问题
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.
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.
回答1:
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
回答2:
If you already know the index you can use .loc:
In [12]: df = pd.DataFrame({"a": [1,2,3,4,5], "b": [4,5,6,7,8]})
In [13]: df
Out[13]:
a b
0 1 4
1 2 5
2 3 6
3 4 7
4 5 8
In [14]: df.loc[[0,2,4]]
Out[14]:
a b
0 1 4
2 3 6
4 5 8
In [15]: df.loc[1:3]
Out[15]:
a b
1 2 5
2 3 6
3 4 7
来源：https://stackoverflow.com/questions/11881165/slice-pandas-dataframe-by-row