Type: Package
Title: Access Indian 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 'World Bank API', and 'REST Countries API', retrieving real-time or historical data related to India, such as economic indicators, and international demographic and geopolitical indicators. Additionally, the package includes one of the largest curated collections of open datasets focused on India, covering topics such as population, economy, weather, politics, health, biodiversity, sports, agriculture, cybercrime, infrastructure, and more. 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: 'World Bank API' https://datahelpdesk.worldbank.org/knowledgebase/articles/889392, 'REST Countries API' https://restcountries.com/.
License: MIT + file LICENSE
Language: en
URL: https://github.com/lightbluetitan/indiapis, https://lightbluetitan.github.io/indiapis/
BugReports: https://github.com/lightbluetitan/indiapis/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: 2025-08-20 19:22:31 UTC; Renzo
Author: Renzo Caceres Rossi ORCID iD [aut, cre]
Repository: CRAN
Date/Publication: 2025-08-26 14:10:15 UTC

IndiAPIs: Access Indian Data via Public APIs and Curated Datasets

Description

This package provides functions to access data from public RESTful APIs including 'World Bank API', and 'REST Countries API', retrieving real-time or historical data related to India, such as economic indicators, and international demographic and geopolitical indicators. Additionally, the package includes one of the largest curated collections of open datasets focused on India, covering topics such as population, economy, weather, politics, health, biodiversity, sports, agriculture, cybercrime, infrastructure, and more.

Details

IndiAPIs: Access Indian Data via Public APIs and Curated Datasets

logo

Access Indian Data via Public APIs and Curated Datasets.

Author(s)

Maintainer: Renzo Caceres Rossi arenzocaceresrossi@gmail.com

See Also

Useful links:

Changes in Human Birth and Death Rates in India Over the 20th Century

Description

This dataset, BirthDeathRates_df, is a data frame containing data on human birth and death rates in India over the 20th century. It includes the year, birth rate, and death rate for each recorded period.

Usage

data(BirthDeathRates_df)

Format

A data frame with 27 observations and 3 variables:

Year

Year of observation (factor)

Birth.rate

Birth rate (numeric)

death.rate

Death rate (numeric)

Details

The dataset name has been kept as 'BirthDeathRates_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the IndiAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame object. The original content has not been modified in any way.

Source

Data taken from the gpk package version 1.0

Weekly deaths from bubonic plague in Bombay in 1905-06

Description

This dataset, BombayPlague1905_df, is a data frame containing the number of plague deaths per week in Bombay in 1905–06. The data was originally reported by Kermack and McCormick (1927). Bombay is the former name for the Indian coastal city Mumbai, which is the capital of Maharashtra and one of the largest cities in the world.

Usage

data(BombayPlague1905_df)

Format

A data frame with 32 observations and 2 variables:

Week

Week number of the observation period (integer)

CumulativeDeaths

Cumulative number of plague deaths (integer)

Details

The dataset name has been kept as 'BombayPlague1905_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the IndiAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame object. The original content has not been modified in any way.

Source

Data taken from the primer package version 1.2.0

Yearly Rice Yield Data in Burdwan District, West Bengal

Description

This dataset, BurdwanRiceYield_df, is a data frame containing yearly rice yield data for the Burdwan district of West Bengal, India, over a period of 39 years. It includes the year and the yield in tonnes per hectare for each recorded year.

Usage

data(BurdwanRiceYield_df)

Format

A data frame with 39 observations and 2 variables:

Year

Year of observation (character)

burdwan

Rice yield in tonnes per hectare (numeric)

Details

The dataset name has been kept as 'BurdwanRiceYield_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the IndiAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame object. The original content has not been modified in any way.

Source

Data taken from the weatherindices package version 0.1.0

Weekly Weather Data for Rice Growing Season in Burdwan District

Description

This dataset, BurdwanWeather_df, is a data frame containing weekly weather data for the rice growing season in the Burdwan district of West Bengal, India, over a period of 39 years. It includes the date, standard meteorological week, week number, and four weather variables: maximum temperature, minimum temperature, precipitation, and relative humidity.

Usage

data(BurdwanWeather_df)

Format

A data frame with 741 observations and 7 variables:

Date

Date of observation (character)

SMW

Standard Meteorological Week (integer)

Week

Week number within the season (integer)

Max.Temperature

Maximum temperature in degrees Celsius (numeric)

Min.Temperature

Minimum temperature in degrees Celsius (numeric)

Precipitation

Total precipitation in millimeters (numeric)

Relative.Humidity

Relative humidity in percentage (numeric)

Details

The dataset name has been kept as 'BurdwanWeather_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the IndiAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame object. The original content has not been modified in any way.

Source

Data taken from the weatherindices package version 0.1.0

Distribution of Butterfly Species in India

Description

This dataset, ButterflySpecies_df, is a data frame containing the distribution of butterfly species counts among five groups across different localities in India. It includes information on the total number of species and counts for each butterfly group such as Skippers, Swallow tails, Whites & Yellows, Blues, and Brush Footed.

Usage

data(ButterflySpecies_df)

Format

A data frame with 44 observations and 9 variables:

Serial_Number

Serial number identifier (integer)

Area

Geographic area within India (factor with 8 levels)

Locality

Specific locality name (factor with 44 levels)

Total_Species_count

Total number of butterfly species in the locality (integer)

Skippers

Count of Skippers species (integer)

Swallow_tails

Count of Swallow tail species (integer)

Whites_Yellows

Count of Whites and Yellows species (integer)

Blues

Count of Blues species (integer)

Brush_Footed

Count of Brush Footed species (integer)

Details

The dataset name has been kept as 'ButterflySpecies_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the IndiAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame object. The original content has not been modified in any way.

Source

Data taken from the gpk package version 1.0

CyberCrime in India

Description

This dataset, CyberCrime_India_tbl_df, is a tibble containing cybercrime statistics across Indian cities. It includes counts of various types of cybercrimes such as personal revenge, anger, fraud, extortion, causing disrepute, prank, sexual exploitation, disruption of public service, illegal drug sales, business development, piracy spreading, psychological offenses, information theft, abetment to suicide, and others, along with the total number of cases. The dataset preserves the original structure from its source on Kaggle.

Usage

data(CyberCrime_India_tbl_df)

Format

A tibble with 191 observations and 17 variables:

City

City name (character)

Personal Revenge

Number of cybercrime cases related to personal revenge (numeric)

Anger

Number of cybercrime cases related to anger (numeric)

Fraud

Number of fraud-related cybercrime cases (numeric)

Extortion

Number of extortion-related cybercrime cases (numeric)

Causing Disrepute

Number of cases causing disrepute (numeric)

Prank

Number of prank-related cybercrime cases (numeric)

Sexual Exploitation

Number of sexual exploitation cases (numeric)

Disrupt Public Service

Number of cases disrupting public services (numeric)

Sale purchase illegal drugs

Number of cases involving sale or purchase of illegal drugs (numeric)

Developing own business

Number of cases related to developing own business (numeric)

Spreading Piracy

Number of cases involving spreading piracy (numeric)

Psycho or Pervert

Number of psychological or pervert-related cases (numeric)

Steal Information

Number of information theft cases (numeric)

Abetment to Suicide

Number of cases of abetment to suicide (numeric)

Others

Number of other types of cybercrime cases (numeric)

Total

Total number of cybercrime cases (numeric)

Details

The dataset name has been kept as 'CyberCrime_India_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/seanangelonathanael/dataset-cybercrime-in-india

Data Science Jobs in India

Description

This dataset, DataScienceJobs_tbl_df, is a tibble containing job listings related to Data Science positions across India. It includes company names, job titles, minimum experience required, average, minimum and maximum salaries, and the number of salary reports. The dataset preserves the original structure from its source on Kaggle.

Usage

data(DataScienceJobs_tbl_df)

Format

A tibble with 1,602 observations and 8 variables:

...1

Original column from the source file (numeric)

company_name

Name of the company offering the job (character)

job_title

Title of the job position (character)

min_experience

Minimum experience required in years (numeric)

avg_salary

Average salary offered (numeric)

min_salary

Minimum salary offered (numeric)

max_salary

Maximum salary offered (numeric)

num_of_salaries

Number of salary reports for the job (numeric)

Details

The dataset name has been kept as 'DataScienceJobs_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/madhurpant/data-science-jobs-in-india

Monthly Average Potato Price of Delhi Market (India)

Description

This dataset, DelhiPotatoPrices_ts, is a time series containing the monthly average potato prices of the Delhi market from January 2010 to July 2020.

Usage

data(DelhiPotatoPrices_ts)

Format

A time series with 127 time points and 1 variable:

Delhi

Monthly average potato price in the Delhi market (numeric)

Details

The dataset name has been kept as 'DelhiPotatoPrices_ts' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the IndiAPIs 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 stlELM package version 0.1.1

India GDP (1960-2022)

Description

This dataset, GDPIndia_tbl_df, is a tibble containing historical GDP data for India from 1960 to 2022. It includes columns as present in the original source file, preserving their exact names and formats. The dataset preserves the original structure from its source on Kaggle.

Usage

data(GDPIndia_tbl_df)

Format

A tibble with 63 observations and 5 variables:

...1

Original column from the source file (numeric)

India GDP - Historical Data...2

Original column from the source file (character)

India GDP - Historical Data...3

Original column from the source file (character)

India GDP - Historical Data...4

Original column from the source file (character)

India GDP - Historical Data...5

Original column from the source file (character)

Details

The dataset name has been kept as 'GDPIndia_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/dheerajmukati/india-gdp-19602022

Gold Prices Across Six Indian Cities from February 2022 to January 2023

Description

This dataset, GoldPricesIndia_df, is a data frame containing the monthly high and low prices (in rupees per gram) of 22-carat gold in six Indian cities: Chennai, Kolkatta, Bangalore, Madurai, Hyderabad, and Delhi. Data were collected from February 2022 to January 2023.

Usage

data(GoldPricesIndia_df)

Format

A data frame with 12 observations and 13 variables:

Month

Month of observation (character)

Chennai_Low

Lowest price in Chennai (numeric)

Chennai_High

Highest price in Chennai (numeric)

Kolkatta_Low

Lowest price in Kolkatta (numeric)

Kolkatta_High

Highest price in Kolkatta (numeric)

Bangalore_Low

Lowest price in Bangalore (numeric)

Bangalore_High

Highest price in Bangalore (numeric)

Madurai_Low

Lowest price in Madurai (numeric)

Madurai_High

Highest price in Madurai (numeric)

Hyderabad_Low

Lowest price in Hyderabad (numeric)

Hyderabad_High

Highest price in Hyderabad (numeric)

Delhi_Low

Lowest price in Delhi (numeric)

Delhi_High

Highest price in Delhi (numeric)

Details

The dataset name has been kept as 'GoldPricesIndia_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the IndiAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame object. The original content has not been modified in any way.

Source

Data taken from the neutrostat package version 0.0.2

Cricket data set for different seasons of Indian Premier League

Description

This dataset, IPLCricket_tbl_df, is a tibble containing match data from the Indian Premier League (IPL) played by teams representing different cities in India from 2008 to 2016.

Usage

data(IPLCricket_tbl_df)

Format

A tibble with 8,560 observations and 10 variables:

season

Season year of the IPL (numeric)

match_id

Unique match identifier (numeric)

batting_team

Name of the batting team (character)

bowling_team

Name of the bowling team (character)

inning

Inning number (numeric)

over

Over number (numeric)

wicket

Number of wickets taken in the over (numeric)

dot_balls

Number of dot balls in the over (numeric)

runs_per_over

Runs scored in the over (numeric)

run_rate

Run rate for the over (numeric)

Details

The dataset name has been kept as 'IPLCricket_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the IndiAPIs 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 gravitas package version 0.1.3

Politics and Land Reforms in India

Description

This dataset, IndiaLandReforms_df, is a data frame containing information on politics and land reforms in India. It includes variables related to agricultural landholding patterns, rural development indicators, election outcomes, political participation, and socio-economic measures across different districts and years.

Usage

data(IndiaLandReforms_df)

Format

A data frame with 2670 observations and 32 variables:

mouza

Mouza code or identifier (integer)

year

Year of observation (integer)

district

District code or identifier (integer)

rplacul

Proportion of land cultivated (numeric)

rpdrhh

Proportion of rural households (numeric)

rblacul

Proportion of land below a certain threshold (numeric)

rbgdrrghh

Proportion of rural households with a given characteristic (numeric)

election

Election year indicator (integer)

preelect

Pre-election indicator (integer)

edwalfco

Electoral variable - women in local councils (numeric)

erlesscu

Electoral variable - less cultivated land (numeric)

ermgcu

Electoral variable - medium cultivated land (numeric)

ersmcu

Electoral variable - small cultivated land (numeric)

ermdcu

Electoral variable - medium developed cultivated land (numeric)

ercusmol

Electoral variable - custom smallholder measure (numeric)

ercubgol

Electoral variable - custom big landholder measure (numeric)

erillnb

Electoral variable - illiteracy rate (numeric)

erlow

Electoral variable - low-income households (numeric)

ratleft0

Political variable - left party ratio before adjustment (numeric)

dwalfco

Development variable - women in local councils (numeric)

inflat

Inflation rate (numeric)

smfempyv

Share of female employment in youth (numeric)

incseats

Number of seats won by incumbents (numeric)

lfseats

Number of seats won by left parties (numeric)

inflflag

Inflation flag indicator (numeric)

inclflag

Incumbent flag indicator (numeric)

lflflag

Left party flag indicator (numeric)

ratleft

Political variable - left party ratio (numeric)

infiw

Inflation index for wages (numeric)

infumme

Inflation index for unspecified metric (numeric)

infal

Inflation index for agricultural labor (numeric)

gp

Gram Panchayat code or identifier (integer)

Details

The dataset name has been kept as 'IndiaLandReforms_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the IndiAPIs package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame object. The original content has not been modified in any way.

Source

Data taken from the pder package version 1.0-2

List of places, abbreviations, and populations in India

Description

This dataset, IndiaPopulation_dt, is a data table containing the names of states and union territories in India along with their respective abbreviations and populations. The dataset also includes the total population of India. These are 2019 projections as reported in the Unique Identification Authority of India 2019-2020 Annual Report.

Usage

data(IndiaPopulation_dt)

Format

A data.table with 39 observations and 3 variables:

place

Name of the state or union territory (character)

abbrev

Abbreviation for the state or union territory (character)

population

Population in 2019 projection (numeric)

Details

The dataset name has been kept as 'IndiaPopulation_dt' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the IndiAPIs package and assists users in identifying its specific characteristics. The suffix 'dt' indicates that the dataset is a data.table object. The original content has not been modified in any way.

Source

Data taken from the covid19india package version 0.1.4

Indian Companies in the Fortune Global 500

Description

This dataset, India_Companies_tbl_df, is a tibble containing information about notable companies headquartered in India, including those in the Fortune Global 500. It includes company names, industry, sector, headquarters location, founding year, notes, private or state ownership status, and whether the company is active or defunct. The dataset preserves the original structure from its source on Kaggle.

Usage

data(India_Companies_tbl_df)

Format

A tibble with 493 observations and 8 variables:

Name

Name of the company (character)

Industry

Industry classification (character)

Sector

Sector classification (character)

Headquarters

Primary headquarters location (character)

Founded

Year the company was founded (character)

Notes

Additional notes or remarks (character)

Private/State

Ownership status: private or state-owned (character)

Active/Defunct

Company status: active or defunct (character)

Details

The dataset name has been kept as 'India_Companies_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/mrmars1010/companies-in-india

Shark Tank India Dataset

Description

This dataset, India_SharkTank_tbl_df, is a tibble containing detailed information on pitches presented on Shark Tank India. It includes episode and pitch numbers, brand names, business ideas, deal status, financial details (ask amount, equity, valuation, deal amount, equity, and valuation), presence of each shark during the pitch, whether each shark invested, total sharks invested, amount per shark, and equity per shark. The dataset preserves the original structure from its source on Kaggle.

Usage

data(India_SharkTank_tbl_df)

Format

A tibble with 117 observations and 28 variables:

episode_number

Episode number (numeric)

pitch_number

Pitch number within the episode (numeric)

brand_name

Name of the brand presented (character)

idea

Business idea description (character)

deal

Indicator if a deal was made (numeric; 1 = yes, 0 = no)

pitcher_ask_amount

Amount requested by the pitcher (numeric)

ask_equity

Equity percentage requested by the pitcher (numeric)

ask_valuation

Valuation based on the pitcher’s ask (numeric)

deal_amount

Amount invested in the deal (numeric)

deal_equity

Equity percentage given in the deal (numeric)

deal_valuation

Valuation based on the deal (numeric)

ashneer_present

Indicator if Ashneer was present (numeric; 1 = yes, 0 = no)

anupam_present

Indicator if Anupam was present (numeric; 1 = yes, 0 = no)

aman_present

Indicator if Aman was present (numeric; 1 = yes, 0 = no)

namita_present

Indicator if Namita was present (numeric; 1 = yes, 0 = no)

vineeta_present

Indicator if Vineeta was present (numeric; 1 = yes, 0 = no)

peyush_present

Indicator if Peyush was present (numeric; 1 = yes, 0 = no)

ghazal_present

Indicator if Ghazal was present (numeric; 1 = yes, 0 = no)

ashneer_deal

Indicator if Ashneer invested (numeric; 1 = yes, 0 = no)

anupam_deal

Indicator if Anupam invested (numeric; 1 = yes, 0 = no)

aman_deal

Indicator if Aman invested (numeric; 1 = yes, 0 = no)

namita_deal

Indicator if Namita invested (numeric; 1 = yes, 0 = no)

vineeta_deal

Indicator if Vineeta invested (numeric; 1 = yes, 0 = no)

peyush_deal

Indicator if Peyush invested (numeric; 1 = yes, 0 = no)

ghazal_deal

Indicator if Ghazal invested (numeric; 1 = yes, 0 = no)

total_sharks_invested

Total number of sharks who invested (numeric)

amount_per_shark

Investment amount per shark (numeric)

equity_per_shark

Equity percentage per shark (numeric)

Details

The dataset name has been kept as 'India_SharkTank_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/shivavashishtha/shark-tank-india-dataset

Indian Districts Population Data (2011 Census)

Description

This dataset, India_census2011_tbl_df, is a tibble containing population statistics for Indian districts based on the 2011 Census. It includes district ranking, population, growth rate, sex ratio, and literacy statistics for each district. The dataset preserves the original structure from its source on Kaggle.

Usage

data(India_census2011_tbl_df)

Format

A tibble with 610 observations and 7 variables:

Ranking

District ranking (numeric)

District

District name (character)

State

State name (character)

Population

Population count (numeric)

Growth

Population growth rate (character)

Sex-Ratio

Sex ratio (number of females per 1000 males) (numeric)

Literacy

Literacy rate (numeric)

Details

The dataset name has been kept as 'India_census2011_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/shiivvvaam/indian-districts-population-data

Top 500 Indian Cities

Description

This dataset, Top500Cities_tbl_df, is a tibble containing demographic and literacy data for the top 500 cities in India. It includes population counts by gender and age group, literacy rates, sex ratios, graduation counts, and location information. The dataset preserves the original structure from its source on Kaggle.

Usage

data(Top500Cities_tbl_df)

Format

A tibble with 493 observations and 22 variables:

name_of_city

Name of the city (character)

state_code

State code (numeric)

state_name

Name of the state (character)

dist_code

District code (numeric)

population_total

Total population (numeric)

population_male

Male population (numeric)

population_female

Female population (numeric)

0-6_population_total

Total population aged 0-6 years (numeric)

0-6_population_male

Male population aged 0-6 years (numeric)

0-6_population_female

Female population aged 0-6 years (numeric)

literates_total

Total literates (numeric)

literates_male

Male literates (numeric)

literates_female

Female literates (numeric)

sex_ratio

Sex ratio (females per 1000 males) (numeric)

child_sex_ratio

Child sex ratio (females per 1000 males) (numeric)

effective_literacy_rate_total

Effective literacy rate total (numeric)

effective_literacy_rate_male

Effective literacy rate for males (numeric)

effective_literacy_rate_female

Effective literacy rate for females (numeric)

location

Location coordinates or description (character)

total_graduates

Total number of graduates (numeric)

male_graduates

Number of male graduates (numeric)

female_graduates

Number of female graduates (numeric)

Details

The dataset name has been kept as 'Top500Cities_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/zed9941/top-500-indian-cities

Indian Unicorn Startups 2023

Description

This dataset, Unicorn_startups_tbl_df, is a tibble containing information about Indian unicorn startups as of 2023. It includes company names, sectors, entry valuations, current valuations, entry years, locations, and select investors. The dataset preserves the original structure from its source on Kaggle.

Usage

data(Unicorn_startups_tbl_df)

Format

A tibble with 102 observations and 8 variables:

No.

Serial number (numeric)

Company

Name of the startup company (character)

Sector

Business sector of the startup (character)

Entry Valuation^^ (B)

Entry valuation in billions (numeric)

Valuation (B)

Current valuation in billions (numeric)

Entry

Year of entry into unicorn status (character)

Location

Location of the startup (character)

Select Investors

Select investors in the startup (character)

Details

The dataset name has been kept as 'Unicorn_startups_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/mlvprasad/indian-unicorn-startups-2023-june-updated

West Bengal Population, Sex-Ratio, and Literacy Data (2011)

Description

This dataset, WestBengalPop_tbl_df, is a tibble containing demographic data for districts of West Bengal, India, based on the 2011 Census. It includes total population, population increase percentage, sex ratio, literacy percentage, and population density for each district.

Usage

data(WestBengalPop_tbl_df)

Format

A tibble with 23 observations and 8 variables:

code

Numeric district code (numeric)

abbr

District abbreviation (character)

district

Full district name (character)

pop_2011

Population in the year 2011 (numeric)

pop_increase_2011

Population increase percentage in 2011 compared to the previous census (numeric)

sex_ratio_2011

Sex ratio in 2011, expressed as females per 1,000 males (numeric)

literacy_per_2011

Literacy rate in 2011, expressed as a percentage (numeric)

density_2011

Population density in 2011 (persons per square kilometer) (numeric)

Details

The dataset name has been kept as 'WestBengalPop_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the IndiAPIs 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 mapindia package version 1.0.1

Indian Bird Observations: Tracking Species

Description

This dataset, birds_watching_tbl_df, is a tibble containing detailed information on bird species observed in India, including species names, scientific names, the date of last observation, and total recorded sightings. The dataset preserves the original structure from its source on Kaggle.

Usage

data(birds_watching_tbl_df)

Format

A tibble with 490 observations and 4 variables:

name

Common name of the bird species (character)

scientific name

Scientific name of the bird species (character)

last observation

Date of last recorded observation (character)

total observations

Total number of recorded sightings (numeric)

Details

The dataset name has been kept as 'birds_watching_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/prajwaldongre/indian-bird-observations-tracking-species

Daily Diesel Fuel Price Data in India (2002-2020)

Description

This dataset, diesel_fuelprice_tbl_df, is a tibble containing daily diesel fuel price data across multiple cities and states in India from 2002 to 2020. It includes city and state information, along with the date and diesel price rate. The dataset preserves the original structure from its source on Kaggle.

Usage

data(diesel_fuelprice_tbl_df)

Format

A tibble with 17,235 observations and 4 variables:

city

Name of the city (character)

date

Date of the observation (Date)

rate

Diesel price rate (numeric)

state

Name of the state (character)

Details

The dataset name has been kept as 'diesel_fuelprice_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/sudhirnl7/fuel-price-in-india

Exports and Imports of India (1997-July 2022)

Description

This dataset, exports_imports_tbl_df, is a tibble containing export and import data for India from 1997 to July 2022. It includes information on country-wise exports, imports, total trade, and trade balance along with the financial year start and end dates. The dataset preserves the original structure from its source on Kaggle.

Usage

data(exports_imports_tbl_df)

Format

A tibble with 5,994 observations and 7 variables:

Country

Country name (character)

Export

Export value (numeric)

Import

Import value (numeric)

Total Trade

Total trade value (numeric)

Trade Balance

Trade balance value (numeric)

Financial Year(start)

Financial year start (numeric)

Financial Year(end)

Financial year end (character)

Details

The dataset name has been kept as 'exports_imports_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/ramjasmaurya/exports-and-imports-of-india19972022

Get Country Information for India

Description

Retrieves comprehensive country information for India from the REST Countries API. This function fetches data including official and common names, geographical information, capital, area, population, and languages.

Usage

get_country_info_in()

Details

This function makes a request to the REST Countries API v3.1 endpoint specifically for India using full text search. It handles API errors gracefully and returns NULL if the request fails or no data is found.

Value

A tibble with one row containing India's country information:

name_common

Common name of the country

name_official

Official name of the country

region

Geographic region

subregion

Geographic subregion

capital

Capital city(ies)

area

Total area in square kilometers

population

Total population

languages

Languages spoken (comma-separated)

Examples

## Not run: 
# Get India information
in_info <- get_country_info_in()
print(in_info)

## End(Not run)

Get India's Under-5 Mortality Rate from World Bank

Description

Retrieves India's under-5 mortality rate, measured as the number of deaths of children under five years of age 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_india_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:

Note

Requires internet connection.

Source

World Bank Open Data API: https://data.worldbank.org/indicator/SH.DYN.MORT

See Also

GET, fromJSON, as_tibble

Examples

if (interactive()) {
  get_india_child_mortality()
}

Get India's Consumer Price Index (2010 = 100) from World Bank

Description

Retrieves India's Consumer Price Index (CPI), with 2010 as the base year (index = 100), for the years 2010 to 2022 using the World Bank Open Data API. The indicator used is FP.CPI.TOTL.

Usage

get_india_cpi()

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:

Note

Requires internet connection.

Source

World Bank Open Data API: https://data.worldbank.org/indicator/FP.CPI.TOTL

See Also

GET, fromJSON, as_tibble

Examples

if (interactive()) {
  get_india_cpi()
}

Get India's Energy Use (kg of oil equivalent per capita) from World Bank

Description

Retrieves India'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_india_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:

Note

Requires internet connection.

Source

World Bank Open Data API: https://data.worldbank.org/indicator/EG.USE.PCAP.KG.OE

See Also

GET, fromJSON, as_tibble

Examples

if (interactive()) {
  get_india_energy_use()
}

Get India's GDP (current US$) from World Bank

Description

Retrieves India's Gross Domestic Product (GDP) at 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_india_gdp()

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:

Note

Requires internet connection.

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_india_gdp()
}

Get India's Hospital Beds (per 1,000 people) from World Bank

Description

Retrieves the number of hospital beds per 1,000 people in India for the years 2010 to 2022 using the World Bank Open Data API. The indicator used is SH.MED.BEDS.ZS.

Usage

get_india_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:

Note

Requires internet connection.

Source

World Bank Open Data API: https://data.worldbank.org/indicator/SH.MED.BEDS.ZS

See Also

GET, fromJSON, as_tibble

Examples

if (interactive()) {
  get_india_hospital_beds()
}

Get India's Life Expectancy at Birth from World Bank

Description

Retrieves India's life expectancy at birth (total, 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_india_life_expectancy()

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:

Note

Requires internet connection.

Source

World Bank Open Data API: https://data.worldbank.org/indicator/SP.DYN.LE00.IN

See Also

GET, fromJSON, as_tibble

Examples

if (interactive()) {
  get_india_life_expectancy()
}

Get India's Adult Literacy Rate from World Bank

Description

Retrieves India's adult literacy rate, defined as the percentage of people ages 15 and above who can read and write, for the years 2010 to 2022 using the World Bank Open Data API. The indicator used is SE.ADT.LITR.ZS.

Usage

get_india_literacy_rate()

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:

Note

Requires internet connection.

Source

World Bank Open Data API: https://data.worldbank.org/indicator/SE.ADT.LITR.ZS

See Also

GET, fromJSON, as_tibble

Examples

if (interactive()) {
  get_india_literacy_rate()
}

Get India's Total Population from World Bank

Description

Retrieves India'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_india_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:

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_india_population()
}

Get India's Unemployment Rate from World Bank

Description

Retrieves India's total unemployment rate as a percentage of the total labor force for the years 2010 to 2022 using the World Bank Open Data API. The indicator used is SL.UEM.TOTL.ZS.

Usage

get_india_unemployment()

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:

Note

Requires internet connection.

Source

World Bank Open Data API: https://data.worldbank.org/indicator/SL.UEM.TOTL.ZS

See Also

GET, fromJSON, as_tibble

Examples

## Not run: 
  unemployment_data <- get_india_unemployment()
  print(unemployment_data)

## End(Not run)

Hospitals Count in India - Statewise

Description

This dataset, hospitalcount_tbl_df, is a tibble containing the count of hospitals in India by state and union territory. It includes the number of hospitals in the public sector, the private sector, and the total number of hospitals (public + private) for each state or UT. The dataset preserves the original structure from its source on Kaggle.

Usage

data(hospitalcount_tbl_df)

Format

A tibble with 37 observations and 4 variables:

States/UTs

Name of the state or union territory (character)

Number of hospitals in public sector

Number of hospitals in the public sector (numeric)

Number of hospitals in private sector

Number of hospitals in the private sector (numeric)

Total number of hospitals (public+private)

Total number of hospitals combining public and private sectors (numeric)

Details

The dataset name has been kept as 'hospitalcount_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/gokulprakash22/hospitals-count-in-india-statewise

Indian Population (Census and Projections) by States

Description

This dataset, indianPopulation_tbl_df, is a tibble containing census data and population projections for Indian states across multiple years. It includes state codes, abbreviations, names, and population figures for the years 1901, 1951, 2011, 2023, and 2024.

Usage

data(indianPopulation_tbl_df)

Format

A tibble with 36 observations and 8 variables:

code

Numeric state code (numeric)

abbr

State abbreviation (character)

state

Full state name (character)

pop_1901

Population in the year 1901 (numeric)

pop_1951

Population in the year 1951 (numeric)

pop_2011

Population in the year 2011 (numeric)

pop_2023

Population in the year 2023 (numeric)

pop_2024

Population in the year 2024 (numeric)

Details

The dataset name has been kept as 'indianPopulation_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the IndiAPIs 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 mapindia package version 1.0.1

Daily Petrol Fuel Price Data in India (2002-2020)

Description

This dataset, petrol_fuelprice_tbl_df, is a tibble containing daily petrol fuel price data across multiple cities and states in India from 2002 to 2020. It includes city and state information, along with the date and petrol price rate. The dataset preserves the original structure from its source on Kaggle.

Usage

data(petrol_fuelprice_tbl_df)

Format

A tibble with 5,048 observations and 4 variables:

city

Name of the city (character)

date

Date of the observation (Date)

rate

Petrol price rate (numeric)

state

Name of the state (character)

Details

The dataset name has been kept as 'petrol_fuelprice_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/sudhirnl7/fuel-price-in-india

Petrol Prices in India

Description

This dataset, petrol_prices_tbl_df, is a tibble containing petrol price information across various cities in India. It includes the city name, date of the price record, and the petrol rate on that date. The dataset preserves the original structure from its source on Kaggle.

Usage

data(petrol_prices_tbl_df)

Format

A tibble with 1,024 observations and 3 variables:

city

Name of the city (character)

date

Date of the petrol price record (Date)

rate

Petrol price rate (numeric)

Details

The dataset name has been kept as 'petrol_prices_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/sandipdevre/petrol-prices-in-india

Rainfall in India (1901-2021)

Description

This dataset, rainfall_tbl_df, is a tibble containing historical monthly rainfall data for subdivisions in India from 1901 to 2021. It includes rainfall measurements for June, July, August, September, and the total for June to September, along with the year and subdivision name. The dataset preserves the original structure from its source on Kaggle.

Usage

data(rainfall_tbl_df)

Format

A tibble with 4,332 observations and 7 variables:

subdivision

Name of the subdivision (character)

YEAR

Year of observation (numeric)

JUN

Rainfall in June (numeric)

JUL

Rainfall in July (numeric)

AUG

Rainfall in August (numeric)

SEP

Rainfall in September (numeric)

JUN-SEP

Total rainfall from June to September (numeric)

Details

The dataset name has been kept as 'rainfall_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/aksahaha/rainfall-india

India Road and Population Data by State

Description

This dataset, road_population_tbl_df, is a tibble containing detailed information about road infrastructure and population data for Indian states. It includes lengths of various road types, road density metrics, area statistics, and rural and urban population data according to the 2011 census. The dataset preserves the original structure from its source on Kaggle.

Usage

data(road_population_tbl_df)

Format

A tibble with 36 observations and 27 variables:

Name of the States

Name of the state or union territory (character)

National Highways

Length of national highways in kilometers (numeric)

State Highways

Length of state highways in kilometers (numeric)

District Roads

Length of district roads in kilometers (numeric)

Rural Roads

Length of rural roads in kilometers (numeric)

Urban roads

Length of urban roads in kilometers (numeric)

Project Roads

Length of project roads in kilometers (numeric)

Total road Length

Total length of roads in kilometers (numeric)

Total Area

Total area of the state/UT in square kilometers (numeric)

Urban Road density

Density of urban roads (numeric)

Rural Road density

Density of rural roads (numeric)

Entire State Road length per 1000 sq km

Road length per 1000 square kilometers of entire state (numeric)

Urban Road lngth per 1000 sq km

Urban road length per 1000 square kilometers (numeric)

Rural Road lngth per 1000 sq km

Rural road length per 1000 square kilometers (numeric)

Road Density

Overall road density (numeric)

Road Density per 1000 Sq. Km - National Highways

National highways road density per 1000 sq km (numeric)

Road Density per 1000 Sq. Km - State Highways

State highways road density per 1000 sq km (numeric)

Road Density per 1000 Sq. Km - District Roads

District roads road density per 1000 sq km (numeric)

Road Density per 1000 Sq. Km - Rural Roads

Rural roads road density per 1000 sq km (numeric)

Road Density per 1000 Sq. Km - Urban roads

Urban roads road density per 1000 sq km (numeric)

Road Density per 1000 Sq. Km - Project Roads

Project roads road density per 1000 sq km (numeric)

Area

Area of the state/UT (numeric)

Rural Area (2011 census)

Rural area in 2011 census (numeric)

Urban Area (2011 census)

Urban area in 2011 census (numeric)

Rural Pop (2011 census)

Rural population according to 2011 census (numeric)

Urban Pop (2011 census)

Urban population according to 2011 census (numeric)

Total Population

Total population of the state/UT (numeric)

Details

The dataset name has been kept as 'road_population_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/zsinghrahulk/india-roadforpopulation-data

5G Smartphones Available in India (2022)

Description

This dataset, smartphones5G_tbl_df, is a tibble containing detailed information about 5G smartphones available in India as of 2022. It includes product names, processor details, camera specifications, display size, RAM, storage, battery, Android version, pricing from two different websites, the real price available, and scores by SmartPrice. The dataset preserves the original structure from its source on Kaggle.

Usage

data(smartphones5G_tbl_df)

Format

A tibble with 257 observations and 15 variables:

product name

Name of the smartphone product (character)

processor name

Name of the processor used (character)

camera specs rear

Rear camera specifications (character)

camera specs front

Front camera specifications (character)

display size

Display size specification (character)

ram of phone

RAM size specification (character)

storage

Storage capacity specification (character)

battery

Battery specification (character)

android version

Android version running on the phone (character)

first site

First website for price reference (character)

price in first site

Price listed on the first site (character)

second site

Second website for price reference (character)

price in second site

Price listed on the second site (character)

real price available

Actual available price (numeric)

score by smartprice

Score assigned by SmartPrice (numeric)

Details

The dataset name has been kept as 'smartphones5G_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/ramjasmaurya/5g-smartphones-available-in-india

Indian Startup Funding

Description

This dataset, startup_funding_tbl_df, is a tibble containing detailed funding information for startups in India. It includes the serial number, date, startup name, industry vertical, sub-vertical, city location, investors' names, investment type, amount in USD, and any additional remarks. The dataset preserves the original structure from its source on Kaggle.

Usage

data(startup_funding_tbl_df)

Format

A tibble with 3,044 observations and 10 variables:

Sr No

Serial number of the record (numeric)

Date dd/mm/yyyy

Date of the funding record in dd/mm/yyyy format (character)

Startup Name

Name of the startup (character)

Industry Vertical

Primary industry vertical of the startup (character)

SubVertical

Specific sub-vertical within the industry (character)

City Location

City where the startup is located (character)

Investors Name

Name(s) of the investor(s) (character)

InvestmentnType

Type of investment (character)

Amount in USD

Funding amount in US dollars (character)

Remarks

Additional remarks related to the record (character)

Details

The dataset name has been kept as 'startup_funding_tbl_df' to maintain consistency with the naming conventions in the IndiAPIs 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/sudalairajkumar/indian-startup-funding

View Available Datasets in IndiAPIs

Description

This function lists all datasets available in the 'IndiAPIs' package. If the 'IndiAPIs' 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_IndiAPIs()

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("IndiAPIs", quietly = TRUE)) {
  library(IndiAPIs)
  view_datasets_IndiAPIs()
}

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