Pandas groupby year object building its year after year

I want to build 6 years with data for 12 months on the same axis for 12 months from December to January.

import pandas as pd
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

df = pd.Series(np.random.randn(72), index=pd.date_range('1/1/2000', periods=72, freq='M'))
grouped = df.groupby(df.index.map(lambda x: x.year))

grouped.plot()

enter image description here

Thus, I get breaks in the lines between each year. However, what I want to do is lay the year on top of each other. Any simple and clean ways to do this?

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1 answer

Probably the best way:

In [44]: vals = df.groupby(lambda x: (x.year, x.month)).sum()

In [45]: vals
Out[45]: 
(2000, 1)    -0.235044
(2000, 2)    -1.196815
(2000, 3)    -0.370850
(2000, 4)     0.719915
(2000, 5)    -1.228286
(2000, 6)    -0.192108
(2000, 7)    -0.337032
(2000, 8)    -0.174219
(2000, 9)     0.605742
(2000, 10)    1.061558
(2000, 11)   -0.683674
(2000, 12)   -0.813779
(2001, 1)     2.103178
(2001, 2)    -1.099845
(2001, 3)     0.366811
...
(2004, 10)   -0.905740
(2004, 11)   -0.143628
(2004, 12)    2.166758
(2005, 1)     0.944993
(2005, 2)    -0.741785
(2005, 3)     1.531754
(2005, 4)    -1.106024
(2005, 5)    -1.925078
(2005, 6)     0.400930
(2005, 7)     0.321962
(2005, 8)    -0.851656
(2005, 9)     0.371305
(2005, 10)   -0.868836
(2005, 11)   -0.932977
(2005, 12)   -0.530207
Length: 72, dtype: float64

Now change the index valstoMultiIndex

In [46]: vals.index = pd.MultiIndex.from_tuples(vals.index)

In [47]: vals.head()
Out[47]: 
2000  1   -0.235044
      2   -1.196815
      3   -0.370850
      4    0.719915
      5   -1.228286
dtype: float64

Then set aside and write:

In [48]: vals.unstack(0).plot()
Out[48]: <matplotlib.axes.AxesSubplot at 0x1171a2dd0>

enter image description here

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Source: https://habr.com/ru/post/1527091/


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