# Visualizing Time Series Data in Python

4.5+
12 reviews
Intermediate

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

4 Hours17 Videos59 Exercises

or

## 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.

Play Chapter Now
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 with Python

Collaborators

Thomas Vincent

Head of Data Science at Getty Images

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## Don’t just take our word for it

*4.5
from 12 reviews
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• K K.
11 months

It is a great course for a beginner.

• Dmitri G.
11 months

Was very fun

• Martin G.
12 months

Great course for begginers

• David T.

One of the best courses on datacamp if you are interested in data analysis. Well presented and great useful content.

• Rachel Z.
over 1 year

This is a great course. I thoroughly enjoyed it and learnt a lot about plotting time series data using Matplotlib.

"It is a great course for a beginner."

K K.

"Was very fun"

Dmitri G.

"Great course for begginers"

Martin G.