TypeError: '<' not supported between instances of 'NoneType' and 'float'

What @Taras Mogetich wrote was pretty correct, however you might need to put the if-statement in its own for-loop. Liko so:

for row in hqm_dataframe.index:
    for time_period in time_periods:
    
        change_col = f'{time_period} Price Return'
        percentile_col = f'{time_period} Return Percentile'
        if hqm_dataframe.loc[row, change_col] == None:
            hqm_dataframe.loc[row, change_col] = 0.0

And then separately:

for row in hqm_dataframe.index:
    for time_period in time_periods:
    
        change_col = f'{time_period} Price Return'
        percentile_col = f'{time_period} Return Percentile'

        hqm_dataframe.loc[row, percentile_col] = score(hqm_dataframe[change_col], hqm_dataframe.loc[row, change_col])

I'm working through this tutorial as well. I looked deeper into the data in the four '___ Price Return' columns. Looking at my batch API call, there's four rows that have the value 'None' instead of a float which is why the 'NoneError' appears, as the percentileofscore function is trying to calculate the percentiles using 'None' which isn't a float.

To work around this API error, I manually changed the None values to 0 which calculated the Percentiles, with the code below...

time_periods = [
                'One-Year',
                'Six-Month',
                'Three-Month',
                'One-Month'
                ]

for row in hqm_dataframe.index:
    for time_period in time_periods:
        if hqm_dataframe.loc[row, f'{time_period} Price Return'] == None:
            hqm_dataframe.loc[row, f'{time_period} Price Return'] = 0

Funny to google the problem I'm having and it's literally the exact same tutorial you're working through!

As mentioned, some data from the API call has a value of None, which causes an error with the percentileofscore function. My solution is to convert all None type to integer 0 upon initial creation of the hqm_dataframe.

hqm_columns = [
    'Ticker',
    'Price',
    'Number of Shares to Buy',
    'One-Year Price Return',
    'One-Year Return Percentile',
    'Six-Month Price Return',
    'Six-Month Return Percentile',
    'Three-Month Price Return',
    'Three-Month Return Percentile',
    'One-Month Price Return',
    'One-Month Return Percentile'
]

hqm_dataframe = pd.DataFrame(columns=hqm_columns)
convert_none = lambda x : 0 if x is None else x

for symbol_string in symbol_strings:
    batch_api_call_url = f'https://sandbox.iexapis.com/stable/stock/market/batch?symbols={symbol_string}&types=price,stats&token={IEX_CLOUD_API_TOKEN}'
    data = requests.get(batch_api_call_url).json()
    
    for symbol in symbol_string.split(','):
        hqm_dataframe = hqm_dataframe.append(
            pd.Series(
                [
                    symbol,
                    data[symbol]['price'],
                    'N/A',
                    convert_none(data[symbol]['stats']['year1ChangePercent']),
                    'N/A',
                    convert_none(data[symbol]['stats']['month6ChangePercent']),
                    'N/A',
                    convert_none(data[symbol]['stats']['month3ChangePercent']),
                    'N/A',
                    convert_none(data[symbol]['stats']['month1ChangePercent']),
                    'N/A'
                ],
                index = hqm_columns
            ),
            ignore_index=True
        )