Pandas：根据条件将数据从df提取到新的df

Question

I have the following df1:

Person  Day1  Day2  Day3
1       2     1     1
2       2     0     7
3       4     1     2

And then another df2:

Person  Day1  Day2  Day3
1       a     b     b
2       a     c     a
3       c     b     c

So these two dataframes have the same index and columns. How can I select elements of df1 that only have "c" in df2?

The result should be values from df1 when the condition is met, and 0 otherwise:

Person  Day1  Day2  Day3
1       0     0     0
2       0     0     0
3       4     0     2

Answer 1

If first column is index use DataFrame.where :

df = df1.where(df2.eq('c'), 0)
print (df)
        Day1  Day2  Day3
Person                  
1          0     0     0
2          0     0     0
3          4     0     2

If first column is not index, one possible idea is select all columns without first and assign back:

df1.iloc[:, 1:]= df1.iloc[:, 1:].where(df2.iloc[:, 1:].eq('c'), 0)
print (df1)
   Person  Day1  Day2  Day3
0       1     0     0     0
1       2     0     0     0
2       3     4     0     2

Or:

df = df1.set_index('Person').where(df2.set_index('Person').eq('c'), 0).reset_index()
print (df)
   Person  Day1  Day2  Day3
0       1     0     0     0
1       2     0     0     0
2       3     4     0     2

Answer 2

With @jezrael's help, another solution using np.where :

import numpy as np
df = pd.DataFrame(np.where(df2.eq('c'), df1, 0), index=df1.index, columns=df1.columns).reset_index()

Output:

   Person  Day1  Day2  Day3
0       1     0     0     0
1       2     0     0     0
2       3     4     0     2