How can I draw Yearly series using monthly data from a DateTimeIndex in Matplotlib?

I have monthly data of 6 variables from 2014 until 2018 in one dataset. I'm trying to draw 6 subplots (one for each variable) with monthly X axis (Jan, Feb....) and 5 series (one for each year) with their legend.

This is part of the data: Preview of the data

I created 5 series (one for each year) per variable (30 in total) and I'm getting the expected output but using MANY lines of code.

What is the best way to achieve this using less lines of code?

This is an example how I created the series:

CL2014 = data_total['Charity Lottery'].where(data_total['Date'].dt.year == 2014)[0:12]

CL2015 = data_total['Charity Lottery'].where(data_total['Date'].dt.year == 2015)[12:24]

This is an example of how I'm plotting the series: axCL.plot(xvals, CL2014)

axCL.plot(xvals, CL2015)

axCL.plot(xvals, CL2016)

axCL.plot(xvals, CL2017)

axCL.plot(xvals, CL2018)

There's no need to litter your namespace with 30 variables. Seaborn makes the job very easy but you need to normalize your dataframe first. This is what "normalized" or "unpivoted" looks like (Seaborn calls this "long form"):

Date        variable         value
2014-01-01  Charity Lottery  ...
2014-01-01  Racecourse       ...
2014-04-01  Bingo Halls      ...
2014-04-01  Casino           ...

Your screenshot is a "pivoted" or "wide form" dataframe.

df_plot = pd.melt(df, id_vars='Date')
df_plot['Year'] = df_plot['Date'].dt.year
df_plot['Month'] = df_plot['Date'].dt.strftime('%b')

import seaborn as sns
plot = sns.catplot(data=df_plot, x='Month', y='value',
                   row='Year', col='variable', kind='bar',
                   sharex=False)
plot.savefig('figure.png', dpi=300)

Result (all numbers are randomly generated):

Seaborn result