NumPy, Pandas, Matplotlib, and Seaborn Explained for Beginners.

NumPy, Pandas, Matplotlib, and Seaborn Explained for Beginners.

Gaurav Pandey

Published on Sep 15, 2021

2 min read

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As we know that NumPy, Pandas, Matplotlib, and Seaborn are essential libraries for Data Science and Machine Learning. So, Here is a small Introduction to these Data Libraries.

1. NumPy

NumPy stands for Numerical Python. It is a Python Package for mathematical and logical operations on arrays in Python. It is used in most Python Projects Involving managing data sets. It is different from Lists.

  • NumPy can contain only one type of data, hence not flexible with data types.
  • It is widely used for Arithmetic operations.
  • It Cannot be directly Initialize. It can be operated with the NumPy package only.
  • In NumPy functions like concatenation, appending, etc, are not trivially possible with arrays.
  • Arrays take less memory space.

2. Pandas

Pandas is a library in Python for Data Manipulation and analysis. It offers data structures and operations for manipulating tables and time-series data. Pandas is built on top of NumPy and can be integrated with third parties libraries.

Pandas is well suited for many different kinds of data:

  • Tabular data such as SQL table or Excel
  • Time series data
  • Any form of data sets - labeled or unlabelled

The two data structures of Pandas are:

  • Series (1-D)
  • DataFrame (2-D)

Few use cases of Pandas include:

  • Handling of missing data or NaN
  • Columns can be inserted and deleted from the data frame
  • Slicing, indexing, and subsetting of large data sets
  • Managing data sets - joining and pivoting

3. Matplotlib

Matplotlib is a visualization library built on NumPy in Python for 2-D plots of arrays. It is useful to visualize and interpret large data sets. Matplotlib comes with a variety of inbuilt plots and offers lots of flexibility.

4. Seaborn

Seaborn is a Python data visualization library based on Matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.

Thank You

I hope you understand well, this is a short introduction to NumPy, Matplotlib, Pandas, and Seaborn.

I hope you found it useful. If you did make sure you follow me on Twitter @gaurtvin .

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