python pandas subset multiple conditions
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Certainly! In this tutorial, I'll guide you through the process of subsetting data using multiple conditions in Python with the help of the Pandas library. We'll cover the basics of using the DataFrame and Series objects to filter data based on various conditions.
If you haven't installed Pandas yet, you can do so using the following command:
Once installed, import the Pandas library in your Python script or Jupyter Notebook:
Let's start by creating a sample DataFrame for demonstration purposes:
This will create a DataFrame with columns 'Name', 'Age', 'City', and 'Salary'.
Now, let's learn how to subset data based on multiple conditions. We'll use logical operators (& for AND, | for OR, and ~ for NOT) to combine conditions.
This will select rows where the age is greater than 25 and the city is 'New York'.
This will select rows where the salary is greater than 70000 or the name starts with 'A'.
You can also use parentheses to group conditions and create more complex filters.
This example selects rows where the age is greater than 25 or the salary is greater than 70000, excluding rows where the city is either 'Chicago' or 'Miami'.
By following these steps, you can effectively subset data in Pandas using multiple conditions. This approach provides flexibility and allows you to filter data based on various criteria in your DataFrame.
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