This is part of the “Intro to Data Analysis with Python” series of posts, with content from the Enki app. If you stumbled upon this, you could start from the beginning.
pandas is an open-source data manipulation tool. It is fast, powerful, and flexible.
It offers an efficient DataFrame object used for data manipulation.
With DataFrames you can import, transform, manipulate, clean, and analyze datasets.
Think of an DataFrame as a library with empty shelves. When we import a dataset into the DataFrame we fill up the shelves with books(data).
After we fill up our library, we can clean it up and analyze it.
For instance, we could search through the library, remove the books we don't like, split books into different shelves by organizing them into categories, sort, count, remove duplicates, and more.
pandas is built on the numerical python library called numpy.
To be able to use pandas, you will have to install numpy first.
Check out the footnote to learn how to install pandas through pip or conda.
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