"data_files = glob.glob(os.path.expanduser('~\\\\Data\\\\*.json'))\n"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import os\n",
+ "\n",
+ "for file in data_files:\n",
+ "\tprint(f\"{file}\", os.path.getsize(file))\n"
+ ]
+ },
{
"cell_type": "code",
"execution_count": 5,
"\n",
"data_sets = []\n",
"\n",
- "file = data_files[0]\n",
+ "file = data_files[6]\n",
"print(file)\n",
"\n",
"f = open(file, encoding='utf-16')\n",
- "data = pd.read_json(f)\n",
+ "df = pd.read_json(f)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "<class 'pandas._libs.tslibs.timestamps.Timestamp'>\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(type(df.closed[0]))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "df['count'] = np.zeros(len(df))\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "print(df.milestone[22].get('title'))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 68,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "closed_months = pd.to_datetime(df['closedAt'], format='ISO8601')\n",
+ "df['closed_month'] = closed_months.dt.month"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 69,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "df['mile'] = [d.get('title') if d else None for d in df.milestone]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 39,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "for_plot = df.groupby(df.closed.dt.month)['url'].count()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 70,
+ "metadata": {},
+ "outputs": [],
+ "source": [
"\n",
- "print(data)\n"
+ "grp_df = df.groupby(['mile', 'closed_month']).count().reset_index()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "print(grp_df)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Plot of closed issues by month for one project\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "for_plot.plot(kind='bar')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 75,
+ "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.lineplot(x='closed_month', y='url', hue='mile', data=grp_df, marker='o', ci=None)\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()"
]
}
],