{ "cells": [ { "cell_type": "markdown", "source": [ "# Kış ve Yaz Aylarında NYC Taksi Verileri\n", "\n", "Sağlanan sütunlar hakkında daha fazla bilgi edinmek için [Veri sözlüğüne](https://www1.nyc.gov/assets/tlc/downloads/pdf/data_dictionary_trip_records_yellow.pdf) göz atabilirsiniz.\n" ], "metadata": {} }, { "cell_type": "code", "execution_count": null, "source": [ "#Install the pandas library\r\n", "!pip install pandas" ], "outputs": [], "metadata": { "scrolled": true } }, { "cell_type": "code", "execution_count": 7, "source": [ "import pandas as pd\r\n", "\r\n", "path = '../../data/taxi.csv'\r\n", "\r\n", "#Load the csv file into a dataframe\r\n", "df = pd.read_csv(path)\r\n", "\r\n", "#Print the dataframe\r\n", "print(df)\r\n" ], "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ " VendorID tpep_pickup_datetime tpep_dropoff_datetime passenger_count \\\n", "0 2.0 2019-07-15 16:27:53 2019-07-15 16:44:21 3.0 \n", "1 2.0 2019-07-17 20:26:35 2019-07-17 20:40:09 6.0 \n", "2 2.0 2019-07-06 16:01:08 2019-07-06 16:10:25 1.0 \n", "3 1.0 2019-07-18 22:32:23 2019-07-18 22:35:08 1.0 \n", "4 2.0 2019-07-19 14:54:29 2019-07-19 15:19:08 1.0 \n", ".. ... ... ... ... \n", "195 2.0 2019-01-18 08:42:15 2019-01-18 08:56:57 1.0 \n", "196 1.0 2019-01-19 04:34:45 2019-01-19 04:43:44 1.0 \n", "197 2.0 2019-01-05 10:37:39 2019-01-05 10:42:03 1.0 \n", "198 2.0 2019-01-23 10:36:29 2019-01-23 10:44:34 2.0 \n", "199 2.0 2019-01-30 06:55:58 2019-01-30 07:07:02 5.0 \n", "\n", " trip_distance RatecodeID store_and_fwd_flag PULocationID DOLocationID \\\n", "0 2.02 1.0 N 186 233 \n", "1 1.59 1.0 N 141 161 \n", "2 1.69 1.0 N 246 249 \n", "3 0.90 1.0 N 229 141 \n", "4 4.79 1.0 N 237 107 \n", ".. ... ... ... ... ... \n", "195 1.18 1.0 N 43 237 \n", "196 2.30 1.0 N 148 234 \n", "197 0.83 1.0 N 237 263 \n", "198 1.12 1.0 N 144 113 \n", "199 2.41 1.0 N 209 107 \n", "\n", " payment_type fare_amount extra mta_tax tip_amount tolls_amount \\\n", "0 1.0 12.0 1.0 0.5 4.08 0.0 \n", "1 2.0 10.0 0.5 0.5 0.00 0.0 \n", "2 2.0 8.5 0.0 0.5 0.00 0.0 \n", "3 1.0 4.5 3.0 0.5 1.65 0.0 \n", "4 1.0 19.5 0.0 0.5 5.70 0.0 \n", ".. ... ... ... ... ... ... \n", "195 1.0 10.0 0.0 0.5 2.16 0.0 \n", "196 1.0 9.5 0.5 0.5 2.15 0.0 \n", "197 1.0 5.0 0.0 0.5 1.16 0.0 \n", "198 2.0 7.0 0.0 0.5 0.00 0.0 \n", "199 1.0 10.5 0.0 0.5 1.00 0.0 \n", "\n", " improvement_surcharge total_amount congestion_surcharge \n", "0 0.3 20.38 2.5 \n", "1 0.3 13.80 2.5 \n", "2 0.3 11.80 2.5 \n", "3 0.3 9.95 2.5 \n", "4 0.3 28.50 2.5 \n", ".. ... ... ... \n", "195 0.3 12.96 0.0 \n", "196 0.3 12.95 0.0 \n", "197 0.3 6.96 0.0 \n", "198 0.3 7.80 0.0 \n", "199 0.3 12.30 0.0 \n", "\n", "[200 rows x 18 columns]\n" ] } ], "metadata": {} }, { "cell_type": "markdown", "source": [ "# Aşağıdaki hücreleri kendi Keşifsel Veri Analizinizi yapmak için kullanın\n" ], "metadata": {} }, { "cell_type": "code", "execution_count": null, "source": [], "outputs": [], "metadata": {} }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n---\n\n**Feragatname**: \nBu belge, [Co-op Translator](https://github.com/Azure/co-op-translator) adlı yapay zeka çeviri hizmeti kullanılarak çevrilmiştir. Doğruluk için çaba göstersek de, otomatik çevirilerin hata veya yanlışlıklar içerebileceğini lütfen unutmayın. Belgenin orijinal dili, yetkili kaynak olarak kabul edilmelidir. Kritik bilgiler için profesyonel insan çevirisi önerilir. Bu çevirinin kullanımından kaynaklanan yanlış anlama veya yanlış yorumlamalardan sorumlu değiliz.\n" ] } ], "metadata": { "kernelspec": { "name": "python3", "display_name": "Python 3.9.7 64-bit ('venv': venv)" }, "language_info": { "mimetype": "text/x-python", "name": "python", "pygments_lexer": "ipython3", "codemirror_mode": { "name": "ipython", "version": 3 }, "version": "3.9.7", "nbconvert_exporter": "python", "file_extension": ".py" }, "name": "04-nyc-taxi-join-weather-in-pandas", "notebookId": 1709144033725344, "interpreter": { "hash": "6b9b57232c4b57163d057191678da2030059e733b8becc68f245de5a75abe84e" }, "coopTranslator": { "original_hash": "7bca1c1abc1e55842817b62e44e1a963", "translation_date": "2025-09-02T08:33:37+00:00", "source_file": "4-Data-Science-Lifecycle/15-analyzing/assignment.ipynb", "language_code": "tr" } }, "nbformat": 4, "nbformat_minor": 2 }