'numpy.float64' object has no attribute 'apply'

Question

I'm trying to change a cell value (colour 'red' or 'green') based on a value of another cell. I run the following:

df.loc[0, 'Colour'] = df.loc[0, 'Count'].apply(lambda x: 'Red' if x <= 500 
    else 'Green')

I get the following error:

AttributeError: 'numpy.float64' object has no attribute 'apply'

any help is greatly appreciated

Answer 1

When you use df.loc[0, 'Count'] you are only returning the item that is actually that location which is a float. apply is a method of a Pandas or numpy series so you need to have a Series class to use that method. So most likely you want to do something like this but without a test data set it's hard to know.

df['Colour'] = df['Count'].apply(lambda x: 'Red' if x <=500 else 'Green')

Creating a test dataset shows you how this works all together:

import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randint(0,1000,size=(10, 4)), columns=list('ABCD'))
df['Colour'] = df['A'].apply(lambda x: 'Red' if x <=500 else 'Green')
df.head()

Which returns:

    A   B   C   D   Colour
0   223 360 133 285 Red
1   300 125 642 238 Red
2   118 293 442 382 Red
3   448 357 55  124 Red
4   995 395 658 559 Green

If you want to use .loc to access the whole column you can use df.loc[:, 'Count'] You can read more about the .loc method here