1. Pandas:
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.
import pandas as pd
//To Read the Data sets:
dataset = pd.read_csv('Data.csv')
2.Numpy
NumPy is the fundamental package for scientific computing with Python. It contains among other things: 1: a powerful N-dimensional array object 2: sophisticated (broadcasting) functions 3: tools for integrating C/C++ and Fortran code 4: useful linear algebra, Fourier transform, and random number capabilities
import numpy as np3.matplotlib
Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK+
import matplotlib.pyplot as plt4.Scikit Learn
Scikit-learn is probably the most useful library for machine learning in Python. The sklearn library contains a lot of efficient tools for machine learning and statistical modeling including classification, regression, clustering and dimensionality reduction
import sklearn