Step-by-Step Data Cleaning in Python with Pandas | Jupyter Notebook Tutorial | CSV to visualization

A Step-by-Step Data Cleaning in Python: Removing Duplicates, Nulls & Visualizing Data. Master Data Cleaning with Python Pandas: CSV File to Visualization in Jupyter Notebook.
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In this video, I’ll show you how to clean data using Python, Pandas, and Jupyter Notebook. We'll start by loading a CSV file, then tackle common data issues like duplicates and missing values. I'll also guide you through dropping unnecessary data and creating visualizations such as pie charts and bar charts. Plus, we’ll create a new variable to categorize age groups, giving you practical tools for effective data cleaning.
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The dataset used is "customer data on purchases" for a clothing store.
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===Great Books For Mastering Data Science and Data Cleaning===
Python For Data Analysis: amzn.to/4dQUOaF
Python Data Science HandBook: amzn.to/3BV6hsk
Hands On Machine Learning with Scikit-Learn & TensorFlow: amzn.to/4h8IxRS
Python Machine Learning by Sebastian Raschka: amzn.to/401eIMU
Modern Python Cookbook: updated: amzn.to/3BV6sE0
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