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Time Series in Python

Updated 03/2026
Gain the skills you need to manipulate, interpret, and visualize time series data in Python, using pandas, NumPy, and Matplotlib.
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PythonProbability & Statistics20 hr28,538

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Track Description

Time Series in Python

Time series data is one of the most common data types and understanding how to work with it is a critical data science skill if you want to make predictions and report on trends. In this track, you'll learn how to manipulate time series data using pandas, work with statistical libraries including NumPy and statsmodels to analyze data, and develop your visualization skills using Matplotlib, SciPy, and seaborn. You'll then apply your time series skills using real-world data, including financial stock data, UFO sightings, CO2 levels in Maui, monthly candy production in the US, and heartbeat sounds. By the end of this track, you'll know how to forecast the future using ARIMA class models and generate predictions and insights using machine learning models.

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Manipulating Time Series Data in Python

    In this course you'll learn the basics of working with time series data.

  • Project

    bonus

    Time Series Analysis for Transportation

    Explore transportation time series data analysis to uncover patterns and forecast travel costs.

Time Series in Python
5 Courses
Track
Complete

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FAQs

Is this Track suitable for beginners?

Yes, this track is suitable for beginners as the courses are designed to build your knowledge and skills from the ground up, allowing you to progress at your own pace.

What is the programming language of this Track?

The programming language used in this track is Python.

Which jobs will benefit from this Track?

This track will be beneficial to data scientists, data engineers, data analysts, and software developers looking to gain experience in working with time series data.

How will this Track prepare me for my career?

This track will equip you with the skills and knowledge you need to effectively work with time series data. You will also be exposed to a variety of techniques for analyzing and visualizing data, which will be invaluable for your career.

How long does it take to complete this Track?

It takes approximately 20 hours to complete this track.

What's the difference between a skill track and a career track?

The main difference between a skill track and a career track is that a skill track focuses on building practical skills in a particular area, while a career track focuses on gaining qualifications and preparation for a certain job.

Who should create this Track?

This Track was created by DataCamp's industry experts with vast experience in working with time series data.

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