In computer programming, pandas is a software library written for the Python programming language for data manipulation and analysis. It is primarily used for data cleaning and preparation through the use of dataframes and series. In particular, it offers data structures and operations for manipulating numerical tables and time series. It is a free software anyone can download.

Pandas

NumPy, which stands for Numerical Python, is a Python library that contains n-dimensional arrays and tools for processing those arrays.

NumPy

The SciPy library is one of the core packages that make up the SciPy stack. It provides many user-friendly and efficient numerical routines, such as routines for numerical integration, interpolation, optimization, linear algebra, and statistics. SciPy is NumPy extension of Python.

-Interacting with NumPy
-Linear Algebra with SciPy

SciPy Library

University of Michigan - Ann Arbor

Python's data science libraries can be broken down into three different categories:
- Data Mining
- Data Processing and Modeling
- Data Visualization

Categorizing Python Libraries for DS

https://www.dataquest.io/blog/15-python-libraries-for-data-science/

Python Libraries for Data Science

Data Mining Libraries

•Data mining: Obtaining data that can be used to deduce conclusions.
•Data processing and modeling: Cleaning extracted data in order to prepare it for analysis and processing this cleaned data in order to reach conclusions. 
•Data visualization: Visually depicting data in various forms allowing for easy interpretation of conclusions.



Defining the Different Library Types for Data Science

The rapid development of Transformers have brought a new wave of powerful tools to natural language processing. These models are large and very expensive to train, so pre-trained versions are shared and leveraged by researchers and practitioners.    
  
Hugging Face offers a wide variety of pre-trained transformers as open-source libraries, and you can incorporate these with only one line of code.  

The Transformer in NLP is a novel architecture that aims to solve sequence-to-sequence tasks while handling long-range dependencies with ease. The Transformer was proposed in the paper Attention Is All You Need. It is recommended reading for anyone interested in NLP.

Hugging Face transformers

Data visualization tools, such as seaborn, Bokeh, and matplotlib, are essential for manually inspecting datasets. By plotting the data, practitioners can visually identify underlying data quality issues—like extreme outliers or recording errors—and develop an intuition for the type of problems they may need to address before feeding data into a model.

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