如何删除 pivot 表中的索引并将其调平

Question

import numpy as np
import pandas as pd
import seaborn as sns

Here I bring sns flights detail and try to remove index to do a correlation. I first need to do a make dataframe looks like the last data frame in here

flights = sns.load_dataset("flights")
flights.head()

flights = flights.pivot( "month","year", "passengers")
flights.reset_index(inplace=True)
flights.head()

year month     1949 1950    1951    1952    1953    1954    1955    
0   January     112  115    145     171     196     204     242     
1   February    118  126    150     180     196     188     233     
2   March       132  141    178     193     236     235     267     
3   April       129  135    163     181     235     227     269     
4   May         121  125    172     183     229     234     270     

I basically want to remove year in here and keep the dataframe as below without any level

 month     1949 1950    1951    1952    1953    1954    1955    1956    1957    1958    1959    1960
January     112  115    145     171     196     204     242     284     315     340     360     417
February    118  126    150     180     196     188     233     277     301     318     342     391
March       132  141    178     193     236     235     267     317     356     362     406     419
April       129  135    163     181     235     227     269     313     348     348     396     461
May         121  125    172     183     229     234     270     318     355     363     420     472

Answer 1

You can change name of the columns and reset_index as:

flights.columns.name = None
flights = flights.reset_index()

print(flights.iloc[:,:5])
        month  1949  1950  1951  1952
0     January   112   115   145   171
1    February   118   126   150   180
2       March   132   141   178   193
3       April   129   135   163   181
4         May   121   125   172   183
5        June   135   149   178   218
6        July   148   170   199   230
7      August   148   170   199   242
8   September   136   158   184   209
9     October   119   133   162   191
10   November   104   114   146   172
11   December   118   140   166   194