如何比较 pandas 中两个数据框的值? [英] How to Compare Values of two Dataframes in Pandas?

问题描述

我有两个这样的数据框df和df2

I have two dataframes df and df2 like this

    id  initials
0   100 J
1   200 S
2   300 Y

    name  initials
0   John   J
1   Smith  S
2   Nathan N

我想比较(df和df2)中找到的initials列中的值，并将其初始名称与初始名称匹配的名称(在df2中)复制到第一个数据帧中的初始名称(df)

I want to compare the values in the initials columns found in (df and df2) and copy the name (in df2) which its initial is matching to the initial in the first dataframe (df)

import pandas as pd

for i in df.initials:
    for j in df2.initials:
        if i == j:
        # copy the name value of this particular initial to df

输出应如下所示:

     id name
 0   100 Johon
 1   200 Smith
 2   300   

有什么办法解决这个问题吗?

Any idea how to solve this problem?

推荐答案

如何?

df3 = df.merge(df2,on='initials',
                   how='outer').drop(['initials'],axis=1).dropna(subset=['id'])
>>> df3
      id    name
0  100.0    John
1  200.0   Smith
2  300.0     NaN

因此，"initials"列将被删除，"id"列中带有np.nan的所有内容也将被删除.

So the 'initials' column is dropped and so is anything with np.nan in the 'id' column.

如果您不希望在.fillna()上添加np.nan:

If you don't want the np.nan in there tack on a .fillna():

df3 = df.merge(df2,on='initials',
                   how='outer').drop(['initials'],axis=1).dropna(subset=['id']).fillna('')
>>> df3
      id   name
0  100.0   John
1  200.0  Smith
2  300.0

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