Remove ALL gitpod/docker/devcontainer related files and docs

.gitattributes

@@ -65,14 +65,12 @@ pandas/_version.py export-subst
 asv_bench export-ignore
 ci export-ignore
 doc export-ignore
-gitpod export-ignore
 MANIFEST.in export-ignore
 scripts/** export-ignore
 typings export-ignore
 web export-ignore
 CITATION.cff export-ignore
 codecov.yml export-ignore
-Dockerfile export-ignore
 environment.yml export-ignore
 setup.py export-ignore
 

.github/workflows/code-checks.yml

@@ -131,33 +131,6 @@ jobs:
         asv machine --yes
         asv run --quick --dry-run --durations=30 --python=same --show-stderr
 
-  build_docker_dev_environment:
-    name: Build Docker Dev Environment
-    runs-on: ubuntu-24.04
-    defaults:
-      run:
-        shell: bash -el {0}
-
-    concurrency:
-      # https://github.community/t/concurrecy-not-work-for-push/183068/7
-      group: ${{ github.event_name == 'push' && github.run_number || github.ref }}-build_docker_dev_environment
-      cancel-in-progress: true
-
-    steps:
-      - name: Clean up dangling images
-        run: docker image prune -f
-
-      - name: Checkout
-        uses: actions/checkout@v5
-        with:
-          fetch-depth: 0
-
-      - name: Build image
-        run: docker build --pull --no-cache --tag pandas-dev-env .
-
-      - name: Show environment
-        run: docker run --rm pandas-dev-env python -c "import pandas as pd; print(pd.show_versions())"
-
   requirements-dev-text-installable:
     name: Test install requirements-dev.txt
     runs-on: ubuntu-24.04

doc/source/conf.py

@@ -828,7 +828,6 @@ def setup(app) -> None:
             "https://github.com/pandas-dev/pandas/blob/v0.20.2/pandas/core/generic.py#L568",
             "https://github.com/pandas-dev/pandas/blob/v0.20.2/pandas/core/frame.py#L1495",
             "https://github.com/pandas-dev/pandas/issues/174151",
-            "https://gitpod.io/#https://github.com/USERNAME/pandas",
             "https://manishamde.github.io/blog/2013/03/07/pandas-and-python-top-10/",
             "https://matplotlib.org/api/axes_api.html#matplotlib.axes.Axes.table",
             "https://nipunbatra.github.io/blog/visualisation/2013/05/01/aggregation-timeseries.html",

doc/source/development/contributing_environment.rst

@@ -16,13 +16,11 @@ locally before pushing your changes. It's recommended to also install the :ref:`
     :maxdepth: 2
     :hidden:
 
-    contributing_gitpod.rst
 
 Step 1: install a C compiler
 ----------------------------
 
-How to do this will depend on your platform. If you choose to use ``Docker`` or ``GitPod``
-in the next step, then you can skip this step.
+How to do this will depend on your platform.
 
 **Windows**
 
@@ -163,51 +161,6 @@ should already exist.
    # Install the build dependencies
    python -m pip install -r requirements-dev.txt
 
-Option 3: using Docker
-~~~~~~~~~~~~~~~~~~~~~~
-
-pandas provides a ``DockerFile`` in the root directory to build a Docker image
-with a full pandas development environment.
-
-**Docker Commands**
-
-Build the Docker image::
-
-    # Build the image
-    docker build -t pandas-dev .
-
-Run Container::
-
-    # Run a container and bind your local repo to the container
-    # This command assumes you are running from your local repo
-    # but if not alter ${PWD} to match your local repo path
-    docker run -it --rm -v ${PWD}:/home/pandas pandas-dev
-
-*Even easier, you can integrate Docker with the following IDEs:*
-
-**Visual Studio Code**
-
-You can use the DockerFile to launch a remote session with Visual Studio Code,
-a popular free IDE, using the ``.devcontainer.json`` file.
-See https://code.visualstudio.com/docs/remote/containers for details.
-
-**PyCharm (Professional)**
-
-Enable Docker support and use the Services tool window to build and manage images as well as
-run and interact with containers.
-See https://www.jetbrains.com/help/pycharm/docker.html for details.
-
-Option 4: using Gitpod
-~~~~~~~~~~~~~~~~~~~~~~
-
-Gitpod is an open-source platform that automatically creates the correct development
-environment right in your browser, reducing the need to install local development
-environments and deal with incompatible dependencies.
-
-If you are a Windows user, unfamiliar with using the command line or building pandas
-for the first time, it is often faster to build with Gitpod. Here are the in-depth instructions
-for :ref:`building pandas with GitPod <contributing-gitpod>`.
-
 Step 3: build and install pandas
 --------------------------------