Multiple boxplots on the same graph-CodePudding

I need to create multiple boxplots on the same graph. The sports are 3. I need to obtain 3 boxplots on the same graph of each sport, with a specific variable on the y-axis. I need to be able to change the variable. The variable for each student is registered various times and is given by the mean of the 3 largest numbers. I have 30 students identified with an ID (that goes from 1 to 30). Each student does only one sport. This is what I wrote but clearly it doesn't work. Can someone help? I hope my explanation made sense.

def boxplot(sport, variable):
    list=[]
    for l in range(1,31):
        g = df[(df.ID == l) & (df.sport == sport)][variable].nlargest(n=3).mean()
        list.append(g)
    my_dict = {f'Boxplot for {variable} in {sport}': list}
    fig, ax = plt.subplots()
    ax.boxplot(my_dict.values())
    ax.set_xticklabels(my_dict.keys())
    plt.show()

CodePudding user response：

Here's one way to do it.

import plotly.express as px

df = px.data.tips()

fig = px.box(df, x="day", y="total_bill", color="smoker")
fig.update_traces(quartilemethod="exclusive") # or "inclusive", or "linear" by default
fig.show()

If you data is not melted or stacked, you can change the layout like this.

Here is one final update. Make sure the y-axis is numeric...

import pandas as pd
import plotly.express as px
import matplotlib.pyplot as plot

df = px.data.tips()
df=pd.DataFrame(df)
print(type(df))
df.head()
df.columns = ['total_bill', 'tip', 'sex', 'smoker', 'day', 'time', 'size']

b_plot = df.boxplot(column = ['tip','size','total_bill']) 
b_plot.plot()
plot.show()