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Today, the editor will share with you the relevant knowledge points about how to set up index in Python dataframe. The content is detailed and the logic is clear. I believe most people still know too much about this knowledge, so share this article for your reference. I hope you can get something after reading this article. Let's take a look at it.

Dataframe sets indexDataFrame.set_index (keys, drop=True, append=False, inplace=False, verify_integrity=False)

Where: keys is a column label or array list

Drop: deletes the column to be used as the new index. Boolean defaults to True.

Whether append:boolean appends a column to an existing index defaults to False,inplace to modify DataFrame (do not create new objects) defaults to False

Verify_integrity: check if there are duplicates in the new index. The default is False.

Example:

In []: df = pd.DataFrame ({'Aids: [' A0,'A1,'A2,'A3],'B0,'B1,'B2,'B3],'C8: ['C0,'C1, C2,'C3] 'During: ['D0','D1','D2','D3']}, index= [0,1,2 3]) Out []: A B C D0A0B0C0D0D01 A1 B1 C1 D12 A2 B2 C2 D23 A3 B3 C3 D3 > > df1= df.set_index (['A','B']) > df2 = df.set_index ([[1,2]) ]) DataFrame.reset_index (level=None, drop=False, inplace=False, col_level=0, col_fill='')

Level means that only a given level is removed from the index, all levels int,str,tuple or list are removed by default, and the default is None. Drop determines whether an index column will revert to a normal column

Example:

> df.reset_index () rename index method of dataframe 1: direct assignment method

Because the index of dataframe is also data in series format, you can modify the index of dataframe by directly specifying index as a new series:

Method 2:map

Method 3:rename

Pass a function via rename to replace index or rename in batches:

You can also specify to modify index or column by passing in a dictionary:

Custom map function handles dataframe

The map function batches objects by passing in a function:

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