This lesson is still being designed and assembled (Pre-Alpha version)

Time Series Analysis of Smart Meter Power Consumption Data

This lesson is the first in a series of lessons focused on using Python to analyse time series data.

Prerequisites

Learners should be familiar with foundational concepts in Python, including data types and structures, loops, conditionals, and functions. Completion of a core Carpentries Python lesson (for example Software Carpentry’s Programming with Python), is recommended.

Learning Objectives

After following this lesson, learners will be able to:

  • Read and plot timeseries data using Python Pandas.
  • Group data and generate descriptive statistics.
  • Resample timeseries data using datetime indexing in Pandas.

Schedule

Setup Download files required for the lesson
00:00 1. Introduction What are common use cases for timeseries analysis?
00:25 2. Reading Data Files with Python How can we manipulate tabular data files in Python?
01:30 3. Subsetting Dataframes with PANDAS How can we filter and subset data in Python?
02:15 4. Summarizing Tabular Data with PANDAS How can we summarize large datasets?
03:00 5. Creating a Datetime Index with Pandas How can we visualize trends in time series?
04:00 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.