Playing around with R using data van Google
Analytics, using the following recipes:
Here are some graphs:
Daily visits for 2014
ggplot(myresults, aes(x=date, y=visits))+ geom_point() +
+ stat_smooth()
Here data per month and the statistics.
mydata <- ga$getData(id,
start.date="2014-01-01", end.date="2014-12-31",metrics =
"ga:visits, ga:pageviews", dimensions = "ga:month")
mydata
month visits pageviews
1 1 0 0
2 2 35 54
3 3 51 76
4 4 79 95
5 5 83 143
6 6 24 24
7 7 27 33
8 8 55 74
9 9 112 153
10 10 326 417
11 11 888 1201
12 12 1120 1596
summary(mydata)
month visits pageviews
1 :1 Min. : 0.0 Min. : 0.00
2 :1 1st Qu.: 33.0 1st Qu.: 48.75
3 :1 Median : 67.0 Median : 85.50
4 :1 Mean : 233.3 Mean : 322.17
5 :1 3rd Qu.: 165.5 3rd Qu.: 219.00
6 :1 Max. :1120.0 Max. :1596.00
Here is a bar graph for visits per month
for 2014
barplot(mydata$visits, main="Visits by
month", xlab="Month", names.arg=mydata$month, las=1,
col=rainbow(9))
Where are the visitors coming from? mylocal <- ga$getData
(id, start.date="2014-01-01",
end.date="2014-12-31",
metrics = "ga:visits",
dimensions = "ga:country",
sort = "-ga:visits",start = 1, max = 100)
mylocal
country visits
1 United States 802
2 Netherlands 320
3 United Kingdom 208
4 Canada 192
5 France 163
6 Germany 117
7 Australia 97
8 Spain 64
9 Italy 59
10 Israel 50
mysystem <- ga$getData(id, start.date="2014-01-01", end.date="2014-12-31",
metrics = "ga:visits", dimensions = "ga:browser",sort = "-ga:visits",start = 1,
max = 100)
> mysystem browser visits
1 Chrome 1612
2 Firefox 517
3 Android Browser 275
4 Internet Explorer 241
5 Safari 105
6 Opera 18
7 Safari (in-app) 13
8 UC Browser 9
mysystem2 <- ga$getData(id, start.date="2014-01-01", end.date="2014-12-31",
metrics = "ga:visits", dimensions = "ga:operatingSystem",sort = "-ga:visits",
start = 1, max = 100)
> mysystem2 operatingSystem visits
1 Windows 1555
2 Android 825
3 Linux 183
4 Macintosh 144
5 iOS 79
6 Windows Phone 5
7 (not set) 3
8 BlackBerry 3
9 Chrome OS 3
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