How to plot a bar graph from a pandas series?

Question

Consider my series as below: First column is article_id and the second column is frequency count.

article_id   1         39  2         49  3        187  4        159  5        158          ...   16947     14  16948      7  16976      2  16977      1  16978      1  16980      1   Name: article_id, dtype: int64 

I got this series from a dataframe with the following command:

logs.loc[logs['article_id'] <= 17029].groupby('article_id')['article_id'].count() 

logs is the dataframe here and article_id is one of the columns in it.

How do I plot a bar chart(using Matlplotlib) such that the article_id is on the X-axis and the frequency count on the Y-axis ?

My natural instinct was to convert it into a list using .tolist() but that doesn't preserve the article_id.

Answer 1

IIUC you need Series.plot.bar:

#pandas 0.17.0 and above s.plot.bar() #pandas below 0.17.0 s.plot('bar') 

Sample:

import pandas as pd import matplotlib.pyplot as plt  s = pd.Series({16976: 2, 1: 39, 2: 49, 3: 187, 4: 159,                 5: 158, 16947: 14, 16977: 1, 16948: 7, 16978: 1, 16980: 1},                name='article_id') print (s) 1         39 2         49 3        187 4        159 5        158 16947     14 16948      7 16976      2 16977      1 16978      1 16980      1 Name: article_id, dtype: int64   s.plot.bar()  plt.show() 

Answer 2

The new pandas API suggests the following way:

import pandas as pd  s = pd.Series({16976: 2, 1: 39, 2: 49, 3: 187, 4: 159,                 5: 158, 16947: 14, 16977: 1, 16948: 7, 16978: 1, 16980: 1},                name='article_id')  s.plot(kind="bar", figsize=(20,10)) 

If you are working on Jupyter, you don't need the matplotlib library.