Select multiple rows from pandas data frame where one of column contains some values as NaN

Question

Select rows with columns ['A','B'] where rows with column 'C' contain NaN values in python (Pandas)

1. I have pandas data frame with three columns 'A' , 'B', 'C'.
2. In column 'C' there are some rows which contains NaN values.

Now I want to select column 'A' and column 'B' of data frame where column 'C' contains NaN values.

If all columns or only one column needs to be selected then I can do below,

df['A'][df['C'].isnull()]

or

df[df['C'].isnull()]

but I am not getting how to select multiple columns.

Answer 1

您可以在第一种形式中放置多个列名。

df[['A','B']][df['C'].isnull()]                                            

Answer 2

You can use loc , and select a list of columns:

df.loc[df['C'].isnull(), ['A','B']]

For example

>>> df = pd.DataFrame({'A':[1,2,3,4], 'B':[5,6,7,8], 'C':[np.nan,1,np.nan,2]})     

>>> df                                                                                                   
   A  B    C                                                                                             
0  1  5  NaN
1  2  6  1.0
2  3  7  NaN
3  4  8  2.0

>>> df.loc[df['C'].isnull(), ['A','B']]                                                                     
   A  B                                                                                                  
0  1  5
2  3  7

Answer 3

I like dropna and drop , since we will not have copy warning when we forget add the .copy()

sub=df.dropna(subset=['C']).drop('C',1)
sub
Out[26]: 
   A  B
1  2  6
3  4  8