pandas.DataFrame.set_index的使用介紹

官方參考鏈接：

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.set_index.html#pandas.DataFrame.set_index

Set the DataFrame index using existing columns.

Set the DataFrame index (row labels) using one or more existing columns or arrays (of the correct length). The index can replace the existing index or expand on it.

Parameters

keys label or array-like or list of labels/arrays

This parameter can be either a single column key, a single array of the same length as the calling DataFrame, or a list containing an arbitrary combination of column keys and arrays. Here, “array” encompasses Series, Index, np.ndarray, and instances of Iterator.

drop bool, default True

Delete columns to be used as the new index.

append bool, default False

Whether to append columns to existing index.

inplace bool, default False

If True, modifies the DataFrame in place (do not create a new object).

verify_integrity bool, default False

Check the new index for duplicates. Otherwise defer the check until necessary. Setting to False will improve the performance of this method.

Returns

DataFrame or None

Changed row labels or None if inplace=True.

個人理解：

這是一個設置index的命令，主要參數為keys. 這個參數可以式已經存在的df對象中的columns的名稱，也可以是一個單獨的數組對象，數組對象包含Series, Index, np.ndarray, and instances of Iterator.

drop :表示為是否丟棄設置為index的columns   bool值，默認為true。

append: 是否為添加的索引，默認為flase，true會與源索引變成組合索引。

verify_integrity:檢查新索引是否有重復項，默認為false。

 

官方代碼實操學習

常規操作，設置一個列為index

In [32]: df = pd.DataFrame({'month': [1, 4, 7, 10], 
    ...:                    'year': [2012, 2014, 2013, 2014], 
    ...:                    'sale': [55, 40, 84, 31]})                                                      

In [33]: df                                                                                                 
Out[33]: 
   month  year  sale
0      1  2012    55
1      4  2014    40
2      7  2013    84
3     10  2014    31

In [34]: df.set_index('month')                                                                              
Out[34]: 
       year  sale
month            
1      2012    55
4      2014    40
7      2013    84
10     2014    31

　　

設置append為True，組合為聯合索引。

In [35]: df.set_index('year',append=True)                                                                   
Out[35]: 
        month  sale
  year             
0 2012      1    55
1 2014      4    40
2 2013      7    84
3 2014     10    31

　　

當然也可以通過設置多列，設置組合索引。

In [37]: df.set_index(['year','month'])                                                                     
Out[37]: 
            sale
year month      
2012 1        55
2014 4        40
2013 7        84
2014 10       31

In [38]:                                                                                                    

In [38]: df.set_index([pd.Index([2,3,4,5]),'year'])                                                         
Out[38]: 
        month  sale
  year             
2 2012      1    55
3 2014      4    40
4 2013      7    84
5 2014     10    31

　　最后也可以設置外部傳入的可迭代對象為index

In [39]: new_index = list('abcd')                                                                           

In [40]: df.set_index([new_index])                                                                          
Out[40]: 
   month  year  sale
a      1  2012    55
b      4  2014    40
c      7  2013    84
d     10  2014    31