python - Conditional Logic on Pandas DataFrame

Question

How to apply conditional logic to a Pandas DataFrame.

See DataFrame shown below,

   data desired_output
0     1          False
1     2          False
2     3           True
3     4           True

My original data is show in the 'data' column and the desired_output is shown next to it. If the number in 'data' is below 2.5, the desired_output is False.

I could apply a loop and do re-construct the DataFrame... but that would be 'un-pythonic'

Answer 1

In [1]: df
Out[1]:
   data
0     1
1     2
2     3
3     4

You want to apply a function that conditionally returns a value based on the selected dataframe column.

In [2]: df['data'].apply(lambda x: 'true' if x <= 2.5 else 'false')
Out[2]:
0     true
1     true
2    false
3    false
Name: data

You can then assign that returned column to a new column in your dataframe:

In [3]: df['desired_output'] = df['data'].apply(lambda x: 'true' if x <= 2.5 else 'false')

In [4]: df
Out[4]:
   data desired_output
0     1           true
1     2           true
2     3          false
3     4          false