{"id":20064147,"url":"https://github.com/i10416/data-analysis-workplace","last_synced_at":"2026-05-07T03:39:00.330Z","repository":{"id":48619006,"uuid":"354083223","full_name":"i10416/data-analysis-workplace","owner":"i10416","description":"This repository gives example and tutorial resources to set up data analysis environment with JupyterLab supporting Python, R and Scala kernel.","archived":false,"fork":false,"pushed_at":"2022-06-26T08:18:11.000Z","size":6264,"stargazers_count":0,"open_issues_count":1,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-01-12T22:43:56.703Z","etag":null,"topics":["data-science","python","scala"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/i10416.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2021-04-02T17:08:51.000Z","updated_at":"2021-07-30T14:06:05.000Z","dependencies_parsed_at":"2022-08-31T20:02:15.750Z","dependency_job_id":null,"html_url":"https://github.com/i10416/data-analysis-workplace","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/i10416%2Fdata-analysis-workplace","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/i10416%2Fdata-analysis-workplace/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/i10416%2Fdata-analysis-workplace/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/i10416%2Fdata-analysis-workplace/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/i10416","download_url":"https://codeload.github.com/i10416/data-analysis-workplace/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241494142,"owners_count":19971870,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["data-science","python","scala"],"created_at":"2024-11-13T13:44:57.433Z","updated_at":"2026-05-07T03:38:55.297Z","avatar_url":"https://github.com/i10416.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# python/scala/R data analysis env\nNote: I recommend you use Docker-based templates https://github.com/ItoYo16u/workspace_templates \n\n## required\n- ubuntu 18.x /20.x\n- cuda\n- pyenv\n- Pandoc\n- node v14.16.0 and npm\n- R\n- coursier(cs)\n\n\n### install pyenv\n```bash\nsudo apt install -y \\\nbuild-essential \\\nlibffi-dev \\\nlibssl-dev \\\nzlib1g-dev \\\nliblzma-dev \\\nlibbz2-dev \\\nlibreadline-dev \\\nlibsqlite3-dev\n\ngit clone https://github.com/pyenv/pyenv.git ~/.pyenv\ngit clone git://github.com/yyuu/pyenv-update.git ~/.pyenv/plugins/pyenv-update\n```\n\n### install pandoc\n\n```bash\nsudo apt install texlive-lang-japanese\nsudo apt install texlive-xetex\nsudo apt install pandoc pandoc-citeproc\n```\n\n### install node with nodebrew\n```bash\ncurl -L git.io/nodebrew | perl - setup\n# export path/to/nodebrew in ~/.(ba|z)shrc\nnodebrew install v14.16.0\nnodebrew use v14.16.0\n```\n\n### install R\n\n```bash\n\n```bash\nsudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9\nsudo add-apt-repository  'deb https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/'\nsudo apt update \u0026\u0026 sudo apt upgrade\nsudo apt install r-base\nsudo apt install build-essential libcurl4-gnutls-dev libxml2-dev libssl-dev\n# ここから下は jupyter インストール後\nR\n```\n\n```R\ninstall.packages(c('repr', 'IRdisplay', 'pbdZMQ', 'devtools'))\ninstall.packages(\"plotly\")\ndevtools::install_github('IRkernel/IRkernel')\nIRkernel::installspec()\n```\n\n### install scala kernel\n\n```bash\ncs launch almond --scala 2.13.4 -- --install --display-name \"Scala (2.13)\"\n\n```\n\n## getting started\n\n```bash\ngit clone path/to/repository\ncd repository\npyenv local 3.9.2\npip install --upgrade pip\npython -m venv .venv\nsource .venv/bin/activate\npip install -r requirements.txt\njupyter labextension install @krassowski/jupyterlab-lsp\njupyter labextension install jupyterlab-plotly\njupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget\njupyter lab --generate-config\nsed -i -e 's/# c.ServerApp.use_redirect_file = True/c.ServerApp.use_redirect_file = False/g' ~/.jupyter/jupyter_lab_config.py\ngrep use_redirect_file ~/.jupyter/jupyter_lab_config.py\ncp ./metals-ls.json ./.venv/etc/jupyter/jupyter_server_config.d/metals-ls.json\ncp ./jupyter_lab_config.json ~/.jupyter/jupyter_lab_config.json\n\njupyter lab\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fi10416%2Fdata-analysis-workplace","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fi10416%2Fdata-analysis-workplace","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fi10416%2Fdata-analysis-workplace/lists"}