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

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 .

for more tweets on :

- Python
- Software Development
- Mathematics
- Machine Learning