"cells": [
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import platform\n",
+ "print(platform.python_version())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\tprint(f\"{file}\", os.path.getsize(file))\n"
]
},
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "3.12.2\n"
- ]
- }
- ],
- "source": [
- "import platform\n",
- "print(platform.python_version())"
- ]
- },
{
"cell_type": "code",
"execution_count": null,
"\n",
"data_sets = []\n",
"\n",
- "file = data_files[6]\n",
+ "file = data_files[2]\n",
"print(file)\n",
"\n",
- "f = open(file, encoding='utf-16')\n",
+ "f = open(file, encoding='utf-8')\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,
"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"
+ "df['closed_month'] = closed_months.dt.month\n",
+ "df.drop(columns=['closedAt'], inplace=True)"
]
},
{
"cell_type": "code",
- "execution_count": 69,
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": [
},
{
"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,
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\n",
- "grp_df = df.groupby(['mile', 'closed_month']).count().reset_index()"
+ "grp_df = df.groupby(['mile', 'closed_month']).count().reset_index()\n",
+ "grp_df.drop(columns=['milestone', 'title', 'url'], inplace=True)"
]
},
{
"metadata": {},
"outputs": [],
"source": [
+ "\n",
"print(grp_df)"
]
},
"cell_type": "markdown",
"metadata": {},
"source": [
- "#### Plot of closed issues by month for one project\n"
+ "#### Plot of closed issues by month and milestone for one project\n"
]
},
{
"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",
"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",
+ "sns.barplot(x='closed_month', y='url', hue='mile', data=grp_df)\n",
"plt.xlabel('Closed Month')\n",
"plt.ylabel('ClosedAt')\n",
"plt.title('Stacked Line Chart: Milestone Effort by Issue Close Date')\n",