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Pivot tables

Use this function to pivot tables. This is performed by designating three columns: index, column, and value.

  • Index is the column where pivoted rows should be aligned on.
  • Column represents the column to pivot.
  • Value specifies the values of the pivoted table.

For cases with multiple indexes for a column label, the aggregation method is to pick the first occurrence in the data frame.

note
  • All rows of a single index value must fit on one node.
  • The maximum rows for a single index value and column label is Chunk size * Chunk size.
import h2o
h2o.init()

# Create a simple data frame by inputting values
df = h2o.H2OFrame({'colorID': ['1','2','3','3','1','4'],
                   'value': ['red','orange','yellow','yellow','red','blue'],
                   'amount': ['4','2','4','3','6','3']})

# View the dataset
df
colorID      amount  value
---------  --------  -------
        1         4  red
        2         2  orange
        3         4  yellow
        3         3  yellow
        1         6  red
        4         3  blue

[6 rows x 3 columns]

# Pivot the table on the colorID column and aligned on the amount column
df2 = df.pivot(index="amount",column="colorID",value="value")
df2
  amount    1    2    3    4
--------  ---  ---  ---  ---
       2  nan    1  nan  nan
       3  nan  nan    3    0
       4    2  nan    3  nan
       6    2  nan  nan  nan

[4 rows x 5 columns]
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