不要在熊猫中使用循环，与矢量化解决方案相比，它们比较慢-通过

Don't use loops in pandas, they are slow compared to a vectorized solution - convert boolean mask to integers by astype True, False are converted to 1, 0:

dataframe = pd.DataFrame({'A':list('abcdef'),
                   'B':[4,5,4,5,5,4],
                   'C':[7,8,9,4,2,3],
                   'D':[1,3,5,7,1,0],
                   'E':list('aaabbb'),
                   'F':[5,3,6,9,2,4],
                   'G':[5,3,6,9,2,4]
})

a = 5
dataframe['new'] = (dataframe.iloc[:,5] >= a).astype(int)
print (dataframe)
   A  B  C  D  E  F  G  new
0  a  4  7  1  a  5  5    1
1  b  5  8  3  a  3  3    0
2  c  4  9  5  a  6  6    1
3  d  5  4  7  b  9  9    1
4  e  5  2  1  b  2  2    0
5  f  4  3  0  b  4  4    0

如果要覆盖第7列:

a = 5
dataframe.iloc[:,6] = (dataframe.iloc[:,5] >= a).astype(int)
print (dataframe)
   A  B  C  D  E  F  G
0  a  4  7  1  a  5  1
1  b  5  8  3  a  3  0
2  c  4  9  5  a  6  1
3  d  5  4  7  b  9  1
4  e  5  2  1  b  2  0
5  f  4  3  0  b  4  0