如何比较两个 CSV 文件并找出差异？

我有两个 CSV 文件，

a1.csv

city,state,link
Aguila,Arizona,https://www.glendaleaz.com/planning/documents/AppendixAZONING.pdf
AkChin,Arizona,http://www.maricopa-az.gov/zoningcode/wp-content/uploads/2014/05/Zoning-Code-Rewrite-Public-Review-Draft-3-Tracked-Edits-lowres1.pdf
Aguila,Arizona,http://www.co.apache.az.us/planning-and-zoning-division/zoning-ordinances/

a2.csv

city,state,link
Aguila,Arizona,http://www.co.apache.az.us

我想得到差异。

这是我的尝试：

import pandas as pd

a = pd.read_csv('a1.csv')
b = pd.read_csv('a2.csv')

mask = a.isin(b.to_dict(orient='list'))
# Reverse the mask and remove null rows.
# Upside is that index of original rows that
# are now gone are preserved (see result).
c = a[~mask].dropna()
print c

预期输出：

city,state,link
Aguila,Arizona,https://www.glendaleaz.com/planning/documents/AppendixAZONING.pdf
AkChin,Arizona,http://www.maricopa-az.gov/zoningcode/wp-content/uploads/2014/05/Zoning-Code-Rewrite-Public-Review-Draft-3-Tracked-Edits-lowres1.pdf

但我收到错误：

Empty DataFrame
Columns: [city, state, link]
Index: []**

我想根据前两行进行检查，如果它们相同，则将其删除。

您可以使用pandas要读入两个文件，将它们连接起来并删除所有重复的行：

import pandas as pd
a = pd.read_csv('a1.csv')
b = pd.read_csv('a2.csv')
ab = pd.concat([a,b], axis=0)
ab.drop_duplicates(keep=False)

参考：https://pandas.pydata.org/pandas-docs/stable/ generated/pandas.DataFrame.drop_duplicates.html