Martin Monkman MonkmanMH

Using Google Maps API and R

This script uses RCurl and RJSONIO to download data from Google's API to get the latitude, longitude, location type, and formatted address

library(RCurl)

	# THE HISTORICAL RECORD - RUNS PER GAME BY TEAM
	#
	# public Gist of this code can be found at
	# https://gist.github.com/MonkmanMH/4720641
	#
	# data source: Lahman Database
	# http://www.seanlahman.com/baseball-archive/statistics/
	# 2012 version (1871-2012)
	# data table "Teams.csv"
	#

	# INDIVIDUAL TEAM HISTORY
	#
	# discussion and output can be found at
	# http://bayesball.blogspot.ca/XXXXXXXXXXXXXXXXXXXXX
	#
	# Select the team you want from the franchID variable in the Teams.merge data frame
	# and create a new data frame called "Team1"
	# For this exercise we will use the Seattle Mariners, which are coded as SEA
	# Note the use of double "=" to define the team!
	Team1 <- as.data.frame(subset (Teams.merge, franchID == "SEA"))

	# MAJOR LEAGUE BASEBALL - RUNS PER GAME TREND
	#
	# discussion at
	# 1. http://bayesball.blogspot.ca/2012/07/trends-in-al-run-scoring-using-r.html
	# 2. http://bayesball.blogspot.ca/2012/07/trends-in-run-scoring-nl-edition-more-r.html
	# 3. http://bayesball.blogspot.ca/2012/08/trends-in-run-scoring-comparing-leagues.html
	#
	# data source: Baseball Reference
	# http://www.baseball-reference.com
	# http://www.baseball-reference.com/leagues/AL/bat.shtml

	# THE HISTORICAL RECORD - RUNS PER GAME
	#
	# discussion and output can be found at
	# http://bayesball.blogspot.ca/2013/02/comparing-individual-team-run-production.html
	#
	# data source: Lahman Database
	# http://www.seanlahman.com/baseball-archive/statistics/
	# 2012 version (1871-2012)
	# table: "Teams"
	#

	# INDIVIDUAL TEAM HISTORY - RUNS ALLOWED
	#
	# select the team you want from the franchID variable in the Teams.merge data frame
	# and create a new data frame called "Team1"
	# note the use of double "=" to define the team!
	Team1 <- as.data.frame(subset (Teams.merge, franchID == "SEA"))
	#
	# create what will be the chart title from the contents of Team1
	# note that teams sprang into existence in different years, thus the requirement to define both the start and end dates
	firstyear <- Team1$yearID[1]

	# load the package and data set "Teams"
	install.packages("Lahman")
	library("Lahman")
	data(Teams)
	#
	#
	# CREATE LEAGUE SUMMARY TABLES
	# ============================
	#
	# select a sub-set of teams from 1901 [the establishment of the American League] forward to 2012

	#
	# for details see
	# http://bayesball.blogspot.ca/2013/06/annotating-select-points-on-x-y-plot.html
	#
	# load the ggplot2 and grid packages
	library(ggplot2)
	library(grid)
	# read data (note csv files are renamed)
	tbl1 = read.csv("FanGraphs_Leaderboard_h.csv")
	tbl2 = read.csv("FanGraphs_Leaderboard_d.csv")

	# ######################
	#
	# Blog with output and discussion:
	# "Fair weather fans? (An R scatter plot matrix)" 2013-07-18
	# http://bayesball.blogspot.ca/2013/07/fair-weather-fans-r-scatter-plot-matrix.html
	#
	# data: pulled from www.harbourcats.com
	# saved on Google Drive:
	# https://docs.google.com/spreadsheet/ccc?key=0Art4wpcrwqkBdHZvTUFzOUo5U3BzMHFveXdYOTdTWUE&usp=sharing
	# File / Download as > Comma Separated Values (CSV)

	num,date,day,day2,day.night,vs,attend,cloud,sun,temp.c,temp.f,wind,note
	1,6/5/2013,Wed,1,1,Kelowna,3026,mainly sunny,4,21,70,,Opening Night
	2,6/6/2013,Thu,1,1,Kelowna,1082,mainly sunny,4,18,64,,
	3,6/7/2013,Fri,3,1,Kelowna,1542,mainly sunny,4,19,66,windy,
	4,6/11/2013,Tue,1,1,Medford,1014,mostly cloudy,2,17,63,,
	5,6/12/2013,Wed,1,1,Medford,1003,mostly cloudy,2,16,60,,
	6,6/13/2013,Thu,1,1,Medford,1015,partly cloudy,3,19,66,,
	7,6/21/2013,Fri,3,1,Bend,1248,sunny,5,18,64,,
	8,6/22/2013,Sat,3,1,Bend,1640,sunny,5,21,70,,
	9,6/23/2013,Sun,2,0,Bend,1246,cloudy,1,18,64,,