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I have many labels under a variable for which I want to filter on that label and create new separate data frames for each label. I’m interested in the best way of doing this. Currently I am trying to do this using a for loop. (In R, how do I create a df for each “i” and save it to a new variable, preferably by the name of “i”?)

I will then be using the output of each new df to run it through another function that creates charts and figures for each of these 8 separate programs.

In the MRE, I am filtering by each cylinder category (4,6,8) and creating a new data frame for each cylinder.

This would be cyl_4, cyl_6, cyl_8 would be the output I want.

filter_cyl = function(cylinder){
  mtcars%>%filter(cyl == cylinder)
}

cyl_4 = filter_cyl(4)
cyl_6 = filter_cyl(6)
cyl_8 = filter_cyl(8)

Obviously, below only gets me the last data frame.

for (i in unique(mtcars$cyl)){
  new_df = filter_cyl(i)
}
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1 Answer 1

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You can simply run split

> split(mtcars, ~cyl)
$`4`
                mpg cyl  disp  hp drat    wt  qsec vs am gear carb
Datsun 710     22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
Merc 240D      24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
Merc 230       22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
Fiat 128       32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
Honda Civic    30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
Toyota Corolla 33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
Toyota Corona  21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
Fiat X1-9      27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
Porsche 914-2  26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
Lotus Europa   30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
Volvo 142E     21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2

$`6`
                mpg cyl  disp  hp drat    wt  qsec vs am gear carb
Mazda RX4      21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
Mazda RX4 Wag  21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
Hornet 4 Drive 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
Valiant        18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
Merc 280       19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
Merc 280C      17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
Ferrari Dino   19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6

$`8`
                     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
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3 Comments

Thank you for this...it seems that the question was closed then reopened. Didn't realize split existed! I see that the output is a list of data frames: I have a question on operating on this list of dfs for my desired purpose. If there are 8 programs (so 8 datasets), and I want to still perform several functions depending on the variables in the datasets, how would I store the output for each variable for all 8 dfs)? (Now it is only storing the output for the last dataset for age and language). for (i in dfs){ age = some_fun(i, age) language = some_fun(i, language) }
@James you can use lapply, like lapply(dfs, \(i) {list(age = some_fun(i, age), language = some_fun(i,language)})
Amazing...thanks so much!

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