Package 'globaltrends'

Add batches of control or object keywords

Description

The function adds one or more batches of keywords with a time period for downloads to the database. The batches serve as input for all download and computation functions.

Usage

add_control_keyword(keyword, start_date = "2010-01", end_date = "2020-12")

add_object_keyword(keyword, start_date = "2010-01", end_date = "2020-12")

Arguments

keyword	Keywords that should be added as batch. Vector of type character or a list of character vectors. The function also allows the usage of codes for search topics instead of search terms.
start_date	Start of time frame for which the batch data should be downloaded. Object of type character that takes the from "YYYY-MM". Defaults to "2010-01".
end_date	End of time frame for which the batch data should be downloaded. Object of type character that takes the from "YYYY-MM". Defaults to "2020-12".

Details

Since Google Trends allows a maximum of five keywords for each query, batches of control keywords can consist of up to five keywords. Since one control keyword is added to batches of object keywords for mapping, object batch length is limited to four keywords. When a character vector contains more than four (five) keywords, the vector is split into four-keyword (five-keyword) batches. A list must contain character vectors of length four (five) or less. Each batch of keywords is combined with a time period for which data will be downloaded. To change the time period for an existing batch, all downloads and computations must be rerun.

Value

Message that the batch has been created successfully. Batch data is written to tables batch_keywords and batch_time. Numeric vector containing the newly added batch numbers are returned.

Warning

If you use search topics for object keywords, make sure to use search topics for control keywords and vice versa. See Google's FAQ for additional information on search topics.

Note

To avoid trailing spaces stringr::str_squish is automatically applied to all keywords.

See Also

• example_keywords()

• example_time()

• stringr::str_squish()

Examples

## Not run: 
add_control_keyword(
  keyword = c("gmail", "maps", "translate", "wikipedia", "youtube"),
  start_date = "2016-01", end_date = "2019-12"
)
add_object_keyword(
  keyword = c("apple", "facebook", "google", "microsoft"),
  start_date = "2016-01", end_date = "2019-12"
)

add_control_keyword(
  keyword = c("gmail", "maps", "news", "translate", "weather", "wikipedia", "youtube"),
  start_date = "2016-01", end_date = "2019-12"
)
add_control_keyword(
  keyword = c("amazon", "apple", "facebook", "google", "microsoft", "netflix", "twitter"),
  start_date = "2016-01", end_date = "2019-12"
)

add_control_keyword(
  keyword = list(
    c("gmail", "maps", "news"),
    c("translate", "weather", "wikipedia", "youtube")
  ),
  start_date = "2016-01", end_date = "2019-12"
)
add_control_keyword(
  keyword = list(
    c("amazon", "apple", "facebook", "google"),
    c("microsoft", "netflix", "twitter")
  ),
  start_date = "2016-01", end_date = "2019-12"
)

# search topics
add_control_keyword(
  keyword = c("%2Fm%2F02q_bk", "%2Fm%2F055t58", "%2Fm%2F025sndk", "%2Fm%2F0d07ph", "%2Fm%2F09jcvs"),
  start_date = "2016-01", end_date = "2019-12"
)
# This adds the following topics: Gmail, Google Maps, Google Translate, Wikipedia, YouTube

## End(Not run)

---

Add sets of locations

Description

The function adds a new set of locations for downloads and computations to the database. The location set serves as input for all download and computation functions.

Usage

add_locations(locations, type, export = TRUE)

Arguments

locations	Locations that should be added as set of locations. Vector of type character.
type	Name of the location set that should be added. Object of type character of length 1.
export	Indicator whether the new location set should be directly exported to the package environment gt.env. Object of type logical, defaults to TRUE.

Details

Location sets control the locations for which data is downloaded or to which computations are applied. By adding new location sets, the default sets countries and us_states can be expanded by additional sets. Thereby, users can compute DOI within a region (e.g., adding EU countries as a set) or single countries (e.g., adding regions of France as a set). Download and computation functions check whether data for a location already exists. Therefore, data will not be duplicated when location data already exists from another set.

Value

Message that the location set has been created successfully. Location data is written to table data_locations.

Warning

Unfortunately, the Google Trends API cannot handle the location "NA - Namibia". Therefore, the location will be dropped automatically.

Examples

## Not run: 
add_locations(locations = c("AT", "CH", "DE"), type = "DACH")

## End(Not run)

---

Add synonyms for object keywords

Description

The function allows to add synonyms for object keywords. Sometimes, objects of interest can be searched with different keywords on Google e.g., FC Bayern for Bayern Munich. Search scores for keywords that are added as synonyms are aggregated when running compute_score. The function allows to add synonyms for a single keyword at a time.

Usage

add_synonym(keyword, synonym)

## S3 method for class 'character'
add_synonym(keyword, synonym)

## S3 method for class 'list'
add_synonym(keyword, synonym)

Arguments

keyword	Keyword of type character and length 1 for which the synonyms are added.
synonym	Synonym of type character.

Value

Message that the synonym has been added successfully. Synonym data is written to table keyword_synonyms.

Note

To avoid trailing spaces stringr::str_squish is automatically applied to all keywords and synonyms.

See Also

• compute_score()

• stringr::str_squish()

Examples

## Not run: 
add_synonym(
  keyword = "fc bayern",
  synonym = "bayern munich"
)

## End(Not run)

---

Aggregate search scores for synonym terms

Description

The function aggregates search scores for object keywords across synonyms defined through add_synonyms. Users should run this funciton after running compute_score. Then, search scores will be added and the synonym terms removed from the data_score table. For efficiency reasons, the function uses purrr::map to iterate across batch_o.

Usage

aggregate_synonyms(control, vacuum = TRUE)

Arguments

control	Control batch for which the data is downloaded. Object of type numeric. Defaults to 1.
vacuum	Indicator whether the function should call vacuum_data(). Object of type logical. Defaults to TRUE.

Details

The function proceeds in five steps:

1. Export data from the database using purrr::map_dfr

2. Aggreagate score data from synonyms to main term

3. Remove batches that include synonyms from the database using purrr::walk

4. If vacuum = TRUE, run vacuum_data() on the database

5. Write aggregated data to the database using purrr::walk

During these steps, map_dfr and walk calls return progress information through .progress = TRUE.

Value

Message that the aggregation of synonyms is complete. During the aggregation process, messages regarding each step. The function shows the purrr::map_dfr and purrr:walk progress bars.

Note

The aggregation of synonyms can be very time-consuming when using a large dataset! Particulalry, the vacuum_data() call can require substantial time to run.

See Also

• add_synonym()

• vacuum_data()

Examples

## Not run: 
compute_score(object = 1:2, control = 1)
aggregate_synonyms(control = 1, vacuum = FALSE)

## End(Not run)

---

batch_keywords

Description

The table batch_keywords contains the keywords for each batch. Each line contains one keyword, the type of the batch (i.e., control or object) and the id of the batch to which the keyword is assigned. Keywords can be added with the function add_keywords. The function start_db exports the table batch_keywords as objects keywords_control and keywords_object to the package environment gt.env.

Example data for the table batch_keywords is available as R object example_keywords.

Usage

example_keywords

Format

A tibble with 19 rows and 3 variables:

type

Column of type character showing the type of each batch, takes "control" for control batches and "object" for object batches.

batch

Column of type integer showing the number of each batch.

keyword

Column of type character showing the keywords included in each batch.

See Also

• add_control_keyword()

---

batch_time

Description

The table batch_time contains the time period for which data is downloaded for each batch. Each line contains the start date, the end date, the type of the batch (i.e., control or object), and the id of the batch to which the time period is assigned. Start and end dates take the form "YYYY-MM". Time periods are added automatically through the function add_keywords. The function start_db exports the table batch_time as objects time_control and time_object to .GlobalEnv.

Example data for the table batch_time is available as R object example_time.

Usage

example_time

Format

A tibble with 5 rows and 3 variables:

type

Column of type character showing the type of each batch, takes "control" for control batches and "object" for object batches.

batch

Column of type integer showing number of each batch.

start_date

Column of type character showing the start date for each batch as "YYYY-MM".

end_date

Column of type character showing the end date for each batch as "YYYY-MM".

See Also

• add_control_keyword()

---

Aggregate keyword-country data and compute DOI

Description

The function computes degree of internationalization (DOI) for object keywords. Degree of internationalization is measured based on the distribution of country search scores.

Usage

compute_doi(object, control = 1, locations = "countries")

## S3 method for class 'numeric'
compute_doi(object, control = 1, locations = "countries")

## S3 method for class 'list'
compute_doi(object, control = 1, locations = "countries")

Arguments

object	Object batch for which the keyword-country data is aggregated and DOI is computed. Object of type numeric.
control	Control batch for which the search score is used. Object of type numeric.
locations	List of locations for which the search score is used. Object of type character. Defaults to "countries".

Details

The function uses an inverted Gini-coefficient as measure for the degree of internationalization. The more uniform the distribution of search scores across all countries, the higher the inverted Gini-coefficient and the greater the degree of internationalization. In addition to the Gini-coefficient, the package uses inverted Herfindahl index and inverted Entropy as measures for internationalization.

Value

Message that data was aggregated successfully. Data is written to table data_doi.

See Also

• example_doi()

Examples

## Not run: 
compute_doi(
  object = 1,
  control = 1,
  locations = "countries"
)
compute_doi(
  object = as.list(1:5),
  control = 1,
  locations = "countries"
)

## End(Not run)

---

Compute keyword-country search score

Description

The function computes search scores for object keywords. Search volumes for control and object batches are mapped to the same base. Next, search volumes for object batches are divided by the sum of search volumes for the respective control batch. compute_voi computes volume of internationalization (VOI) as global search scores.

Usage

compute_score(object, control = 1, locations = gt.env$countries)

## S3 method for class 'numeric'
compute_score(object, control = 1, locations = gt.env$countries)

## S3 method for class 'list'
compute_score(object, control = 1, locations = gt.env$countries)

compute_voi(object, control = 1)

Arguments

object	Object batch for which the data is downloaded. Object of type numeric or object of type list containing single objects of type numeric.
control	Control batch for which the data is downloaded. Object of type numeric. Defaults to 1.
locations	List of countries or regions for which the data is downloaded. Refers to lists generated in start_db. Defaults to countries.

Details

The search score computation proceeds in four steps. First, the function aggregates all search volumes to monthly data. Next, it follows the procedure outlined by Castelnuovo and Tran (2017, pp. A1-A2) to map control and object data. After the mapping, object search volumes are divided by the sum of control search volumes in the respective control batch. We use the sum of search volumes for a set of control keywords, rather than the search volumes for a single control keyword, to smooth-out variation in the underlying control data.

Castelnuovo, E. & Tran, T. D. 2017. Google It Up! A Google Trends-based Uncertainty index for the United States and Australia. Economics Letters, 161: 149-153.

Value

Message that data has been computed successfully. Data is written to table data_score.

Note

When synonyms were specified through add_synonym, run aggregate_synonyms to add their search scores to the main term.

See Also

• example_score()

• add_synonym()

Examples

## Not run: 
compute_score(
  object = 1,
  control = 1,
  locations = countries
)
compute_voi(
  object = 1,
  control = 1
)
compute_score(
  object = as.list(1:5),
  control = 1,
  locations = countries
)

## End(Not run)

---

countries

Description

A character vector that includes ISO2 codes for all countries with a share in global GDP >= 0.1\ World Development Indicators database. The data includes:

• AE

• AO

• AR

• AT

• AU

• BD

• BE

• BR

• CA

• CH

• CL

• CN

• CO

• CU

• CZ

• DE

• DK

• DO

• DZ

• EC

• EG

• ES

• ET

• FI

• FR

• GB

• GR

• HK

• HU

• ID

• IE

• IL

• IN

• IQ

• IR

• IT

• JP

• KR

• KW

• KZ

• LK

• MA

• MX

• MY

• NG

• NL

• NO

• NZ

• OM

• PE

• PH

• PK

• PL

• PR

• PT

• QA

• RO

• RU

• SA

• SD

• SE

• SG

• SK

• TH

• TR

• TW

• UA

• US

• UZ

• VN

• ZA

Usage

countries

Format

An object of class character of length 71.

---

countries_wdi

Description

A data.frame that includes ISO2 codes and country names for all countries and locations in the World Bank's World Development Indicators database.

Usage

countries_wdi

Format

An object of class data.frame with 299 rows and 2 columns.

---

data_control

Description

The table data_control contains the downloaded data for each control batch. Each line contains the search hits for each keyword in a control batch for a given location and date. Global data gets the value world as location. Data is downloaded and automatically written to the table through the function download_control. The function start_db exports the table data_control as database connection tbl_control to the package environment gt.env. Users can access the database table through dplyr::tbl. The sample data included in data_control was simulated based on actual Google Trends data.

Example data for the table data_control is available as R object example_control.

Usage

example_control

Format

A tibble with 2,400 rows and 5 variables:

location

Column of type character showing the ISO2 code of the country or region for which the data was downloaded.

keyword

Column of type character showing the keyword for which the data was downloaded.

date

Column of type integer showing the date for which the data was downloaded. Can be transformed into date format with lubridate::as_date.⁠\item{hits}{Column of type⁠double⁠showing search volumes for the respective location-keyword-date combination.} \item{batch}{Column of type⁠integer' showing the number of each batch.

Source

https://trends.google.com/trends/

See Also

• download_control()

• dplyr::tbl()

---

data_doi

Description

The table data_doi contains the degree of internationalization (DOI) for each object batch. Each line contains the DOI computed as inverted gini coefficient, as inverted hhi, or inverted entropy for each keyword in an object batch_o for a given date. The column batch_c indicates the control batch that has been used as baseline for mapping. Column locations indicates which set of locations was used to compute the distribution of search scores. DOI is computed and automatically written to the table with the function compute_doi. The function start_db exports the table data_doi as database connection tbl_doi to the package environment gt.env. Users can access the database table through dplyr::tbl. The sample data included in data_doi was simulated based on actual Google Trends data.

Usage

example_doi

Format

A tibble with 4,320 rows and 9 variables:

keyword

Column of type character showing the keyword for which the data was computed.

date

Column of type integer showing the date for which the data was computed Can be transformed into date format with lubridate::as_date.

gini

Column of type double showing the DOI computed as inverted Gini coefficient of the search score distribution from data_score.

hhi

Column of type double showing the DOI computed as inverted Herfindahl-Hirschman index of the search score distribution from data_score.

entropy

Column of type double showing the DOI computed as inverted Entropy measure for the search score distribution from data_score.

batch_c

Column of type integer showing the number of each control batch.

batch_o

Column of type integer showing the number of each object batch.

locations

Column of type character showing the list of locations for which the search score distribution is used.

See Also

• compute_doi()

• dplyr::tbl()

---

data_object

Description

The table data_object contains the downloaded data for each object batch. Each line contains the search hits for each keyword in an object batch_o for a given location and date. The column batch_c indicates the control batch to which the data will be mapped. Global data takes the value world as location. Data is downloaded and automatically written to the table through the function download_object. The function start_db exports the table data_object as database connection tbl_object to the package environment gt.env. Users can access the database table through dplyr::tbl. The sample data included in data_object was simulated based on actual Google Trends data.

Example data for the table data_object is available as R object example_object.

Usage

example_object

Format

A tibble with 8,640 rows and 6 variables:

location

Column of type character showing the ISO2 code of the country or region for which the data was downloaded.

keyword

Column of type character showing the keyword for which the data was downloaded.

date

Column of type integer showing the date for which the data was downloaded. Can be transformed into date format with lubridate::as_date.

hits

Column of type double showing search volumes for the respective location-keyword-date combination.

batch_c

Column of type integer showing the number of each control batch.

batch_o

Column of type integer showing the number of each object batch.

Source

https://trends.google.com/trends/

See Also

• download_object()

• dplyr::tbl()

---

data_score

Description

The table data_score contains the search scores for each object batch. Each line contains the search score (score) for each keyword in an object batch_o for a given location and date. The column batch_c indicates the control batch that has been used as baseline for mapping. Global data takes the value world as location. Search scores are computed and automatically written to the table with the function compute_score. The function start_db exports the table data_score as database connection tbl_score to the package environment gt.env. Users can access the database table through dplyr::tbl. The sample data included in data_score was simulated based on actual Google Trends data.

Example data for the table data_score is available as R object example_score.

Usage

example_score

Format

A tibble with 6,000 rows and 7 variables:

location

Column of type character showing the ISO2 code of the country or region for which the data was computed.

keyword

Column of type character showing the keyword for which the data was downloaded.

date

Column of type integer showing the date for which the data was computed Can be transformed into date format with lubridate::as_date.

score

Column of type double showing search score for the respective location-keyword-date combination.

batch_c

Column of type integer showing the number of each control batch.

batch_o

Column of type integer showing the number of each object batch.

See Also

• compute_score()

• compute_voi()

• dplyr::tbl()

---

Disconnect from database

Description

The function closes the connection to the database file db/globaltrends_db.sqlite in the working directory.

Usage

disconnect_db()

Value

Message that disconnection was successful.

Warning

SQLite databases only allow one writer at any instant in time. To run parallel downloads use one database for each download client and merge them once all downloads are complete.

See Also

• initialize_db()

• start_db()

Examples

## Not run: 
disconnect_db()

## End(Not run)

---

Download data for control keywords

Description

The function downloads search volumes from Google Trends for a control batch in a set of locations. Data is automatically written to table data_control. For download_control_global the input location is automatically set to world.

Usage

download_control(control, locations = gt.env$countries)

## S3 method for class 'numeric'
download_control(control, locations = gt.env$countries)

## S3 method for class 'list'
download_control(control, locations = gt.env$countries)

download_control_global(control)

Arguments

control	Control batch for which the data is downloaded. Object of type numeric or object of type list containing single objects of type numeric.
locations	List of countries or regions for which the data is downloaded. Refers to lists generated in start_db. Defaults to gt.env$countries.

Details

Downloads through the Google Trends API are made through gtrendsR::gtrends. Each control batch can consist of up to five keywords and is predefined in tables batch_keywords and batch_time through add_keywords. The download for a single keyword batch for a single location takes about 30 seconds. This includes a randomized waiting period of 5-10 seconds between downloads. Depending on the frequency of downloads, Google Trends might block users for some time (about 1,500 downloads within 24 hours). In this case, download_control waits 60 minutes before it retries the download.

Value

Message that data has been downloaded successfully. Data is written to table data_control.

Warning

We advise against the usage of category codes in downloads. If you use categories to narrow the context of keyword usage, these categories are applied to ALL keywords in the batch. This applies to control keywords as well as object keywords and can result in unintended behavior.

See Also

• example_control()

• gtrendsR::gtrends()

Examples

## Not run: 
download_control(
  control = 1,
  locations = countries
)
download_control(
  control = as.list(1:5),
  locations = countries
)

## End(Not run)

---

Download data for object batch

Description

The function downloads search volumes from Google Trends for an object batch (batch_o) and one keyword from a control batch (batch_c) in a set of locations. Data is automatically written to table data_object. For download_object_global the input location is automatically set to world.

Usage

download_object(object, control = 1, locations = gt.env$countries)

## S3 method for class 'numeric'
download_object(object, control = 1, locations = gt.env$countries)

## S3 method for class 'list'
download_object(object, control = 1, locations = gt.env$countries)

download_object_global(object, control = 1)

Arguments

object	Object batch for which the data is downloaded. Object of type numeric or object of type list containing single object of type numeric.
control	Control batch that is used for mapping. Object of type numeric. Defaults to 1.
locations	List of countries or regions for which the data is downloaded. Refers to lists generated in start_db. Defaults to countries.

Details

Downloads through the Google Trends API are made through gtrendsR::gtrends. Each object batch can consist of up to four keywords and is predefined in tables batch_keywords and batch_time through add_keywords. In addition, one control keyword is added to each object batch. The control keyword then allows a mapping between search volumes for control keywords stored in data_control and search volumes for object keywords. The download for a single keyword batch for a single location takes about 30 seconds. This includes a randomized waiting period of 5-10 seconds between downloads. Depending on the frequency of downloads, Google Trends might block users for some time (about 1,500 downloads within 24 hours). In this case, download_object waits 60 minutes before it retries the download.

Value

Message that data was downloaded successfully. Data is written to table data_object.

Warning

We advise against the usage of category codes in downloads. If you use categories to narrow the context of keyword usage, these categories are applied to ALL keywords in the batch. This applies to control keywords as well as object keywords and can result in unintended behavior.

See Also

• example_object()

• gtrendsR::gtrends()

Examples

## Not run: 
download_object(
  object = 1,
  locations = countries
)
download_object(
  object = as.list(1:5),
  locations = countries
)

## End(Not run)

---

Export data from database table

Description

The function allows to export data from database tables. In combination with various write functions in R, the functions allow exports from the database to local files.

Usage

export_control(control = NULL, location = NULL)

export_control_global(control = NULL)

export_object(keyword = NULL, object = NULL, control = NULL, location = NULL)

export_object_global(keyword = NULL, object = NULL, control = NULL)

export_score(keyword = NULL, object = NULL, control = NULL, location = NULL)

export_voi(keyword = NULL, object = NULL, control = NULL)

export_doi(keyword = NULL, object = NULL, control = NULL, locations = NULL)

Arguments

control	Control batch number for which data should be exported. Only for export_control and export_control_global, input is also possible as list.
location	List of locations for which the data is exported. Refers to lists generated in start_db or character objects in these lists. Only for export_control, export_object, or export_score.
keyword	Object keywords for which data should be exported. Object or list of objects of type character.
object	Object batch number for which data should be exported.
locations	List of locations for which the data is exported. Refers to names of lists generated in start_db as an object of type character. Only for export_doi.

Details

Exports can be filtered by keyword, object, control, location, locations, or type. Not all filters are applicable for all functions. When filter keyword and object are used together, keyword overrules object. When supplying NULL as input, no filter is applied to the variable.

Value

The functions export and filter the respective database tables.

• export_control and export_control_global export data from table data_control with columns location, keyword, date, hits, control. Object of class "data.frame". Methods are applied based on input control.

• export_object and export_object_global export data from table data_object with columns location, keyword, date, hits, object. Object of class "data.frame". Methods are applied based on input keyword.

• export_score exports data from table data_score with columns location, keyword, date, score, control, object. Object of class "data.frame". Methods are applied based on input keyword.

• export_voi exports data from table data_score with columns keyword, date, score, control, filters for location == "world". Object of class "data.frame". Methods are applied based on input keyword.

• export_doi exports data from table data_doi with columns keyword, date, gini, hhi, entropy, control, object, locations. Object of class "data.frame". Methods are applied based on input keyword.

See Also

• example_control()

• example_object()

• example_score()

• example_doi()

Examples

## Not run: 
export_control(control = 2)

export_object(
  keyword = "manchester united",
  locations = countries
)

export_object(
  keyword = c("manchester united", "real madrid")
)

export_object(
  keyword = list("manchester united", "real madrid")
)

export_score(
  object = 3,
  control = 1,
  location = us_states
) %>%
  readr::write_csv("data_score.csv")

export_doi(
  keyword = "manchester united",
  control = 2,
  locations = "us_states"
) %>%
  writexl::write_xlsx("data_doi.xlsx")

## End(Not run)

---

globaltrends package environment

Description

The environment gt.env contains all package-related data objects, such as the handle for the SQLite database file or connections to tables. The object contains:

• globaltrends_db: Handle for the SQLite database file.

• tbl_locations: Connection to table that contains the lists of locations saved in the database.

• tbl_keywords: Connection to table that contains the lists of keywords saved in the database.

• tbl_time: Connection to table that contains the lists of batch times saved in the database.

• tbl_synonyms: Connection to table that contains the lists of keyword synonyms saved in the database.

• tbl_doi: Connection to table that contains the DOI data saved in the database.

• tbl_control: Connection to table that contains data on search volume for control terms saved in the database.

• tbl_object: Connection to table that contains data on search volume for object terms saved in the database.

• tbl_score: Connection to table that contains data on search scores saved in the database.

• keywords_control: Tibble that contains all keywords per control batch.

• time_control: Tibble that contains all batch times per control batch.

• keywords_object: Tibble that contains all keywords per object batch.

• time_object: Tibble that contains all batch times per object batch.

• keyword_synonyms: Tibble that contains all keyword/synonym combinations.

• query_wait: Number of seconds to wait between queries (default = 0.1s).

• py_setup: TRUE/FALSE indicator whether initialize_python has been called.

Usage

gt.env

Format

An object of class environment of length 16.

See Also

• example_control()

• example_object()

• example_score()

• example_doi()

---

Initialize database

Description

The function creates a new database for the globaltrends package and creates all necessary tables within the database.

Usage

initialize_db()

Details

The function creates a new SQLite database for the globaltrends package. The database is saved as file db/globaltrends_db.sqlite in the working directory. If the folder db does not exists in the working directory, the folder is created. If the database already exists in the working directory, the function exits with an error. Within the database all tables are created and the default location sets are added to the respective table:

• countries - all countries with a share in global GDP >= 0.1\ in 2018.

• us_states - all US federal states and Washington DC.

After creating the database, the function disconnects from the database.

Value

Database is created.

Warning

SQLite databases only allow one writer at any instant in time. To run parallel downloads use one database for each download client and merge them once all downloads are complete.

See Also

• start_db()

• disconnect_db()

• countries()

• us_states()

• example_keywords()

• example_time()

• example_control()

• example_object()

• example_score()

• example_doi()

• https://www.sqlite.org/index.html

Examples

## Not run: 
initialize_db()

## End(Not run)

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Initialize gtrends Python module

Description

The function initializes the Python session required to download data from Google Trends using the Google Trends research API. The user can define an API key and either a Conda or Python environment.

Usage

initialize_python(api_key, conda_env = NULL, python_env = NULL)

Arguments

api_key	API key obtained from Google. Object of type character.
conda_env	Storage location of a Conda environment. Object of type character.
python_env	Storage location of a Python environment. Object of type character.

Details

To use this API acces, you must:

1. Apply for API access online. and generate an API key in your Google developer console.

2. Create a Python or Conda environment where you install the google-api-python-client package with pip.

Value

The functions sets the environment variable gt.env to TRUE. This channels downloads to the API. Otherwise, globaltrends uses gtrendsR::gtrends for downloads.

Examples

## Not run: 
initialize_python(
  api_key = "XXX",
  conda_env = "/xxx/venv"
)

## End(Not run)

---

Remove data from database tables

Description

The function removes data from database tables for control or object batches.

Usage

remove_data(table, control = NULL, object = NULL)

vacuum_data()

Arguments

table	Database table from which the batch should be removed. Object of type character.
control	Control batch for which the data is removed Object of type numeric.
object	Object batch for which the data is removed Object of type numeric.

Details

The function removes data "greedily": all data that builds on the deleted data is removed. For example, when data from data_control is removed data in data_object that maps to this control batch is also removed. The dependency structure works as follows: batch_keyword / batch_time -> data_control -> data_object -> data_score -> data_doi.

After using remove_data, run vacuum_data to free-up unused memory in the database file. Depending on the database size, vacuum_data might take some minutes for execution.

Value

Message that data has been removed successfully. Data is removed from database tables.

See Also

• example_keywords()

• example_time()

• example_control()

• example_object()

• example_score()

• example_doi()

Examples

## Not run: 
remove_data(
  table = "batch_keywords",
  control = 1
)
remove_data(
  table = "data_score",
  control = 1,
  object = 1
)
vacuum_data()

## End(Not run)

---

Load globaltrends database and tables

Description

The function connects to the database file db/globaltrends_db.sqlite in the working directory. After connecting to the database connections to the database tables (through dplyr::tbl) are created. Data from the tables batch_keywords and batch_time are exported to the tibble objects keywords_control, keywords_object, time_control, and time_object.

Usage

start_db()

Value

The function exports the following objects to the package environment globaltrends_db:

• globaltrends_db A DBIConnection object, as returned by DBI::dbConnect(), connecting to the SQLite database in the working directory

• tbl_doi A remote data source pointing to the table data_doi in the connected SQLite database

• tbl_control A remote data source pointing to the table data_control in the connected SQLite database

• tbl_mapping A remote data source pointing to the table data_mapping in the connected SQLite database

• tbl_object A remote data source pointing to the table data_object in the connected SQLite database

• tbl_score A remote data source pointing to the table data_score in the connected SQLite database

• countries A character vector containing ISO2 country codes of countries that add at least 0.1\

• us_states A character vector containing ISO2 regional codes of US states

• keywords_control A tibble containing keywords of control batches

• time_control A tibble containing times of control batches

• keywords_object A tibble containing keywords of object batches

• time_object A tibble containing times of control batches

• keyword_synonyms A tibble containing synonymous keywords

Warning

SQLite databases only allow one writer at any instant in time. To run parallel downloads use one database for each download client and merge them once all downloads are complete.

See Also

• initialize_db()

• disconnect_db()

• dplyr::tbl()

Examples

## Not run: 
start_db()

## End(Not run)

---

us_states

Description

A character vector that includes ISO2 codes for all US federal states and Washington DC. The data includes:

• US-AL

• US-AK

• US-AZ

• US-AR

• US-CA

• US-CO

• US-CT

• US-DE

• US-FL

• US-GA

• US-HI

• US-ID

• US-IL

• US-IN

• US-IA

• US-KS

• US-KY

• US-LA

• US-ME

• US-MD

• US-MA

• US-MI

• US-MN

• US-MS

• US-MO

• US-MT

• US-NE

• US-NV

• US-NH

• US-NJ

• US-NM

• US-NY

• US-NC

• US-ND

• US-OH

• US-OK

• US-OR

• US-PA

• US-RI

• US-SC

• US-SD

• US-TN

• US-TX

• US-UT

• US-VT

• US-VA

• US-WA

• US-WV

• US-WI

• US-WY

• US-DC

Usage

us_states

Format

An object of class character of length 51.

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