Visualizing seasonal patterns

As we will learn in Chapter XXX, seasonality plays a very important role in time series analysis. By seasonality, we mean the presence of patterns that occur at regular intervals (shorter than a year). For example, imagine the sales of ice creams, which most likely experience a peak in the summer months, while the sales decrease in winter. And such patterns can be seen year over year. We show how to use the line plot with a slight twist to efficiently investigate such patterns.

In this recipe, we will visually investigate seasonal patterns in the US unemployment rate from the years 2014-2019.

How to do it…

Execute the following steps to create a line plot showing seasonal patterns.

1. Import the libraries and authenticate:

import pandas as pd
import quandl
import seaborn as sns
 quandl.ApiConfig.api_key = "YOUR_KEY_HERE"

1. Download and display unemployment data from Quandl:

df = (
    quandl.get(dataset=" FRED/UNRATENSA",
  ...