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View gist:4289817
library("ggplot2")
crime <- read.csv("/Users/marcin/R/crime/crime.csv", header=TRUE)
mayors <- read.csv("/Users/marcin/R/crime/mayors.csv", header=TRUE)
(crimeplot <- qplot(Year, Murder, data=crime, geom="line",xlab = "", ylab = "No. Murders"))
crimeplot + geom_vline(aes(xintercept = start), data = mayors)
View mayors.csv
row.names name start end party
4 Wagner Jr. 1954 1965 Democratic
5 Lindsay 1966 1973 Liberal
6 Beame 1974 1977 Democratic
7 Koch 1978 1989 Democratic
8 Dinkins 1990 1993 Democratic
9 Giuliani 1994 2001 Republican
10 Bloomberg 2002 2011 Republican
View crime.csv
Year Population Murder Rape Robbery Assault Burglary CarTheft
1965 18073000 836 2320 28182 27464 183443 58452
1966 18258000 882 2439 30098 29142 196127 64368
1967 18336000 996 2665 40202 31261 219157 83775
1968 18113000 1185 2527 59857 34946 250918 104877
1969 18321000 1324 2902 64754 36890 248477 115400
1970 18190740 1444 2875 81149 39145 267474 125674
1971 18391000 1823 3225 97682 42318 273704 127658
1972 18366000 2026 4199 86391 45926 239886 105081
1973 18265000 2040 4852 80795 47781 246246 112328
View negative-words.txt
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;
; Opinion Lexicon: Negative
;
; This file contains a list of NEGATIVE opinion words (or sentiment words).
;
; This file and the papers can all be downloaded from
; http://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html
;
; If you use this list, please cite one of the following two papers:
View positive-words.txt
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;
; Opinion Lexicon: Positive
;
; This file contains a list of POSITIVE opinion words (or sentiment words).
;
; This file and the papers can all be downloaded from
; http://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html
;
; If you use this list, please cite one of the following two papers:
View sentiment_analysis_hotel.r
# load twitter library
library(twitteR)
# search for all the hilton tweets
hilton.tweets=searchTwitter('@hilton',n=1500)
length(hilton.tweets)
class(hilton.tweets)
tweet=hilton.tweets[[1]]
class(tweet)
View f1_2011_heatmap.r
#ggplot is an implementation of the grammar of graphics in R
library("ggplot2")
#Load the data into F1_POS dataframe
F1_POS <- read.csv("E:/R/f1/F1_POS.csv")
#The drivers are ordered by points, and the Salary variable converted to a factor for sorting.
F1_POS$Driver <- with(F1_POS, reorder(Driver, Salary))
library("reshape2")
View f1_2011_data.csv
Driver Salary Australia Malaysia China Turkey Spain Monaco Canada Europe Great Britain Germany Hungary Belgium Italy Singapore Japan Korea India Abu Dhabi Brazil
Fernando Alonso 30000000.00 4 6 7 3 5 2 25 2 1 2 3 4 3 4 2 5 3 2 4
Lewis Hamilton 16000000.00 2 8 1 4 2 6 25 4 4 1 4 25 4 5 5 2 7 1 25
Felipe Massa 10000000.00 7 5 6 11 25 25 6 5 5 5 6 8 6 9 7 6 25 5 5
Jenson Button 10000000.00 6 2 4 6 3 3 1 6 25 25 1 3 2 2 1 4 2 3 3
Michael Schumacher 8000000.00 25 9 8 12 6 25 4 17 9 8 25 5 5 25 6 25 5 7 15
Nico Rosberg 8000000.00 25 12 5 5 7 11 11 7 6 7 9 6 25 7 10 8 6 6 7
Sebastian Vettel 8000000.00 1 1 2 1 1 1 2 1 2 4 2 1 1 1 3 1 1 25 2
Mark Webber 8000000.00 5 4 3 2 4 4 3 3 3 3 5 2 25 3 4 3 4 4 1
Jarno Trulli 3000000.00 13 25 19 18 18 13 16 20 25 25 25 14 14 25 19 17 19 18 18
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