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dm_flatten_to_tbl() gathers all information of interest in one place in a wide table. It performs a disambiguation of column names and a cascade of joins.

Usage

dm_flatten_to_tbl(dm, .start, ..., .recursive = FALSE, .join = left_join)

Arguments

dm

A dm object.

.start

The table from which all outgoing foreign key relations are considered when establishing a processing order for the joins. An interesting choice could be for example a fact table in a star schema.

...

[Experimental]

Unquoted names of the tables to be included in addition to the .start table. The order of the tables here determines the order of the joins. If the argument is empty, all tables that can be reached will be included. tidyselect is supported, see dplyr::select() for details on the semantics.

.recursive

Logical, defaults to FALSE. Should not only parent tables be joined to .start, but also their ancestors?

.join

The type of join to be performed, see dplyr::join().

Value

A single table that results from consecutively joining all affected tables to the .start table.

Details

With ... left empty, this function will join together all the tables of your dm object that can be reached from the .start table, in the direction of the foreign key relations (pointing from the child tables to the parent tables), using the foreign key relations to determine the argument by for the necessary joins. The result is one table with unique column names. Use the ... argument if you would like to control which tables should be joined to the .start table.

Mind that calling dm_flatten_to_tbl() with .join = right_join and no table order determined in the ... argument will not lead to a well-defined result if two or more foreign tables are to be joined to .start. The resulting table would depend on the order the tables that are listed in the dm. Therefore, trying this will result in a warning.

Since .join = nest_join does not make sense in this direction (LHS = child table, RHS = parent table: for valid key constraints each nested column entry would be a tibble of one row), an error will be thrown if this method is chosen.

The difference between .recursive = FALSE and .recursive = TRUE is the following (see the examples):

  • .recursive = FALSE allows only one level of hierarchy (i.e., direct neighbors to table .start), while

  • .recursive = TRUE will go through all levels of hierarchy while joining.

Additionally, these functions differ from dm_wrap_tbl(), which always returns a dm object.

Examples


dm_financial() %>%
  dm_select_tbl(-loans) %>%
  dm_flatten_to_tbl(.start = cards)
#> Renaming ambiguous columns: %>%
#>   dm_rename(cards, type.cards = type) %>%
#>   dm_rename(disps, type.disps = type)
#> # Source:   SQL [?? x 7]
#> # Database: mysql  [guest@relational.fel.cvut.cz:3306/Financial_ijs]
#>       id disp_id type.cards issued     client_id account_id type.disps
#>    <int>   <int> <chr>      <date>         <int>      <int> <chr>     
#>  1     1       9 gold       1998-10-16         9          7 OWNER     
#>  2     2      19 classic    1998-03-13        19         14 OWNER     
#>  3     3      41 gold       1995-09-03        41         33 OWNER     
#>  4     4      42 classic    1998-11-26        42         34 OWNER     
#>  5     5      51 junior     1995-04-24        51         43 OWNER     
#>  6     7      56 classic    1998-06-11        56         48 OWNER     
#>  7     8      60 junior     1998-05-20        60         51 OWNER     
#>  8     9      76 classic    1997-10-25        76         65 OWNER     
#>  9    10      77 classic    1996-12-07        77         66 OWNER     
#> 10    11      79 gold       1997-10-25        79         68 OWNER     
#> # ℹ more rows

dm_financial() %>%
  dm_select_tbl(-loans) %>%
  dm_flatten_to_tbl(.start = cards, .recursive = TRUE)
#> Renaming ambiguous columns: %>%
#>   dm_rename(cards, type.cards = type) %>%
#>   dm_rename(disps, type.disps = type) %>%
#>   dm_rename(clients, district_id.clients = district_id) %>%
#>   dm_rename(accounts, district_id.accounts = district_id)
#> # Source:   SQL [?? x 28]
#> # Database: mysql  [guest@relational.fel.cvut.cz:3306/Financial_ijs]
#>       id disp_id type.cards issued     client_id account_id type.disps
#>    <int>   <int> <chr>      <date>         <int>      <int> <chr>     
#>  1     1       9 gold       1998-10-16         9          7 OWNER     
#>  2     2      19 classic    1998-03-13        19         14 OWNER     
#>  3     3      41 gold       1995-09-03        41         33 OWNER     
#>  4     4      42 classic    1998-11-26        42         34 OWNER     
#>  5     5      51 junior     1995-04-24        51         43 OWNER     
#>  6     7      56 classic    1998-06-11        56         48 OWNER     
#>  7     8      60 junior     1998-05-20        60         51 OWNER     
#>  8     9      76 classic    1997-10-25        76         65 OWNER     
#>  9    10      77 classic    1996-12-07        77         66 OWNER     
#> 10    11      79 gold       1997-10-25        79         68 OWNER     
#> # ℹ more rows
#> # ℹ 21 more variables: birth_number <chr>, district_id.clients <int>,
#> #   tkey_id <int>, district_id.accounts <int>, frequency <chr>, date <date>,
#> #   A2 <chr>, A3 <chr>, A4 <int>, A5 <int>, A6 <int>, A7 <int>, A8 <int>,
#> #   A9 <int>, A10 <dbl>, A11 <int>, A12 <dbl>, A13 <dbl>, A14 <int>, A15 <int>,
#> #   A16 <int>