Determine employee level for each day

Question

I'm trying to determine an employee's depth in the organization by each day. The top level (CEO) is Level 1, their direct reports are level 2, etc.

I was able to calculate w/o date but having trouble calculating employee level for each day. Here's what I've done:

import pandas as pd

# setup df
df = pd.DataFrame({'date': ['3/29/2020', '3/29/2020', '3/29/2020', '3/30/2020', '3/30/2020', '3/30/2020', '3/30/2020'],
                   'empid': [1, 2, 3, 1, 2, 3, 4], 'mgrid': [0, 1, 2, 0, 1, 1, 2]})

# create dictionary
dct = dict(zip(df['empid'].values, df['mgrid'].values))

# function to create employee level
def level(empid):
    top = 1
    while (dct[empid]) != 0:
        top += 1
        empid = dct[empid]
    return top

#apply level
df['level'] = df['empid'].apply(level)

current output

expected output

user_3545273 · Answer

You could use a groupby and pass the dct dict per day:

def level(empid, dct):
    top = 1
    while (dct[empid]) != 0:
        top += 1
        empid = dct[empid]
    return top

def dflevel(x):
    dct = dict(zip(x['empid'].values, x['mgrid'].values))
    return x['empid'].apply(level, args=[dct])

df['level'] = df.groupby('date').apply(dflevel).values

It gives as expected:

        date  empid  mgrid  level
0  3/29/2020      1      0      1
1  3/29/2020      2      1      2
2  3/29/2020      3      2      3
3  3/30/2020      1      0      1
4  3/30/2020      2      1      2
5  3/30/2020      3      1      2
6  3/30/2020      4      2      3

Determine employee level for each day

1 Answers