Pandas Table Scrape

I am trying to figure the best approach of converting a table into JSON records. At present I have the output as desired however the format of the table is puzzling me a little. Th

Solution 1:

The output dict line is not the same that you expected, but your dict sintax was wrong. Try this. Only with Pandas

p=[[123,"Test Item 1","Electric","Elctrotech","60%"], [124,"Test Item 2","Wood"," TY Toys","100%"],[125,"Test Item 1","Plastic","NA Materials","100%"], [123,"Test Item 1","Foo","Bar","80%"], [123,"Test Item 1","Electric","TRY TRY TRY","70%"]]

x=pd.DataFrame(p, columns=["ID","Product","Item_Material","Owner","Interest %"])

d=dict(ID="", Item_Material="", Owners={"Owner":[], "Interest %":[]})
x_gb=x.groupby(["Product", "Item_Material"])
grouped_Series_Owner = x_gb["Owner"].apply(list).to_dict()
grouped_Series_Interest = x_gb["Interest %"].apply(list).to_dict()
for k in out.keys():
    d["Item_Material"]=out[k]["Item_Material"]
    d["ID"]=out[k]["Product"]
    d["Owners"]["Owner"]= grouped_Series_Owner[(out[k]["Product"], out[k]["Item_Material"])]
    d["Owners"]["Interest %"]= grouped_Series_Interest[(out[k]["Product"], out[k]["Item_Material"])]
    print(d)