course
Data Manipulation with pandas
GrundläggandeFärdighetsnivå
Uppdaterad 2025-09Börja Kursen Gratis
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PythonData Manipulation4 timmar15 videos56 exercises4,850 XP540K+Uttalande om prestation
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Discover Data Manipulation with pandas
With this course, you’ll learn why pandas is the world's most popular Python library, used for everything from data manipulation to data analysis. You’ll explore how to manipulate DataFrames, as you extract, filter, and transform real-world datasets for analysis.With pandas, you’ll explore all the core data science concepts. Using real-world data, including Walmart sales figures and global temperature time series, you’ll learn how to import, clean, calculate statistics, and create visualizations—using pandas to add to the power of Python.
Work with pandas Data to Explore Core Data Science Concepts
You’ll start by mastering the pandas basics, including how to inspect DataFrames and perform some fundamental manipulations. You’ll also learn about aggregating DataFrames, before moving on to slicing and indexing.You’ll wrap up the course by learning how to visualize the contents of your DataFrames, working with a dataset that contains weekly US avocado sales.
Learn to Manipulate DataFrames
By completing this pandas course, you’ll understand how to use this Python library for data manipulation. You’ll have an understanding of DataFrames and how to use them, as well as be able to visualize your data in Python.Förkunskapskrav
Intermediate Python1
Transforming DataFrames
Let’s master the pandas basics. Learn how to inspect DataFrames and perform fundamental manipulations, including sorting rows, subsetting, and adding new columns.
2
Aggregating DataFrames
In this chapter, you’ll calculate summary statistics on DataFrame columns, and master grouped summary statistics and pivot tables.
3
Slicing and Indexing DataFrames
Indexes are supercharged row and column names. Learn how they can be combined with slicing for powerful DataFrame subsetting.
4
Creating and Visualizing DataFrames
Learn to visualize the contents of your DataFrames, handle missing data values, and import data from and export data to CSV files.
Data Manipulation with pandas
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