Pandas Pyplot: Counting columns for scatter plot

Question

I have a data frame with following columns:

df = pd.read_csv('edtech.csv')
print(df.head())

   Unnamed: 0                                         Title      Date Country  \
0           3     Apple acquires edtech company LearnSprout  15-01-16      US   
1           9  LearnLaunch Accelerator launches new program  15-01-16      US   
2          15                   Flex Class raises financing  15-01-16   India   
3          16               Grovo raises Series C financing  15-01-16      US   
4          17                    Myly raises seed financing  15-01-16   India   

                          Segment  
0             Tools for Educators  
1     Accelerators and Incubators  
2  Adult and Continuing Education  
3               Platforms and LMS  
4                     Mobile Apps  
>>>

Now, I want to create a scatter plot by mapping 'Country' on one axis and 'Segment' on another. E.g. for US and 'Tools for Educator', there will be one dot on the chart.

How do I convert this dataframe, so that I have numbers, which I can render into a scatter plot? I am able to get the chart in Tableau through count, but don't know the exact working behind the same.

Would be grateful if anyone can help me out. TIA

What numbers do you want to plot? Country and Segment are catagorical — kezzos
– kezzos, Commented Nov 23, 2016 at 10:37
Hi @kezzos I want to plot their count against each other. E.g. US for Tools for Educator, and US for Mobile apps — chhibbz
– chhibbz, Commented Nov 24, 2016 at 3:35

Khris · Accepted Answer · 2016-11-23 11:52:22Z

1

I don't know if the possibility of creating a scatter plot with two non-numerical categorical variables exists, the closest I could get to the kind of thing you want is creating counts with groupby, reshaping the data with pivot, and making a heatmap using seaborn:

import pandas as pd
import seaborn as sns

df = pd.read_csv('edtech.csv')
dd = df[['Country','Segment','Title']]
gg = dd.groupby(['Country','Segment'],as_index=False).count().rename(columns={"Title":"Number"})
gp = gg.pivot(columns="Segment",index="Country",values="Number").fillna(0.0)
sns.heatmap(gp,cbar=False)

answered Nov 23, 2016 at 11:52

Khris

3,2323 gold badges39 silver badges61 bronze badges

Sign up to request clarification or add additional context in comments.

1 Comment

chhibbz Over a year ago

Thanks @Khris Though not exactly what I wanted, but it did work. Will create a pivot for count

Collectives™ on Stack Overflow

Pandas Pyplot: Counting columns for scatter plot

1 Answer 1

1 Comment

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

1 Comment

Your Answer

Sign up or log in

Post as a guest

Related