Title: A Group of Fun Datasets of Various Sizes and Differing Levels of Quality
Version: 0.1.1
Description: Four datasets are provided here from the 'Intendo' game 'Super Jetroid'. It is data from the 2015 year of operation and it comprises a revenue table ('all_revenue'), a daily users table ('users_daily'), a user summary table ('user_summary'), and a table with data on all user sessions ('all_sessions'). These core datasets come in different sizes, and, each of them has a variant that was intentionally made faulty (totally riddled with errors and inconsistencies). This suite of tables is useful for testing with packages that focus on data validation and data documentation.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.1
Suggests: DBI (≥ 1.1.3), dplyr (≥ 1.1.0), duckdb (≥ 0.7.0), pointblank (≥ 0.11.3), testthat, tibble (≥ 3.1.8)
Depends: R (≥ 3.5)
NeedsCompilation: no
Packaged: 2024-02-29 15:25:30 UTC; riannone
Author: Richard Iannone ORCID iD [aut, cre]
Maintainer: Richard Iannone <riannone@me.com>
Repository: CRAN
Date/Publication: 2024-02-29 15:40:02 UTC

All revenue amounts for Super Jetroid

Description

This summary table provides revenue data for every in-app purchase and ad view for players of Super Jetroid in 2015.

Usage

all_revenue(
  size = c("small", "medium", "large", "xlarge", "preview"),
  quality = c("perfect", "faulty"),
  type = c("tibble", "data.frame", "duckdb", "csv"),
  keep = FALSE
)

Arguments

size

A keyword that allows getting different variants of the table based on the size of player base. The default "small" table has the lowest number of players/records. Increasing in size, we can also opt for the "medium", "large", or "xlarge" versions.

quality

The data quality level of the returned dataset. There are two options: (1) "perfect" provides a pristine table with no errors at all and (2) "faulty" gives you a table with a multitude of errors.

type

The table return type. By default, this is a "tibble" but a "data.frame" can instead be returned if using that keyword. If you have the duckdb package installed, you can instead obtain the table as an in-memory DuckDB database table.

keep

Should the downloaded data be stored on disk in the working directory? By default, this is FALSE. If the file is available in the next invocation then the data won't be downloaded again.

Value

A data table object, which could be a tibble (tbl_df) a data frame, or an in-memory DuckDB table (tbl_dbi). If a CSV is written then TRUE will be invisibly returned.

Examples


# Get a preview of the `all_revenue` dataset
# with the 'preview' size option
all_revenue(size = "preview")

Data Dictionary for all_revenue

Description

The all_revenue_dd() function generates a data dictionary based on the all_revenue table.

Usage

all_revenue_dd(
  size = c("small", "medium", "large", "xlarge", "preview"),
  quality = c("perfect", "faulty"),
  type = c("tibble", "data.frame", "duckdb")
)

Arguments

size

A keyword that allows getting different variants of the table based on the size of player base. The default "small" table has the lowest number of players/records. Increasing in size, we can also opt for the "medium", "large", or "xlarge" versions.

quality

The data quality level of the returned dataset. There are two options: (1) "perfect" provides a pristine table with no errors at all and (2) "faulty" gives you a table with a multitude of errors.

type

The table return type. By default, this is a "tibble" but a "data.frame" can instead be returned if using that keyword. If you have the duckdb package installed, you can instead obtain the table as an in-memory DuckDB database table.

Value

A ptblank_informant object.

Examples


# Get a preview of the `all_revenue` dataset
# with the 'preview' size option
all_revenue_dd(size = "preview")

All player sessions for Super Jetroid

Description

This table provides information on player sessions and summarizes the number of revenue events (ad views and IAP spends) and provides total revenue amounts (in USD) broken down by type for the session.

Usage

all_sessions(
  size = c("small", "medium", "large", "xlarge", "preview"),
  quality = c("perfect", "faulty"),
  type = c("tibble", "data.frame", "duckdb", "csv"),
  keep = FALSE
)

Arguments

size

A keyword that allows getting different variants of the table based on the size of player base. The default "small" table has the lowest number of players/records. Increasing in size, we can also opt for the "medium", "large", or "xlarge" versions.

quality

The data quality level of the returned dataset. There are two options: (1) "perfect" provides a pristine table with no errors at all and (2) "faulty" gives you a table with a multitude of errors.

type

The table return type. By default, this is a "tibble" but a "data.frame" can instead be returned if using that keyword. If you have the duckdb package installed, you can instead obtain the table as an in-memory DuckDB database table.

keep

Should the downloaded data be stored on disk in the working directory? By default, this is FALSE. If the file is available in the next invocation then the data won't be downloaded again.

Value

A data table object, which could be a tibble (tbl_df) a data frame, or an in-memory DuckDB table (tbl_dbi). If a CSV is written then TRUE will be invisibly returned.

Examples


# Get a preview of the `all_sessions` dataset
# with the 'preview' size option
all_sessions(size = "preview")

Data Dictionary for all_sessions

Description

The all_sessions_dd() function generates a data dictionary based on the all_sessions table.

Usage

all_sessions_dd(
  size = c("small", "medium", "large", "xlarge", "preview"),
  quality = c("perfect", "faulty"),
  type = c("tibble", "data.frame", "duckdb")
)

Arguments

size

A keyword that allows getting different variants of the table based on the size of player base. The default "small" table has the lowest number of players/records. Increasing in size, we can also opt for the "medium", "large", or "xlarge" versions.

quality

The data quality level of the returned dataset. There are two options: (1) "perfect" provides a pristine table with no errors at all and (2) "faulty" gives you a table with a multitude of errors.

type

The table return type. By default, this is a "tibble" but a "data.frame" can instead be returned if using that keyword. If you have the duckdb package installed, you can instead obtain the table as an in-memory DuckDB database table.

Value

A ptblank_informant object.

Examples


# Get a preview of the `all_sessions` dataset
# with the 'preview' size option
all_sessions_dd(size = "preview")

Get a data frame with metadata for all datasets

Description

The intendo_metadata() function provides a data frame containing metadata for datasets in the intendo package.

Usage

intendo_metadata(include = c("all", "perfect", "faulty"))

Arguments

include

Should both perfect and faulty datasets be included in the metadata table? This is the default ("all"), otherwise one can use the "perfect" or "faulty" keywords to get a subset of the metadata table.

Value

A data frame.

Examples


# Obtain metadata on all datasets in the package but
# only those in their 'perfect' form
intendo_metadata(include = "perfect")

User summaries for Super Jetroid

Description

This summary table provides information on each user. We get information here such as the first login/session time and some information useful for segmentation.

Usage

user_summary(
  size = c("small", "medium", "large", "xlarge", "preview"),
  quality = c("perfect", "faulty"),
  type = c("tibble", "data.frame", "duckdb", "csv"),
  keep = FALSE
)

Arguments

size

A keyword that allows getting different variants of the table based on the size of player base. The default "small" table has the lowest number of players/records. Increasing in size, we can also opt for the "medium", "large", or "xlarge" versions.

quality

The data quality level of the returned dataset. There are two options: (1) "perfect" provides a pristine table with no errors at all and (2) "faulty" gives you a table with a multitude of errors.

type

The table return type. By default, this is a "tibble" but a "data.frame" can instead be returned if using that keyword. If you have the duckdb package installed, you can instead obtain the table as an in-memory DuckDB database table.

keep

Should the downloaded data be stored on disk in the working directory? By default, this is FALSE. If the file is available in the next invocation then the data won't be downloaded again.

Value

A data table object, which could be a tibble (tbl_df) a data frame, or an in-memory DuckDB table (tbl_dbi). If a CSV is written then TRUE will be invisibly returned.

Examples


# Get a preview of the `user_summary` dataset
# with the 'preview' size option
user_summary(size = "preview")

Data Dictionary for user_summary

Description

The user_summary_dd() function generates a data dictionary based on the user_summary table.

Usage

user_summary_dd(
  size = c("small", "medium", "large", "xlarge", "preview"),
  quality = c("perfect", "faulty"),
  type = c("tibble", "data.frame", "duckdb")
)

Arguments

size

A keyword that allows getting different variants of the table based on the size of player base. The default "small" table has the lowest number of players/records. Increasing in size, we can also opt for the "medium", "large", or "xlarge" versions.

quality

The data quality level of the returned dataset. There are two options: (1) "perfect" provides a pristine table with no errors at all and (2) "faulty" gives you a table with a multitude of errors.

type

The table return type. By default, this is a "tibble" but a "data.frame" can instead be returned if using that keyword. If you have the duckdb package installed, you can instead obtain the table as an in-memory DuckDB database table.

Value

A ptblank_informant object.

Examples


# Get a preview of the `user_summary` dataset
# with the 'preview' size option
user_summary_dd(size = "preview")

Daily users playing Super Jetroid

Description

This summary table provides daily totals for every player that had at least one login/session in a day. We get measures such as daily sessions, time played, number of IAPs bought and ads viewed, revenue gained, progression info, and some segmentation categories.

Usage

users_daily(
  size = c("small", "medium", "large", "xlarge", "preview"),
  quality = c("perfect", "faulty"),
  type = c("tibble", "data.frame", "duckdb", "csv"),
  keep = FALSE
)

Arguments

size

A keyword that allows getting different variants of the table based on the size of player base. The default "small" table has the lowest number of players/records. Increasing in size, we can also opt for the "medium", "large", or "xlarge" versions.

quality

The data quality level of the returned dataset. There are two options: (1) "perfect" provides a pristine table with no errors at all and (2) "faulty" gives you a table with a multitude of errors.

type

The table return type. By default, this is a "tibble" but a "data.frame" can instead be returned if using that keyword. If you have the duckdb package installed, you can instead obtain the table as an in-memory DuckDB database table.

keep

Should the downloaded data be stored on disk in the working directory? By default, this is FALSE. If the file is available in the next invocation then the data won't be downloaded again.

Value

A data table object, which could be a tibble (tbl_df) a data frame, or an in-memory DuckDB table (tbl_dbi). If a CSV is written then TRUE will be invisibly returned.

Examples


# Get a preview of the `users_daily` dataset
# with the 'preview' size option
users_daily(size = "preview")

Data Dictionary for users_daily

Description

The users_daily_dd() function generates a data dictionary based on the users_daily table.

Usage

users_daily_dd(
  size = c("small", "medium", "large", "xlarge", "preview"),
  quality = c("perfect", "faulty"),
  type = c("tibble", "data.frame", "duckdb")
)

Arguments

size

A keyword that allows getting different variants of the table based on the size of player base. The default "small" table has the lowest number of players/records. Increasing in size, we can also opt for the "medium", "large", or "xlarge" versions.

quality

The data quality level of the returned dataset. There are two options: (1) "perfect" provides a pristine table with no errors at all and (2) "faulty" gives you a table with a multitude of errors.

type

The table return type. By default, this is a "tibble" but a "data.frame" can instead be returned if using that keyword. If you have the duckdb package installed, you can instead obtain the table as an in-memory DuckDB database table.

Value

A ptblank_informant object.

Examples


# Get a preview of the `users_daily` dataset
# with the 'preview' size option
users_daily_dd(size = "preview")