The visualization in D3 (or basically any visualization tool) is carried out in the following steps:<\/p>\n
1. Data acquisition \u2013 Obtain the data from a source (disk or over a network).
\n2. Parse \u2013 Give it a structure for its meaning and then order it into categories. The amount of data might be immense, but it is necessary to put it in a structure to make it easier to convey the message to the others.
\n3. Filter – Only keep the data that matters, which is in the interest of your claim.
\n4. Mine – Apply methods from statistics or data mining as a way to discern patterns or place the data in mathematical context.
\n5. Represent – Choose the idiom that fits to represent the data. Eg – bar graph, scatter plot, map, etc.
\n6. Refine – Improve the basic representation to make it more clear and which better give the insights by looking at it. You can change the color scheme or change the entire idiom.
\n7. Interact – Add methods for manipulating the data or controlling what features are visible. D3 is very powerful in this section.<\/p>\n
To start implementing in D3.js, you can follow the tutorials given on the website:
\nhttps:\/\/www.dashingd3js.com\/d3js-first-steps<\/p>\n
Reference:
\nhttps:\/\/www.dashingd3js.com\/the-data-visualization-process<\/p>\n","protected":false},"excerpt":{"rendered":"
The visualization in D3 (or basically any visualization tool) is carried out in the following steps: 1. Data acquisition \u2013 Obtain the data from a source (disk or over a network). 2. Parse \u2013 Give it a structure for its meaning and then order it into categories. The amount of data might be immense, but … Continue reading Data Visualization process in D3<\/span><\/a><\/p>\n","protected":false},"author":1873,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"qubely_global_settings":"","qubely_interactions":"","kk_blocks_editor_width":"","_kiokenblocks_attr":"","_kiokenblocks_dimensions":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-1245","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"gutentor_comment":0,"qubely_featured_image_url":null,"qubely_author":{"display_name":"Neeraj","author_link":"https:\/\/blogs.scu.edu\/dataviz\/author\/neeraj04\/"},"qubely_comment":0,"qubely_category":"Uncategorized<\/a>","qubely_excerpt":"The visualization in D3 (or basically any visualization tool) is carried out in the following steps: 1. Data acquisition \u2013 Obtain the data from a source (disk or over a network). 2. Parse \u2013 Give it a structure for its meaning and then order it into categories. The amount of data might be immense, but…","post_mailing_queue_ids":[],"_links":{"self":[{"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/posts\/1245","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/users\/1873"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/comments?post=1245"}],"version-history":[{"count":2,"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/posts\/1245\/revisions"}],"predecessor-version":[{"id":1252,"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/posts\/1245\/revisions\/1252"}],"wp:attachment":[{"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/media?parent=1245"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/categories?post=1245"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.scu.edu\/dataviz\/wp-json\/wp\/v2\/tags?post=1245"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}