I have a dataframe with a multi-index. I want to change the value of the 2nd index when certain conditions on the first index are met. I found a similar (but different) question here: Replace a value in MultiIndex (pandas) which doesn't answer my point because that was about changing a single row, and the solution passed the value of the first index (which didn't need changing), too. In my case I am dealing with multiple rows and I haven't been able to adapt that solution to my case.
A minimal example of my data is below. Thanks!
import pandas as pd
import numpy as np
consdf=pd.DataFrame()
for mylocation in ['North','South']:
for scenario in np.arange(1,4):
df= pd.DataFrame()
df['mylocation'] = [mylocation]
df['scenario']= [scenario]
df['this'] = np.random.randint(10,100)
df['that'] = df['this'] * 2
df['something else'] = df['this'] * 3
consdf=pd.concat((consdf, df ), axis=0, ignore_index=True)
mypiv = consdf.pivot('mylocation','scenario').transpose()
level_list =['this','that']
# if level 0 is in level_list --> set level 1 to np.nan
mypiv.iloc[mypiv.index.get_level_values(0).isin(level_list)].index.set_levels([np.nan], level =1, inplace=True)
The last line doesn't work: I get:
ValueError: On level 1, label max (2) >= length of level (1). NOTE: this index is in an inconsistent state