Popular Python libraries used in Data Science

 Scientific Computing and Statistics

NumPy (Numerical Python)—Python does not have a built-in array data structure. It uses lists, which are convenient but relatively slow. NumPy provides the high-performance ndarray data structure to represent lists and matrices, and it also provides routines for processing such data structures.

SciPy (Scientific Python)—Built on NumPy, SciPy adds routines for scientific processing, such as integrals, differential equations, additional matrix processing and more. scipy.org controls SciPy and NumPy.

StatsModels—Provides support for estimations of statistical models, statistical tests and statistical data exploration.

Data Manipulation and Analysis :

Pandas—An extremely popular library for data manipulations. Pandas makes abundant use of NumPy’s ndarray. Its two key data structures are Series (one dimensional) and DataFrames (two dimensional).

Visualization :

Matplotlib—A highly customizable visualization and plotting library. Supported plots include regular, scatter, bar, contour, pie, quiver, grid, polar axis, 3D and text.

Seaborn—A higher-level visualization library built on Matplotlib. Seaborn adds a

nicer look and feel, additional visualizations and enables you to create visualizations

with less code.

Machine Learning, Deep Learning, and Reinforcement Learning

scikit learn— Top machine learning library. Machine learning is a subset of AI. Deep learning is a subset of machine learning that focuses on neural networks.

TensorFlow—From Google, this is the most widely used deep learning library. TensorFlow works with GPUs (graphics processing units) or Google’s custom TPUs (Tensor processing units) for performance. TensorFlow is important in AI and big data analytics—where processing demands are huge. You’ll use the version of Keras that’s built into TensorFlow.

OpenAI Gym—A library and environment for developing, testing, and comparing reinforcement-learning algorithms.

Natural Language Processing (NLP)

NLTK (Natural Language Toolkit)—Used for natural language processing (NLP)

tasks.

TextBlob—An object-oriented NLP text-processing library built on the NLTK and pattern NLP libraries. TextBlob simplifies many NLP tasks.

Gensim—Similar to NLTK. Commonly used to build an index for a collection of documents, then determine how similar another document is to each of those in the index.