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March 3, 2018 22:52
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opendata hackathon 2018 (rough draft)
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| { | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "- https://data.winnipeg.ca/Recreation/Pool-Facility-Usage/j4s8-s9ap\n", | |
| " \n", | |
| " " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 1, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:05.274240Z", | |
| "start_time": "2018-03-03T22:49:05.269528Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "#!pip install sodapy" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 2, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:05.686883Z", | |
| "start_time": "2018-03-03T22:49:05.277887Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "import pandas as pd\n", | |
| "from sodapy import Socrata" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 3, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:06.217582Z", | |
| "start_time": "2018-03-03T22:49:05.689848Z" | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stderr", | |
| "output_type": "stream", | |
| "text": [ | |
| "WARNING:root:Requests made without an app_token will be subject to strict throttling limits.\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "client = Socrata(\"data.winnipeg.ca\", None)\n", | |
| "results = client.get(\"t2d2-j4v9\", limit=2000)\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 4, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:06.231800Z", | |
| "start_time": "2018-03-03T22:49:06.220507Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "df = pd.DataFrame.from_records(results)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 5, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:06.249445Z", | |
| "start_time": "2018-03-03T22:49:06.234000Z" | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "Index(['activity_category', 'activity_name', 'activity_number',\n", | |
| " 'activity_status', 'activity_type', 'attendance', 'center',\n", | |
| " 'customer_type', 'end_date', 'end_time', 'event_type', 'item_name',\n", | |
| " 'item_type', 'schedule_type', 'secondary_category', 'start_date',\n", | |
| " 'start_time'],\n", | |
| " dtype='object')" | |
| ] | |
| }, | |
| "execution_count": 5, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "df.columns" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 6, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:06.273564Z", | |
| "start_time": "2018-03-03T22:49:06.251690Z" | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
| "<div>\n", | |
| "<style scoped>\n", | |
| " .dataframe tbody tr th:only-of-type {\n", | |
| " vertical-align: middle;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe tbody tr th {\n", | |
| " vertical-align: top;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe thead th {\n", | |
| " text-align: right;\n", | |
| " }\n", | |
| "</style>\n", | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>0</th>\n", | |
| " <th>1</th>\n", | |
| " <th>2</th>\n", | |
| " <th>3</th>\n", | |
| " <th>4</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>activity_category</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>Preschool - Birth to 5 years</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>activity_name</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>Kinder Ballet Level I 3-5 years</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>activity_number</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>6259</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>activity_status</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>Closed</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>activity_type</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>Activity</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>attendance</th>\n", | |
| " <td>30</td>\n", | |
| " <td>15</td>\n", | |
| " <td>30</td>\n", | |
| " <td>11</td>\n", | |
| " <td>6</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>center</th>\n", | |
| " <td>Pan Am Pool</td>\n", | |
| " <td>Cindy Klassen Recreation Complex</td>\n", | |
| " <td>Pan Am Pool</td>\n", | |
| " <td>Pan Am Pool</td>\n", | |
| " <td>Pan Am Pool</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>customer_type</th>\n", | |
| " <td>Authorized Agent</td>\n", | |
| " <td>Authorized Agent</td>\n", | |
| " <td>Authorized Agent</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>General Public</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>end_date</th>\n", | |
| " <td>2016-01-19T00:00:00.000</td>\n", | |
| " <td>2016-01-30T00:00:00.000</td>\n", | |
| " <td>2016-01-22T00:00:00.000</td>\n", | |
| " <td>2016-02-20T00:00:00.000</td>\n", | |
| " <td>2016-03-05T00:00:00.000</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>end_time</th>\n", | |
| " <td>8:00 PM</td>\n", | |
| " <td>8:30 AM</td>\n", | |
| " <td>7:30 AM</td>\n", | |
| " <td>9:45 AM</td>\n", | |
| " <td>11:30 AM</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>event_type</th>\n", | |
| " <td>Aquatics - Contract User</td>\n", | |
| " <td>Aquatics - Contract User</td>\n", | |
| " <td>Aquatics - Contract User</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>Aquatics - Contract User</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>item_name</th>\n", | |
| " <td>PAP - Middle - Lane 6</td>\n", | |
| " <td>CKRC - Middle - Lane 7</td>\n", | |
| " <td>PAP - Middle - Lane 10</td>\n", | |
| " <td>PAP - Kiddie Pool - Area 1</td>\n", | |
| " <td>PAP - Training - North - Lane 1</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>item_type</th>\n", | |
| " <td>Pool - Indoor</td>\n", | |
| " <td>Pool - Indoor</td>\n", | |
| " <td>Pool - Indoor</td>\n", | |
| " <td>Pool - Indoor</td>\n", | |
| " <td>Pool - Indoor</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>schedule_type</th>\n", | |
| " <td>External Reservation</td>\n", | |
| " <td>External Reservation</td>\n", | |
| " <td>External Reservation</td>\n", | |
| " <td>Standard Activity</td>\n", | |
| " <td>External Reservation</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>secondary_category</th>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>NaN</td>\n", | |
| " <td>Movement/Fitness</td>\n", | |
| " <td>NaN</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>start_date</th>\n", | |
| " <td>2016-01-19T00:00:00.000</td>\n", | |
| " <td>2016-01-30T00:00:00.000</td>\n", | |
| " <td>2016-01-22T00:00:00.000</td>\n", | |
| " <td>2016-02-20T00:00:00.000</td>\n", | |
| " <td>2016-03-05T00:00:00.000</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>start_time</th>\n", | |
| " <td>5:00 PM</td>\n", | |
| " <td>7:30 AM</td>\n", | |
| " <td>5:45 AM</td>\n", | |
| " <td>9:00 AM</td>\n", | |
| " <td>10:00 AM</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| " 0 \\\n", | |
| "activity_category NaN \n", | |
| "activity_name NaN \n", | |
| "activity_number NaN \n", | |
| "activity_status NaN \n", | |
| "activity_type NaN \n", | |
| "attendance 30 \n", | |
| "center Pan Am Pool \n", | |
| "customer_type Authorized Agent \n", | |
| "end_date 2016-01-19T00:00:00.000 \n", | |
| "end_time 8:00 PM \n", | |
| "event_type Aquatics - Contract User \n", | |
| "item_name PAP - Middle - Lane 6 \n", | |
| "item_type Pool - Indoor \n", | |
| "schedule_type External Reservation \n", | |
| "secondary_category NaN \n", | |
| "start_date 2016-01-19T00:00:00.000 \n", | |
| "start_time 5:00 PM \n", | |
| "\n", | |
| " 1 \\\n", | |
| "activity_category NaN \n", | |
| "activity_name NaN \n", | |
| "activity_number NaN \n", | |
| "activity_status NaN \n", | |
| "activity_type NaN \n", | |
| "attendance 15 \n", | |
| "center Cindy Klassen Recreation Complex \n", | |
| "customer_type Authorized Agent \n", | |
| "end_date 2016-01-30T00:00:00.000 \n", | |
| "end_time 8:30 AM \n", | |
| "event_type Aquatics - Contract User \n", | |
| "item_name CKRC - Middle - Lane 7 \n", | |
| "item_type Pool - Indoor \n", | |
| "schedule_type External Reservation \n", | |
| "secondary_category NaN \n", | |
| "start_date 2016-01-30T00:00:00.000 \n", | |
| "start_time 7:30 AM \n", | |
| "\n", | |
| " 2 3 \\\n", | |
| "activity_category NaN Preschool - Birth to 5 years \n", | |
| "activity_name NaN Kinder Ballet Level I 3-5 years \n", | |
| "activity_number NaN 6259 \n", | |
| "activity_status NaN Closed \n", | |
| "activity_type NaN Activity \n", | |
| "attendance 30 11 \n", | |
| "center Pan Am Pool Pan Am Pool \n", | |
| "customer_type Authorized Agent NaN \n", | |
| "end_date 2016-01-22T00:00:00.000 2016-02-20T00:00:00.000 \n", | |
| "end_time 7:30 AM 9:45 AM \n", | |
| "event_type Aquatics - Contract User NaN \n", | |
| "item_name PAP - Middle - Lane 10 PAP - Kiddie Pool - Area 1 \n", | |
| "item_type Pool - Indoor Pool - Indoor \n", | |
| "schedule_type External Reservation Standard Activity \n", | |
| "secondary_category NaN Movement/Fitness \n", | |
| "start_date 2016-01-22T00:00:00.000 2016-02-20T00:00:00.000 \n", | |
| "start_time 5:45 AM 9:00 AM \n", | |
| "\n", | |
| " 4 \n", | |
| "activity_category NaN \n", | |
| "activity_name NaN \n", | |
| "activity_number NaN \n", | |
| "activity_status NaN \n", | |
| "activity_type NaN \n", | |
| "attendance 6 \n", | |
| "center Pan Am Pool \n", | |
| "customer_type General Public \n", | |
| "end_date 2016-03-05T00:00:00.000 \n", | |
| "end_time 11:30 AM \n", | |
| "event_type Aquatics - Contract User \n", | |
| "item_name PAP - Training - North - Lane 1 \n", | |
| "item_type Pool - Indoor \n", | |
| "schedule_type External Reservation \n", | |
| "secondary_category NaN \n", | |
| "start_date 2016-03-05T00:00:00.000 \n", | |
| "start_time 10:00 AM " | |
| ] | |
| }, | |
| "execution_count": 6, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "df.head().T" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 7, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:06.605440Z", | |
| "start_time": "2018-03-03T22:49:06.275730Z" | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stderr", | |
| "output_type": "stream", | |
| "text": [ | |
| "WARNING:root:Requests made without an app_token will be subject to strict throttling limits.\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "client = Socrata(\"data.winnipeg.ca\", None)\n", | |
| "bugs = client.get(\"du7c-8488\", limit=2000)\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 8, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:06.621642Z", | |
| "start_time": "2018-03-03T22:49:06.608311Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "bugsdf = pd.DataFrame(bugs)\n", | |
| "bugsdf.T\n", | |
| "idvars = ['count_date', 'trap_days']" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 9, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:06.645020Z", | |
| "start_time": "2018-03-03T22:49:06.634085Z" | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/plain": [ | |
| "37" | |
| ] | |
| }, | |
| "execution_count": 9, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "idvars = ['count_date', 'trap_days']\n", | |
| "location_only = [x for x in bugsdf.columns if \"average\" not in x]\n", | |
| "location_only = [x for x in location_only if x not in idvars]\n", | |
| "len(location_only)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 10, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:06.763449Z", | |
| "start_time": "2018-03-03T22:49:06.648087Z" | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "Datasets.ipynb\tDatasets_v2.ipynb environment.yml\r\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "!ls " | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "hello world" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 11, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:06.776469Z", | |
| "start_time": "2018-03-03T22:49:06.765589Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "bugcleaned = pd.melt(bugsdf[location_only + idvars], id_vars = idvars, var_name = 'location', value_name = 'bugcount')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 12, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:07.235648Z", | |
| "start_time": "2018-03-03T22:49:06.779903Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "import seaborn as sns\n", | |
| "import matplotlib.pyplot as plt" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:13:32.163458Z", | |
| "start_time": "2018-03-03T22:13:32.060247Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 13, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:07.511118Z", | |
| "start_time": "2018-03-03T22:49:07.238249Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "parkbikedata = \"9t9k-ya8b\"\n", | |
| "parkbikedf = client.get(\"9t9k-ya8b\", limit=2000)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 14, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:07.578104Z", | |
| "start_time": "2018-03-03T22:49:07.513702Z" | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "text/html": [ | |
| "<div>\n", | |
| "<style scoped>\n", | |
| " .dataframe tbody tr th:only-of-type {\n", | |
| " vertical-align: middle;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe tbody tr th {\n", | |
| " vertical-align: top;\n", | |
| " }\n", | |
| "\n", | |
| " .dataframe thead th {\n", | |
| " text-align: right;\n", | |
| " }\n", | |
| "</style>\n", | |
| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
| " <th>0</th>\n", | |
| " <th>1</th>\n", | |
| " <th>2</th>\n", | |
| " <th>3</th>\n", | |
| " <th>4</th>\n", | |
| " <th>5</th>\n", | |
| " <th>6</th>\n", | |
| " <th>7</th>\n", | |
| " <th>8</th>\n", | |
| " <th>9</th>\n", | |
| " <th>...</th>\n", | |
| " <th>1990</th>\n", | |
| " <th>1991</th>\n", | |
| " <th>1992</th>\n", | |
| " <th>1993</th>\n", | |
| " <th>1994</th>\n", | |
| " <th>1995</th>\n", | |
| " <th>1996</th>\n", | |
| " <th>1997</th>\n", | |
| " <th>1998</th>\n", | |
| " <th>1999</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>asset_class</th>\n", | |
| " <td>STAND-ALONE PLAY COMPONENT</td>\n", | |
| " <td>SEATING</td>\n", | |
| " <td>SEATING</td>\n", | |
| " <td>SEATING</td>\n", | |
| " <td>SEATING</td>\n", | |
| " <td>SEATING</td>\n", | |
| " <td>SWING SET</td>\n", | |
| " <td>STAND-ALONE PLAY COMPONENT</td>\n", | |
| " <td>PLAY STRUCTURE</td>\n", | |
| " <td>SEATING</td>\n", | |
| " <td>...</td>\n", | |
| " <td>SEATING</td>\n", | |
| " <td>SEATING</td>\n", | |
| " <td>SEATING</td>\n", | |
| " <td>STAND-ALONE PLAY COMPONENT</td>\n", | |
| " <td>STAND-ALONE PLAY COMPONENT</td>\n", | |
| " <td>SWING SET</td>\n", | |
| " <td>STAND-ALONE PLAY COMPONENT</td>\n", | |
| " <td>SEATING</td>\n", | |
| " <td>BBQ</td>\n", | |
| " <td>SEATING</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>asset_id</th>\n", | |
| " <td>46292</td>\n", | |
| " <td>47525</td>\n", | |
| " <td>24478</td>\n", | |
| " <td>22744</td>\n", | |
| " <td>23769</td>\n", | |
| " <td>24506</td>\n", | |
| " <td>44743</td>\n", | |
| " <td>45304</td>\n", | |
| " <td>46922</td>\n", | |
| " <td>62218</td>\n", | |
| " <td>...</td>\n", | |
| " <td>35198</td>\n", | |
| " <td>24586</td>\n", | |
| " <td>23821</td>\n", | |
| " <td>46209</td>\n", | |
| " <td>45287</td>\n", | |
| " <td>62281</td>\n", | |
| " <td>45419</td>\n", | |
| " <td>23978</td>\n", | |
| " <td>38673</td>\n", | |
| " <td>22264</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>asset_size</th>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>1 BAY</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>SMALL</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>...</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>1 BAY</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>asset_type</th>\n", | |
| " <td>N/A</td>\n", | |
| " <td>BENCH</td>\n", | |
| " <td>BENCH</td>\n", | |
| " <td>BENCH</td>\n", | |
| " <td>BENCH</td>\n", | |
| " <td>BENCH</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>2 TO 5</td>\n", | |
| " <td>BENCH</td>\n", | |
| " <td>...</td>\n", | |
| " <td>PLAYERS BENCH</td>\n", | |
| " <td>BENCH</td>\n", | |
| " <td>BENCH</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>BENCH</td>\n", | |
| " <td>PIT</td>\n", | |
| " <td>BENCH</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>geom_type</th>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>...</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " <td>POINT</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>park_id</th>\n", | |
| " <td>1137</td>\n", | |
| " <td>266</td>\n", | |
| " <td>1179</td>\n", | |
| " <td>1040</td>\n", | |
| " <td>52</td>\n", | |
| " <td>918</td>\n", | |
| " <td>55</td>\n", | |
| " <td>410</td>\n", | |
| " <td>1137</td>\n", | |
| " <td>59</td>\n", | |
| " <td>...</td>\n", | |
| " <td>1070</td>\n", | |
| " <td>1070</td>\n", | |
| " <td>142</td>\n", | |
| " <td>237</td>\n", | |
| " <td>173</td>\n", | |
| " <td>146</td>\n", | |
| " <td>1129</td>\n", | |
| " <td>609</td>\n", | |
| " <td>1313</td>\n", | |
| " <td>747</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>park_name</th>\n", | |
| " <td>Frontenac Park</td>\n", | |
| " <td>Muriel Street Park</td>\n", | |
| " <td>Aberdeen Adventure Playground</td>\n", | |
| " <td>Wightman Green</td>\n", | |
| " <td>Rotary Prairie Nature Park</td>\n", | |
| " <td>Cordova Park</td>\n", | |
| " <td>Scouts Park</td>\n", | |
| " <td>Parr Tot Lot</td>\n", | |
| " <td>Frontenac Park</td>\n", | |
| " <td>Central Corydon C.C - River Heights Site</td>\n", | |
| " <td>...</td>\n", | |
| " <td>Kirkbridge Park</td>\n", | |
| " <td>Kirkbridge Park</td>\n", | |
| " <td>Valour C.C-Clifton Site</td>\n", | |
| " <td>George Minaker Park</td>\n", | |
| " <td>Pinkham Park</td>\n", | |
| " <td>Valour C.C - Isaac Brock Site</td>\n", | |
| " <td>Evesham Key Park</td>\n", | |
| " <td>Paulicelli Park</td>\n", | |
| " <td>Kilcona Park</td>\n", | |
| " <td>Parc Joseph Royal</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>prim_field</th>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>...</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " <td>N/A</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>the_geom</th>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.08174796...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.29729904...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.12915711...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.22794918...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.03366551...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.18933524...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.00751582...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.14154370...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.08170560...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.18075583...</td>\n", | |
| " <td>...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.16548156...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.16275159...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.18967885...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.27178997...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.15868988...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.18664174...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.26272864...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.02866826...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.03826030...</td>\n", | |
| " <td>{'type': 'Point', 'coordinates': [-97.12547259...</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>9 rows × 2000 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| " 0 \\\n", | |
| "asset_class STAND-ALONE PLAY COMPONENT \n", | |
| "asset_id 46292 \n", | |
| "asset_size N/A \n", | |
| "asset_type N/A \n", | |
| "geom_type POINT \n", | |
| "park_id 1137 \n", | |
| "park_name Frontenac Park \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.08174796... \n", | |
| "\n", | |
| " 1 \\\n", | |
| "asset_class SEATING \n", | |
| "asset_id 47525 \n", | |
| "asset_size N/A \n", | |
| "asset_type BENCH \n", | |
| "geom_type POINT \n", | |
| "park_id 266 \n", | |
| "park_name Muriel Street Park \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.29729904... \n", | |
| "\n", | |
| " 2 \\\n", | |
| "asset_class SEATING \n", | |
| "asset_id 24478 \n", | |
| "asset_size N/A \n", | |
| "asset_type BENCH \n", | |
| "geom_type POINT \n", | |
| "park_id 1179 \n", | |
| "park_name Aberdeen Adventure Playground \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.12915711... \n", | |
| "\n", | |
| " 3 \\\n", | |
| "asset_class SEATING \n", | |
| "asset_id 22744 \n", | |
| "asset_size N/A \n", | |
| "asset_type BENCH \n", | |
| "geom_type POINT \n", | |
| "park_id 1040 \n", | |
| "park_name Wightman Green \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.22794918... \n", | |
| "\n", | |
| " 4 \\\n", | |
| "asset_class SEATING \n", | |
| "asset_id 23769 \n", | |
| "asset_size N/A \n", | |
| "asset_type BENCH \n", | |
| "geom_type POINT \n", | |
| "park_id 52 \n", | |
| "park_name Rotary Prairie Nature Park \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.03366551... \n", | |
| "\n", | |
| " 5 \\\n", | |
| "asset_class SEATING \n", | |
| "asset_id 24506 \n", | |
| "asset_size N/A \n", | |
| "asset_type BENCH \n", | |
| "geom_type POINT \n", | |
| "park_id 918 \n", | |
| "park_name Cordova Park \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.18933524... \n", | |
| "\n", | |
| " 6 \\\n", | |
| "asset_class SWING SET \n", | |
| "asset_id 44743 \n", | |
| "asset_size 1 BAY \n", | |
| "asset_type N/A \n", | |
| "geom_type POINT \n", | |
| "park_id 55 \n", | |
| "park_name Scouts Park \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.00751582... \n", | |
| "\n", | |
| " 7 \\\n", | |
| "asset_class STAND-ALONE PLAY COMPONENT \n", | |
| "asset_id 45304 \n", | |
| "asset_size N/A \n", | |
| "asset_type N/A \n", | |
| "geom_type POINT \n", | |
| "park_id 410 \n", | |
| "park_name Parr Tot Lot \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.14154370... \n", | |
| "\n", | |
| " 8 \\\n", | |
| "asset_class PLAY STRUCTURE \n", | |
| "asset_id 46922 \n", | |
| "asset_size SMALL \n", | |
| "asset_type 2 TO 5 \n", | |
| "geom_type POINT \n", | |
| "park_id 1137 \n", | |
| "park_name Frontenac Park \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.08170560... \n", | |
| "\n", | |
| " 9 \\\n", | |
| "asset_class SEATING \n", | |
| "asset_id 62218 \n", | |
| "asset_size N/A \n", | |
| "asset_type BENCH \n", | |
| "geom_type POINT \n", | |
| "park_id 59 \n", | |
| "park_name Central Corydon C.C - River Heights Site \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.18075583... \n", | |
| "\n", | |
| " ... \\\n", | |
| "asset_class ... \n", | |
| "asset_id ... \n", | |
| "asset_size ... \n", | |
| "asset_type ... \n", | |
| "geom_type ... \n", | |
| "park_id ... \n", | |
| "park_name ... \n", | |
| "prim_field ... \n", | |
| "the_geom ... \n", | |
| "\n", | |
| " 1990 \\\n", | |
| "asset_class SEATING \n", | |
| "asset_id 35198 \n", | |
| "asset_size N/A \n", | |
| "asset_type PLAYERS BENCH \n", | |
| "geom_type POINT \n", | |
| "park_id 1070 \n", | |
| "park_name Kirkbridge Park \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.16548156... \n", | |
| "\n", | |
| " 1991 \\\n", | |
| "asset_class SEATING \n", | |
| "asset_id 24586 \n", | |
| "asset_size N/A \n", | |
| "asset_type BENCH \n", | |
| "geom_type POINT \n", | |
| "park_id 1070 \n", | |
| "park_name Kirkbridge Park \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.16275159... \n", | |
| "\n", | |
| " 1992 \\\n", | |
| "asset_class SEATING \n", | |
| "asset_id 23821 \n", | |
| "asset_size N/A \n", | |
| "asset_type BENCH \n", | |
| "geom_type POINT \n", | |
| "park_id 142 \n", | |
| "park_name Valour C.C-Clifton Site \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.18967885... \n", | |
| "\n", | |
| " 1993 \\\n", | |
| "asset_class STAND-ALONE PLAY COMPONENT \n", | |
| "asset_id 46209 \n", | |
| "asset_size N/A \n", | |
| "asset_type N/A \n", | |
| "geom_type POINT \n", | |
| "park_id 237 \n", | |
| "park_name George Minaker Park \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.27178997... \n", | |
| "\n", | |
| " 1994 \\\n", | |
| "asset_class STAND-ALONE PLAY COMPONENT \n", | |
| "asset_id 45287 \n", | |
| "asset_size N/A \n", | |
| "asset_type N/A \n", | |
| "geom_type POINT \n", | |
| "park_id 173 \n", | |
| "park_name Pinkham Park \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.15868988... \n", | |
| "\n", | |
| " 1995 \\\n", | |
| "asset_class SWING SET \n", | |
| "asset_id 62281 \n", | |
| "asset_size 1 BAY \n", | |
| "asset_type N/A \n", | |
| "geom_type POINT \n", | |
| "park_id 146 \n", | |
| "park_name Valour C.C - Isaac Brock Site \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.18664174... \n", | |
| "\n", | |
| " 1996 \\\n", | |
| "asset_class STAND-ALONE PLAY COMPONENT \n", | |
| "asset_id 45419 \n", | |
| "asset_size N/A \n", | |
| "asset_type N/A \n", | |
| "geom_type POINT \n", | |
| "park_id 1129 \n", | |
| "park_name Evesham Key Park \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.26272864... \n", | |
| "\n", | |
| " 1997 \\\n", | |
| "asset_class SEATING \n", | |
| "asset_id 23978 \n", | |
| "asset_size N/A \n", | |
| "asset_type BENCH \n", | |
| "geom_type POINT \n", | |
| "park_id 609 \n", | |
| "park_name Paulicelli Park \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.02866826... \n", | |
| "\n", | |
| " 1998 \\\n", | |
| "asset_class BBQ \n", | |
| "asset_id 38673 \n", | |
| "asset_size N/A \n", | |
| "asset_type PIT \n", | |
| "geom_type POINT \n", | |
| "park_id 1313 \n", | |
| "park_name Kilcona Park \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.03826030... \n", | |
| "\n", | |
| " 1999 \n", | |
| "asset_class SEATING \n", | |
| "asset_id 22264 \n", | |
| "asset_size N/A \n", | |
| "asset_type BENCH \n", | |
| "geom_type POINT \n", | |
| "park_id 747 \n", | |
| "park_name Parc Joseph Royal \n", | |
| "prim_field N/A \n", | |
| "the_geom {'type': 'Point', 'coordinates': [-97.12547259... \n", | |
| "\n", | |
| "[9 rows x 2000 columns]" | |
| ] | |
| }, | |
| "execution_count": 14, | |
| "metadata": {}, | |
| "output_type": "execute_result" | |
| } | |
| ], | |
| "source": [ | |
| "pd.DataFrame(parkbikedf).T" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 15, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:07.590691Z", | |
| "start_time": "2018-03-03T22:49:07.582964Z" | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stderr", | |
| "output_type": "stream", | |
| "text": [ | |
| "WARNING:root:Requests made without an app_token will be subject to strict throttling limits.\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "client = Socrata(\"data.winnipeg.ca\", None)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 16, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:07.599202Z", | |
| "start_time": "2018-03-03T22:49:07.594577Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "bikeurl = \"https://data.winnipeg.ca/resource/9t9k-ya8b.json\"" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 17, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:07.974047Z", | |
| "start_time": "2018-03-03T22:49:07.602187Z" | |
| }, | |
| "scrolled": true | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stderr", | |
| "output_type": "stream", | |
| "text": [ | |
| "WARNING:root:Requests made without an app_token will be subject to strict throttling limits.\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "client = Socrata(\"data.winnipeg.ca\", None)\n", | |
| "bikes = client.get(\"9t9k-ya8b\", limit=2000)\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "neighbourhood map\n", | |
| "\n", | |
| "https://data.winnipeg.ca/resource/xaux-29zr.json" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 18, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.618142Z", | |
| "start_time": "2018-03-03T22:49:07.977123Z" | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "name": "stderr", | |
| "output_type": "stream", | |
| "text": [ | |
| "WARNING:root:Requests made without an app_token will be subject to strict throttling limits.\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "client = Socrata(\"data.winnipeg.ca\", None)\n", | |
| "neighbourhoods = client.get(\"xaux-29zr\", limit=2000)\n", | |
| "import shapely.geometry\n", | |
| "from geopandas import GeoDataFrame\n", | |
| "neighbourhoods = GeoDataFrame(neighbourhoods)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 19, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.626792Z", | |
| "start_time": "2018-03-03T22:49:08.621024Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "import shapely.geometry\n", | |
| "example = [x['coordinates'] for x in neighbourhoods.the_geom][0]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 20, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.801674Z", | |
| "start_time": "2018-03-03T22:49:08.630416Z" | |
| } | |
| }, | |
| "outputs": [ | |
| { | |
| "ename": "NameError", | |
| "evalue": "name 'Polygon' is not defined", | |
| "output_type": "error", | |
| "traceback": [ | |
| "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", | |
| "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", | |
| "\u001b[0;32m<ipython-input-20-c35807141f48>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnewgeom\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mPolygon\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'coordinates'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mneighbourhoods\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mthe_geom\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", | |
| "\u001b[0;32m<ipython-input-20-c35807141f48>\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnewgeom\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mPolygon\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'coordinates'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mx\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mneighbourhoods\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mthe_geom\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", | |
| "\u001b[0;31mNameError\u001b[0m: name 'Polygon' is not defined" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "newgeom = [Polygon(x['coordinates'][0][0]) for x in neighbourhoods.the_geom]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.803306Z", | |
| "start_time": "2018-03-03T22:49:05.816Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "neighbourhoods['newgeom'] = newgeom\n", | |
| "neighbourhoods = neighbourhoods.set_geometry('newgeom')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.805454Z", | |
| "start_time": "2018-03-03T22:49:05.820Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "neighbourhoods.plot()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.807240Z", | |
| "start_time": "2018-03-03T22:49:05.829Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "neighbourhoods" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.809377Z", | |
| "start_time": "2018-03-03T22:49:05.833Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "neighbourhoods.the_geom[0].keys()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.811461Z", | |
| "start_time": "2018-03-03T22:49:05.837Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "neighbourhoods.the_geom[0]['type']" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.813522Z", | |
| "start_time": "2018-03-03T22:49:05.841Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "example = neighbourhoods.the_geom[0]['coordinates']" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.815562Z", | |
| "start_time": "2018-03-03T22:49:05.845Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "example[0][0]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.817605Z", | |
| "start_time": "2018-03-03T22:49:05.849Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "from shapely.geometry import Polygon\n", | |
| "Polygon(example[0][0])" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.819621Z", | |
| "start_time": "2018-03-03T22:49:05.859Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "from shapely.geometry import MultiPolygon\n", | |
| "MultiPolygon(example)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.821602Z", | |
| "start_time": "2018-03-03T22:49:05.864Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "set(new_geom)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.823678Z", | |
| "start_time": "2018-03-03T22:49:05.868Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "gdf.DataFrame(neighbourhoods)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.826019Z", | |
| "start_time": "2018-03-03T22:49:05.877Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "import shapely.geometry" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.828181Z", | |
| "start_time": "2018-03-03T22:49:05.884Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "neipd.DataFrame(neighbourhoods)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.830145Z", | |
| "start_time": "2018-03-03T22:49:05.894Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "bikes_df = pd.DataFrame(bikes)\n", | |
| "bikes_df.head()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.832160Z", | |
| "start_time": "2018-03-03T22:49:05.898Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "testcoord = bikes_df.the_geom[0]\n", | |
| "testcoord" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.834299Z", | |
| "start_time": "2018-03-03T22:49:05.903Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "import ipyleaflet" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.836400Z", | |
| "start_time": "2018-03-03T22:49:05.908Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "!jupyter nbextension enable --py --sys-prefix ipyleaflet" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.838561Z", | |
| "start_time": "2018-03-03T22:49:05.913Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "from ipyleaflet import Map" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.840775Z", | |
| "start_time": "2018-03-03T22:49:05.920Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "Map(center = testcoord['coordinates'])" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.844480Z", | |
| "start_time": "2018-03-03T22:49:05.925Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "# for x in bugcleaned.location.unique():\n", | |
| "# print(x)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T21:15:44.002394Z", | |
| "start_time": "2018-03-03T21:15:43.996590Z" | |
| } | |
| }, | |
| "source": [ | |
| "https://docs.google.com/document/d/1xWBXAFSwtUGgZ3hQmzXE7ODnufQEWkji26vnsqfZzZ0/\n", | |
| "\n", | |
| "http://winnipeg.ca/publicworks/insectcontrol/mosquitoes/nuisanceschedule.stm\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.846467Z", | |
| "start_time": "2018-03-03T22:49:06.174Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "client = Socrata(\"data.winnipeg.ca\", None)\n", | |
| "mapdata = \"tug6-p73s\"\n", | |
| "mapdata = client.get(\"tug6-p73s\", limit=2000)\n", | |
| "mapdata" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "North_east_1: 49.951867, -97.059306\n", | |
| "North_east_2: 49.933941, -97.096341\n", | |
| "North_east_3: 49.924809, -97.056330\n", | |
| "North_east_4: 49.906175, -97.094797\n", | |
| "North_east_5: 49.892358, -97.022426\n", | |
| "North_east_6: 49.918257, -97.043848\n", | |
| "North_east_7: 49.904900, -96.981602\n", | |
| "North_west_1: 49.890104, -97.308464\n", | |
| "North_west_2: 49.882624, -97.238131\n", | |
| "North_west_3: 49.888943, -97.193254\n", | |
| "North_west_4: 49.920877, -97.202540\n", | |
| "North_west_5: 49.931627, -97.170450\n", | |
| "North_west_6: 49.975104, -97.147863\n", | |
| "North_west_7: 49.948876, -97.126311\n", | |
| "Rural_aa: 49.981128, -97.244987\n", | |
| "Rural_bb: 49.999793, -97.194880\n", | |
| "Rural_cc: 49.991068, -97.089770\n", | |
| "Rural_dd: 49.990523, -97.013920\n", | |
| "Rural_ee: 49.852485, -96.986202\n", | |
| "Rural_ff: 49.800355, -97.073122\n", | |
| "Rural_gg: 49.782835, -97.339871\n", | |
| "Rural_hh: 49.854707, -97.338403 \n", | |
| "Rural_ii: 49.890188, -97.341707\n", | |
| "South_east_1: 49.5242.6, 97.07156\n", | |
| "South_east_2: 49.856801, -97.109705\n", | |
| "south_east_3:49.859405, -97.066774\n", | |
| "South_east_4: 49.824369, -97.133797\n", | |
| "South_east_5: 49.829048, -97.098352\n", | |
| "South_east_6: 49.827414, -97.060787\n", | |
| "South_east_7: 49.806356, -97.100467\n", | |
| "South_west_1: 49.832983, -97.332547\n", | |
| "South_west_2: 49.852445, -97.275173\n", | |
| "South_west_3: 49.868974, -97.243095\n", | |
| "South_west_4: 49.868834, -97.184476\n", | |
| "South_west_5: 49.818122, -97.165982\n", | |
| "South_west_6: 49.805538, -97.138229\n", | |
| "South_west_7: 49.827168, -97.170704\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.848332Z", | |
| "start_time": "2018-03-03T22:49:06.426Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "import geopandas" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.850142Z", | |
| "start_time": "2018-03-03T22:49:06.432Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "from geopandas import GeoDataFrame" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.851832Z", | |
| "start_time": "2018-03-03T22:49:06.437Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "from shapely.geometry import Point" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.853538Z", | |
| "start_time": "2018-03-03T22:49:06.443Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "mypoint = testcoord['coordinates']" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.855418Z", | |
| "start_time": "2018-03-03T22:49:06.449Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "GeoDataFrame() " | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.857129Z", | |
| "start_time": "2018-03-03T22:49:06.454Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "from shapely.geometry import Point" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.859171Z", | |
| "start_time": "2018-03-03T22:49:06.463Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "geotypes = [x['type'] for x in bikes_df.the_geom]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.860883Z", | |
| "start_time": "2018-03-03T22:49:06.469Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "set(geotypes)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.862732Z", | |
| "start_time": "2018-03-03T22:49:06.476Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "Point()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.864585Z", | |
| "start_time": "2018-03-03T22:49:06.481Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "newgeom = [Point(x['coordinates']) for x in bikes_df.the_geom]\n", | |
| "bikes_df['newgeom'] = newgeom" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.866612Z", | |
| "start_time": "2018-03-03T22:49:06.487Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "gdf = bikes_df\n", | |
| "gdf = gdf.set_geometry('newgeom')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.868884Z", | |
| "start_time": "2018-03-03T22:49:06.492Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "gdf.head()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.871074Z", | |
| "start_time": "2018-03-03T22:49:06.498Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "gdf.plot()" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.873071Z", | |
| "start_time": "2018-03-03T22:49:06.505Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "gdf.set_geometry('newgeom')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.875617Z", | |
| "start_time": "2018-03-03T22:49:06.514Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "bikes_df" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.877718Z", | |
| "start_time": "2018-03-03T22:49:06.526Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "bikes_df" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.879847Z", | |
| "start_time": "2018-03-03T22:49:06.532Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "import geopandas as gpd" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.881866Z", | |
| "start_time": "2018-03-03T22:49:06.539Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "gdf = gpd.GeoDataFrame(bikes)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": { | |
| "ExecuteTime": { | |
| "end_time": "2018-03-03T22:49:08.884023Z", | |
| "start_time": "2018-03-03T22:49:06.546Z" | |
| } | |
| }, | |
| "outputs": [], | |
| "source": [ | |
| "gdf.set_geometry('the_geom')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| } | |
| ], | |
| "metadata": { | |
| "hide_input": false, | |
| "kernelspec": { | |
| "display_name": "PythonPath (python)", | |
| "language": "python", | |
| "name": "python_ruxi" | |
| }, | |
| "language_info": { | |
| "codemirror_mode": { | |
| "name": "ipython", | |
| "version": 3 | |
| }, | |
| "file_extension": ".py", | |
| "mimetype": "text/x-python", | |
| "name": "python", | |
| "nbconvert_exporter": "python", | |
| "pygments_lexer": "ipython3", | |
| "version": "3.6.4" | |
| }, | |
| "latex_envs": { | |
| "LaTeX_envs_menu_present": true, | |
| "bibliofile": "biblio.bib", | |
| "cite_by": "apalike", | |
| "current_citInitial": 1, | |
| "eqLabelWithNumbers": true, | |
| "eqNumInitial": 1, | |
| "labels_anchors": false, | |
| "latex_user_defs": false, | |
| "report_style_numbering": false, | |
| "user_envs_cfg": false | |
| }, | |
| "toc": { | |
| "colors": { | |
| "hover_highlight": "#DAA520", | |
| "running_highlight": "#FF0000", | |
| "selected_highlight": "#FFD700" | |
| }, | |
| "moveMenuLeft": true, | |
| "nav_menu": { | |
| "height": "12px", | |
| "width": "252px" | |
| }, | |
| "navigate_menu": true, | |
| "number_sections": true, | |
| "sideBar": true, | |
| "threshold": 4, | |
| "toc_cell": false, | |
| "toc_section_display": "block", | |
| "toc_window_display": false | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 2 | |
| } |
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