如何使用python将多个CSV文件合并为一个文件，并在最终的CSV文件中创建超级模式

Question

如何在python 2.4版本(python 2.x)中将多个CSV文件合并为一个CSV文件。我想合并近30个CSV文件到一个单一的CSV文件。最终的CSV文件包含超级模式列(来自每个文件的所有列)。不可用的列值考虑为最终CSV文件中的空值或空格值。

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，不可用的列应为空值或空格。

最终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!

使用pandas组合两个csv文件

pandas.DataFrame.append