python pandas apply groupby

Опубликовано: 08 Октябрь 2024
на канале: CodeLive

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pandas is a powerful data manipulation library in python, and it provides a versatile apply function along with the groupby function to perform operations on grouped data. in this tutorial, we'll explore how to use apply with groupby in pandas with practical examples.
the apply function in pandas is used to apply a function along the axis of a dataframe. it can be applied to both series and dataframe objects.
the groupby function in pandas is used to split the data into groups based on some criteria and then apply a function to each group independently.
let's start with a basic example of grouping data and applying a summary function:
this will output:
you can use apply in combination with groupby to apply custom functions. let's say we want to find the range (max - min) for each group:
this will output:
you can apply functions to multiple columns using groupby. let's calculate the sum of values and the average of another column for each category:
this will output:
when working with real-world data, missing values are common. pandas handles missing data gracefully. let's see how to use apply and groupby with missing data:
in this tutorial, we covered the basics of using apply with groupby in pandas. you've learned how to group data, apply custom functions, work with multiple columns, and handle missing data. this knowledge is essential for efficiently analyzing and transforming data using pandas. experiment with different datasets and functions to deepen your understanding. happy coding!
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