Filtering
Learn about filtering, its techniques, and its best practices.
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Introduction
Filtering refers to the process of finding specific items in a list or a table. This process lets us choose only rows or columns that meet certain conditions. For example, if we have a table of students and their grades, we can use filtering to select only the students who got an A grade. Or, we can use filtering to select only the students’ names and grades, not their ages.
Reasons to perform filtering
There are many reasons why we perform filtering using pandas. Here are a few reasons why filtering is crucial when working with data, along with a few examples for each point:
- We can use it for data cleaning: Filtering can identify and remove invalid or missing values from our data, improving the quality and accuracy of our analysis. For example, we might filter a dataset to remove rows with null values or outliers.
- We can improve efficiency:
