This vignette describes which changes are necessary to adapt your
code when updating the {dm} package version from a version
0.0.5
or lower to 0.0.6
or higher.
0.0.5
to
0.0.6
cdm
with dm
During this update the prevalent prefix cdm
was
discarded in favor of dm
. The old prefix would still do its
job, but a warning message would be issued each time a function
beginning with cdm
was being used, informing that the
function is soft-deprecated and suggesting the use of its newer
version.
If you have a script which is based on an older {dm} version, it should still work with the newer version, albeit complaining each time an outdated function is being used. This can be repaired by:
cdm
by
dm
in this script. This can e.g. be done in RStudio using
“Find” or in the terminal using
sed -e 's/cdm/dm/g' path-to-file
on Windows or
sed -i '' -e 's/cdm/dm/g' path-to-file
on a Mac. If the
script errors after this step, you will need to check where exactly the
error happens and manually repair the damage.dm
: tbl
,
[[
, $
Furthermore, you need to pay attention if you used one of
tbl.dm()
, [[.dm()
, $.dm()
. During
the same update the implementation for those methods changed as well,
and here you don’t get the convenient warning messages. The change was,
that before the update, the mentioned methods would return the table
after “filtering” it to just contain the rows with values that relate
via foreign key relations to other tables that were filtered earlier.
After the update just the table as is would be returned. If you want to
retain the former behavior, you need to replace each of the methods with
the function dm_apply_filters_to_tbl()
, which was made
available with the update.
The methods are of course not to be avoided in general, if no filters are set anyway the result will not change after the update.
Here a short example for the different cases:
Formerly you would access the “filtered” tables using the following syntax:
library(dm)
<- dm_nycflights13()
flights_dm tbl(flights_dm, "airports")
#> Warning: `tbl.dm()` was deprecated in dm 0.2.0.
#> Use `dm[[table_name]]` instead to access a specific table.
#> # A tibble: 86 × 8
#> faa name lat lon alt tz dst tzone
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <chr> <chr>
#> 1 ALB Albany Intl 42.7 -73.8 285 -5 A Amer…
#> 2 ATL Hartsfield Jackson Atlanta I… 33.6 -84.4 1026 -5 A Amer…
#> 3 AUS Austin Bergstrom Intl 30.2 -97.7 542 -6 A Amer…
#> 4 BDL Bradley Intl 41.9 -72.7 173 -5 A Amer…
#> 5 BHM Birmingham Intl 33.6 -86.8 644 -6 A Amer…
#> 6 BNA Nashville Intl 36.1 -86.7 599 -6 A Amer…
#> 7 BOS General Edward Lawrence Loga… 42.4 -71.0 19 -5 A Amer…
#> 8 BTV Burlington Intl 44.5 -73.2 335 -5 A Amer…
#> 9 BUF Buffalo Niagara Intl 42.9 -78.7 724 -5 A Amer…
#> 10 BUR Bob Hope 34.2 -118. 778 -8 A Amer…
#> # … with 76 more rows
$planes flights_dm
#> # A tibble: 945 × 9
#> tailnum year type manufacturer model engines seats speed engine
#> <chr> <int> <chr> <chr> <chr> <int> <int> <int> <chr>
#> 1 N10156 2004 Fixed wing … EMBRAER EMB-… 2 55 NA Turbo…
#> 2 N104UW 1999 Fixed wing … AIRBUS INDU… A320… 2 182 NA Turbo…
#> 3 N10575 2002 Fixed wing … EMBRAER EMB-… 2 55 NA Turbo…
#> 4 N105UW 1999 Fixed wing … AIRBUS INDU… A320… 2 182 NA Turbo…
#> 5 N110UW 1999 Fixed wing … AIRBUS INDU… A320… 2 182 NA Turbo…
#> 6 N11106 2002 Fixed wing … EMBRAER EMB-… 2 55 NA Turbo…
#> 7 N11107 2002 Fixed wing … EMBRAER EMB-… 2 55 NA Turbo…
#> 8 N11109 2002 Fixed wing … EMBRAER EMB-… 2 55 NA Turbo…
#> 9 N11121 2003 Fixed wing … EMBRAER EMB-… 2 55 NA Turbo…
#> 10 N11137 2003 Fixed wing … EMBRAER EMB-… 2 55 NA Turbo…
#> # … with 935 more rows
"weather"]] flights_dm[[
#> # A tibble: 144 × 15
#> origin year month day hour temp dewp humid wind_dir wind_speed
#> <chr> <int> <int> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 EWR 2013 1 10 0 41 32 70.1 230 8.06
#> 2 EWR 2013 1 10 1 39.0 30.0 69.9 210 9.21
#> 3 EWR 2013 1 10 2 39.0 28.9 66.8 230 6.90
#> 4 EWR 2013 1 10 3 39.9 27.0 59.5 270 5.75
#> 5 EWR 2013 1 10 4 41 26.1 55.0 320 6.90
#> 6 EWR 2013 1 10 5 41 26.1 55.0 300 12.7
#> 7 EWR 2013 1 10 6 39.9 25.0 54.8 280 6.90
#> 8 EWR 2013 1 10 7 41 25.0 52.6 330 6.90
#> 9 EWR 2013 1 10 8 43.0 25.0 48.7 330 8.06
#> 10 EWR 2013 1 10 9 45.0 23 41.6 320 17.3
#> # … with 134 more rows, and 5 more variables: wind_gust <dbl>,
#> # precip <dbl>, pressure <dbl>, visib <dbl>, time_hour <dttm>
After the update the same result is achieved by this type of function call:
dm_apply_filters_to_tbl(flights_dm, airlines)
#> # A tibble: 15 × 2
#> carrier name
#> <chr> <chr>
#> 1 9E Endeavor Air Inc.
#> 2 AA American Airlines Inc.
#> 3 AS Alaska Airlines Inc.
#> 4 B6 JetBlue Airways
#> 5 DL Delta Air Lines Inc.
#> 6 EV ExpressJet Airlines Inc.
#> 7 F9 Frontier Airlines Inc.
#> 8 FL AirTran Airways Corporation
#> 9 HA Hawaiian Airlines Inc.
#> 10 MQ Envoy Air
#> 11 UA United Air Lines Inc.
#> 12 US US Airways Inc.
#> 13 VX Virgin America
#> 14 WN Southwest Airlines Co.
#> 15 YV Mesa Airlines Inc.