These functions allow easily computing means and sums. Note that if you
attach rosetta to the search path,
means(
...,
data = NULL,
requiredValidValues = 0,
returnIfInvalid = NA,
silent = FALSE
)
sums(
...,
data = NULL,
requiredValidValues = 0,
returnIfInvalid = NA,
silent = FALSE
)The dataframe or vectors for which to compute the means or sums.
When passing a dataframe as unnamed argument (i.e. in the "dots", ...),
the means or sums for all columns in the dataframe will be computed. If you
want to select one or more columns, make sure to pass the dataframe as data.
If a dataframe is passed as data, the values passed in
the "dots" (...) will be taken as column names or indices in that
dataframe. This allows easy indexing.
The number (if larger than 1) or proportion (if between 0 and 1) of values that have to be valid (i.e. nonmissing) before the mean or sum is returned.
Which value to return for rows not meeting the
criterion specified in requiredValidValues.
Whether to suppress messages.
The means or sums.
rosetta::means(mtcars$mpg, mtcars$disp, mtcars$wt);
#> [1] 61.20667 61.29167 44.37333 94.20500 127.38000 82.18667 125.95667
#> [8] 58.09667 55.58333 63.41333 62.94667 98.75667 98.94333 98.26000
#> [15] 162.55000 158.60800 153.34833 37.76667 35.90500 35.61167 48.02167
#> [22] 112.34000 107.54500 122.38000 141.01500 36.07833 49.48000 42.33767
#> [29] 123.32333 55.82333 106.52333 48.39333
rosetta::means(data=mtcars, 'mpg', 'disp', 'wt');
#> Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive
#> 61.20667 61.29167 44.37333 94.20500
#> Hornet Sportabout Valiant Duster 360 Merc 240D
#> 127.38000 82.18667 125.95667 58.09667
#> Merc 230 Merc 280 Merc 280C Merc 450SE
#> 55.58333 63.41333 62.94667 98.75667
#> Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental
#> 98.94333 98.26000 162.55000 158.60800
#> Chrysler Imperial Fiat 128 Honda Civic Toyota Corolla
#> 153.34833 37.76667 35.90500 35.61167
#> Toyota Corona Dodge Challenger AMC Javelin Camaro Z28
#> 48.02167 112.34000 107.54500 122.38000
#> Pontiac Firebird Fiat X1-9 Porsche 914-2 Lotus Europa
#> 141.01500 36.07833 49.48000 42.33767
#> Ford Pantera L Ferrari Dino Maserati Bora Volvo 142E
#> 123.32333 55.82333 106.52333 48.39333
rosetta::sums(mtcars$mpg, mtcars$disp, mtcars$wt);
#> [1] 183.620 183.875 133.120 282.615 382.140 246.560 377.870 174.290 166.750
#> [10] 190.240 188.840 296.270 296.830 294.780 487.650 475.824 460.045 113.300
#> [19] 107.715 106.835 144.065 337.020 322.635 367.140 423.045 108.235 148.440
#> [28] 127.013 369.970 167.470 319.570 145.180
rosetta::sums(data=mtcars, 'mpg', 'disp', 'wt');
#> Mazda RX4 Mazda RX4 Wag Datsun 710 Hornet 4 Drive
#> 183.620 183.875 133.120 282.615
#> Hornet Sportabout Valiant Duster 360 Merc 240D
#> 382.140 246.560 377.870 174.290
#> Merc 230 Merc 280 Merc 280C Merc 450SE
#> 166.750 190.240 188.840 296.270
#> Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental
#> 296.830 294.780 487.650 475.824
#> Chrysler Imperial Fiat 128 Honda Civic Toyota Corolla
#> 460.045 113.300 107.715 106.835
#> Toyota Corona Dodge Challenger AMC Javelin Camaro Z28
#> 144.065 337.020 322.635 367.140
#> Pontiac Firebird Fiat X1-9 Porsche 914-2 Lotus Europa
#> 423.045 108.235 148.440 127.013
#> Ford Pantera L Ferrari Dino Maserati Bora Volvo 142E
#> 369.970 167.470 319.570 145.180