使用 Pandas 合并多个 CVS 文件

Question

I am struggling with merging multiple .csv files using pandas.

All of the files have the same structure as presented below, where 'UniqueColumn' varies for every csv, and column "Name" is same for every csv but they are not sorted in the same way:

csv1:
Name, UniqueColumnA
testName, DataA
...

csv2:
Name, UniqueColumnB
testName, DataB
...

etc.

Desired merged csv file would look like this:

Name, UniqueColumnA, UniqueColumnB, UniqueColumnC
testName, DataA, DataB, DataC

I've tried to use the following code:

files = glob.glob(r'pathname*.csv')
df = pd.concat([pd.read_csv(f, index_col=['Name']) for f in files])
df.to_csv('merged.csv')

But the output was

testName, DataA
testName, DataB
...

I'm not very much familiar with Python, especially with pandas so I would really appreciate a helping hand here

Answer 1

有重复的索引，您需要告诉熊猫如何处理它们，在您的情况下，您需要一个inner join因此以下内容应该适合您：

df = pd.concat([pd.read_csv(f, index_col='Name') for f in files], join='inner', axis=1)