A practical tutorial on essential Pandas functions for data exploration, demonstrating key methods like head(), tail(), describe(), and value_counts() using a sample order dataset. The article provide
s code examples and explanations for each function, helping analysts efficiently understand and analyze their data.
Reasons to Read -- Learn:
how to create realistic sample datasets using Python and Faker, which you can use for practicing data analysis techniques without requiring real data.
10 essential Pandas functions that will help you quickly understand your dataset's structure, statistical properties, and unique values, improving your data exploration efficiency.
practical code examples of implementing Pandas functions on a real-world order dataset, allowing you to immediately apply these techniques to your own data analysis projects.
publisher: @tubelwj
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