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
我想得到结果的差异, 这是我试过的代码,
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
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
但收到错误: - 空DataFrame 专栏:[城市,州,链接] 指数:[]
我想根据前两行进行检查,如果相同,则将其删除。
先谢谢。
答案 0 :(得分:1)
您可以使用pandas
读入两个文件,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)
参考:https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.drop_duplicates.html
答案 1 :(得分:1)
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)