From 5a2b8743183324c7cba790ab641b7818919e2087 Mon Sep 17 00:00:00 2001 From: lrrbrody Date: Tue, 10 Oct 2017 10:18:24 -0400 Subject: [PATCH 1/4] searched for husband's tweets. --- .gitignore | 5 +++++ twitter-code.Rproj | 13 +++++++++++++ 2 files changed, 18 insertions(+) create mode 100644 .gitignore create mode 100644 twitter-code.Rproj diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..d5a36a0 --- /dev/null +++ b/.gitignore @@ -0,0 +1,5 @@ +.Rproj.user +.Rhistory +.RData +.Ruserdata +.httr-oauth diff --git a/twitter-code.Rproj b/twitter-code.Rproj new file mode 100644 index 0000000..8e3c2eb --- /dev/null +++ b/twitter-code.Rproj @@ -0,0 +1,13 @@ +Version: 1.0 + +RestoreWorkspace: Default +SaveWorkspace: Default +AlwaysSaveHistory: Default + +EnableCodeIndexing: Yes +UseSpacesForTab: Yes +NumSpacesForTab: 2 +Encoding: UTF-8 + +RnwWeave: Sweave +LaTeX: pdfLaTeX From 50d78ea7129bb683e18abb7b0dc4eaf4320754b1 Mon Sep 17 00:00:00 2001 From: lrrbrody Date: Tue, 21 Nov 2017 15:37:26 -0500 Subject: [PATCH 2/4] I think it should work? --- .DS_Store | Bin 0 -> 6148 bytes Twitter search code.Rmd | 83 ++++++++++++++++++++++++++++++++++++---- Twitter.Rproj | 13 +++++++ 3 files changed, 88 insertions(+), 8 deletions(-) create mode 100644 .DS_Store create mode 100644 Twitter.Rproj diff --git a/.DS_Store b/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..fbf2bace049f7ed825279e5ad5f952313ab2eff3 GIT binary patch literal 6148 zcmeHK%}T>S5dJm>sr1sL$9)2^R}T_OJbAM(P-vuD3< zW?=T)%+Bo3m#~uo;8tC=1Qq~hRKe_u%?~2uq9e)FB7;umc-t-4+ooV zkgk4NOnWAK`H(56=1g|>t7o!LY{I107z4(DF>s~~FlUR*n51uMm zDE1M<)xjo|0K}Z;AnZ#mAu(RDQ0yaegyLc-F@`!VF;E*!o{Rxw;H(&MdATlEJd)La~oX3&nl}0u9y}1AofEH>=A Date: Sun, 28 Jul 2019 20:18:55 -0400 Subject: [PATCH 3/4] Created using Colaboratory --- TDI_Project_Proposal.ipynb | 1842 ++++++++++++++++++++++++++++++++++++ 1 file changed, 1842 insertions(+) create mode 100644 TDI_Project_Proposal.ipynb diff --git a/TDI_Project_Proposal.ipynb b/TDI_Project_Proposal.ipynb new file mode 100644 index 0000000..bce033c --- /dev/null +++ b/TDI_Project_Proposal.ipynb @@ -0,0 +1,1842 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "TDI Project Proposal.ipynb", + "version": "0.3.2", + "provenance": [], + "collapsed_sections": [], + "include_colab_link": true + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9r9Mll23E0C1", + "colab_type": "text" + }, + "source": [ + "https://www.milliontreesnyc.org/html/newsroom/pr_milliontreesnyc_launch.shtml\n", + "https://www.milliontreesnyc.org/html/about/letter.shtml\n", + "https://www1.nyc.gov/office-of-the-mayor/news/862-15/mayor-de-blasio-celebrates-one-millionth-tree-former-mayor-michael-bloomberg-bette-midler-#/0\n", + "https://en.wikipedia.org/wiki/PlaNYC\n", + "https://www.nycgovparks.org/trees/treescount\n", + "\n", + "https://www.census.gov/quickfacts/fact/table/newyorkcountymanhattanboroughnewyork,bronxcountybronxboroughnewyork,queenscountyqueensboroughnewyork,kingscountybrooklynboroughnewyork,richmondcountystatenislandboroughnewyork,newyorkcitynewyork/PST045218#\n", + "\n", + "https://www.baruch.cuny.edu/nycdata/income-taxes/hhold_income-numbers.htm\n", + "\n", + "https://data.cityofnewyork.us/Environment/1995-Street-Tree-Census/kyad-zm4j\n", + "https://data.cityofnewyork.us/Environment/2005-Street-Tree-Census/29bw-z7pj\n", + "https://data.cityofnewyork.us/Environment/2015-Street-Tree-Census-Tree-Data/uvpi-gqnh\n", + "\n", + "\n", + "https://data.cityofnewyork.us/Public-Safety/NYPD-Complaint-Data-Historic/qgea-i56i\n", + "https://data.cityofnewyork.us/Public-Safety/NYPD-Arrests-Data-Historic-/8h9b-rp9u\n", + "https://data.cityofnewyork.us/Public-Safety/NYPD-Shooting-Incident-Data-Historic-/833y-fsy8\n", + "https://data.cityofnewyork.us/Education/2005-2015-Graduation-Outcomes/qk7d-gecv\n", + "https://data.cityofnewyork.us/Education/2016-2017-Graduation-Outcomes-School/nb39-jx2v\n", + "https://data.cityofnewyork.us/Health/DOHMH-Community-Health-Survey-2010-2016-/csut-3wpr\n", + "\n", + "https://www1.nyc.gov/assets/planning/download/pdf/planning-level/nyc-population/census2000/sociopp.pdf" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "G0vrt97SvHrJ", + "colab_type": "code", + "outputId": "281680f8-dddc-4ec1-b699-fb0a65d65dc4", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 122 + }, + "cellView": "both" + }, + "source": [ + "#Connect to drive to access saved datasets\n", + "from google.colab import drive\n", + "drive.mount('/content/drive')" + ], + "execution_count": 1, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3Aietf%3Awg%3Aoauth%3A2.0%3Aoob&scope=email%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdocs.test%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive.photos.readonly%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fpeopleapi.readonly&response_type=code\n", + "\n", + "Enter your authorization code:\n", + "··········\n", + "Mounted at /content/drive\n" + ], + "name": "stdout" + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "3o96BldywRH7", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#Get setup and load the three tree datasets from 1995, 2005, 2015\n", + "import pandas as pd\n", + "\n", + "#Load 1995 NYC Tree Census https://data.cityofnewyork.us/Environment/1995-Street-Tree-Census/kyad-zm4j\n", + "Tree95=pd.read_csv(\"/content/drive/My Drive/1995_Street_Tree_Census.csv\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "ZkYgtgt4wcS1", + "colab_type": "code", + "outputId": "8b8d2cd7-fb52-4c8b-c1ae-50d98d8fa692", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 264 + } + }, + "source": [ + "Tree95.head(3)" + ], + "execution_count": 3, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
RecordIdAddressHouse_NumberStreetPostcode_OriginalCommunity Board_OriginalSiteSpeciesDiameterConditionWiresSidewalk_ConditionSupport_StructureBoroughXYLongitudeLatitudeCB_NewZip_NewCensusTract_2010CensusBlock_2010NTA_2010SegmentIDSpc_CommonSpc_LatinLocationCouncil DistrictBINBBL
01245 E 17 ST245.0E 17 ST10003106FrontPLAC8UnknownNoneNaNNoneManhattan988618.9688206893.7640-73.98423540.7345511061000348.02000.0MN2133134LONDON PLANETREEPLATANUS ACERIFOLIA(40.734551, -73.984235)2.01019566.01.008980e+09
1280 N MOORE ST80.0N MOORE ST10013101SideACPL7GoodNoneGoodNoneManhattan981330.4271201649.9518-74.01053240.7201591011001339.02001.0MN2431567MAPLE, NORWAYACER PLATANOIDES(40.720159, -74.010532)1.01083157.01.001420e+09
2380 N MOORE ST80.0N MOORE ST10013101SideACPL6GoodNoneGoodNoneManhattan981330.4271201649.9518-74.01053240.7201591011001339.02001.0MN2431567MAPLE, NORWAYACER PLATANOIDES(40.720159, -74.010532)1.01083157.01.001420e+09
\n", + "
" + ], + "text/plain": [ + " RecordId Address ... BIN BBL\n", + "0 1 245 E 17 ST ... 1019566.0 1.008980e+09\n", + "1 2 80 N MOORE ST ... 1083157.0 1.001420e+09\n", + "2 3 80 N MOORE ST ... 1083157.0 1.001420e+09\n", + "\n", + "[3 rows x 30 columns]" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 3 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "btgsCL2LxOIq", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#Load 2005 NYC Tree Census https://data.cityofnewyork.us/Environment/2005-Street-Tree-Census/29bw-z7pj\n", + "Tree05=pd.read_csv(\"/content/drive/My Drive/2005_Street_Tree_Census.csv\", low_memory=False)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "j6WNjVb9y11c", + "colab_type": "code", + "outputId": "899af3bb-a809-4ab4-ee01-01c90e7dcd88", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 332 + } + }, + "source": [ + "Tree05.head(3)" + ], + "execution_count": 5, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
OBJECTIDcen_yeartree_dbhaddresstree_locpit_typesoil_lvlstatusspc_latinspc_commonvert_othervert_pgrdvert_tgrdvert_wallhorz_blckhorz_gratehorz_planthorz_othersidw_cracksidw_raisewire_htapwire_primewire_2ndwire_otherinf_canopyinf_guardinf_wiresinf_pavinginf_outletinf_shoesinf_lightsinf_othertrunk_dmgzipcodezip_citycb_numborocodeboronamecncldistst_assemst_senatentanta_nameboro_ctstatelatitudelongitudex_spy_spobjectid_1census tractbinbblLocation 1
0592373200561139 57 STREETFrontSidewalk PitLevelGoodPYRUS CALLERYANAPEAR, CALLERYNoNoNoNoNoNoYesNoNoNoNoYesNoNoNoNoNoNoNoNoNoNoNone11219Brooklyn3123Brooklyn444817BK88Borough Park3021600.0New York40.632653-74.0002459841821697690216.03140038.03.056890e+09(40.63265321, -74.00024499)
1592374200562220 BERGEN AVENUEAcrossSidewalk PitLevelGoodPLATANUS ACERIFOLIALONDON PLANETREENoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoYesNone11234Brooklyn3183Brooklyn465919BK45Georgetown-Marine Park-Bergen Beach-Mill Basin3070600.0New York40.620084-73.90145310116081652051706.03238037.03.084440e+09(40.62008375, -73.9014528)
25923752005132360 BERGEN AVENUEFrontContinuous PitLevelGoodACER PLATANOIDES CRIMSON KINGMAPLE, NORWAY-CR KNGNoNoNoNoNoNoYesYesNoNoYesYesYesNoNoNoNoYesNoNoNoYesCavity11234Brooklyn3183Brooklyn465919BK45Georgetown-Marine Park-Bergen Beach-Mill Basin3070600.0New York40.617996-73.89911110122591644452706.03238299.03.084530e+09(40.61799567, -73.89911096)
\n", + "
" + ], + "text/plain": [ + " OBJECTID cen_year ... bbl Location 1\n", + "0 592373 2005 ... 3.056890e+09 (40.63265321, -74.00024499)\n", + "1 592374 2005 ... 3.084440e+09 (40.62008375, -73.9014528)\n", + "2 592375 2005 ... 3.084530e+09 (40.61799567, -73.89911096)\n", + "\n", + "[3 rows x 54 columns]" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 5 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "9qH_DlU_xYNt", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#Load 2015 NYC Tree Census https://data.cityofnewyork.us/Environment/2015-Street-Tree-Census-Tree-Data/uvpi-gqnh\n", + "Tree15=pd.read_csv(\"/content/drive/My Drive/2015_Street_Tree_Census_-_Tree_Data.csv\")" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "AzeQk_q00Iiq", + "colab_type": "code", + "outputId": "fb1264b2-2e61-4cf7-9789-bd3a41346eb5", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 281 + } + }, + "source": [ + "Tree15.head(3)" + ], + "execution_count": 7, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
tree_idblock_idcreated_attree_dbhstump_diamcurb_locstatushealthspc_latinspc_commonstewardguardssidewalkuser_typeproblemsroot_stoneroot_grateroot_othertrunk_wiretrnk_lighttrnk_otherbrch_lightbrch_shoebrch_otheraddresspostcodezip_citycommunity boardborocodeboroughcncldistst_assemst_senatentanta_nameboro_ctstatelatitudelongitudex_spy_spcouncil districtcensus tractbinbbl
018068334871108/27/201530OnCurbAliveFairAcer rubrumred mapleNoneNoneNoDamageTreesCount StaffNoneNoNoNoNoNoNoNoNoNo108-005 70 AVENUE11375Forest Hills4064Queens292816QN17Forest Hills4073900New York40.723092-73.8442151027431.148202756.768729.0739.04052307.04.022210e+09
120054031598609/03/2015210OnCurbAliveFairQuercus palustrispin oakNoneNoneDamageTreesCount StaffStonesYesNoNoNoNoNoNoNoNo147-074 7 AVENUE11357Whitestone4074Queens192711QN49Whitestone4097300New York40.794111-73.8186791034455.701228644.837419.0973.04101931.04.044750e+09
220402621836509/05/201530OnCurbAliveGoodGleditsia triacanthos var. inermishoneylocust1or2NoneDamageVolunteerNoneNoNoNoNoNoNoNoNoNo390 MORGAN AVENUE11211Brooklyn3013Brooklyn345018BK90East Williamsburg3044900New York40.717581-73.9366081001822.831200716.891334.0449.03338310.03.028870e+09
\n", + "
" + ], + "text/plain": [ + " tree_id block_id created_at ... census tract bin bbl\n", + "0 180683 348711 08/27/2015 ... 739.0 4052307.0 4.022210e+09\n", + "1 200540 315986 09/03/2015 ... 973.0 4101931.0 4.044750e+09\n", + "2 204026 218365 09/05/2015 ... 449.0 3338310.0 3.028870e+09\n", + "\n", + "[3 rows x 45 columns]" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 7 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "cDq6z_Qi0TkI", + "colab_type": "code", + "colab": {} + }, + "source": [ + "#Would love better visuals, but better to get basic ones done now and hit requirements. Can make better later. \n", + "#import seaborn as sns\n", + "#sns.set(style=\"darkgrid\")\n", + "#T95 = sns.load_dataset(\"Tree95\")\n", + "#ax = sns.countplot(x=\"Borough\", data=Tree95)\n", + "#ax = sns.countplot(x=\"boroname\", data=Tree05)" + ], + "execution_count": 0, + "outputs": [] + }, + { + "cell_type": "code", + "metadata": { + "id": "JG0zr25C4E6B", + "colab_type": "code", + "outputId": "64d13f71-f997-4f13-a797-d3ada0e5224d", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 235 + } + }, + "source": [ + "#Combine counts for each year grouped by borough to compare results\n", + "Count95=Tree95.groupby(Tree95['Borough']).count()\n", + "Count95 = Count95.iloc[:,0:1]\n", + "Count95.columns = ['1995']\n", + "Count95" + ], + "execution_count": 9, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
1995
Borough
Bronx48487
Brooklyn117101
Manhattan47215
Queens227552
Staten Island76634
\n", + "
" + ], + "text/plain": [ + " 1995\n", + "Borough \n", + "Bronx 48487\n", + "Brooklyn 117101\n", + "Manhattan 47215\n", + "Queens 227552\n", + "Staten Island 76634" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 9 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Ck1D10qU4oCo", + "colab_type": "code", + "outputId": "353538d9-e2f0-4c4f-8c3c-1f6745a86281", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 235 + } + }, + "source": [ + "Count05=Tree05.groupby(Tree05['boroname']).count()\n", + "Count05 = Count05.iloc[:,0:1]\n", + "Count05.columns = ['2005']\n", + "Borough = [\"Staten Island\", \"Bronx\", \"Brooklyn\", \"Manhattan\", \"Queens\"]\n", + "Count05['Borough'] = Borough\n", + "Count05.set_index('Borough', inplace=True)\n", + "Count05" + ], + "execution_count": 10, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
2005
Borough
Staten Island99701
Bronx59925
Brooklyn142852
Manhattan49886
Queens240008
\n", + "
" + ], + "text/plain": [ + " 2005\n", + "Borough \n", + "Staten Island 99701\n", + "Bronx 59925\n", + "Brooklyn 142852\n", + "Manhattan 49886\n", + "Queens 240008" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 10 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "eynOVJ8D-XSh", + "colab_type": "code", + "outputId": "be3c83f8-76f1-41da-d001-d9dc7380180e", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 235 + } + }, + "source": [ + "Count15=Tree15.groupby(Tree15['borough']).count()\n", + "Count15 = Count15.iloc[:,0:1]\n", + "Count15.columns = ['2015']\n", + "Count15" + ], + "execution_count": 11, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
2015
borough
Bronx85203
Brooklyn177293
Manhattan65423
Queens250551
Staten Island105318
\n", + "
" + ], + "text/plain": [ + " 2015\n", + "borough \n", + "Bronx 85203\n", + "Brooklyn 177293\n", + "Manhattan 65423\n", + "Queens 250551\n", + "Staten Island 105318" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 11 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "UmjilNHF-qLB", + "colab_type": "code", + "outputId": "01d243f4-c85d-40ee-9e91-3e31bbe355de", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 235 + } + }, + "source": [ + "#Join the borough counts for the 3 years to make a simple plot\n", + "Counts=Count95.join(Count05)\n", + "Counts=Counts.join(Count15)\n", + "Borough = [\"Bronx\", \"Brooklyn\", \"Manhattan\", \"Queens\", \"Staten Island\"]\n", + "Counts['Borough'] = Borough\n", + "Counts" + ], + "execution_count": 12, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
199520052015Borough
Borough
Bronx484875992585203Bronx
Brooklyn117101142852177293Brooklyn
Manhattan472154988665423Manhattan
Queens227552240008250551Queens
Staten Island7663499701105318Staten Island
\n", + "
" + ], + "text/plain": [ + " 1995 2005 2015 Borough\n", + "Borough \n", + "Bronx 48487 59925 85203 Bronx\n", + "Brooklyn 117101 142852 177293 Brooklyn\n", + "Manhattan 47215 49886 65423 Manhattan\n", + "Queens 227552 240008 250551 Queens\n", + "Staten Island 76634 99701 105318 Staten Island" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 12 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "H-rkuyPrC6Cx", + "colab_type": "code", + "outputId": "f83aef7e-555b-4ec8-f15f-8afa8bbd32cd", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 355 + } + }, + "source": [ + "#Basic plot (for now) to confirm intuition and press releases that there are more trees in NYC now than before (or at least more recorded trees)\n", + "TreePlot=Counts.plot(x=\"Borough\", y=[\"1995\", \"2005\", \"2015\"], kind=\"bar\")\n", + "TreePlot\n", + "#Looks like the PR didn't lie, certainly seem to be adding trees over the years" + ], + "execution_count": 13, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 13 + }, + { + "output_type": "display_data", + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY0AAAFBCAYAAACLjfMeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nBR+sUATl+pNOAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "Unyq12P-_yk0", + "colab_type": "code", + "outputId": "b0f87364-2e56-4d71-d072-7282b037a0a3", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 173 + } + }, + "source": [ + "#Filter the three dataset to confirm that trees volunteers are counting (and in the plot above) are actual live trees and not stumps/dead\n", + "Status15=Tree15.groupby(\"status\").count()\n", + "Status15 = Status15.iloc[:,0:1]\n", + "Status15.columns = ['2015']\n", + "Status15\n", + "#Health/Status columns end up being more consistent than alive/dead, so using those for now. " + ], + "execution_count": 14, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
2015
status
Alive652173
Dead13961
Stump17654
\n", + "
" + ], + "text/plain": [ + " 2015\n", + "status \n", + "Alive 652173\n", + "Dead 13961\n", + "Stump 17654" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 14 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "VL0WJEBuBtdj", + "colab_type": "code", + "outputId": "a9fc6a65-cdb7-4ed0-ee47-023312518fa1", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + } + }, + "source": [ + "#Filter datasets for tree health \n", + "Alive15=Tree15[(Tree15['status']) == \"Alive\"]\n", + "Health15=Alive15.groupby('health').count()\n", + "Health15 = Health15.iloc[:,0:1]\n", + "Health15.columns = ['2015']\n", + "Health15.loc[-1] = [13961] #Taken from counts above manually because it was a separate column for this dataset\n", + "Status = [\"Good\", \"Excellent\", \"Poor\", \"Dead\"]\n", + "Health15['Status'] = Status\n", + "Health15.set_index('Status', inplace=True)\n", + "Health15" + ], + "execution_count": 41, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
2015
Status
Good96504
Excellent528850
Poor26818
Dead13961
\n", + "
" + ], + "text/plain": [ + " 2015\n", + "Status \n", + "Good 96504\n", + "Excellent 528850\n", + "Poor 26818\n", + "Dead 13961" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 41 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "x6jJq8JUBMI7", + "colab_type": "code", + "outputId": "3bfbb84f-b235-422e-afa7-5e35ad815c76", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + } + }, + "source": [ + "Alive05=Tree05.groupby(\"status\").count()\n", + "Alive05 = Alive05.iloc[:,0:1]\n", + "Alive05.columns = ['2005']\n", + "Status = [\"Dead\", \"Excellent\", \"Good\", \"Poor\"]\n", + "Alive05['Status'] = Status\n", + "Alive05.set_index('Status', inplace=True)\n", + "Alive05" + ], + "execution_count": 32, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
2005
Status
Dead8120
Excellent141657
Good393464
Poor49131
\n", + "
" + ], + "text/plain": [ + " 2005\n", + "Status \n", + "Dead 8120\n", + "Excellent 141657\n", + "Good 393464\n", + "Poor 49131" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 32 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "sBYdDhhbFnc4", + "colab_type": "code", + "outputId": "fa195f81-4db2-4fd0-ac1a-2f468b5bfcac", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + } + }, + "source": [ + "Cond95=Tree95.groupby(\"Condition\").count()\n", + "Cond95 = Cond95.iloc[0:7,0:1]\n", + "Status95 = [\"Critical\", \"Dead\", \"Excellent\", \"Fair\", \"Good\", \"Planting_Space\", \"Poor\"]\n", + "Cond95['Status'] = Status95\n", + "Cond95=Cond95[Cond95[\"Status\"] != \"Critical\"] #only 2, dropping for now\n", + "Cond95=Cond95[Cond95[\"Status\"] != \"Planting_Space\"] #not useful for now and doesn't match the other datasets, dropping for now\n", + "Cond95=Cond95[Cond95[\"Status\"] != \"Fair\"] #added to 'Good'\n", + "Cond95.set_index('Status', inplace=True)\n", + "Cond95.columns = ['1995']\n", + "Cond95.at['Good', '1995'] = (332562 + 327) #sum of \"fair\" and \"good\" since the other datasets don't have this particular distinction\n", + "Cond95" + ], + "execution_count": 30, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
1995
Status
Dead12859
Excellent100286
Good332889
Poor38571
\n", + "
" + ], + "text/plain": [ + " 1995\n", + "Status \n", + "Dead 12859\n", + "Excellent 100286\n", + "Good 332889\n", + "Poor 38571" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 30 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "A_RaSdLT-Z7F", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + }, + "outputId": "0be8e5c6-b029-462f-e4a3-5ee7e4621f0d" + }, + "source": [ + "#Joining the tree statuses from the 3 years to build a simple plot\n", + "ActualTrees=Cond95.join(Alive05)\n", + "ActualTrees=ActualTrees.join(Health15)\n", + "Status = [\"Dead\", \"Excellent\", \"Good\", \"Poor\"]\n", + "ActualTrees['Status'] = Status\n", + "ActualTrees" + ], + "execution_count": 38, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
199520052015Status
Status
Dead12859812013961Dead
Excellent100286141657528850Excellent
Good33288939346496504Good
Poor385714913126818Poor
\n", + "
" + ], + "text/plain": [ + " 1995 2005 2015 Status\n", + "Status \n", + "Dead 12859 8120 13961 Dead\n", + "Excellent 100286 141657 528850 Excellent\n", + "Good 332889 393464 96504 Good\n", + "Poor 38571 49131 26818 Poor" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 38 + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "mpkvf7xR_Ryd", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 336 + }, + "outputId": "58939f61-9c5e-4cc8-e901-8f0eef320afa" + }, + "source": [ + "#Visual to confirm the tree count going up doesn't have a ton of dead/stump/empty plots.\n", + "ActualTreesPlot=ActualTrees.plot(x=\"Status\", y=[\"1995\", \"2005\", \"2015\"], kind=\"bar\")\n", + "ActualTreesPlot\n", + "#Looks pretty good, deeper looking should consider combining \"excellent\" and \"good\" to see if it evens things out \n", + "#(maybe more trees had a positive effect and volunteers had a better outlook!)" + ], + "execution_count": 39, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 39 + }, + { + "output_type": "display_data", + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY0AAAEuCAYAAAByL06RAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "tags": [] + } + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "5aoZxCg-Dk0J", + "colab_type": "text" + }, + "source": [ + "Conclusions:\n", + "2015 Street Tree census certainly shows more trees in NYC than in 1995 or 2005, and those trees seem to be doing well. \n", + "\n", + "For next time: \n", + "- better plots\n", + "- more datasets to look for \"better\" life factors:\n", + " - less crime? or less violent crime? specific to parks or less dense tree areas?\n", + " - less asthma related hospitalizations?\n", + " - higher incomes? specific to certain areas/tree densities?\n", + " - higher graduation rates? \n", + " \n", + "Is there a correlation or additional observations that can be made regarding the above or similar?\n", + "\n", + "Do other cities with similar initiatives have similar correlations? \n", + "LA and London both have improvement initiatives and open datasets online. " + ] + } + ] +} \ No newline at end of file From d18ccade394d45bb8a21921153639fd85eb99caf Mon Sep 17 00:00:00 2001 From: Lauren Romine Date: Sun, 28 Jul 2019 20:19:11 -0400 Subject: [PATCH 4/4] Delete TDI_Project_Proposal.ipynb --- TDI_Project_Proposal.ipynb | 1842 ------------------------------------ 1 file changed, 1842 deletions(-) delete mode 100644 TDI_Project_Proposal.ipynb diff --git a/TDI_Project_Proposal.ipynb b/TDI_Project_Proposal.ipynb deleted file mode 100644 index bce033c..0000000 --- a/TDI_Project_Proposal.ipynb +++ /dev/null @@ -1,1842 +0,0 @@ -{ - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "name": "TDI Project Proposal.ipynb", - "version": "0.3.2", - "provenance": [], - "collapsed_sections": [], - "include_colab_link": true - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - } - }, - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "view-in-github", - "colab_type": "text" - }, - "source": [ - "\"Open" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "9r9Mll23E0C1", - "colab_type": "text" - }, - "source": [ - "https://www.milliontreesnyc.org/html/newsroom/pr_milliontreesnyc_launch.shtml\n", - "https://www.milliontreesnyc.org/html/about/letter.shtml\n", - "https://www1.nyc.gov/office-of-the-mayor/news/862-15/mayor-de-blasio-celebrates-one-millionth-tree-former-mayor-michael-bloomberg-bette-midler-#/0\n", - "https://en.wikipedia.org/wiki/PlaNYC\n", - "https://www.nycgovparks.org/trees/treescount\n", - "\n", - "https://www.census.gov/quickfacts/fact/table/newyorkcountymanhattanboroughnewyork,bronxcountybronxboroughnewyork,queenscountyqueensboroughnewyork,kingscountybrooklynboroughnewyork,richmondcountystatenislandboroughnewyork,newyorkcitynewyork/PST045218#\n", - "\n", - "https://www.baruch.cuny.edu/nycdata/income-taxes/hhold_income-numbers.htm\n", - "\n", - "https://data.cityofnewyork.us/Environment/1995-Street-Tree-Census/kyad-zm4j\n", - "https://data.cityofnewyork.us/Environment/2005-Street-Tree-Census/29bw-z7pj\n", - "https://data.cityofnewyork.us/Environment/2015-Street-Tree-Census-Tree-Data/uvpi-gqnh\n", - "\n", - "\n", - "https://data.cityofnewyork.us/Public-Safety/NYPD-Complaint-Data-Historic/qgea-i56i\n", - "https://data.cityofnewyork.us/Public-Safety/NYPD-Arrests-Data-Historic-/8h9b-rp9u\n", - "https://data.cityofnewyork.us/Public-Safety/NYPD-Shooting-Incident-Data-Historic-/833y-fsy8\n", - "https://data.cityofnewyork.us/Education/2005-2015-Graduation-Outcomes/qk7d-gecv\n", - "https://data.cityofnewyork.us/Education/2016-2017-Graduation-Outcomes-School/nb39-jx2v\n", - "https://data.cityofnewyork.us/Health/DOHMH-Community-Health-Survey-2010-2016-/csut-3wpr\n", - "\n", - "https://www1.nyc.gov/assets/planning/download/pdf/planning-level/nyc-population/census2000/sociopp.pdf" - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "G0vrt97SvHrJ", - "colab_type": "code", - "outputId": "281680f8-dddc-4ec1-b699-fb0a65d65dc4", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 122 - }, - "cellView": "both" - }, - "source": [ - "#Connect to drive to access saved datasets\n", - "from google.colab import drive\n", - "drive.mount('/content/drive')" - ], - "execution_count": 1, - "outputs": [ - { - "output_type": "stream", - "text": [ - "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3Aietf%3Awg%3Aoauth%3A2.0%3Aoob&scope=email%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdocs.test%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive.photos.readonly%20https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fpeopleapi.readonly&response_type=code\n", - "\n", - "Enter your authorization code:\n", - "··········\n", - "Mounted at /content/drive\n" - ], - "name": "stdout" - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "3o96BldywRH7", - "colab_type": "code", - "colab": {} - }, - "source": [ - "#Get setup and load the three tree datasets from 1995, 2005, 2015\n", - "import pandas as pd\n", - "\n", - "#Load 1995 NYC Tree Census https://data.cityofnewyork.us/Environment/1995-Street-Tree-Census/kyad-zm4j\n", - "Tree95=pd.read_csv(\"/content/drive/My Drive/1995_Street_Tree_Census.csv\")" - ], - "execution_count": 0, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "ZkYgtgt4wcS1", - "colab_type": "code", - "outputId": "8b8d2cd7-fb52-4c8b-c1ae-50d98d8fa692", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 264 - } - }, - "source": [ - "Tree95.head(3)" - ], - "execution_count": 3, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
RecordIdAddressHouse_NumberStreetPostcode_OriginalCommunity Board_OriginalSiteSpeciesDiameterConditionWiresSidewalk_ConditionSupport_StructureBoroughXYLongitudeLatitudeCB_NewZip_NewCensusTract_2010CensusBlock_2010NTA_2010SegmentIDSpc_CommonSpc_LatinLocationCouncil DistrictBINBBL
01245 E 17 ST245.0E 17 ST10003106FrontPLAC8UnknownNoneNaNNoneManhattan988618.9688206893.7640-73.98423540.7345511061000348.02000.0MN2133134LONDON PLANETREEPLATANUS ACERIFOLIA(40.734551, -73.984235)2.01019566.01.008980e+09
1280 N MOORE ST80.0N MOORE ST10013101SideACPL7GoodNoneGoodNoneManhattan981330.4271201649.9518-74.01053240.7201591011001339.02001.0MN2431567MAPLE, NORWAYACER PLATANOIDES(40.720159, -74.010532)1.01083157.01.001420e+09
2380 N MOORE ST80.0N MOORE ST10013101SideACPL6GoodNoneGoodNoneManhattan981330.4271201649.9518-74.01053240.7201591011001339.02001.0MN2431567MAPLE, NORWAYACER PLATANOIDES(40.720159, -74.010532)1.01083157.01.001420e+09
\n", - "
" - ], - "text/plain": [ - " RecordId Address ... BIN BBL\n", - "0 1 245 E 17 ST ... 1019566.0 1.008980e+09\n", - "1 2 80 N MOORE ST ... 1083157.0 1.001420e+09\n", - "2 3 80 N MOORE ST ... 1083157.0 1.001420e+09\n", - "\n", - "[3 rows x 30 columns]" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 3 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "btgsCL2LxOIq", - "colab_type": "code", - "colab": {} - }, - "source": [ - "#Load 2005 NYC Tree Census https://data.cityofnewyork.us/Environment/2005-Street-Tree-Census/29bw-z7pj\n", - "Tree05=pd.read_csv(\"/content/drive/My Drive/2005_Street_Tree_Census.csv\", low_memory=False)" - ], - "execution_count": 0, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "j6WNjVb9y11c", - "colab_type": "code", - "outputId": "899af3bb-a809-4ab4-ee01-01c90e7dcd88", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 332 - } - }, - "source": [ - "Tree05.head(3)" - ], - "execution_count": 5, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
OBJECTIDcen_yeartree_dbhaddresstree_locpit_typesoil_lvlstatusspc_latinspc_commonvert_othervert_pgrdvert_tgrdvert_wallhorz_blckhorz_gratehorz_planthorz_othersidw_cracksidw_raisewire_htapwire_primewire_2ndwire_otherinf_canopyinf_guardinf_wiresinf_pavinginf_outletinf_shoesinf_lightsinf_othertrunk_dmgzipcodezip_citycb_numborocodeboronamecncldistst_assemst_senatentanta_nameboro_ctstatelatitudelongitudex_spy_spobjectid_1census tractbinbblLocation 1
0592373200561139 57 STREETFrontSidewalk PitLevelGoodPYRUS CALLERYANAPEAR, CALLERYNoNoNoNoNoNoYesNoNoNoNoYesNoNoNoNoNoNoNoNoNoNoNone11219Brooklyn3123Brooklyn444817BK88Borough Park3021600.0New York40.632653-74.0002459841821697690216.03140038.03.056890e+09(40.63265321, -74.00024499)
1592374200562220 BERGEN AVENUEAcrossSidewalk PitLevelGoodPLATANUS ACERIFOLIALONDON PLANETREENoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoYesNone11234Brooklyn3183Brooklyn465919BK45Georgetown-Marine Park-Bergen Beach-Mill Basin3070600.0New York40.620084-73.90145310116081652051706.03238037.03.084440e+09(40.62008375, -73.9014528)
25923752005132360 BERGEN AVENUEFrontContinuous PitLevelGoodACER PLATANOIDES CRIMSON KINGMAPLE, NORWAY-CR KNGNoNoNoNoNoNoYesYesNoNoYesYesYesNoNoNoNoYesNoNoNoYesCavity11234Brooklyn3183Brooklyn465919BK45Georgetown-Marine Park-Bergen Beach-Mill Basin3070600.0New York40.617996-73.89911110122591644452706.03238299.03.084530e+09(40.61799567, -73.89911096)
\n", - "
" - ], - "text/plain": [ - " OBJECTID cen_year ... bbl Location 1\n", - "0 592373 2005 ... 3.056890e+09 (40.63265321, -74.00024499)\n", - "1 592374 2005 ... 3.084440e+09 (40.62008375, -73.9014528)\n", - "2 592375 2005 ... 3.084530e+09 (40.61799567, -73.89911096)\n", - "\n", - "[3 rows x 54 columns]" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 5 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "9qH_DlU_xYNt", - "colab_type": "code", - "colab": {} - }, - "source": [ - "#Load 2015 NYC Tree Census https://data.cityofnewyork.us/Environment/2015-Street-Tree-Census-Tree-Data/uvpi-gqnh\n", - "Tree15=pd.read_csv(\"/content/drive/My Drive/2015_Street_Tree_Census_-_Tree_Data.csv\")" - ], - "execution_count": 0, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "AzeQk_q00Iiq", - "colab_type": "code", - "outputId": "fb1264b2-2e61-4cf7-9789-bd3a41346eb5", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 281 - } - }, - "source": [ - "Tree15.head(3)" - ], - "execution_count": 7, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
tree_idblock_idcreated_attree_dbhstump_diamcurb_locstatushealthspc_latinspc_commonstewardguardssidewalkuser_typeproblemsroot_stoneroot_grateroot_othertrunk_wiretrnk_lighttrnk_otherbrch_lightbrch_shoebrch_otheraddresspostcodezip_citycommunity boardborocodeboroughcncldistst_assemst_senatentanta_nameboro_ctstatelatitudelongitudex_spy_spcouncil districtcensus tractbinbbl
018068334871108/27/201530OnCurbAliveFairAcer rubrumred mapleNoneNoneNoDamageTreesCount StaffNoneNoNoNoNoNoNoNoNoNo108-005 70 AVENUE11375Forest Hills4064Queens292816QN17Forest Hills4073900New York40.723092-73.8442151027431.148202756.768729.0739.04052307.04.022210e+09
120054031598609/03/2015210OnCurbAliveFairQuercus palustrispin oakNoneNoneDamageTreesCount StaffStonesYesNoNoNoNoNoNoNoNo147-074 7 AVENUE11357Whitestone4074Queens192711QN49Whitestone4097300New York40.794111-73.8186791034455.701228644.837419.0973.04101931.04.044750e+09
220402621836509/05/201530OnCurbAliveGoodGleditsia triacanthos var. inermishoneylocust1or2NoneDamageVolunteerNoneNoNoNoNoNoNoNoNoNo390 MORGAN AVENUE11211Brooklyn3013Brooklyn345018BK90East Williamsburg3044900New York40.717581-73.9366081001822.831200716.891334.0449.03338310.03.028870e+09
\n", - "
" - ], - "text/plain": [ - " tree_id block_id created_at ... census tract bin bbl\n", - "0 180683 348711 08/27/2015 ... 739.0 4052307.0 4.022210e+09\n", - "1 200540 315986 09/03/2015 ... 973.0 4101931.0 4.044750e+09\n", - "2 204026 218365 09/05/2015 ... 449.0 3338310.0 3.028870e+09\n", - "\n", - "[3 rows x 45 columns]" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 7 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "cDq6z_Qi0TkI", - "colab_type": "code", - "colab": {} - }, - "source": [ - "#Would love better visuals, but better to get basic ones done now and hit requirements. Can make better later. \n", - "#import seaborn as sns\n", - "#sns.set(style=\"darkgrid\")\n", - "#T95 = sns.load_dataset(\"Tree95\")\n", - "#ax = sns.countplot(x=\"Borough\", data=Tree95)\n", - "#ax = sns.countplot(x=\"boroname\", data=Tree05)" - ], - "execution_count": 0, - "outputs": [] - }, - { - "cell_type": "code", - "metadata": { - "id": "JG0zr25C4E6B", - "colab_type": "code", - "outputId": "64d13f71-f997-4f13-a797-d3ada0e5224d", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 235 - } - }, - "source": [ - "#Combine counts for each year grouped by borough to compare results\n", - "Count95=Tree95.groupby(Tree95['Borough']).count()\n", - "Count95 = Count95.iloc[:,0:1]\n", - "Count95.columns = ['1995']\n", - "Count95" - ], - "execution_count": 9, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
1995
Borough
Bronx48487
Brooklyn117101
Manhattan47215
Queens227552
Staten Island76634
\n", - "
" - ], - "text/plain": [ - " 1995\n", - "Borough \n", - "Bronx 48487\n", - "Brooklyn 117101\n", - "Manhattan 47215\n", - "Queens 227552\n", - "Staten Island 76634" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 9 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "Ck1D10qU4oCo", - "colab_type": "code", - "outputId": "353538d9-e2f0-4c4f-8c3c-1f6745a86281", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 235 - } - }, - "source": [ - "Count05=Tree05.groupby(Tree05['boroname']).count()\n", - "Count05 = Count05.iloc[:,0:1]\n", - "Count05.columns = ['2005']\n", - "Borough = [\"Staten Island\", \"Bronx\", \"Brooklyn\", \"Manhattan\", \"Queens\"]\n", - "Count05['Borough'] = Borough\n", - "Count05.set_index('Borough', inplace=True)\n", - "Count05" - ], - "execution_count": 10, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
2005
Borough
Staten Island99701
Bronx59925
Brooklyn142852
Manhattan49886
Queens240008
\n", - "
" - ], - "text/plain": [ - " 2005\n", - "Borough \n", - "Staten Island 99701\n", - "Bronx 59925\n", - "Brooklyn 142852\n", - "Manhattan 49886\n", - "Queens 240008" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 10 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "eynOVJ8D-XSh", - "colab_type": "code", - "outputId": "be3c83f8-76f1-41da-d001-d9dc7380180e", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 235 - } - }, - "source": [ - "Count15=Tree15.groupby(Tree15['borough']).count()\n", - "Count15 = Count15.iloc[:,0:1]\n", - "Count15.columns = ['2015']\n", - "Count15" - ], - "execution_count": 11, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
2015
borough
Bronx85203
Brooklyn177293
Manhattan65423
Queens250551
Staten Island105318
\n", - "
" - ], - "text/plain": [ - " 2015\n", - "borough \n", - "Bronx 85203\n", - "Brooklyn 177293\n", - "Manhattan 65423\n", - "Queens 250551\n", - "Staten Island 105318" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 11 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "UmjilNHF-qLB", - "colab_type": "code", - "outputId": "01d243f4-c85d-40ee-9e91-3e31bbe355de", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 235 - } - }, - "source": [ - "#Join the borough counts for the 3 years to make a simple plot\n", - "Counts=Count95.join(Count05)\n", - "Counts=Counts.join(Count15)\n", - "Borough = [\"Bronx\", \"Brooklyn\", \"Manhattan\", \"Queens\", \"Staten Island\"]\n", - "Counts['Borough'] = Borough\n", - "Counts" - ], - "execution_count": 12, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
199520052015Borough
Borough
Bronx484875992585203Bronx
Brooklyn117101142852177293Brooklyn
Manhattan472154988665423Manhattan
Queens227552240008250551Queens
Staten Island7663499701105318Staten Island
\n", - "
" - ], - "text/plain": [ - " 1995 2005 2015 Borough\n", - "Borough \n", - "Bronx 48487 59925 85203 Bronx\n", - "Brooklyn 117101 142852 177293 Brooklyn\n", - "Manhattan 47215 49886 65423 Manhattan\n", - "Queens 227552 240008 250551 Queens\n", - "Staten Island 76634 99701 105318 Staten Island" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 12 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "H-rkuyPrC6Cx", - "colab_type": "code", - "outputId": "f83aef7e-555b-4ec8-f15f-8afa8bbd32cd", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 355 - } - }, - "source": [ - "#Basic plot (for now) to confirm intuition and press releases that there are more trees in NYC now than before (or at least more recorded trees)\n", - "TreePlot=Counts.plot(x=\"Borough\", y=[\"1995\", \"2005\", \"2015\"], kind=\"bar\")\n", - "TreePlot\n", - "#Looks like the PR didn't lie, certainly seem to be adding trees over the years" - ], - "execution_count": 13, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 13 - }, - { - "output_type": "display_data", - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY0AAAFBCAYAAACLjfMeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nBR+sUATl+pNOAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - } - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "Unyq12P-_yk0", - "colab_type": "code", - "outputId": "b0f87364-2e56-4d71-d072-7282b037a0a3", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 173 - } - }, - "source": [ - "#Filter the three dataset to confirm that trees volunteers are counting (and in the plot above) are actual live trees and not stumps/dead\n", - "Status15=Tree15.groupby(\"status\").count()\n", - "Status15 = Status15.iloc[:,0:1]\n", - "Status15.columns = ['2015']\n", - "Status15\n", - "#Health/Status columns end up being more consistent than alive/dead, so using those for now. " - ], - "execution_count": 14, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
2015
status
Alive652173
Dead13961
Stump17654
\n", - "
" - ], - "text/plain": [ - " 2015\n", - "status \n", - "Alive 652173\n", - "Dead 13961\n", - "Stump 17654" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 14 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "VL0WJEBuBtdj", - "colab_type": "code", - "outputId": "a9fc6a65-cdb7-4ed0-ee47-023312518fa1", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 204 - } - }, - "source": [ - "#Filter datasets for tree health \n", - "Alive15=Tree15[(Tree15['status']) == \"Alive\"]\n", - "Health15=Alive15.groupby('health').count()\n", - "Health15 = Health15.iloc[:,0:1]\n", - "Health15.columns = ['2015']\n", - "Health15.loc[-1] = [13961] #Taken from counts above manually because it was a separate column for this dataset\n", - "Status = [\"Good\", \"Excellent\", \"Poor\", \"Dead\"]\n", - "Health15['Status'] = Status\n", - "Health15.set_index('Status', inplace=True)\n", - "Health15" - ], - "execution_count": 41, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
2015
Status
Good96504
Excellent528850
Poor26818
Dead13961
\n", - "
" - ], - "text/plain": [ - " 2015\n", - "Status \n", - "Good 96504\n", - "Excellent 528850\n", - "Poor 26818\n", - "Dead 13961" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 41 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "x6jJq8JUBMI7", - "colab_type": "code", - "outputId": "3bfbb84f-b235-422e-afa7-5e35ad815c76", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 204 - } - }, - "source": [ - "Alive05=Tree05.groupby(\"status\").count()\n", - "Alive05 = Alive05.iloc[:,0:1]\n", - "Alive05.columns = ['2005']\n", - "Status = [\"Dead\", \"Excellent\", \"Good\", \"Poor\"]\n", - "Alive05['Status'] = Status\n", - "Alive05.set_index('Status', inplace=True)\n", - "Alive05" - ], - "execution_count": 32, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
2005
Status
Dead8120
Excellent141657
Good393464
Poor49131
\n", - "
" - ], - "text/plain": [ - " 2005\n", - "Status \n", - "Dead 8120\n", - "Excellent 141657\n", - "Good 393464\n", - "Poor 49131" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 32 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "sBYdDhhbFnc4", - "colab_type": "code", - "outputId": "fa195f81-4db2-4fd0-ac1a-2f468b5bfcac", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 204 - } - }, - "source": [ - "Cond95=Tree95.groupby(\"Condition\").count()\n", - "Cond95 = Cond95.iloc[0:7,0:1]\n", - "Status95 = [\"Critical\", \"Dead\", \"Excellent\", \"Fair\", \"Good\", \"Planting_Space\", \"Poor\"]\n", - "Cond95['Status'] = Status95\n", - "Cond95=Cond95[Cond95[\"Status\"] != \"Critical\"] #only 2, dropping for now\n", - "Cond95=Cond95[Cond95[\"Status\"] != \"Planting_Space\"] #not useful for now and doesn't match the other datasets, dropping for now\n", - "Cond95=Cond95[Cond95[\"Status\"] != \"Fair\"] #added to 'Good'\n", - "Cond95.set_index('Status', inplace=True)\n", - "Cond95.columns = ['1995']\n", - "Cond95.at['Good', '1995'] = (332562 + 327) #sum of \"fair\" and \"good\" since the other datasets don't have this particular distinction\n", - "Cond95" - ], - "execution_count": 30, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
1995
Status
Dead12859
Excellent100286
Good332889
Poor38571
\n", - "
" - ], - "text/plain": [ - " 1995\n", - "Status \n", - "Dead 12859\n", - "Excellent 100286\n", - "Good 332889\n", - "Poor 38571" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 30 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "A_RaSdLT-Z7F", - "colab_type": "code", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 204 - }, - "outputId": "0be8e5c6-b029-462f-e4a3-5ee7e4621f0d" - }, - "source": [ - "#Joining the tree statuses from the 3 years to build a simple plot\n", - "ActualTrees=Cond95.join(Alive05)\n", - "ActualTrees=ActualTrees.join(Health15)\n", - "Status = [\"Dead\", \"Excellent\", \"Good\", \"Poor\"]\n", - "ActualTrees['Status'] = Status\n", - "ActualTrees" - ], - "execution_count": 38, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
199520052015Status
Status
Dead12859812013961Dead
Excellent100286141657528850Excellent
Good33288939346496504Good
Poor385714913126818Poor
\n", - "
" - ], - "text/plain": [ - " 1995 2005 2015 Status\n", - "Status \n", - "Dead 12859 8120 13961 Dead\n", - "Excellent 100286 141657 528850 Excellent\n", - "Good 332889 393464 96504 Good\n", - "Poor 38571 49131 26818 Poor" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 38 - } - ] - }, - { - "cell_type": "code", - "metadata": { - "id": "mpkvf7xR_Ryd", - "colab_type": "code", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 336 - }, - "outputId": "58939f61-9c5e-4cc8-e901-8f0eef320afa" - }, - "source": [ - "#Visual to confirm the tree count going up doesn't have a ton of dead/stump/empty plots.\n", - "ActualTreesPlot=ActualTrees.plot(x=\"Status\", y=[\"1995\", \"2005\", \"2015\"], kind=\"bar\")\n", - "ActualTreesPlot\n", - "#Looks pretty good, deeper looking should consider combining \"excellent\" and \"good\" to see if it evens things out \n", - "#(maybe more trees had a positive effect and volunteers had a better outlook!)" - ], - "execution_count": 39, - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "" - ] - }, - "metadata": { - "tags": [] - }, - "execution_count": 39 - }, - { - "output_type": "display_data", - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY0AAAEuCAYAAAByL06RAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - } - } - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "5aoZxCg-Dk0J", - "colab_type": "text" - }, - "source": [ - "Conclusions:\n", - "2015 Street Tree census certainly shows more trees in NYC than in 1995 or 2005, and those trees seem to be doing well. \n", - "\n", - "For next time: \n", - "- better plots\n", - "- more datasets to look for \"better\" life factors:\n", - " - less crime? or less violent crime? specific to parks or less dense tree areas?\n", - " - less asthma related hospitalizations?\n", - " - higher incomes? specific to certain areas/tree densities?\n", - " - higher graduation rates? \n", - " \n", - "Is there a correlation or additional observations that can be made regarding the above or similar?\n", - "\n", - "Do other cities with similar initiatives have similar correlations? \n", - "LA and London both have improvement initiatives and open datasets online. " - ] - } - ] -} \ No newline at end of file