# gridwiz_analytics
Utilities to analyze GridWiz e-bike data from Excel files. **You provide the file at call-time** (e.g., `July.xlsx`).
## Install
```bash
pip install .
# or build first:
python -m build && pip install dist/*.whl
```
## Usage
```python
from gridwiz_analytics import (
RevenueTrendAnalyzer, PeakUsageAnalyzer,
HourlyPeakAnalyzer, BikeUsageAnalyzer,
DailyRevenueAnalyzer, DailyRidingAnalyzer
)
# Revenue per parking spot (read Excel when you instantiate)
rev = RevenueTrendAnalyzer("July.xlsx")
print(rev.total_revenue_by_spot())
rev.plot_revenue_by_spot(selected_spots=[
"Gridwiz Parking Area","Fakultas Teknik","Fakultas Kedokteran"
])
# Peak usage by day for selected spots
peak = PeakUsageAnalyzer("Agustus.xlsx")
peak.plot_daily_peak_usage(["Islamic Center"])
# Hourly usage for top-N spots
hourly = HourlyPeakAnalyzer("august.xlsx")
hourly.plot_hourly_usage_top_spots(from_spots=["Islamic Center","UTTARA"], top_n=5)
# Total usage counts (filtered list)
bike = BikeUsageAnalyzer("data_july.xlsx")
bike.plot_usage([
"Gridwiz Parking Area","Fakultas Teknik","UPT Perpustakaan","Rektorat"
])
# Daily revenue per spot (wide date range filled with zeros)
daily_rev = DailyRevenueAnalyzer("16-26.xlsx")
daily_rev.plot_daily_revenue(["Gridwiz Parking Area","Fakultas Teknik"])
# Daily riding counts per spot
daily_ride = DailyRidingAnalyzer("16-26.xlsx")
daily_ride.plot_daily_riding(["Islamic Center","UTTARA"], title="Daily Riding Partnership")
```
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"description": "# gridwiz_analytics\n\nUtilities to analyze GridWiz e-bike data from Excel files. **You provide the file at call-time** (e.g., `July.xlsx`).\n\n## Install\n```bash\npip install .\n# or build first:\npython -m build && pip install dist/*.whl\n```\n\n## Usage\n```python\nfrom gridwiz_analytics import (\n RevenueTrendAnalyzer, PeakUsageAnalyzer,\n HourlyPeakAnalyzer, BikeUsageAnalyzer,\n DailyRevenueAnalyzer, DailyRidingAnalyzer\n)\n\n# Revenue per parking spot (read Excel when you instantiate)\nrev = RevenueTrendAnalyzer(\"July.xlsx\")\nprint(rev.total_revenue_by_spot())\nrev.plot_revenue_by_spot(selected_spots=[\n \"Gridwiz Parking Area\",\"Fakultas Teknik\",\"Fakultas Kedokteran\"\n])\n\n# Peak usage by day for selected spots\npeak = PeakUsageAnalyzer(\"Agustus.xlsx\")\npeak.plot_daily_peak_usage([\"Islamic Center\"])\n\n# Hourly usage for top-N spots\nhourly = HourlyPeakAnalyzer(\"august.xlsx\")\nhourly.plot_hourly_usage_top_spots(from_spots=[\"Islamic Center\",\"UTTARA\"], top_n=5)\n\n# Total usage counts (filtered list)\nbike = BikeUsageAnalyzer(\"data_july.xlsx\")\nbike.plot_usage([\n \"Gridwiz Parking Area\",\"Fakultas Teknik\",\"UPT Perpustakaan\",\"Rektorat\"\n])\n\n# Daily revenue per spot (wide date range filled with zeros)\ndaily_rev = DailyRevenueAnalyzer(\"16-26.xlsx\")\ndaily_rev.plot_daily_revenue([\"Gridwiz Parking Area\",\"Fakultas Teknik\"])\n\n# Daily riding counts per spot\ndaily_ride = DailyRidingAnalyzer(\"16-26.xlsx\")\ndaily_ride.plot_daily_riding([\"Islamic Center\",\"UTTARA\"], title=\"Daily Riding Partnership\")\n```\n",
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