Combine columns from two datasets

The cbind function lets you combine datasets by adding columns from one dataset into another. If the datasets contain common column names, H2O will append the joined column with 0.

note

The two datasets you are combining columns from must have the same number of rows.

Python

import h2o
h2o.init()
import numpy as np

# Generate a random dataset with 10 rows 4 columns. 
# Label the columns A, B, C, and D.
cols1_df = h2o.H2OFrame.from_python(np.random.randn(10,4).tolist(), column_names=list('ABCD'))
cols1_df.describe
        A          B          C           D
---------  ---------  ---------  ---------- 
 0.660737  -1.11679    0.278233  -0.0326621
-0.124613  -0.668794   0.558957   1.11402
 0.944408  -1.6397     0.616223   0.137581
 0.739501   0.671192   0.715497  -0.361146
 1.52177    0.232701   0.196153   0.499426
-1.48407    0.222175   2.45155   -0.470239
 0.880962   0.906569  -0.767418   1.38261
 0.509212   0.602155   1.41956    1.96045
 1.11071    0.779309   1.77455   -0.400746
-0.881062  -0.897391   0.980548  -0.266982

[10 rows x 4 columns]

# Generate a second random dataset with 10 rows and 2 columns. 
# Label the columns, Y and Z.
cols2_df = h2o.H2OFrame.from_python(np.random.randn(10,2).tolist(), column_names=list('YZ'))
cols2_df.describe
         Y           Z
----------  ----------
 0.54945     0.0283338
 1.27367    -1.46298
 0.875547    0.317876
 2.12603     0.371443
 0.662796    1.0291
-0.267864    0.86477
-1.51065     0.71466
 0.0676983  -0.844925
 0.311779    0.0397941
 0.363517    0.465146

[10 rows x 2 columns]

# Add the columns from the second dataset into the first. 
# H2O will append these as the right-most columns.
colsCombine_df = cols1_df.cbind(cols2_df)
colsCombine_df.describe
        A          B          C           D           Y           Z
---------  ---------  ---------  ----------  ----------  ----------
 0.660737  -1.11679    0.278233  -0.0326621   0.54945     0.0283338
-0.124613  -0.668794   0.558957   1.11402     1.27367    -1.46298
 0.944408  -1.6397     0.616223   0.137581    0.875547    0.317876
 0.739501   0.671192   0.715497  -0.361146    2.12603     0.371443
 1.52177    0.232701   0.196153   0.499426    0.662796    1.0291
-1.48407    0.222175   2.45155   -0.470239   -0.267864    0.86477
 0.880962   0.906569  -0.767418   1.38261    -1.51065     0.71466
 0.509212   0.602155   1.41956    1.96045     0.0676983  -0.844925
 1.11071    0.779309   1.77455   -0.400746    0.311779    0.0397941
-0.881062  -0.897391   0.980548  -0.266982    0.363517    0.465146

[10 rows x 6 columns]

R

library(h2o)
h2o.init()

# Create two simple, two-column R data frames by inputting values, 
# ensuring that both have a common column (in this case, "fruit").
left <- data.frame(fruit = c('apple', 'orange', 'banana', 'lemon', 'strawberry', 'blueberry'), 
     color = c('red', 'orange', 'yellow', 'yellow', 'red', 'blue'))
right <- data.frame(fruit = c('apple', 'orange', 'banana', 'lemon', 'strawberry', 'watermelon'), 
    citrus = c(FALSE, TRUE, FALSE, TRUE, FALSE, FALSE))

# Create the H2O data frames from the inputted data.
left_frame <- as.h2o(left)
print(left_frame)
        fruit  color
 1      apple    red
 2     orange orange
 3     banana yellow
 4      lemon yellow
 5 strawberry    red
 6  blueberry   blue

[6 rows x 2 columns]

right_frame <- as.h2o(right)
print(right_frame)
        fruit  citrus
 1      apple  FALSE
 2     orange   TRUE
 3     banana  FALSE
 4      lemon   TRUE
 5 strawberry  FALSE
 6 watermelon  FALSE

[6 rows x 2 columns]

# Combine the l.hex and r.hex datasets into a single dataset. 
# The columns from r.hex will be appended to the right side of the final dataset. 
# In addition, because both datasets include a "fruit" column, H2O will append the 
# second "fruit" column name with "0". Note that this is different than ``merge``, 
# which combines data from two commonly named columns in two datasets. 

columns <- h2o.cbind(left_frame, right_frame)
print(columns)
       fruit  color     fruit0 citrus
1      apple    red      apple  FALSE
2     orange orange     orange   TRUE
3     banana yellow     banana  FALSE
4      lemon yellow      lemon   TRUE
5 strawberry    red strawberry  FALSE
6  blueberry   blue watermelon  FALSE

[6 rows x 4 columns]

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