adding boolean column in pandas dataframe

Question

with this code i want to create boolean column check to check if the value in the column LTP is in the range of 0.10% of column val.

all values are of type float.

   df = df.assign(upper_range=lambda x: (x['val'] +(x['val'] * 0.001)))
   df = df.assign(lower_range=lambda x: ( x['val']- (x['val'] * 0.001) ) )
   df = df.assign(check=lambda x: (x['LTP'] >= x['lower_range'] & x['LTP'] <= x['upper_range']))

this code gave error

    TypeError: ufunc 'bitwise_and' not supported for the input types, 
    and the inputs could not be safely coerced to any supported types according to the casting rule 
    ''safe''

    TypeError: unsupported operand type(s) for &: 'float' and 'float'

for comparison i also tried using and instead of & for which following error occured

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

how to fix this?

jezrael · Accepted Answer · 2021-04-20 11:35:42Z

1

There is not closed () correctly, need parantheses for each condition:

 df = df.assign(check=lambda x: (x['LTP'] >= x['lower_range']) & (x['LTP'] <= x['upper_range']))

answered Apr 20, 2021 at 11:35

jezrael

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1 Comment

jezrael Over a year ago

@user4599 - Unfortunately no experiece with flask, so cannot help you.

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