argument of type 'float' is not iterable - TypeError

Question

I am simply applying some filter on data-frame and calculation 1st Quartile, but it shows me error like "TypeError: argument of type 'float' is not iterable". many sources says that it is because of NAN value in your data frame but i can not ignor that row.

# Import pandas 
import pandas as pd
import numpy as np 
outstanding_df = pd.read_csv("outstandings-Pune-PCMC-Nov2019_.csv")
outstanding_df.head()


    Outstandings    YearMonthNum    StoreId StoreName   storepartycode  storepartyname  storepartypincode   storepartyaddress1  storepartyaddress2  RegionId    RegionName  InvoiceAmount   ReceivedAmount  OutstandingBalance
0   Outstandings    201911  1475    TAPADIYA COSMOGEN   6452    MIRA MEDICAL    0.0 BIBVEWADI PUNE  UNITY HEIGHTS   1   Pune    168.0   0.0 168.0
1   Outstandings    201911  1475    TAPADIYA COSMOGEN   9594    MEDICO POINT    411037.0    GANESH CORNERBIBVEWADI  NaN 1   Pune    965.0   0.0 965.0
2   Outstandings    201911  1475    TAPADIYA COSMOGEN   6819    BALAJI MEDICAL  NaN UNDRIHADAPSAR   SHOP NO 4 MAHALAXMI MARKET  1   Pune    3204.0  0.0 3204.0
3   Outstandings    201911  1475    TAPADIYA COSMOGEN   2137    PERFECT MEDICAL GEN STORES  NaN KONDHAWA. NIBM ROAD.    SHOP NO 4 SUNSHREE D2   1   Pune    1719.0  0.0 1719.0
4   Outstandings    201911  1475    TAPADIYA COSMOGEN   8601    SAI MEDICAL GENERAL STORE   NaN NIBM ROAD   SUNSHREE SUNTEC SHOP NO 20  1   Pune    725.0   0.0 725.0

_

outstanding_df['Flag'] = ""
Distributors = ['agency','dist','distributor','pharma','agencies']
for index, row in outstanding_df.iterrows():
    if any(word in row['storepartyname'] for word in Distributors):
        #print(row['storepartyname'])
        outstanding_df.at[index,'Flag']='True' 


# find the quantiles over the index axis
outstanding_df['InvoiceAmount'].quantile(.25) # 4th Quartile data Value 


# Apply Filter for OrderAmount!=True 
a = outstanding_df[outstanding_df['InvoiceAmount']!='True']
print(a['InvoiceAmount'].quantile(.25)) # 4th Quartile data Value

_

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-100-af5f80284d23> in <module>
      5 Distributors = ['agency','dist','distributor','pharma','agencies']
      6 for index, row in outstanding_df.iterrows():
----> 7     if any(word in row['storepartyname'] for word in Distributors):
      8         #print(row['storepartyname'])
      9         outstanding_df.at[index,'Flag']='True'

<ipython-input-100-af5f80284d23> in <genexpr>(.0)
      5 Distributors = ['agency','dist','distributor','pharma','agencies']
      6 for index, row in outstanding_df.iterrows():
----> 7     if any(word in row['storepartyname'] for word in Distributors):
      8         #print(row['storepartyname'])
      9         outstanding_df.at[index,'Flag']='True'

TypeError: argument of type 'float' is not iterable

Sample CSV Data

Outstandings,YearMonthNum,StoreId,StoreName,storepartycode,storepartyname,storepartypincode,storepartyaddress1,storepartyaddress2,RegionId,RegionName,InvoiceAmount,ReceivedAmount,OutstandingBalance
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","6452","MIRA MEDICAL","0","BIBVEWADI PUNE","UNITY HEIGHTS",1,"Pune",168.00,0.00,168.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","9594","MEDICO POINT","411037","GANESH CORNERBIBVEWADI","N/A",1,"Pune",965.00,0.00,965.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","6819","BALAJI MEDICAL","N/A","UNDRIHADAPSAR","SHOP NO 4 MAHALAXMI MARKET",1,"Pune",3204.00,0.00,3204.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","2137","PERFECT MEDICAL  GEN STORES","N/A","KONDHAWA. NIBM ROAD.","SHOP NO 4 SUNSHREE D2",1,"Pune",1719.00,0.00,1719.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","8601","SAI MEDICAL  GENERAL STORE","N/A","NIBM ROAD","SUNSHREE SUNTEC SHOP NO 20",1,"Pune",725.00,0.00,725.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","1820","METRO CHEMIST.","0","KONDHAWA.  26830382","SHOP NO 4NOVEDITA GARDEN",1,"Pune",896.00,0.00,896.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","298","VISHWAS MEDICO","N/A","ERANDWANA PH.5448865","SIDDHARTH APTS.PUNE",1,"Pune",272.00,0.00,272.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","567","MUKESH MEDICALS","0","PAUD ROAD RAMBHAG COL KOTHRUD","RAJDEEP APPT",1,"Pune",201.00,0.00,201.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","8569","GAURAV MEDICAL","N/A","SUDARSHAN APPT. KOTHRUD","SHOP NO 8 SHILAVIHAR COLONY",1,"Pune",979.00,0.00,979.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","10383","SAMRUDHI MEDICAL  SUPER STORE","0","SNEH PARADISE MIT COLLEGE RD","KOTHRUD",1,"Pune",806.00,0.00,806.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","9715","PAVAN CHEMIST","0","SHOP NO-5MANGAL CLASSIC HISSA","OPP SURYAPRABHA PAUD ROAD",1,"Pune",477.00,0.00,477.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","5417","LAXMI MEDICAL","N/A","KOTHRUD SHIVTHIRTHNAGAR","N/A",1,"Pune",1457.00,0.00,1457.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","404","SOURABH MEDICALS  GEN STORES","0","POUD ROAD","PRANJAL COPTV HSG SOC",1,"Pune",2245.00,0.00,2245.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","3604","ROYAL MEDICO","0","PAUD ROAD","RAHUL COMPLEX SHOP NO 23",1,"Pune",1464.00,0.00,1464.00
"Outstandings",201911,551,"Meena Pharma","4221","CENTRAL MEDICAL STORES","0","GRANT MEDICAL FOUNDATION","RUBY HALL CLINIC SASOON ROAD",1,"Pune",21157.00,0.00,21157.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","10070","AAIJI MEDICO","0","KUMAR PRANGANSHOP NO 3","NEAR WARJE KSHETRIYA KARYALAY",1,"Pune",2991.00,0.00,2991.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","319","JEEVAN MEDICALS","N/A","KARVENAGARMADHUBAN COLONY","SHOP NOP 3 38/2",1,"Pune",758.00,0.00,758.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","822","GETWELL MEDICAL","0","ERANDWANE.PH.NO.25451628","PUNE.",1,"Pune",813.00,0.00,813.00
"Outstandings",201911,1475,"TAPADIYA COSMOGEN","4792","MEDICO HOUSE.","0","KOTHRUD 9823250106","SHOP NO 2/3 VARUN COMPLEX",1,"Pune",652.00,0.00,652.00
"Outstandings",201911,15,"New Amar Agencies","4000","SHRI MEDICAL (ST)##","N/A","GHODNADI SHIRUR DR.UPLENCHWAR","GHODNADI SHIRUR DR.UPLENCHWAR",1,"Pune",22547.00,0.00,22547.00
"Outstandings",201911,7,"Anand Medical Distributors","5178","SONY MEDICALS","N/A","KONDHWA","N/A",1,"Pune",552.00,0.00,552.00
"Outstandings",201911,31,"Shah Enterprises","4768","MAULI MEDICAL & GEN STORES","N/A","SIHGAD ROAD","PUNE,",1,"Pune",169.00,0.00,169.00
"Outstandings",201911,31,"Shah Enterprises","7668","SHREE VINAYAK MEDICAL CENTRE","N/A","GHORPADE PETH","PUNE,",1,"Pune",545.00,0.00,545.00
"Outstandings",201911,31,"Shah Enterprises","9791","SHREE KOHINOOR MEDICO ( DHAYARI )","N/A","SHOP NO.2 & 3 NEAR UMBARYA GANPATI","UMBARYA GANPATI MITRA MANDAL",1,"Pune",84.00,0.00,84.00
"Outstandings",201911,33,"Premier Distributors","3642","OM MEDICO & GENERAL ST.","N/A","SHOP NO1  OPP SANSKRUTI APTS   HANDEWADI ROAD  UDYOG NAGAR","HADAPSAR",1,"Pune",114.00,0.00,114.00
"Outstandings",201911,33,"Premier Distributors","7060","KRISHNA MEDICAL & GEN STORES","N/A","SHOP.NO.2, PAARGE CHOWK,","KONDHWA KHURD",1,"Pune",132.00,0.00,132.00
"Outstandings",201911,33,"Premier Distributors","2871","LAXMI MEDICAL & GEN STORES","N/A","NEAR KAWDE HOSPITAL N.D.A.  SHIVANE UTTAMNAGAR PUNE -23","N/A",1,"Pune",167.00,0.00,167.00
"Outstandings",201911,33,"Premier Distributors","10462","SHRI SADGURU KRUPA MEDICAL","N/A","SHOP NO.8 SR.NO.114/115/16","RAGHUNANDAN PLAZA PUNE BANGLORE HIGHWAY",1,"Pune",83.00,0.00,83.00

Answer 1

I resolved the error by just converting row['storepartyname'] into string dynamically like str(row['storepartyname'])

Final working code

outstanding_df['Flag'] = ""
Distributors = ['agency','dist','distributor','pharma','agencies']
for index, row in outstanding_df.iterrows():
    if any(word in str(row['storepartyname']) for word in Distributors):
        #print(row['storepartyname'])
        outstanding_df.at[index,'Flag']='True' 


# find the quantiles over the index axis
outstanding_df['InvoiceAmount'].quantile(.25) # 4th Quartile data Value 


# Apply Filter for OrderAmount!=True 
a = outstanding_df[outstanding_df['InvoiceAmount']!='True']
print(a['InvoiceAmount'].quantile(.25)) # 4th Quartile data Value