Converting Object to Dataframe and it is giving me Value, Name, and dtype in each cell

Question

I am running a for loop off a regression per item within a multi-item dataset.
I want to output to give me the price point at the max revenue point of the parameters set in the np.arrange.
Here is the code I am working with:

upc_modelfit_summary = []
upcs = df['upc'].unique()

for x in upcs:
    
    df_upc = df[(df['upc'] == x)]     
    max_val = df_upc['arp_np'].max()
    min_val = df_upc['arp_np'].min()
    price = np.arange(min_val, max_val, 0.1)
    cost = .50
    model = ols("units_np ~ arp_np", data=df_upc).fit()
    quantity = []
    revenue = []
    
    for i in price:
     demand = model.params[0] + (model.params[1] * i)
     quantity.append(demand)
     revenue.append((i-cost) * demand)
    profit = pd.DataFrame({"Price": price, "Revenue": revenue, "Quantity": quantity, "UPC": x})
    max_val = profit.loc[(profit['Revenue'] == profit['Revenue'].max())]
    upc_modelfit_summary.append(
        {
            'Price': max_val['Price'],
            'Revenue': max_val['Revenue'],
            'Quantity': max_val['Quantity'],
            'UPC': max_val['UPC']
        })

a= pd.DataFrame(upc_modelfit_summary)
a

I would like to create a dataframe that compiles the price, revenue, quantity, and upc for each item that is looped.

For some reason when converting this to a dataframe it is giving me the values, names, and dtypes of each cell value (see image)

Is there a better way to do this? Ideally the end result would be a df that could be exported in some fashion.

Price   Revenue Quantity    UPC
0   4 4.49 Name: Price, dtype: float64  4 3.99 Name: Revenue, dtype: float64    4 1.0 Name: Quantity, dtype: float64    4 00-28400-04330 Name: UPC, dtype: object

enter image description here

Asked By: Ryan McConnell

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Source

Answer 1

The issue is that you’re adding the entire data-frame max_val[Col] into the upc_modelfit_summary dictionary instead of just the value. Change the upc_modelfit_summary.append() line to this:

 upc_modelfit_summary.append(
    {
        'Price': max_val['Price'].values[0] if max_val['Price'].values.size > 0 else np.nan,
        'Revenue': max_val['Revenue'].values[0] if max_val['Revenue'].values.size > 0 else np.nan,
        'Quantity': max_val['Quantity'].values[0] if max_val['Quantity'].values.size > 0 else np.nan,
        'UPC': max_val['UPC'].values[0] if max_val['UPC'].values.size > 0 else np.nan
    })

Answered By: Marcelo Paco

Converting Object to Dataframe and it is giving me Value, Name, and dtype in each cell

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