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Merge pull request #1148 from cal-itp/annual_ntd_outline
Start of Annual NTD Ridership Report Outline
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‎ntd_annual_ridership/README.md

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# NTD Annual Ridership by RTPA
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Provide CalSTA with NTD Annual Ridership by each regional transportation planning authority (RTPA)
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This reoport shows general ridership trends by agency, mode and type of service.
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## Dataset
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1. [NTD Annual Service data](https://www.transit.dot.gov/ntd/data-product/2022-annual-database-service)
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2. [RTPA list](https://gis.data.ca.gov/datasets/CAEnergy::regional-transportation-planning-agencies/explore?appid=cf412a17daaa47bca93c6d6b7e77aff0&edit=true)
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3. Download our processed data here
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‎ntd_annual_ridership/annual_report_test2.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "f69ce09b-de2a-4d6e-a5b9-d6fa2ecf2be2",
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"metadata": {},
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"outputs": [],
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"source": [
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"from calitp_data_analysis.tables import tbls\n",
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"from siuba import *\n",
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"import pandas as pd\n",
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"GCS_FILE_PATH = \"gs://calitp-analytics-data/data-analyses/ntd/\"\n",
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"\n",
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"pd.set_option('display.max_rows', None) \n",
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"pd.set_option('display.max_columns', None) "
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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": 16,
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"id": "d92464c2-e8a2-46b4-a78e-8f25d2bb4c3f",
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"metadata": {},
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"outputs": [],
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"source": [
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"# using siuba to read in data from warehouse.\n",
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"ntd_info = (tbls.mart_ntd.dim_annual_ntd_agency_information() \n",
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" >> filter(_._is_current == True,\n",
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" _.year == 2022,\n",
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" _.region == 9) \n",
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" >> collect()\n",
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" )\n",
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"\n",
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"# need to find a way to filter ntd service to California agencies only. \n",
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"ntd_service = (tbls.mart_ntd.dim_annual_ntd_agency_service()\n",
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" >> group_by(_.ntd_id)\n",
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" >> distinct(_.agency_name)\n",
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" >> collect()\n",
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" )#can i add pd filters after this?\n",
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"\n",
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"# reading in NTD ID crosswalk from GCS\n",
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"crosswalk = pd.read_csv(\n",
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" f\"{GCS_FILE_PATH}ntd_id_rtpa_crosswalk.csv\", \n",
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" dtype = {\"NTD ID\": \"str\"}\n",
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" ).rename(columns={\"NTD ID\": \"ntd_id\"})"
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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": 17,
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"id": "a5dc49d8-6da7-422a-8482-d4bacafde914",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(322, 46)"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
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"(2259, 2)"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": [
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"(117, 6)"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"display(\n",
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" ntd_info.shape,\n",
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" ntd_service.shape,\n",
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" crosswalk.shape\n",
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")"
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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": 19,
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"id": "82a51ca6-8150-431e-8b4c-acf7be22e240",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>ntd_id</th>\n",
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" <th>agency_name</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>00001</td>\n",
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" <td>King County Department of Metro Transit</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>00002</td>\n",
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" <td>Spokane Transit Authority</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>00003</td>\n",
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" <td>Pierce County Transportation Benefit Area Auth...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>00004</td>\n",
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" <td>Confederated Tribes of the Colville Indian Res...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>00005</td>\n",
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" <td>City of Everett</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" ntd_id agency_name\n",
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"0 00001 King County Department of Metro Transit\n",
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"1 00002 Spokane Transit Authority\n",
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"2 00003 Pierce County Transportation Benefit Area Auth...\n",
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"3 00004 Confederated Tribes of the Colville Indian Res...\n",
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"4 00005 City of Everett"
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]
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},
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"execution_count": 19,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"ntd_service.head()"
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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": null,
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"id": "c025cbe8-6752-43c8-ba36-0eeb368fdd9c",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.13"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎ntd_annual_ridership/annual_ridership_DRAFT.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "34028321-6cdf-4264-867b-97f042d6d871",
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"metadata": {},
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"outputs": [],
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"source": [
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"%%capture\n",
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"import sys\n",
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"sys.path.append(\"../bus_service_increase\")\n",
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"\n",
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"import warnings\n",
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"warnings.filterwarnings('ignore')\n",
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"\n",
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"import altair as alt\n",
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"import calitp_data_analysis.magics\n",
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"import pandas as pd\n",
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"\n",
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"from IPython.display import display, HTML\n",
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"\n",
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"from bus_service_utils import chart_utils\n",
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"from calitp_data_analysis import calitp_color_palette as cp\n",
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"#from update_vars import GCS_FILE_PATH, PUBLIC_FILENAME, YEAR, MONTH\n",
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"#from monthly_ridership_by_rtpa import get_percent_change\n",
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"#from shared_utils.rt_dates import MONTH_DICT\n",
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"\n",
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"#alt.renderers.enable(\"html\")\n",
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"alt.data_transformers.enable('default', max_rows=None)"
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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": null,
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"id": "6437e80c-fa8a-433f-b2aa-7138360d04a1",
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"metadata": {
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"tags": [
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"parameter"
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]
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},
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"outputs": [],
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"source": [
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"# parameters cell for local\n",
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"rtpa = \"Metropolitan Transportation Commission\""
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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": null,
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"id": "b7055fb6-4331-425e-b4e5-e896b11b3acd",
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"metadata": {},
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"outputs": [],
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"source": [
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"%%capture_parameters\n",
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"rtpa"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8e07bb7c-ae9c-49ca-a875-9f3e2037d5f8",
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"metadata": {},
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"source": [
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"# {rtpa}\n",
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"## Annual Ridership Trends\n",
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"\n",
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"**Download data from our public [folder](https://console.cloud.google.com/storage/browser/calitp-publish-data-analysis)** by navigating to `ntd_annual_ridership` and selecting a file."
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]
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},
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{
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"cell_type": "markdown",
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"id": "9e285f5a-6c01-4c99-a442-a816ebe3ed63",
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"metadata": {},
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"source": [
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"### Transit Agency"
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]
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},
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{
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"cell_type": "markdown",
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"id": "888db6c8-df34-4399-93bd-1eced6fd6b09",
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"metadata": {},
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"source": [
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"### Transit Mode"
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]
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},
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{
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"cell_type": "markdown",
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"id": "e86a399b-1682-49c4-b9cc-cbdd2691777b",
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"metadata": {},
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"source": [
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"### Type of Service"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.13"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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