New column in Pandas dataframe based on boolean conditions

Question

I\'d like to create a new column to a Pandas dataframe populated with True or False based on the other values in each specific row. My approach to solve this task was to app

Answer 1

You should work column-wise (vectorised, efficient) rather than row-wise (inefficient, Python loop):

df1['ops_on'] = (df1['Feed'] > 10) & (df1['Pressure'] > 10) & (df1['Temp'] > 10)

The & ("and") operator is applied to Boolean series element-wise. An arbitrary number of such conditions can be chained.

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Alternatively, for the special case where you are performing the same comparison multiple times:

df1['ops_on'] = df1[['Feed', 'Pressure', 'Temp']].gt(10).all(1)

Answer 2

In your current setup, just re-write your function like this:

def ops_on(row):
    return (row['Feed'] > 10) & (row['Pressure'] > 10) & (row['Temp'] > 10)