Functional programming is part of the Tech-Track course from project Information Design at CMD
Functional Programming | Frontend Data | Frontend Applications given during Project Information Design @CMDA⤴︎
More information about the Tech Track? @CMDA-TT⤴︎ ⦿ Features
⦿ Example
⦿ Installation
⦿ API
⦿ Assignment
⦿ Functional Programming
⦿ Frontend Data
⦿ Frontend Applications
⦿ Rubric
⦿ Resources
⦿ Credits
const url = 'https://opendata.rdw.nl/resource/';
const tijdvak = 'ixf8-gtwq.json';
fetch(url + endPoint)
.then(responseStatus)
.then(sendResponseJSON)
.then((result) => {
logResult(result);
})
.catch((error) => {
console.error('Can not fetch becasuse: ' + error);
});
function responseStatus(response) {
if (response.status >= 200 && response.status < 300) {
console.log(response);
return Promise.resolve(response);
} else {
return Promise.reject(new Error(response.statusText));
}
}
function readResponseJSON(response) {
return response.json();
}
function logResult(result) {
console.table(result);
return result;
}
First, clone the repo to your local machine.
$ git clone https://github.com/GiovanniDw/functional-programming.git
Then $ cd/
into the project folder.
$ npm install
Now run the project!
$ npm run dev
Most of the data that will be used, comes from the opendata.rdw.nl⤴︎ API.
API-endpoint:
https://opendata.rdw.nl/resource/ixf8-gtwq.json
Create a data visualisation with d3 based on given data.
During this course the code in this repo will use functional patterns to get, filter, clean & transform datasets from external sources about parking. And visualise that data. For more details about te concept and the data go to the Wiki⤴︎
During this course I will
⦿ Apply functional programming patterns to clean & transform data.
⦿ Develop a concept for The Volkskrant based on external datasets
⦿ Create interactive visualizations with data by using D3