Difference between revisions of "Spatial Pattern Analysis with CartoDB"
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For many general GIS users CartoDB may seem complex and very daunting. But the great thing with CartoDB is that being a master at SQL, CSS and databases is not always required for using CartoDB. For more basic use cases it can be used with limited coding experience. It is extremely powerful and versatile with a wide array of use cases, namely data visualization, spatial analysis, and other geospatial applications. |
For many general GIS users CartoDB may seem complex and very daunting. But the great thing with CartoDB is that being a master at SQL, CSS and databases is not always required for using CartoDB. For more basic use cases it can be used with limited coding experience. It is extremely powerful and versatile with a wide array of use cases, namely data visualization, spatial analysis, and other geospatial applications. |
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− | + | This tutorial will provide a basic run down of how to set up CartoDB and provide some information on performing spatial analysis in CartoDB. |
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== Install Guide for Ubuntu 20.04 LTS x64 == |
== Install Guide for Ubuntu 20.04 LTS x64 == |
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− | + | This tutorial will guide you through the basic process of installing CartoDB on Ubuntu 20.04. |
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Most will likely install CartoDB inside a VM on a local PC but other commercial options exist. |
Most will likely install CartoDB inside a VM on a local PC but other commercial options exist. |
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The creators of CartoDB have a basic, 12 month [https://carto.com/pricing/ free trial] and paid options. Alternative hosting options are also available from Digital Ocean. |
The creators of CartoDB have a basic, 12 month [https://carto.com/pricing/ free trial] and paid options. Alternative hosting options are also available from Digital Ocean. |
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Each dataset is known as a table that corresponds to a spreadsheet that can be visualized on a map. Examination or modification of data are performed by SQL statements or using the GUI. |
Each dataset is known as a table that corresponds to a spreadsheet that can be visualized on a map. Examination or modification of data are performed by SQL statements or using the GUI. |
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− | ===How do you map data? How do you visualize data? A short note |
+ | ===How do you map data? How do you visualize data? A short note on styling, the visualization wizard, base maps, and labels.=== |
− | Cartodb provides full control over styling of map using SQL and CSS. Visualization wizards provide options to visualize data with simple, choropleth, category, bubble, intensity, density and a animated data categorization called torque. Torque, simple and category are used in this project. Column labels are toggled on for each row to provide the user information about name and location for incubators and bixi docks with the addition of how many bikes are available at each location. There are support from base maps from Google, CartoDB, Mapbox, WMS, XYZ and more. CartoDB Dark is used in this project. |
+ | Cartodb provides full control over styling of map using SQL, Python and CSS. Visualization wizards provide options to visualize data with simple, choropleth, category, bubble, intensity, density and a animated data categorization called torque. Torque, simple and category are used in this project. Column labels are toggled on for each row to provide the user information about name and location for incubators and bixi docks with the addition of how many bikes are available at each location. There are support from base maps from Google, CartoDB, Mapbox, WMS, XYZ and more. CartoDB Dark is used in this project. |
Many great examples of [https://carto.com/spatial-data-catalog/ projects] created with CartoDB and further [https://vimeo.com/channels/carto video tutorials] or [https://carto.com/help/ help centers] exist online. |
Many great examples of [https://carto.com/spatial-data-catalog/ projects] created with CartoDB and further [https://vimeo.com/channels/carto video tutorials] or [https://carto.com/help/ help centers] exist online. |
Latest revision as of 14:17, 19 October 2020
Contents
- 1 Introduction to CartoDB
- 2 Install Guide for Ubuntu 20.04 LTS x64
- 3 User Interface
- 4 Dataset
- 5 Data Analysis
- 6 References
Introduction to CartoDB
For many general GIS users CartoDB may seem complex and very daunting. But the great thing with CartoDB is that being a master at SQL, CSS and databases is not always required for using CartoDB. For more basic use cases it can be used with limited coding experience. It is extremely powerful and versatile with a wide array of use cases, namely data visualization, spatial analysis, and other geospatial applications.
This tutorial will provide a basic run down of how to set up CartoDB and provide some information on performing spatial analysis in CartoDB.
Install Guide for Ubuntu 20.04 LTS x64
This tutorial will guide you through the basic process of installing CartoDB on Ubuntu 20.04. Most will likely install CartoDB inside a VM on a local PC but other commercial options exist. The creators of CartoDB have a basic, 12 month free trial and paid options. Alternative hosting options are also available from Digital Ocean.
CartoDB has several dependencies which it uses to run:
- PostgreSQL
- PostGIS
- Redis
- CARTO PostgreSQL extensions
- CARTO Builder
- Maps API
- SQL API
Install GIT
This tutorial requires the use of git for the installation of some packages.
sudo apt-get install git
Install PostgreSQL
Add the custom PostgreSQL repository for CartoDB. The reason for the custom package can be found here.
sudo add-apt-repository ppa:cartodb/postgresql-10 && sudo apt-get update
Then install PostgreSQL
sudo apt-get install postgresql-10 \
postgresql-plpython-10 \
postgresql-server-dev-10
PostgreSQL Configuration
To make this installation easier, and because we are installing within a local environment we can make authentication less secure.
Simply run:
sudo nano etc/postgresql/10/main/pg_hba.conf
And make sure that the lines appear as below:
local all postgres trust
local all all trust
host all all 127.0.0.1/32 trust
Once done restart PostgreSQL:
sudo systemctl restart postgresql
Then add the required CARTO users to PostgreSQL:
sudo createuser publicuser --no-createrole --no-createdb --no-superuser -U postgres
sudo createuser tileuser --no-createrole --no-createdb --no-superuser -U postgres
Install PostgreSQL Helper Extensions
Finally install some PostgreSQL extensions that expand upon PostgreSQL to work better with the other dependencies.
git clone https://github.com/CartoDB/cartodb-postgresql.git
cd cartodb-postgresql
git checkout <LATEST cartodb-postgresql tag>
sudo make all install
Install GDAL and PostGIS
sudo add-apt-repository ppa:cartodb/gis && sudo apt-get update
sudo apt-get install gdal-bin libgdal-dev postgis
Configure PostGIS Database:
sudo createdb -T template0 -O postgres -U postgres -E UTF8 template_postgis
psql -U postgres template_postgis -c 'CREATE EXTENSION postgis;CREATE EXTENSION postgis_topology;'
sudo ldconfig
Install Redis
sudo add-apt-repository ppa:cartodb/redis-next && sudo apt-get update
sudo apt-get install redis
Install Node.js
curl -sL https://deb.nodesource.com/setup_10.x | sudo -E bash -
sudo apt-get install -y nodejs
Some more dependencies:
sudo apt-get install libpixman-1-0 libpixman-1-dev libcairo2-dev libjpeg-dev libgif-dev libpango1.0-dev
I promise we're getting close to the end.
Install SQL API
git clone git://github.com/CartoDB/CartoDB-SQL-API.git
cd CartoDB-SQL-API
npm install
Configure our local development environment and then Start Node.js:
cp config/environments/development.js.example config/environments/development.js
node app.js development
Install MAPS API
git clone git://github.com/CartoDB/Windshaft-cartodb.git
cd Windshaft-cartodb
npm install
Then configure the API and start it:
cp config/environments/development.js.example config/environments/development.js
mkdir logs
node app.js development
Install Ruby
- No not the mineral type
sudo apt-add-repository ppa:brightbox/ruby-ng && sudo apt-get update
sudo apt-get install ruby2.4 ruby2.4-dev ruby-bundler
sudo gem install compass
And Finally Install Builder and CartoDB
Download and install CartoDB with additonal dependencies:
git clone --recursive https://github.com/CartoDB/cartodb.git
cd cartodb
sudo apt-get install python-pip imagemagick unp zip libicu-dev
RAILS_ENV=development bundle install
sudo pip install --no-use-wheel -r python_requirements.txt
Finish up:
npm install
npm run carto-node && npm run build:static
Configure CartoDB:
cp config/app_config.yml.sample config/app_config.yml
cp config/database.yml.sample config/database.yml
Start remaining services and initialize database:
sudo systemctl start redis-server
RAILS_ENV=development bundle exec rake db:create
RAILS_ENV=development bundle exec rake db:migrate
RAILS_ENV=development bundle exec rails server
And finally close that console and then in a new one run:
RAILS_ENV=development bundle exec ./script/resque
First Time CartoDB Run
Create user account and development environment:
cd cartodb
export SUBDOMAIN=development
# Add entries to /etc/hosts in development
echo "127.0.0.1 ${SUBDOMAIN}.localhost.lan" | sudo tee -a /etc/hosts
# Create the development user
sh script/create_dev_user
Run the remaining processes:
bundle exec script/resque
bundle exec thin start --threaded -p 3000 --threadpool-size 5
cd cartodb-sql-api && node app.js
cd windshaft-cartodb && node app.js
That's it!
Go to http://<mysubdomain>.localhost.lan:3000
And enter your login created using the password entered above.
User Interface
Now that CartoDB is intstalled there are several ways to begin using it.
The three most popular ones that many people use are directly throught the web builder interface online, through Jupiter Notebook or with the PythonSDK.
How do you upload data?
Importing data is seamless and easy. The 'new table' icon with the plus sign will open a dialog box with options to:
- paste a url or select a file (e.x. shapefiles),
- Online cloud storage such as dropbox or google drive data,
- or create a new table from scratch or other database services
How do you explore added data?
Each dataset is known as a table that corresponds to a spreadsheet that can be visualized on a map. Examination or modification of data are performed by SQL statements or using the GUI.
How do you map data? How do you visualize data? A short note on styling, the visualization wizard, base maps, and labels.
Cartodb provides full control over styling of map using SQL, Python and CSS. Visualization wizards provide options to visualize data with simple, choropleth, category, bubble, intensity, density and a animated data categorization called torque. Torque, simple and category are used in this project. Column labels are toggled on for each row to provide the user information about name and location for incubators and bixi docks with the addition of how many bikes are available at each location. There are support from base maps from Google, CartoDB, Mapbox, WMS, XYZ and more. CartoDB Dark is used in this project.
Many great examples of projects created with CartoDB and further video tutorials or help centers exist online.
Maps are shared from the options menu in the top right, by link, embed or as an api.
Dataset
Bicycle Stations (Bixi) and Business Incubators from the City of Toronto open data initiative are the two data sets utilized in this project. As of this writing, business incubators is no longer offered. Bixi dataset had been preprocessed to include the latitude and longitude derived from address.
Data Analysis
Cartodb has full support for both vector and raster data. The example below takes advantage of a short SQL script.
Example: SQL statement is derived from Andrew Hill: https://gist.github.com/andrewxhill/5979532.
SELECT ST_MakeLine( --This function can take two or more points and make a line the_geom_webmercator, --We select the_geom_webmercator, since CartoDB will need it to draw your maps ( --This is a nested query that will run for every row in our outer query SELECT the_geom_webmercator FROM plout10 -- Here we select the geometry from our second dataset ORDER BY the_geom <-> c.the_geom -- We then order it by its distance to the geometry in the first dataset (c.the_geom) LIMIT 1 -- And limit it to just 1, i.e. we find just the closest ) ) the_geom_webmercator -- Here we alias the result to a column we call, 'the_geom_webmercator', so that CartoDB will draw it FROM citibike_stations c -- Here we alias our table to 'c' so we can type it nicely above :)
The following SQL statement is used to visualize the closest Biki locations to an incubator. These statement utilizes PostGIS and PostgresSQL functions.
SELECT ST_MakeLine(the_geom_webmercator, ( SELECT the_geom_webmercator FROM business_incubators_toronto ORDER BY the_geom <-> c.the_geom LIMIT 1 ) ) the_geom_webmercator FROM station c
References
CartoDB Developers Page: https://carto.com/developers/
CartoDB Official Documentation: https://cartodb.readthedocs.io/en/latest/install.html
VirtualBox https://www.virtualbox.org/
Old Ubuntu Releases http://old-releases.ubuntu.com/releases/
Digital Ocean https://www.digitalocean.com/
CartoDB Repository https://github.com/CartoDB/cartodb
PostGIS Reference http://postgis.net/docs/reference.html
PostgreSQL Tutorial http://www.postgresql.org/docs/9.1/static/tutorial.html
Lord Linus's RVM tutorial https://github.com/lordlinus/cartodb
Michael Schmid's suggestions https://groups.google.com/forum/#!topic/cartodb/o5_cVk-owe0
Andrew Hill's SQL query https://gist.github.com/andrewxhill/5979532
Open Data Toronto http://www1.toronto.ca/wps/portal/contentonly?vgnextoid=1a66e03bb8d1e310VgnVCM10000071d60f89RCRD
Bixi http://www1.toronto.ca/wps/portal/contentonly?vgnextoid=ad3cb6b6ae92b310VgnVCM10000071d60f89RCRD&vgnextchannel=1a66e03bb8d1e310VgnVCM10000071d60f89RCRD