How do I change or access pandas MultiIndex column headers?

Question

I have the following Pandas DataFrame, but am having trouble updating a column header value, or easily accessing the header values (for example, for plotting a time at the (lon,lat) location from the header).

df = pd.DataFrame(columns = ["id0", "id1", "id2"])
df.loc[2012]= [24, 25, 26]
df.loc[2013]= [28, 28, 29]
df.loc[2014]= [30, 31, 32]

df.columns = pd.MultiIndex.from_arrays([df.columns, [66,67,68], [110,111,112]],
                                       names=['id','lat','lon'])

Which then looks like this:

>>> df
id     id0   id1   id2
lat     66    67    68
lon    110   111   112
2012  24.0  25.0  26.0
2013  28.0  28.0  29.0
2014  30.0  31.0  32.0

I'd like to be able to adjust the latitude or longitude for df['id0'], or plot(df.ix[2014]) but at (x,y) location based on (lon,lat).

Answer 1

You can use df.columns.get_level_values('lat') in order to get the index object. This returns a copy of the index, so you cannot extend this approach to modify the coordinates inplace.

However, you can access the levels directly and modify them inplace using this workaround.

import pandas as pd
import numpy as np

df = pd.DataFrame(columns = ["id0", "id1", "id2"])
df.loc[2012]= [24, 25, 26]
df.loc[2013]= [28, 28, 29]
df.loc[2014]= [30, 31, 32]

df.columns = pd.MultiIndex.from_arrays([df.columns, [66,67,68], [110,111,112]],
                                       names=['id','lat','lon'])

ids = df.columns.get_level_values('id')
id_ = 'id0'
column_position = np.where(ids.values == id_)

new_lat = 90
new_lon = 0

df.columns._levels[1].values[column_position] = new_lat
df.columns._levels[2].values[column_position] = new_lon