按行切片Pandas DataFrame [英] Slice Pandas DataFrame by Row

问题描述

我正在处理通过pandas软件包从h5文件作为hdf = pandas.HDFStore('Survey.h5')加载的调查数据.在此DataFrame中，所有行都是单个调查的结果，而列则是单个调查中所有问题的答案.

I am working with survey data loaded from an h5-file as hdf = pandas.HDFStore('Survey.h5') through the pandas package. Within this DataFrame, all rows are the results of a single survey, whereas the columns are the answers for all questions within a single survey.

我的目标是将数据集缩小为较小的DataFrame，仅包括对某个问题具有特定答案的行，即该列中的所有值均相同.在这种情况下，我能够确定所有行的索引值，但是我找不到如何删除该行或仅使用这些行创建新的df.

I am aiming to reduce this dataset to a smaller DataFrame including only the rows with a certain depicted answer on a certain question, i.e. with all the same value in this column. I am able to determine the index values of all rows with this condition, but I can't find how to delete this rows or make a new df with these rows only.

推荐答案

In [36]: df
Out[36]:
   A  B  C  D
a  0  2  6  0
b  6  1  5  2
c  0  2  6  0
d  9  3  2  2

In [37]: rows
Out[37]: ['a', 'c']

In [38]: df.drop(rows)
Out[38]:
   A  B  C  D
b  6  1  5  2
d  9  3  2  2

In [39]: df[~((df.A == 0) & (df.B == 2) & (df.C == 6) & (df.D == 0))]
Out[39]:
   A  B  C  D
b  6  1  5  2
d  9  3  2  2

In [40]: df.ix[rows]
Out[40]:
   A  B  C  D
a  0  2  6  0
c  0  2  6  0

In [41]: df[((df.A == 0) & (df.B == 2) & (df.C == 6) & (df.D == 0))]
Out[41]:
   A  B  C  D
a  0  2  6  0
c  0  2  6  0

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