How to Create and Download a Custom Spreadsheet Using the Datacart
The data cart tool on OpenDataCommunities provides an easy way to download custom combinations of data from datasets in the site. This guide describes:
- What the data cart is
- How to add data to the data cart
- How to remove data from the data cart
- How to download and share a data cart
The data cart is a way of building up a custom spreadsheet, with data from one or more datasets.
You can choose both rows and columns, and end up with is a spreadsheet which cross references statistics (columns) against geographical areas (rows). We can then download or share this custom spreadsheet.
How to add data to the data cart
This is what an empty data cart looks like (Go to: Tools -> Your Data Cart), or Click on the link "Your data cart" at the foot of every page.
To build up your cart, need to add rows and columns to it. To do this, you need to find datasets and areas that you are interested in, and add data from them to the cart.
Say, for example, you wanted to get data for the ratio of median house prices to median earnings, and the number of dwellings being built across the country, so that we can compare them in excel, or show them in a GIS: you can use the Data Cart to do this!
Add Columns to your cart
First, find the two data sets that you're interested in, and narrow down the dataset until you see a spreadsheet view.
For the ‘Permanent Dwellings’ dataset, you might get to a spreadsheet that looks like this:
In your example analysis, we are interested in ‘All’ dwellings, so if we click on that column heading we get this menu:
Selecting ‘Add column to cart’ will add this column to the cart. We’ll get confirmation a the top of the screen, and the data cart status at the bottom of the page will be updated:
We can then repeat the above steps with the dataset ’House price to earnings ratio’, and we’ll have 2 slices of data in the cart.
Note that adding columns doesn't add any actual data yet, but it records the fact that you're interested in those columns. For the cart to return data you also need to tell the cart tool which rows (areas) you're interested in.
Add rows to your cart
The final thing to do is to add all local authorities in England to the cart, as our rows. To do this, we Explore by Area (Explore -> By Area), and go to English Lower Tier Authorities.
From there, we can use the add to cart button to add all local authorities to the cart.
View your cart
Your data cart now shows that there are 2 slices of data and 370 geographical areas, as shown in the page footer:
Clicking the "data cart" link from that message (or Tools -> Your Data Cart) will take us to our populated Data Cart, which will now look like this:
There are a variety of different ways of adding data to a cart, but we've just demonstrated the simplest way.
It is also possible to only add specific geographical areas, or choose to add all columns from a particular dataset in one go. Look out for the buttons with a shopping cart and plus sign!
Editing your in-progress Data Cart
Before we save the cart for download, we can optionally remove dataset slices (columns) or geographic areas (rows), by simply clicking the white cross on red button next to the item in the cart:
How to download and share data from a data cart
Once we are happy with the content of our data cart, we can press Save. This will save this version of the data cart, ready for us to download or share.
Note: Once you've saved a cart, you can't edit it again (so that the contents stay consistent for anyone you've shared it with!). However, you (or anyone you've shared it with) can add rows and columns from a saved cart into your new (empty) in-progress cart.
To share a cart, you can just send someone (or share on social media) the link under the "Share" heading. This particular one is: http://opendatacommunities.org/carts/d1b89204-e234-43fb-aa02-11d284305e6d. This URL will never change.
To download the data in your cart as CSV, click the CSV button. The download is returned with the areas as rows, and the dimension values as the columns.
To continue exploring our datasets, return to opendatacommunities.org