pandas 比较两个csv文件并使用python获取差异
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Comparing two csv files and get the difference using python
提问by vishal
I have two csv files,
我有两个 csv 文件，
a1.csv
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
a2.csv
city,state,link
Aguila,Arizona,http://www.co.apache.az.us
I want to get the difference of result, Here is the code which i tried,
我想得到结果的差异，这是我尝试过的代码，
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
Expected Output:
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
But am getting Error:- Empty DataFrame Columns: [city, state, link] Index: []
但我收到错误：- Empty DataFrame Columns: [city, state, link] 索引：[]
I want to check based on first two rows, if its same then remove it off.
我想根据前两行进行检查，如果相同则将其删除。
Thanks in Advance.
提前致谢。
采纳答案by shindig_
First, concatenate the DataFrames, then drop the duplicates while still keeping the first one. Then reset the index to keep it consistent.
首先，连接 DataFrames，然后删除重复项，同时保留第一个。然后重置索引以保持一致。
import pandas as pd
a = pd.read_csv('a1.csv')
b = pd.read_csv('a2.csv')
c = pd.concat([a,b], axis=0)
c.drop_duplicates(keep='first', inplace=True) # Set keep to False if you don't want any
# of the duplicates at all
c.reset_index(drop=True, inplace=True)
print(c)
回答by TYZ
You can use pandasto read in two files, join them and remove all duplicate rows:
您可以使用pandas读取两个文件，加入它们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)
Reference: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.drop_duplicates.html
参考：https: //pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.drop_duplicates.html
