How to Plot 2 lines based on the value not column

Question

I have a data set:

ReviewDate_year,ReviewDate_month,Sales
 2010,11,1
 2011,02,2
 2011,11,1
 2011,12,6
 2012,01,11
 2012,02,8
 2012,03,3
 2012,04,1
 2012,05,8
 2012,06,3
 2012,07,1
 2012,08,2
 2012,09,1
 2012,11,1
 2012,12,8
 2013,01,2
 2013,02,2
 2013,03,4
 2013,04,4
 2013,05,7
 2013,06,5
 2013,07,6
 2013,08,4
 2013,09,4
 2013,10,5
 2013,11,3
 2013,12,5
 2014,01,9
 2014,02,4
 2014,03,8
 2014,04,7
 2014,05,3
 2014,06,7
 2014,07,1

How do I plot Sales by month and different year in different line

I can certainly do it by year

df_2013 = df_monthlycount[df_monthlycount['ReviewDate_year'] == 2013]
df_2014 = df_monthlycount[df_monthlycount['ReviewDate_year'] == 2014]

df_2013.plot(x='ReviewDate_month',y='ProductId')

plt.show()

but how can I make lines of different year in a single chart?

Data shaping without pandas: http://stackoverflow.com/questions/31863083/python-split-numpy-array-based-on-values-in-the-array — Ciro Santilli OurBigBook.com, Sep 07 '16 at 07:40
Related: http://stackoverflow.com/questions/15465645/plotting-results-of-pandas-groupby — Ciro Santilli OurBigBook.com, Sep 07 '16 at 07:48

CT Zhu · Answer 1 · 2015-11-10T06:01:45.007

You can use groupby plot. Instead of creating one ax for each group, you can specify an ax and have everything plotted on that ax:

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

ax = plt.subplot(111)
df[df.ReviewDate_year.isin([2012,2013])].groupby('ReviewDate_year').plot(y='Sales', x='ReviewDate_month', kind='line', ax=ax)
L = plt.legend()
_ = [plt.setp(item, 'text', T) for item, T in zip(L.texts, ['2012','2013'])]
_ = ax.set_xticks(df.ReviewDate_month.unique())

How to Plot 2 lines based on the value not column

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