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154 lines
6.9 KiB
154 lines
6.9 KiB
{
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"cells": [
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{
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"cell_type": "markdown",
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"source": [
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"# NYC-Taxidaten im Winter und Sommer\n",
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"\n",
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"Siehe das [Datenwörterbuch](https://www1.nyc.gov/assets/tlc/downloads/pdf/data_dictionary_trip_records_yellow.pdf), um mehr über die bereitgestellten Spalten zu erfahren.\n"
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],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [
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"#Install the pandas library\r\n",
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"!pip install pandas"
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],
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"outputs": [],
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"metadata": {
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"scrolled": true
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}
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"source": [
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"import pandas as pd\r\n",
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"\r\n",
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"path = '../../data/taxi.csv'\r\n",
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"\r\n",
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"#Load the csv file into a dataframe\r\n",
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"df = pd.read_csv(path)\r\n",
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"\r\n",
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"#Print the dataframe\r\n",
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"print(df)\r\n"
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],
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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" VendorID tpep_pickup_datetime tpep_dropoff_datetime passenger_count \\\n",
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"0 2.0 2019-07-15 16:27:53 2019-07-15 16:44:21 3.0 \n",
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"1 2.0 2019-07-17 20:26:35 2019-07-17 20:40:09 6.0 \n",
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"2 2.0 2019-07-06 16:01:08 2019-07-06 16:10:25 1.0 \n",
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"3 1.0 2019-07-18 22:32:23 2019-07-18 22:35:08 1.0 \n",
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"4 2.0 2019-07-19 14:54:29 2019-07-19 15:19:08 1.0 \n",
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".. ... ... ... ... \n",
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"195 2.0 2019-01-18 08:42:15 2019-01-18 08:56:57 1.0 \n",
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"196 1.0 2019-01-19 04:34:45 2019-01-19 04:43:44 1.0 \n",
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"197 2.0 2019-01-05 10:37:39 2019-01-05 10:42:03 1.0 \n",
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"198 2.0 2019-01-23 10:36:29 2019-01-23 10:44:34 2.0 \n",
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"199 2.0 2019-01-30 06:55:58 2019-01-30 07:07:02 5.0 \n",
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"\n",
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" trip_distance RatecodeID store_and_fwd_flag PULocationID DOLocationID \\\n",
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"0 2.02 1.0 N 186 233 \n",
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"1 1.59 1.0 N 141 161 \n",
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"2 1.69 1.0 N 246 249 \n",
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"3 0.90 1.0 N 229 141 \n",
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"4 4.79 1.0 N 237 107 \n",
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".. ... ... ... ... ... \n",
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"195 1.18 1.0 N 43 237 \n",
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"196 2.30 1.0 N 148 234 \n",
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"197 0.83 1.0 N 237 263 \n",
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"198 1.12 1.0 N 144 113 \n",
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"199 2.41 1.0 N 209 107 \n",
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"\n",
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" payment_type fare_amount extra mta_tax tip_amount tolls_amount \\\n",
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"0 1.0 12.0 1.0 0.5 4.08 0.0 \n",
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"1 2.0 10.0 0.5 0.5 0.00 0.0 \n",
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"2 2.0 8.5 0.0 0.5 0.00 0.0 \n",
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"3 1.0 4.5 3.0 0.5 1.65 0.0 \n",
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"4 1.0 19.5 0.0 0.5 5.70 0.0 \n",
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".. ... ... ... ... ... ... \n",
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"195 1.0 10.0 0.0 0.5 2.16 0.0 \n",
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"196 1.0 9.5 0.5 0.5 2.15 0.0 \n",
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"197 1.0 5.0 0.0 0.5 1.16 0.0 \n",
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"198 2.0 7.0 0.0 0.5 0.00 0.0 \n",
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"199 1.0 10.5 0.0 0.5 1.00 0.0 \n",
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"\n",
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" improvement_surcharge total_amount congestion_surcharge \n",
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"0 0.3 20.38 2.5 \n",
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"1 0.3 13.80 2.5 \n",
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"2 0.3 11.80 2.5 \n",
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"3 0.3 9.95 2.5 \n",
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"4 0.3 28.50 2.5 \n",
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".. ... ... ... \n",
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"195 0.3 12.96 0.0 \n",
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"196 0.3 12.95 0.0 \n",
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"197 0.3 6.96 0.0 \n",
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"198 0.3 7.80 0.0 \n",
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"199 0.3 12.30 0.0 \n",
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"\n",
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"[200 rows x 18 columns]\n"
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]
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}
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],
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"metadata": {}
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},
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{
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"cell_type": "markdown",
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"source": [
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"# Verwenden Sie die folgenden Zellen, um Ihre eigene explorative Datenanalyse durchzuführen\n"
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],
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"metadata": {}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"source": [],
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"outputs": [],
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"metadata": {}
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n---\n\n**Haftungsausschluss**: \nDieses Dokument wurde mit dem KI-Übersetzungsdienst [Co-op Translator](https://github.com/Azure/co-op-translator) übersetzt. Obwohl wir uns um Genauigkeit bemühen, beachten Sie bitte, dass automatisierte Übersetzungen Fehler oder Ungenauigkeiten enthalten können. Das Originaldokument in seiner ursprünglichen Sprache sollte als maßgebliche Quelle betrachtet werden. Für kritische Informationen wird eine professionelle menschliche Übersetzung empfohlen. Wir übernehmen keine Haftung für Missverständnisse oder Fehlinterpretationen, die sich aus der Nutzung dieser Übersetzung ergeben.\n"
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]
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}
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