Create one-time use DC.js charts from csv files.
Try the Demo
Initial page load. Pick an example data set or upload your own. Then click the "Load Data" or "Use this example" buttons.
A simple test example is the Cars dataset from Raw.js
The table below shows all the columns and their datatypes that were found from the loaded data. It also selects default chart types and enables all the dimensions for charting.
Row charts work for most data types, Bar charts require numerical data, and Time charts require Dates. Click the "Go" button to create the actual charts.
Let's filter for fast cars (low 0-60s time).
By selecting/filtering a chart, notice that all the other charts updated immediately. Let's now pick the least economical ones (low mpg)
Below the charts is a counter showing on how many data points match the cross-filter criteria out of the total number of data points. Here you can download a copy of the filtered data.
Finally, the table at the bottom shows the filtered data in table-format. It also groups the data by what was selected from the creation table.
- Get npm
- Install bower
npm install -g bower
(might need admin privileges) - Get a static file-server like http-server, Apache, nginx, Caddy, or use Python's built-in SimpleHTTPServer
- Get the code, install dependencies, and serve the directory (this is using http-server)
git clone https://github.com/Weatherproof/AutoDC
cd AutoDC
npm i
bower install
npm run build
http-server .
Check it out: http://localhost:8080/public/index.html
The example data sets were plucked from PivotTable.js and Raw.js
- An "advanced" view for creating a chart that has more grouping options, allows the user to pick the x-axis and y-axis dimensions, etc.
- More chart types. DC.js has documentation for donut/pie, line, bubble, scatter, heatmap, choropleth, and boxplot.