Description Usage Arguments Details Value Author(s) Examples
The googletrend
package was developed to load and transform Google Trends data within R. The aim of the package is to minimize the effort of manually downloading and merging different CSV files from Google Trends.
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keyword |
this argument allows to specify the Google Trend search term(s) (example: |
geo |
this argument allows to specify country or state (example: use |
year |
this argument allows to specify a particular year (example: |
plot |
this binary argument allows to specify whether a trend figure shall be displayed or not. Default is TRUE, i.e. shows trend figures. |
simple |
this binary argument allows to specify whether full attribute data (such as top cities, countries, top related keyword list) shall be returned or not. Default is TRUE, i.e. the function only returns the Google Trend index without any further attributes. If FALSE, the function returns full attribute data (incl. top cities, countries, related top keywords list, raising new keywords, etc.). |
use.monthly |
this binary argument allows to specify whether the Google Trend index shall be aggregated to monthly frequency data or not. Default is FALSE, i.e. use weekly data.
compare |
this binary argument allows specify whether different search terms, locations or time ranges shall be compared or not. Default is FALSE, i.e. multiple search terms, multiple geo locations or multiple time ranges are loaded individually one-by-one. If TRUE the values of those attributes are compared for which there are multiple terms (either multiple keywords, multiple geos or multiple years).
USING GOOGLE SPECIAL SEARCH OPERATOR (+,-,"")
gettrend(keyword = 'tennis shoes') #result includes searches containing both 'tennis' and 'shoes' in any order.
gettrend(keyword = '"tennis shoes"') #result includes exact search term
gettrend(keyword = 'tennis+shoes') #result contains searches the word 'tennis' OR 'shoes'
gettrend(keyword = 'tennis-shoes') #results will include searches with the word 'tennis' but excludes searches with the word 'shoes'
NULL - no result matches with keyword; trend data frame - dataframe(Date,Index) if simple=TRUE; list - all trend attributes like spatial info if simple=FALSE;
Chris Okugami
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# (1) LOAD SINGLE KEYWORDS
(1.1) Load single keyword index
TREND.A <- gettrend(keyword = 'Basketball')
TREND.B <- gettrend(keyword = 'Football')
TREND.C <- gettrend(keyword = 'Tennis')
> head(TREND.C)
week index
1 2004-01-04 42
2 2004-01-11 43
3 2004-01-18 55
4 2004-01-25 57
5 2004-02-01 45
6 2004-02-08 42
# (2) LOAD AND MERGE MULTIPLE KEYWORDS
TRENDS.ABC <- gettrend(keyword='Basketball, Football, Tennis')
MERGED.TRENDS.ABC <- googletrend::mergetrend(TRENDS.ABC)
> head(MERGED.TRENDS.ABC)
week Basketball Football Tennis
1 2004-01-04 42 39 42
2 2004-01-11 46 37 43
3 2004-01-18 47 37 55
4 2004-01-25 43 35 57
5 2004-02-01 44 40 45
6 2004-02-08 46 33 42
# (3) LOAD FULL ATTRIBUTE LISTS
# (3.1) Load full attribute list
TREND.ATT <- gettrend(keyword = 'Tennis', simple=FALSE)
# Show attributea via $top.region, $top.city or $top.search
> head(TREND.ATT$top.region)
region index
576 Australia 100
577 Bermuda 93
578 Monaco 90
579 San Marino 87
580 Switzerland 82
581 France 80
> head(TREND.ATT$top.city)
region index
747 Paris (France) 100
748 Melbourne (Australia) 99
749 London (United Kingdom) 94
750 Zurich (Switzerland) 91
751 Sydney (Australia) 85
752 Brussels (Belgium) 78
> head(TREND.ATT$top.search)
top.search index
764 tennis us open 75
765 us open 70
766 atp tennis 60
767 atp 60
768 live tennis 50
769 tennis shoes 40
# (4) ADDITIONAL SPECIFICATIONS
# (4.1) Search for keyword in a specific country or state (e.g. 'Australia' or 'New South Wales')
TREND.GEO <- gettrend(keyword = 'Tennis', geo = 'AU')
TREND.GEO <- gettrend(keyword = 'Tennis', geo = 'AU-NSW')
# (4.2) Search for keyword during a particular year (e.g. '2012')
TREND.GEO <- gettrend(keyword = 'Tennis', year = '2012')
# (4.3) Search for keyword within a particular category (e.g. 'Sports')
TREND.CAT <- gettrend(keyword = 'Tennis', category='0-20')
# (4.4) Compare different search terms, locations, or time spans,
TREND.COMP.KEY <- gettrend(keyword = 'Basketball, Football, Tennis', compare = TRUE)
TREND.COMP.GEO <- gettrend(keyword = 'Tennis', geo = 'AU, IN, US', compare = TRUE)
TREND.COMP.TSP <- gettrend(keyword = 'Tennis', year= '2011, 2012, 2013', compare = TRUE)
# (4.5) Use monthly values (i.e. index is aggregated/summed over different weeks)
TREND.MTH <- gettrend (keyword = 'Tennis', use.monthly=TRUE)
# (5) COMPUTATIONS AND DATA MANIPULATION
# (5.1) Plot a single keyword (use $'...' for keywords with space)
TRENDS.ABC <- gettrend(keyword='Basketball, Football, Tennis')
MERGED.TRENDS.ABC <- googletrend::mergetrend(TRENDS.ABC)
plot(MERGED.TRENDS.ABC$Basketball,type='l')
# (5.2) Correlation among multiple keywords
TRENDS.ABC <- gettrend(keyword='Basketball, Football, Tennis')
MERGED.TRENDS.ABC <- googletrend::mergetrend(TRENDS.ABC)
cor(MERGED.TRENDS.ABC[,-1])
# (5.3) Fit linear regression to the data
TRENDS.ABC <- gettrend(keyword='Basketball, Football, Tennis')
MERGED.TRENDS.ABC <- googletrend::mergetrend(TRENDS.ABC)
REGMODELL <- lm(Basketball ~ Football + Tennis, data=MERGED.TRENDS.ABC)
summary(REGMODELL)
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