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Exchange of variables

Three ways of transferring variables

Magic %get and %put





In [1]:



    


n=5



    











In [2]:



    


%get n
rn <- rnorm(n)



    











In [3]:



    


%get rn --from R
rn



    


















    
Out[3]:








[-0.717208726490722,
 -0.716307792602076,
 0.210121660734453,
 -1.50107629089392,
 0.105600079729086]

















In [4]:



    


rn = [x+1 for x in rn]



    











In [5]:



    


%put rn --to R



    











In [6]:



    


rn



    


















    







    
	
  1. 0.282791273509278
    2. 
	
  2. 0.283692207397924
    3. 
	
  3. 1.21012166073445
    4. 
	
  4. -0.50107629089392
    5. 
	
  5. 1.10560007972909
    6.

Magic %with





In [7]:



    


n=5



    











In [8]:



    


%with R -i n -o rn
rn <- rnorm(n)



    











In [9]:



    


rn



    


















    
Out[9]:








[-0.200078426229837,
 -0.425017555400589,
 0.749107473681659,
 -0.333266605572932,
 1.09653643921428]

sos-named Variables





In [10]:



    


sos_n = 5



    











In [11]:



    


sos_rn <- rnorm(sos_n)



    











In [12]:



    


sos_rn



    


















    
Out[12]:








[-0.493718017873675,
 0.00641199595342825,
 3.18527800389836,
 -0.53589119458946,
 1.3786041453922]

Transfer variables of other types





In [13]:



    


a = 3
b = c(3, 2, 1)



    











In [14]:



    


%get a b --from R



    











In [15]:



    


a



    


















    
Out[15]:








3

















In [16]:



    


b



    


















    
Out[16]:








[3, 2, 1]

















In [17]:



    


%get mtcars --from R
mtcars



    


















    






Loading required package: feather










    
Out[17]:











  
    

      
      mpg
      cyl
      disp
      hp
      drat
      wt
      qsec
      vs
      am
      gear
      carb
    

  
  
    

      Mazda RX4
      21.0
      6.0
      160.0
      110.0
      3.90
      2.620
      16.46
      0.0
      1.0
      4.0
      4.0
    

    

      Mazda RX4 Wag
      21.0
      6.0
      160.0
      110.0
      3.90
      2.875
      17.02
      0.0
      1.0
      4.0
      4.0
    

    

      Datsun 710
      22.8
      4.0
      108.0
      93.0
      3.85
      2.320
      18.61
      1.0
      1.0
      4.0
      1.0
    

    

      Hornet 4 Drive
      21.4
      6.0
      258.0
      110.0
      3.08
      3.215
      19.44
      1.0
      0.0
      3.0
      1.0
    

    

      Hornet Sportabout
      18.7
      8.0
      360.0
      175.0
      3.15
      3.440
      17.02
      0.0
      0.0
      3.0
      2.0
    

    

      Valiant
      18.1
      6.0
      225.0
      105.0
      2.76
      3.460
      20.22
      1.0
      0.0
      3.0
      1.0
    

    

      Duster 360
      14.3
      8.0
      360.0
      245.0
      3.21
      3.570
      15.84
      0.0
      0.0
      3.0
      4.0
    

    

      Merc 240D
      24.4
      4.0
      146.7
      62.0
      3.69
      3.190
      20.00
      1.0
      0.0
      4.0
      2.0
    

    

      Merc 230
      22.8
      4.0
      140.8
      95.0
      3.92
      3.150
      22.90
      1.0
      0.0
      4.0
      2.0
    

    

      Merc 280
      19.2
      6.0
      167.6
      123.0
      3.92
      3.440
      18.30
      1.0
      0.0
      4.0
      4.0
    

    

      Merc 280C
      17.8
      6.0
      167.6
      123.0
      3.92
      3.440
      18.90
      1.0
      0.0
      4.0
      4.0
    

    

      Merc 450SE
      16.4
      8.0
      275.8
      180.0
      3.07
      4.070
      17.40
      0.0
      0.0
      3.0
      3.0
    

    

      Merc 450SL
      17.3
      8.0
      275.8
      180.0
      3.07
      3.730
      17.60
      0.0
      0.0
      3.0
      3.0
    

    

      Merc 450SLC
      15.2
      8.0
      275.8
      180.0
      3.07
      3.780
      18.00
      0.0
      0.0
      3.0
      3.0
    

    

      Cadillac Fleetwood
      10.4
      8.0
      472.0
      205.0
      2.93
      5.250
      17.98
      0.0
      0.0
      3.0
      4.0
    

    

      Lincoln Continental
      10.4
      8.0
      460.0
      215.0
      3.00
      5.424
      17.82
      0.0
      0.0
      3.0
      4.0
    

    

      Chrysler Imperial
      14.7
      8.0
      440.0
      230.0
      3.23
      5.345
      17.42
      0.0
      0.0
      3.0
      4.0
    

    

      Fiat 128
      32.4
      4.0
      78.7
      66.0
      4.08
      2.200
      19.47
      1.0
      1.0
      4.0
      1.0
    

    

      Honda Civic
      30.4
      4.0
      75.7
      52.0
      4.93
      1.615
      18.52
      1.0
      1.0
      4.0
      2.0
    

    

      Toyota Corolla
      33.9
      4.0
      71.1
      65.0
      4.22
      1.835
      19.90
      1.0
      1.0
      4.0
      1.0
    

    

      Toyota Corona
      21.5
      4.0
      120.1
      97.0
      3.70
      2.465
      20.01
      1.0
      0.0
      3.0
      1.0
    

    

      Dodge Challenger
      15.5
      8.0
      318.0
      150.0
      2.76
      3.520
      16.87
      0.0
      0.0
      3.0
      2.0
    

    

      AMC Javelin
      15.2
      8.0
      304.0
      150.0
      3.15
      3.435
      17.30
      0.0
      0.0
      3.0
      2.0
    

    

      Camaro Z28
      13.3
      8.0
      350.0
      245.0
      3.73
      3.840
      15.41
      0.0
      0.0
      3.0
      4.0
    

    

      Pontiac Firebird
      19.2
      8.0
      400.0
      175.0
      3.08
      3.845
      17.05
      0.0
      0.0
      3.0
      2.0
    

    

      Fiat X1-9
      27.3
      4.0
      79.0
      66.0
      4.08
      1.935
      18.90
      1.0
      1.0
      4.0
      1.0
    

    

      Porsche 914-2
      26.0
      4.0
      120.3
      91.0
      4.43
      2.140
      16.70
      0.0
      1.0
      5.0
      2.0
    

    

      Lotus Europa
      30.4
      4.0
      95.1
      113.0
      3.77
      1.513
      16.90
      1.0
      1.0
      5.0
      2.0
    

    

      Ford Pantera L
      15.8
      8.0
      351.0
      264.0
      4.22
      3.170
      14.50
      0.0
      1.0
      5.0
      4.0
    

    

      Ferrari Dino
      19.7
      6.0
      145.0
      175.0
      3.62
      2.770
      15.50
      0.0
      1.0
      5.0
      6.0
    

    

      Maserati Bora
      15.0
      8.0
      301.0
      335.0
      3.54
      3.570
      14.60
      0.0
      1.0
      5.0
      8.0
    

    

      Volvo 142E
      21.4
      4.0
      121.0
      109.0
      4.11
      2.780
      18.60
      1.0
      1.0
      4.0
      2.0
    

  




















In [18]:



    


%sessioninfo



    


















    







SoS





SoS Version
0.9.16.8






R





Kernel
ir





Language
R






R version 3.5.0 (2018-04-23)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS Sierra 10.12.5

Matrix products: default
BLAS/LAPACK: /Users/bpeng1/anaconda3/envs/JupyterCon18/lib/libopenblasp-r0.2.20.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] feather_0.3.1

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.18    digest_0.6.15   crayon_1.3.4    IRdisplay_0.5.0
 [5] repr_0.15.0     jsonlite_1.5    magrittr_1.5    evaluate_0.11  
 [9] pillar_1.3.0    rlang_0.2.2     stringi_1.2.4   uuid_0.1-2     
[13] IRkernel_0.8.11 tools_3.5.0     stringr_1.3.1   hms_0.4.2      
[17] compiler_3.5.0  pkgconfig_2.0.2 base64enc_0.1-3 htmltools_0.3.6
[21] pbdZMQ_0.3-3    tibble_1.4.2

Content source: vatlab/SOS

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