Data Cleaning with pandas

Learn how to clean messy data with pandas. Discover how to handle missing values, fix text with regular expressions, remove outliers, and prepare reliable datasets for analysis.
Course details

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Real-world data arrives messy. Missing values, inconsistent text, and outliers can quietly skew your results. In this hands-on course, discover how to turn that raw data into clean, analysis-ready datasets with pandas. Start with pandas fundamentals, then move into the techniques data professionals rely on to prepare data with confidence. Explore how to work with pandas Series and DataFrames, select rows and columns with iloc and loc, and filter data with Boolean conditions. Learn how to clean and match text using regular expressions, handle missing data by dropping or filling values with statistical techniques, and reason about what outliers mean before you remove them. By the end of this course, you'll be prepared to diagnose data-quality issues and clean a dataset for reliable analysis. This intermediate-level course is an ideal fit for data analysts, data scientists, Python developers, and anyone who works with data.This course was created by Anaconda, Inc. We are pleased to host this training in our library.
Skills covered

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Pandas (Software), Data Cleaning, Python (Programming Language)
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