Exploratory data analysis with sweetviz

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“Exploratory Data Analysis (EDA) is an analysis approach that identifies general patterns in the data. These patterns include outliers and features of the data that might be unexpected. EDA is an important first step in any data analysis.” 1

“Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Output is a fully self-contained HTML application.”

Installation

Before installing Sweetviz, you need to ensure that Python is installed on your system. You can check this by opening your command line or terminal and running the following command:

python --version

If Python is installed, this command will display the version number. For example, you might see something like Python 3.8.10. If Python is not installed, you can download and install it from the official Python website.

Once Python is installed, you can proceed to install Sweetviz using pip. Run the following command in your command line or terminal:

pip install sweetviz

Basic Program

Once Sweetviz is installed, you can create a simple program to generate a data report. We’ll use the Titanic dataset for this example.

import pandas as pd
import sweetviz as sv

# Load the dataset
data = pd.read_csv('titanic.csv')
# Generate the Sweetviz report
report = sv.analyze(data)
# Display the report in the browser
report.show_html()

Explanation of the Code

1. Import Libraries: Import the necessary libraries, pandas for data manipulation and sweetviz for generating the report.
2. Load Dataset: Read the Titanic dataset into a Pandas DataFrame.
3. Generate Report: Use Sweetviz’s analyze function to create a report based on the DataFrame.
4. Show Report: Generate an HTML report that is automatically opened in your web browser.

Output

After running the script, Sweetviz will generate a self-contained HTML report and open it in your default web browser. The report provides visualisations and analysis of your dataset.

Resources

To further enhance your understanding and usage of Sweetviz and Python scripts, here are some additional resources:

• Download the dataset used in this example: https://github.com/datasciencedojo/datasets/blob/master/titanic.csv
• A comprehensive guide on running Python scripts, useful for beginners: https://www.knowledgehut.com/blog/programming/run-python-scripts#how-to-run-python-script-by-the-interpreter

Conclusion

Sweetviz is a powerful tool that simplifies the process of exploratory data analysis by generating interactive reports. By following the steps outlined in this article, you can quickly start analysing your datasets and gain valuable insights. Feel free to explore more features and customise your reports to suit your needs.