# Visualizing Time Series Data in Python

Visualize seasonality, trends and other patterns in your time series data.

4 Hours17 Videos59 Exercises16,231 Learners
4850 XP

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## Course Description

Time series data is omnipresent in the field of Data Science. Whether it is analyzing business trends, forecasting company revenue or exploring customer behavior, every data scientist is likely to encounter time series data at some point during their work. To get you started on working with time series data, this course will provide practical knowledge on visualizing time series data using Python.

1. 1

### Line Plots

Free

You will learn how to leverage basic plottings tools in Python, and how to annotate and personalize your time series plots. By the end of this chapter, you will be able to take any static dataset and produce compelling plots of your data.

Welcome to the course!
50 xp
100 xp
Test whether your data is of the correct type
100 xp
50 xp
100 xp
Specify plot styles
100 xp
Display and label plots
100 xp
50 xp
Subset time series data
100 xp
100 xp
100 xp
2. 2

### Summary Statistics and Diagnostics

In this chapter, you will gain a deeper understanding of your time series data by computing summary statistics and plotting aggregated views of your data.

3. 3

### Seasonality, Trend and Noise

You will go beyond summary statistics by learning about autocorrelation and partial autocorrelation plots. You will also learn how to automatically detect seasonality, trend and noise in your time series data.

4. 4

### Work with Multiple Time Series

In the field of Data Science, it is common to be involved in projects where multiple time series need to be studied simultaneously. In this chapter, we will show you how to plot multiple time series at once, and how to discover and describe relationships between multiple time series.

5. 5

### Case Study: Unemployment Rate

This chapter will give you a chance to practice all the concepts covered in the course. You will visualize the unemployment rate in the US from 2000 to 2010.

In the following tracks

Time Series

Collaborators

#### Thomas Vincent

Head of Data Science at Getty Images

Thomas is an experienced statistician and programmer who is passionate about developing tools and pipelines to discover and retrieve underlying phenomenons and patterns in modern-day datasets. He enjoys applying his statistical skills to solve practical problems and blogs about his analyses at tlfvincent.github.io.

## What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden