How can I construct a multi-index in pandas for an example dataframe of:
import pandas as pd
df = pd.DataFrame({'day':['2020-01-01', '2020-01-02'], 'value_mean':[1,5], 'value_max':[40,100]})
Transform the existing:
day value_mean value_max
0 2020-01-01 1 40
1 2020-01-02 5 100
To something like:
value
day mean max
0 2020-01-01 1 40
1 2020-01-02 5 100
There is problem join no Multiindex with MultiIndex columns, only trick should be use empty strings for second level:
df.columns = df.columns.str.split('_', expand=True)
df = df.rename(columns = lambda x: x if pd.notna(x) else '')
print (df)
day value
mean max
0 2020-01-01 1 40
1 2020-01-02 5 100
print (df.columns)
MultiIndex([( 'day', ''),
('value', 'mean'),
('value', 'max')],
)
If want clean, not empty strings values in levels:
df = df.set_index('day')
df.columns = df.columns.str.split('_', expand=True)
print (df)
value
mean max
day
2020-01-01 1 40
2020-01-02 5 100
Another option:
df.columns = pd.MultiIndex(levels=[['value', 'day'], ['mean','max','']], codes=[[1,0,0],[2,0,1]])
Output:
day value
mean max
0 2020-01-01 1 40
1 2020-01-02 5 100
