Llibyddap

import pandas as pd
import re
import numpy as np

data= [['Empty','CMI-General Liability | 05-9632','Empty','Empty'],['Empty','Central Operations','Empty','Empty'],['Empty','Alarm Central 05-8642','Empty','Empty'],['Empty','Market 466','Empty','Empty'],['Empty','Talent, Experience','Empty','Empty'],['Empty','Food Division','Empty','Empty'],['Empty','Quality WMCC','Empty','Empty'],['Empty','Modular Execution Team | 01-9700','Empty','Empty'],['Empty','US Central Operations','Empty','Empty'],['Empty','CE - Engineering - US','Empty','Empty'],['Empty','Fresh, Freezer & Cooler - 18-8110','Empty','Empty'],['Empty','9701','Empty','Empty'],['Empty','Contact Center','Empty','Empty'],['Empty','Central Operations','Empty','Empty'],['Empty','US Central Operations','Empty','Empty'],['Empty','Private Brands GM - 01-8683','Empty','Empty']]
df2=pd.DataFrame(data,columns=['JobTitle','Department','TrueDepartment','Dept_Function'])

data5 = [[1,'TRUCKING, MARCY, NY','Empty','Empty'],[2,'TRUCKING-GREENVILLE,TN','Empty','Empty'],[

Llibyddap

import pandas as pd
import numpy as np

df = df_flat = pd.DataFrame({"BS": ['BS1 - BS5', 'BS2 - BS7', 'BS1 - BS9', 'BS9 - BS1'],
                   "N" : [1, 2, 2, 1]})

df = df.pivot(columns='BS',
              values='N')

df_flat = df_flat.pivot_table(