pyairbyte_notebooks/PyAirbyte_Github_Incremental_Demo.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "view-in-github"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/airbytehq/quickstarts/blob/master/pyairbyte_notebooks/PyAirbyte_Github_Incremental_Demo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gS3oGgI0CVpn"
      },
      "source": [
        "In this demo, we use PyAirbyte to extract data from Github, followed by a series of transformations and analyses to derive meaningful insights from this data. In particular, we demonstrate PyAirbyte capabilities for extracting data incrementally.\n",
        "\n",
        "#### Prerequisites:\n",
        "\n",
        "-   A Github personal access token. For details on configuring authetication credentials, refer to the Github source connector [documentation](https://docs.airbyte.com/integrations/sources/github).\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "bM4Te8XEWECV"
      },
      "outputs": [],
      "source": [
        "# Add virtual environment support in Google Colab\n",
        "!apt-get install -qq python3.10-venv\n",
        "\n",
        "# Install airbyte\n",
        "%pip install --quiet airbyte"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qTmx2CsKDgXy"
      },
      "source": [
        "### Load source data from Github to local cache\n",
        "\n",
        "In this section, we establish a connection to Github via PyAirbyte. The source connector is configured with necessary parameters like the credentials repository we are interested in. Check the [docs](https://docs.airbyte.com/integrations/sources/github) for more details on these parameters.\n",
        "\n",
        "After configuring the source connector, we perform a `check()` to ensure that the configuration is correct and the connection to the API is successful. Then, we list the available streams for this source and select the ones we are interested in syncing.\n",
        "\n",
        "Then, we proceed to read from the source into the internal DuckDB cache.\n",
        "\n",
        "Note: The credentials are retrieved securely using the `get_secret()` method. This will automatically locate a matching Google Colab secret or environment variable, ensuring they are not hard-coded into the notebook. Make sure to add your key to the Secrets section on the left.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 149
        },
        "id": "JjFChgoNXIfE",
        "outputId": "1097be03-026f-464c-da35-33d17fc4385c"
      },
      "outputs": [
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          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Installing <span style=\"color: #008000; text-decoration-color: #008000\">'source-github'</span> into virtual environment <span style=\"color: #008000; text-decoration-color: #008000\">'/content/.venv-source-github'</span>.\n",
              "Running <span style=\"color: #008000; text-decoration-color: #008000\">'pip install airbyte-source-github'</span><span style=\"color: #808000; text-decoration-color: #808000\">...</span>\n",
              "\n",
              "</pre>\n"
            ],
            "text/plain": [
              "Installing \u001b[32m'source-github'\u001b[0m into virtual environment \u001b[32m'/content/.venv-source-github'\u001b[0m.\n",
              "Running \u001b[32m'pip install airbyte-source-github'\u001b[0m\u001b[33m...\u001b[0m\n",
              "\n"
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            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Connector <span style=\"color: #008000; text-decoration-color: #008000\">'source-github'</span> installed successfully!\n",
              "For more information, see the source-github documentation:\n",
              "<span style=\"color: #0000ff; text-decoration-color: #0000ff; text-decoration: underline\">https://docs.airbyte.com/integrations/sources/github#reference</span>\n",
              "\n",
              "</pre>\n"
            ],
            "text/plain": [
              "Connector \u001b[32m'source-github'\u001b[0m installed successfully!\n",
              "For more information, see the source-github documentation:\n",
              "\u001b[4;94mhttps://docs.airbyte.com/integrations/sources/github#reference\u001b[0m\n",
              "\n"
            ]
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            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Connection check succeeded for `source-github`.\n",
              "</pre>\n"
            ],
            "text/plain": [
              "Connection check succeeded for `source-github`.\n"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import airbyte as ab\n",
        "\n",
        "# Create and configure the source:\n",
        "source = ab.get_source(\n",
        "    \"source-github\",\n",
        "    install_if_missing=True,\n",
        "    config={\n",
        "        \"repositories\": [\"airbytehq/quickstarts\"],\n",
        "        \"credentials\": {\n",
        "            \"personal_access_token\": ab.get_secret(\"GITHUB_PERSONAL_ACCESS_TOKEN\"),\n",
        "        },\n",
        "    },\n",
        ")\n",
        "\n",
        "# Verify the config and creds by running `check`:\n",
        "source.check()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gyn_ymCiEVD6",
        "outputId": "e5ca7ea5-5082-4ddf-9234-74051853a5a3"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['issue_timeline_events',\n",
              " 'assignees',\n",
              " 'branches',\n",
              " 'collaborators',\n",
              " 'comments',\n",
              " 'commit_comment_reactions',\n",
              " 'commit_comments',\n",
              " 'commits',\n",
              " 'contributor_activity',\n",
              " 'deployments',\n",
              " 'events',\n",
              " 'issue_comment_reactions',\n",
              " 'issue_events',\n",
              " 'issue_labels',\n",
              " 'issue_milestones',\n",
              " 'issue_reactions',\n",
              " 'issues',\n",
              " 'organizations',\n",
              " 'project_cards',\n",
              " 'project_columns',\n",
              " 'projects',\n",
              " 'pull_request_comment_reactions',\n",
              " 'pull_request_commits',\n",
              " 'pull_request_stats',\n",
              " 'projects_v2',\n",
              " 'pull_requests',\n",
              " 'releases',\n",
              " 'repositories',\n",
              " 'review_comments',\n",
              " 'reviews',\n",
              " 'stargazers',\n",
              " 'tags',\n",
              " 'teams',\n",
              " 'team_members',\n",
              " 'users',\n",
              " 'workflows',\n",
              " 'workflow_runs',\n",
              " 'workflow_jobs',\n",
              " 'team_memberships']"
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# List the available streams available for the Github source\n",
        "source.get_available_streams()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "w94J7TIFiBt1",
        "outputId": "65633720-0948-472b-cf81-f587b772abb5"
      },
      "outputs": [
        {
          "data": {
            "text/markdown": [
              "## Read Progress\n",
              "\n",
              "Started reading at 22:16:25.\n",
              "\n",
              "Read **314** records over **6 seconds** (52.3 records / second).\n",
              "\n",
              "Wrote **314** records over 4 batches.\n",
              "\n",
              "Finished reading at 22:16:32.\n",
              "\n",
              "Started finalizing streams at 22:16:32.\n",
              "\n",
              "Finalized **4** batches over 2 seconds.\n",
              "\n",
              "Completed 4 out of 4 streams:\n",
              "\n",
              "  - reviews\n",
              "  - stargazers\n",
              "  - pull_requests\n",
              "  - issues\n",
              "\n",
              "\n",
              "Completed writing at 22:16:34. Total time elapsed: 8 seconds\n",
              "\n",
              "\n",
              "------------------------------------------------\n"
            ],
            "text/plain": [
              "<IPython.core.display.Markdown object>"
            ]
          },
          "metadata": {},
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        },
        {
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Completed `source-github` read operation at <span style=\"color: #00ff00; text-decoration-color: #00ff00; font-weight: bold\">22:16:34</span>.\n",
              "</pre>\n"
            ],
            "text/plain": [
              "Completed `source-github` read operation at \u001b[1;92m22:16:34\u001b[0m.\n"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Select the streams we are interested in loading to cache\n",
        "source.set_streams([\"pull_requests\", \"issues\", \"reviews\", \"stargazers\"])\n",
        "\n",
        "# Read into DuckDB local default cache\n",
        "cache = ab.get_default_cache()\n",
        "result = source.read(cache=cache)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7iFNbPbPFB3q"
      },
      "source": [
        "### Read again to sync changes\n",
        "\n",
        "The PyAirbyte Github source connector has the ability to read data incrementally by default, meaning that after the first successful data sync, only updates and new records will be synced in subsequent reads.\n",
        "\n",
        "For more information on sync modes for this source, you can refer to the [docs](https://docs.airbyte.com/integrations/sources/github).\n",
        "\n",
        "Let's read again, and see how no records will be loaded to cache.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 332
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        "id": "UOm1jvefGMrR",
        "outputId": "a4fc014c-0d48-4186-c21b-1ba6e890f9ae"
      },
      "outputs": [
        {
          "data": {
            "text/markdown": [
              "## Read Progress\n",
              "\n",
              "Started reading at 22:17:30.\n",
              "\n",
              "Read **0** records over **3 seconds** (0.0 records / second).\n",
              "\n",
              "Finished reading at 22:17:33.\n",
              "\n",
              "Started finalizing streams at 22:17:33.\n",
              "\n",
              "Finalized **0** batches over 0 seconds.\n",
              "\n",
              "Completed 4 out of 4 streams:\n",
              "\n",
              "  - reviews\n",
              "  - stargazers\n",
              "  - pull_requests\n",
              "  - issues\n",
              "\n",
              "\n",
              "Completed writing at 22:17:33. Total time elapsed: 3 seconds\n",
              "\n",
              "\n",
              "------------------------------------------------\n"
            ],
            "text/plain": [
              "<IPython.core.display.Markdown object>"
            ]
          },
          "metadata": {},
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        },
        {
          "data": {
            "text/html": [
              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Completed `source-github` read operation at <span style=\"color: #00ff00; text-decoration-color: #00ff00; font-weight: bold\">22:17:33</span>.\n",
              "</pre>\n"
            ],
            "text/plain": [
              "Completed `source-github` read operation at \u001b[1;92m22:17:33\u001b[0m.\n"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "result = source.read(cache=cache)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EZfsqKfJGg_Z"
      },
      "source": [
        "### Read data from the cache\n",
        "\n",
        "Read from the already-written DuckDB cache into a pandas Dataframe. After the data is in the cache, you can read it without re-configuring or re-creating the source object. You can also select a specific stream to read from.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "E5-ADp0dGnGR"
      },
      "outputs": [],
      "source": [
        "# Read from the cache into a pandas Dataframe:\n",
        "reviews = cache[\"reviews\"].to_pandas()\n",
        "stargazers = cache[\"stargazers\"].to_pandas()\n",
        "pull_requests = cache[\"pull_requests\"].to_pandas()\n",
        "issues = cache[\"issues\"].to_pandas()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EDs_pEAaGP5X"
      },
      "source": [
        "### Transform and analyze the data\n",
        "\n",
        "Let's take our Github data and run some analysis with `pandas` and `matplotlib`.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 216
        },
        "id": "DkUfVobeGbMG",
        "outputId": "5c0c1712-66e9-4a58-dc04-8c9709359a36"
      },
      "outputs": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>repository</th>\n",
              "      <th>id</th>\n",
              "      <th>node_id</th>\n",
              "      <th>user</th>\n",
              "      <th>body</th>\n",
              "      <th>state</th>\n",
              "      <th>html_url</th>\n",
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              "      <th>0</th>\n",
              "      <td>airbytehq/quickstarts</td>\n",
              "      <td>1689913150</td>\n",
              "      <td>PRR_kwDOKQqr2s5kugc-</td>\n",
              "      <td>{'avatar_url': https://avatars.githubuserconte...</td>\n",
              "      <td></td>\n",
              "      <td>COMMENTED</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/...</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/59</td>\n",
              "      <td>{'html': {'href': https://github.com/airbytehq...</td>\n",
              "      <td>2023-10-20 12:18:17</td>\n",
              "      <td>2023-10-20 12:18:17</td>\n",
              "      <td>2023-10-20 12:18:17</td>\n",
              "      <td>29ca06ae449b07f17c1be6bb104264b6d62dafcc</td>\n",
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              "      <td>1689921852</td>\n",
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              "      <td>https://github.com/airbytehq/quickstarts/pull/...</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/59</td>\n",
              "      <td>{'html': {'href': https://github.com/airbytehq...</td>\n",
              "      <td>2023-10-20 12:23:23</td>\n",
              "      <td>2023-10-20 12:23:22</td>\n",
              "      <td>2023-10-20 12:23:23</td>\n",
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              "      <td>{'html': {'href': https://github.com/airbytehq...</td>\n",
              "      <td>2023-10-20 12:38:03</td>\n",
              "      <td>2023-10-20 12:38:03</td>\n",
              "      <td>2023-10-20 12:38:03</td>\n",
              "      <td>29ca06ae449b07f17c1be6bb104264b6d62dafcc</td>\n",
              "      <td>CONTRIBUTOR</td>\n",
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              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-fill-color: #666;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "    display: none;\n",
              "    fill: var(--fill-color);\n",
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              "    padding: 0;\n",
              "    width: 32px;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
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              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "\n",
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              "      border-color: transparent;\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "    (() => {\n",
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              "        document.querySelector('#df-cd49da00-b2c9-4bb6-8895-fd2f3df224b5 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
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            ],
            "text/plain": [
              "              repository          id               node_id  \\\n",
              "0  airbytehq/quickstarts  1689913150  PRR_kwDOKQqr2s5kugc-   \n",
              "1  airbytehq/quickstarts  1689921852  PRR_kwDOKQqr2s5kuik8   \n",
              "2  airbytehq/quickstarts  1689945893  PRR_kwDOKQqr2s5kuocl   \n",
              "\n",
              "                                                user body      state  \\\n",
              "0  {'avatar_url': https://avatars.githubuserconte...       COMMENTED   \n",
              "1  {'avatar_url': https://avatars.githubuserconte...       COMMENTED   \n",
              "2  {'avatar_url': https://avatars.githubuserconte...       COMMENTED   \n",
              "\n",
              "                                            html_url  \\\n",
              "0  https://github.com/airbytehq/quickstarts/pull/...   \n",
              "1  https://github.com/airbytehq/quickstarts/pull/...   \n",
              "2  https://github.com/airbytehq/quickstarts/pull/...   \n",
              "\n",
              "                                   pull_request_url  \\\n",
              "0  https://github.com/airbytehq/quickstarts/pull/59   \n",
              "1  https://github.com/airbytehq/quickstarts/pull/59   \n",
              "2  https://github.com/airbytehq/quickstarts/pull/59   \n",
              "\n",
              "                                              _links        submitted_at  \\\n",
              "0  {'html': {'href': https://github.com/airbytehq... 2023-10-20 12:18:17   \n",
              "1  {'html': {'href': https://github.com/airbytehq... 2023-10-20 12:23:23   \n",
              "2  {'html': {'href': https://github.com/airbytehq... 2023-10-20 12:38:03   \n",
              "\n",
              "           created_at          updated_at  \\\n",
              "0 2023-10-20 12:18:17 2023-10-20 12:18:17   \n",
              "1 2023-10-20 12:23:22 2023-10-20 12:23:23   \n",
              "2 2023-10-20 12:38:03 2023-10-20 12:38:03   \n",
              "\n",
              "                                  commit_id author_association  \n",
              "0  29ca06ae449b07f17c1be6bb104264b6d62dafcc             MEMBER  \n",
              "1  29ca06ae449b07f17c1be6bb104264b6d62dafcc        CONTRIBUTOR  \n",
              "2  29ca06ae449b07f17c1be6bb104264b6d62dafcc        CONTRIBUTOR  "
            ]
          },
          "execution_count": 8,
          "metadata": {},
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        "id": "3ACTSw_CHWXQ",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "        document.querySelector('#df-ecf47bf4-2e9c-4aec-b6f5-870745fde36a button.colab-df-convert');\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-ecf47bf4-2e9c-4aec-b6f5-870745fde36a');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "\n",
              "  .colab-df-spinner {\n",
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            ],
            "text/plain": [
              "              repository    user_id          starred_at  \\\n",
              "0  airbytehq/quickstarts   95236817 2023-10-02 16:40:52   \n",
              "1  airbytehq/quickstarts  123734227 2023-10-17 10:50:04   \n",
              "2  airbytehq/quickstarts   70362748 2023-10-31 02:20:26   \n",
              "\n",
              "                                                user  \n",
              "0  {'avatar_url': https://avatars.githubuserconte...  \n",
              "1  {'avatar_url': https://avatars.githubuserconte...  \n",
              "2  {'avatar_url': https://avatars.githubuserconte...  "
            ]
          },
          "execution_count": 9,
          "metadata": {},
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    },
    {
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          "height": 349
        },
        "id": "unxq3DdCHZBM",
        "outputId": "5f8d47d0-2960-41e9-a715-e8de04bbc4e4"
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        {
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              "      <th>base</th>\n",
              "      <th>_links</th>\n",
              "      <th>author_association</th>\n",
              "      <th>auto_merge</th>\n",
              "      <th>draft</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>airbytehq/quickstarts</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>1534111883</td>\n",
              "      <td>PR_kwDOKQqr2s5bcLCL</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/35</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/...</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>...</td>\n",
              "      <td>None</td>\n",
              "      <td>[]</td>\n",
              "      <td>[]</td>\n",
              "      <td>[]</td>\n",
              "      <td>{'label': airbytehq:ecommerce-analytics-stack,...</td>\n",
              "      <td>{'label': airbytehq:main, 'ref': main, 'repo':...</td>\n",
              "      <td>{'comments': {'href': https://api.github.com/r...</td>\n",
              "      <td>MEMBER</td>\n",
              "      <td>None</td>\n",
              "      <td>false</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>airbytehq/quickstarts</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>1534172082</td>\n",
              "      <td>PR_kwDOKQqr2s5bcZuy</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/36</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/...</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>...</td>\n",
              "      <td>None</td>\n",
              "      <td>[]</td>\n",
              "      <td>[]</td>\n",
              "      <td>[]</td>\n",
              "      <td>{'label': airbytehq:ecommerce-analytics-stack,...</td>\n",
              "      <td>{'label': airbytehq:main, 'ref': main, 'repo':...</td>\n",
              "      <td>{'comments': {'href': https://api.github.com/r...</td>\n",
              "      <td>MEMBER</td>\n",
              "      <td>None</td>\n",
              "      <td>false</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>airbytehq/quickstarts</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>1545412143</td>\n",
              "      <td>PR_kwDOKQqr2s5cHR4v</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/38</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/...</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>...</td>\n",
              "      <td>None</td>\n",
              "      <td>[]</td>\n",
              "      <td>[]</td>\n",
              "      <td>[]</td>\n",
              "      <td>{'label': avionmission:feature/pad_bigquery_st...</td>\n",
              "      <td>{'label': airbytehq:main, 'ref': main, 'repo':...</td>\n",
              "      <td>{'comments': {'href': https://api.github.com/r...</td>\n",
              "      <td>FIRST_TIME_CONTRIBUTOR</td>\n",
              "      <td>None</td>\n",
              "      <td>false</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3 rows × 37 columns</p>\n",
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              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "                                                    [key], {});\n",
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              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
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              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
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              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "    (() => {\n",
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            "text/plain": [
              "              repository                                                url  \\\n",
              "0  airbytehq/quickstarts  https://api.github.com/repos/airbytehq/quickst...   \n",
              "1  airbytehq/quickstarts  https://api.github.com/repos/airbytehq/quickst...   \n",
              "2  airbytehq/quickstarts  https://api.github.com/repos/airbytehq/quickst...   \n",
              "\n",
              "           id              node_id  \\\n",
              "0  1534111883  PR_kwDOKQqr2s5bcLCL   \n",
              "1  1534172082  PR_kwDOKQqr2s5bcZuy   \n",
              "2  1545412143  PR_kwDOKQqr2s5cHR4v   \n",
              "\n",
              "                                           html_url  \\\n",
              "0  https://github.com/airbytehq/quickstarts/pull/35   \n",
              "1  https://github.com/airbytehq/quickstarts/pull/36   \n",
              "2  https://github.com/airbytehq/quickstarts/pull/38   \n",
              "\n",
              "                                            diff_url  \\\n",
              "0  https://github.com/airbytehq/quickstarts/pull/...   \n",
              "1  https://github.com/airbytehq/quickstarts/pull/...   \n",
              "2  https://github.com/airbytehq/quickstarts/pull/...   \n",
              "\n",
              "                                           patch_url  \\\n",
              "0  https://github.com/airbytehq/quickstarts/pull/...   \n",
              "1  https://github.com/airbytehq/quickstarts/pull/...   \n",
              "2  https://github.com/airbytehq/quickstarts/pull/...   \n",
              "\n",
              "                                           issue_url  \\\n",
              "0  https://api.github.com/repos/airbytehq/quickst...   \n",
              "1  https://api.github.com/repos/airbytehq/quickst...   \n",
              "2  https://api.github.com/repos/airbytehq/quickst...   \n",
              "\n",
              "                                         commits_url  \\\n",
              "0  https://api.github.com/repos/airbytehq/quickst...   \n",
              "1  https://api.github.com/repos/airbytehq/quickst...   \n",
              "2  https://api.github.com/repos/airbytehq/quickst...   \n",
              "\n",
              "                                 review_comments_url  ... assignee assignees  \\\n",
              "0  https://api.github.com/repos/airbytehq/quickst...  ...     None        []   \n",
              "1  https://api.github.com/repos/airbytehq/quickst...  ...     None        []   \n",
              "2  https://api.github.com/repos/airbytehq/quickst...  ...     None        []   \n",
              "\n",
              "  requested_reviewers requested_teams  \\\n",
              "0                  []              []   \n",
              "1                  []              []   \n",
              "2                  []              []   \n",
              "\n",
              "                                                head  \\\n",
              "0  {'label': airbytehq:ecommerce-analytics-stack,...   \n",
              "1  {'label': airbytehq:ecommerce-analytics-stack,...   \n",
              "2  {'label': avionmission:feature/pad_bigquery_st...   \n",
              "\n",
              "                                                base  \\\n",
              "0  {'label': airbytehq:main, 'ref': main, 'repo':...   \n",
              "1  {'label': airbytehq:main, 'ref': main, 'repo':...   \n",
              "2  {'label': airbytehq:main, 'ref': main, 'repo':...   \n",
              "\n",
              "                                              _links      author_association  \\\n",
              "0  {'comments': {'href': https://api.github.com/r...                  MEMBER   \n",
              "1  {'comments': {'href': https://api.github.com/r...                  MEMBER   \n",
              "2  {'comments': {'href': https://api.github.com/r...  FIRST_TIME_CONTRIBUTOR   \n",
              "\n",
              "  auto_merge  draft  \n",
              "0       None  false  \n",
              "1       None  false  \n",
              "2       None  false  \n",
              "\n",
              "[3 rows x 37 columns]"
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "pull_requests.head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 401
        },
        "id": "q2BDOUmcHbmj",
        "outputId": "0f8b4003-1059-444e-c9c7-d1ed7ebf8fdb"
      },
      "outputs": [
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              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/35</td>\n",
              "      <td>35</td>\n",
              "      <td>...</td>\n",
              "      <td>{'diff_url': https://github.com/airbytehq/quic...</td>\n",
              "      <td>2023-09-28T12:35:12Z</td>\n",
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              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/36</td>\n",
              "      <td>36</td>\n",
              "      <td>...</td>\n",
              "      <td>{'diff_url': https://github.com/airbytehq/quic...</td>\n",
              "      <td>2023-09-28T13:02:56Z</td>\n",
              "      <td>2023-09-28 13:01:48</td>\n",
              "      <td>2023-09-28 13:02:56</td>\n",
              "      <td>MEMBER</td>\n",
              "      <td>false</td>\n",
              "      <td>{'+1': 0, '-1': 0, 'confused': 0, 'eyes': 0, '...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>airbytehq/quickstarts</td>\n",
              "      <td>1930249843</td>\n",
              "      <td>PR_kwDOKQqr2s5cHR4v</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>https://github.com/airbytehq/quickstarts/pull/38</td>\n",
              "      <td>38</td>\n",
              "      <td>...</td>\n",
              "      <td>{'diff_url': https://github.com/airbytehq/quic...</td>\n",
              "      <td>None</td>\n",
              "      <td>2023-10-06 14:04:27</td>\n",
              "      <td>2023-10-12 15:20:21</td>\n",
              "      <td>FIRST_TIME_CONTRIBUTOR</td>\n",
              "      <td>false</td>\n",
              "      <td>{'+1': 0, '-1': 0, 'confused': 0, 'eyes': 0, '...</td>\n",
              "      <td>https://api.github.com/repos/airbytehq/quickst...</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3 rows × 32 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2230e017-5454-4b71-bdb3-02273823f5c2')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-2230e017-5454-4b71-bdb3-02273823f5c2 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-2230e017-5454-4b71-bdb3-02273823f5c2');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-d635b1d4-96ca-450d-a896-1ccd4a7ed775\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d635b1d4-96ca-450d-a896-1ccd4a7ed775')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-d635b1d4-96ca-450d-a896-1ccd4a7ed775 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "              repository          id              node_id  \\\n",
              "0  airbytehq/quickstarts  1917441405  PR_kwDOKQqr2s5bcLCL   \n",
              "1  airbytehq/quickstarts  1917507008  PR_kwDOKQqr2s5bcZuy   \n",
              "2  airbytehq/quickstarts  1930249843  PR_kwDOKQqr2s5cHR4v   \n",
              "\n",
              "                                                 url  \\\n",
              "0  https://api.github.com/repos/airbytehq/quickst...   \n",
              "1  https://api.github.com/repos/airbytehq/quickst...   \n",
              "2  https://api.github.com/repos/airbytehq/quickst...   \n",
              "\n",
              "                                      repository_url  \\\n",
              "0  https://api.github.com/repos/airbytehq/quickst...   \n",
              "1  https://api.github.com/repos/airbytehq/quickst...   \n",
              "2  https://api.github.com/repos/airbytehq/quickst...   \n",
              "\n",
              "                                          labels_url  \\\n",
              "0  https://api.github.com/repos/airbytehq/quickst...   \n",
              "1  https://api.github.com/repos/airbytehq/quickst...   \n",
              "2  https://api.github.com/repos/airbytehq/quickst...   \n",
              "\n",
              "                                        comments_url  \\\n",
              "0  https://api.github.com/repos/airbytehq/quickst...   \n",
              "1  https://api.github.com/repos/airbytehq/quickst...   \n",
              "2  https://api.github.com/repos/airbytehq/quickst...   \n",
              "\n",
              "                                          events_url  \\\n",
              "0  https://api.github.com/repos/airbytehq/quickst...   \n",
              "1  https://api.github.com/repos/airbytehq/quickst...   \n",
              "2  https://api.github.com/repos/airbytehq/quickst...   \n",
              "\n",
              "                                           html_url number  ...  \\\n",
              "0  https://github.com/airbytehq/quickstarts/pull/35     35  ...   \n",
              "1  https://github.com/airbytehq/quickstarts/pull/36     36  ...   \n",
              "2  https://github.com/airbytehq/quickstarts/pull/38     38  ...   \n",
              "\n",
              "                                        pull_request             closed_at  \\\n",
              "0  {'diff_url': https://github.com/airbytehq/quic...  2023-09-28T12:35:12Z   \n",
              "1  {'diff_url': https://github.com/airbytehq/quic...  2023-09-28T13:02:56Z   \n",
              "2  {'diff_url': https://github.com/airbytehq/quic...                  None   \n",
              "\n",
              "           created_at          updated_at      author_association  draft  \\\n",
              "0 2023-09-28 12:32:19 2023-09-28 12:35:12                  MEMBER  false   \n",
              "1 2023-09-28 13:01:48 2023-09-28 13:02:56                  MEMBER  false   \n",
              "2 2023-10-06 14:04:27 2023-10-12 15:20:21  FIRST_TIME_CONTRIBUTOR  false   \n",
              "\n",
              "                                           reactions  \\\n",
              "0  {'+1': 0, '-1': 0, 'confused': 0, 'eyes': 0, '...   \n",
              "1  {'+1': 0, '-1': 0, 'confused': 0, 'eyes': 0, '...   \n",
              "2  {'+1': 0, '-1': 0, 'confused': 0, 'eyes': 0, '...   \n",
              "\n",
              "                                        timeline_url performed_via_github_app  \\\n",
              "0  https://api.github.com/repos/airbytehq/quickst...                     None   \n",
              "1  https://api.github.com/repos/airbytehq/quickst...                     None   \n",
              "2  https://api.github.com/repos/airbytehq/quickst...                     None   \n",
              "\n",
              "  state_reason  \n",
              "0         None  \n",
              "1         None  \n",
              "2         None  \n",
              "\n",
              "[3 rows x 32 columns]"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "issues.head(3)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BuXrJDOOJAyu"
      },
      "source": [
        "#### Pull Requests Trend Over Time\n",
        "\n",
        "This will visualize the number of pull requests created over time.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "I-y3H82qJWVX",
        "outputId": "ebdd1ee0-35da-4df2-9f0d-9856fb18fcff"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Assuming 'pull_requests' dataframe is available and has a 'created_at' column in datetime format\n",
        "pull_requests[\"created_at\"] = pd.to_datetime(pull_requests[\"created_at\"])\n",
        "pr_trend = pull_requests.resample(\"M\", on=\"created_at\").size()\n",
        "\n",
        "plt.figure(figsize=(12, 6))\n",
        "pr_trend.plot(kind=\"line\", color=\"blue\", marker=\"o\")\n",
        "plt.title(\"Monthly Pull Requests Trend\")\n",
        "plt.xlabel(\"Month\")\n",
        "plt.ylabel(\"Number of Pull Requests\")\n",
        "plt.grid(True)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OK5jXo0nJcnW"
      },
      "source": [
        "#### Open vs Closed Issues\n",
        "\n",
        "Compare the number of open versus closed issues.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "WFtnoUE5Jhus",
        "outputId": "4ea9b4a2-1b6d-4f69-8eee-4d7df78a0109"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Assuming 'issues' dataframe has a 'state' column\n",
        "issue_status_count = issues[\"state\"].value_counts()\n",
        "\n",
        "plt.figure(figsize=(8, 6))\n",
        "issue_status_count.plot(kind=\"bar\", color=[\"blue\", \"green\"])\n",
        "plt.title(\"Open vs Closed Issues\")\n",
        "plt.xlabel(\"State\")\n",
        "plt.ylabel(\"Number of Issues\")\n",
        "plt.xticks(rotation=0)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ETo6-qu4JsI_"
      },
      "source": [
        "#### Star Growth Over Time\n",
        "\n",
        "Plot the cumulative count of stars over time.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "NC7PthQMJxpd",
        "outputId": "654b3bc8-9eaa-469a-f2d1-bdf139e5e04b"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Assuming 'stargazers' dataframe has a 'starred_at' column in datetime format\n",
        "stargazers[\"starred_at\"] = pd.to_datetime(stargazers[\"starred_at\"])\n",
        "star_growth = stargazers.resample(\"M\", on=\"starred_at\").size().cumsum()\n",
        "\n",
        "plt.figure(figsize=(12, 6))\n",
        "star_growth.plot(kind=\"line\", color=\"gold\", marker=\"*\")\n",
        "plt.title(\"Cumulative Star Growth Over Time\")\n",
        "plt.xlabel(\"Month\")\n",
        "plt.ylabel(\"Cumulative Stars\")\n",
        "plt.grid(True)\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lwacZs7vKiTd"
      },
      "source": [
        "#### Issue Resolution Followed by Pull Requests\n",
        "\n",
        "This analysis checks if there's a trend in issue resolutions followed by pull requests, which might indicate active development in response to issues.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "STHueLOoKoZ9"
      },
      "outputs": [],
      "source": [
        "# Convert created_at and closet_at to datetime\n",
        "pull_requests[\"created_at\"] = pd.to_datetime(pull_requests[\"created_at\"])\n",
        "issues[\"closed_at\"] = issues[\"closed_at\"].dt.tz_localize(None)\n",
        "\n",
        "# Resample both dataframes to get monthly counts\n",
        "monthly_closed_issues = issues.resample(\"M\", on=\"closed_at\").size()\n",
        "monthly_created_prs = pull_requests.resample(\"M\", on=\"created_at\").size()\n",
        "\n",
        "# Combine into a single dataframe\n",
        "combined_issues_prs_df = pd.concat([monthly_closed_issues, monthly_created_prs], axis=1)\n",
        "combined_issues_prs_df.columns = [\"Monthly Closed Issues\", \"Monthly Created PRs\"]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "-nRXduEbKr4_",
        "outputId": "5a0fe25b-0f1b-4400-d943-88da874f969d"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "combined_issues_prs_df.plot(kind=\"line\", figsize=(12, 6))\n",
        "plt.title(\"Monthly Closed Issues vs Monthly Created Pull Requests\")\n",
        "plt.xlabel(\"Month\")\n",
        "plt.ylabel(\"Count\")\n",
        "plt.grid(True)\n",
        "plt.show()"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "include_colab_link": true,
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}