Applying various log function to full data frame in H2O

The follow code shows how to apply various log function to a full data frame or a particular column into data frame:

// Use h2o
import h2o
h2o.init()

// Creating a new data frame and then converting it to H2O data frame
c_names = [‘Num’, ‘Prediction’]
data1 = np.array([[1, 0.12],
 [2, 0.43],
 [3,0.90],
 [4,0.002],
 [5,0.52]])
df = h2o.H2OFrame().from_python(data1, destination_frame=‘df’, column_names=c_names)

// Printing H2O Dataframe
print “df:\n”,df

// Applying log1p
df = df.log1p()

// Applying log()
df = df.log()

// Applying log2
df = df.log2()

// Applying log10
df = df.log10()

// Applying log 10 to only a column
df['Num'] = df['Num'].log10()

 

Thats it, Enjoy!!

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