There are two Census datasets used in the labs:
Table of LSOA areas in Liverpool with population counts by World region. The table is derived from the CDRC Census data pack (see below). “Lab 1 - Extra” contains an in detail explanation of how the table is constructed.
Source: available here.
Collection of socio-demographic characteristics from the 2011 Census for the city of Liverpool. A detailed description of the dataset, as well as instructions as to how to download it are available on the source link.
Source: CDRC’s Census data pack for the city of Liverpool (UK). Available in this
link.
Instructions: you will need to be registered on the CDRC website, which is free and very easy. Once logged in, click on the link provided above and select “Download” on the dataset’s page.
Scores, ranks, and components of the 2015 Index of Multiple Deprivation (IMD). A detailed description of the dataset, as well as instructions as to how to download it are available on the source link.
Source: CDRC’s English Indices of Deprivation 2015 Geodata Pack for the city of Liverpool (UK). Available in this link.
Instructions: you will need to be registered on the CDRC website, which is free and very easy. Once logged in, click on the link provided above and select “Download” on the dataset’s page.
This is a compilation of spatial data about the city of Liverpool produced by the Ordnance Survey, distributed as open data, and provided by the CDRC. A detailed description of the dataset, as well as instructions as to how to download it are available on the source link.
Source: CDRC’s Geodata pack for the city of Liverpool (UK). Available in this link.
Instructions: you will need to be registered on the CDRC website, which is free and very easy. Once logged in, click on the link provided above and select “Download” on the dataset’s page.
Lab 2 includes a blurb on displaying raster data. To do that, it uses a file
from the Ordnance Survey that is available from the OS website:
https://www.ordnancesurvey.co.uk/opendatadownload/products.html
For convenience, the file is also available for download here.
This is the dataset of the famous cholera map in central London in 1854, made by Dr. John Snow
The folder contains the street network, point data for the location of the pumps -one of which was contaminated with cholera- and a polygon file with building blocks from the Ordnance Survey (OS data © Crown copyright and database right, 2015). An explanation of the data sources is provided in the companion text file README.txt.
All the necessary data are available as a single download from the course website on the following link:
This dataset contains information for AirBnb properties for the area of Inner London aggregated at the MSOA level. It has been prepared by Dani Arribas-Bel using as the original source the full listing of AirBnb locations for London provided by Inside AirBnb. Same as the source, the dataset is released under a CC0 1.0 Universal License.
For every polygon, the following variables are provided:
id: MSOA unique identifier.accommodates: average property capacity in the MSOA.bathrooms: average number of bathrooms in the properties within the MSOA.bedrooms: average number of bedrooms in the properties within the MSOA.beds: average number of beds in the properties within the MSOA.number_of_reviews: average number of reviews received by the properties within the MSOA.reviews_per_month: average number of reviews per month received by the properties within the MSOA.review_scores_ratings: average rating score received by the properties within the MSOA.review_scores_accuracy: average accuracy score received by the properties within the MSOA.review_scores_cleanliness: average cleanliness score received by the properties within the MSOA.review_scores_checkin: average checkin score received by the properties within the MSOA.review_scores_communication: average communication score received by the properties within the MSOA.review_scores_location: average location score received by the properties within the MSOA.review_scores_value: average value score received by the properties within the MSOA.property_count: total number of AirBnb properties listed withing the MSOA.Source: Inside AirBnb’s extract of AirBnb locations in London (UK).
Instructions: the data is provided as a GeoJSON file and is available for download in the following url (right-clik and “Save As” on the link):
The lab also uses an additional file that contains the boundary lines of the London boroughs, which has been obtained from:
https://github.com/radoi90/housequest-data/blob/master/london_boroughs.geojson
However, some students have experienced problems with the original file. If that is the case for you, go ahead and download this version from the course website:
http://darribas.org/gds16/content/labs/data/london_boroughs.geojson
Additional files: A Jupyter notebook showing the process of cleaning and aggregation carried out from the original data to the file provided here can be accessed in .ipynb and html format.
This dataset, provided as a shapefile, contains a collection of locations and
time stamps relating to Twitter postings within the
municipality of Liverpool. The data was originally provided by Guy Lansley
from UCL and processed by Dani Arribas-Bel.
Every row in the dataset contains an individual tweet, and is provided with the
following information:
LAT: latitude of the location where the posting took place.LON: longitude of the location where the posting took place.YEAR: year of posting.MONTH: month of posting.DAY: day of the month (1-31) when the message was posted.DOW: day of the week (0-6) when the message was posted.HOUR: hour of the posting.MINUTE: minute of the posting.X: longitude projected to the British National Grid (EPSG:Y: latitude projected to the British National Grid (EPSG:LSOA11CD: unique identifier code of the LSOA where the tweet location fallsSource: Twitter via Guy Lansley (UCL).
Instructions: given the Twitter license that applies to the data, this
dataset cannot be redistributed publicly online. For that reason, it has been
uploaded to the VITAL page of the course. You can find it on the following
location:
VITAL ENVS3/563 –> Learning Resources –> Twitter dataset
The shapefile is provided as a compressed .zip file. Download it and extract
it where you can access and set the path appropriately.