如何用列名填充 dataframe 的真值？

Question

I have a DataFrame with True and False values.

       A      B      C      D
0  False  True   True   False
1  False  False  True   False
2  True   True   False  False

I want to fill the true values with column names and false values with 0. How can I do that?

ie To get the result as

   A  B  C  D
0  0  B  C  0
1  0  0  C  0
2  A  B  0  0

Answer 1

First replace booelan to int and then use mask or where with inverting mask by ~ :

df = df.astype(int).mask(df, df.columns.to_series(), axis=1)
print (df)
   A  B  C  D
0  0  B  C  0
1  0  0  C  0
2  A  B  0  0

---

df = df.astype(int).where(~df, df.columns.to_series(), axis=1)
print (df)
   A  B  C  D
0  0  B  C  0
1  0  0  C  0
2  A  B  0  0

Thank you John Galt for improvement in new versions of pandas 0.21.x :

df = df.astype(int).mask(df, df.columns, axis=1)

numpy solution:

a = np.tile(df.columns, [len(df.index),1])
print (a)
[['A' 'B' 'C' 'D']
 ['A' 'B' 'C' 'D']
 ['A' 'B' 'C' 'D']]

df = pd.DataFrame(np.where(df.astype(int), a, 0), columns=df.columns, index = df.index)
print (df)
   A  B  C  D
0  0  B  C  0
1  0  0  C  0
2  A  B  0  0

Answer 2

pandas 1.5.2

df = df.mask(df.astype(bool), df.columns.to_series(), axis=1)

---

not astype(int) but astype(bool) or astype('bool')

Otherwise ValueError: Boolean array expected for the condition, not uint8

---

can't remove .to_series()

Otherwise ValueError: other must be the same shape as self when an ndarray