stedy/gas2014.csv

## gas2014.csv

          
            Date
            Brand
            Mileage
            Cost
            Grade
            Amount
            TotalCost

            
              1/3/2014
              76
              43159
              3.499
              87
              4.985
              17.44

            
              1/13/2014
              Arco
              43415
              3.29
              87
              9.205
              30.28

            
              1/18/2014
              Shell
              43655
              3.499
              87
              9.521
              33.31

            
              1/22/2014
              Costco
              43938
              3.179
              87
              9.28
              29.5

            
              1/28/2014
              76
              44201
              3.499
              87
              9.263
              32.41

            
              2/15/2014
              76
              44434
              3.499
              87
              9.434
              33.01

            
              3/5/2014
              Shell
              44664
              3.699
              87
              9.801
              36.25

            
              3/16/2014
              76
              44917
              3.519
              87
              9.014
              31.72

            
              3/21/2014
              7-11 (Citgo)
              45179
              3.699
              87
              9.014
              33.34

            
              3/26/2014
              Arco
              45471
              3.639
              87
              9.656
              35.14

            
              3/31/2014
              Arco
              45770
              3.679
              87
              9.463
              34.81

            
              4/12/2014
              76
              45995
              3.959
              87
              8.88
              35.16

            
              4/27/2014
              76
              46208
              4.099
              87
              8.671
              35.54

            
              5/17/2014
              76
              46475
              3.999
              87
              9.101
              36.39

            
              5/25/2014
              Safeway
              46735
              3.819
              87
              9.037
              34.51

            
              5/31/2014
              Shell
              47035
              4.05
              87
              9.326
              37.77

            
              6/15/2014
              76
              47270
              4.059
              87
              8.292
              33.66

            
              7/4/2014
              Safeway
              47531
              3.959
              87
              9.12
              36.11

            
              7/6/2014
              Safeway
              47843
              4.119
              87
              8.796
              36.23

            
              7/18/2014
              Shell
              48130
              3.939
              87
              8.967
              35.32

            
              7/19/2014
              Chevron
              48449
              3.999
              87
              9.166
              36.65

            
              7/27/2014
              Shell
              48743
              4.099
              87
              8.572
              35.14

## gas_calc.R
library(plyr)
library(ggplot2)
raw <- read.csv("gas2014.csv")
avediff <- diff(raw$Mileage)
raw$totalmiles <- c(NA, avediff)
raw$Avgcost <- raw$totalmiles / raw$TotalCost
raw$AvgMPG <- raw$totalmiles / raw$Amount

costsummary <- ddply(raw, "Brand", function(x) data.frame(meancost = mean(x$Avgcost, na.rm=T)))
mpgsummary <- ddply(raw, "Brand", function(x) data.frame(meanMPG = mean(x$AvgMPG, na.rm=T)))
final <- merge(costsummary, mpgsummary)

ggplot(final, aes(x= meancost, y= meanMPG, label= Brand)) +
  geom_point(size=4) +·
  geom_text(aes(label= Brand), hjust= -0.2, vjust= -0.2, size=8) +
  scale_x_continuous(limits = c(7,10)) +
  ylab("mean MPG") + xlab("Mean cost") +
  theme(axis.text.x = element_text(face='bold', size=20),
      axis.text.y = element_text(face='bold', size=20),
      axis.title.y = element_text(face="bold", size=20, angle=90),
      axis.title.x = element_text(face="bold", size=20)
  )
Date	Brand	Mileage	Cost	Grade	Amount	TotalCost
1/3/2014	76	43159	3.499	87	4.985	17.44
1/13/2014	Arco	43415	3.29	87	9.205	30.28
1/18/2014	Shell	43655	3.499	87	9.521	33.31
1/22/2014	Costco	43938	3.179	87	9.28	29.5
1/28/2014	76	44201	3.499	87	9.263	32.41
2/15/2014	76	44434	3.499	87	9.434	33.01
3/5/2014	Shell	44664	3.699	87	9.801	36.25
3/16/2014	76	44917	3.519	87	9.014	31.72
3/21/2014	7-11 (Citgo)	45179	3.699	87	9.014	33.34
3/26/2014	Arco	45471	3.639	87	9.656	35.14
3/31/2014	Arco	45770	3.679	87	9.463	34.81
4/12/2014	76	45995	3.959	87	8.88	35.16
4/27/2014	76	46208	4.099	87	8.671	35.54
5/17/2014	76	46475	3.999	87	9.101	36.39
5/25/2014	Safeway	46735	3.819	87	9.037	34.51
5/31/2014	Shell	47035	4.05	87	9.326	37.77
6/15/2014	76	47270	4.059	87	8.292	33.66
7/4/2014	Safeway	47531	3.959	87	9.12	36.11
7/6/2014	Safeway	47843	4.119	87	8.796	36.23
7/18/2014	Shell	48130	3.939	87	8.967	35.32
7/19/2014	Chevron	48449	3.999	87	9.166	36.65
7/27/2014	Shell	48743	4.099	87	8.572	35.14
	library(plyr)
	library(ggplot2)
	raw <- read.csv("gas2014.csv")
	avediff <- diff(raw$Mileage)
	raw$totalmiles <- c(NA, avediff)
	raw$Avgcost <- raw$totalmiles / raw$TotalCost
	raw$AvgMPG <- raw$totalmiles / raw$Amount

	costsummary <- ddply(raw, "Brand", function(x) data.frame(meancost = mean(x$Avgcost, na.rm=T)))
	mpgsummary <- ddply(raw, "Brand", function(x) data.frame(meanMPG = mean(x$AvgMPG, na.rm=T)))
	final <- merge(costsummary, mpgsummary)

	ggplot(final, aes(x= meancost, y= meanMPG, label= Brand)) +
	geom_point(size=4) +·
	geom_text(aes(label= Brand), hjust= -0.2, vjust= -0.2, size=8) +
	scale_x_continuous(limits = c(7,10)) +
	ylab("mean MPG") + xlab("Mean cost") +
	theme(axis.text.x = element_text(face='bold', size=20),
	axis.text.y = element_text(face='bold', size=20),
	axis.title.y = element_text(face="bold", size=20, angle=90),
	axis.title.x = element_text(face="bold", size=20)
	)