In order to extract meaningful insights from time-series data, we have to extract statistics from it. These stats can be things like mean, variance, correlation, maximum value, and so on. These stats have to be computed on a rolling basis using a window. We use a predetermined window size and keep computing these stats. When we visualize the stats over time, we will see interesting patterns. Let's see how to extract these stats from time-series data.
Create a new Python file and import the following packages:
import numpy as np import matplotlib.pyplot as plt import pandas as pd from timeseries import read_data
Define the input filename:
# Input filename input_file = 'data_2D.txt'
Load the third and fourth ...