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I am trying to duplicate what a Seaborn countplot is able to do, but with a lineplot. Below is a code sample showing what countplot is doing:

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns

df=pd.DataFrame({
    'date' : ['2020-01-01', '2020-01-01', '2020-01-01', '2020-01-02', '2020-01-02', '2020-01-02', '2020-01-03'],
    'type' : ['A', 'B', 'B', 'B', 'A', 'A', 'C']
    })

sns.countplot(
    data=df, x=df['date'], hue=df['type'])
plt.show()

which produces this graph: countplot graph

I want to do the same thing, but with a line graph, so that x= date, y= amount of type for that date, and hue= type.

So my question is... Is this possible? I have tried with multiple different Seaborn graphs (relplot, lineplot, etc) and have not got this to work.

question from:https://stackoverflow.com/questions/65598557/plotting-categorial-data-as-a-lineplot-in-seaborn

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IIUC, you can do it by first get the size of each date and type with groupby.size and use lineplot with the transformed dataframe.

sns.lineplot(
    data=df.groupby(['date','type']).size().reset_index(name='count'), 
    x='date', y='count', hue='type')

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