Matplotlib charts are an eyesore by default — right here’s what to do about it.
Information visualization presents a lot deeper insights than uncooked, numerical information.
Nevertheless, creating interesting charts takes effort and time. Matplotlib is a de facto commonplace library for information visualization in Python. It’s easy, has been used for many years, and something you’re in search of is one internet search away.
But it surely’s not all sunshine and rainbows. Matplotlib visualizations look horrendous by default, and also you as a knowledge skilled must flip many cogs to get one thing usable. Getting you there’s the aim of right this moment’s article.
By the top, you’ll have a code snippet you may follow any Jupyter Pocket book.
You received’t must obtain any dataset to observe alongside. You’ll create an artificial time sequence dataset with rising pattern and repeatable seasonal patterns:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt# Single season multiplier elements - for seasonality impact
seasonal_multipliers = [1.1, 1.3, 1.2, 1.5, 1.9, 2.3, 2.1, 2.8, 2.0, 1.7, 1.5, 1.2]…