th>\n",
  1375. " <th></th>\n",
  1376. " <th></th>\n",
  1377. " <th>spend_prop</th>\n",
  1378. " <th>cpt</th>\n",
  1379. " </tr>\n",
  1380. " <tr>\n",
  1381. " <th>Billing Event</th>\n",
  1382. " <th>Ad Type</th>\n",
  1383. " <th>Locations</th>\n",
  1384. " <th>Age Range</th>\n",
  1385. " <th></th>\n",
  1386. " <th></th>\n",
  1387. " </tr>\n",
  1388. " </thead>\n",
  1389. " <tbody>\n",
  1390. " <tr>\n",
  1391. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  1392. " <th rowspan=\"2\" valign=\"top\">Carousel</th>\n",
  1393. " <th rowspan=\"2\" valign=\"top\">IN</th>\n",
  1394. " <th>18-35</th>\n",
  1395. " <td>5.928406</td>\n",
  1396. " <td>1951.147547</td>\n",
  1397. " </tr>\n",
  1398. " <tr>\n",
  1399. " <th>23-38</th>\n",
  1400. " <td>3.084434</td>\n",
  1401. " <td>1855.262874</td>\n",
  1402. " </tr>\n",
  1403. " </tbody>\n",
  1404. "</table>\n",
  1405. "</div>"
  1406. ],
  1407. "text/plain": [
  1408. " spend_prop cpt\n",
  1409. "Billing Event Ad Type Locations Age Range \n",
  1410. "Impressions Carousel IN 18-35 5.928406 1951.147547\n",
  1411. " 23-38 3.084434 1855.262874"
  1412. ]
  1413. },
  1414. "metadata": {},
  1415. "output_type": "display_data"
  1416. },
  1417. {
  1418. "data": {
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  1421. "<table border=\"1\" class=\"dataframe\">\n",
  1422. " <thead>\n",
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  1424. " <th></th>\n",
  1425. " <th></th>\n",
  1426. " <th></th>\n",
  1427. " <th></th>\n",
  1428. " <th>spend_prop</th>\n",
  1429. " <th>cpt</th>\n",
  1430. " </tr>\n",
  1431. " <tr>\n",
  1432. " <th>Billing Event</th>\n",
  1433. " <th>Audience Strategy</th>\n",
  1434. " <th>Locations</th>\n",
  1435. " <th>Age Range</th>\n",
  1436. " <th></th>\n",
  1437. " <th></th>\n",
  1438. " </tr>\n",
  1439. " </thead>\n",
  1440. " <tbody>\n",
  1441. " <tr>\n",
  1442. " <th>Impressions</th>\n",
  1443. " <th>Prospecting</th>\n",
  1444. " <th>IN</th>\n",
  1445. " <th>23-38</th>\n",
  1446. " <td>3.084434</td>\n",
  1447. " <td>1855.262874</td>\n",
  1448. " </tr>\n",
  1449. " </tbody>\n",
  1450. "</table>\n",
  1451. "</div>"
  1452. ],
  1453. "text/plain": [
  1454. " spend_prop cpt\n",
  1455. "Billing Event Audience Strategy Locations Age Range \n",
  1456. "Impressions Prospecting IN 23-38 3.084434 1855.262874"
  1457. ]
  1458. },
  1459. "metadata": {},
  1460. "output_type": "display_data"
  1461. },
  1462. {
  1463. "data": {
  1464. "text/html": [
  1465. "<div>\n",
  1466. "<table border=\"1\" class=\"dataframe\">\n",
  1467. " <thead>\n",
  1468. " <tr style=\"text-align: right;\">\n",
  1469. " <th></th>\n",
  1470. " <th></th>\n",
  1471. " <th></th>\n",
  1472. " <th></th>\n",
  1473. " <th>spend_prop</th>\n",
  1474. " <th>cpt</th>\n",
  1475. " </tr>\n",
  1476. " <tr>\n",
  1477. " <th>Billing Event</th>\n",
  1478. " <th>Campaign Objective</th>\n",
  1479. " <th>strategy</th>\n",
  1480. " <th>Landing Pages</th>\n",
  1481. " <th></th>\n",
  1482. " <th></th>\n",
  1483. " </tr>\n",
  1484. " </thead>\n",
  1485. " <tbody>\n",
  1486. " <tr>\n",
  1487. " <th>Impressions</th>\n",
  1488. " <th>Conversions</th>\n",
  1489. " <th>conversions</th>\n",
  1490. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  1491. " <td>2.03591</td>\n",
  1492. " <td>2048.823077</td>\n",
  1493. " </tr>\n",
  1494. " </tbody>\n",
  1495. "</table>\n",
  1496. "</div>"
  1497. ],
  1498. "text/plain": [
  1499. " spend_prop \\\n",
  1500. "Billing Event Campaign Objective strategy Landing Pages \n",
  1501. "Impressions Conversions conversions www.koovs.com/women/dresses, www.koovs.com/wome... 2.03591 \n",
  1502. "\n",
  1503. " cpt \n",
  1504. "Billing Event Campaign Objective strategy Landing Pages \n",
  1505. "Impressions Conversions conversions www.koovs.com/women/dresses, www.koovs.com/wome... 2048.823077 "
  1506. ]
  1507. },
  1508. "metadata": {},
  1509. "output_type": "display_data"
  1510. },
  1511. {
  1512. "data": {
  1513. "text/html": [
  1514. "<div>\n",
  1515. "<table border=\"1\" class=\"dataframe\">\n",
  1516. " <thead>\n",
  1517. " <tr style=\"text-align: right;\">\n",
  1518. " <th></th>\n",
  1519. " <th></th>\n",
  1520. " <th></th>\n",
  1521. " <th></th>\n",
  1522. " <th>spend_prop</th>\n",
  1523. " <th>cpt</th>\n",
  1524. " </tr>\n",
  1525. " <tr>\n",
  1526. " <th>Billing Event</th>\n",
  1527. " <th>Ad Type</th>\n",
  1528. " <th>Audience Types</th>\n",
  1529. " <th>Interests</th>\n",
  1530. " <th></th>\n",
  1531. " <th></th>\n",
  1532. " </tr>\n",
  1533. " </thead>\n",
  1534. " <tbody>\n",
  1535. " <tr>\n",
  1536. " <th>Impressions</th>\n",
  1537. " <th>Carousel</th>\n",
  1538. " <th>Interests</th>\n",
  1539. " <th>Amazon.com or Flipkart</th>\n",
  1540. " <td>2.510142</td>\n",
  1541. " <td>2478.401698</td>\n",
  1542. " </tr>\n",
  1543. " </tbody>\n",
  1544. "</table>\n",
  1545. "</div>"
  1546. ],
  1547. "text/plain": [
  1548. " spend_prop \\\n",
  1549. "Billing Event Ad Type Audience Types Interests \n",
  1550. "Impressions Carousel Interests Amazon.com or Flipkart 2.510142 \n",
  1551. "\n",
  1552. " cpt \n",
  1553. "Billing Event Ad Type Audience Types Interests \n",
  1554. "Impressions Carousel Interests Amazon.com or Flipkart 2478.401698 "
  1555. ]
  1556. },
  1557. "metadata": {},
  1558. "output_type": "display_data"
  1559. },
  1560. {
  1561. "data": {
  1562. "text/html": [
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  1567. " <th></th>\n",
  1568. " <th></th>\n",
  1569. " <th></th>\n",
  1570. " <th></th>\n",
  1571. " <th>spend_prop</th>\n",
  1572. " <th>cpt</th>\n",
  1573. " </tr>\n",
  1574. " <tr>\n",
  1575. " <th>Billing Event</th>\n",
  1576. " <th>Audience Strategy</th>\n",
  1577. " <th>Publisher Platforms</th>\n",
  1578. " <th>Age Range</th>\n",
  1579. " <th></th>\n",
  1580. " <th></th>\n",
  1581. " </tr>\n",
  1582. " </thead>\n",
  1583. " <tbody>\n",
  1584. " <tr>\n",
  1585. " <th>Impressions</th>\n",
  1586. " <th>Prospecting</th>\n",
  1587. " <th>audience_network or facebook</th>\n",
  1588. " <th>18-35</th>\n",
  1589. " <td>3.72539</td>\n",
  1590. " <td>2119.010761</td>\n",
  1591. " </tr>\n",
  1592. " </tbody>\n",
  1593. "</table>\n",
  1594. "</div>"
  1595. ],
  1596. "text/plain": [
  1597. " spend_prop \\\n",
  1598. "Billing Event Audience Strategy Publisher Platforms Age Range \n",
  1599. "Impressions Prospecting audience_network or facebook 18-35 3.72539 \n",
  1600. "\n",
  1601. " cpt \n",
  1602. "Billing Event Audience Strategy Publisher Platforms Age Range \n",
  1603. "Impressions Prospecting audience_network or facebook 18-35 2119.010761 "
  1604. ]
  1605. },
  1606. "metadata": {},
  1607. "output_type": "display_data"
  1608. },
  1609. {
  1610. "data": {
  1611. "text/html": [
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  1613. "<table border=\"1\" class=\"dataframe\">\n",
  1614. " <thead>\n",
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  1616. " <th></th>\n",
  1617. " <th></th>\n",
  1618. " <th></th>\n",
  1619. " <th></th>\n",
  1620. " <th>spend_prop</th>\n",
  1621. " <th>cpt</th>\n",
  1622. " </tr>\n",
  1623. " <tr>\n",
  1624. " <th>Billing Event</th>\n",
  1625. " <th>Gender</th>\n",
  1626. " <th>Locations</th>\n",
  1627. " <th>Landing Pages</th>\n",
  1628. " <th></th>\n",
  1629. " <th></th>\n",
  1630. " </tr>\n",
  1631. " </thead>\n",
  1632. " <tbody>\n",
  1633. " <tr>\n",
  1634. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  1635. " <th rowspan=\"2\" valign=\"top\">Female</th>\n",
  1636. " <th rowspan=\"2\" valign=\"top\">IN</th>\n",
  1637. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  1638. " <td>4.280234</td>\n",
  1639. " <td>2017.872793</td>\n",
  1640. " </tr>\n",
  1641. " <tr>\n",
  1642. " <th>www.koovs.com/women/tags/holi-promo</th>\n",
  1643. " <td>2.236692</td>\n",
  1644. " <td>1672.081429</td>\n",
  1645. " </tr>\n",
  1646. " </tbody>\n",
  1647. "</table>\n",
  1648. "</div>"
  1649. ],
  1650. "text/plain": [
  1651. " spend_prop \\\n",
  1652. "Billing Event Gender Locations Landing Pages \n",
  1653. "Impressions Female IN www.koovs.com/women/dresses, www.koovs.com/wome... 4.280234 \n",
  1654. " www.koovs.com/women/tags/holi-promo 2.236692 \n",
  1655. "\n",
  1656. " cpt \n",
  1657. "Billing Event Gender Locations Landing Pages \n",
  1658. "Impressions Female IN www.koovs.com/women/dresses, www.koovs.com/wome... 2017.872793 \n",
  1659. " www.koovs.com/women/tags/holi-promo 1672.081429 "
  1660. ]
  1661. },
  1662. "metadata": {},
  1663. "output_type": "display_data"
  1664. },
  1665. {
  1666. "data": {
  1667. "text/html": [
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  1670. " <thead>\n",
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  1672. " <th></th>\n",
  1673. " <th></th>\n",
  1674. " <th></th>\n",
  1675. " <th></th>\n",
  1676. " <th>spend_prop</th>\n",
  1677. " <th>cpt</th>\n",
  1678. " </tr>\n",
  1679. " <tr>\n",
  1680. " <th>Billing Event</th>\n",
  1681. " <th>Audience Strategy</th>\n",
  1682. " <th>Facebook Positions</th>\n",
  1683. " <th>Landing Pages</th>\n",
  1684. " <th></th>\n",
  1685. " <th></th>\n",
  1686. " </tr>\n",
  1687. " </thead>\n",
  1688. " <tbody>\n",
  1689. " <tr>\n",
  1690. " <th>Impressions</th>\n",
  1691. " <th>Prospecting</th>\n",
  1692. " <th>feed</th>\n",
  1693. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  1694. " <td>2.058482</td>\n",
  1695. " <td>1923.571964</td>\n",
  1696. " </tr>\n",
  1697. " </tbody>\n",
  1698. "</table>\n",
  1699. "</div>"
  1700. ],
  1701. "text/plain": [
  1702. " spend_prop \\\n",
  1703. "Billing Event Audience Strategy Facebook Positions Landing Pages \n",
  1704. "Impressions Prospecting feed www.koovs.com/women/dresses, www.koovs.com/wome... 2.058482 \n",
  1705. "\n",
  1706. " cpt \n",
  1707. "Billing Event Audience Strategy Facebook Positions Landing Pages \n",
  1708. "Impressions Prospecting feed www.koovs.com/women/dresses, www.koovs.com/wome... 1923.571964 "
  1709. ]
  1710. },
  1711. "metadata": {},
  1712. "output_type": "display_data"
  1713. },
  1714. {
  1715. "data": {
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  1719. " <thead>\n",
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  1721. " <th></th>\n",
  1722. " <th></th>\n",
  1723. " <th></th>\n",
  1724. " <th></th>\n",
  1725. " <th>spend_prop</th>\n",
  1726. " <th>cpt</th>\n",
  1727. " </tr>\n",
  1728. " <tr>\n",
  1729. " <th>Billing Event</th>\n",
  1730. " <th>Ad Format</th>\n",
  1731. " <th>Audience Types</th>\n",
  1732. " <th>Interests</th>\n",
  1733. " <th></th>\n",
  1734. " <th></th>\n",
  1735. " </tr>\n",
  1736. " </thead>\n",
  1737. " <tbody>\n",
  1738. " <tr>\n",
  1739. " <th>Impressions</th>\n",
  1740. " <th>Image</th>\n",
  1741. " <th>Interests</th>\n",
  1742. " <th>Amazon.com or Flipkart</th>\n",
  1743. " <td>2.510142</td>\n",
  1744. " <td>2478.401698</td>\n",
  1745. " </tr>\n",
  1746. " </tbody>\n",
  1747. "</table>\n",
  1748. "</div>"
  1749. ],
  1750. "text/plain": [
  1751. " spend_prop \\\n",
  1752. "Billing Event Ad Format Audience Types Interests \n",
  1753. "Impressions Image Interests Amazon.com or Flipkart 2.510142 \n",
  1754. "\n",
  1755. " cpt \n",
  1756. "Billing Event Ad Format Audience Types Interests \n",
  1757. "Impressions Image Interests Amazon.com or Flipkart 2478.401698 "
  1758. ]
  1759. },
  1760. "metadata": {},
  1761. "output_type": "display_data"
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  1763. {
  1764. "data": {
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  1766. "<div>\n",
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  1768. " <thead>\n",
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  1770. " <th></th>\n",
  1771. " <th></th>\n",
  1772. " <th></th>\n",
  1773. " <th></th>\n",
  1774. " <th>spend_prop</th>\n",
  1775. " <th>cpt</th>\n",
  1776. " </tr>\n",
  1777. " <tr>\n",
  1778. " <th>Billing Event</th>\n",
  1779. " <th>Campaign Objective</th>\n",
  1780. " <th>Publisher Platforms</th>\n",
  1781. " <th>Landing Pages</th>\n",
  1782. " <th></th>\n",
  1783. " <th></th>\n",
  1784. " </tr>\n",
  1785. " </thead>\n",
  1786. " <tbody>\n",
  1787. " <tr>\n",
  1788. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  1789. " <th rowspan=\"2\" valign=\"top\">Conversions</th>\n",
  1790. " <th rowspan=\"2\" valign=\"top\">audience_network or facebook</th>\n",
  1791. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  1792. " <td>4.041050</td>\n",
  1793. " <td>1871.393097</td>\n",
  1794. " </tr>\n",
  1795. " <tr>\n",
  1796. " <th>www.koovs.com/women/tags/spring-into-march</th>\n",
  1797. " <td>3.592959</td>\n",
  1798. " <td>1899.180808</td>\n",
  1799. " </tr>\n",
  1800. " </tbody>\n",
  1801. "</table>\n",
  1802. "</div>"
  1803. ],
  1804. "text/plain": [
  1805. " spend_prop \\\n",
  1806. "Billing Event Campaign Objective Publisher Platforms Landing Pages \n",
  1807. "Impressions Conversions audience_network or facebook www.koovs.com/women/dresses, www.koovs.com/wome... 4.041050 \n",
  1808. " www.koovs.com/women/tags/spring-into-march 3.592959 \n",
  1809. "\n",
  1810. " cpt \n",
  1811. "Billing Event Campaign Objective Publisher Platforms Landing Pages \n",
  1812. "Impressions Conversions audience_network or facebook www.koovs.com/women/dresses, www.koovs.com/wome... 1871.393097 \n",
  1813. " www.koovs.com/women/tags/spring-into-march 1899.180808 "
  1814. ]
  1815. },
  1816. "metadata": {},
  1817. "output_type": "display_data"
  1818. },
  1819. {
  1820. "data": {
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  1826. " <th></th>\n",
  1827. " <th></th>\n",
  1828. " <th></th>\n",
  1829. " <th></th>\n",
  1830. " <th>spend_prop</th>\n",
  1831. " <th>cpt</th>\n",
  1832. " </tr>\n",
  1833. " <tr>\n",
  1834. " <th>Billing Event</th>\n",
  1835. " <th>Gender</th>\n",
  1836. " <th>Facebook Positions</th>\n",
  1837. " <th>Landing Pages</th>\n",
  1838. " <th></th>\n",
  1839. " <th></th>\n",
  1840. " </tr>\n",
  1841. " </thead>\n",
  1842. " <tbody>\n",
  1843. " <tr>\n",
  1844. " <th>Impressions</th>\n",
  1845. " <th>Female</th>\n",
  1846. " <th>feed</th>\n",
  1847. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  1848. " <td>2.058482</td>\n",
  1849. " <td>1923.571964</td>\n",
  1850. " </tr>\n",
  1851. " </tbody>\n",
  1852. "</table>\n",
  1853. "</div>"
  1854. ],
  1855. "text/plain": [
  1856. " spend_prop \\\n",
  1857. "Billing Event Gender Facebook Positions Landing Pages \n",
  1858. "Impressions Female feed www.koovs.com/women/dresses, www.koovs.com/wome... 2.058482 \n",
  1859. "\n",
  1860. " cpt \n",
  1861. "Billing Event Gender Facebook Positions Landing Pages \n",
  1862. "Impressions Female feed www.koovs.com/women/dresses, www.koovs.com/wome... 1923.571964 "
  1863. ]
  1864. },
  1865. "metadata": {},
  1866. "output_type": "display_data"
  1867. },
  1868. {
  1869. "data": {
  1870. "text/html": [
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  1873. " <thead>\n",
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  1875. " <th></th>\n",
  1876. " <th></th>\n",
  1877. " <th></th>\n",
  1878. " <th></th>\n",
  1879. " <th>spend_prop</th>\n",
  1880. " <th>cpt</th>\n",
  1881. " </tr>\n",
  1882. " <tr>\n",
  1883. " <th>Billing Event</th>\n",
  1884. " <th>Ad Type</th>\n",
  1885. " <th>Locations</th>\n",
  1886. " <th>Landing Pages</th>\n",
  1887. " <th></th>\n",
  1888. " <th></th>\n",
  1889. " </tr>\n",
  1890. " </thead>\n",
  1891. " <tbody>\n",
  1892. " <tr>\n",
  1893. " <th>Impressions</th>\n",
  1894. " <th>Carousel</th>\n",
  1895. " <th>IN</th>\n",
  1896. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  1897. " <td>4.280234</td>\n",
  1898. " <td>2017.872793</td>\n",
  1899. " </tr>\n",
  1900. " </tbody>\n",
  1901. "</table>\n",
  1902. "</div>"
  1903. ],
  1904. "text/plain": [
  1905. " spend_prop \\\n",
  1906. "Billing Event Ad Type Locations Landing Pages \n",
  1907. "Impressions Carousel IN www.koovs.com/women/dresses, www.koovs.com/wome... 4.280234 \n",
  1908. "\n",
  1909. " cpt \n",
  1910. "Billing Event Ad Type Locations Landing Pages \n",
  1911. "Impressions Carousel IN www.koovs.com/women/dresses, www.koovs.com/wome... 2017.872793 "
  1912. ]
  1913. },
  1914. "metadata": {},
  1915. "output_type": "display_data"
  1916. },
  1917. {
  1918. "data": {
  1919. "text/html": [
  1920. "<div>\n",
  1921. "<table border=\"1\" class=\"dataframe\">\n",
  1922. " <thead>\n",
  1923. " <tr style=\"text-align: right;\">\n",
  1924. " <th></th>\n",
  1925. " <th></th>\n",
  1926. " <th></th>\n",
  1927. " <th></th>\n",
  1928. " <th>spend_prop</th>\n",
  1929. " <th>cpt</th>\n",
  1930. " </tr>\n",
  1931. " <tr>\n",
  1932. " <th>Billing Event</th>\n",
  1933. " <th>Device Platforms</th>\n",
  1934. " <th>Publisher Platforms</th>\n",
  1935. " <th>Interests</th>\n",
  1936. " <th></th>\n",
  1937. " <th></th>\n",
  1938. " </tr>\n",
  1939. " </thead>\n",
  1940. " <tbody>\n",
  1941. " <tr>\n",
  1942. " <th rowspan=\"3\" valign=\"top\">Impressions</th>\n",
  1943. " <th rowspan=\"3\" valign=\"top\">desktop or mobile</th>\n",
  1944. " <th rowspan=\"3\" valign=\"top\">audience_network or facebook</th>\n",
  1945. " <th>Amazon.com or Flipkart</th>\n",
  1946. " <td>2.510142</td>\n",
  1947. " <td>2478.401698</td>\n",
  1948. " </tr>\n",
  1949. " <tr>\n",
  1950. " <th>Ballet or Bars or Concerts or Dancehalls or Dresses or Others</th>\n",
  1951. " <td>3.375193</td>\n",
  1952. " <td>2053.758837</td>\n",
  1953. " </tr>\n",
  1954. " <tr>\n",
  1955. " <th>Clothing or Coupons or Discount stores or Fashion accessories or Footwear or Others</th>\n",
  1956. " <td>2.583539</td>\n",
  1957. " <td>1904.170986</td>\n",
  1958. " </tr>\n",
  1959. " </tbody>\n",
  1960. "</table>\n",
  1961. "</div>"
  1962. ],
  1963. "text/plain": [
  1964. " spend_prop \\\n",
  1965. "Billing Event Device Platforms Publisher Platforms Interests \n",
  1966. "Impressions desktop or mobile audience_network or facebook Amazon.com or Flipkart 2.510142 \n",
  1967. " Ballet or Bars or Concerts or Dancehalls or Dre... 3.375193 \n",
  1968. " Clothing or Coupons or Discount stores or Fashi... 2.583539 \n",
  1969. "\n",
  1970. " cpt \n",
  1971. "Billing Event Device Platforms Publisher Platforms Interests \n",
  1972. "Impressions desktop or mobile audience_network or facebook Amazon.com or Flipkart 2478.401698 \n",
  1973. " Ballet or Bars or Concerts or Dancehalls or Dre... 2053.758837 \n",
  1974. " Clothing or Coupons or Discount stores or Fashi... 1904.170986 "
  1975. ]
  1976. },
  1977. "metadata": {},
  1978. "output_type": "display_data"
  1979. },
  1980. {
  1981. "data": {
  1982. "text/html": [
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  1984. "<table border=\"1\" class=\"dataframe\">\n",
  1985. " <thead>\n",
  1986. " <tr style=\"text-align: right;\">\n",
  1987. " <th></th>\n",
  1988. " <th></th>\n",
  1989. " <th></th>\n",
  1990. " <th></th>\n",
  1991. " <th>spend_prop</th>\n",
  1992. " <th>cpt</th>\n",
  1993. " </tr>\n",
  1994. " <tr>\n",
  1995. " <th>Billing Event</th>\n",
  1996. " <th>Ad Type</th>\n",
  1997. " <th>strategy</th>\n",
  1998. " <th>Landing Pages</th>\n",
  1999. " <th></th>\n",
  2000. " <th></th>\n",
  2001. " </tr>\n",
  2002. " </thead>\n",
  2003. " <tbody>\n",
  2004. " <tr>\n",
  2005. " <th>Impressions</th>\n",
  2006. " <th>Carousel</th>\n",
  2007. " <th>conversions</th>\n",
  2008. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  2009. " <td>2.03591</td>\n",
  2010. " <td>2048.823077</td>\n",
  2011. " </tr>\n",
  2012. " </tbody>\n",
  2013. "</table>\n",
  2014. "</div>"
  2015. ],
  2016. "text/plain": [
  2017. " spend_prop \\\n",
  2018. "Billing Event Ad Type strategy Landing Pages \n",
  2019. "Impressions Carousel conversions www.koovs.com/women/dresses, www.koovs.com/wome... 2.03591 \n",
  2020. "\n",
  2021. " cpt \n",
  2022. "Billing Event Ad Type strategy Landing Pages \n",
  2023. "Impressions Carousel conversions www.koovs.com/women/dresses, www.koovs.com/wome... 2048.823077 "
  2024. ]
  2025. },
  2026. "metadata": {},
  2027. "output_type": "display_data"
  2028. },
  2029. {
  2030. "data": {
  2031. "text/html": [
  2032. "<div>\n",
  2033. "<table border=\"1\" class=\"dataframe\">\n",
  2034. " <thead>\n",
  2035. " <tr style=\"text-align: right;\">\n",
  2036. " <th></th>\n",
  2037. " <th></th>\n",
  2038. " <th></th>\n",
  2039. " <th></th>\n",
  2040. " <th>spend_prop</th>\n",
  2041. " <th>cpt</th>\n",
  2042. " </tr>\n",
  2043. " <tr>\n",
  2044. " <th>Billing Event</th>\n",
  2045. " <th>Campaign Objective</th>\n",
  2046. " <th>Locations</th>\n",
  2047. " <th>Landing Pages</th>\n",
  2048. " <th></th>\n",
  2049. " <th></th>\n",
  2050. " </tr>\n",
  2051. " </thead>\n",
  2052. " <tbody>\n",
  2053. " <tr>\n",
  2054. " <th>Impressions</th>\n",
  2055. " <th>Conversions</th>\n",
  2056. " <th>IN</th>\n",
  2057. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  2058. " <td>4.280234</td>\n",
  2059. " <td>2017.872793</td>\n",
  2060. " </tr>\n",
  2061. " </tbody>\n",
  2062. "</table>\n",
  2063. "</div>"
  2064. ],
  2065. "text/plain": [
  2066. " spend_prop \\\n",
  2067. "Billing Event Campaign Objective Locations Landing Pages \n",
  2068. "Impressions Conversions IN www.koovs.com/women/dresses, www.koovs.com/wome... 4.280234 \n",
  2069. "\n",
  2070. " cpt \n",
  2071. "Billing Event Campaign Objective Locations Landing Pages \n",
  2072. "Impressions Conversions IN www.koovs.com/women/dresses, www.koovs.com/wome... 2017.872793 "
  2073. ]
  2074. },
  2075. "metadata": {},
  2076. "output_type": "display_data"
  2077. },
  2078. {
  2079. "data": {
  2080. "text/html": [
  2081. "<div>\n",
  2082. "<table border=\"1\" class=\"dataframe\">\n",
  2083. " <thead>\n",
  2084. " <tr style=\"text-align: right;\">\n",
  2085. " <th></th>\n",
  2086. " <th></th>\n",
  2087. " <th></th>\n",
  2088. " <th></th>\n",
  2089. " <th>spend_prop</th>\n",
  2090. " <th>cpt</th>\n",
  2091. " </tr>\n",
  2092. " <tr>\n",
  2093. " <th>Billing Event</th>\n",
  2094. " <th>Campaign Objective</th>\n",
  2095. " <th>strategy</th>\n",
  2096. " <th>Age Range</th>\n",
  2097. " <th></th>\n",
  2098. " <th></th>\n",
  2099. " </tr>\n",
  2100. " </thead>\n",
  2101. " <tbody>\n",
  2102. " <tr>\n",
  2103. " <th>Impressions</th>\n",
  2104. " <th>Conversions</th>\n",
  2105. " <th>conversions</th>\n",
  2106. " <th>25-34</th>\n",
  2107. " <td>2.504454</td>\n",
  2108. " <td>1985.72197</td>\n",
  2109. " </tr>\n",
  2110. " </tbody>\n",
  2111. "</table>\n",
  2112. "</div>"
  2113. ],
  2114. "text/plain": [
  2115. " spend_prop cpt\n",
  2116. "Billing Event Campaign Objective strategy Age Range \n",
  2117. "Impressions Conversions conversions 25-34 2.504454 1985.72197"
  2118. ]
  2119. },
  2120. "metadata": {},
  2121. "output_type": "display_data"
  2122. },
  2123. {
  2124. "data": {
  2125. "text/html": [
  2126. "<div>\n",
  2127. "<table border=\"1\" class=\"dataframe\">\n",
  2128. " <thead>\n",
  2129. " <tr style=\"text-align: right;\">\n",
  2130. " <th></th>\n",
  2131. " <th></th>\n",
  2132. " <th></th>\n",
  2133. " <th></th>\n",
  2134. " <th>spend_prop</th>\n",
  2135. " <th>cpt</th>\n",
  2136. " </tr>\n",
  2137. " <tr>\n",
  2138. " <th>Billing Event</th>\n",
  2139. " <th>Ad Format</th>\n",
  2140. " <th>Locations</th>\n",
  2141. " <th>Landing Pages</th>\n",
  2142. " <th></th>\n",
  2143. " <th></th>\n",
  2144. " </tr>\n",
  2145. " </thead>\n",
  2146. " <tbody>\n",
  2147. " <tr>\n",
  2148. " <th>Impressions</th>\n",
  2149. " <th>Image</th>\n",
  2150. " <th>IN</th>\n",
  2151. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  2152. " <td>4.280234</td>\n",
  2153. " <td>2017.872793</td>\n",
  2154. " </tr>\n",
  2155. " </tbody>\n",
  2156. "</table>\n",
  2157. "</div>"
  2158. ],
  2159. "text/plain": [
  2160. " spend_prop \\\n",
  2161. "Billing Event Ad Format Locations Landing Pages \n",
  2162. "Impressions Image IN www.koovs.com/women/dresses, www.koovs.com/wome... 4.280234 \n",
  2163. "\n",
  2164. " cpt \n",
  2165. "Billing Event Ad Format Locations Landing Pages \n",
  2166. "Impressions Image IN www.koovs.com/women/dresses, www.koovs.com/wome... 2017.872793 "
  2167. ]
  2168. },
  2169. "metadata": {},
  2170. "output_type": "display_data"
  2171. },
  2172. {
  2173. "data": {
  2174. "text/html": [
  2175. "<div>\n",
  2176. "<table border=\"1\" class=\"dataframe\">\n",
  2177. " <thead>\n",
  2178. " <tr style=\"text-align: right;\">\n",
  2179. " <th></th>\n",
  2180. " <th></th>\n",
  2181. " <th></th>\n",
  2182. " <th></th>\n",
  2183. " <th>spend_prop</th>\n",
  2184. " <th>cpt</th>\n",
  2185. " </tr>\n",
  2186. " <tr>\n",
  2187. " <th>Billing Event</th>\n",
  2188. " <th>Gender</th>\n",
  2189. " <th>Audience Types</th>\n",
  2190. " <th>Interests</th>\n",
  2191. " <th></th>\n",
  2192. " <th></th>\n",
  2193. " </tr>\n",
  2194. " </thead>\n",
  2195. " <tbody>\n",
  2196. " <tr>\n",
  2197. " <th>Impressions</th>\n",
  2198. " <th>Female</th>\n",
  2199. " <th>Interests</th>\n",
  2200. " <th>Amazon.com or Flipkart</th>\n",
  2201. " <td>2.235705</td>\n",
  2202. " <td>2489.235745</td>\n",
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  2210. "Billing Event Gender Audience Types Interests \n",
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  2213. " cpt \n",
  2214. "Billing Event Gender Audience Types Interests \n",
  2215. "Impressions Female Interests Amazon.com or Flipkart 2489.235745 "
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  2266. " <td>1991.620990</td>\n",
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  2277. " Ballet or Bars or Concerts or Dancehalls or Dre... 3.539806 \n",
  2278. " Shoes 3.843959 \n",
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  2280. " cpt \n",
  2281. "Billing Event Ad Format Locations Interests \n",
  2282. "Impressions Image IN Allen Solly or Formal wear or Mango (clothing) ... 1855.262874 \n",
  2283. " Amazon.com or Flipkart 2478.401698 \n",
  2284. " Ballet or Bars or Concerts or Dancehalls or Dre... 2081.319326 \n",
  2285. " Shoes 1991.620990 "
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  2380. "\n",
  2381. " cpt \n",
  2382. "Billing Event Audience Strategy strategy Landing Pages \n",
  2383. "Impressions Prospecting conversions www.koovs.com/women/dresses, www.koovs.com/wome... 2048.823077 "
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  2440. " Ballet or Bars or Concerts or Dancehalls or Dre... 3.375193 \n",
  2441. "\n",
  2442. " cpt \n",
  2443. "Billing Event Gender Publisher Platforms Interests \n",
  2444. "Impressions Female audience_network or facebook Allen Solly or Formal wear or Mango (clothing) ... 1855.262874 \n",
  2445. " Amazon.com or Flipkart 2489.235745 \n",
  2446. " Ballet or Bars or Concerts or Dancehalls or Dre... 2053.758837 "
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  2502. " Amazon.com or Flipkart 2.235705 \n",
  2503. " Ballet or Bars or Concerts or Dancehalls or Dre... 3.539806 \n",
  2504. "\n",
  2505. " cpt \n",
  2506. "Billing Event Gender Locations Interests \n",
  2507. "Impressions Female IN Allen Solly or Formal wear or Mango (clothing) ... 1855.262874 \n",
  2508. " Amazon.com or Flipkart 2489.235745 \n",
  2509. " Ballet or Bars or Concerts or Dancehalls or Dre... 2081.319326 "
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  2544. " <td>3.480774</td>\n",
  2545. " <td>2305.674937</td>\n",
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  2555. "\n",
  2556. " cpt \n",
  2557. "Billing Event Audience Strategy Locations Landing Pages \n",
  2558. "Impressions Prospecting IN www.koovs.com/women/dresses, www.koovs.com/wome... 2305.674937 "
  2559. ]
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  2608. " <td>2.583539</td>\n",
  2609. " <td>1904.170986</td>\n",
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  2618. "Impressions Conversions audience_network or facebook Allen Solly or Formal wear or Mango (clothing) ... 3.084434 \n",
  2619. " Amazon.com or Flipkart 2.510142 \n",
  2620. " Ballet or Bars or Concerts or Dancehalls or Dre... 3.375193 \n",
  2621. " Clothing or Coupons or Discount stores or Fashi... 2.583539 \n",
  2622. "\n",
  2623. " cpt \n",
  2624. "Billing Event Campaign Objective Publisher Platforms Interests \n",
  2625. "Impressions Conversions audience_network or facebook Allen Solly or Formal wear or Mango (clothing) ... 1855.262874 \n",
  2626. " Amazon.com or Flipkart 2478.401698 \n",
  2627. " Ballet or Bars or Concerts or Dancehalls or Dre... 2053.758837 \n",
  2628. " Clothing or Coupons or Discount stores or Fashi... 1904.170986 "
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  2659. " <th>Impressions</th>\n",
  2660. " <th>desktop or mobile</th>\n",
  2661. " <th>Interests</th>\n",
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  2674. "\n",
  2675. " cpt \n",
  2676. "Billing Event Device Platforms Audience Types Landing Pages \n",
  2677. "Impressions desktop or mobile Interests www.koovs.com/women/tags/spring-into-march 2573.343171 "
  2678. ]
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  2705. " </thead>\n",
  2706. " <tbody>\n",
  2707. " <tr>\n",
  2708. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  2709. " <th rowspan=\"2\" valign=\"top\">Prospecting</th>\n",
  2710. " <th rowspan=\"2\" valign=\"top\">audience_network or facebook</th>\n",
  2711. " <th>Amazon.com or Flipkart</th>\n",
  2712. " <td>2.510142</td>\n",
  2713. " <td>2478.401698</td>\n",
  2714. " </tr>\n",
  2715. " <tr>\n",
  2716. " <th>Ballet or Bars or Concerts or Dancehalls or Dresses or Others</th>\n",
  2717. " <td>3.375193</td>\n",
  2718. " <td>2053.758837</td>\n",
  2719. " </tr>\n",
  2720. " </tbody>\n",
  2721. "</table>\n",
  2722. "</div>"
  2723. ],
  2724. "text/plain": [
  2725. " spend_prop \\\n",
  2726. "Billing Event Audience Strategy Publisher Platforms Interests \n",
  2727. "Impressions Prospecting audience_network or facebook Amazon.com or Flipkart 2.510142 \n",
  2728. " Ballet or Bars or Concerts or Dancehalls or Dre... 3.375193 \n",
  2729. "\n",
  2730. " cpt \n",
  2731. "Billing Event Audience Strategy Publisher Platforms Interests \n",
  2732. "Impressions Prospecting audience_network or facebook Amazon.com or Flipkart 2478.401698 \n",
  2733. " Ballet or Bars or Concerts or Dancehalls or Dre... 2053.758837 "
  2734. ]
  2735. },
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  2739. {
  2740. "data": {
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  2746. " <th></th>\n",
  2747. " <th></th>\n",
  2748. " <th></th>\n",
  2749. " <th></th>\n",
  2750. " <th>spend_prop</th>\n",
  2751. " <th>cpt</th>\n",
  2752. " </tr>\n",
  2753. " <tr>\n",
  2754. " <th>Billing Event</th>\n",
  2755. " <th>Ad Type</th>\n",
  2756. " <th>Publisher Platforms</th>\n",
  2757. " <th>Landing Pages</th>\n",
  2758. " <th></th>\n",
  2759. " <th></th>\n",
  2760. " </tr>\n",
  2761. " </thead>\n",
  2762. " <tbody>\n",
  2763. " <tr>\n",
  2764. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  2765. " <th rowspan=\"2\" valign=\"top\">Carousel</th>\n",
  2766. " <th rowspan=\"2\" valign=\"top\">audience_network or facebook</th>\n",
  2767. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  2768. " <td>4.041050</td>\n",
  2769. " <td>1871.393097</td>\n",
  2770. " </tr>\n",
  2771. " <tr>\n",
  2772. " <th>www.koovs.com/women/tags/spring-into-march</th>\n",
  2773. " <td>3.592959</td>\n",
  2774. " <td>1899.180808</td>\n",
  2775. " </tr>\n",
  2776. " </tbody>\n",
  2777. "</table>\n",
  2778. "</div>"
  2779. ],
  2780. "text/plain": [
  2781. " spend_prop \\\n",
  2782. "Billing Event Ad Type Publisher Platforms Landing Pages \n",
  2783. "Impressions Carousel audience_network or facebook www.koovs.com/women/dresses, www.koovs.com/wome... 4.041050 \n",
  2784. " www.koovs.com/women/tags/spring-into-march 3.592959 \n",
  2785. "\n",
  2786. " cpt \n",
  2787. "Billing Event Ad Type Publisher Platforms Landing Pages \n",
  2788. "Impressions Carousel audience_network or facebook www.koovs.com/women/dresses, www.koovs.com/wome... 1871.393097 \n",
  2789. " www.koovs.com/women/tags/spring-into-march 1899.180808 "
  2790. ]
  2791. },
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  2800. " <thead>\n",
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  2802. " <th></th>\n",
  2803. " <th></th>\n",
  2804. " <th></th>\n",
  2805. " <th></th>\n",
  2806. " <th>spend_prop</th>\n",
  2807. " <th>cpt</th>\n",
  2808. " </tr>\n",
  2809. " <tr>\n",
  2810. " <th>Billing Event</th>\n",
  2811. " <th>Audience Strategy</th>\n",
  2812. " <th>Locations</th>\n",
  2813. " <th>Interests</th>\n",
  2814. " <th></th>\n",
  2815. " <th></th>\n",
  2816. " </tr>\n",
  2817. " </thead>\n",
  2818. " <tbody>\n",
  2819. " <tr>\n",
  2820. " <th rowspan=\"4\" valign=\"top\">Impressions</th>\n",
  2821. " <th rowspan=\"4\" valign=\"top\">Prospecting</th>\n",
  2822. " <th rowspan=\"4\" valign=\"top\">IN</th>\n",
  2823. " <th>Allen Solly or Formal wear or Mango (clothing) or Others or Startup company or Startups</th>\n",
  2824. " <td>3.084434</td>\n",
  2825. " <td>1855.262874</td>\n",
  2826. " </tr>\n",
  2827. " <tr>\n",
  2828. " <th>Amazon.com or Flipkart</th>\n",
  2829. " <td>2.510142</td>\n",
  2830. " <td>2478.401698</td>\n",
  2831. " </tr>\n",
  2832. " <tr>\n",
  2833. " <th>Ballet or Bars or Concerts or Dancehalls or Dresses or Others</th>\n",
  2834. " <td>3.539806</td>\n",
  2835. " <td>2081.319326</td>\n",
  2836. " </tr>\n",
  2837. " <tr>\n",
  2838. " <th>Shoes</th>\n",
  2839. " <td>3.843959</td>\n",
  2840. " <td>1991.620990</td>\n",
  2841. " </tr>\n",
  2842. " </tbody>\n",
  2843. "</table>\n",
  2844. "</div>"
  2845. ],
  2846. "text/plain": [
  2847. " spend_prop \\\n",
  2848. "Billing Event Audience Strategy Locations Interests \n",
  2849. "Impressions Prospecting IN Allen Solly or Formal wear or Mango (clothing) ... 3.084434 \n",
  2850. " Amazon.com or Flipkart 2.510142 \n",
  2851. " Ballet or Bars or Concerts or Dancehalls or Dre... 3.539806 \n",
  2852. " Shoes 3.843959 \n",
  2853. "\n",
  2854. " cpt \n",
  2855. "Billing Event Audience Strategy Locations Interests \n",
  2856. "Impressions Prospecting IN Allen Solly or Formal wear or Mango (clothing) ... 1855.262874 \n",
  2857. " Amazon.com or Flipkart 2478.401698 \n",
  2858. " Ballet or Bars or Concerts or Dancehalls or Dre... 2081.319326 \n",
  2859. " Shoes 1991.620990 "
  2860. ]
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  2862. "metadata": {},
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  2865. {
  2866. "data": {
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  2870. " <thead>\n",
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  2872. " <th></th>\n",
  2873. " <th></th>\n",
  2874. " <th></th>\n",
  2875. " <th></th>\n",
  2876. " <th>spend_prop</th>\n",
  2877. " <th>cpt</th>\n",
  2878. " </tr>\n",
  2879. " <tr>\n",
  2880. " <th>Billing Event</th>\n",
  2881. " <th>Device Platforms</th>\n",
  2882. " <th>Publisher Platforms</th>\n",
  2883. " <th>Landing Pages</th>\n",
  2884. " <th></th>\n",
  2885. " <th></th>\n",
  2886. " </tr>\n",
  2887. " </thead>\n",
  2888. " <tbody>\n",
  2889. " <tr>\n",
  2890. " <th>Impressions</th>\n",
  2891. " <th>desktop or mobile</th>\n",
  2892. " <th>audience_network or facebook</th>\n",
  2893. " <th>www.koovs.com/women/tags/spring-into-march</th>\n",
  2894. " <td>2.493648</td>\n",
  2895. " <td>2330.217679</td>\n",
  2896. " </tr>\n",
  2897. " </tbody>\n",
  2898. "</table>\n",
  2899. "</div>"
  2900. ],
  2901. "text/plain": [
  2902. " spend_prop \\\n",
  2903. "Billing Event Device Platforms Publisher Platforms Landing Pages \n",
  2904. "Impressions desktop or mobile audience_network or facebook www.koovs.com/women/tags/spring-into-march 2.493648 \n",
  2905. "\n",
  2906. " cpt \n",
  2907. "Billing Event Device Platforms Publisher Platforms Landing Pages \n",
  2908. "Impressions desktop or mobile audience_network or facebook www.koovs.com/women/tags/spring-into-march 2330.217679 "
  2909. ]
  2910. },
  2911. "metadata": {},
  2912. "output_type": "display_data"
  2913. },
  2914. {
  2915. "data": {
  2916. "text/html": [
  2917. "<div>\n",
  2918. "<table border=\"1\" class=\"dataframe\">\n",
  2919. " <thead>\n",
  2920. " <tr style=\"text-align: right;\">\n",
  2921. " <th></th>\n",
  2922. " <th></th>\n",
  2923. " <th></th>\n",
  2924. " <th></th>\n",
  2925. " <th>spend_prop</th>\n",
  2926. " <th>cpt</th>\n",
  2927. " </tr>\n",
  2928. " <tr>\n",
  2929. " <th>Billing Event</th>\n",
  2930. " <th>Device Platforms</th>\n",
  2931. " <th>Locations</th>\n",
  2932. " <th>Age Range</th>\n",
  2933. " <th></th>\n",
  2934. " <th></th>\n",
  2935. " </tr>\n",
  2936. " </thead>\n",
  2937. " <tbody>\n",
  2938. " <tr>\n",
  2939. " <th rowspan=\"3\" valign=\"top\">Impressions</th>\n",
  2940. " <th rowspan=\"3\" valign=\"top\">desktop or mobile</th>\n",
  2941. " <th rowspan=\"3\" valign=\"top\">IN</th>\n",
  2942. " <th>18-35</th>\n",
  2943. " <td>4.206169</td>\n",
  2944. " <td>2316.927368</td>\n",
  2945. " </tr>\n",
  2946. " <tr>\n",
  2947. " <th>18-45</th>\n",
  2948. " <td>6.509013</td>\n",
  2949. " <td>1703.077550</td>\n",
  2950. " </tr>\n",
  2951. " <tr>\n",
  2952. " <th>23-38</th>\n",
  2953. " <td>3.084434</td>\n",
  2954. " <td>1855.262874</td>\n",
  2955. " </tr>\n",
  2956. " </tbody>\n",
  2957. "</table>\n",
  2958. "</div>"
  2959. ],
  2960. "text/plain": [
  2961. " spend_prop cpt\n",
  2962. "Billing Event Device Platforms Locations Age Range \n",
  2963. "Impressions desktop or mobile IN 18-35 4.206169 2316.927368\n",
  2964. " 18-45 6.509013 1703.077550\n",
  2965. " 23-38 3.084434 1855.262874"
  2966. ]
  2967. },
  2968. "metadata": {},
  2969. "output_type": "display_data"
  2970. },
  2971. {
  2972. "data": {
  2973. "text/html": [
  2974. "<div>\n",
  2975. "<table border=\"1\" class=\"dataframe\">\n",
  2976. " <thead>\n",
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  2978. " <th></th>\n",
  2979. " <th></th>\n",
  2980. " <th></th>\n",
  2981. " <th></th>\n",
  2982. " <th>spend_prop</th>\n",
  2983. " <th>cpt</th>\n",
  2984. " </tr>\n",
  2985. " <tr>\n",
  2986. " <th>Billing Event</th>\n",
  2987. " <th>Ad Type</th>\n",
  2988. " <th>Locations</th>\n",
  2989. " <th>Interests</th>\n",
  2990. " <th></th>\n",
  2991. " <th></th>\n",
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  2993. " </thead>\n",
  2994. " <tbody>\n",
  2995. " <tr>\n",
  2996. " <th rowspan=\"4\" valign=\"top\">Impressions</th>\n",
  2997. " <th rowspan=\"4\" valign=\"top\">Carousel</th>\n",
  2998. " <th rowspan=\"4\" valign=\"top\">IN</th>\n",
  2999. " <th>Allen Solly or Formal wear or Mango (clothing) or Others or Startup company or Startups</th>\n",
  3000. " <td>3.084434</td>\n",
  3001. " <td>1855.262874</td>\n",
  3002. " </tr>\n",
  3003. " <tr>\n",
  3004. " <th>Amazon.com or Flipkart</th>\n",
  3005. " <td>2.510142</td>\n",
  3006. " <td>2478.401698</td>\n",
  3007. " </tr>\n",
  3008. " <tr>\n",
  3009. " <th>Ballet or Bars or Concerts or Dancehalls or Dresses or Others</th>\n",
  3010. " <td>3.539806</td>\n",
  3011. " <td>2081.319326</td>\n",
  3012. " </tr>\n",
  3013. " <tr>\n",
  3014. " <th>Shoes</th>\n",
  3015. " <td>3.843959</td>\n",
  3016. " <td>1991.620990</td>\n",
  3017. " </tr>\n",
  3018. " </tbody>\n",
  3019. "</table>\n",
  3020. "</div>"
  3021. ],
  3022. "text/plain": [
  3023. " spend_prop \\\n",
  3024. "Billing Event Ad Type Locations Interests \n",
  3025. "Impressions Carousel IN Allen Solly or Formal wear or Mango (clothing) ... 3.084434 \n",
  3026. " Amazon.com or Flipkart 2.510142 \n",
  3027. " Ballet or Bars or Concerts or Dancehalls or Dre... 3.539806 \n",
  3028. " Shoes 3.843959 \n",
  3029. "\n",
  3030. " cpt \n",
  3031. "Billing Event Ad Type Locations Interests \n",
  3032. "Impressions Carousel IN Allen Solly or Formal wear or Mango (clothing) ... 1855.262874 \n",
  3033. " Amazon.com or Flipkart 2478.401698 \n",
  3034. " Ballet or Bars or Concerts or Dancehalls or Dre... 2081.319326 \n",
  3035. " Shoes 1991.620990 "
  3036. ]
  3037. },
  3038. "metadata": {},
  3039. "output_type": "display_data"
  3040. },
  3041. {
  3042. "data": {
  3043. "text/html": [
  3044. "<div>\n",
  3045. "<table border=\"1\" class=\"dataframe\">\n",
  3046. " <thead>\n",
  3047. " <tr style=\"text-align: right;\">\n",
  3048. " <th></th>\n",
  3049. " <th></th>\n",
  3050. " <th></th>\n",
  3051. " <th></th>\n",
  3052. " <th>spend_prop</th>\n",
  3053. " <th>cpt</th>\n",
  3054. " </tr>\n",
  3055. " <tr>\n",
  3056. " <th>Billing Event</th>\n",
  3057. " <th>Ad Format</th>\n",
  3058. " <th>strategy</th>\n",
  3059. " <th>Interests</th>\n",
  3060. " <th></th>\n",
  3061. " <th></th>\n",
  3062. " </tr>\n",
  3063. " </thead>\n",
  3064. " <tbody>\n",
  3065. " <tr>\n",
  3066. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  3067. " <th rowspan=\"2\" valign=\"top\">Image</th>\n",
  3068. " <th rowspan=\"2\" valign=\"top\">conversions</th>\n",
  3069. " <th>Clothing or Coupons or Discount stores or Fashion accessories or Footwear or Others</th>\n",
  3070. " <td>2.633819</td>\n",
  3071. " <td>1914.268194</td>\n",
  3072. " </tr>\n",
  3073. " <tr>\n",
  3074. " <th>Shoes</th>\n",
  3075. " <td>3.843959</td>\n",
  3076. " <td>1991.620990</td>\n",
  3077. " </tr>\n",
  3078. " </tbody>\n",
  3079. "</table>\n",
  3080. "</div>"
  3081. ],
  3082. "text/plain": [
  3083. " spend_prop \\\n",
  3084. "Billing Event Ad Format strategy Interests \n",
  3085. "Impressions Image conversions Clothing or Coupons or Discount stores or Fashi... 2.633819 \n",
  3086. " Shoes 3.843959 \n",
  3087. "\n",
  3088. " cpt \n",
  3089. "Billing Event Ad Format strategy Interests \n",
  3090. "Impressions Image conversions Clothing or Coupons or Discount stores or Fashi... 1914.268194 \n",
  3091. " Shoes 1991.620990 "
  3092. ]
  3093. },
  3094. "metadata": {},
  3095. "output_type": "display_data"
  3096. },
  3097. {
  3098. "data": {
  3099. "text/html": [
  3100. "<div>\n",
  3101. "<table border=\"1\" class=\"dataframe\">\n",
  3102. " <thead>\n",
  3103. " <tr style=\"text-align: right;\">\n",
  3104. " <th></th>\n",
  3105. " <th></th>\n",
  3106. " <th></th>\n",
  3107. " <th></th>\n",
  3108. " <th>spend_prop</th>\n",
  3109. " <th>cpt</th>\n",
  3110. " </tr>\n",
  3111. " <tr>\n",
  3112. " <th>Billing Event</th>\n",
  3113. " <th>Ad Format</th>\n",
  3114. " <th>Locations</th>\n",
  3115. " <th>Age Range</th>\n",
  3116. " <th></th>\n",
  3117. " <th></th>\n",
  3118. " </tr>\n",
  3119. " </thead>\n",
  3120. " <tbody>\n",
  3121. " <tr>\n",
  3122. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  3123. " <th rowspan=\"2\" valign=\"top\">Image</th>\n",
  3124. " <th rowspan=\"2\" valign=\"top\">IN</th>\n",
  3125. " <th>18-35</th>\n",
  3126. " <td>5.928406</td>\n",
  3127. " <td>1951.147547</td>\n",
  3128. " </tr>\n",
  3129. " <tr>\n",
  3130. " <th>23-38</th>\n",
  3131. " <td>3.084434</td>\n",
  3132. " <td>1855.262874</td>\n",
  3133. " </tr>\n",
  3134. " </tbody>\n",
  3135. "</table>\n",
  3136. "</div>"
  3137. ],
  3138. "text/plain": [
  3139. " spend_prop cpt\n",
  3140. "Billing Event Ad Format Locations Age Range \n",
  3141. "Impressions Image IN 18-35 5.928406 1951.147547\n",
  3142. " 23-38 3.084434 1855.262874"
  3143. ]
  3144. },
  3145. "metadata": {},
  3146. "output_type": "display_data"
  3147. },
  3148. {
  3149. "data": {
  3150. "text/html": [
  3151. "<div>\n",
  3152. "<table border=\"1\" class=\"dataframe\">\n",
  3153. " <thead>\n",
  3154. " <tr style=\"text-align: right;\">\n",
  3155. " <th></th>\n",
  3156. " <th></th>\n",
  3157. " <th></th>\n",
  3158. " <th></th>\n",
  3159. " <th>spend_prop</th>\n",
  3160. " <th>cpt</th>\n",
  3161. " </tr>\n",
  3162. " <tr>\n",
  3163. " <th>Billing Event</th>\n",
  3164. " <th>Ad Format</th>\n",
  3165. " <th>Publisher Platforms</th>\n",
  3166. " <th>Interests</th>\n",
  3167. " <th></th>\n",
  3168. " <th></th>\n",
  3169. " </tr>\n",
  3170. " </thead>\n",
  3171. " <tbody>\n",
  3172. " <tr>\n",
  3173. " <th rowspan=\"4\" valign=\"top\">Impressions</th>\n",
  3174. " <th rowspan=\"4\" valign=\"top\">Image</th>\n",
  3175. " <th rowspan=\"4\" valign=\"top\">audience_network or facebook</th>\n",
  3176. " <th>Allen Solly or Formal wear or Mango (clothing) or Others or Startup company or Startups</th>\n",
  3177. " <td>3.084434</td>\n",
  3178. " <td>1855.262874</td>\n",
  3179. " </tr>\n",
  3180. " <tr>\n",
  3181. " <th>Amazon.com or Flipkart</th>\n",
  3182. " <td>2.510142</td>\n",
  3183. " <td>2478.401698</td>\n",
  3184. " </tr>\n",
  3185. " <tr>\n",
  3186. " <th>Ballet or Bars or Concerts or Dancehalls or Dresses or Others</th>\n",
  3187. " <td>3.375193</td>\n",
  3188. " <td>2053.758837</td>\n",
  3189. " </tr>\n",
  3190. " <tr>\n",
  3191. " <th>Clothing or Coupons or Discount stores or Fashion accessories or Footwear or Others</th>\n",
  3192. " <td>2.583539</td>\n",
  3193. " <td>1904.170986</td>\n",
  3194. " </tr>\n",
  3195. " </tbody>\n",
  3196. "</table>\n",
  3197. "</div>"
  3198. ],
  3199. "text/plain": [
  3200. " spend_prop \\\n",
  3201. "Billing Event Ad Format Publisher Platforms Interests \n",
  3202. "Impressions Image audience_network or facebook Allen Solly or Formal wear or Mango (clothing) ... 3.084434 \n",
  3203. " Amazon.com or Flipkart 2.510142 \n",
  3204. " Ballet or Bars or Concerts or Dancehalls or Dre... 3.375193 \n",
  3205. " Clothing or Coupons or Discount stores or Fashi... 2.583539 \n",
  3206. "\n",
  3207. " cpt \n",
  3208. "Billing Event Ad Format Publisher Platforms Interests \n",
  3209. "Impressions Image audience_network or facebook Allen Solly or Formal wear or Mango (clothing) ... 1855.262874 \n",
  3210. " Amazon.com or Flipkart 2478.401698 \n",
  3211. " Ballet or Bars or Concerts or Dancehalls or Dre... 2053.758837 \n",
  3212. " Clothing or Coupons or Discount stores or Fashi... 1904.170986 "
  3213. ]
  3214. },
  3215. "metadata": {},
  3216. "output_type": "display_data"
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  3218. {
  3219. "data": {
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  3225. " <th></th>\n",
  3226. " <th></th>\n",
  3227. " <th></th>\n",
  3228. " <th></th>\n",
  3229. " <th>spend_prop</th>\n",
  3230. " <th>cpt</th>\n",
  3231. " </tr>\n",
  3232. " <tr>\n",
  3233. " <th>Billing Event</th>\n",
  3234. " <th>Ad Type</th>\n",
  3235. " <th>strategy</th>\n",
  3236. " <th>Age Range</th>\n",
  3237. " <th></th>\n",
  3238. " <th></th>\n",
  3239. " </tr>\n",
  3240. " </thead>\n",
  3241. " <tbody>\n",
  3242. " <tr>\n",
  3243. " <th>Impressions</th>\n",
  3244. " <th>Carousel</th>\n",
  3245. " <th>conversions</th>\n",
  3246. " <th>25-34</th>\n",
  3247. " <td>2.504454</td>\n",
  3248. " <td>1985.72197</td>\n",
  3249. " </tr>\n",
  3250. " </tbody>\n",
  3251. "</table>\n",
  3252. "</div>"
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  3254. "text/plain": [
  3255. " spend_prop cpt\n",
  3256. "Billing Event Ad Type strategy Age Range \n",
  3257. "Impressions Carousel conversions 25-34 2.504454 1985.72197"
  3258. ]
  3259. },
  3260. "metadata": {},
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  3270. " <th></th>\n",
  3271. " <th></th>\n",
  3272. " <th></th>\n",
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  3277. " <tr>\n",
  3278. " <th>Billing Event</th>\n",
  3279. " <th>Gender</th>\n",
  3280. " <th>Publisher Platforms</th>\n",
  3281. " <th>Landing Pages</th>\n",
  3282. " <th></th>\n",
  3283. " <th></th>\n",
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  3286. " <tbody>\n",
  3287. " <tr>\n",
  3288. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  3289. " <th rowspan=\"2\" valign=\"top\">Female</th>\n",
  3290. " <th rowspan=\"2\" valign=\"top\">audience_network or facebook</th>\n",
  3291. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  3292. " <td>4.041050</td>\n",
  3293. " <td>1871.393097</td>\n",
  3294. " </tr>\n",
  3295. " <tr>\n",
  3296. " <th>www.koovs.com/women/tags/spring-into-march</th>\n",
  3297. " <td>3.592959</td>\n",
  3298. " <td>1899.180808</td>\n",
  3299. " </tr>\n",
  3300. " </tbody>\n",
  3301. "</table>\n",
  3302. "</div>"
  3303. ],
  3304. "text/plain": [
  3305. " spend_prop \\\n",
  3306. "Billing Event Gender Publisher Platforms Landing Pages \n",
  3307. "Impressions Female audience_network or facebook www.koovs.com/women/dresses, www.koovs.com/wome... 4.041050 \n",
  3308. " www.koovs.com/women/tags/spring-into-march 3.592959 \n",
  3309. "\n",
  3310. " cpt \n",
  3311. "Billing Event Gender Publisher Platforms Landing Pages \n",
  3312. "Impressions Female audience_network or facebook www.koovs.com/women/dresses, www.koovs.com/wome... 1871.393097 \n",
  3313. " www.koovs.com/women/tags/spring-into-march 1899.180808 "
  3314. ]
  3315. },
  3316. "metadata": {},
  3317. "output_type": "display_data"
  3318. },
  3319. {
  3320. "data": {
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  3323. "<table border=\"1\" class=\"dataframe\">\n",
  3324. " <thead>\n",
  3325. " <tr style=\"text-align: right;\">\n",
  3326. " <th></th>\n",
  3327. " <th></th>\n",
  3328. " <th></th>\n",
  3329. " <th></th>\n",
  3330. " <th>spend_prop</th>\n",
  3331. " <th>cpt</th>\n",
  3332. " </tr>\n",
  3333. " <tr>\n",
  3334. " <th>Billing Event</th>\n",
  3335. " <th>Campaign Objective</th>\n",
  3336. " <th>Locations</th>\n",
  3337. " <th>Age Range</th>\n",
  3338. " <th></th>\n",
  3339. " <th></th>\n",
  3340. " </tr>\n",
  3341. " </thead>\n",
  3342. " <tbody>\n",
  3343. " <tr>\n",
  3344. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  3345. " <th rowspan=\"2\" valign=\"top\">Conversions</th>\n",
  3346. " <th rowspan=\"2\" valign=\"top\">IN</th>\n",
  3347. " <th>18-35</th>\n",
  3348. " <td>5.928406</td>\n",
  3349. " <td>1951.147547</td>\n",
  3350. " </tr>\n",
  3351. " <tr>\n",
  3352. " <th>23-38</th>\n",
  3353. " <td>3.084434</td>\n",
  3354. " <td>1855.262874</td>\n",
  3355. " </tr>\n",
  3356. " </tbody>\n",
  3357. "</table>\n",
  3358. "</div>"
  3359. ],
  3360. "text/plain": [
  3361. " spend_prop cpt\n",
  3362. "Billing Event Campaign Objective Locations Age Range \n",
  3363. "Impressions Conversions IN 18-35 5.928406 1951.147547\n",
  3364. " 23-38 3.084434 1855.262874"
  3365. ]
  3366. },
  3367. "metadata": {},
  3368. "output_type": "display_data"
  3369. },
  3370. {
  3371. "data": {
  3372. "text/html": [
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  3374. "<table border=\"1\" class=\"dataframe\">\n",
  3375. " <thead>\n",
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  3377. " <th></th>\n",
  3378. " <th></th>\n",
  3379. " <th></th>\n",
  3380. " <th></th>\n",
  3381. " <th>spend_prop</th>\n",
  3382. " <th>cpt</th>\n",
  3383. " </tr>\n",
  3384. " <tr>\n",
  3385. " <th>Billing Event</th>\n",
  3386. " <th>Device Platforms</th>\n",
  3387. " <th>Publisher Platforms</th>\n",
  3388. " <th>Age Range</th>\n",
  3389. " <th></th>\n",
  3390. " <th></th>\n",
  3391. " </tr>\n",
  3392. " </thead>\n",
  3393. " <tbody>\n",
  3394. " <tr>\n",
  3395. " <th>Impressions</th>\n",
  3396. " <th>desktop or mobile</th>\n",
  3397. " <th>audience_network or facebook</th>\n",
  3398. " <th>18-35</th>\n",
  3399. " <td>3.375193</td>\n",
  3400. " <td>2053.758837</td>\n",
  3401. " </tr>\n",
  3402. " <tr>\n",
  3403. " <th>Link_clicks</th>\n",
  3404. " <th>desktop or mobile</th>\n",
  3405. " <th>audience_network or facebook</th>\n",
  3406. " <th>18-45</th>\n",
  3407. " <td>7.667755</td>\n",
  3408. " <td>955.362571</td>\n",
  3409. " </tr>\n",
  3410. " </tbody>\n",
  3411. "</table>\n",
  3412. "</div>"
  3413. ],
  3414. "text/plain": [
  3415. " spend_prop \\\n",
  3416. "Billing Event Device Platforms Publisher Platforms Age Range \n",
  3417. "Impressions desktop or mobile audience_network or facebook 18-35 3.375193 \n",
  3418. "Link_clicks desktop or mobile audience_network or facebook 18-45 7.667755 \n",
  3419. "\n",
  3420. " cpt \n",
  3421. "Billing Event Device Platforms Publisher Platforms Age Range \n",
  3422. "Impressions desktop or mobile audience_network or facebook 18-35 2053.758837 \n",
  3423. "Link_clicks desktop or mobile audience_network or facebook 18-45 955.362571 "
  3424. ]
  3425. },
  3426. "metadata": {},
  3427. "output_type": "display_data"
  3428. },
  3429. {
  3430. "data": {
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  3434. " <thead>\n",
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  3436. " <th></th>\n",
  3437. " <th></th>\n",
  3438. " <th></th>\n",
  3439. " <th></th>\n",
  3440. " <th>spend_prop</th>\n",
  3441. " <th>cpt</th>\n",
  3442. " </tr>\n",
  3443. " <tr>\n",
  3444. " <th>Billing Event</th>\n",
  3445. " <th>Gender</th>\n",
  3446. " <th>Facebook Positions</th>\n",
  3447. " <th>Age Range</th>\n",
  3448. " <th></th>\n",
  3449. " <th></th>\n",
  3450. " </tr>\n",
  3451. " </thead>\n",
  3452. " <tbody>\n",
  3453. " <tr>\n",
  3454. " <th>Impressions</th>\n",
  3455. " <th>Female</th>\n",
  3456. " <th>feed or right_hand_column</th>\n",
  3457. " <th>18-35</th>\n",
  3458. " <td>3.375193</td>\n",
  3459. " <td>2053.758837</td>\n",
  3460. " </tr>\n",
  3461. " <tr>\n",
  3462. " <th>Link_clicks</th>\n",
  3463. " <th>Female</th>\n",
  3464. " <th>feed or right_hand_column</th>\n",
  3465. " <th>18-45</th>\n",
  3466. " <td>6.010736</td>\n",
  3467. " <td>1077.194418</td>\n",
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  3469. " </tbody>\n",
  3470. "</table>\n",
  3471. "</div>"
  3472. ],
  3473. "text/plain": [
  3474. " spend_prop \\\n",
  3475. "Billing Event Gender Facebook Positions Age Range \n",
  3476. "Impressions Female feed or right_hand_column 18-35 3.375193 \n",
  3477. "Link_clicks Female feed or right_hand_column 18-45 6.010736 \n",
  3478. "\n",
  3479. " cpt \n",
  3480. "Billing Event Gender Facebook Positions Age Range \n",
  3481. "Impressions Female feed or right_hand_column 18-35 2053.758837 \n",
  3482. "Link_clicks Female feed or right_hand_column 18-45 1077.194418 "
  3483. ]
  3484. },
  3485. "metadata": {},
  3486. "output_type": "display_data"
  3487. },
  3488. {
  3489. "data": {
  3490. "text/html": [
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  3492. "<table border=\"1\" class=\"dataframe\">\n",
  3493. " <thead>\n",
  3494. " <tr style=\"text-align: right;\">\n",
  3495. " <th></th>\n",
  3496. " <th></th>\n",
  3497. " <th></th>\n",
  3498. " <th></th>\n",
  3499. " <th>spend_prop</th>\n",
  3500. " <th>cpt</th>\n",
  3501. " </tr>\n",
  3502. " <tr>\n",
  3503. " <th>Billing Event</th>\n",
  3504. " <th>Ad Type</th>\n",
  3505. " <th>Facebook Positions</th>\n",
  3506. " <th>Landing Pages</th>\n",
  3507. " <th></th>\n",
  3508. " <th></th>\n",
  3509. " </tr>\n",
  3510. " </thead>\n",
  3511. " <tbody>\n",
  3512. " <tr>\n",
  3513. " <th>Impressions</th>\n",
  3514. " <th>Carousel</th>\n",
  3515. " <th>feed</th>\n",
  3516. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  3517. " <td>2.058482</td>\n",
  3518. " <td>1923.571964</td>\n",
  3519. " </tr>\n",
  3520. " </tbody>\n",
  3521. "</table>\n",
  3522. "</div>"
  3523. ],
  3524. "text/plain": [
  3525. " spend_prop \\\n",
  3526. "Billing Event Ad Type Facebook Positions Landing Pages \n",
  3527. "Impressions Carousel feed www.koovs.com/women/dresses, www.koovs.com/wome... 2.058482 \n",
  3528. "\n",
  3529. " cpt \n",
  3530. "Billing Event Ad Type Facebook Positions Landing Pages \n",
  3531. "Impressions Carousel feed www.koovs.com/women/dresses, www.koovs.com/wome... 1923.571964 "
  3532. ]
  3533. },
  3534. "metadata": {},
  3535. "output_type": "display_data"
  3536. },
  3537. {
  3538. "data": {
  3539. "text/html": [
  3540. "<div>\n",
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  3544. " <th></th>\n",
  3545. " <th></th>\n",
  3546. " <th></th>\n",
  3547. " <th></th>\n",
  3548. " <th>spend_prop</th>\n",
  3549. " <th>cpt</th>\n",
  3550. " </tr>\n",
  3551. " <tr>\n",
  3552. " <th>Billing Event</th>\n",
  3553. " <th>Audience Strategy</th>\n",
  3554. " <th>Audience Types</th>\n",
  3555. " <th>Interests</th>\n",
  3556. " <th></th>\n",
  3557. " <th></th>\n",
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  3560. " <tbody>\n",
  3561. " <tr>\n",
  3562. " <th>Impressions</th>\n",
  3563. " <th>Prospecting</th>\n",
  3564. " <th>Interests</th>\n",
  3565. " <th>Amazon.com or Flipkart</th>\n",
  3566. " <td>2.510142</td>\n",
  3567. " <td>2478.401698</td>\n",
  3568. " </tr>\n",
  3569. " </tbody>\n",
  3570. "</table>\n",
  3571. "</div>"
  3572. ],
  3573. "text/plain": [
  3574. " spend_prop \\\n",
  3575. "Billing Event Audience Strategy Audience Types Interests \n",
  3576. "Impressions Prospecting Interests Amazon.com or Flipkart 2.510142 \n",
  3577. "\n",
  3578. " cpt \n",
  3579. "Billing Event Audience Strategy Audience Types Interests \n",
  3580. "Impressions Prospecting Interests Amazon.com or Flipkart 2478.401698 "
  3581. ]
  3582. },
  3583. "metadata": {},
  3584. "output_type": "display_data"
  3585. },
  3586. {
  3587. "data": {
  3588. "text/html": [
  3589. "<div>\n",
  3590. "<table border=\"1\" class=\"dataframe\">\n",
  3591. " <thead>\n",
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  3593. " <th></th>\n",
  3594. " <th></th>\n",
  3595. " <th></th>\n",
  3596. " <th></th>\n",
  3597. " <th>spend_prop</th>\n",
  3598. " <th>cpt</th>\n",
  3599. " </tr>\n",
  3600. " <tr>\n",
  3601. " <th>Billing Event</th>\n",
  3602. " <th>Device Platforms</th>\n",
  3603. " <th>Locations</th>\n",
  3604. " <th>Landing Pages</th>\n",
  3605. " <th></th>\n",
  3606. " <th></th>\n",
  3607. " </tr>\n",
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  3609. " <tbody>\n",
  3610. " <tr>\n",
  3611. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  3612. " <th rowspan=\"2\" valign=\"top\">desktop or mobile</th>\n",
  3613. " <th rowspan=\"2\" valign=\"top\">IN</th>\n",
  3614. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  3615. " <td>2.494728</td>\n",
  3616. " <td>1978.010000</td>\n",
  3617. " </tr>\n",
  3618. " <tr>\n",
  3619. " <th>www.koovs.com/women/tags/spring-into-march</th>\n",
  3620. " <td>2.195466</td>\n",
  3621. " <td>2393.507083</td>\n",
  3622. " </tr>\n",
  3623. " </tbody>\n",
  3624. "</table>\n",
  3625. "</div>"
  3626. ],
  3627. "text/plain": [
  3628. " spend_prop \\\n",
  3629. "Billing Event Device Platforms Locations Landing Pages \n",
  3630. "Impressions desktop or mobile IN www.koovs.com/women/dresses, www.koovs.com/wome... 2.494728 \n",
  3631. " www.koovs.com/women/tags/spring-into-march 2.195466 \n",
  3632. "\n",
  3633. " cpt \n",
  3634. "Billing Event Device Platforms Locations Landing Pages \n",
  3635. "Impressions desktop or mobile IN www.koovs.com/women/dresses, www.koovs.com/wome... 1978.010000 \n",
  3636. " www.koovs.com/women/tags/spring-into-march 2393.507083 "
  3637. ]
  3638. },
  3639. "metadata": {},
  3640. "output_type": "display_data"
  3641. },
  3642. {
  3643. "data": {
  3644. "text/html": [
  3645. "<div>\n",
  3646. "<table border=\"1\" class=\"dataframe\">\n",
  3647. " <thead>\n",
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  3649. " <th></th>\n",
  3650. " <th></th>\n",
  3651. " <th></th>\n",
  3652. " <th></th>\n",
  3653. " <th>spend_prop</th>\n",
  3654. " <th>cpt</th>\n",
  3655. " </tr>\n",
  3656. " <tr>\n",
  3657. " <th>Billing Event</th>\n",
  3658. " <th>Ad Type</th>\n",
  3659. " <th>Publisher Platforms</th>\n",
  3660. " <th>Interests</th>\n",
  3661. " <th></th>\n",
  3662. " <th></th>\n",
  3663. " </tr>\n",
  3664. " </thead>\n",
  3665. " <tbody>\n",
  3666. " <tr>\n",
  3667. " <th rowspan=\"4\" valign=\"top\">Impressions</th>\n",
  3668. " <th rowspan=\"4\" valign=\"top\">Carousel</th>\n",
  3669. " <th rowspan=\"4\" valign=\"top\">audience_network or facebook</th>\n",
  3670. " <th>Allen Solly or Formal wear or Mango (clothing) or Others or Startup company or Startups</th>\n",
  3671. " <td>3.084434</td>\n",
  3672. " <td>1855.262874</td>\n",
  3673. " </tr>\n",
  3674. " <tr>\n",
  3675. " <th>Amazon.com or Flipkart</th>\n",
  3676. " <td>2.510142</td>\n",
  3677. " <td>2478.401698</td>\n",
  3678. " </tr>\n",
  3679. " <tr>\n",
  3680. " <th>Ballet or Bars or Concerts or Dancehalls or Dresses or Others</th>\n",
  3681. " <td>3.375193</td>\n",
  3682. " <td>2053.758837</td>\n",
  3683. " </tr>\n",
  3684. " <tr>\n",
  3685. " <th>Clothing or Coupons or Discount stores or Fashion accessories or Footwear or Others</th>\n",
  3686. " <td>2.583539</td>\n",
  3687. " <td>1904.170986</td>\n",
  3688. " </tr>\n",
  3689. " </tbody>\n",
  3690. "</table>\n",
  3691. "</div>"
  3692. ],
  3693. "text/plain": [
  3694. " spend_prop \\\n",
  3695. "Billing Event Ad Type Publisher Platforms Interests \n",
  3696. "Impressions Carousel audience_network or facebook Allen Solly or Formal wear or Mango (clothing) ... 3.084434 \n",
  3697. " Amazon.com or Flipkart 2.510142 \n",
  3698. " Ballet or Bars or Concerts or Dancehalls or Dre... 3.375193 \n",
  3699. " Clothing or Coupons or Discount stores or Fashi... 2.583539 \n",
  3700. "\n",
  3701. " cpt \n",
  3702. "Billing Event Ad Type Publisher Platforms Interests \n",
  3703. "Impressions Carousel audience_network or facebook Allen Solly or Formal wear or Mango (clothing) ... 1855.262874 \n",
  3704. " Amazon.com or Flipkart 2478.401698 \n",
  3705. " Ballet or Bars or Concerts or Dancehalls or Dre... 2053.758837 \n",
  3706. " Clothing or Coupons or Discount stores or Fashi... 1904.170986 "
  3707. ]
  3708. },
  3709. "metadata": {},
  3710. "output_type": "display_data"
  3711. },
  3712. {
  3713. "data": {
  3714. "text/html": [
  3715. "<div>\n",
  3716. "<table border=\"1\" class=\"dataframe\">\n",
  3717. " <thead>\n",
  3718. " <tr style=\"text-align: right;\">\n",
  3719. " <th></th>\n",
  3720. " <th></th>\n",
  3721. " <th></th>\n",
  3722. " <th></th>\n",
  3723. " <th>spend_prop</th>\n",
  3724. " <th>cpt</th>\n",
  3725. " </tr>\n",
  3726. " <tr>\n",
  3727. " <th>Billing Event</th>\n",
  3728. " <th>Ad Format</th>\n",
  3729. " <th>strategy</th>\n",
  3730. " <th>Age Range</th>\n",
  3731. " <th></th>\n",
  3732. " <th></th>\n",
  3733. " </tr>\n",
  3734. " </thead>\n",
  3735. " <tbody>\n",
  3736. " <tr>\n",
  3737. " <th>Impressions</th>\n",
  3738. " <th>Image</th>\n",
  3739. " <th>conversions</th>\n",
  3740. " <th>25-34</th>\n",
  3741. " <td>2.504454</td>\n",
  3742. " <td>1985.72197</td>\n",
  3743. " </tr>\n",
  3744. " </tbody>\n",
  3745. "</table>\n",
  3746. "</div>"
  3747. ],
  3748. "text/plain": [
  3749. " spend_prop cpt\n",
  3750. "Billing Event Ad Format strategy Age Range \n",
  3751. "Impressions Image conversions 25-34 2.504454 1985.72197"
  3752. ]
  3753. },
  3754. "metadata": {},
  3755. "output_type": "display_data"
  3756. },
  3757. {
  3758. "data": {
  3759. "text/html": [
  3760. "<div>\n",
  3761. "<table border=\"1\" class=\"dataframe\">\n",
  3762. " <thead>\n",
  3763. " <tr style=\"text-align: right;\">\n",
  3764. " <th></th>\n",
  3765. " <th></th>\n",
  3766. " <th></th>\n",
  3767. " <th></th>\n",
  3768. " <th>spend_prop</th>\n",
  3769. " <th>cpt</th>\n",
  3770. " </tr>\n",
  3771. " <tr>\n",
  3772. " <th>Billing Event</th>\n",
  3773. " <th>Ad Format</th>\n",
  3774. " <th>Publisher Platforms</th>\n",
  3775. " <th>Landing Pages</th>\n",
  3776. " <th></th>\n",
  3777. " <th></th>\n",
  3778. " </tr>\n",
  3779. " </thead>\n",
  3780. " <tbody>\n",
  3781. " <tr>\n",
  3782. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  3783. " <th rowspan=\"2\" valign=\"top\">Image</th>\n",
  3784. " <th rowspan=\"2\" valign=\"top\">audience_network or facebook</th>\n",
  3785. " <th>www.koovs.com/women/dresses, www.koovs.com/women/tops/sortby-latest, www.koovs.com/women/shoes/sortby-latest, www.koovs.com/women/jeans/sortby-latest</th>\n",
  3786. " <td>4.041050</td>\n",
  3787. " <td>1871.393097</td>\n",
  3788. " </tr>\n",
  3789. " <tr>\n",
  3790. " <th>www.koovs.com/women/tags/spring-into-march</th>\n",
  3791. " <td>3.592959</td>\n",
  3792. " <td>1899.180808</td>\n",
  3793. " </tr>\n",
  3794. " </tbody>\n",
  3795. "</table>\n",
  3796. "</div>"
  3797. ],
  3798. "text/plain": [
  3799. " spend_prop \\\n",
  3800. "Billing Event Ad Format Publisher Platforms Landing Pages \n",
  3801. "Impressions Image audience_network or facebook www.koovs.com/women/dresses, www.koovs.com/wome... 4.041050 \n",
  3802. " www.koovs.com/women/tags/spring-into-march 3.592959 \n",
  3803. "\n",
  3804. " cpt \n",
  3805. "Billing Event Ad Format Publisher Platforms Landing Pages \n",
  3806. "Impressions Image audience_network or facebook www.koovs.com/women/dresses, www.koovs.com/wome... 1871.393097 \n",
  3807. " www.koovs.com/women/tags/spring-into-march 1899.180808 "
  3808. ]
  3809. },
  3810. "metadata": {},
  3811. "output_type": "display_data"
  3812. },
  3813. {
  3814. "data": {
  3815. "text/html": [
  3816. "<div>\n",
  3817. "<table border=\"1\" class=\"dataframe\">\n",
  3818. " <thead>\n",
  3819. " <tr style=\"text-align: right;\">\n",
  3820. " <th></th>\n",
  3821. " <th></th>\n",
  3822. " <th></th>\n",
  3823. " <th></th>\n",
  3824. " <th>spend_prop</th>\n",
  3825. " <th>cpt</th>\n",
  3826. " </tr>\n",
  3827. " <tr>\n",
  3828. " <th>Billing Event</th>\n",
  3829. " <th>Audience Strategy</th>\n",
  3830. " <th>strategy</th>\n",
  3831. " <th>Age Range</th>\n",
  3832. " <th></th>\n",
  3833. " <th></th>\n",
  3834. " </tr>\n",
  3835. " </thead>\n",
  3836. " <tbody>\n",
  3837. " <tr>\n",
  3838. " <th>Impressions</th>\n",
  3839. " <th>Prospecting</th>\n",
  3840. " <th>conversions</th>\n",
  3841. " <th>25-34</th>\n",
  3842. " <td>2.504454</td>\n",
  3843. " <td>1985.72197</td>\n",
  3844. " </tr>\n",
  3845. " </tbody>\n",
  3846. "</table>\n",
  3847. "</div>"
  3848. ],
  3849. "text/plain": [
  3850. " spend_prop cpt\n",
  3851. "Billing Event Audience Strategy strategy Age Range \n",
  3852. "Impressions Prospecting conversions 25-34 2.504454 1985.72197"
  3853. ]
  3854. },
  3855. "metadata": {},
  3856. "output_type": "display_data"
  3857. },
  3858. {
  3859. "data": {
  3860. "text/html": [
  3861. "<div>\n",
  3862. "<table border=\"1\" class=\"dataframe\">\n",
  3863. " <thead>\n",
  3864. " <tr style=\"text-align: right;\">\n",
  3865. " <th></th>\n",
  3866. " <th></th>\n",
  3867. " <th></th>\n",
  3868. " <th></th>\n",
  3869. " <th>spend_prop</th>\n",
  3870. " <th>cpt</th>\n",
  3871. " </tr>\n",
  3872. " <tr>\n",
  3873. " <th>Billing Event</th>\n",
  3874. " <th>Ad Type</th>\n",
  3875. " <th>Publisher Platforms</th>\n",
  3876. " <th>Age Range</th>\n",
  3877. " <th></th>\n",
  3878. " <th></th>\n",
  3879. " </tr>\n",
  3880. " </thead>\n",
  3881. " <tbody>\n",
  3882. " <tr>\n",
  3883. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  3884. " <th rowspan=\"2\" valign=\"top\">Carousel</th>\n",
  3885. " <th rowspan=\"2\" valign=\"top\">audience_network or facebook</th>\n",
  3886. " <th>18-35</th>\n",
  3887. " <td>3.725390</td>\n",
  3888. " <td>2119.010761</td>\n",
  3889. " </tr>\n",
  3890. " <tr>\n",
  3891. " <th>23-38</th>\n",
  3892. " <td>3.084434</td>\n",
  3893. " <td>1855.262874</td>\n",
  3894. " </tr>\n",
  3895. " </tbody>\n",
  3896. "</table>\n",
  3897. "</div>"
  3898. ],
  3899. "text/plain": [
  3900. " spend_prop \\\n",
  3901. "Billing Event Ad Type Publisher Platforms Age Range \n",
  3902. "Impressions Carousel audience_network or facebook 18-35 3.725390 \n",
  3903. " 23-38 3.084434 \n",
  3904. "\n",
  3905. " cpt \n",
  3906. "Billing Event Ad Type Publisher Platforms Age Range \n",
  3907. "Impressions Carousel audience_network or facebook 18-35 2119.010761 \n",
  3908. " 23-38 1855.262874 "
  3909. ]
  3910. },
  3911. "metadata": {},
  3912. "output_type": "display_data"
  3913. },
  3914. {
  3915. "data": {
  3916. "text/html": [
  3917. "<div>\n",
  3918. "<table border=\"1\" class=\"dataframe\">\n",
  3919. " <thead>\n",
  3920. " <tr style=\"text-align: right;\">\n",
  3921. " <th></th>\n",
  3922. " <th></th>\n",
  3923. " <th></th>\n",
  3924. " <th></th>\n",
  3925. " <th>spend_prop</th>\n",
  3926. " <th>cpt</th>\n",
  3927. " </tr>\n",
  3928. " <tr>\n",
  3929. " <th>Billing Event</th>\n",
  3930. " <th>Campaign Objective</th>\n",
  3931. " <th>strategy</th>\n",
  3932. " <th>Interests</th>\n",
  3933. " <th></th>\n",
  3934. " <th></th>\n",
  3935. " </tr>\n",
  3936. " </thead>\n",
  3937. " <tbody>\n",
  3938. " <tr>\n",
  3939. " <th rowspan=\"2\" valign=\"top\">Impressions</th>\n",
  3940. " <th rowspan=\"2\" valign=\"top\">Conversions</th>\n",
  3941. " <th rowspan=\"2\" valign=\"top\">conversions</th>\n",
  3942. " <th>Clothing or Coupons or Discount stores or Fashion accessories or Footwear or Others</th>\n",
  3943. " <td>2.633819</td>\n",
  3944. " <td>1914.268194</td>\n",
  3945. " </tr>\n",
  3946. " <tr>\n",
  3947. " <th>Shoes</th>\n",
  3948. " <td>3.843959</td>\n",
  3949. " <td>1991.620990</td>\n",
  3950. " </tr>\n",
  3951. " </tbody>\n",
  3952. "</table>\n",
  3953. "</div>"
  3954. ],
  3955. "text/plain": [
  3956. " spend_prop \\\n",
  3957. "Billing Event Campaign Objective strategy Interests \n",
  3958. "Impressions Conversions conversions Clothing or Coupons or Discount stores or Fashi... 2.633819 \n",
  3959. " Shoes 3.843959 \n",
  3960. "\n",
  3961. " cpt \n",
  3962. "Billing Event Campaign Objective strategy Interests \n",
  3963. "Impressions Conversions conversions Clothing or Coupons or Discount stores or Fashi... 1914.268194 \n",
  3964. " Shoes 1991.620990 "
  3965. ]
  3966. },
  3967. "metadata": {},
  3968. "output_type": "display_data"
  3969. }
  3970. ],
  3971. "source": [
  3972. "bad_new, bad_impacts = get_filtered_paths(bad_raw)\n",
  3973. "bad_impacts_list = [value[0] for value in bad_impacts]\n",
  3974. "\n",
  3975. "display_df(bad_new, bad_impacts_list, num=100, level=[4])"
  3976. ]
  3977. },
  3978. {
  3979. "cell_type": "markdown",
  3980. "metadata": {},
  3981. "source": [
  3982. "### Good Paths"
  3983. ]
  3984. },
  3985. {
  3986. "cell_type": "code",
  3987. "execution_count": 64,
  3988. "metadata": {
  3989. "collapsed": true
  3990. },
  3991. "outputs": [
  3992. {
  3993. "data": {
  3994. "text/html": [
  3995. "<div>\n",
  3996. "<table border=\"1\" class=\"dataframe\">\n",
  3997. " <thead>\n",
  3998. " <tr style=\"text-align: right;\">\n",
  3999. " <th></th>\n",
  4000. " <th></th>\n",
  4001. " <th></th>\n",
  4002. " <th></th>\n",
  4003. " <th>spend_prop</th>\n",
  4004. " <th>cpt</th>\n",
  4005. " </tr>\n",
  4006. " <tr>\n",
  4007. " <th>Billing Event</th>\n",
  4008. " <th>Gender</th>\n",
  4009. " <th>Locations</th>\n",
  4010. " <th>Lookalike Types</th>\n",
  4011. " <th></th>\n",
  4012. " <th></th>\n",
  4013. " </tr>\n",
  4014. " </thead>\n",
  4015. " <tbody>\n",
  4016. " <tr>\n",
  4017. " <th>Impressions</th>\n",
  4018. " <th>Female</th>\n",
  4019. " <th>IN</th>\n",
  4020. " <th>1%</th>\n",
  4021. " <td>9.745652</td>\n",
  4022. " <td>1073.659579</td>\n",
  4023. " </tr>\n",
  4024. " </tbody>\n",
  4025. "</table>\n",
  4026. "</div>"
  4027. ],
  4028. "text/plain": [
  4029. " spend_prop cpt\n",
  4030. "Billing Event Gender Locations Lookalike Types \n",
  4031. "Impressions Female IN 1% 9.745652 1073.659579"
  4032. ]
  4033. },
  4034. "metadata": {},
  4035. "output_type": "display_data"
  4036. },
  4037. {
  4038. "data": {
  4039. "text/html": [
  4040. "<div>\n",
  4041. "<table border=\"1\" class=\"dataframe\">\n",
  4042. " <thead>\n",
  4043. " <tr style=\"text-align: right;\">\n",
  4044. " <th></th>\n",
  4045. " <th></th>\n",
  4046. " <th></th>\n",
  4047. " <th></th>\n",
  4048. " <th>spend_prop</th>\n",
  4049. " <th>cpt</th>\n",
  4050. " </tr>\n",
  4051. " <tr>\n",
  4052. " <th>Billing Event</th>\n",
  4053. " <th>Device Platforms</th>\n",
  4054. " <th>Publisher Platforms</th>\n",
  4055. " <th>Custom Audiences</th>\n",
  4056. " <th></th>\n",
  4057. " <th></th>\n",
  4058. " </tr>\n",
  4059. " </thead>\n",
  4060. " <tbody>\n",
  4061. " <tr>\n",
  4062. " <th>Impressions</th>\n",
  4063. " <th>desktop or mobile</th>\n",
  4064. " <th>audience_network or facebook</th>\n",
  4065. " <th>ECOMMERCE MOBILE & EMAIL IDS FEB 2017</th>\n",
  4066. " <td>5.03836</td>\n",
  4067. " <td>1193.015747</td>\n",
  4068. " </tr>\n",
  4069. " </tbody>\n",
  4070. "</table>\n",
  4071. "</div>"
  4072. ],
  4073. "text/plain": [
  4074. " spend_prop \\\n",
  4075. "Billing Event Device Platforms Publisher Platforms Custom Audiences \n",
  4076. "Impressions desktop or mobile audience_network or facebook ECOMMERCE MOBILE & EMAIL IDS FEB 2017 5.03836 \n",
  4077. "\n",
  4078. " cpt \n",
  4079. "Billing Event Device Platforms Publisher Platforms Custom Audiences \n",
  4080. "Impressions desktop or mobile audience_network or facebook ECOMMERCE MOBILE & EMAIL IDS FEB 2017 1193.015747 "
  4081. ]
  4082. },
  4083. "metadata": {},
  4084. "output_type": "display_data"
  4085. },
  4086. {
  4087. "data": {
  4088. "text/html": [
  4089. "<div>\n",
  4090. "<table border=\"1\" class=\"dataframe\">\n",
  4091. " <thead>\n",
  4092. " <tr style=\"text-align: right;\">\n",
  4093. " <th></th>\n",
  4094. " <th></th>\n",
  4095. " <th></th>\n",
  4096. " <th></th>\n",
  4097. " <th>spend_prop</th>\n",
  4098. " <th>cpt</th>\n",
  4099. " </tr>\n",
  4100. " <tr>\n",
  4101. " <th>Billing Event</th>\n",
  4102. " <th>Device Platforms</th>\n",
  4103. " <th>Audience Types</th>\n",
  4104. " <th>-</th>\n",
  4105. " <th></th>\n",
  4106. " <th></th>\n",
  4107. " </tr>\n",
  4108. " </thead>\n",
  4109. " <tbody>\n",
  4110. " <tr>\n",
  4111. " <th>Impressions</th>\n",
  4112. " <th>desktop or mobile</th>\n",
  4113. " <th>DPA</th>\n",
  4114. " <th>-</th>\n",
  4115. " <td>6.354514</td>\n",
  4116. " <td>678.633878</td>\n",
  4117. " </tr>\n",
  4118. " </tbody>\n",
  4119. "</table>\n",
  4120. "</div>"
  4121. ],
  4122. "text/plain": [
  4123. " spend_prop cpt\n",
  4124. "Billing Event Device Platforms Audience Types - \n",
  4125. "Impressions desktop or mobile DPA - 6.354514 678.633878"
  4126. ]
  4127. },
  4128. "metadata": {},
  4129. "output_type": "display_data"
  4130. },
  4131. {
  4132. "data": {
  4133. "text/html": [
  4134. "<div>\n",
  4135. "<table border=\"1\" class=\"dataframe\">\n",
  4136. " <thead>\n",
  4137. " <tr style=\"text-align: right;\">\n",
  4138. " <th></th>\n",
  4139. " <th></th>\n",
  4140. " <th></th>\n",
  4141. " <th></th>\n",
  4142. " <th>spend_prop</th>\n",
  4143. " <th>cpt</th>\n",
  4144. " </tr>\n",
  4145. " <tr>\n",
  4146. " <th>Billing Event</th>\n",
  4147. " <th>Campaign Objective</th>\n",
  4148. " <th>Publisher Platforms</th>\n",
  4149. " <th>Age Range</th>\n",
  4150. " <th></th>\n",
  4151. " <th></th>\n",
  4152. " </tr>\n",
  4153. " </thead>\n",
  4154. " <tbody>\n",
  4155. " <tr>\n",
  4156. " <th>Impressions</th>\n",
  4157. " <th>Conversions</th>\n",
  4158. " <th>audience_network or facebook</th>\n",
  4159. " <th>18-65</th>\n",
  4160. " <td>5.230758</td>\n",
  4161. " <td>1174.783948</td>\n",
  4162. " </tr>\n",
  4163. " </tbody>\n",
  4164. "</table>\n",
  4165. "</div>"
  4166. ],
  4167. "text/plain": [
  4168. " spend_prop \\\n",
  4169. "Billing Event Campaign Objective Publisher Platforms Age Range \n",
  4170. "Impressions Conversions audience_network or facebook 18-65 5.230758 \n",
  4171. "\n",
  4172. " cpt \n",
  4173. "Billing Event Campaign Objective Publisher Platforms Age Range \n",
  4174. "Impressions Conversions audience_network or facebook 18-65 1174.783948 "
  4175. ]
  4176. },
  4177. "metadata": {},
  4178. "output_type": "display_data"
  4179. },
  4180. {
  4181. "data": {
  4182. "text/html": [
  4183. "<div>\n",
  4184. "<table border=\"1\" class=\"dataframe\">\n",
  4185. " <thead>\n",
  4186. " <tr style=\"text-align: right;\">\n",
  4187. " <th></th>\n",
  4188. " <th></th>\n",
  4189. " <th></th>\n",
  4190. " <th></th>\n",
  4191. " <th>spend_prop</th>\n",
  4192. " <th>cpt</th>\n",
  4193. " </tr>\n",
  4194. " <tr>\n",
  4195. " <th>Billing Event</th>\n",
  4196. " <th>Audience Strategy</th>\n",
  4197. " <th>Publisher Platforms</th>\n",
  4198. " <th>Landing Pages</th>\n",
  4199. " <th></th>\n",
  4200. " <th></th>\n",
  4201. " </tr>\n",
  4202. " </thead>\n",
  4203. " <tbody>\n",
  4204. " <tr>\n",
  4205. " <th>Impressions</th>\n",
  4206. " <th>Prospecting</th>\n",
  4207. " <th>audience_network or facebook</th>\n",
  4208. " <th>www.koovs.com/women/tags/half-way-there</th>\n",
  4209. " <td>2.291822</td>\n",
  4210. " <td>869.062826</td>\n",
  4211. " </tr>\n",
  4212. " </tbody>\n",
  4213. "</table>\n",
  4214. "</div>"
  4215. ],
  4216. "text/plain": [
  4217. " spend_prop \\\n",
  4218. "Billing Event Audience Strategy Publisher Platforms Landing Pages \n",
  4219. "Impressions Prospecting audience_network or facebook www.koovs.com/women/tags/half-way-there 2.291822 \n",
  4220. "\n",
  4221. " cpt \n",
  4222. "Billing Event Audience Strategy Publisher Platforms Landing Pages \n",
  4223. "Impressions Prospecting audience_network or facebook www.koovs.com/women/tags/half-way-there 869.062826 "
  4224. ]
  4225. },
  4226. "metadata": {},
  4227. "output_type": "display_data"
  4228. },
  4229. {
  4230. "data": {
  4231. "text/html": [
  4232. "<div>\n",
  4233. "<table border=\"1\" class=\"dataframe\">\n",
  4234. " <thead>\n",
  4235. " <tr style=\"text-align: right;\">\n",
  4236. " <th></th>\n",
  4237. " <th></th>\n",
  4238. " <th></th>\n",
  4239. " <th></th>\n",
  4240. " <th>spend_prop</th>\n",
  4241. " <th>cpt</th>\n",
  4242. " </tr>\n",
  4243. " <tr>\n",
  4244. " <th>Billing Event</th>\n",
  4245. " <th>Device Platforms</th>\n",
  4246. " <th>Locations</th>\n",
  4247. " <th>Landing Pages</th>\n",
  4248. " <th></th>\n",
  4249. " <th></th>\n",
  4250. " </tr>\n",
  4251. " </thead>\n",
  4252. " <tbody>\n",
  4253. " <tr>\n",
  4254. " <th>Impressions</th>\n",
  4255. " <th>desktop or mobile</th>\n",
  4256. " <th>IN</th>\n",
  4257. " <th>koovs.com</th>\n",
  4258. " <td>6.354514</td>\n",
  4259. " <td>678.633878</td>\n",
  4260. " </tr>\n",
  4261. " </tbody>\n",
  4262. "</table>\n",
  4263. "</div>"
  4264. ],
  4265. "text/plain": [
  4266. " spend_prop \\\n",
  4267. "Billing Event Device Platforms Locations Landing Pages \n",
  4268. "Impressions desktop or mobile IN koovs.com 6.354514 \n",
  4269. "\n",
  4270. " cpt \n",
  4271. "Billing Event Device Platforms Locations Landing Pages \n",
  4272. "Impressions desktop or mobile IN koovs.com 678.633878 "
  4273. ]
  4274. },
  4275. "metadata": {},
  4276. "output_type": "display_data"
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  4278. {
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  4285. " <th></th>\n",
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  4291. " </tr>\n",
  4292. " <tr>\n",
  4293. " <th>Billing Event</th>\n",
  4294. " <th>Gender</th>\n",
  4295. " <th>Publisher Platforms</th>\n",
  4296. " <th>Age Range</th>\n",
  4297. " <th></th>\n",
  4298. " <th></th>\n",
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  4300. " </thead>\n",
  4301. " <tbody>\n",
  4302. " <tr>\n",
  4303. " <th>Impressions</th>\n",
  4304. " <th>Female</th>\n",
  4305. " <th>audience_network or facebook</th>\n",
  4306. " <th>18-65</th>\n",
  4307. " <td>3.595755</td>\n",
  4308. " <td>1213.969355</td>\n",
  4309. " </tr>\n",
  4310. " </tbody>\n",
  4311. "</table>\n",
  4312. "</div>"
  4313. ],
  4314. "text/plain": [
  4315. " spend_prop \\\n",
  4316. "Billing Event Gender Publisher Platforms Age Range \n",
  4317. "Impressions Female audience_network or facebook 18-65 3.595755 \n",
  4318. "\n",
  4319. " cpt \n",
  4320. "Billing Event Gender Publisher Platforms Age Range \n",
  4321. "Impressions Female audience_network or facebook 18-65 1213.969355 "
  4322. ]
  4323. },
  4324. "metadata": {},
  4325. "output_type": "display_data"
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  4334. " <th></th>\n",
  4335. " <th></th>\n",
  4336. " <th></th>\n",
  4337. " <th></th>\n",
  4338. " <th>spend_prop</th>\n",
  4339. " <th>cpt</th>\n",
  4340. " </tr>\n",
  4341. " <tr>\n",
  4342. " <th>Billing Event</th>\n",
  4343. " <th>Ad Type</th>\n",
  4344. " <th>Audience Types</th>\n",
  4345. " <th>-</th>\n",
  4346. " <th></th>\n",
  4347. " <th></th>\n",
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  4349. " </thead>\n",
  4350. " <tbody>\n",
  4351. " <tr>\n",
  4352. " <th>Impressions</th>\n",
  4353. " <th>Carousel</th>\n",
  4354. " <th>Custom</th>\n",
  4355. " <th>-</th>\n",
  4356. " <td>5.03836</td>\n",
  4357. " <td>1193.015747</td>\n",
  4358. " </tr>\n",
  4359. " </tbody>\n",
  4360. "</table>\n",
  4361. "</div>"
  4362. ],
  4363. "text/plain": [
  4364. " spend_prop cpt\n",
  4365. "Billing Event Ad Type Audience Types - \n",
  4366. "Impressions Carousel Custom - 5.03836 1193.015747"
  4367. ]
  4368. },
  4369. "metadata": {},
  4370. "output_type": "display_data"
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  4372. {
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  4379. " <th></th>\n",
  4380. " <th></th>\n",
  4381. " <th></th>\n",
  4382. " <th></th>\n",
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  4385. " </tr>\n",
  4386. " <tr>\n",
  4387. " <th>Billing Event</th>\n",
  4388. " <th>Ad Type</th>\n",
  4389. " <th>Publisher Platforms</th>\n",
  4390. " <th>Landing Pages</th>\n",
  4391. " <th></th>\n",
  4392. " <th></th>\n",
  4393. " </tr>\n",
  4394. " </thead>\n",
  4395. " <tbody>\n",
  4396. " <tr>\n",
  4397. " <th>Impressions</th>\n",
  4398. " <th>Carousel</th>\n",
  4399. " <th>audience_network or facebook</th>\n",
  4400. " <th>www.koovs.com/women/tags/half-way-there</th>\n",
  4401. " <td>2.524207</td>\n",
  4402. " <td>836.021013</td>\n",
  4403. " </tr>\n",
  4404. " </tbody>\n",
  4405. "</table>\n",
  4406. "</div>"
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  4408. "text/plain": [
  4409. " spend_prop \\\n",
  4410. "Billing Event Ad Type Publisher Platforms Landing Pages \n",
  4411. "Impressions Carousel audience_network or facebook www.koovs.com/women/tags/half-way-there 2.524207 \n",
  4412. "\n",
  4413. " cpt \n",
  4414. "Billing Event Ad Type Publisher Platforms Landing Pages \n",
  4415. "Impressions Carousel audience_network or facebook www.koovs.com/women/tags/half-way-there 836.021013 "
  4416. ]
  4417. },
  4418. "metadata": {},
  4419. "output_type": "display_data"
  4420. },
  4421. {
  4422. "data": {
  4423. "text/html": [
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  4428. " <th></th>\n",
  4429. " <th></th>\n",
  4430. " <th></th>\n",
  4431. " <th></th>\n",
  4432. " <th>spend_prop</th>\n",
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  4434. " </tr>\n",
  4435. " <tr>\n",
  4436. " <th>Billing Event</th>\n",
  4437. " <th>Device Platforms</th>\n",
  4438. " <th>Publisher Platforms</th>\n",
  4439. " <th>Landing Pages</th>\n",
  4440. " <th></th>\n",
  4441. " <th></th>\n",
  4442. " </tr>\n",
  4443. " </thead>\n",
  4444. " <tbody>\n",
  4445. " <tr>\n",
  4446. " <th>Link_clicks</th>\n",
  4447. " <th>desktop or mobile</th>\n",
  4448. " <th>audience_network or facebook</th>\n",
  4449. " <th>koovs.com</th>\n",
  4450. " <td>6.417334</td>\n",
  4451. " <td>596.479503</td>\n",
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  4453. " </tbody>\n",
  4454. "</table>\n",
  4455. "</div>"
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  4457. "text/plain": [
  4458. " spend_prop \\\n",
  4459. "Billing Event Device Platforms Publisher Platforms Landing Pages \n",
  4460. "Link_clicks desktop or mobile audience_network or facebook koovs.com 6.417334 \n",
  4461. "\n",
  4462. " cpt \n",
  4463. "Billing Event Device Platforms Publisher Platforms Landing Pages \n",
  4464. "Link_clicks desktop or mobile audience_network or facebook koovs.com 596.479503 "
  4465. ]
  4466. },
  4467. "metadata": {},
  4468. "output_type": "display_data"
  4469. },
  4470. {
  4471. "data": {
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  4475. " <thead>\n",
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  4477. " <th></th>\n",
  4478. " <th></th>\n",
  4479. " <th></th>\n",
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  4483. " </tr>\n",
  4484. " <tr>\n",
  4485. " <th>Billing Event</th>\n",
  4486. " <th>Gender</th>\n",
  4487. " <th>Facebook Positions</th>\n",
  4488. " <th>Custom Audiences</th>\n",
  4489. " <th></th>\n",
  4490. " <th></th>\n",
  4491. " </tr>\n",
  4492. " </thead>\n",
  4493. " <tbody>\n",
  4494. " <tr>\n",
  4495. " <th>Impressions</th>\n",
  4496. " <th>Female</th>\n",
  4497. " <th>feed or right_hand_column</th>\n",
  4498. " <th>ECOMMERCE MOBILE & EMAIL IDS FEB 2017</th>\n",
  4499. " <td>3.595755</td>\n",
  4500. " <td>1213.969355</td>\n",
  4501. " </tr>\n",
  4502. " </tbody>\n",
  4503. "</table>\n",
  4504. "</div>"
  4505. ],
  4506. "text/plain": [
  4507. " spend_prop \\\n",
  4508. "Billing Event Gender Facebook Positions Custom Audiences \n",
  4509. "Impressions Female feed or right_hand_column ECOMMERCE MOBILE & EMAIL IDS FEB 2017 3.595755 \n",
  4510. "\n",
  4511. " cpt \n",
  4512. "Billing Event Gender Facebook Positions Custom Audiences \n",
  4513. "Impressions Female feed or right_hand_column ECOMMERCE MOBILE & EMAIL IDS FEB 2017 1213.969355 "
  4514. ]
  4515. },
  4516. "metadata": {},
  4517. "output_type": "display_data"
  4518. },
  4519. {
  4520. "data": {
  4521. "text/html": [
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  4523. "<table border=\"1\" class=\"dataframe\">\n",
  4524. " <thead>\n",
  4525. " <tr style=\"text-align: right;\">\n",
  4526. " <th></th>\n",
  4527. " <th></th>\n",
  4528. " <th></th>\n",
  4529. " <th></th>\n",
  4530. " <th>spend_prop</th>\n",
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  4532. " </tr>\n",
  4533. " <tr>\n",
  4534. " <th>Billing Event</th>\n",
  4535. " <th>Gender</th>\n",
  4536. " <th>Audience Types</th>\n",
  4537. " <th>-</th>\n",
  4538. " <th></th>\n",
  4539. " <th></th>\n",
  4540. " </tr>\n",
  4541. " </thead>\n",
  4542. " <tbody>\n",
  4543. " <tr>\n",
  4544. " <th>Impressions</th>\n",
  4545. " <th>Female</th>\n",
  4546. " <th>Lookalike</th>\n",
  4547. " <th>-</th>\n",
  4548. " <td>9.766021</td>\n",
  4549. " <td>1066.918935</td>\n",
  4550. " </tr>\n",
  4551. " </tbody>\n",
  4552. "</table>\n",
  4553. "</div>"
  4554. ],
  4555. "text/plain": [
  4556. " spend_prop cpt\n",
  4557. "Billing Event Gender Audience Types - \n",
  4558. "Impressions Female Lookalike - 9.766021 1066.918935"
  4559. ]
  4560. },
  4561. "metadata": {},
  4562. "output_type": "display_data"
  4563. },
  4564. {
  4565. "data": {
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  4569. " <thead>\n",
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  4571. " <th></th>\n",
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  4578. " <tr>\n",
  4579. " <th>Billing Event</th>\n",
  4580. " <th>Ad Format</th>\n",
  4581. " <th>Publisher Platforms</th>\n",
  4582. " <th>Age Range</th>\n",
  4583. " <th></th>\n",
  4584. " <th></th>\n",
  4585. " </tr>\n",
  4586. " </thead>\n",
  4587. " <tbody>\n",
  4588. " <tr>\n",
  4589. " <th>Impressions</th>\n",
  4590. " <th>Image</th>\n",
  4591. " <th>audience_network or facebook</th>\n",
  4592. " <th>18-65</th>\n",
  4593. " <td>5.230758</td>\n",
  4594. " <td>1174.783948</td>\n",
  4595. " </tr>\n",
  4596. " </tbody>\n",
  4597. "</table>\n",
  4598. "</div>"
  4599. ],
  4600. "text/plain": [
  4601. " spend_prop \\\n",
  4602. "Billing Event Ad Format Publisher Platforms Age Range \n",
  4603. "Impressions Image audience_network or facebook 18-65 5.230758 \n",
  4604. "\n",
  4605. " cpt \n",
  4606. "Billing Event Ad Format Publisher Platforms Age Range \n",
  4607. "Impressions Image audience_network or facebook 18-65 1174.783948 "
  4608. ]
  4609. },
  4610. "metadata": {},
  4611. "output_type": "display_data"
  4612. },
  4613. {
  4614. "data": {
  4615. "text/html": [
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  4618. " <thead>\n",
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  4620. " <th></th>\n",
  4621. " <th></th>\n",
  4622. " <th></th>\n",
  4623. " <th></th>\n",
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  4625. " <th>cpt</th>\n",
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  4627. " <tr>\n",
  4628. " <th>Billing Event</th>\n",
  4629. " <th>Device Platforms</th>\n",
  4630. " <th>Facebook Positions</th>\n",
  4631. " <th>Landing Pages</th>\n",
  4632. " <th></th>\n",
  4633. " <th></th>\n",
  4634. " </tr>\n",
  4635. " </thead>\n",
  4636. " <tbody>\n",
  4637. " <tr>\n",
  4638. " <th>Impressions</th>\n",
  4639. " <th>desktop or mobile</th>\n",
  4640. " <th>feed or right_hand_column</th>\n",
  4641. " <th>koovs.com</th>\n",
  4642. " <td>6.354514</td>\n",
  4643. " <td>678.633878</td>\n",
  4644. " </tr>\n",
  4645. " </tbody>\n",
  4646. "</table>\n",
  4647. "</div>"
  4648. ],
  4649. "text/plain": [
  4650. " spend_prop \\\n",
  4651. "Billing Event Device Platforms Facebook Positions Landing Pages \n",
  4652. "Impressions desktop or mobile feed or right_hand_column koovs.com 6.354514 \n",
  4653. "\n",
  4654. " cpt \n",
  4655. "Billing Event Device Platforms Facebook Positions Landing Pages \n",
  4656. "Impressions desktop or mobile feed or right_hand_column koovs.com 678.633878 "
  4657. ]
  4658. },
  4659. "metadata": {},
  4660. "output_type": "display_data"
  4661. },
  4662. {
  4663. "data": {
  4664. "text/html": [
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  4666. "<table border=\"1\" class=\"dataframe\">\n",
  4667. " <thead>\n",
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  4669. " <th></th>\n",
  4670. " <th></th>\n",
  4671. " <th></th>\n",
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  4676. " <tr>\n",
  4677. " <th>Billing Event</th>\n",
  4678. " <th>Device Platforms</th>\n",
  4679. " <th>Locations</th>\n",
  4680. " <th>Age Range</th>\n",
  4681. " <th></th>\n",
  4682. " <th></th>\n",
  4683. " </tr>\n",
  4684. " </thead>\n",
  4685. " <tbody>\n",
  4686. " <tr>\n",
  4687. " <th>Impressions</th>\n",
  4688. " <th>desktop or mobile</th>\n",
  4689. " <th>IN</th>\n",
  4690. " <th>18-65</th>\n",
  4691. " <td>11.585272</td>\n",
  4692. " <td>838.527331</td>\n",
  4693. " </tr>\n",
  4694. " </tbody>\n",
  4695. "</table>\n",
  4696. "</div>"
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  4698. "text/plain": [
  4699. " spend_prop cpt\n",
  4700. "Billing Event Device Platforms Locations Age Range \n",
  4701. "Impressions desktop or mobile IN 18-65 11.585272 838.527331"
  4702. ]
  4703. },
  4704. "metadata": {},
  4705. "output_type": "display_data"
  4706. },
  4707. {
  4708. "data": {
  4709. "text/html": [
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  4711. "<table border=\"1\" class=\"dataframe\">\n",
  4712. " <thead>\n",
  4713. " <tr style=\"text-align: right;\">\n",
  4714. " <th></th>\n",
  4715. " <th></th>\n",
  4716. " <th></th>\n",
  4717. " <th></th>\n",
  4718. " <th>spend_prop</th>\n",
  4719. " <th>cpt</th>\n",
  4720. " </tr>\n",
  4721. " <tr>\n",
  4722. " <th>Billing Event</th>\n",
  4723. " <th>Audience Strategy</th>\n",
  4724. " <th>Locations</th>\n",
  4725. " <th>Lookalike Types</th>\n",
  4726. " <th></th>\n",
  4727. " <th></th>\n",
  4728. " </tr>\n",
  4729. " </thead>\n",
  4730. " <tbody>\n",
  4731. " <tr>\n",
  4732. " <th>Impressions</th>\n",
  4733. " <th>Prospecting</th>\n",
  4734. " <th>IN</th>\n",
  4735. " <th>1%</th>\n",
  4736. " <td>14.422285</td>\n",
  4737. " <td>1173.741291</td>\n",
  4738. " </tr>\n",
  4739. " </tbody>\n",
  4740. "</table>\n",
  4741. "</div>"
  4742. ],
  4743. "text/plain": [
  4744. " spend_prop \\\n",
  4745. "Billing Event Audience Strategy Locations Lookalike Types \n",
  4746. "Impressions Prospecting IN 1% 14.422285 \n",
  4747. "\n",
  4748. " cpt \n",
  4749. "Billing Event Audience Strategy Locations Lookalike Types \n",
  4750. "Impressions Prospecting IN 1% 1173.741291 "
  4751. ]
  4752. },
  4753. "metadata": {},
  4754. "output_type": "display_data"
  4755. },
  4756. {
  4757. "data": {
  4758. "text/html": [
  4759. "<div>\n",
  4760. "<table border=\"1\" class=\"dataframe\">\n",
  4761. " <thead>\n",
  4762. " <tr style=\"text-align: right;\">\n",
  4763. " <th></th>\n",
  4764. " <th></th>\n",
  4765. " <th></th>\n",
  4766. " <th></th>\n",
  4767. " <th>spend_prop</th>\n",
  4768. " <th>cpt</th>\n",
  4769. " </tr>\n",
  4770. " <tr>\n",
  4771. " <th>Billing Event</th>\n",
  4772. " <th>Audience Strategy</th>\n",
  4773. " <th>Audience Types</th>\n",
  4774. " <th>-</th>\n",
  4775. " <th></th>\n",
  4776. " <th></th>\n",
  4777. " </tr>\n",
  4778. " </thead>\n",
  4779. " <tbody>\n",
  4780. " <tr>\n",
  4781. " <th>Impressions</th>\n",
  4782. " <th>Prospecting</th>\n",
  4783. " <th>Lookalike</th>\n",
  4784. " <th>-</th>\n",
  4785. " <td>16.463493</td>\n",
  4786. " <td>1208.319369</td>\n",
  4787. " </tr>\n",
  4788. " </tbody>\n",
  4789. "</table>\n",
  4790. "</div>"
  4791. ],
  4792. "text/plain": [
  4793. " spend_prop cpt\n",
  4794. "Billing Event Audience Strategy Audience Types - \n",
  4795. "Impressions Prospecting Lookalike - 16.463493 1208.319369"
  4796. ]
  4797. },
  4798. "metadata": {},
  4799. "output_type": "display_data"
  4800. },
  4801. {
  4802. "data": {
  4803. "text/html": [
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  4805. "<table border=\"1\" class=\"dataframe\">\n",
  4806. " <thead>\n",
  4807. " <tr style=\"text-align: right;\">\n",
  4808. " <th></th>\n",
  4809. " <th></th>\n",
  4810. " <th></th>\n",
  4811. " <th></th>\n",
  4812. " <th>spend_prop</th>\n",
  4813. " <th>cpt</th>\n",
  4814. " </tr>\n",
  4815. " <tr>\n",
  4816. " <th>Billing Event</th>\n",
  4817. " <th>Campaign Objective</th>\n",
  4818. " <th>Publisher Platforms</th>\n",
  4819. " <th>Custom Audiences</th>\n",
  4820. " <th></th>\n",
  4821. " <th></th>\n",
  4822. " </tr>\n",
  4823. " </thead>\n",
  4824. " <tbody>\n",
  4825. " <tr>\n",
  4826. " <th>Impressions</th>\n",
  4827. " <th>Conversions</th>\n",
  4828. " <th>audience_network or facebook</th>\n",
  4829. " <th>ECOMMERCE MOBILE & EMAIL IDS FEB 2017</th>\n",
  4830. " <td>5.03836</td>\n",
  4831. " <td>1193.015747</td>\n",
  4832. " </tr>\n",
  4833. " </tbody>\n",
  4834. "</table>\n",
  4835. "</div>"
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  4837. "text/plain": [
  4838. " spend_prop \\\n",
  4839. "Billing Event Campaign Objective Publisher Platforms Custom Audiences \n",
  4840. "Impressions Conversions audience_network or facebook ECOMMERCE MOBILE & EMAIL IDS FEB 2017 5.03836 \n",
  4841. "\n",
  4842. " cpt \n",
  4843. "Billing Event Campaign Objective Publisher Platforms Custom Audiences \n",
  4844. "Impressions Conversions audience_network or facebook ECOMMERCE MOBILE & EMAIL IDS FEB 2017 1193.015747 "
  4845. ]
  4846. },
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  4864. " <tr>\n",
  4865. " <th>Billing Event</th>\n",
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  4875. " <th>Impressions</th>\n",
  4876. " <th>Carousel</th>\n",
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  4879. " <td>5.03836</td>\n",
  4880. " <td>1193.015747</td>\n",
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  4888. "Billing Event Ad Type Publisher Platforms Custom Audiences \n",
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  4890. "\n",
  4891. " cpt \n",
  4892. "Billing Event Ad Type Publisher Platforms Custom Audiences \n",
  4893. "Impressions Carousel audience_network or facebook ECOMMERCE MOBILE & EMAIL IDS FEB 2017 1193.015747 "
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  4914. " <th>Billing Event</th>\n",
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  4924. " <th>Impressions</th>\n",
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  4927. " <th>www.koovs.com/women/tags/half-way-there</th>\n",
  4928. " <td>2.524207</td>\n",
  4929. " <td>836.021013</td>\n",
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  4937. "Billing Event Campaign Objective Publisher Platforms Landing Pages \n",
  4938. "Impressions Conversions audience_network or facebook www.koovs.com/women/tags/half-way-there 2.524207 \n",
  4939. "\n",
  4940. " cpt \n",
  4941. "Billing Event Campaign Objective Publisher Platforms Landing Pages \n",
  4942. "Impressions Conversions audience_network or facebook www.koovs.com/women/tags/half-way-there 836.021013 "
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  4964. " <th>Device Platforms</th>\n",
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  4967. " <th></th>\n",
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  4972. " <tr>\n",
  4973. " <th>Impressions</th>\n",
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  4975. " <th>audience_network or facebook</th>\n",
  4976. " <th>18-65</th>\n",
  4977. " <td>5.230758</td>\n",
  4978. " <td>1174.783948</td>\n",
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  4980. " <tr>\n",
  4981. " <th>Link_clicks</th>\n",
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  4983. " <th>audience_network or facebook</th>\n",
  4984. " <th>18-65</th>\n",
  4985. " <td>8.572545</td>\n",
  4986. " <td>607.036265</td>\n",
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  4988. " </tbody>\n",
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  4992. "text/plain": [
  4993. " spend_prop \\\n",
  4994. "Billing Event Device Platforms Publisher Platforms Age Range \n",
  4995. "Impressions desktop or mobile audience_network or facebook 18-65 5.230758 \n",
  4996. "Link_clicks desktop or mobile audience_network or facebook 18-65 8.572545 \n",
  4997. "\n",
  4998. " cpt \n",
  4999. "Billing Event Device Platforms Publisher Platforms Age Range \n",
  5000. "Impressions desktop or mobile audience_network or facebook 18-65 1174.783948 \n",
  5001. "Link_clicks desktop or mobile audience_network or facebook 18-65 607.036265 "
  5002. ]
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  5014. " <th></th>\n",
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  5016. " <th></th>\n",
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  5019. " <th>cpt</th>\n",
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  5021. " <tr>\n",
  5022. " <th>Billing Event</th>\n",
  5023. " <th>Gender</th>\n",
  5024. " <th>Publisher Platforms</th>\n",
  5025. " <th>-</th>\n",
  5026. " <th></th>\n",
  5027. " <th></th>\n",
  5028. " </tr>\n",
  5029. " </thead>\n",
  5030. " <tbody>\n",
  5031. " <tr>\n",
  5032. " <th>Impressions</th>\n",
  5033. " <th>Female</th>\n",
  5034. " <th>facebook</th>\n",
  5035. " <th>-</th>\n",
  5036. " <td>4.942352</td>\n",
  5037. " <td>975.971396</td>\n",
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  5039. " </tbody>\n",
  5040. "</table>\n",
  5041. "</div>"
  5042. ],
  5043. "text/plain": [
  5044. " spend_prop cpt\n",
  5045. "Billing Event Gender Publisher Platforms - \n",
  5046. "Impressions Female facebook - 4.942352 975.971396"
  5047. ]
  5048. },
  5049. "metadata": {},
  5050. "output_type": "display_data"
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  5059. " <th></th>\n",
  5060. " <th></th>\n",
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  5067. " <th>Billing Event</th>\n",
  5068. " <th>Audience Strategy</th>\n",
  5069. " <th>Locations</th>\n",
  5070. " <th>Custom Audiences</th>\n",
  5071. " <th></th>\n",
  5072. " <th></th>\n",
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  5074. " </thead>\n",
  5075. " <tbody>\n",
  5076. " <tr>\n",
  5077. " <th>Impressions</th>\n",
  5078. " <th>Prospecting</th>\n",
  5079. " <th>IN</th>\n",
  5080. " <th>Lookalike (IN, 1%) - loyal_purchasers_data_20160415</th>\n",
  5081. " <td>13.68701</td>\n",
  5082. " <td>1170.324902</td>\n",
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  5085. "</table>\n",
  5086. "</div>"
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  5088. "text/plain": [
  5089. " spend_prop \\\n",
  5090. "Billing Event Audience Strategy Locations Custom Audiences \n",
  5091. "Impressions Prospecting IN Lookalike (IN, 1%) - loyal_purchasers_data_2016... 13.68701 \n",
  5092. "\n",
  5093. " cpt \n",
  5094. "Billing Event Audience Strategy Locations Custom Audiences \n",
  5095. "Impressions Prospecting IN Lookalike (IN, 1%) - loyal_purchasers_data_2016... 1170.324902 "
  5096. ]
  5097. },
  5098. "metadata": {},
  5099. "output_type": "display_data"
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  5101. {
  5102. "data": {
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  5108. " <th></th>\n",
  5109. " <th></th>\n",
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  5115. " <tr>\n",
  5116. " <th>Billing Event</th>\n",
  5117. " <th>Campaign Objective</th>\n",
  5118. " <th>Audience Types</th>\n",
  5119. " <th>-</th>\n",
  5120. " <th></th>\n",
  5121. " <th></th>\n",
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  5123. " </thead>\n",
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  5125. " <tr>\n",
  5126. " <th>Impressions</th>\n",
  5127. " <th>Conversions</th>\n",
  5128. " <th>Custom</th>\n",
  5129. " <th>-</th>\n",
  5130. " <td>5.03836</td>\n",
  5131. " <td>1193.015747</td>\n",
  5132. " </tr>\n",
  5133. " </tbody>\n",
  5134. "</table>\n",
  5135. "</div>"
  5136. ],
  5137. "text/plain": [
  5138. " spend_prop cpt\n",
  5139. "Billing Event Campaign Objective Audience Types - \n",
  5140. "Impressions Conversions Custom - 5.03836 1193.015747"
  5141. ]
  5142. },
  5143. "metadata": {},
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  5153. " <th></th>\n",
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  5160. " <tr>\n",
  5161. " <th>Billing Event</th>\n",
  5162. " <th>Ad Format</th>\n",
  5163. " <th>Audience Types</th>\n",
  5164. " <th>-</th>\n",
  5165. " <th></th>\n",
  5166. " <th></th>\n",
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  5169. " <tbody>\n",
  5170. " <tr>\n",
  5171. " <th>Impressions</th>\n",
  5172. " <th>Image</th>\n",
  5173. " <th>Custom</th>\n",
  5174. " <th>-</th>\n",
  5175. " <td>5.03836</td>\n",
  5176. " <td>1193.015747</td>\n",
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  5178. " </tbody>\n",
  5179. "</table>\n",
  5180. "</div>"
  5181. ],
  5182. "text/plain": [
  5183. " spend_prop cpt\n",
  5184. "Billing Event Ad Format Audience Types - \n",
  5185. "Impressions Image Custom - 5.03836 1193.015747"
  5186. ]
  5187. },
  5188. "metadata": {},
  5189. "output_type": "display_data"
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  5191. {
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  5198. " <th></th>\n",
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  5205. " <tr>\n",
  5206. " <th>Billing Event</th>\n",
  5207. " <th>Gender</th>\n",
  5208. " <th>Facebook Positions</th>\n",
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  5210. " <th></th>\n",
  5211. " <th></th>\n",
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  5213. " </thead>\n",
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  5216. " <th>Impressions</th>\n",
  5217. " <th>Female</th>\n",
  5218. " <th>feed or right_hand_column</th>\n",
  5219. " <th>18-65</th>\n",
  5220. " <td>3.595755</td>\n",
  5221. " <td>1213.969355</td>\n",
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  5223. " </tbody>\n",
  5224. "</table>\n",
  5225. "</div>"
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  5227. "text/plain": [
  5228. " spend_prop \\\n",
  5229. "Billing Event Gender Facebook Positions Age Range \n",
  5230. "Impressions Female feed or right_hand_column 18-65 3.595755 \n",
  5231. "\n",
  5232. " cpt \n",
  5233. "Billing Event Gender Facebook Positions Age Range \n",
  5234. "Impressions Female feed or right_hand_column 18-65 1213.969355 "
  5235. ]
  5236. },
  5237. "metadata": {},
  5238. "output_type": "display_data"
  5239. },
  5240. {
  5241. "data": {
  5242. "text/html": [
  5243. "<div>\n",
  5244. "<table border=\"1\" class=\"dataframe\">\n",
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  5247. " <th></th>\n",
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  5254. " <tr>\n",
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  5259. " <th></th>\n",
  5260. " <th></th>\n",
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  5262. " </thead>\n",
  5263. " <tbody>\n",
  5264. " <tr>\n",
  5265. " <th>Impressions</th>\n",
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  5267. " <th>IN</th>\n",
  5268. " <th>Lookalike (IN, 1%) - loyal_purchasers_data_20160415</th>\n",
  5269. " <td>9.745652</td>\n",
  5270. " <td>1073.659579</td>\n",
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  5276. "text/plain": [
  5277. " spend_prop \\\n",
  5278. "Billing Event Gender Locations Custom Audiences \n",
  5279. "Impressions Female IN Lookalike (IN, 1%) - loyal_purchasers_data_2016... 9.745652 \n",
  5280. "\n",
  5281. " cpt \n",
  5282. "Billing Event Gender Locations Custom Audiences \n",
  5283. "Impressions Female IN Lookalike (IN, 1%) - loyal_purchasers_data_2016... 1073.659579 "
  5284. ]
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  5286. "metadata": {},
  5287. "output_type": "display_data"
  5288. },
  5289. {
  5290. "data": {
  5291. "text/html": [
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  5296. " <th></th>\n",
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  5303. " <tr>\n",
  5304. " <th>Billing Event</th>\n",
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  5308. " <th></th>\n",
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  5312. " <tbody>\n",
  5313. " <tr>\n",
  5314. " <th>Impressions</th>\n",
  5315. " <th>Image</th>\n",
  5316. " <th>IN</th>\n",
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  5318. " <td>3.041823</td>\n",
  5319. " <td>776.478439</td>\n",
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  5321. " </tbody>\n",
  5322. "</table>\n",
  5323. "</div>"
  5324. ],
  5325. "text/plain": [
  5326. " spend_prop \\\n",
  5327. "Billing Event Ad Format Locations Landing Pages \n",
  5328. "Impressions Image IN www.koovs.com/women/tags/half-way-there 3.041823 \n",
  5329. "\n",
  5330. " cpt \n",
  5331. "Billing Event Ad Format Locations Landing Pages \n",
  5332. "Impressions Image IN www.koovs.com/women/tags/half-way-there 776.478439 "
  5333. ]
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  5335. "metadata": {},
  5336. "output_type": "display_data"
  5337. },
  5338. {
  5339. "data": {
  5340. "text/html": [
  5341. "<div>\n",
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  5345. " <th></th>\n",
  5346. " <th></th>\n",
  5347. " <th></th>\n",
  5348. " <th></th>\n",
  5349. " <th>spend_prop</th>\n",
  5350. " <th>cpt</th>\n",
  5351. " </tr>\n",
  5352. " <tr>\n",
  5353. " <th>Billing Event</th>\n",
  5354. " <th>Audience Strategy</th>\n",
  5355. " <th>Locations</th>\n",
  5356. " <th>Landing Pages</th>\n",
  5357. " <th></th>\n",
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  5361. " <tbody>\n",
  5362. " <tr>\n",
  5363. " <th>Impressions</th>\n",
  5364. " <th>Prospecting</th>\n",
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  5366. " <th>www.koovs.com/women/tags/half-way-there</th>\n",
  5367. " <td>2.809439</td>\n",
  5368. " <td>794.688811</td>\n",
  5369. " </tr>\n",
  5370. " </tbody>\n",
  5371. "</table>\n",
  5372. "</div>"
  5373. ],
  5374. "text/plain": [
  5375. " spend_prop \\\n",
  5376. "Billing Event Audience Strategy Locations Landing Pages \n",
  5377. "Impressions Prospecting IN www.koovs.com/women/tags/half-way-there 2.809439 \n",
  5378. "\n",
  5379. " cpt \n",
  5380. "Billing Event Audience Strategy Locations Landing Pages \n",
  5381. "Impressions Prospecting IN www.koovs.com/women/tags/half-way-there 794.688811 "
  5382. ]
  5383. },
  5384. "metadata": {},
  5385. "output_type": "display_data"
  5386. },
  5387. {
  5388. "data": {
  5389. "text/html": [
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  5392. " <thead>\n",
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  5394. " <th></th>\n",
  5395. " <th></th>\n",
  5396. " <th></th>\n",
  5397. " <th></th>\n",
  5398. " <th>spend_prop</th>\n",
  5399. " <th>cpt</th>\n",
  5400. " </tr>\n",
  5401. " <tr>\n",
  5402. " <th>Billing Event</th>\n",
  5403. " <th>Gender</th>\n",
  5404. " <th>Publisher Platforms</th>\n",
  5405. " <th>Custom Audiences</th>\n",
  5406. " <th></th>\n",
  5407. " <th></th>\n",
  5408. " </tr>\n",
  5409. " </thead>\n",
  5410. " <tbody>\n",
  5411. " <tr>\n",
  5412. " <th>Impressions</th>\n",
  5413. " <th>Female</th>\n",
  5414. " <th>audience_network or facebook</th>\n",
  5415. " <th>ECOMMERCE MOBILE & EMAIL IDS FEB 2017</th>\n",
  5416. " <td>3.595755</td>\n",
  5417. " <td>1213.969355</td>\n",
  5418. " </tr>\n",
  5419. " </tbody>\n",
  5420. "</table>\n",
  5421. "</div>"
  5422. ],
  5423. "text/plain": [
  5424. " spend_prop \\\n",
  5425. "Billing Event Gender Publisher Platforms Custom Audiences \n",
  5426. "Impressions Female audience_network or facebook ECOMMERCE MOBILE & EMAIL IDS FEB 2017 3.595755 \n",
  5427. "\n",
  5428. " cpt \n",
  5429. "Billing Event Gender Publisher Platforms Custom Audiences \n",
  5430. "Impressions Female audience_network or facebook ECOMMERCE MOBILE & EMAIL IDS FEB 2017 1213.969355 "
  5431. ]
  5432. },
  5433. "metadata": {},
  5434. "output_type": "display_data"
  5435. },
  5436. {
  5437. "data": {
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  5451. " <th>Billing Event</th>\n",
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  5455. " <th></th>\n",
  5456. " <th></th>\n",
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  5459. " <tbody>\n",
  5460. " <tr>\n",
  5461. " <th>Impressions</th>\n",
  5462. " <th>Female</th>\n",
  5463. " <th>IN</th>\n",
  5464. " <th>www.koovs.com/women/tags/half-way-there</th>\n",
  5465. " <td>3.041823</td>\n",
  5466. " <td>776.478439</td>\n",
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  5468. " </tbody>\n",
  5469. "</table>\n",
  5470. "</div>"
  5471. ],
  5472. "text/plain": [
  5473. " spend_prop \\\n",
  5474. "Billing Event Gender Locations Landing Pages \n",
  5475. "Impressions Female IN www.koovs.com/women/tags/half-way-there 3.041823 \n",
  5476. "\n",
  5477. " cpt \n",
  5478. "Billing Event Gender Locations Landing Pages \n",
  5479. "Impressions Female IN www.koovs.com/women/tags/half-way-there 776.478439 "
  5480. ]
  5481. },
  5482. "metadata": {},
  5483. "output_type": "display_data"
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  5485. {
  5486. "data": {
  5487. "text/html": [
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  5492. " <th></th>\n",
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  5499. " <tr>\n",
  5500. " <th>Billing Event</th>\n",
  5501. " <th>Gender</th>\n",
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  5504. " <th></th>\n",
  5505. " <th></th>\n",
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  5509. " <tr>\n",
  5510. " <th>Impressions</th>\n",
  5511. " <th>Female</th>\n",
  5512. " <th>audience_network or facebook</th>\n",
  5513. " <th>www.koovs.com/women/tags/half-way-there</th>\n",
  5514. " <td>2.524207</td>\n",
  5515. " <td>836.021013</td>\n",
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  5517. " </tbody>\n",
  5518. "</table>\n",
  5519. "</div>"
  5520. ],
  5521. "text/plain": [
  5522. " spend_prop \\\n",
  5523. "Billing Event Gender Publisher Platforms Landing Pages \n",
  5524. "Impressions Female audience_network or facebook www.koovs.com/women/tags/half-way-there 2.524207 \n",
  5525. "\n",
  5526. " cpt \n",
  5527. "Billing Event Gender Publisher Platforms Landing Pages \n",
  5528. "Impressions Female audience_network or facebook www.koovs.com/women/tags/half-way-there 836.021013 "
  5529. ]
  5530. },
  5531. "metadata": {},
  5532. "output_type": "display_data"
  5533. },
  5534. {
  5535. "data": {
  5536. "text/html": [
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  5541. " <th></th>\n",
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  5545. " <th>spend_prop</th>\n",
  5546. " <th>cpt</th>\n",
  5547. " </tr>\n",
  5548. " <tr>\n",
  5549. " <th>Billing Event</th>\n",
  5550. " <th>Ad Type</th>\n",
  5551. " <th>Locations</th>\n",
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  5553. " <th></th>\n",
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  5556. " </thead>\n",
  5557. " <tbody>\n",
  5558. " <tr>\n",
  5559. " <th>Impressions</th>\n",
  5560. " <th>Carousel</th>\n",
  5561. " <th>IN</th>\n",
  5562. " <th>www.koovs.com/women/tags/half-way-there</th>\n",
  5563. " <td>3.041823</td>\n",
  5564. " <td>776.478439</td>\n",
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  5567. "</table>\n",
  5568. "</div>"
  5569. ],
  5570. "text/plain": [
  5571. " spend_prop \\\n",
  5572. "Billing Event Ad Type Locations Landing Pages \n",
  5573. "Impressions Carousel IN www.koovs.com/women/tags/half-way-there 3.041823 \n",
  5574. "\n",
  5575. " cpt \n",
  5576. "Billing Event Ad Type Locations Landing Pages \n",
  5577. "Impressions Carousel IN www.koovs.com/women/tags/half-way-there 776.478439 "
  5578. ]
  5579. },
  5580. "metadata": {},
  5581. "output_type": "display_data"
  5582. },
  5583. {
  5584. "data": {
  5585. "text/html": [
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  5590. " <th></th>\n",
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  5592. " <th></th>\n",
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  5594. " <th>spend_prop</th>\n",
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  5596. " </tr>\n",
  5597. " <tr>\n",
  5598. " <th>Billing Event</th>\n",
  5599. " <th>Campaign Objective</th>\n",
  5600. " <th>Locations</th>\n",
  5601. " <th>Landing Pages</th>\n",
  5602. " <th></th>\n",
  5603. " <th></th>\n",
  5604. " </tr>\n",
  5605. " </thead>\n",
  5606. " <tbody>\n",
  5607. " <tr>\n",
  5608. " <th>Impressions</th>\n",
  5609. " <th>Conversions</th>\n",
  5610. " <th>IN</th>\n",
  5611. " <th>www.koovs.com/women/tags/half-way-there</th>\n",
  5612. " <td>3.041823</td>\n",
  5613. " <td>776.478439</td>\n",
  5614. " </tr>\n",
  5615. " </tbody>\n",
  5616. "</table>\n",
  5617. "</div>"
  5618. ],
  5619. "text/plain": [
  5620. " spend_prop \\\n",
  5621. "Billing Event Campaign Objective Locations Landing Pages \n",
  5622. "Impressions Conversions IN www.koovs.com/women/tags/half-way-there 3.041823 \n",
  5623. "\n",
  5624. " cpt \n",
  5625. "Billing Event Campaign Objective Locations Landing Pages \n",
  5626. "Impressions Conversions IN www.koovs.com/women/tags/half-way-there 776.478439 "
  5627. ]
  5628. },
  5629. "metadata": {},
  5630. "output_type": "display_data"
  5631. },
  5632. {
  5633. "data": {
  5634. "text/html": [
  5635. "<div>\n",
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  5639. " <th></th>\n",
  5640. " <th></th>\n",
  5641. " <th></th>\n",
  5642. " <th></th>\n",
  5643. " <th>spend_prop</th>\n",
  5644. " <th>cpt</th>\n",
  5645. " </tr>\n",
  5646. " <tr>\n",
  5647. " <th>Billing Event</th>\n",
  5648. " <th>Device Platforms</th>\n",
  5649. " <th>Publisher Platforms</th>\n",
  5650. " <th>-</th>\n",
  5651. " <th></th>\n",
  5652. " <th></th>\n",
  5653. " </tr>\n",
  5654. " </thead>\n",
  5655. " <tbody>\n",
  5656. " <tr>\n",
  5657. " <th>Impressions</th>\n",
  5658. " <th>desktop or mobile</th>\n",
  5659. " <th>audience_network or facebook or instagram</th>\n",
  5660. " <th>-</th>\n",
  5661. " <td>7.19356</td>\n",
  5662. " <td>742.480769</td>\n",
  5663. " </tr>\n",
  5664. " </tbody>\n",
  5665. "</table>\n",
  5666. "</div>"
  5667. ],
  5668. "text/plain": [
  5669. " spend_prop \\\n",
  5670. "Billing Event Device Platforms Publisher Platforms - \n",
  5671. "Impressions desktop or mobile audience_network or facebook or instagram - 7.19356 \n",
  5672. "\n",
  5673. " cpt \n",
  5674. "Billing Event Device Platforms Publisher Platforms - \n",
  5675. "Impressions desktop or mobile audience_network or facebook or instagram - 742.480769 "
  5676. ]
  5677. },
  5678. "metadata": {},
  5679. "output_type": "display_data"
  5680. },
  5681. {
  5682. "data": {
  5683. "text/html": [
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  5688. " <th></th>\n",
  5689. " <th></th>\n",
  5690. " <th></th>\n",
  5691. " <th></th>\n",
  5692. " <th>spend_prop</th>\n",
  5693. " <th>cpt</th>\n",
  5694. " </tr>\n",
  5695. " <tr>\n",
  5696. " <th>Billing Event</th>\n",
  5697. " <th>Ad Format</th>\n",
  5698. " <th>Publisher Platforms</th>\n",
  5699. " <th>Landing Pages</th>\n",
  5700. " <th></th>\n",
  5701. " <th></th>\n",
  5702. " </tr>\n",
  5703. " </thead>\n",
  5704. " <tbody>\n",
  5705. " <tr>\n",
  5706. " <th>Impressions</th>\n",
  5707. " <th>Image</th>\n",
  5708. " <th>audience_network or facebook</th>\n",
  5709. " <th>www.koovs.com/women/tags/half-way-there</th>\n",
  5710. " <td>2.524207</td>\n",
  5711. " <td>836.021013</td>\n",
  5712. " </tr>\n",
  5713. " </tbody>\n",
  5714. "</table>\n",
  5715. "</div>"
  5716. ],
  5717. "text/plain": [
  5718. " spend_prop \\\n",
  5719. "Billing Event Ad Format Publisher Platforms Landing Pages \n",
  5720. "Impressions Image audience_network or facebook www.koovs.com/women/tags/half-way-there 2.524207 \n",
  5721. "\n",
  5722. " cpt \n",
  5723. "Billing Event Ad Format Publisher Platforms Landing Pages \n",
  5724. "Impressions Image audience_network or facebook www.koovs.com/women/tags/half-way-there 836.021013 "
  5725. ]
  5726. },
  5727. "metadata": {},
  5728. "output_type": "display_data"
  5729. },
  5730. {
  5731. "data": {
  5732. "text/html": [
  5733. "<div>\n",
  5734. "<table border=\"1\" class=\"dataframe\">\n",
  5735. " <thead>\n",
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  5737. " <th></th>\n",
  5738. " <th></th>\n",
  5739. " <th></th>\n",
  5740. " <th></th>\n",
  5741. " <th>spend_prop</th>\n",
  5742. " <th>cpt</th>\n",
  5743. " </tr>\n",
  5744. " <tr>\n",
  5745. " <th>Billing Event</th>\n",
  5746. " <th>Ad Format</th>\n",
  5747. " <th>Publisher Platforms</th>\n",
  5748. " <th>Custom Audiences</th>\n",
  5749. " <th></th>\n",
  5750. " <th></th>\n",
  5751. " </tr>\n",
  5752. " </thead>\n",
  5753. " <tbody>\n",
  5754. " <tr>\n",
  5755. " <th>Impressions</th>\n",
  5756. " <th>Image</th>\n",
  5757. " <th>audience_network or facebook</th>\n",
  5758. " <th>ECOMMERCE MOBILE & EMAIL IDS FEB 2017</th>\n",
  5759. " <td>5.03836</td>\n",
  5760. " <td>1193.015747</td>\n",
  5761. " </tr>\n",
  5762. " </tbody>\n",
  5763. "</table>\n",
  5764. "</div>"
  5765. ],
  5766. "text/plain": [
  5767. " spend_prop \\\n",
  5768. "Billing Event Ad Format Publisher Platforms Custom Audiences \n",
  5769. "Impressions Image audience_network or facebook ECOMMERCE MOBILE & EMAIL IDS FEB 2017 5.03836 \n",
  5770. "\n",
  5771. " cpt \n",
  5772. "Billing Event Ad Format Publisher Platforms Custom Audiences \n",
  5773. "Impressions Image audience_network or facebook ECOMMERCE MOBILE & EMAIL IDS FEB 2017 1193.015747 "
  5774. ]
  5775. },
  5776. "metadata": {},
  5777. "output_type": "display_data"
  5778. },
  5779. {
  5780. "data": {
  5781. "text/html": [
  5782. "<div>\n",
  5783. "<table border=\"1\" class=\"dataframe\">\n",
  5784. " <thead>\n",
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  5786. " <th></th>\n",
  5787. " <th></th>\n",
  5788. " <th></th>\n",
  5789. " <th></th>\n",
  5790. " <th>spend_prop</th>\n",
  5791. " <th>cpt</th>\n",
  5792. " </tr>\n",
  5793. " <tr>\n",
  5794. " <th>Billing Event</th>\n",
  5795. " <th>Ad Type</th>\n",
  5796. " <th>Publisher Platforms</th>\n",
  5797. " <th>Age Range</th>\n",
  5798. " <th></th>\n",
  5799. " <th></th>\n",
  5800. " </tr>\n",
  5801. " </thead>\n",
  5802. " <tbody>\n",
  5803. " <tr>\n",
  5804. " <th>Impressions</th>\n",
  5805. " <th>Carousel</th>\n",
  5806. " <th>audience_network or facebook</th>\n",
  5807. " <th>18-65</th>\n",
  5808. " <td>5.230758</td>\n",
  5809. " <td>1174.783948</td>\n",
  5810. " </tr>\n",
  5811. " </tbody>\n",
  5812. "</table>\n",
  5813. "</div>"
  5814. ],
  5815. "text/plain": [
  5816. " spend_prop \\\n",
  5817. "Billing Event Ad Type Publisher Platforms Age Range \n",
  5818. "Impressions Carousel audience_network or facebook 18-65 5.230758 \n",
  5819. "\n",
  5820. " cpt \n",
  5821. "Billing Event Ad Type Publisher Platforms Age Range \n",
  5822. "Impressions Carousel audience_network or facebook 18-65 1174.783948 "
  5823. ]
  5824. },
  5825. "metadata": {},
  5826. "output_type": "display_data"
  5827. }
  5828. ],
  5829. "source": [
  5830. "good_new, good_impacts = get_filtered_paths(good_raw)\n",
  5831. "good_impacts_list = [value[0] for value in good_impacts]\n",
  5832. "\n",
  5833. "display_df(good_new, good_impacts_list, num=100, level=[3, 4])"
  5834. ]
  5835. },
  5836. {
  5837. "cell_type": "code",
  5838. "execution_count": null,
  5839. "metadata": {
  5840. "collapsed": true
  5841. },
  5842. "outputs": [],
  5843. "source": []
  5844. }
  5845. ],
  5846. "metadata": {
  5847. "anaconda-cloud": {},
  5848. "kernelspec": {
  5849. "display_name": "Python [jarvis1]",
  5850. "language": "python",
  5851. "name": "Python [jarvis1]"
  5852. },
  5853. "language_info": {
  5854. "codemirror_mode": {
  5855. "name": "ipython",
  5856. "version": 3
  5857. },
  5858. "file_extension": ".py",
  5859. "mimetype": "text/x-python",
  5860. "name": "python",
  5861. "nbconvert_exporter": "python",
  5862. "pygments_lexer": "ipython3",
  5863. "version": "3.5.2"
  5864. }
  5865. },
  5866. "nbformat": 4,
  5867. "nbformat_minor": 0
  5868. }
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