add markdown and new clean notebook for the script

project_prioritization/accessibility/Markdown.md

@@ -0,0 +1,10 @@
+# Converting Jsons to Shapefiles for Accessibility Analysis
+
+Use these steps to convert jsons to a zipped shape file: 
+1. Upload json file to folder in Jupyter Notebook
+2. Open notebook `project_location_to_shapefiles.ipynb`
+3. Add the following information for the uploaded to the function `json_to_shpfile`:
+    * json file, 
+    * name for geojson 
+    * then the name of the zip file output 
+4. Download your zipped shape file from the Cal-ITP GCS bucket or from the folder [zipped_locations](data-analyses/project_prioritization/accessibility/zipped_locations). 

project_prioritization/accessibility/_utils.py

@@ -19,17 +19,18 @@
 
 from shared_utils import utils
 
-# local_path = "/home/jovyan/data-analyses/project_prioritization/accessibility/"
+local_folder = "zipped_locations/"
 GCS_PATH = "gs://calitp-analytics-data/data-analyses/project_prioritization/zipped_shpfiles/"
 
 """
 For this function you will need to specify the name of the geojson file you want to read in before. example:
 file = "project_location_bike.geojson"
 """
 
-def read_and_create_shpfiles(geojson_file, zip_name):
+def read_and_create_shpfiles(geojson_file, zip_name, localfolder):
+    localfolder_str = str(localfolder)
     location = gpd.read_file(geojson_file)
-    location_zipped = utils.make_zipped_shapefile(location, zip_name, gcs_folder = GCS_PATH)
+    location_zipped = utils.make_zipped_shapefile(location, local_path = f"{localfolder_str}{zip_name}", gcs_folder = GCS_PATH)
 
 
 ## Function takes a json, creates a string and then modifies it so that it is in a geojson format that works for us. 
@@ -60,10 +61,16 @@ def manipulate_json(json_file, geojson_file_name):
 
 
 ## function puts together the two previous functions, to get from json file to shp file.
-def json_to_shpfile(json_file, geojson_file_name, zip_name):
+def json_to_shpfile(json_file, geojson_file_name, zip_name, local_folder):
+    '''
+    use this function to convert jsons to a zipped shp file
+    1. upload json file to folder in jupyter notebook
+    2. open notebook project_location_to_shapefiles.ipynb
+    3. add information for the uploaded json file, name for geojson and then the name of the zip file output 
+    '''
     ## run through json manipulation
     manipulate_json(json_file, geojson_file_name)
 
     ## run through function to get shpfiles
-    read_and_create_shpfiles(f"{geojson_file_name}.geojson", zip_name)    
+    read_and_create_shpfiles(f"{geojson_file_name}.geojson", zip_name, local_folder)    
 

project_prioritization/accessibility/project_location_to_shapefiles.ipynb

@@ -0,0 +1,111 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "20aaf3ca-9186-47ab-bb5a-2779c43de265",
+   "metadata": {},
+   "source": [
+    "# Converting Jsons to Zipped GeoJsons"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "6fcea931-86eb-4cc5-947a-3444e71485a7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import geopandas as gpd\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "import _utils\n",
+    "\n",
+    "import json\n",
+    "import re \n",
+    "import ast\n",
+    "import gcsfs\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "17f7db63-e65e-4821-a467-5a4628c998be",
+   "metadata": {},
+   "source": [
+    "### Use function in _utils"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e011563b-e4d8-4738-90f6-761499accfd3",
+   "metadata": {},
+   "source": [
+    "Add the following information for the uploaded to the function `json_to_shpfile`:\n",
+    "* json file, \n",
+    "* name for geojson \n",
+    "* then the name of the zip file output \n",
+    "\n",
+    "\n",
+    "Download your zipped shape file from the Cal-ITP GCS bucket or from the folder [zipped_locations](data-analyses/project_prioritization/accessibility/zipped_locations). \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "05afd750-4490-4485-b2e4-14c46047de2b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "_utils.json_to_shpfile('.json',      ##json file upload here\n",
+    "                       ''            ##local file name\n",
+    "                       'test_zipped_us101cc' ###name of the final zip file\n",
+    "                      )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "34e1d063-d483-4f38-a702-5fd4130f8930",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f3ca5cc4-2529-4f1a-87b6-d28a3282a51b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.13"
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "state": {},
+    "version_major": 2,
+    "version_minor": 0
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}