如何使用 pandas 打印两列的差异? [英] How to use pandas to print the difference of two columns?

问题描述

我有两个数据集

1设置有一个带有电子邮件地址列表的列:

1 set it has a column with a list of email address:

DF1

Email
[e-mail]
[e-mail]
[e-mail]
[e-mail]
[e-mail]

第二个CSV 数据框2

2nd csv Dataframe2

Email
[e-mail]
[e-mail]
[e-mail]
[e-mail]
[e-mail]
[e-mail]
[e-mail]

---

import pandas as pd

SansList = r'C:\\Sans compare\\SansList.csv'
AllUsers = r'C:\\Sans compare\\AllUser.csv'

## print Name column only and turn into data sets from CSV ##
df1 = pd.read_csv(SansList, usecols=[0])

df2 = pd.read_csv(AllUsers, usecols=[2])

**print(df1['Email'].isin(df2)==False)**

我希望结果是

Dataframe3
[e-mail]
[e-mail]
[e-mail]

不太确定如何修复我的数据集...:(

Not quite sure how to fix my dataset... :(

推荐答案

选项1
isin

Option 1
isin

df2[~df2.Email.isin(df1.Email)]

          Email
4  [e-mail]
5  [e-mail]
6  [e-mail]

选项2
query

Option 2
query

df2.query('Email not in @df1.Email')

          Email
4  [e-mail]
5  [e-mail]
6  [e-mail]

选项3
merge

Option 3
merge

pd.DataFrame.merge和indicator=True，可让您查看该行来自哪个数据帧.然后我们可以对其进行过滤.

pd.DataFrame.merge with indicator=True, enables you to see which dataframe the row came from. We can then filter on it.

df2.merge(
    df1, 'outer', indicator=True
).query('_merge == "left_only"').drop('_merge', 1)

           Email
20  [e-mail]
21  [e-mail]
22  [e-mail]

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