{"id":18494240,"url":"https://github.com/amitkaps/data-vis-workshop","last_synced_at":"2026-01-21T09:32:07.413Z","repository":{"id":39782563,"uuid":"207059789","full_name":"amitkaps/data-vis-workshop","owner":"amitkaps","description":"Data Visualisation Workshop","archived":false,"fork":false,"pushed_at":"2019-09-22T06:37:30.000Z","size":54297,"stargazers_count":2,"open_issues_count":0,"forks_count":3,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-02-16T23:28:30.072Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/amitkaps.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-09-08T04:06:56.000Z","updated_at":"2022-06-25T01:50:23.000Z","dependencies_parsed_at":"2022-09-20T11:25:44.127Z","dependency_job_id":null,"html_url":"https://github.com/amitkaps/data-vis-workshop","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/amitkaps/data-vis-workshop","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amitkaps%2Fdata-vis-workshop","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amitkaps%2Fdata-vis-workshop/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amitkaps%2Fdata-vis-workshop/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amitkaps%2Fdata-vis-workshop/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/amitkaps","download_url":"https://codeload.github.com/amitkaps/data-vis-workshop/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/amitkaps%2Fdata-vis-workshop/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28631142,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-21T04:47:28.174Z","status":"ssl_error","status_checked_at":"2026-01-21T04:47:22.943Z","response_time":86,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-06T13:18:46.276Z","updated_at":"2026-01-21T09:32:07.388Z","avatar_url":"https://github.com/amitkaps.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data Visualisation Workshop\n\n\n### Notes and Slides\n\n- [Introduction](notes/Introduction.pdf): Overall introductions\n- [Representation](notes/Representation.pdf): Walk though different chart guidelines\n- [Aesthetics](notes/Aesthetics.pdf): Include decoding guidelines, color, chart-junk\n- [Interaction](notes/Interaction.pdf): Overview on animation and interation\n- [Model Vis](notes/Modelvis.pdf): Concepts on model visualisation\n- [Storytelling](notes/Storytelling.pdf): Storytelling and link to data visualisation\n- [Dashboards](notes/Dasboard.pdf): Concepts on structuring an interactive dashboard\n- [Tools \u0026 Resources](notes/Resources.pdf): List of tools and resources for visualisation\n\n\n### In-Class Notebooks\n- [01-Simple](01-Simple.html)\n- [02-Telco-Basic](02-Telco-Basic.html)\n- [03-Facets](03-Facets.html)\n- [04-Interactive](04-Interactive.html)\n- [05-Chart-Serving](05-chart.py)\n\n\n### Additional Resources:\n\n- Visualisation Libraries: \n    - [pyviz.org](http://pyviz.org): Overview on all python libraries got data visualisation\n    - [Altair](http://altair-viz.github.io): Python library for Interactive Grammar of Graphics\n    - [Vega-lite](http://vega.github.io/vega-lite): JS library for Interactive Grammar of Graphics\n- Chart Guidelines e.g. Visual Vocabulary\n    - FT Version: [ft.com/vocabulary](http://ft.com/vocabulary)\n    - Vega-lite Version: [gramener.github.io/visual-vocabulary-vega/](https://gramener.github.io/visual-vocabulary-vega/)\n\n\n\n### Session Plan\n\n**Day 1**\n\n- *Workshop Introduction*\n- *Session #1: Value of Data Visualisation*\n- *Session #2: Tools \u0026 Abstractions for Data Visualisation*\n- *Session #3: Theory of Data Visualisation*\n- *Session #4: Guidelines for Better Data Visualisation*\n- *Day One Summary*\n- *Data-Story Group Exercise*\n\n**Day 2**\n\n- *Recap \u0026 Questions*\n- *Data-Story Presentations*\n- *Session #5: Crafting Visual Stories with Data*\n- *Data-Story Rework*\n- *Session #6: Interactivity*\n- *Session #7: Explorable Vis for Business Users*\n- *Session #8: Putting together an Interactive Application*\n- *Overall Summary \u0026 Way Forward*\n\nDetailed session plan can be read at [session.md](session.md)\n\n### Setup \u0026 Installation\n\nSystem Requirements: \n\n- You need a laptop for hands-on coding during the workshop, with the following minimum specifications:\n   - 2 or more CPU Cores\n   - 4GB or more RAM\n   - 10 GB or more free disk space\n   - Running Windows 7+, 64-bit macOS, or Linux\n   \nStep 1:\n- For Python data science libraries, please install the latest Anaconda Python 3 Distribution (currently Python 3.7) for your OS: https://www.anaconda.com/distribution/\n- Detailed install instruction \u0026 troubleshooting is available at http://docs.anaconda.com/anaconda/install/\n\nStep 2:\n- Please download using https://github.com/amitkaps/data-vis-workshop/archive/master.zip or clone the repo from: https://github.com/amitkaps/data-vis-workshop.git\n\nStep 3:\n- Once you have Anaconda installed (Step 1) and downloaded or cloned the repo (Step 3), you can use the following conda commands to install all the required packages. \n\nPlease note:\n- Do `cd` into the folder and then run these commands.\n- If you are on Windows, then please only use the Anaconda Prompt (and not command prompt)\n\n```\nconda env create --file vis.yaml\nconda activate vis\n\npython install_check.py\n\u003e\u003e\u003e All-Set! Packages installed.\n```\n\n### Datasets\n\nThe list of datasets are available in the `data` folder and you can read about them at [datasets.md](datasets.md)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Famitkaps%2Fdata-vis-workshop","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Famitkaps%2Fdata-vis-workshop","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Famitkaps%2Fdata-vis-workshop/lists"}