Splitting pandas.diff () at multi-index level
My question is about calling .diff () in the layered section
In the following example, the output of the first
df.diff () -
values
Greek English
alpha a NaN
b 2
c 2
d 2
beta e 11
f 1
g 1
h 1
But I want it to be:
values
Greek English
alpha a NaN
b 2
c 2
d 2
beta e NaN
f 1
g 1
h 1
Here is a solution using a loop, but I think I can avoid this loop !
import pandas as pd
import numpy as np
df = pd.DataFrame({'values' : [1.,3.,5.,7.,18.,19.,20.,21.],
'Greek' : ['alpha', 'alpha', 'alpha', 'alpha','beta','beta','beta','beta'],
'English' : ['a', 'b', 'c', 'd','e','f','g','h']})
df.set_index(['Greek','English'],inplace =True)
print df
# (1.) This is not the type of .diff() i want.
# I need it to respect the level='Greek' and restart
print df.diff()
# this is one way to achieve my desired result but i have to think
# there is a way that does not involve the need to loop.
idx = pd.IndexSlice
for greek_letter in df.index.get_level_values('Greek').unique():
df.loc[idx[greek_letter,:]]['values'] = df.loc[idx[greek_letter,:]].diff()
print df
+3
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