Datasets:
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"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# NYC Yellow Taxi 2017-10 데이터 탐색"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"\n",
"df = pd.read_parquet('yellow_tripdata_2017-10.parquet')\n",
"print(f'총 {len(df):,}건, {len(df.columns)}개 컬럼')\n",
"df.head(10)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"df.info()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"df.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Zone Lookup 매핑"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"zones = pd.read_csv('taxi+_zone_lookup.csv')\n",
"zones.head(10)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# 픽업/드롭오프에 Zone 이름 붙이기\n",
"df_named = df.merge(zones[['LocationID','Borough','Zone']], left_on='PULocationID', right_on='LocationID', how='left')\n",
"df_named = df_named.rename(columns={'Borough': 'PU_Borough', 'Zone': 'PU_Zone'}).drop(columns='LocationID')\n",
"df_named = df_named.merge(zones[['LocationID','Borough','Zone']], left_on='DOLocationID', right_on='LocationID', how='left')\n",
"df_named = df_named.rename(columns={'Borough': 'DO_Borough', 'Zone': 'DO_Zone'}).drop(columns='LocationID')\n",
"\n",
"df_named[['tpep_pickup_datetime','PU_Borough','PU_Zone','DO_Borough','DO_Zone','trip_distance','total_amount']].head(20)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 기본 분포"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# 픽업 많은 Zone Top 15\n",
"top_pu = df_named['PU_Zone'].value_counts().head(15)\n",
"print('=== 픽업 Top 15 ===')\n",
"print(top_pu)\n",
"print()\n",
"\n",
"# 자치구별 건수\n",
"print('=== 자치구별 픽업 ===')\n",
"print(df_named['PU_Borough'].value_counts())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# 시간대별 수요\n",
"df['hour'] = df['tpep_pickup_datetime'].dt.hour\n",
"hourly = df['hour'].value_counts().sort_index()\n",
"hourly.plot(kind='bar', figsize=(12,4), title='시간대별 픽업 건수')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# 거리 & 요금 분포 (이상치 제거)\n",
"reasonable = df[(df['trip_distance'] > 0) & (df['trip_distance'] < 30) & (df['total_amount'] > 0) & (df['total_amount'] < 100)]\n",
"reasonable[['trip_distance','total_amount']].hist(bins=50, figsize=(12,4))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"name": "python",
"version": "3.13.0"
}
},
"nbformat": 4,
"nbformat_minor": 4
} |