I have data frame with 3 columns and more than 200000 rows. The first 2 columns are the x and y address of 3 column (values) and each address is repeating 365 times with different values. I have to extract each x,y address with it 365 values saperately.
X Y Value
3297 33.625184 70.875 0.04
3298 33.875184 70.875 0.02
3299 34.125184 70.875 0.01
3300 34.375184 70.875 0.03
3301 34.625184 70.875 0.09
3302 34.875184 70.875 0.14
3303 35.125184 70.875 0.17
3304 35.375184 70.875 0.12
3305 35.625184 70.875 0.13
3306 35.875184 70.875 0.11
3307 36.125184 70.875 0.12
3308 36.375184 70.875 0.11
3309 36.625184 70.875 0.07
3310 36.875184 70.875 0.08
3311 37.125184 70.875 0.13
3312 37.375184 70.875 6.61
3313 33.125185 70.875 3.15
3314 33.375185 70.875 3.72
3315 33.625185 70.875 4.24
3316 33.875185 70.875 3.20
3317 34.125185 70.875 2.83
3318 34.375185 70.875 3.53
3319 34.625185 70.875 4.24
3320 34.875185 70.875 3.81
3321 35.125185 70.875 1.50
3322 35.375185 70.875 0.51
3323 35.625185 70.875 0.01
3324 35.875185 70.875 0.00
3325 36.125185 70.875 0.01
3326 36.375185 70.875 0.13
3327 36.625185 70.875 0.18
3328 36.875185 70.875 0.22
3329 37.125185 70.875 0.21
3330 37.375185 70.875 0.00
3331 33.125186 70.875 0.00
3332 33.375186 70.875 0.00
3333 33.625186 70.875 0.00
I have tried $ command but could not work. Any help will be highly appreciable.
The expected output will be like this:
x,y(1:365) values.
Assuming you want to subset 365 similar values of X and Y in one group. You can split the data frame w.r.t X and Y using,
split(df, list(df$X, df$Y))
For example in mtcars dataset if you need to split it according to cyl and am column then
split(mtcars,list(mtcars$cyl,mtcars$am))
which would give you output as
#$`4.0`
# mpg cyl disp hp drat wt qsec vs am gear carb
#Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
#Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
#Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
#$`6.0`
# mpg cyl disp hp drat wt qsec vs am gear carb
#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
#$`8.0`
# mpg cyl disp hp drat wt qsec vs am gear carb
#Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
#Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
#Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
#Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
#Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
#Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
#Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
#Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
#Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
#AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
#Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
#Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
#$`4.1`
# 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
#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
#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
#$`6.1`
# mpg cyl disp hp drat wt qsec vs am gear carb
#Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
#Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
#Ferrari Dino 19.7 6 145 175 3.62 2.770 15.50 0 1 5 6
#$`8.1`
# mpg cyl disp hp drat wt qsec vs am gear carb
#Ford Pantera L 15.8 8 351 264 4.22 3.17 14.5 0 1 5 4
#Maserati Bora 15.0 8 301 335 3.54 3.57 14.6 0 1 5 8
