## Converting 9 sales volume and percentage lists for 9 business units
l_keeper = [list() for _ in range(8)]
s_keeper = [0] * 8 
lp_keeper = [list() for _ in range(8)]

detailed_cust=list()
detailed_cust=pd.DataFrame(detailed_cust,columns=["BU Anchor","BU Diamond","BU Direct Fastening","BU Fire Protection","BU Measuring Systems","BU Power Tools & Acc","BU Screw Fastening","BU Tool Services","Other"])
detailed_cust
l0=list()
l1=list()
l2=list()
l3=list()
l4=list()
l5=list()
l6=list()
l7=list()
l8=list()
s0=0
s1=0
s2=0
s3=0
s4=0
s5=0
s6=0
s7=0
s8=0
lp0=list()
lp1=list()
lp2=list()
lp3=list()
lp4=list()
lp5=list()
lp6=list()
lp7=list()
lp8=list()
for i in np.arange(0,len(piedata),1):
    for bu in np.arange(0,len(piedata[i]),1):
        
        if piedata[i].iloc[bu].butext==bulist[0]:
            l0.append(piedata[i].iloc[bu]["try"])
            lp0.append(piedata[i].iloc[bu]["percantage (%)"])
            s0=1
        elif piedata[i].iloc[bu].butext==bulist[1]:
            l1.append(piedata[i].iloc[bu]["try"])
            lp1.append(piedata[i].iloc[bu]["percantage (%)"])
            s1=1
        elif piedata[i].iloc[bu].butext==bulist[2]:
            l2.append(piedata[i].iloc[bu]["try"])
            lp2.append(piedata[i].iloc[bu]["percantage (%)"])
            s2=1
        elif piedata[i].iloc[bu].butext==bulist[3]:
            l3.append(piedata[i].iloc[bu]["try"])
            lp3.append(piedata[i].iloc[bu]["percantage (%)"])
            s3=1
        elif piedata[i].iloc[bu].butext==bulist[4]:
            l4.append(piedata[i].iloc[bu]["try"])
            lp4.append(piedata[i].iloc[bu]["percantage (%)"])
            s4=1
        elif piedata[i].iloc[bu].butext==bulist[5]:
            l5.append(piedata[i].iloc[bu]["try"])
            lp5.append(piedata[i].iloc[bu]["percantage (%)"])
            s5=1
        elif piedata[i].iloc[bu].butext==bulist[6]:
            l6.append(piedata[i].iloc[bu]["try"])
            lp6.append(piedata[i].iloc[bu]["percantage (%)"])
            s6=1
        elif piedata[i].iloc[bu].butext==bulist[7]:
            l7.append(piedata[i].iloc[bu]["try"])
            lp7.append(piedata[i].iloc[bu]["percantage (%)"])
            s7=1
        elif piedata[i].iloc[bu].butext==bulist[8]:
            l8.append(piedata[i].iloc[bu]["try"])
            lp8.append(piedata[i].iloc[bu]["percantage (%)"])
            s8=1
    if s0==0:
        l0.append(0)
        lp0.append(0)
    if s1==0:
        l1.append(0)
        lp1.append(0)
    if s2==0:
        l2.append(0)
        lp2.append(0)
    if s3==0:
        l3.append(0)
        lp3.append(0)
    if s4==0:
        l4.append(0)
        lp4.append(0)
    if s5==0:
        l5.append(0)
        lp5.append(0)
    if s6==0:
        l6.append(0)
        lp6.append(0)
    if s7==0:
        l7.append(0)
        lp7.append(0)
    if s8==0:
        l8.append(0)
        lp8.append(0)
    s0=0
    s1=0
    s2=0
    s3=0
    s4=0
    s5=0
    s6=0
    s7=0
    s8=0
     
    ## list to dataframe
     
l0=pd.DataFrame(l0)
l1=pd.DataFrame(l1)
l2=pd.DataFrame(l2)
l3=pd.DataFrame(l3)
l4=pd.DataFrame(l4)
l5=pd.DataFrame(l5)
l6=pd.DataFrame(l6)
l7=pd.DataFrame(l7)
l8=pd.DataFrame(l8)
lp0=pd.DataFrame(lp0)
lp1=pd.DataFrame(lp1)
lp2=pd.DataFrame(lp2)
lp3=pd.DataFrame(lp3)
lp4=pd.DataFrame(lp4)
lp5=pd.DataFrame(lp5)
lp6=pd.DataFrame(lp6)
lp7=pd.DataFrame(lp7)
lp8=pd.DataFrame(lp8)

## Merging every customer sales volume with each other
bu_sales_per_customer=l0.merge(l1,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l2,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l3,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l4,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l5,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l6,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l7,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l8,left_index=True, right_index=True)
## Setting new sales per customerdataframe's column names

bu_sales_per_customer.columns=["BU Anchor","BU Diamond","BU Direct Fastening","BU Fire Protection","BU Measuring Systems","BU Power Tools & Acc","BU Screw Fastening","BU Tool Services","Other"]

## Same for percentage too

bu_percentage_per_customer=lp0.merge(lp1,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp2,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp3,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp4,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp5,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp6,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp7,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp8,left_index=True, right_index=True)

## Setting new bu_percentage_per_customer dataframe's column names

bu_percentage_per_customer.columns=["BU Anchor","BU Diamond","BU Direct Fastening","BU Fire Protection","BU Measuring Systems","BU Power Tools & Acc","BU Screw Fastening","BU Tool Services","Other"]

## Calculating confidance intervals for Sales volume and Sales percentage for each customer

rp.summary_cont(bu_sales_per_customer[["BU Anchor","BU Diamond","BU Direct Fastening","BU Fire Protection","BU Measuring Systems","BU Power Tools & Acc","BU Screw Fastening","BU Tool Services","Other"]].head(8))
## Stats about sales per customer
bu_sales_per_customer_head_8.describe().T

bu_sales_per_customer[(bu_sales_per_customer["try"]>50000)&(bu_sales_per_customer["try"]<100000)].describe().T

61cd53c7fbd2e697c2dde435e089623fd6654fd5
<mask token>

<mask token>
detailed_cust
<mask token>
for i in np.arange(0, len(piedata), 1):
    for bu in np.arange(0, len(piedata[i]), 1):
        if piedata[i].iloc[bu].butext == bulist[0]:
            l0.append(piedata[i].iloc[bu]['try'])
            lp0.append(piedata[i].iloc[bu]['percantage (%)'])
            s0 = 1
        elif piedata[i].iloc[bu].butext == bulist[1]:
            l1.append(piedata[i].iloc[bu]['try'])
            lp1.append(piedata[i].iloc[bu]['percantage (%)'])
            s1 = 1
        elif piedata[i].iloc[bu].butext == bulist[2]:
            l2.append(piedata[i].iloc[bu]['try'])
            lp2.append(piedata[i].iloc[bu]['percantage (%)'])
            s2 = 1
        elif piedata[i].iloc[bu].butext == bulist[3]:
            l3.append(piedata[i].iloc[bu]['try'])
            lp3.append(piedata[i].iloc[bu]['percantage (%)'])
            s3 = 1
        elif piedata[i].iloc[bu].butext == bulist[4]:
            l4.append(piedata[i].iloc[bu]['try'])
            lp4.append(piedata[i].iloc[bu]['percantage (%)'])
            s4 = 1
        elif piedata[i].iloc[bu].butext == bulist[5]:
            l5.append(piedata[i].iloc[bu]['try'])
            lp5.append(piedata[i].iloc[bu]['percantage (%)'])
            s5 = 1
        elif piedata[i].iloc[bu].butext == bulist[6]:
            l6.append(piedata[i].iloc[bu]['try'])
            lp6.append(piedata[i].iloc[bu]['percantage (%)'])
            s6 = 1
        elif piedata[i].iloc[bu].butext == bulist[7]:
            l7.append(piedata[i].iloc[bu]['try'])
            lp7.append(piedata[i].iloc[bu]['percantage (%)'])
            s7 = 1
        elif piedata[i].iloc[bu].butext == bulist[8]:
            l8.append(piedata[i].iloc[bu]['try'])
            lp8.append(piedata[i].iloc[bu]['percantage (%)'])
            s8 = 1
    if s0 == 0:
        l0.append(0)
        lp0.append(0)
    if s1 == 0:
        l1.append(0)
        lp1.append(0)
    if s2 == 0:
        l2.append(0)
        lp2.append(0)
    if s3 == 0:
        l3.append(0)
        lp3.append(0)
    if s4 == 0:
        l4.append(0)
        lp4.append(0)
    if s5 == 0:
        l5.append(0)
        lp5.append(0)
    if s6 == 0:
        l6.append(0)
        lp6.append(0)
    if s7 == 0:
        l7.append(0)
        lp7.append(0)
    if s8 == 0:
        l8.append(0)
        lp8.append(0)
    s0 = 0
    s1 = 0
    s2 = 0
    s3 = 0
    s4 = 0
    s5 = 0
    s6 = 0
    s7 = 0
    s8 = 0
<mask token>
rp.summary_cont(bu_sales_per_customer[['BU Anchor', 'BU Diamond',
    'BU Direct Fastening', 'BU Fire Protection', 'BU Measuring Systems',
    'BU Power Tools & Acc', 'BU Screw Fastening', 'BU Tool Services',
    'Other']].head(8))
bu_sales_per_customer_head_8.describe().T
bu_sales_per_customer[(bu_sales_per_customer['try'] > 50000) & (
    bu_sales_per_customer['try'] < 100000)].describe().T

l_keeper = [list() for _ in range(8)]
s_keeper = [0] * 8
lp_keeper = [list() for _ in range(8)]
detailed_cust = list()
detailed_cust = pd.DataFrame(detailed_cust, columns=['BU Anchor',
    'BU Diamond', 'BU Direct Fastening', 'BU Fire Protection',
    'BU Measuring Systems', 'BU Power Tools & Acc', 'BU Screw Fastening',
    'BU Tool Services', 'Other'])
detailed_cust
l0 = list()
l1 = list()
l2 = list()
l3 = list()
l4 = list()
l5 = list()
l6 = list()
l7 = list()
l8 = list()
s0 = 0
s1 = 0
s2 = 0
s3 = 0
s4 = 0
s5 = 0
s6 = 0
s7 = 0
s8 = 0
lp0 = list()
lp1 = list()
lp2 = list()
lp3 = list()
lp4 = list()
lp5 = list()
lp6 = list()
lp7 = list()
lp8 = list()
for i in np.arange(0, len(piedata), 1):
    for bu in np.arange(0, len(piedata[i]), 1):
        if piedata[i].iloc[bu].butext == bulist[0]:
            l0.append(piedata[i].iloc[bu]['try'])
            lp0.append(piedata[i].iloc[bu]['percantage (%)'])
            s0 = 1
        elif piedata[i].iloc[bu].butext == bulist[1]:
            l1.append(piedata[i].iloc[bu]['try'])
            lp1.append(piedata[i].iloc[bu]['percantage (%)'])
            s1 = 1
        elif piedata[i].iloc[bu].butext == bulist[2]:
            l2.append(piedata[i].iloc[bu]['try'])
            lp2.append(piedata[i].iloc[bu]['percantage (%)'])
            s2 = 1
        elif piedata[i].iloc[bu].butext == bulist[3]:
            l3.append(piedata[i].iloc[bu]['try'])
            lp3.append(piedata[i].iloc[bu]['percantage (%)'])
            s3 = 1
        elif piedata[i].iloc[bu].butext == bulist[4]:
            l4.append(piedata[i].iloc[bu]['try'])
            lp4.append(piedata[i].iloc[bu]['percantage (%)'])
            s4 = 1
        elif piedata[i].iloc[bu].butext == bulist[5]:
            l5.append(piedata[i].iloc[bu]['try'])
            lp5.append(piedata[i].iloc[bu]['percantage (%)'])
            s5 = 1
        elif piedata[i].iloc[bu].butext == bulist[6]:
            l6.append(piedata[i].iloc[bu]['try'])
            lp6.append(piedata[i].iloc[bu]['percantage (%)'])
            s6 = 1
        elif piedata[i].iloc[bu].butext == bulist[7]:
            l7.append(piedata[i].iloc[bu]['try'])
            lp7.append(piedata[i].iloc[bu]['percantage (%)'])
            s7 = 1
        elif piedata[i].iloc[bu].butext == bulist[8]:
            l8.append(piedata[i].iloc[bu]['try'])
            lp8.append(piedata[i].iloc[bu]['percantage (%)'])
            s8 = 1
    if s0 == 0:
        l0.append(0)
        lp0.append(0)
    if s1 == 0:
        l1.append(0)
        lp1.append(0)
    if s2 == 0:
        l2.append(0)
        lp2.append(0)
    if s3 == 0:
        l3.append(0)
        lp3.append(0)
    if s4 == 0:
        l4.append(0)
        lp4.append(0)
    if s5 == 0:
        l5.append(0)
        lp5.append(0)
    if s6 == 0:
        l6.append(0)
        lp6.append(0)
    if s7 == 0:
        l7.append(0)
        lp7.append(0)
    if s8 == 0:
        l8.append(0)
        lp8.append(0)
    s0 = 0
    s1 = 0
    s2 = 0
    s3 = 0
    s4 = 0
    s5 = 0
    s6 = 0
    s7 = 0
    s8 = 0
l0 = pd.DataFrame(l0)
l1 = pd.DataFrame(l1)
l2 = pd.DataFrame(l2)
l3 = pd.DataFrame(l3)
l4 = pd.DataFrame(l4)
l5 = pd.DataFrame(l5)
l6 = pd.DataFrame(l6)
l7 = pd.DataFrame(l7)
l8 = pd.DataFrame(l8)
lp0 = pd.DataFrame(lp0)
lp1 = pd.DataFrame(lp1)
lp2 = pd.DataFrame(lp2)
lp3 = pd.DataFrame(lp3)
lp4 = pd.DataFrame(lp4)
lp5 = pd.DataFrame(lp5)
lp6 = pd.DataFrame(lp6)
lp7 = pd.DataFrame(lp7)
lp8 = pd.DataFrame(lp8)
bu_sales_per_customer = l0.merge(l1, left_index=True, right_index=True)
bu_sales_per_customer = bu_sales_per_customer.merge(l2, left_index=True,
    right_index=True)
bu_sales_per_customer = bu_sales_per_customer.merge(l3, left_index=True,
    right_index=True)
bu_sales_per_customer = bu_sales_per_customer.merge(l4, left_index=True,
    right_index=True)
bu_sales_per_customer = bu_sales_per_customer.merge(l5, left_index=True,
    right_index=True)
bu_sales_per_customer = bu_sales_per_customer.merge(l6, left_index=True,
    right_index=True)
bu_sales_per_customer = bu_sales_per_customer.merge(l7, left_index=True,
    right_index=True)
bu_sales_per_customer = bu_sales_per_customer.merge(l8, left_index=True,
    right_index=True)
bu_sales_per_customer.columns = ['BU Anchor', 'BU Diamond',
    'BU Direct Fastening', 'BU Fire Protection', 'BU Measuring Systems',
    'BU Power Tools & Acc', 'BU Screw Fastening', 'BU Tool Services', 'Other']
bu_percentage_per_customer = lp0.merge(lp1, left_index=True, right_index=True)
bu_percentage_per_customer = bu_percentage_per_customer.merge(lp2,
    left_index=True, right_index=True)
bu_percentage_per_customer = bu_percentage_per_customer.merge(lp3,
    left_index=True, right_index=True)
bu_percentage_per_customer = bu_percentage_per_customer.merge(lp4,
    left_index=True, right_index=True)
bu_percentage_per_customer = bu_percentage_per_customer.merge(lp5,
    left_index=True, right_index=True)
bu_percentage_per_customer = bu_percentage_per_customer.merge(lp6,
    left_index=True, right_index=True)
bu_percentage_per_customer = bu_percentage_per_customer.merge(lp7,
    left_index=True, right_index=True)
bu_percentage_per_customer = bu_percentage_per_customer.merge(lp8,
    left_index=True, right_index=True)
bu_percentage_per_customer.columns = ['BU Anchor', 'BU Diamond',
    'BU Direct Fastening', 'BU Fire Protection', 'BU Measuring Systems',
    'BU Power Tools & Acc', 'BU Screw Fastening', 'BU Tool Services', 'Other']
rp.summary_cont(bu_sales_per_customer[['BU Anchor', 'BU Diamond',
    'BU Direct Fastening', 'BU Fire Protection', 'BU Measuring Systems',
    'BU Power Tools & Acc', 'BU Screw Fastening', 'BU Tool Services',
    'Other']].head(8))
bu_sales_per_customer_head_8.describe().T
bu_sales_per_customer[(bu_sales_per_customer['try'] > 50000) & (
    bu_sales_per_customer['try'] < 100000)].describe().T

## Converting 9 sales volume and percentage lists for 9 business units
l_keeper = [list() for _ in range(8)]
s_keeper = [0] * 8 
lp_keeper = [list() for _ in range(8)]

detailed_cust=list()
detailed_cust=pd.DataFrame(detailed_cust,columns=["BU Anchor","BU Diamond","BU Direct Fastening","BU Fire Protection","BU Measuring Systems","BU Power Tools & Acc","BU Screw Fastening","BU Tool Services","Other"])
detailed_cust
l0=list()
l1=list()
l2=list()
l3=list()
l4=list()
l5=list()
l6=list()
l7=list()
l8=list()
s0=0
s1=0
s2=0
s3=0
s4=0
s5=0
s6=0
s7=0
s8=0
lp0=list()
lp1=list()
lp2=list()
lp3=list()
lp4=list()
lp5=list()
lp6=list()
lp7=list()
lp8=list()
for i in np.arange(0,len(piedata),1):
    for bu in np.arange(0,len(piedata[i]),1):
        
        if piedata[i].iloc[bu].butext==bulist[0]:
            l0.append(piedata[i].iloc[bu]["try"])
            lp0.append(piedata[i].iloc[bu]["percantage (%)"])
            s0=1
        elif piedata[i].iloc[bu].butext==bulist[1]:
            l1.append(piedata[i].iloc[bu]["try"])
            lp1.append(piedata[i].iloc[bu]["percantage (%)"])
            s1=1
        elif piedata[i].iloc[bu].butext==bulist[2]:
            l2.append(piedata[i].iloc[bu]["try"])
            lp2.append(piedata[i].iloc[bu]["percantage (%)"])
            s2=1
        elif piedata[i].iloc[bu].butext==bulist[3]:
            l3.append(piedata[i].iloc[bu]["try"])
            lp3.append(piedata[i].iloc[bu]["percantage (%)"])
            s3=1
        elif piedata[i].iloc[bu].butext==bulist[4]:
            l4.append(piedata[i].iloc[bu]["try"])
            lp4.append(piedata[i].iloc[bu]["percantage (%)"])
            s4=1
        elif piedata[i].iloc[bu].butext==bulist[5]:
            l5.append(piedata[i].iloc[bu]["try"])
            lp5.append(piedata[i].iloc[bu]["percantage (%)"])
            s5=1
        elif piedata[i].iloc[bu].butext==bulist[6]:
            l6.append(piedata[i].iloc[bu]["try"])
            lp6.append(piedata[i].iloc[bu]["percantage (%)"])
            s6=1
        elif piedata[i].iloc[bu].butext==bulist[7]:
            l7.append(piedata[i].iloc[bu]["try"])
            lp7.append(piedata[i].iloc[bu]["percantage (%)"])
            s7=1
        elif piedata[i].iloc[bu].butext==bulist[8]:
            l8.append(piedata[i].iloc[bu]["try"])
            lp8.append(piedata[i].iloc[bu]["percantage (%)"])
            s8=1
    if s0==0:
        l0.append(0)
        lp0.append(0)
    if s1==0:
        l1.append(0)
        lp1.append(0)
    if s2==0:
        l2.append(0)
        lp2.append(0)
    if s3==0:
        l3.append(0)
        lp3.append(0)
    if s4==0:
        l4.append(0)
        lp4.append(0)
    if s5==0:
        l5.append(0)
        lp5.append(0)
    if s6==0:
        l6.append(0)
        lp6.append(0)
    if s7==0:
        l7.append(0)
        lp7.append(0)
    if s8==0:
        l8.append(0)
        lp8.append(0)
    s0=0
    s1=0
    s2=0
    s3=0
    s4=0
    s5=0
    s6=0
    s7=0
    s8=0
     
    ## list to dataframe
     
l0=pd.DataFrame(l0)
l1=pd.DataFrame(l1)
l2=pd.DataFrame(l2)
l3=pd.DataFrame(l3)
l4=pd.DataFrame(l4)
l5=pd.DataFrame(l5)
l6=pd.DataFrame(l6)
l7=pd.DataFrame(l7)
l8=pd.DataFrame(l8)
lp0=pd.DataFrame(lp0)
lp1=pd.DataFrame(lp1)
lp2=pd.DataFrame(lp2)
lp3=pd.DataFrame(lp3)
lp4=pd.DataFrame(lp4)
lp5=pd.DataFrame(lp5)
lp6=pd.DataFrame(lp6)
lp7=pd.DataFrame(lp7)
lp8=pd.DataFrame(lp8)

## Merging every customer sales volume with each other
bu_sales_per_customer=l0.merge(l1,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l2,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l3,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l4,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l5,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l6,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l7,left_index=True, right_index=True)
bu_sales_per_customer=bu_sales_per_customer.merge(l8,left_index=True, right_index=True)
## Setting new sales per customerdataframe's column names

bu_sales_per_customer.columns=["BU Anchor","BU Diamond","BU Direct Fastening","BU Fire Protection","BU Measuring Systems","BU Power Tools & Acc","BU Screw Fastening","BU Tool Services","Other"]

## Same for percentage too

bu_percentage_per_customer=lp0.merge(lp1,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp2,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp3,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp4,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp5,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp6,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp7,left_index=True, right_index=True)
bu_percentage_per_customer=bu_percentage_per_customer.merge(lp8,left_index=True, right_index=True)

## Setting new bu_percentage_per_customer dataframe's column names

bu_percentage_per_customer.columns=["BU Anchor","BU Diamond","BU Direct Fastening","BU Fire Protection","BU Measuring Systems","BU Power Tools & Acc","BU Screw Fastening","BU Tool Services","Other"]

## Calculating confidance intervals for Sales volume and Sales percentage for each customer

rp.summary_cont(bu_sales_per_customer[["BU Anchor","BU Diamond","BU Direct Fastening","BU Fire Protection","BU Measuring Systems","BU Power Tools & Acc","BU Screw Fastening","BU Tool Services","Other"]].head(8))
## Stats about sales per customer
bu_sales_per_customer_head_8.describe().T

bu_sales_per_customer[(bu_sales_per_customer["try"]>50000)&(bu_sales_per_customer["try"]<100000)].describe().T
