split a pd dataframe
split a pd dataframe
xxxxxxxxxxIn [255]: df = pd.DataFrame(np.random.rand(5, 6), columns=list('abcdef'))In [256]: dfOut[256]: a b c d e f0 0.823638 0.767999 0.460358 0.034578 0.592420 0.7768031 0.344320 0.754412 0.274944 0.545039 0.031752 0.7845642 0.238826 0.610893 0.861127 0.189441 0.294646 0.5570343 0.478562 0.571750 0.116209 0.534039 0.869545 0.8555204 0.130601 0.678583 0.157052 0.899672 0.093976 0.268974In [257]: dfs = np.split(df, [4], axis=1)In [258]: dfs[0]Out[258]: a b c d0 0.823638 0.767999 0.460358 0.0345781 0.344320 0.754412 0.274944 0.5450392 0.238826 0.610893 0.861127 0.1894413 0.478562 0.571750 0.116209 0.5340394 0.130601 0.678583 0.157052 0.899672In [259]: dfs[1]Out[259]: e f0 0.592420 0.7768031 0.031752 0.7845642 0.294646 0.5570343 0.869545 0.8555204 0.093976 0.268974Source: stackoverflow.com
Closely Related Answers
xxxxxxxxxxIn [42]:df[['V','allele']] = df['V'].str.split('-',expand=True)dfOut[42]: ID Prob V allele0 3009 1.0000 IGHV7 B*011 129 1.0000 IGHV7 B*012 119 0.8000 IGHV6 A*013 120 0.8056 GHV6 A*014 121 0.9000 IGHV6 A*015 122 0.8050 IGHV6 A*016 130 1.0000 IGHV4 L*037 3014 1.0000 IGHV4 L*038 266 0.9970 IGHV5 A*019 849 0.4010 IGHV5 A*0410 174 1.0000 IGHV6 A*0211 844 1.0000 IGHV6 A*02Source: stackoverflow.com
xxxxxxxxxxtrain[['deck', 'num','side']] = train['Cabin'].str.split('/', expand=True)Source: Grepper
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