Multi-indexing plotting with Matplotlib

Question

I am trying to graph multi indexing plot using matplotlib. However, I was struggling to find the exact code from the previously answered code. Can anyone assist me how can I produce similar graph.

import pandas as pd
import matplotlib.pyplot as plt
import pylab as pl 
import numpy as np
import pandas 

xls_filename = "abc.xlsx"
f = pandas.ExcelFile(xls_filename)
df = f.parse("Sheet1", index_col='Year' and 'Month')
f.close()

matplotlib.rcParams.update({'font.size': 18})  # Font size of x and y-axis
df.plot(kind= 'bar', alpha=0.70)

It is not indexing as I wanted and not produced the graph as expected as well. Help appreciated.

Uğur Güney · Accepted Answer · 2016-08-05 19:19:23Z

1

I created a DataFrame from some of the values I see on your attached plot and plotted it.

index = pd.MultiIndex.from_tuples(tuples=[(2011, ), (2012, ), (2016, 'M'), (2016, 'J')], names=['year', 'month'])
df = pd.DataFrame(index=index, data={'1': [10, 140, 6, 9], '2': [23, 31, 4, 5], '3': [33, 23, 1, 1]})
df.plot(kind='bar')

This is the outcome

where the DataFrame is this

answered Aug 5, 2016 at 19:19

Uğur Güney

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3 Comments

saltymisty73 Over a year ago

Hi @Uğur Güney, thanks. Any idea how to eliminate the NaN from the graph. I tried df[~np.isnan(df)] where df is the current dataframe.

Uğur Güney Over a year ago

Hi! np.isnan(df) or df.isnan() checks only the values of a dataframe, not its indices. And if you look at the month level index via df.index.levels[1] you see that there are no None's in there. I guess those NaNs appear only when the df table is displayed. I put single quotes to month section instead of leaving it empty when creating the tuples: tuples=[(2011, ''), (2012, ''), (2016, 'M'), (2016, 'J')] Still not a nice solution but at least you don't see the word "NaN" on the plot.

saltymisty73 Over a year ago

hmm...Thats interesting. I did try the similar to avoid NaN, however still the bracket appear on the graph. But, your method gave an idea to produce a graph like the above.

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