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[Heroku](https://www.heroku.com/), built using [plotly dash](https://plotly.com/dash/).\n\nIt was originally intended for time series data, hence the repo's name.\n\n## Why it exists\n\nCountless times a business expert or myself had to annotate tabular data, this solution made it faster.\n\n## How it works\n\n- Load data from a _csv_ (make sure csv is comma-separeted) or _xlsx_\n- Select _x-axis_ (datetime or numeric dtype) and _y-axis_ (numeric dtype) to plot\n- Input label value and select form color\n- Draw rectangle or closed freeform in the graph to assign label\n- Download results as _csv_ file\n\n## Run locally\nFirst step to run locally is to clone the repo:\n```\ngit clone https://github.com/FBruzzesi/ts-annotator.git\n```\n\n### Using environment\nInstall _requirements.txt_ and then serve gunicorn server:\n```\npip install -r requirements.txt\ngunicorn --bind 127.0.0.1:8080 --pythonpath app index:server\n```\n\n### Using docker\nTo run the app using docker after cloning the repo, one should build the docker image and then run it:\n```\ndocker build . -t ts-annotator\ndocker run -p 8080:8080 ts-annotator\n```\nThen go to http://localhost:8080/\n\n## Issues\n\nIssues and feedbacks are more than welcome\n\n## Support\n\n[![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/L3L37807E)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffbruzzesi%2Fts-annotator","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffbruzzesi%2Fts-annotator","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffbruzzesi%2Fts-annotator/lists"}