我有两个要合并的csv文件,如下所示-或多或少地使用第一列ID_作为唯一标识符,并将AMT列附加到最终文件中的新行。
CSV1
ID_ CUSTOMER_ID_ EMAIL_ADDRESS_
1090 1 example1@example.com
1106 2 example2@example.com
1145 3 example3@example.com
1206 4 example4@example.com
1247 5 example5@example.com
1254 6 example6@example.com
1260 7 example7@example.com
1361 8 example8@example.com
1376 9 example9@example.com
CSV2
ID_ AMT
1090 5
1106 5
1145 5
1206 5
1247 5
1254 65
1260 5
1361 10
1376 5
这是我在最终文件中寻找的内容:
ID_ CUSTOMER_ID_ EMAIL_ADDRESS_ AMT
1090 1 example1@example.com 5
1106 2 example2@example.com 5
1145 3 example3@example.com 5
1206 4 example4@example.com 5
1247 5 example5@example.com 5
1254 6 example6@example.com 65
1260 7 example7@example.com 5
1361 8 example8@example.com 10
1376 9 example9@example.com 5
我尝试过尽可能在下面修改此内容,但无法获得所需的内容。真的卡在了这里-不知道我还能做什么。非常感谢任何帮助!
join -t, File1.csv File2.csv
此示例中显示的数据包含选项卡,但如上所述,我的实际文件是CSV,并且将逗号作为分隔符。
答案 0 :(得分:2)
可以使用Pandas库轻松完成此操作。这是我执行此操作的代码:
'''
This program reads two csv files and merges them based on a common key column.
'''
# import the pandas library
# you can install using the following command: pip install pandas
import pandas as pd
# Read the files into two dataframes.
df1 = pd.read_csv('CSV1.csv')
df2 = pd.read_csv('CSV2.csv')
# Merge the two dataframes, using _ID column as key
df3 = pd.merge(df1, df2, on = 'ID_')
df3.set_index('ID_', inplace = True)
# Write it to a new CSV file
df3.to_csv('CSV3.csv')
您可以在此处找到有关熊猫的简短教程: https://pandas.pydata.org/pandas-docs/stable/getting_started/10min.html