rxhl/github_stars.ipynb

## github_stars.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5ec49591",
   "metadata": {},
   "source": [
    "\n",
    "# Github Stars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5d9148e9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-16T18:17:40.568075Z",
     "iopub.status.busy": "2023-08-16T18:17:40.567193Z",
     "iopub.status.idle": "2023-08-16T18:17:41.117309Z",
     "shell.execute_reply": "2023-08-16T18:17:41.117018Z"
    }
   },
   "outputs": [],
   "source": [
    "import pickle\n",
    "github_stargazers_by_week = pickle.loads(b'\\x80\\x04\\x95\\r\\x03\\x00\\x00\\x00\\x00\\x00\\x00\\x8c\\x11pandas.core.frame\\x94\\x8c\\tDataFrame\\x94\\x93\\x94)\\x81\\x94}\\x94(\\x8c\\x04_mgr\\x94\\x8c\\x1epandas.core.internals.managers\\x94\\x8c\\x0cBlockManager\\x94\\x93\\x94\\x8c\\x16pandas._libs.internals\\x94\\x8c\\x0f_unpickle_block\\x94\\x93\\x94\\x8c\\x15numpy.core.multiarray\\x94\\x8c\\x0c_reconstruct\\x94\\x93\\x94\\x8c\\x05numpy\\x94\\x8c\\x07ndarray\\x94\\x93\\x94K\\x00\\x85\\x94C\\x01b\\x94\\x87\\x94R\\x94(K\\x01K\\x01K\\x07\\x86\\x94h\\x0f\\x8c\\x05dtype\\x94\\x93\\x94\\x8c\\x02i8\\x94\\x89\\x88\\x87\\x94R\\x94(K\\x03\\x8c\\x01<\\x94NNNJ\\xff\\xff\\xff\\xffJ\\xff\\xff\\xff\\xffK\\x00t\\x94b\\x89C8\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x94t\\x94b\\x8c\\x08builtins\\x94\\x8c\\x05slice\\x94\\x93\\x94K\\x00K\\x01K\\x01\\x87\\x94R\\x94K\\x02\\x87\\x94R\\x94\\x85\\x94]\\x94(\\x8c\\x18pandas.core.indexes.base\\x94\\x8c\\n_new_Index\\x94\\x93\\x94h)\\x8c\\x05Index\\x94\\x93\\x94}\\x94(\\x8c\\x04data\\x94h\\x0eh\\x11K\\x00\\x85\\x94h\\x13\\x87\\x94R\\x94(K\\x01K\\x01\\x85\\x94h\\x18\\x8c\\x02O8\\x94\\x89\\x88\\x87\\x94R\\x94(K\\x03\\x8c\\x01|\\x94NNNJ\\xff\\xff\\xff\\xffJ\\xff\\xff\\xff\\xffK?t\\x94b\\x89]\\x94\\x8c\\x05users\\x94at\\x94b\\x8c\\x04name\\x94Nu\\x86\\x94R\\x94h+h-}\\x94(h/h\\x0eh\\x11K\\x00\\x85\\x94h\\x13\\x87\\x94R\\x94(K\\x01K\\x07\\x85\\x94h6\\x89]\\x94(\\x8c\\x08datetime\\x94\\x8c\\x04date\\x94\\x93\\x94C\\x04\\x07\\xe6\\x01\\t\\x94\\x85\\x94R\\x94hGC\\x04\\x07\\xe6\\x01\\x17\\x94\\x85\\x94R\\x94hGC\\x04\\x07\\xe6\\x02\\x14\\x94\\x85\\x94R\\x94hGC\\x04\\x07\\xe6\\x03\\x1b\\x94\\x85\\x94R\\x94hGC\\x04\\x07\\xe6\\n\\t\\x94\\x85\\x94R\\x94hGC\\x04\\x07\\xe7\\x07\\t\\x94\\x85\\x94R\\x94hGC\\x04\\x07\\xe7\\x07\\x10\\x94\\x85\\x94R\\x94et\\x94bh<\\x8c\\x04week\\x94u\\x86\\x94R\\x94e\\x86\\x94R\\x94\\x8c\\x04_typ\\x94\\x8c\\tdataframe\\x94\\x8c\\t_metadata\\x94]\\x94\\x8c\\x05attrs\\x94}\\x94\\x8c\\x06_flags\\x94}\\x94\\x8c\\x17allows_duplicate_labels\\x94\\x88sub.')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48a8c7fd",
   "metadata": {
    "lines_to_next_cell": 0
   },
   "source": [
    "## Github Stars by Week, last 52 weeks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "88fc978e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-08-16T18:17:41.119088Z",
     "iopub.status.busy": "2023-08-16T18:17:41.118979Z",
     "iopub.status.idle": "2023-08-16T18:17:44.156466Z",
     "shell.execute_reply": "2023-08-16T18:17:44.156166Z"
    },
    "lines_to_next_cell": 0
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='week'>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "github_stargazers_by_week.tail(52).reset_index().plot.bar(x=\"week\", y=\"users\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2425ede",
   "metadata": {},
   "source": [
    "    "
   ]
  }
 ],
 "metadata": {
  "jupytext": {
   "cell_metadata_filter": "-all",
   "main_language": "python",
   "notebook_metadata_filter": "-all",
   "text_representation": {
    "extension": ".md",
    "format_name": "markdown"
   }
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}