pandas 在基于另一个 dataframe 列的列中设置值

Question

Imagine I have two pandas data frame as:

import pandas as pd

df1 = {'y1': [1, 2, 3, 4]}
df2 = {'y2': [3, 1, 2, 6]}

What I want is if a value in y2 is greater than the value in y1, I want to set df2['y2'] to the corresponding df['y1'] . When I try selecting the corresponding columns like:

df2[df2['y2'] > df1['y1']]

This is returns True rather than the index. I was hoping to do something like:

df2[df2['y2'] > df1['y1']]['y2'] = df1['y1'] 

Answer 1

If same index in both DataFrames:

Use DataFrame.loc :

df2.loc[df2['y2'] > df1['y1'], 'y2'] = df1['y1'] 
print (df2)
   y2
0   1
1   1
2   2
3   4

Or Series.where , Series.mask :

df2['y2'] = df1['y1'].where(df2['y2'].gt(df1['y1']), df2['y2'])
df2['y2'] = df2['y2'].mask(df2['y2'].gt(df1['y1']), df1['y1'])
print (df2)
   y2
0   1
1   1
2   2
3   4

Answer 2

Use numpy.where :

In [233]: import numpy as np

In [234]: df1 = pd.DataFrame({'y1': [1, 2, 3, 4]})
In [236]: df2 = pd.DataFrame({'y2': [3, 1, 2, 6]})

In [242]: df2['y2'] = np.where(df2.y2.gt(df1.y1), df1.y1, df2.y2)

In [243]: df2
Out[243]: 
   y2
0   1
1   1
2   2
3   4

Answer 3

np.minimum

Maintain all of existing df2 but with updated column values in 'y2'

df2.assign(y2=np.minimum(df1.y1, df2.y2))

   y2
0   1
1   1
2   2
3   4

Or just a new dataframe with one column

pd.DataFrame({'y2': np.minimum(df1.y1, df2.y2)})

   y2
0   1
1   1
2   2
3   4