This is a project for a data science program. A huge dataset was provided for analysis. Research questions were determined. Methodology and lessons learned were documented. Data was analyzed and graphs were created using Python programming language. A final report were generated.

To better utilize energy, the UK government needs energy providers to introduce smart meters in each home in England, Wales and Scotland. This means more than 26 million homes providing data for the energy providers; the goal is that each home has a smart meter by 2020.

In this dataset, you will find real data from the London energy data warehouse, that contains the energy consumption readings for a sample of 5,567 London Households that took part in a pilot project between November 2011 and February 2014. There are several files in this dataset which are provided as a very large zip file:

a) informations_households.csv : this file that contains all the information on the households in the panel (their acorn group, their tariff) and in which block.csv.gz file their data are stored

b) Several block_x.csv.gz files: Zipped files that contain the smart meter data of some specific household (specified in the informations_household_update.csv). The Linux command gunzip will unzip these files. They are LARGE!! (I put the unzipped files in the repository also.)

c) acorn_details.csv : Details on the acorn groups and their profile of the people in the group. You can find a fuller explanation on the CACI website.

d) A pdf document describing the ACORN approach.