如何使用python将多个CSV文件合并到一个文件中，并在最终的CSV文件中创建超级模式

Question

如何在Python2.4版本（Python2.x）中将多个CSV文件合并为一个CSV文件。我想把30个CSV文件合并成一个CSV文件。最后一个CSV文件包含超级架构列（每个文件中的所有列）。在最终CSV文件中，对于空值或空白值考虑不可用的列值。

第一个文件：

file111.csv:
"E_TYPE","TIMESTAMP","EXEC_TIME","DBT_TIME","CALLOUT_TIME","CLIENT_IP"
"BBCout","20191011000022.423","95","0","2019-01-11T00:00:05.300Z","200.50.000.333" 
"BBCout","20200403122024.123","96","1","2020-04-03T00:00:05.300Z","300.50.000.333"
"BBCout","20210102083426.543","92","0","2021-01-02T00:00:05.300Z","400.50.000.333"

第二个文件：

file222.csv:
"E_TYPE","TIMESTAMP","TYPE","METHOD","TIME","RT_SIZE","URL","UID_DERIVED","CLIENT_IP"
"AACallout","20210215000030.815","REST","POST","61","71","""https://st.aaa.xxx.net/n1/yyy/zzz""","0055QAQ","200.50.000.333"
"AACallout","20201210000012.800","REST","GET","67","75","""https://st.aaa.xxx.net/n1/yyy/zzz""","0055BBBQ","300.00.000.111"

最终合并的CSV应包含所有列，不可用列应为空值或空白

最终的CSV文件

result.csv

"E_TYPE","TIMESTAMP","CLIENT_IP","EXEC_TIME","DBT_TIME","CALLOUT_TIME","TYPE","METHOD","TIME","RT_SIZE","URL","UID_DERIVED"
"BBCout","20191011000022.423","200.50.000.333","95","0","2019-01-11T00:00:05.300Z",,,,,,
"BBCout","20200403122024.123","300.50.000.333","96","1","2020-04-03T00:00:05.300Z",,,,,,
"BBCout","20210102083426.543","400.50.000.333","92","0","2021-01-02T00:00:05.300Z",,,,,,
"AACallout","20210215000030.815","200.50.000.333",,,,"REST","POST","61","71","""https://st.aaa.xxx.net/n1/yyy/zzz""","0055QAQ"
"AACallout","20201210000012.800","300.00.000.111",,,,"REST","GET","67","75","""https://st.aaa.xxx.net/n1/yyy/zzz""","0055BBBQ"

Answer 1

您可以使用pandas.DataFrame.append来实现这一点

Combining two csv files using pandas

pandas.DataFrame.append