Time Serious Forecast using Python
Introduction: Time series are one of the most common things encountered in daily life. For example Financial prices, weather , home energy usage, and even weight are all of data that can be collected at regular intervals. In the series collect the data points at constant interval time which leads the data have the dependency with the time . The Time series has the sudden increase or decrease in certain intervals(Month, day, hour ...). Which will implies the non stationary in the data modelling. The sudden increase we may called like trends , seasonality and so on. Data Analysis in Time series: In python, we have the great library Pandas to handle the time series objects, particularly the datatime64[ns] class which stores time information and allows us to perform some operations really fast. In the below example we are going to use the AirPassanger.csv data set. Initially, we have to load the necessary libraries import pandas as pd import numpy as np im