X-Git-Url: https://apps.delaporte.us/gitweb/dotfiles.git/blobdiff_plain/7c1afefe42dcafe9caf31207b4e54a8032553a94..a910c69f72750663d75dd347c3943ee0a0424bdf:/data/issues.ipynb?ds=sidebyside diff --git a/data/issues.ipynb b/data/issues.ipynb index 2156a71..08d596b 100644 --- a/data/issues.ipynb +++ b/data/issues.ipynb @@ -2,7 +2,34 @@ "cells": [ { "cell_type": "code", - "execution_count": 21, + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import platform\n", + "import matplotlib.pyplot as plt\n", + "print(platform.python_version())" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Todo List\n", + "\n", + "- [x] add calculated year to the metadata\n", + "- [ ] make one chart per year\n", + "- [x] make sure all the data files are getting loaded" + ] + }, + { + "cell_type": "code", + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -10,7 +37,202 @@ "import glob\n", "import os\n", "\n", - "data_files = glob.glob(os.path.expanduser('~\\\\Data\\\\*.json'))" + "data_files = glob.glob(os.path.expanduser('~\\\\Data\\\\*.json'))\n", + "\n", + "for file in data_files:\n", + "\tprint(f\"{file}\", os.path.getsize(file))\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "\n", + "data_frames = []\n", + "for file in data_files:\n", + "\n", + "\tf = open(file, encoding='utf-8')\n", + "\tdf_temp = pd.read_json(f)\n", + "\tdata_frames.append(df_temp)\n", + "\n", + "df = pd.concat(data_frames, ignore_index=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "df['count'] = np.zeros(len(df))\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Pie Chart" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "dfp = df\n", + "# dfp['mile'] = [m.get('title') if m else None for m in dfp.milestone]\n", + "dfp['mile'] = [m.get('title') if hasattr(m, 'get') else None for m in dfp['milestone']]\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "closed_dates = pd.to_datetime(df['closedAt'], format='ISO8601')\n", + "dfp['year'] = closed_dates.dt.year\n", + "\n", + "dfp.drop(columns=['closedAt','milestone', 'url'], inplace=True)\n", + "print(dfp)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "mile_counts = dfp.groupby('mile')['title'].nunique()\n", + "dfp['count'] = dfp['mile'].map(mile_counts)\n", + "# dfp.drop(columns=['title'], inplace=True)\n", + "dfp['mile'] = df['mile'].drop_duplicates()\n", + "dfp.dropna(inplace=True)\n", + "dfp = dfp[dfp['count'] > 5]\n", + "print(dfp)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "mile_counts = df.groupby('mile')['count'].sum()\n", + "mile_counts = mile_counts.loc[lambda x: x > 5]\n", + "\n", + "\n", + "print(mile_counts)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "plt.pie(mile_counts, labels=mile_counts.index, autopct='%0.1f%%')\n", + "plt.title(f\"Tasks by Milestone\")\n", + "plt.axis('equal')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "type(mile_counts)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Plot of closed issues by month and milestone for one project\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "closed_months = pd.to_datetime(df['closedAt'], format='ISO8601')\n", + "df['closed_month'] = closed_months.dt.month\n", + "df.drop(columns=['closedAt'], inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df['mile'] = [d.get('title') if d else None for d in df.milestone]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "dfg = df.groupby(['mile', 'closed_month']).count().reset_index()\n", + "dfg.drop(columns=['milestone', 'title', 'url'], inplace=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "exclude_from_chart = [\n", + "\t'Job Aid Ideas']\n", + "\n", + "for ex in exclude_from_chart:\n", + "\tdfg = dfg[dfg['mile'] != ex]\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "sns.set_theme()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure(figsize=(10, 6))\n", + "sns.pie(x='closed_month', y='count', hue='mile', data=dfg)\n", + "plt.pie(dfg, )\n", + "plt.xlabel('Closed Month')\n", + "plt.ylabel('ClosedAt')\n", + "plt.title('Stacked Line Chart: Milestone Effort by Issue Close Date')\n", + "plt.xticks(rotation=45)\n", + "plt.legend(title='Mile', loc='upper left')\n", + "plt.show()" ] } ], @@ -30,7 +252,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.1" + "version": "3.12.2" } }, "nbformat": 4,