9 Python Basics Pandas
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What is Pandas in Python?
Pandas is an open source Python package that is most widely used for data science/data analysis and machine learning tasks. It is built on top of another package named Numpy, which provides support for multi-dimensional arrays. As one of the most popular data wrangling packages, Pandas works well with many other data science modules inside the Python ecosystem, and is typically included in every Python distribution, from those that come with your operating system to commercial vendor distributions.
What Can you Do with Data Frames using Pandas?
Pandas makes it simple to do many of the time consuming, repetitive tasks associated with working with data, including:
Data cleansing
Data fill
Data normalization
Merges and joins
Data visualization
Statistical analysis
Data inspection
Loading and saving data
And much more
In fact, with Pandas, you can do everything that makes world-leading data scientists vote Pandas as the best data analysis and manipulation tool available.
Pandas Basics - Pandas DataFrames
Pandas is a high-level data manipulation tool developed by Wes McKinney. It is built on the Numpy package and its key data structure is called the DataFrame. DataFrames allow you to store and manipulate tabular data in rows of observations and columns of variables.