pandas dataframe count distinct group by

Title: Pandas DataFrame: Count Distinct with GroupBy - A Comprehensive Tutorial
Introduction:
Pandas is a powerful data manipulation library in Python, and it provides a wide range of functionalities for working with tabular data. In this tutorial, we'll explore how to use Pandas to perform a count of distinct values with the GroupBy operation. This is a common task when dealing with datasets, especially when you need to analyze data across different groups.
Prerequisites:
Make sure you have Pandas installed in your Python environment. If not, you can install it using:
Example Dataset:
Let's start by creating a sample dataset to work with. For this tutorial, we'll use a hypothetical sales dataset with columns 'Region', 'Product', and 'Sales'.
Now, let's dive into the steps to count distinct values with GroupBy.
Step 1: Import the Pandas library
Step 2: Create a DataFrame
Step 3: Use GroupBy and nunique() for Counting Distinct Values
Output:
Explanation:
Conclusion:
Counting distinct values with GroupBy in Pandas is a powerful technique for analyzing datasets with categorical variables. In this tutorial, we've covered the basic steps using a simple example. You can apply the same principles to more complex datasets and adapt the code to suit your specific analysis requirements.
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