R language Combat-Advanced data Management (4)

6. Integration and Refactoring

6.1 Transpose

> Mtcars MPG cyl disp hp Drat wt Qsec VS AM gear Carbmazda RX4 21 6 160 110 3.9 2.6 0 1 4 4Mazda RX4 Wag 6 3.9 2.9 0 1 4 4Datsun 710 23 4 108 9   3 3.8 2.3 1 1 4 1Hornet 4 Drive 6 258 3.1 3.2 1 0 3 1Hornet sportabout 19           8 175 3.1 3.4 0 0 3 2Valiant 6 225 1Duster 2.8 3.5 1 0 3 360 8 245 3.2 3.6 0 0 3 4Merc 240D 4 147 3.7 3.2 1 0 4 2Merc     4 141 3.9 3.1 1 0 4 2MERC 280 19 6 168 123 3.9 3.4 18 1 0 4  4MERC 280C 6 168 123 3.9 3.4 1 0 4 4Merc 450SE 16 8 276 180 3.1 4.1 17  0 0 3 3Merc 450SL 8 276 3.1 3.7 0 0 3 3Merc 450SLC 15 8 276 180 3.1    3.8 18 0) 0 33Cadillac Fleetwood 8 472 205 2.9 5.2 0 0 3 4Lincoln Continental 10 8 460 215 3.0 5.4 18 0    0 3 4Chrysler Imperial 8 3.2 5.3 0 0 3 4Fiat 128 32 4 79 66 4.1 2.2 1 1 4 1Honda Civic 4 4.9 1.6 1 1 4 2Toyota Corolla 34 4 71 6   5 4.2 1.8 1 1 4 1Toyota Corona 4 1Dodge 3.7 2.5 1 0 3 Challenger 16           8 318 2.8 3.5 0 0 3 2AMC Javelin 8 304 2Camaro 3.1 3.4 0 0 3 Z28 8 245 3.7 3.8 0 0 3 4Pontiac Firebird 8 2Fiat 175 3.1 3.8 0 0 3     X1-9 4 4.1 1.9 1 1 4 1Porsche 914-2 26 4 120 91 4.4 2.1 17 0 1 5  2Lotus Europa 4 113 3.8 1.5 1 1 5 2Ford Pantera L 16 8 351 264 4.2 3.2 14 0 1 5 4Ferrari DIno 6 145 175 3.6 2.8 0 1 5 6Maserati Bora 15 8 301 335 3.5 3.6 15 0 1 5                  8Volvo 142E 4 121 109 4.1 2.8 1 1 4 2> > > Cars <-mtcars[1:5, 1:4]> cars   MPG cyl disp Hpmazda RX4 6 110Mazda RX4 Wag 6 110Datsun 710 23 4 108 93Hornet 4 Drive 6 258 110Hornet sportabout 8 175> t (Cars) Mazda RX4 Mazda RX4 Wag Dat          Sun 710 Hornet 4 Drive Hornet Sportaboutmpg 19cyl               6 6 4 6 8disp 160 160 108 258  360HP 175>

6.2 Consolidating data

> Options (digits=3) > Attach (mtcars) > AggData <-Aggregate (Mtcars, By=list (cyl,gear), Fun=mean, Na.rm=true) > AggData  group.1 group.2  MPG cyl disp  hp drat   wt qsec  vs   am Gear CARB1       4       3 21.5   4  3.70 2.46 20.0 1.0 0.00    3 1.002       6       3 19.8   6  242 108 2.92 3.34 19.8 1.0 0.00    3 1.003       8       3 15.1   8  358 194 3.12 4.10 17.1 0.0 0.00    3 3.084       4       4 26.9   4  103  4.11 2.38 19.6 1.0 0.75    4 1.505       6       4 19.8   6 164 by  3.91 3.09 17.7 0.5 0.50
   
    4 4.006       4       5 28.2   4  108 102 4.10 1.83 16.8 0.5 1.00    5 2.007       6       5 19.7   6  145 1 3.62 2.77 15.5 0.0 1.00    5 6.008       8       5 15.4   8  326 300 3.88 3.37 14.6 0.0 1.00    
   

6.3 Reshape Bag

> ID <-C (1,1,2,2) > Time <-C (1,2,1,2) > X1 <-C (5,3,6,2) > X2 <-C (6,5,1,4) > MyData <-data.f Rame (ID, time, X1, X2) > MyData  ID time X1 X21  1    1  5  1    2 3  /  2    1  6  2    2  2  4

6.3.1 Fusion

> Library (Reshape) > MD <-Melt (MyData, id= (c ("id", "Time")) > MD  ID time variable value1  1    1< C20/>x1  1    2       X1  2    1       X1  2    2       X1     25  1    1       X2  1    2       X2 2 1       X2    2       2 X2     

6.3.2 Re-casting

> Library (reshape) > MD <-Melt (MyData, id=c ("id", "Time")) > MD ID Time       Variable value1 1 1 x1 1 2 x1 2 1 x1 2 2 x1 25 1 1 X2 1 2 x2 2 1 x2 2 2 x2 4> cast (MD, id~variable, mean) ID x 1 x21 1 4 5.52 2 4 2.5> cast (MD, time~variable, mean) time X1 x21 1 5.5 3.52 2 2.5 4.5> cast (MD, Id~ti    Me, mean) ID 1 1 5.5 2 3.5 3> cast (MD, id+time~variable) ID time x1 x21 1 1 5 62 1 2 3 53 2 1 6 2 2 2 4> cast (MD, id+variable~time) ID variable 1 1 x1 5 1 x2 6 2 x1 6 2       4 2 x2 1 4> cast (MD, id+variable~time) ID variable 1 1 x1 5 + 1 x2 6 2 X1 6 24 2 X2 1 4> CAST (MD, id~variable+time) ID x1_1 x1_2 x2_1 x2_21 1 5 3 6 2 6 2 1 4> 

R language Combat-Advanced data Management (4)