Uber veri seti güncel (15.12.2025)

.gitattributes

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 final_enriched_trip_data_1000000.csv filter=lfs diff=lfs merge=lfs -text
 gtfs_subway/stop_times.txt filter=lfs diff=lfs merge=lfs -text
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+taxi_zones/taxi_zones.dbf filter=lfs diff=lfs merge=lfs -text
+taxi_zones/taxi_zones.shp filter=lfs diff=lfs merge=lfs -text

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output_files/pipeline_state.json

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+}

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taxi_zones/process_local_shapefile.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fbd48c35",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "📂 Yerel Shapefile işleniyor: taxi_zones.shp...\n",
+      "   -> Projeksiyon dönüştürülüyor (EPSG:2263 -> EPSG:4326)...\n",
+      "   -> Bulunan Sütunlar: ['OBJECTID', 'Shape_Leng', 'Shape_Area', 'zone', 'LocationID', 'borough', 'geometry', 'longitude', 'latitude']\n",
+      "✅ BAŞARILI: 'taxi_zones_centroids.csv' oluşturuldu.\n",
+      "   -> Toplam Bölge: 263\n",
+      "   -> Örnek Veri:\n",
+      "   location_id borough            zone   latitude  longitude\n",
+      "0            1     EWR  Newark Airport  40.691831    -74.174\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_22201/2703805781.py:28: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n",
+      "\n",
+      "  gdf['longitude'] = gdf.geometry.centroid.x\n",
+      "/tmp/ipykernel_22201/2703805781.py:29: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n",
+      "\n",
+      "  gdf['latitude'] = gdf.geometry.centroid.y\n"
+     ]
+    }
+   ],
+   "source": [
+    "# tek seferlik çalıştırdım      .\n",
+    "\n",
+    "import geopandas as gpd\n",
+    "import pandas as pd\n",
+    "import os\n",
+    "\n",
+    "def process_local_shapefile():\n",
+    "    input_file = \"taxi_zones.shp\"\n",
+    "    output_file = \"../taxi_zones_centroids.csv\"\n",
+    "    \n",
+    "    print(f\"Yerel Shapefile işleniyor: {input_file}...\")\n",
+    "    \n",
+    "    if not os.path.exists(input_file):\n",
+    "        print(\"HATA: 'taxi_zones.shp' dosyası bulunamadı!\")\n",
+    "        print(\"Lütfen tüm (.shp, .dbf, .shx, .prj...) dosyalarını bu klasöre koyduğunuzdan emin olun.\")\n",
+    "        return\n",
+    "\n",
+    "    try:\n",
+    "        gdf = gpd.read_file(input_file)\n",
+    "        \n",
+    "        # koordinat sistemini dönüştürür\n",
+    "        # orijinal dosya \"NAD83 / New York Long Island\" (EPSG:2263) formatında\n",
+    "        # bizim simülasyon için \"WGS84\" (Lat/Lon - EPSG:4326) gerekir.\n",
+    "        if gdf.crs.to_string() != \"EPSG:4326\":\n",
+    "            print(f\"   -> Projeksiyon dönüştürülüyor ({gdf.crs.to_string()} -> EPSG:4326)...\")\n",
+    "            gdf = gdf.to_crs(epsg=4326)\n",
+    "            \n",
+    "        # merkez nokta hesabı\n",
+    "        gdf['longitude'] = gdf.geometry.centroid.x\n",
+    "        gdf['latitude'] = gdf.geometry.centroid.y\n",
+    "\n",
+    "        cols = gdf.columns.tolist()\n",
+    "        print(f\"-> Bulunan Sütunlar: {cols}\")\n",
+    "        \n",
+    "        target_cols = ['LocationID', 'borough', 'zone', 'latitude', 'longitude']\n",
+    "        \n",
+    "        rename_map = {c: c for c in cols}\n",
+    "        for c in cols:\n",
+    "            if c.lower() == 'locationid': rename_map[c] = 'location_id'\n",
+    "            \n",
+    "        gdf = gdf.rename(columns=rename_map)\n",
+    "        \n",
+    "        if 'LocationID' in gdf.columns:\n",
+    "            centroids = gdf[['LocationID', 'borough', 'zone', 'latitude', 'longitude']].copy()\n",
+    "            centroids.rename(columns={'LocationID': 'location_id'}, inplace=True)\n",
+    "        elif 'location_id' in gdf.columns:\n",
+    "            centroids = gdf[['location_id', 'borough', 'zone', 'latitude', 'longitude']].copy()\n",
+    "        else:\n",
+    "            # Fallback: ID bulamazsa index kullan (Riskli ama çözüm)\n",
+    "            print(\"⚠️ UYARI: LocationID bulunamadı, OBJECTID kullanılıyor.\")\n",
+    "            centroids = gdf[['OBJECTID', 'borough', 'zone', 'latitude', 'longitude']].copy()\n",
+    "            centroids.rename(columns={'OBJECTID': 'location_id'}, inplace=True)\n",
+    "\n",
+    "        centroids['location_id'] = centroids['location_id'].astype(int)\n",
+    "        \n",
+    "        centroids.to_csv(output_file, index=False)\n",
+    "        \n",
+    "        print(f\"BAŞARILI: '{output_file}' oluşturuldu.\")\n",
+    "        print(f\"-> Toplam Bölge: {len(centroids)}\")\n",
+    "        print(f\"-> Örnek Veri:\\n{centroids.head(1)}\")\n",
+    "        \n",
+    "    except Exception as e:\n",
+    "        print(f\"BEKLENMEYEN HATA: {e}\")\n",
+    "\n",
+    "if __name__ == \"__main__\":\n",
+    "    process_local_shapefile()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d57e094b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "torch_env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.19"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

taxi_zones/taxi_zones.dbf

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taxi_zones/taxi_zones.prj

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+PROJCS["NAD_1983_StatePlane_New_York_Long_Island_FIPS_3104_Feet",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",984250.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-74.0],PARAMETER["Standard_Parallel_1",40.66666666666666],PARAMETER["Standard_Parallel_2",41.03333333333333],PARAMETER["Latitude_Of_Origin",40.16666666666666],UNIT["Foot_US",0.3048006096012192]]

taxi_zones/taxi_zones.shp

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taxi_zones/taxi_zones.shp.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<metadata xml:lang="en"><Esri><CreaDate>20150921</CreaDate><CreaTime>14030900</CreaTime><ArcGISFormat>1.0</ArcGISFormat><SyncOnce>TRUE</SyncOnce><DataProperties><lineage><Process ToolSource="c:\program files (x86)\arcgis\desktop10.1\ArcToolbox\Toolboxes\Data Management Tools.tbx\CalculateField" Date="20150921" Time="140309">CalculateField taxi_zones zone [Taxi_zone] VB #</Process><Process ToolSource="c:\program files (x86)\arcgis\desktop10.1\ArcToolbox\Toolboxes\Data Management Tools.tbx\CalculateField" Date="20150921" Time="140325">CalculateField taxi_zones LocationID [taxi_zone_] VB #</Process><Process ToolSource="c:\program files (x86)\arcgis\desktop10.1\ArcToolbox\Toolboxes\Data Management Tools.tbx\CalculateField" Date="20150921" Time="140338">CalculateField taxi_zones borough [FIRST_Boro] VB #</Process></lineage></DataProperties></Esri></metadata>

taxi_zones_centroids.csv

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+location_id,borough,zone,latitude,longitude
+1,EWR,Newark Airport,40.69183120640151,-74.17400027276302
+2,Queens,Jamaica Bay,40.616745291659875,-73.83129854302209
+3,Bronx,Allerton/Pelham Gardens,40.86447368477544,-73.84742223236718
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+5,Staten Island,Arden Heights,40.552659286945655,-74.1884841018493
+6,Staten Island,Arrochar/Fort Wadsworth,40.60032414603465,-74.07177055895139
+7,Queens,Astoria,40.76149256216375,-73.91969431946073
+8,Queens,Astoria Park,40.77855865375072,-73.92308615750751
+9,Queens,Auburndale,40.75103502557237,-73.78794887777892
+10,Queens,Baisley Park,40.678953310115254,-73.79098635986959
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+22,Brooklyn,Bensonhurst West,40.61221825780563,-73.99525857986234
+23,Staten Island,Bloomfield/Emerson Hill,40.606447701027484,-74.17088688155239
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+28,Queens,Briarwood/Jamaica Hills,40.711596357945076,-73.80872901637517
+29,Brooklyn,Brighton Beach,40.5809219719338,-73.96121676866855
+30,Queens,Broad Channel,40.60368744213565,-73.8219269567942
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