How to make an interactive bar plot with seaborn and ipywidgets

Question

I have a dataset with athletes, their age-range and the year they competed:

import ipywidgets as widgets
from ipywidgets import interact  
import pandas as pd  
import matplotlib.pyplot as plt 
import seaborn as sns  
import numpy as np  

data = {'Name':['Tom', 'Nick', 'Chris', 'Jack'],
        'Age':['20-25', '19<', '>75', '20-25'], 
        'Year':[2019,2019,2018,2018], 
         'Count': [1,1,1,1]} 
df = pd.DataFrame(data)

Mind you, this is 1000s on entries long, but I didn't want to use that much space so I'm using a much simplified version.

I am trying to make an interactive bar plot with ipywidgets using that data.

age = ['20-25', '19<', '>75','20-25']
@interact(Age = age)
def f(Age):      
    df2= df[df['age'].str.contains(Age)].groupby('Year').sum() 
    df2['year'] = ['2018','2019']
    return sns.barplot(x="Year", y="Count", data=df2)

The x axis is the year, the y axis is the number of participants that year and you can interactively filter via a scroll bar and see the number of participants by age range of your choosing.

I didn't know how to do that, so I tried to 'brute force it' and added a count column of 1, so that I would get the total number of participants even when the dataset got filtered. I also brute forced the years, but some age ranges don't compete in all years so It breaks and it's not working.

Age is all the various options of age range, I put them all in a list.

Trenton McKinney · Accepted Answer · 2021-12-02T21:48:32.233

Fix the spelling issues, since you are interchanging upper and lowercase. Also none of the values in the dataframe are numeric (both issue fixed in an edit to the OP).
Create age with age = df.Age.unique()
Reset the index instead of using df2['year'] = ['2018','2019']

age = df.Age.unique()
@interact(Age = age)
def f(Age):      
    df2 = df[df['Age'].str.contains(Age)].groupby('Year').count().reset_index()
    return sns.barplot(x="Year", y="Count", data=df2)

Without adding a 'Count' column
There's no need to add a 'Count' column to the dataframe because .groupby('Year').count() will provide the count for each existing column, in which case y= can be 'Name' or 'Age', but then the ylabel would need to be changed.

age = df.Age.unique()
@interact(Age = age)
def f(Age):      
    df2 = df[df['Age'].str.contains(Age)].groupby('Year').count().reset_index()
    p = sns.barplot(x="Year", y="Age", data=df2)
    p.set_ylabel('Count')
    return p

Use seaborn.countplot instead

age = df.Age.unique()
@interact(Age = age)
def f(Age):      
    data = df[df['Age'].str.contains(Age)]
    return sns.countplot(data=data, x='Year')

How to make an interactive bar plot with seaborn and ipywidgets

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