pandas 中的新列取决于其他行的值

Question

I have an example data as:

column1 column2 column3 column4
  0.       1.      1.      0
  1.       1.      1.      1
  0.       0.      0.      0
  1.       1.      1.      0
  1.       1.      1.      1

I would like to create a new column(output) which shows 1 if at least one of the row values of the dataframe is 1, and 0 if the rows are all 0.

The output should look like this:

column1 column2 column3 column4. output
  0.       1.      1.      0.     1
  1.       1.      1.      1.     1
  0.       0.      0.      0.     0
  1.       1.      1.      0.     1
  1.       1.      1.      1.     1

Answer 1

Use DataFrame.any for test if match at least one match:

df['output'] = df.eq(1).any(axis=1).astype(int)
#alternative
df['output'] = np.where(df.eq(1).any(axis=1), 1, 0)

#if only 0,1 values is possible use
#df['output'] = df.any(axis=1).astype(int)

Answer 2

Use:

df['output'] = np.any(df.eq(1)., axis = 1).astype(int)

Answer 3

You can check that the sum of the all columns in the row is superior to 0

df.output = df.apply(lambda row: int(row.sum() > 0), axis=1)