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- Farm_Name Total Apples Good Apples
- EM 18,327 14,176
- EE 18,785 14,146
- IW 635 486
- L 33,929 24,586
- NE 12,497 9,609
- NW 30,756 23,765
- SC 8,515 6,438
- SE 22,896 17,914
- SW 11,972 9,114
- WM 27,251 20,931
- Y 21,495 16,662
- import pandas as pd
- import io
- temp=u"""Farm_Name;Total Apples;Good Apples
- EM;18,327;14,176
- EE;18,785;14,146
- IW;635;486
- L;33,929;24,586
- NE;12,497;9,609
- NW;30,756;23,765
- SC;8,515;6,438
- SE;22,896;17,914
- SW;11,972;9,114
- WM;27,251;20,931
- Y;21,495;16,662"""
- #after testing replace io.StringIO(temp) to filename
- df = pd.read_csv(io.StringIO(temp), sep=";",thousands=',')
- print df
- Farm_Name Total Apples Good Apples
- 0 EM 18327 14176
- 1 EE 18785 14146
- 2 IW 635 486
- 3 L 33929 24586
- 4 NE 12497 9609
- 5 NW 30756 23765
- 6 SC 8515 6438
- 7 SE 22896 17914
- 8 SW 11972 9114
- 9 WM 27251 20931
- 10 Y 21495 16662
- print df.info()
- <class 'pandas.core.frame.DataFrame'>
- RangeIndex: 11 entries, 0 to 10
- Data columns (total 3 columns):
- Farm_Name 11 non-null object
- Total Apples 11 non-null int64
- Good Apples 11 non-null int64
- dtypes: int64(2), object(1)
- memory usage: 336.0+ bytes
- None
- locale.setlocale(locale.LC_NUMERIC, '')
- df = df[['Farm Name']].join(df[['Total Apples', 'Good Apples']].applymap(locale.atof))
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