Let's compare data prepping in Alteryx and Python.
We'll start with Alteryx in this Blogpost and continue with Python next time.
The Challenge
As an example we will use a simplified version of this data prep challenge:
Our Data lies in two .csv files:
The last three columns can be ommited, as they are not used in this solution.
Also Pokemon without a second and third stage shall be filtered out.
Our goal is to calculate a combat_score for every pokemon by summing all columns from hp to speed and add the values of the first and last stage as columns to the pkm_evolutions.csv table. Then add a column pwr_increase which shows the relative increase in power between first and last stage.
The Alteryx Solution
My Solution in Alteryx has roughly four segments:
- Transpose the columns relevant for combat_power and sum those values using group by name:
- successively join by name and stage 1-3 ("name"="stage_X"):
- union results with two stages and with three stages together:
- calculate first and last combat_pwr aswell as combat_pwr_increase:
And done. Now the resulting table matches our goal!
Up next: creating the same table from the same data, but in Python.