| Title: | A Tidy Grouping Set Aggregation |
| Version: | 0.1.0 |
| Description: | A Tidy implementation of 'grouping sets', 'rollup' and 'cube' - extensions of the 'group_by' clause that allow for computing multiple 'group_by' clauses in a single statement. For more detailed information on these functions, please refer to "Enhanced Aggregation, Cube, Grouping and Rollup" https://cwiki.apache.org/confluence/display/Hive/Enhanced+Aggregation%2C+Cube%2C+Grouping+and+Rollup. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.0 |
| Depends: | R (≥ 2.10), dplyr, tidyr |
| LazyData: | true |
| Suggests: | knitr, rmarkdown |
| VignetteBuilder: | knitr |
| Imports: | rlang, methods, utils, magrittr, sparklyr |
| URL: | https://juyoungahn.github.io/rollup/ |
| NeedsCompilation: | no |
| Packaged: | 2024-08-29 10:35:28 UTC; dan |
| Author: | Ju Young Ahn 
[aut, cre] |
| Maintainer: | Ju Young Ahn <juyoung.ahn@snu.ac.kr> |
| Repository: | CRAN |
| Date/Publication: | 2024-08-29 11:10:04 UTC |
grouped_df_list class definition
Description
A class to represent a list of grouped data frames.
grouping_sets
Description
Compute total amounts at different group levels, producing multiple subtotals. With the 'grouping_sets' clause following 'group_by', you can aggregate multiple grouping variables in one operation. This reflects the 'GROUPING SETS' operations in 'SQL'.
Usage
grouping_sets(df, ...)
Arguments
df |
dataframe or grouped df |
... |
grouping variables |
Value
A list of 'grouped_df' class. each 'grouped_df' object has a different grouping level.
Examples
mtcars %>% group_by(vs, am) %>% grouping_sets("vs","am",c("vs","am"))
mtcars %>% group_by(vs, am) %>% with_rollup()
mtcars %>% group_by(vs, am) %>% with_cube()
Generic summarise function
Description
Generic summarise function
Usage
summarise(object, ...)
Arguments
object |
Object to be summarized. |
... |
Additional arguments. |
Value
An object of the same class as .data. One grouping level will be dropped.
Default method for summarise
Description
Default method for summarise
Usage
## S4 method for signature 'ANY'
summarise(object, ...)
Arguments
object |
An object |
... |
Additional arguments. |
Value
An object of the same class as .data. One grouping level will be dropped.
Method for summarise on grouped_df_list
Description
Method for summarise on grouped_df_list
Usage
## S4 method for signature 'grouped_df_list'
summarise(object, ...)
Arguments
object |
A grouped_df_list object. |
... |
Additional arguments. |
Value
An object of the same class as .data. One grouping level will be dropped.
Generic summarize function
Description
Generic summarize function
Usage
summarize(object, ...)
Arguments
object |
Object to be summarized. |
... |
Additional arguments. |
Value
An object of the same class as .data. One grouping level will be dropped.
Default method for summarize
Description
Default method for summarize
Usage
## S4 method for signature 'ANY'
summarize(object, ...)
Arguments
object |
An object. |
... |
Additional arguments. |
Value
An object of the same class as .data. One grouping level will be dropped.
Method for summarize on grouped_df_list
Description
Method for summarize on grouped_df_list
Usage
## S4 method for signature 'grouped_df_list'
summarize(object, ...)
Arguments
object |
A grouped_df_list object. |
... |
Additional arguments. |
Value
An object of the same class as .data. One grouping level will be dropped.
summarize_rollup
Description
'summarize_rollup' aggregates each 'grouped_df' in the 'grouped_df_list' class and return the unioned aggregated results.
Usage
summarize_rollup(df_list, ...)
Arguments
df_list |
'grouped_df_list' class |
... |
functions for 'summarize' |
Value
An object of the same class as .data. The unioned aggregated result of multiple grouping levels will be dropped.
Web Service Data
Description
A dataset containing information about various web services.
Usage
web_service_data
Format
A data frame with 30,000 rows and 6 variables:
- date_id
date id
- id
user id
- gender
gender
- age
age band
- page_view_cnt
pageview count
- product_view_cnt_cat
product view count (category)
Source
Generated for example purposes
with_cube
Description
Compute total amounts at different group levels, producing multiple subtotals. With the 'with_cube' clause following 'group_by', you can aggregate multiple grouping variables in one operation. This reflects the 'WITH CUBE' operations in 'SQL'.
Usage
with_cube(grouped_df)
Arguments
grouped_df |
'grouped_df' class |
Value
A list of 'grouped_df' class. each 'grouped_df' object has a different grouping level.
Examples
mtcars %>% group_by(vs, am) %>% grouping_sets("vs","am",c("vs","am"))
mtcars %>% group_by(vs, am) %>% with_rollup()
mtcars %>% group_by(vs, am) %>% with_cube()
with_rollup
Description
Compute total amounts at different group levels, producing multiple subtotals. With the 'with_rollup' clause following 'group_by', you can aggregate multiple grouping variables in one operation. This reflects the 'WITH ROLLUP' operations in 'SQL'.
Usage
with_rollup(grouped_df)
Arguments
grouped_df |
'grouped_df' class |
Value
A list of 'grouped_df' class. each 'grouped_df' object has a different grouping level.
Examples
mtcars %>% group_by(vs, am) %>% grouping_sets("vs","am",c("vs","am"))
mtcars %>% group_by(vs, am) %>% with_rollup()
mtcars %>% group_by(vs, am) %>% with_cube()