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  1. {
  2. "cells": [
  3. {
  4. "cell_type": "code",
  5. "execution_count": 2,
  6. "metadata": {
  7. "collapsed": true
  8. },
  9. "outputs": [],
  10. "source": [
  11. "%matplotlib notebook"
  12. ]
  13. },
  14. {
  15. "cell_type": "markdown",
  16. "metadata": {},
  17. "source": [
  18. "### Loading modules"
  19. ]
  20. },
  21. {
  22. "cell_type": "code",
  23. "execution_count": 3,
  24. "metadata": {
  25. "collapsed": true
  26. },
  27. "outputs": [],
  28. "source": [
  29. "import numpy as np\n",
  30. "import pandas as pd\n",
  31. "import matplotlib.pyplot as plt\n",
  32. "import seaborn as sns \n",
  33. "sns.set(style=\"whitegrid\", color_codes=True)"
  34. ]
  35. },
  36. {
  37. "cell_type": "markdown",
  38. "metadata": {},
  39. "source": [
  40. "### Loading the data"
  41. ]
  42. },
  43. {
  44. "cell_type": "code",
  45. "execution_count": 4,
  46. "metadata": {
  47. "collapsed": true
  48. },
  49. "outputs": [],
  50. "source": [
  51. "hepatitis_data = pd.read_csv(\"dataset_55_hepatitis.csv\")"
  52. ]
  53. },
  54. {
  55. "cell_type": "code",
  56. "execution_count": 5,
  57. "metadata": {},
  58. "outputs": [
  59. {
  60. "data": {
  61. "text/plain": [
  62. "(155, 20)"
  63. ]
  64. },
  65. "execution_count": 5,
  66. "metadata": {},
  67. "output_type": "execute_result"
  68. }
  69. ],
  70. "source": [
  71. "hepatitis_data.shape"
  72. ]
  73. }
  74. ],
  75. "metadata": {
  76. "kernelspec": {
  77. "display_name": "Python 3",
  78. "language": "python",
  79. "name": "python3"
  80. },
  81. "language_info": {
  82. "codemirror_mode": {
  83. "name": "ipython",
  84. "version": 3
  85. },
  86. "file_extension": ".py",
  87. "mimetype": "text/x-python",
  88. "name": "python",
  89. "nbconvert_exporter": "python",
  90. "pygments_lexer": "ipython3",
  91. "version": "3.6.3"
  92. }
  93. },
  94. "nbformat": 4,
  95. "nbformat_minor": 2
  96. }
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