python - pandas DataFrame中设置索引的问题

Question

我将给定代码的索引设置为国家/地区名称，但使用 dataframe.set_index(index_name)。我无法更新数据框的索引。我目前正在使用 Python 3.7，为什么这段代码没有设置索引？

import pandas as pd
import numpy as np

df1 = pd.DataFrame({'Country':['Nigeria','Bangladesh','China'],
                    'population':[89765,98744,654520],
                    'Birth_Rate':[23.54,34.43,20.3],
                    'Update_Date':['2016-01-18','2016-02-15','2016-02-03']},
                    columns = ['Country','population','Birth_Rate','Update_Date'])                                                        

df2 = pd.DataFrame({'Country':['India','Sri Lanka','Dubai'],
                    'population':[98343,2453,57432],
                    'Birth_Rate':[33.54,44.44,23.3],
                    'Update_Date':['2016-01-18','2016-02-15','2016-02-03']},
                    columns =['Country','population','Birth_Rate','Update_Date']) 

df3 = df2.append(df1)
df3.set_index('Country')
print(df3)

我期望这是输出:

      Country   population  Birth_Rate Update_Date
0       India       98343       33.54  2016-01-18
1   Sri Lanka        2453       44.44  2016-02-15
2       Dubai       57432       23.30  2016-02-03
0     Nigeria       89765       23.54  2016-01-18
1  Bangladesh       98744       34.43  2016-02-15
2       China      654520       20.30  2016-02-03

but actual output is:
            population  Birth_Rate   Update_Date
Country    
 India       98343       33.54      2016-01-18                               
 Sri Lanka   2453        44.44      2016-02-15
 Dubai       57432       23.30      2016-02-03
 Nigeria     89765       23.54      2016-01-18
 Bangladesh  98744       34.43      2016-02-15
 China       654520      20.30      2016-02-03

Answer 1

使用一个或多个现有列设置 DataFrame 索引(行标签)。

您可以使用DataFrame.set_index(keys, drop=True,append=False, inplace=False, verify_integrity=False)

参数定义的位置:

keys : column label or list of column labels / arrays drop : boolean, default True

Delete columns to be used as the new index

append : boolean, default False

Whether to append columns to existing index

inplace : boolean, default False

Modify the DataFrame in place (do not create a new object)

verify_integrity : boolean, default False

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

import pandas as pd
import numpy as np

df1 = pd.DataFrame({'Country':['Nigeria','Bangladesh','China'],
                    'population':[89765,98744,654520],
                    'Birth_Rate':[23.54,34.43,20.3],
                    'Update_Date':['2016-01-18','2016-02-15','2016-02-03']},
                    columns = ['Country','population','Birth_Rate','Update_Date'])                                                        

df2 = pd.DataFrame({'Country':['India','Sri Lanka','Dubai'],
                    'population':[98343,2453,57432],
                    'Birth_Rate':[33.54,44.44,23.3],
                    'Update_Date':['2016-01-18','2016-02-15','2016-02-03']},
                    columns =['Country','population','Birth_Rate','Update_Date']) 

df3 = df2.append(df1)
df3.set_index('Country', inplace = True, 
                            append = True, drop = True)
print(df3)

输出: