Converting column with various types of numerical units

I have a dataframe with a column that has various unit types

The rawNo column is how the data comes in. I would like to change it to look like the ConvNo column

datasample = pd.DataFrame(columns=['rawNo','ConvNo'])

datasample = datasample.append({'rawNo': '-4.35%','ConvNo': -.0435},ignore_index = True)
datasample = datasample.append({'rawNo': '246.6K','ConvNo': 246600},ignore_index = True)
datasample = datasample.append({'rawNo': np.nan,'ConvNo': np.nan},ignore_index = True)
datasample = datasample.append({'rawNo': '$12.76B','ConvNo': 12760000000},ignore_index = True)
datasample = datasample.append({'rawNo': '4.68%','ConvNo': .0468},ignore_index = True)
datasample = datasample.append({'rawNo': '¥-459.5B','ConvNo': -459500000000},ignore_index = True)
datasample = datasample.append({'rawNo': '€-6.8B','ConvNo': -6000000000},ignore_index = True)
datasample = datasample.append({'rawNo': '£-15.623B','ConvNo': -15623000000},ignore_index = True)

I figure I will have to use some type of conditional apply. This apply to remove the percent is failing

def rPercent(value):
    value = str(value)
    count = value.count('%')
    print(count)
    
    if (count != 0):
        return value.str.rstrip('% ').astype('float') / 100.0
    else:
        return value

datasample["ConvNo"] = datasample['actual'].apply(rPercent)

Error I get:

> AttributeError: 'str' object has no attribute 'str'

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