Plotting a Crosstab Table into a Pie Chart using Pandas and Plotly

In this article, we will explore how to plot a crosstab table from a pandas DataFrame into a pie chart. We will use the crosstab function from pandas to create the crosstab table and then use the Plotly library to plot it as a pie chart.

Understanding the Basics of Crosstab Tables

A crosstab table is a table that displays data in a format that allows for easy comparison between two variables. In this case, we have a DataFrame with three columns: event_type, date, and number_person. The crosstab function will be used to create a new DataFrame that shows the count of number_person for each combination of year_month and event_type.

Understanding the Basics of Pie Charts

A pie chart is a circular graph that displays how different categories contribute to a whole. In this case, we want to use the crosstab table as data for our pie chart.

Creating the DataFrame

# Import necessary libraries
import pandas as pd

# Create a sample DataFrame
data = {
    'event_type': ['watch movie', 'stay at home', 'watch movie', 'swimming', 'stay at home', 'watch movie', 'watch movie', 'stay at home', 'swimming', 'camping', 'watch movie'],
    'date': ['2020-08-14', '2020-08-14', '2020-08-14', '2020-08-14', '2020-08-14', '2019-06-14', '2020-08-14', '2020-08-14', '2020-08-14', '2020-08-14', '2019-09-14'],
    'event_mohafaza': ['loc1', 'loc3', 'loc2', 'loc4', 'loc2', 'loc5', 'loc2', 'loc1', 'loc4', 'loc1', 'loc2'],
    'number_person': [25, 32, 45, 12, 45, 22, 10, 44, 27, 21, 17]
}

df = pd.DataFrame(data)

Creating the Crosstab Table

# Create a crosstab table using the pandas crosstab function
ct = pd.crosstab(df['year_month'], df['event_type'])
print(ct)

# Convert the date column to datetime format
df['date'] = pd.to_datetime(df['date'])

# Create the labels for the pie chart
df['labels'] = df['year_month'].astype(str) + ' ' + df['event_type']

Plotting the Pie Chart

import plotly.graph_objects as go

fig = go.Figure(data=[go.Pie(labels=df['labels'], hoverinfo='label+percent', values=df['number_person'], textposition='outside', rotation=90)])

# Update the layout of the figure
fig.update_layout(title="Percentage of events",
                  font=dict(family='Arial', size=12, color='#909090'),
                  legend=dict(x=0.9, y=0.5)
        )

# Display the figure
fig.show()

This code will create a pie chart that displays the count of number_person for each combination of year_month and event_type.

Discussion

The crosstab function is a powerful tool in pandas that allows us to easily create crosstab tables from our DataFrames. The resulting table can be used as data for various types of plots, including pie charts.

In this article, we used the Plotly library to plot the crosstab table as a pie chart. This allowed us to visualize the data in a clear and concise manner.

The code provided above is a good starting point for anyone looking to create a pie chart from a crosstab table using pandas and Plotly. However, it’s always a good idea to customize your plot according to your needs and experiment with different layouts and designs.

Common Issues and Troubleshooting

Data Types: Make sure that the data types of the columns used in the crosstab function match the expected data type. For example, if you are using a string column as the first argument, make sure it is a string.
Missing Values: If there are missing values in your DataFrame, they will be treated as empty strings in the resulting crosstab table.
Labeling: Make sure that the labels used in the Pie function match the data in the table.

Conclusion

In this article, we explored how to plot a crosstab table from a pandas DataFrame into a pie chart using the Plotly library. We discussed the basics of crosstab tables and pie charts and provided example code to get you started. With practice and experimentation, you can create beautiful and informative plots that help you communicate complex data insights to your audience.

Additional Resources

Last modified on 2024-02-23