pandasmatplotlibplotipythonseries

How to plot a bar graph from a pandas series?


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.


Solution

  • 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()
    

    graph