| Type: | Package | 
| Title: | Access Japanese Data via Public APIs and Curated Datasets | 
| Version: | 0.1.0 | 
| Maintainer: | Renzo Caceres Rossi <arenzocaceresrossi@gmail.com> | 
| Description: | Provides functions to access data from public RESTful APIs including 'Nager.Date', 'World Bank API', and 'REST Countries API', retrieving real-time or historical data related to Japan, such as holidays, economic indicators, and international demographic and geopolitical indicators. Additionally, the package includes one of the largest curated collections of open datasets focused on Japan, covering topics such as natural disasters, economic production, vehicle industry, air quality, demographics, and administrative divisions. The package supports reproducible research and teaching by integrating reliable international APIs and structured datasets from public, academic, and government sources. For more information on the APIs, see: 'Nager.Date' https://date.nager.at/Api, 'World Bank API' https://datahelpdesk.worldbank.org/knowledgebase/articles/889392, and 'REST Countries API' https://restcountries.com/. | 
| License: | MIT + file LICENSE | 
| Language: | en | 
| URL: | https://github.com/lightbluetitan/japanapis, https://lightbluetitan.github.io/japanapis/ | 
| BugReports: | https://github.com/lightbluetitan/japanapis/issues | 
| Encoding: | UTF-8 | 
| LazyData: | true | 
| Depends: | R (≥ 4.1.0) | 
| Imports: | utils, httr, jsonlite, dplyr, scales, tibble | 
| Suggests: | ggplot2, testthat (≥ 3.0.0), knitr, rmarkdown | 
| RoxygenNote: | 7.3.2 | 
| Config/testthat/edition: | 3 | 
| VignetteBuilder: | knitr | 
| NeedsCompilation: | no | 
| Packaged: | 2025-08-21 02:52:15 UTC; Renzo | 
| Author: | Renzo Caceres Rossi | 
| Repository: | CRAN | 
| Date/Publication: | 2025-08-26 19:30:07 UTC | 
JapanAPIs: Access Japanese Data via Public APIs and Curated Datasets
Description
This package provides functions to access data from public RESTful APIs including 'Nager.Date', 'World Bank API', and 'REST Countries API', retrieving real-time or historical data related to Japan, such as holidays, economic indicators, international demographic and geopolitical indicators. Additionally, the package includes one of the largest curated collections of open datasets focused on Japan, covering topics such as natural disasters, economic production, vehicle industry, air quality, demographics, and administrative divisions.
Details
JapanAPIs: Access Japanese Data via Public APIs and Curated Datasets
 
Access Japanese Data via Public APIs and Curated Datasets.
Author(s)
Maintainer: Renzo Caceres Rossi arenzocaceresrossi@gmail.com
See Also
Useful links:
Japanese J1 League Results
Description
This dataset, J1League_tbl_df, is a tibble containing results of Japan's J1 League matches from 2012 to 2022. The dataset includes information such as the season, match date and time, home and away teams, goals scored, and final match result. The dataset preserves the original structure from its source on Kaggle.
Usage
data(J1League_tbl_df)
Format
A tibble with 3,213 observations and 7 variables:
- Season
- Season year of the match (numeric) 
- DateTime
- Date and time of the match (POSIXct) 
- Home
- Home team name (character) 
- Away
- Away team name (character) 
- HG
- Number of goals scored by the home team (numeric) 
- AG
- Number of goals scored by the away team (numeric) 
- Res
- Final result of the match (character) 
Details
The dataset name has been kept as 'J1League_tbl_df' to maintain consistency with the naming conventions in the JapanAPIs package. The suffix 'tbl_df' indicates that this is a tibble data frame. The original content has not been modified in any way.
Source
Data obtained from Kaggle: https://www.kaggle.com/datasets/irkaal/japanese-j1-league
Japanese National Character Survey Sample
Description
This dataset, JNcharacter_df, is a data frame containing a subset of responses from the Survey on the Japanese National Character. It includes demographic variables and responses related to values, opinions, and attitudes.
Usage
data(JNcharacter_df)
Format
A data frame with 85 observations and 10 variables:
- sex
- Sex of the respondent (numeric) 
- age
- Age of the respondent (numeric) 
- pol.party
- Political party preference (numeric) 
- education
- Level of education (numeric) 
- occupation
- Occupation category (numeric) 
- born.again
- Religious identification: born again or not (numeric) 
- difficult
- Perception of life as difficult (numeric) 
- pleasure
- Attitude toward pleasure (numeric) 
- women.job
- Opinion on women working (numeric) 
- money
- Importance of money (numeric) 
Details
The dataset name has been kept as 'JNcharacter_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.
Source
Data taken from the catdap package version 1.3.7
Japanese Atomic Bomb Survivors
Description
This dataset, atomic_bomb_survivors_df, is a data frame containing frequencies of cancer deaths among Japanese atomic bomb survivors, categorized by extent of exposure, years after exposure, and age group. The dataset was used in the journal Statistical Sleuth and analyzed by Gore et al. (2006).
Usage
data(atomic_bomb_survivors_df)
Format
A data frame with 84 observations and 4 variables:
- Radians
- Radiation exposure level (integer) 
- Count.Type
- Type of count (factor) 
- Count.Age.Group
- Age group at time of observation (factor) 
- Frequency
- Frequency of cancer deaths (integer) 
Details
The dataset name has been kept as 'atomic_bomb_survivors_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.
Source
Data taken from the ACSWR package version 1.0
Japanese Centenarians Data
Description
This dataset, centenarian_df, is a data frame containing the number of deaths at each year from 1963 to 1980 for Japanese male centenarians. The data is based on Table 2 of Emura and Murotani (2015), and also references the original work of Sibuya & Hanayama (2004).
Usage
data(centenarian_df)
Format
A data frame with 21 observations and 19 variables:
- X
- Age or identifier (numeric) 
- X1963
- Number of deaths in 1963 (integer) 
- X1964
- Number of deaths in 1964 (integer) 
- X1965
- Number of deaths in 1965 (integer) 
- X1966
- Number of deaths in 1966 (integer) 
- X1967
- Number of deaths in 1967 (integer) 
- X1968
- Number of deaths in 1968 (integer) 
- X1969
- Number of deaths in 1969 (integer) 
- X1970
- Number of deaths in 1970 (integer) 
- X1971
- Number of deaths in 1971 (integer) 
- X1972
- Number of deaths in 1972 (integer) 
- X1973
- Number of deaths in 1973 (integer) 
- X1974
- Number of deaths in 1974 (integer) 
- X1975
- Number of deaths in 1975 (integer) 
- X1976
- Number of deaths in 1976 (integer) 
- X1977
- Number of deaths in 1977 (integer) 
- X1978
- Number of deaths in 1978 (integer) 
- X1979
- Number of deaths in 1979 (integer) 
- X1980
- Number of deaths in 1980 (integer) 
Details
The dataset name has been kept as 'centenarian_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.
Source
Data taken from the depend.truncation package version 3.0
Earthquake Observation Stations in Japan
Description
This dataset, earthquake_station_sf, is a spatial features (sf) tibble containing information about 671 earthquake observation stations managed by the Japan Meteorological Agency. It includes details such as the prefecture, area, station name, address, and observation period.
Usage
data(earthquake_station_sf)
Format
An sf object with 671 observations and 7 variables:
- prefecture
- Name of the prefecture (character) 
- area
- Area within the prefecture (character) 
- station_name
- Name of the observation station (character) 
- address
- Physical address of the station (character) 
- observation_begin
- Start date of observation (character) 
- observation_end
- End date of observation, if available (character) 
- geometry
- XY coordinates of the station (sf geometry column) 
Details
The dataset name has been kept as 'earthquake_station_sf' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'sf' indicates that the dataset is a spatial features object. The original content has not been modified in any way.
Source
Data taken from the jmastats package version 0.3.0
Get Key Country Information About Japan from the REST Countries API
Description
Retrieves selected, essential information about Japan using the REST Countries API. The function returns a tibble with core details such as population, area, capital, region, and official language(s).
See the API documentation at https://restcountries.com/. Example API usage: https://restcountries.com/v3.1/name/japan?fullText=true.
Usage
get_country_info_jp()
Details
The function sends a GET request to the REST Countries API. If the API returns data for Japan,
the function extracts and returns selected fields as a tibble. If the request fails or
Japan is not found, it returns NULL and prints a message.
Value
A tibble with the following 8 columns:
-  name_common: Common name of the country.
-  name_official: Official name of the country.
-  region: Geographical region.
-  subregion: Subregion within the continent.
-  capital: Capital city.
-  area: Area in square kilometers.
-  population: Population of the country.
-  languages: Languages spoken in the country, as a comma-separated string.
Note
Requires internet connection. The data is retrieved in real time from the REST Countries API.
Source
REST Countries API: https://restcountries.com/
Examples
get_country_info_jp()
Get Under-5 Mortality Rate in Japan from World Bank
Description
Retrieves Japan's under-five mortality rate (per 1,000 live births)
for the years 2010 to 2022 using the World Bank Open Data API.
The indicator used is SH.DYN.MORT.
Usage
get_japan_child_mortality()
Details
This function sends a GET request to the World Bank API.
If the API request fails or returns an error status code,
the function returns NULL with an informative message.
Value
A tibble with the following columns:
-  indicator: Indicator name (e.g., "Mortality rate, under-5 (per 1,000 live births)")
-  country: Country name ("Japan")
-  year: Year of the data (integer)
-  value: Under-5 mortality rate per 1,000 live births (numeric)
Note
Requires internet connection.
Source
World Bank Open Data API: https://data.worldbank.org/indicator/SH.DYN.MORT
See Also
Examples
if (interactive()) {
  get_japan_child_mortality()
}
Get Japan's Consumer Price Index from World Bank
Description
Retrieves Japan's Consumer Price Index (2010 = 100)
for the years 2010 to 2022 using the World Bank Open Data API.
The indicator used is FP.CPI.TOTL.
Usage
get_japan_cpi()
Details
The function sends a GET request to the World Bank API.
If the API request fails or returns an error status code, the function returns NULL with an informative message.
Value
A tibble with the following columns:
-  indicator: Indicator name (e.g., "Consumer price index (2010 = 100)")
-  country: Country name ("Japan")
-  year: Year of the data (integer)
-  value: Consumer Price Index value in numeric form
Note
Requires internet connection. The data is retrieved in real time from the World Bank API.
Source
World Bank Open Data API: https://data.worldbank.org/indicator/FP.CPI.TOTL
See Also
Examples
if (interactive()) {
  get_japan_cpi()
}
Get Japan's Energy Use (kg of oil equivalent per capita) from World Bank
Description
Retrieves Japan's energy use per capita, measured in kilograms of oil equivalent,
for the years 2010 to 2022 using the World Bank Open Data API.
The indicator used is EG.USE.PCAP.KG.OE.
Usage
get_japan_energy_use()
Details
This function sends a GET request to the World Bank API.
If the API request fails or returns an error status code,
the function returns NULL with an informative message.
Value
A tibble with the following columns:
-  indicator: Indicator name (e.g., "Energy use (kg of oil equivalent per capita)")
-  country: Country name ("Japan")
-  year: Year of the data (integer)
-  value: Energy use in kilograms of oil equivalent per capita
Note
Requires internet connection.
Source
World Bank Open Data API: https://data.worldbank.org/indicator/EG.USE.PCAP.KG.OE
See Also
Examples
if (interactive()) {
  get_japan_energy_use()
}
Get Japan's GDP (Current US$) from World Bank
Description
Retrieves Japan's Gross Domestic Product (GDP) in current US dollars
for the years 2010 to 2022 using the World Bank Open Data API.
The indicator used is NY.GDP.MKTP.CD.
Usage
get_japan_gdp()
Details
The function sends a GET request to the World Bank API.
If the API request fails or returns an error status code, the function returns NULL with an informative message.
Value
A tibble with the following columns:
-  indicator: Indicator name (e.g., "GDP (current US$)")
-  country: Country name ("Japan")
-  year: Year of the data (integer)
-  value: GDP value in numeric form
-  value_label: Formatted GDP value (e.g., "1,466,464,899,304")
Note
Requires internet connection. The data is retrieved in real time from the World Bank API.
Source
World Bank Open Data API: https://data.worldbank.org/indicator/NY.GDP.MKTP.CD
See Also
GET, fromJSON, as_tibble, comma
Examples
if (interactive()) {
  get_japan_gdp()
}
Get Official Public Holidays in Japan for a Given Year
Description
Retrieves the list of official public holidays in Japan for a specific year using the Nager.Date public holidays API. This function returns a tibble containing the date of the holiday, the name in the local language (Japanese), and the English name. It is useful for academic, planning, and data analysis purposes. The information is retrieved directly from the Nager.Date API and reflects the current status of holidays for the requested year. The field names returned are consistent with the API structure.
Usage
get_japan_holidays(year)
Arguments
| year | An integer indicating the year (e.g., 2024 or 2025). | 
Value
A tibble with the following columns:
-  date: Date of the holiday (classDate)
-  local_name: Holiday name in the local language (Japanese)
-  name: Holiday name in English
Source
Data obtained from the Nager.Date API: https://date.nager.at/
Examples
get_japan_holidays(2024)
get_japan_holidays(2025)
Get Hospital Beds per 1,000 People in Japan from World Bank
Description
Retrieves data on the number of hospital beds per 1,000 people in Japan
from 2010 to 2022 using the World Bank Open Data API.
The indicator used is SH.MED.BEDS.ZS.
Usage
get_japan_hospital_beds()
Details
This function sends a GET request to the World Bank API.
If the API request fails or returns an error status code,
the function returns NULL with an informative message.
Value
A tibble with the following columns:
-  indicator: Indicator name (e.g., "Hospital beds (per 1,000 people)")
-  country: Country name ("Japan")
-  year: Year of the data (integer)
-  value: Hospital beds per 1,000 people (numeric)
Note
Requires internet connection.
Source
World Bank Open Data API: https://data.worldbank.org/indicator/SH.MED.BEDS.ZS
See Also
Examples
if (interactive()) {
  get_japan_hospital_beds()
}
Get Japan's Life Expectancy at Birth from World Bank
Description
Retrieves Japan's life expectancy at birth (in years) for the years 2010 to 2022
using the World Bank Open Data API. The indicator used is SP.DYN.LE00.IN.
Usage
get_japan_life_expectancy()
Details
The function sends a GET request to the World Bank API.
If the API request fails or returns an error status code, the function returns NULL with an informative message.
Value
A tibble with the following columns:
-  indicator: Indicator name (e.g., "Life expectancy at birth, total (years)")
-  country: Country name ("Japan")
-  year: Year of the data (integer)
-  value: Life expectancy value in numeric form (years)
Note
Requires internet connection. The data is retrieved in real time from the World Bank API.
Source
World Bank Open Data API: https://data.worldbank.org/indicator/SP.DYN.LE00.IN
See Also
Examples
if (interactive()) {
  get_japan_life_expectancy()
}
Get Japan's Literacy Rate (Age 15+) from World Bank
Description
Retrieves Japan's literacy rate for adults aged 15 and above,
expressed as a percentage, for the years 2010 to 2022 using the World Bank Open Data API.
The indicator used is SE.ADT.LITR.ZS.
Usage
get_japan_literacy_rate()
Details
The function sends a GET request to the World Bank API.
If the API request fails or returns an error status code, the function returns NULL with an informative message.
Value
A tibble with the following columns:
-  indicator: Indicator name (e.g., "Literacy rate, adult total (
-  country: Country name ("Japan")
-  year: Year of the data (integer)
-  value: Literacy rate as numeric percentage
Note
Requires internet connection. The data is retrieved in real time from the World Bank API.
Source
World Bank Open Data API: https://data.worldbank.org/indicator/SE.ADT.LITR.ZS
See Also
Examples
if (interactive()) {
  get_japan_literacy_rate()
}
Get Japan's Total Population from World Bank
Description
Retrieves Japan's total population for the years 2010 to 2022
using the World Bank Open Data API. The indicator used is SP.POP.TOTL.
Usage
get_japan_population()
Details
The function sends a GET request to the World Bank API.
If the API request fails or returns an error status code, the function returns NULL with an informative message.
Value
A tibble with the following columns:
-  indicator: Indicator name (e.g., "Population, total")
-  country: Country name ("Japan")
-  year: Year of the data (integer)
-  value: Population as a numeric value
-  value_label: Formatted population with commas (e.g., "126,000,000")
Note
Requires internet connection. The data is retrieved in real time from the World Bank API.
Source
World Bank Open Data API: https://data.worldbank.org/indicator/SP.POP.TOTL
See Also
GET, fromJSON, as_tibble, comma
Examples
if (interactive()) {
  get_japan_population()
}
Get Japan's Unemployment Rate from World Bank
Description
Retrieves Japan's Unemployment, total (
for the years 2010 to 2022 using the World Bank Open Data API.
The indicator used is SL.UEM.TOTL.ZS.
Usage
get_japan_unemployment()
Details
The function sends a GET request to the World Bank API.
If the API request fails or returns an error status code, the function returns NULL with an informative message.
Value
A tibble with the following columns:
-  indicator: Indicator name (e.g., "Unemployment, total (
-  country: Country name ("Japan")
-  year: Year of the data (integer)
-  value: Unemployment rate as percentage in numeric form
Note
Requires internet connection. The data is retrieved in real time from the World Bank API.
Source
World Bank Open Data API: https://data.worldbank.org/indicator/SL.UEM.TOTL.ZS
See Also
Examples
if (interactive()) {
  get_japan_unemployment()
}
Hiroshima Atomic Bomb Survivors Cancer Data
Description
This dataset, hiroshima_tbl_df, is a tibble containing data on the number of deaths from leukemia and other cancers among survivors of the Hiroshima atom bomb. The data cover deaths that occurred during the period 1950–1959 among survivors who were aged 25 to 64 years in 1950.
Usage
data(hiroshima_tbl_df)
Format
A tibble with 6 observations and 4 variables:
- radiation
- Radiation exposure category (character) 
- leukemia
- Number of deaths from leukemia (numeric) 
- other cancer
- Number of deaths from other cancers (numeric) 
- total cancers
- Total number of cancer deaths (numeric) 
Details
The dataset name has been kept as 'hiroshima_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble object. The original content has not been modified in any way.
Source
Data taken from the dobson package version 0.4
Japan Birth Demographics
Description
This dataset, japan_birth_stats_tbl_df, is a tibble containing Japan’s birth-related demographic statistics from 1899 to 2022. The dataset includes birth counts by gender, birth rate, fertility rate, infant deaths, stillbirths, birth order, gestational weeks, average parental ages, and legitimacy of births. Some data are missing between the years 1944 and 1946 due to records lost during World War II. The dataset preserves the original structure from its source on Kaggle.
Usage
data(japan_birth_stats_tbl_df)
Format
A tibble with 124 observations and 51 variables:
- ...1
- Index column (numeric) 
- year
- Year of observation (numeric) 
- birth_total
- Total number of births (numeric) 
- birth_male
- Number of male births (numeric) 
- birth_female
- Number of female births (numeric) 
- birth_rate
- Birth rate per 1,000 population (numeric) 
- birth_gender_ratio
- Male to female birth ratio (numeric) 
- total_fertility_rate
- Total fertility rate (numeric) 
- population_total
- Total population (numeric) 
- population_male
- Male population (numeric) 
- population_female
- Female population (numeric) 
- infant_death_total
- Total number of infant deaths (numeric) 
- infant_death_male
- Number of male infant deaths (numeric) 
- infant_death_female
- Number of female infant deaths (numeric) 
- infant_death_unknown_gender
- Infant deaths with unknown gender (numeric) 
- infant_death_rate
- Infant mortality rate (numeric) 
- infant_death_gender_ratio
- Male to female infant death ratio (numeric) 
- infant_deaths_in_total_deaths
- Proportion of infant deaths in total deaths (numeric) 
- stillbirth_total
- Total number of stillbirths (numeric) 
- stillbirth_male
- Number of male stillbirths (numeric) 
- stillbirth_female
- Number of female stillbirths (numeric) 
- stillbirth_unknown_gender
- Stillbirths with unknown gender (numeric) 
- stillbirth_rate
- Stillbirth rate (numeric) 
- stillbirth_gender_ratio
- Male to female stillbirth ratio (numeric) 
- firstborn
- Number of firstborn children (numeric) 
- secondborn
- Number of secondborn children (numeric) 
- thirdborn
- Number of thirdborn children (numeric) 
- forthborn
- Number of fourthborn children (numeric) 
- fifthborn_and_above
- Number of fifthborn and above children (numeric) 
- weeks_under_28
- Births before 28 gestational weeks (numeric) 
- weeks_28-31
- Births between 28 and 31 gestational weeks (numeric) 
- weeks_32-36
- Births between 32 and 36 gestational weeks (numeric) 
- weeks_37-41
- Births between 37 and 41 gestational weeks (numeric) 
- weeks_over_42
- Births after 42 gestational weeks (numeric) 
- mother_age_avg
- Average age of mothers (numeric) 
- mother_age_firstborn
- Average age of mothers for firstborns (numeric) 
- mother_age_secondborn
- Average age of mothers for secondborns (numeric) 
- mother_age_thirdborn
- Average age of mothers for thirdborns (numeric) 
- mother_age_under_19
- Births to mothers under 19 years (numeric) 
- mother_age_20-24
- Births to mothers aged 20–24 (numeric) 
- mother_age_25-29
- Births to mothers aged 25–29 (numeric) 
- mother_age_30-34
- Births to mothers aged 30–34 (numeric) 
- mother_age_35-39
- Births to mothers aged 35–39 (numeric) 
- mother_age_40-44
- Births to mothers aged 40–44 (numeric) 
- mother_age_over_45
- Births to mothers over 45 years (numeric) 
- father_age_avg
- Average age of fathers (numeric) 
- father_age_firstborn
- Average age of fathers for firstborns (numeric) 
- father_age_secondborn
- Average age of fathers for secondborns (numeric) 
- father_age_thirdborn
- Average age of fathers for thirdborns (numeric) 
- legitimate_child
- Number of legitimate children (numeric) 
- illegitimate_child
- Number of illegitimate children (numeric) 
Details
The dataset name has been kept as 'japan_birth_stats_tbl_df' to maintain consistency with the naming conventions in the JapanAPIs package. The suffix 'tbl_df' indicates that this is a tibble data frame. The original content has not been modified in any way.
Source
Data obtained from Kaggle: https://www.kaggle.com/datasets/webdevbadger/japan-birth-statistics
Japan Population Data
Description
This dataset, japan_population_tbl_df, is a tibble containing Japan’s population over time and space. In this dataset you will find the raw population numbers for the prefectures, going as far back as the 1870s. The dataset preserves the original structure from its source on Kaggle.
Usage
data(japan_population_tbl_df)
Format
A tibble with 2,632 observations and 7 variables:
- prefecture
- Name of the prefecture (character) 
- year
- Year of the population observation (numeric) 
- population
- Total population in that year (numeric) 
- capital
- Name of the prefectural capital (character) 
- region
- Geographic region of the prefecture (character) 
- estimated_area
- Estimated area of the prefecture in square kilometers (numeric) 
- island
- Name of the island to which the prefecture belongs (character) 
Details
The dataset name has been kept as 'japan_population_tbl_df' to maintain consistency with the naming conventions in the JapanAPIs package. The suffix 'tbl_df' indicates that this is a tibble data frame. The original content has not been modified in any way.
Source
Data obtained from Kaggle: https://www.kaggle.com/datasets/jd1325/japan-population-data
Japanese Universities
Description
This dataset, japan_universities_tbl_df, is a tibble containing comprehensive data about 813 universities in Japan. It includes information such as the university name (in English and Japanese), location, type, year founded, number of faculties and departments, availability of graduate and remote programs, and difficulty and review metrics. The dataset preserves the original structure from its source on Kaggle.
Usage
data(japan_universities_tbl_df)
Format
A tibble with 813 observations and 22 variables:
- ...1
- Index column (numeric) 
- code
- University code (character) 
- name
- University name in English (character) 
- name_jp
- University name in Japanese (character) 
- type
- Type of university (e.g., Public, Private) (character) 
- type_jp
- Type of university in Japanese (character) 
- address
- Full address of the university (character) 
- postal_code
- Postal code (character) 
- phone
- Contact phone number (character) 
- state
- Name of the prefecture or region in English (character) 
- state_jp
- Name of the prefecture or region in Japanese (character) 
- latitude
- Latitude coordinate (numeric) 
- longitude
- Longitude coordinate (numeric) 
- found
- Year the university was founded (character) 
- faculty_count
- Number of faculties (numeric) 
- department_count
- Number of departments (numeric) 
- has_grad
- Whether the university has graduate programs (logical) 
- has_remote
- Whether the university offers remote programs (logical) 
- review_rating
- Average user review rating (numeric) 
- review_count
- Number of user reviews (numeric) 
- difficulty_SD
- Standard deviation of difficulty ratings (numeric) 
- difficulty_rank
- Relative difficulty rank (character) 
Details
The dataset name has been kept as 'japan_universities_tbl_df' to maintain consistency with the naming conventions in the JapanAPIs package. The suffix 'tbl_df' indicates that this is a tibble data frame. The original content has not been modified in any way.
Source
Data obtained from Kaggle: https://www.kaggle.com/datasets/webdevbadger/japanese-universities
Japanese Whisky Review Dataset
Description
This dataset, japanese_whisky_tbl_df, is a tibble containing over 1,000 reviews of Japanese whisky. The dataset includes the bottle name, brand, review title, and full review content. The dataset preserves the original structure from its source on Kaggle.
Usage
data(japanese_whisky_tbl_df)
Format
A tibble with 1,130 observations and 5 variables:
- ...1
- Index column (numeric) 
- Bottle_name
- Name of the whisky bottle (character) 
- Brand
- Brand of the whisky (character) 
- Title
- Title of the review (character) 
- Review_Content
- Full text content of the review (character) 
Details
The dataset name has been kept as 'japanese_whisky_tbl_df' to maintain consistency with the naming conventions in the JapanAPIs package. The suffix 'tbl_df' indicates that this is a tibble data frame. The original content has not been modified in any way.
Source
Data obtained from Kaggle: https://www.kaggle.com/datasets/koki25ando/japanese-whisky-review
Climate Stations in Japan
Description
This dataset, jpn_climate_stations_tbl_df, is a tibble containing information about 157 climate observation stations located across various regions and prefectures in Japan. It includes details such as station name, location, altitude, coordinates, and city information.
Usage
data(jpn_climate_stations_tbl_df)
Format
A tibble with 157 observations and 11 variables:
- region
- Geographical region where the station is located (character) 
- pref
- Prefecture name (character) 
- no
- Station number (character) 
- station
- Station name (character) 
- altitude
- Altitude of the station (character) 
- latitude
- Latitude coordinate (character) 
- longitude
- Longitude coordinate (character) 
- NS
- Latitude direction, North or South (character) 
- WE
- Longitude direction, West or East (character) 
- yomi
- Station name in Japanese phonetic script (character) 
- city
- City name (character) 
Details
The dataset name has been kept as 'jpn_climate_stations_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble object. The original content has not been modified in any way.
Source
Data taken from the clidatajp package version 0.5.2
Climate Data in Japan
Description
This dataset, jpn_climate_tbl_df, is a tibble containing climate data from various observation stations across Japan. It includes monthly data on temperature, precipitation, snowfall, solar insolation, and metadata such as station name, location, altitude, and coordinates.
Usage
data(jpn_climate_tbl_df)
Format
A tibble with 3,768 observations and 14 variables:
- no
- Observation number (numeric) 
- station
- Name of the weather station (character) 
- month
- Month of observation (numeric) 
- temperature
- Average temperature (numeric) 
- precipitation
- Monthly precipitation (numeric) 
- snowfall
- Monthly snowfall (numeric) 
- insolation
- Monthly solar insolation (numeric) 
- country
- Country name (character) 
- period
- Measurement period or time range (character) 
- altitude
- Altitude of the station (numeric) 
- latitude
- Latitude coordinate (numeric) 
- longitude
- Longitude coordinate (numeric) 
- NS
- Latitude direction, North or South (character) 
- WE
- Longitude direction, West or East (character) 
Details
The dataset name has been kept as 'jpn_climate_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble object. The original content has not been modified in any way.
Source
Data taken from the clidatajp package version 0.5.2
July 26, 2003 N. Miyagi Earthquake Aftershocks
Description
This dataset, jpn_eq_miyagi_2003_df, is a data frame containing aftershock data from the earthquake of magnitude 6.2 that occurred on 26th July 2003 in northern Miyagi-Ken, Japan. It includes information on the time of occurrence, geographic coordinates, depth, and magnitude of each aftershock event.
Usage
data(jpn_eq_miyagi_2003_df)
Format
A data frame with 2305 observations and 5 variables:
- time
- Time of aftershock event (numeric) 
- longitude
- Longitude coordinate (numeric) 
- latitude
- Latitude coordinate (numeric) 
- depth
- Depth in kilometers (numeric) 
- magnitude
- Magnitude of the aftershock (numeric) 
Details
The dataset name has been kept as 'jpn_eq_miyagi_2003_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.
Source
Data taken from the mmpp package version 0.6
Household Consumption and GDP in Japan (1978–2007)
Description
This dataset, jpn_gdp_cons_df, is a data frame containing information on Household Consumption (C) and Gross Domestic Product (GDP, denoted as Y) in Japan from 1978 to 2007. The data is useful for analyzing structural breaks under heteroskedasticity.
Usage
data(jpn_gdp_cons_df)
Format
A data frame with 30 observations and 3 variables:
- Year
- Calendar year (integer) 
- C
- Household Consumption (integer) 
- Y
- Gross Domestic Product (GDP) (integer) 
Details
The dataset name has been kept as 'jpn_gdp_cons_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.
Source
Data taken from the SupMZ package version 0.2.0
Half-Caste Manga Characters
Description
This dataset, jpn_manga_hafu_df, is a data frame containing information on half-caste manga characters. It includes attributes such as the year of publication, manga series, character name, gender, parental origin, and physical traits like eye and hair color.
Usage
data(jpn_manga_hafu_df)
Format
A data frame with 296 observations and 9 variables:
- Year
- Year of publication (integer) 
- Series
- Manga series name (factor) 
- Character
- Character name (factor) 
- Gender
- Gender of the character (factor) 
- Father
- Father's origin (factor) 
- Mother
- Mother's origin (factor) 
- Eyes
- Eye color (factor) 
- Hair
- Hair color (factor) 
- Notes
- Additional notes about the character (factor) 
Details
The dataset name has been kept as 'jpn_manga_hafu_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.
Source
Data taken from the learningr package version 0.29.1
Japan Prefectures 7x7 Grid Dataset
Description
This dataset, jpn_prefectures_tbl_df, is a tibble representing Japan’s 47 prefectures arranged in a 7x7 grid layout. It includes prefectural codes, names in both romaji and kanji, regions, major islands, and grid coordinates.
Usage
data(jpn_prefectures_tbl_df)
Format
A tibble with 47 observations and 8 variables:
- jis_code
- JIS code of the prefecture (character) 
- prefecture
- Prefectural name in romaji (character) 
- region
- Geographical region of the prefecture (factor) 
- major_island
- Major island the prefecture belongs to (character) 
- prefecture_kanji
- Prefectural name in kanji (character) 
- region_kanji
- Region name in kanji (factor) 
- x
- X coordinate for grid placement (integer) 
- y
- Y coordinate for grid placement (integer) 
Details
The dataset name has been kept as 'jpn_prefectures_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble object. The original content has not been modified in any way.
Source
Data taken from the tabularmaps package version 0.1.0
Suicides in Japan by Sex and Age (1978–2022)
Description
This dataset, jpn_suicides_tbl_df, is a tibble containing the number of suicides in Japan from 1978 to 2022 by sex and age group. The dataset includes suicide counts for males and females, overall suicide rates, and counts by specific age ranges. The dataset preserves the original structure from its source on Kaggle.
Usage
data(jpn_suicides_tbl_df)
Format
A tibble with 45 observations and 14 variables:
- year
- Year of observation (numeric) 
- num_suicide_male
- Number of male suicides (numeric) 
- num_suicide_female
- Number of female suicides (numeric) 
- suicide_rate
- Overall suicide rate (numeric) 
- suicide_rate_male
- Suicide rate among males (numeric) 
- suicide_rate_female
- Suicide rate among females (numeric) 
- num_suicide_age_0_19
- Number of suicides aged 0–19 (numeric) 
- num_suicide_age_20_29
- Number of suicides aged 20–29 (numeric) 
- num_suicide_age_30_39
- Number of suicides aged 30–39 (numeric) 
- num_suicide_age_40_49
- Number of suicides aged 40–49 (numeric) 
- num_suicide_age_50_59
- Number of suicides aged 50–59 (numeric) 
- num_suicide_60_plus
- Number of suicides aged 60 and above (numeric) 
- num_suicide_age_unknown
- Number of suicides with unknown age (numeric) 
- num_suicide_total
- Total number of suicides (numeric) 
Details
The dataset name has been kept as 'jpn_suicides_tbl_df' to maintain consistency with the naming conventions in the JapanAPIs package. The suffix 'tbl_df' indicates that this is a tibble data frame. The original content has not been modified in any way.
Source
Data obtained from Kaggle: https://www.kaggle.com/datasets/krisztinboros/suicides-in-japan-by-sex-and-age-19782021
Attributes of Some US and Japanese Automobiles
Description
This dataset, jpn_us_cars_df, is a data frame containing information on 45 automobiles from the United States and Japan. It includes attributes such as model name, country of origin, mileage, and price.
Usage
data(jpn_us_cars_df)
Format
A data frame with 45 observations and 4 variables:
- Model
- Car model (factor) 
- Country
- Country of origin (factor) 
- Mileage
- Mileage in miles per gallon (integer) 
- Price
- Price in US dollars (integer) 
Details
The dataset name has been kept as 'jpn_us_cars_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.
Source
Data taken from the fma package version 2.5
Yen-Dollar Exchange Rate (Weekly, 1975–1989)
Description
This dataset, jpn_usd_exchange_df, is a data frame containing weekly observations of the yen-dollar exchange rate from 1975 to 1989. It includes spot and forward rates, along with 30-day forward rates.
Usage
data(jpn_usd_exchange_df)
Format
A data frame with 778 observations and 4 variables:
- date
- Time index of the observation (integer) 
- s
- Spot exchange rate (numeric) 
- f
- Forward exchange rate (numeric) 
- s30
- 30-day forward exchange rate (numeric) 
Details
The dataset name has been kept as 'jpn_usd_exchange_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.
Source
Data taken from the Ecdat package version 0.4-2
Japanese Motor Vehicle Production (1947–1989)
Description
This dataset, jpn_vehicle_prod_ts, is a univariate time series containing the number of motor vehicles produced in Japan from 1947 to 1989. The figures are recorded annually and expressed in thousands.
Usage
data(jpn_vehicle_prod_ts)
Format
A univariate time series with 43 observations:
- Time
- Yearly observations from 1947 to 1989 
- Values
- Motor vehicle production in Japan (in thousands) 
Details
The dataset name has been kept as 'jpn_vehicle_prod_ts' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'ts' indicates that the dataset is a time series object. The original content has not been modified in any way.
Source
Data taken from the fma package version 2.5
Prefectural Informations in Japan
Description
This dataset, jpnprefs_tbl_df, is a tibble containing information about the 47 prefectures of Japan. It includes details such as prefectural names in kanji and romaji, corresponding JIS codes, the region each prefecture belongs to, and the major island associated with each.
Usage
data(jpnprefs_tbl_df)
Format
A tibble with 47 observations and 5 variables:
- jis_code
- JIS code of the prefecture (character) 
- prefecture_kanji
- Prefectural name in kanji (character) 
- prefecture
- Prefectural name in romaji (character) 
- region
- Geographical region of the prefecture (character) 
- major_island
- Major island the prefecture belongs to (character) 
Details
The dataset name has been kept as 'jpnprefs_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble object. The original content has not been modified in any way.
Source
Data taken from the zipangu package version 0.3.3
1995 Kobe Earthquake Data
Description
This dataset, 'kobe_quake_1995_ts', is a time series containing data related to the 1995 Kobe earthquake. The data are organized sequentially with a frequency of 1, and consist of 3,048 observations.
Usage
data(kobe_quake_1995_ts)
Format
A time series with 3,048 observations:
- observations
- Time series data related to the 1995 Kobe earthquake (numeric) 
Details
The dataset name has been kept as 'kobe_quake_1995_ts' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'ts' indicates that the dataset is a time series object. The original content has not been modified in any way.
Source
Data taken from the waveslim package version 1.8.5
Kojima Hideo Tweets (Japanese)
Description
This dataset, kojima_tweets_tbl_df, is a tibble containing 454 original tweets from Hideo Kojima, posted between November 17, 2019, and January 6, 2020. Retweets are excluded. The dataset includes tweet text, engagement metrics, tweet metadata, user handle information, geolocation data, hashtags, mentions, URLs, and media details. The dataset preserves the original structure from its source on Kaggle.
Usage
data(kojima_tweets_tbl_df)
Format
A tibble with 454 observations and 41 variables:
- Tweet
- Text content of the tweet (character) 
- Created Date
- Date when the tweet was created (character) 
- Retweets
- Number of retweets (numeric) 
- Favourites
- Number of likes (numeric) 
- Engagement
- Sum of retweets and likes (numeric) 
- No of Hashtags
- Count of hashtags used (numeric) 
- No of User Mentions
- Count of user mentions (numeric) 
- No of URLS added
- Count of URLs included (numeric) 
- No of Media added
- Count of media elements attached (numeric) 
- Tweeted Username
- Username who posted the tweet (character) 
- Replied To Username
- Whether it was a reply to another user (logical) 
- Post Type
- Type of post (e.g., tweet, reply, etc.) (character) 
- Media Type
- Type of media included (e.g., photo, video) (character) 
- Is Quote Tweet
- Whether the tweet is a quote (character) 
- Is Retweeted
- Whether the tweet is a retweet (character) 
- Language (Tweets)
- Language of the tweet content (character) 
- Country
- Country information if available (logical) 
- Location (Tweets)
- Geolocation as specified in the tweet (logical) 
- Location Full Name
- Full name of the location (logical) 
- Location Type
- Type of location (logical) 
- Hashtags
- Hashtags used in the tweet (character) 
- User Mentions
- User mentions in the tweet (character) 
- URLS Used
- URLs present in the tweet (character) 
- Media URLS
- Media URLs attached to the tweet (character) 
- Name
- Name associated with the Twitter account (character) 
- Username
- Handle of the Twitter account (character) 
- Created Date (Handles)
- Date when the Twitter account was created (character) 
- Language (Handles)
- Preferred language of the account (character) 
- Tweets
- Total number of tweets from the account (numeric) 
- Followers
- Number of followers (numeric) 
- Friends
- Number of accounts followed (numeric) 
- Favourites (Handles)
- Total number of liked tweets by the account (numeric) 
- Listed Count
- Number of lists the account is included in (numeric) 
- Location (Handles)
- Location listed in the user profile (character) 
- Protected
- Whether the account is protected (character) 
- Verified
- Whether the account is verified (character) 
- URL
- URL included in the profile (character) 
- Description
- Profile description or bio (character) 
- Profile Image URL
- URL of the profile image (character) 
- Account Age in Days
- Age of the account in days (numeric) 
- Avg Tweets per day
- Average tweets per day (numeric) 
Details
The dataset name has been kept as 'kojima_tweets_tbl_df' to maintain consistency with the naming conventions in the JapanAPIs package. The suffix 'tbl_df' indicates that this is a tibble data frame. The original content has not been modified in any way.
Source
Data obtained from Kaggle: https://www.kaggle.com/datasets/luciesteel/kojima-tweets
Japan Life Expectancy and Socioeconomic Indicators (2020)
Description
This dataset, life_exp_japan_tbl_df, is a tibble containing life expectancy and related economic and social indicators for Japan's 47 prefectures as of 2020. It includes variables on healthcare infrastructure, education levels, income, public spending, and environmental indicators. The dataset preserves the original structure from its source on Kaggle.
Usage
data(life_exp_japan_tbl_df)
Format
A tibble with 47 observations and 23 variables:
- Prefecture
- Name of the Japanese prefecture (character) 
- Life_expectancy
- Average life expectancy (numeric) 
- Physician
- Number of physicians per 100,000 people (numeric) 
- Junior_col
- Number of junior colleges (numeric) 
- University
- Number of universities (numeric) 
- Public_Hosp
- Number of public hospitals (numeric) 
- Pshic_hosp
- Number of psychiatric hospitals (numeric) 
- Beds_psic
- Number of psychiatric hospital beds (numeric) 
- Nurses
- Number of nurses per 100,000 people (numeric) 
- Avg_hours
- Average weekly working hours (numeric) 
- Salary
- Average annual salary (numeric) 
- Elementary_school
- Number of elementary schools (numeric) 
- Sport_fac
- Number of sports facilities (numeric) 
- Park
- Number of parks (numeric) 
- Forest
- Percentage of forest area (numeric) 
- Income_per capita
- Per capita income (numeric) 
- Density_pop
- Population density (people per km²) (numeric) 
- Hospitals
- Total number of hospitals (numeric) 
- Beds
- Total number of hospital beds (numeric) 
- Ambulances
- Number of ambulances (numeric) 
- Health_exp
- Health expenditure per capita (numeric) 
- Educ_exp
- Education expenditure per capita (numeric) 
- Welfare_exp
- Welfare expenditure per capita (numeric) 
Details
The dataset name has been kept as 'life_exp_japan_tbl_df' to maintain consistency with the naming conventions in the JapanAPIs package. The suffix 'tbl_df' indicates that this is a tibble data frame. The original content has not been modified in any way.
Source
Data obtained from Kaggle: https://www.kaggle.com/datasets/gianinamariapetrascu/japan-life-expectancy
Japanese NIKKEI Stock Index
Description
This dataset, nikkei_stock_index_df, is a data frame containing the daily log returns in percent of the NIKKEI stock index for the period from 1984-01-04 to 2000-12-22.
Usage
data(nikkei_stock_index_df)
Format
A data frame with 4,246 observations and 2 variables:
- index
- Date or index label (character) 
- value
- Daily log return in percent (numeric) 
Details
The dataset name has been kept as 'nikkei_stock_index_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.
Source
Data taken from the tsgarch package version 1.0.3
Taste Ratings of Japanese Rice Wine (Sake)
Description
This dataset, sake_ratings_df, is a data frame containing data from a study of Japanese rice wine (sake), used to investigate the relationship between two subjective ratings (taste and smell) and a number of physical measurements on 30 brands of sake.
Usage
data(sake_ratings_df)
Format
A data frame with 30 observations and 10 variables:
- taste
- Subjective taste rating (numeric) 
- smell
- Subjective smell rating (numeric) 
- pH
- pH level (numeric) 
- acidity1
- Acidity measure 1 (numeric) 
- acidity2
- Acidity measure 2 (numeric) 
- sake
- Sake meter value (numeric) 
- rsugar
- Reducing sugar content (numeric) 
- tsugar
- Total sugar content (numeric) 
- alcohol
- Alcohol content (numeric) 
- nitrogen
- Nitrogen content (numeric) 
Details
The dataset name has been kept as 'sake_ratings_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.
Source
Data taken from the heplots package version 1.7.0
The Seishu Wine Study
Description
This dataset, seishu_wine_df, is a data frame containing data from a study on wine. The study records the odor and taste of wines, with the aim of explaining these characteristics through various chemical properties such as pH concentration, alcohol content, total sugar, and others.
Usage
data(seishu_wine_df)
Format
A data frame with 30 observations and 10 variables:
- Taste
- Taste rating of the wine (numeric) 
- Odor
- Odor rating of the wine (numeric) 
- pH
- pH concentration (numeric) 
- Acidity_1
- First acidity measurement (numeric) 
- Acidity_2
- Second acidity measurement (numeric) 
- Sake_meter
- Sake meter value (numeric) 
- Direct_reducing_sugar
- Direct reducing sugar content (numeric) 
- Total_sugar
- Total sugar content (numeric) 
- Alcohol
- Alcohol content (numeric) 
- Formyl_nitrogen
- Formyl nitrogen content (numeric) 
Details
The dataset name has been kept as 'seishu_wine_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.
Source
Data taken from the ACSWR package version 1.0
Shinkansen Stations in Japan
Description
This dataset, shinkansen_stations_tbl_df, is a tibble containing information about 113 Shinkansen train stations across Japan. Each row represents a station and includes its name, the Shinkansen line it belongs to, the year it opened, the prefecture it is located in, the distance from Tokyo Station in kilometers, and the operating company. The dataset preserves the original structure from its source on Kaggle.
Usage
data(shinkansen_stations_tbl_df)
Format
A tibble with 113 observations and 6 variables:
- Station_Name
- Name of the Shinkansen station (character) 
- Shinkansen_Line
- Name of the Shinkansen line (character) 
- Year
- Year the station opened (numeric) 
- Prefecture
- Prefecture in which the station is located (character) 
- Distance from Tokyo st
- Distance from Tokyo Station in kilometers (numeric) 
- Company
- Operating company of the station (character) 
Details
The dataset name has been kept as 'shinkansen_stations_tbl_df' to maintain consistency with the naming conventions in the JapanAPIs package. The suffix 'tbl_df' indicates that this is a tibble data frame. The original content has not been modified in any way.
Source
Data obtained from Kaggle: https://www.kaggle.com/datasets/japandata509/shinkansen-stations-in-japan
East Japan Railway's Tokaido Line Stations
Description
This dataset, tokaido_stations_tbl_df, is a tibble containing information about stations on the Tokaido Line operated by East Japan Railway. It includes each station's code and name.
Usage
data(tokaido_stations_tbl_df)
Format
A tibble with 20 observations and 2 variables:
- st_code
- Station code (character) 
- st_name
- Station name (character) 
Details
The dataset name has been kept as 'tokaido_stations_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble object. The original content has not been modified in any way.
Source
Data taken from the ssrn package version 0.1.0
Tokyo Rainfall Data
Description
This dataset, tokyo_rainfall_vec, is a numeric vector containing Tokyo rainfall data from Kitagawa (1987), analysed also by Rue and Held (2005) and Fahrmeir and Tutz (2013). It includes daily rainfall measurements over a period of 366 days.
Usage
data(tokyo_rainfall_vec)
Format
A numeric vector with 366 observations:
Daily rainfall measurements (numeric values ranging from 0 to 2)
Details
The dataset name has been kept as 'tokyo_rainfall_vec' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'vec' indicates that the dataset is a vector object. The original content has not been modified in any way.
Source
Data taken from the gamlss.data package version 6.0-6
Special Wards of Tokyo
Description
This dataset, tokyo_wards_tbl_df, is a tibble containing information on the 23 special wards of Tokyo. It includes ward numbers, names in both romaji and kanji, along with x and y coordinates for spatial layout.
Usage
data(tokyo_wards_tbl_df)
Format
A tibble with 23 observations and 5 variables:
- no
- Ward number (character) 
- ward
- Ward name in romaji (character) 
- ward_kanji
- Ward name in kanji (character) 
- x
- X coordinate for grid placement (numeric) 
- y
- Y coordinate for grid placement (numeric) 
Details
The dataset name has been kept as 'tokyo_wards_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble object. The original content has not been modified in any way.
Source
Data taken from the tabularmaps package version 0.1.0
Toyota Stock Prices
Description
This dataset, toyota_stock_prices_df, is a data frame containing the average monthly stock prices of Toyota from 1982 to 1998.
Usage
data(toyota_stock_prices_df)
Format
A data frame with 255 observations and 2 variables:
- Month
- Month number from the beginning of the time series (integer) 
- Value
- Average monthly stock price (numeric) 
Details
The dataset name has been kept as 'toyota_stock_prices_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the JapanAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.
Source
Data taken from the MMAC package version 0.1.2
View Available Datasets in JapanAPIs
Description
This function lists all datasets available in the 'JapanAPIs' package. If the 'JapanAPIs' package is not loaded, it stops and shows an error message. If no datasets are available, it returns a message and an empty vector.
Usage
view_datasets_JapanAPIs()
Value
A character vector with the names of the available datasets. If no datasets are found, it returns an empty character vector.
Examples
if (requireNamespace("JapanAPIs", quietly = TRUE)) {
  library(JapanAPIs)
  view_datasets_JapanAPIs()
}