Weekly Challenges

PhilipMannering · ‎07-27-2023

Solution attached. Nice work @BS_THE_ANALYST !

from ayx import Alteryx
df = Alteryx.read('#1')

df = df.melt(id_vars=['Employee ID', 'Employee Name'])
df.value = df.value.astype(int)


#################################
# Create a running total of value
df['running_total'] = df.groupby('Employee ID').cumsum()


#################################
# Filter running total to be greater than 0
df = df[df.running_total > 0]


#################################
# Take the first three per employee and average
df.groupby('Employee ID').sample(3)\
    .groupby(['Employee ID', 'Employee Name']).value.mean()\
    .round(2).reset_index()

from ayx import Alteryx df = Alteryx.read('#1') df = df.melt(id_vars=['Employee ID', 'Employee Name']) df.value = df.value.astype(int) ################################# # Create a running total of value df['running_total'] = df.groupby('Employee ID').cumsum() ################################# # Filter running total to be greater than 0 df = df[df.running_total > 0] ################################# # Take the first three per employee and average df.groupby('Employee ID').sample(3)\ .groupby(['Employee ID', 'Employee Name']).value.mean()\ .round(2).reset_index()