how to generate n number of columns based on rows in previous column data in python, I am very new to python, pandas data frames

Question

I have csv file data as below

ModelNumber  Variables
----------   ----------
 208          TotalTerms 
 208          Children 
 208          Property
 208          isMarried 
 207          HasLoan
 207          Children

how to generate below output

ModelNumber  Variable1   Variable2   Variable3   Variable4
----------   ----------  ----------  ----------  ----------
208         TotalTerms   Children    Property    isMarried
207         HasLoan      Children

Answer 1

I think a better case for your problem is to use pivot_table and define each variable as column instead of variable1, variable2, etc... And simply use 1/0 (True/False)for each variable in each model number:

df_1 = pd.DataFrame({'ModelNumber':[208,208,208,208,207,207],
                    'Variables':['TotalTerms','Children','Property','isMarried','HasLoan','Children']})
df_output = pd.pivot_table(df_1,index='ModelNumber',columns='Variables',aggfunc=len)
print(df_output)

Output:

Variables    Children  HasLoan  Property  TotalTerms  isMarried
ModelNumber                                                    
207                 1        1         0           0          0
208                 1        0         1           1          1

Answer 2

I'll write steps so it will be easier for you.

Step 1: Read csv file

Step 2: While reading put data in the dict (we want to have data like ModelNumber as a key and Variables as an array elements), if the variable value is in the dict then append it's value to the array, if not, add its key to the dict with empty array as a value and then add this variable to the array.

Example data representation based on your data:

{
    "208": ["TotalTerms", "Children", "Property", "isMarried"],
    "207": ["HasLoan", "Children"]
}

Step 3: export this data back to csv