X-Git-Url: https://us-delaporte.pagekite.me/gitweb/dotfiles.git/blobdiff_plain/39aa091f5951f7dde7ae65831749d9c5d03b8b51..ea3abfdad5df78e020429d07e6e476b1cb1317e8:/data/issues.ipynb diff --git a/data/issues.ipynb b/data/issues.ipynb index 011beec..7b7f1be 100644 --- a/data/issues.ipynb +++ b/data/issues.ipynb @@ -7,9 +7,21 @@ "outputs": [], "source": [ "import platform\n", + "import matplotlib.pyplot as plt\n", "print(platform.python_version())" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Todo List\n", + "\n", + "- [ ] trim each chart to just a single, selected year\n", + "- [ ] make one chart per year\n", + "- [x] make sure all the data files are getting loaded" + ] + }, { "cell_type": "code", "execution_count": null, @@ -43,13 +55,14 @@ "source": [ "import pandas as pd\n", "\n", - "data_sets = []\n", + "data_frames = []\n", + "for file in data_files:\n", "\n", - "file = data_files[2]\n", - "print(file)\n", + "\tf = open(file, encoding='utf-8')\n", + "\tdf_temp = pd.read_json(f)\n", + "\tdata_frames.append(df_temp)\n", "\n", - "f = open(file, encoding='utf-8')\n", - "df = pd.read_json(f)" + "df = pd.concat(data_frames, ignore_index=True)" ] }, { @@ -63,15 +76,27 @@ "\n" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Pie Chart" + ] + }, { "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)" + "dfp = df\n", + "dfp['mile'] = [d.get('title') if d else None for d in dfp.milestone]\n", + "closed_dates = pd.to_datetime(df['closedAt'], format='ISO8601')\n", + "dfp['year'] = closed_dates.dt.year\n", + "\n", + "# TODO: Split by YEAR before dropping 'closedAt'\n", + "dfp.drop(columns=['closedAt','milestone', 'url'], inplace=True)\n", + "print(dfp)" ] }, { @@ -80,7 +105,14 @@ "metadata": {}, "outputs": [], "source": [ - "df['mile'] = [d.get('title') if d else None for d in df.milestone]" + "\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)" ] }, { @@ -89,9 +121,11 @@ "metadata": {}, "outputs": [], "source": [ + "mile_counts = df.groupby('mile')['count'].sum()\n", + "mile_counts = mile_counts.loc[lambda x: x > 5]\n", "\n", - "dfg = df.groupby(['mile', 'closed_month']).count().reset_index()\n", - "dfg.drop(columns=['milestone', 'title', 'url'], inplace=True)\n" + "\n", + "print(mile_counts)" ] }, { @@ -101,7 +135,19 @@ "outputs": [], "source": [ "\n", - "print(dfg)" + "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)" ] }, { @@ -113,7 +159,38 @@ }, { "cell_type": "code", - "execution_count": 32, + "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": [ @@ -142,7 +219,8 @@ "outputs": [], "source": [ "plt.figure(figsize=(10, 6))\n", - "sns.barplot(x='closed_month', y='count', hue='mile', data=dfg)\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",