How to create count plot only for one value?

Question

I have a dataset that looks like this:

Date of     Waivered 
Issuance    Regulation  month   day     year    107.29  107.31  
29/12/2017  107.29      12.0    29.0    2017.0  1.0     0.0
29/12/2017  107.29      12.0    29.0    2017.0  1.0     0.0
29/12/2017  107.29      12.0    29.0    2017.0  1.0     0.0
28/12/2017  107.29      12.0    28.0    2017.0  1.0     0.0
27/12/2017  107.29      12.0    27.0    2017.0  1.0     0.0

The last two columns ('107.29' and '107.31') only have 0 or 1 as value.

I want to create a count plot, but limit it only to the 1 values, so excluding the 0 values. When I create a regular count plot, this is what I have got:

In this plot you can barely see the 1 values, so I would like to have the graph with only those. How can I achieve that?

I mean that I want to create a count plot that includes only the 1 values, without the 0. In the previous plot, you can see that the 1 values can barely be seen. — Nadav Kiani
– Nadav Kiani, Commented Feb 28, 2019 at 13:32

Ted Petrou · Accepted Answer · 2020-06-11 17:40:58Z

1

Use the normalize parameter to normalize the counts over any variable (or combination of variables with a tuple). You can also use True to normalize over the grand total of counts.

import dexplot as dxp

dxp.count('107.31', data=df, split='month', normalize='107.31')

edited Jun 11, 2020 at 17:40

Ted Petrou

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answered Feb 28, 2019 at 14:35

Abhishek Sharma Acharya

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Comments

kuzand · Accepted Answer · 2019-02-28 16:48:54Z

0

This will give you only the 1's at the column '107.31':

df1 = df[df['107.31'] == 1]

Then you can group it by month, count the 1's for each month and plot:

df1.groupby('month').size().plot(kind='bar')

edited Feb 28, 2019 at 16:48

answered Feb 28, 2019 at 14:39

kuzand

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