CODEWITHSUNDEEP
pythonpandasdataframe
SoftwareTurtle
SoftwareTurtle

Reputation: 43

"TypeError: 'DataFrame' object is not callable"

I'm trying to compute the mean age of blonde people from the data in df:

np.random.seed(0)
df = pd.DataFrame(
    {
        'Age': [18, 21, 28, 19, 23, 22, 18, 24, 25, 20],
        'Hair colour': [
            'Blonde', 'Brown', 'Black', 'Blonde', 'Blonde',
            'Black','Brown', 'Brown', 'Black', 'Black'],
        'Length (in cm)': np.random.normal(175, 10, 10).round(1),
        'Weight (in kg)': np.random.normal(70, 5, 10).round(1)},
    index=[
        'Leon', 'Mirta', 'Nathan', 'Linda', 'Bandar',
        'Violeta', 'Noah', 'Niji', 'Lucy', 'Mark'],)

I need to get the one number.

Firstly, I attempted to use the "df.divide".

import pandas as pd
import numpy as np

ans_3 = df({'Age'}).divide(df({'Hair colour': ['Blonde']}))

However, I have got this TypeError: 'DataFrame' object is not callable.

What should I do for working my code that I'll get the appropriate result?

Upvotes: -1

Views: 7886

Answers (4)

DrWhat
DrWhat

Reputation: 2490

If this happens when loading a sheet from excel into a dataframe using xlwings, you may have accidentally added (), like so to the code:

df = alreadyLoadedSheet.range("a1:b1").options(pd.DataFrame).value()

Remove the empty brackets, remove the error.

df = alreadyLoadedSheet.range("a1:b1").options(pd.DataFrame).value

Upvotes: 0

Maxime Lavaud
Maxime Lavaud

Reputation: 127

As it has been pointed out, the errors arises since you are using parenthesis that are made to call a callable object as a function for exemple. Instead you should use brackets that are make for slicing and select data.

As an advice I would suggest you to use the groupby method to check population statistics. Here if you want to know the mean value of your observables a function of the Hair color you can do :

df.groupby("Hair colour").mean()

that would return you the following

Hair colour Age Length (in cm) Weight (in kg)
Black 23.75 175.775 70.7
Blonde 20.0 194.5666666666667 71.16666666666667
Brown 21.0 179.0 74.60000000000001

you can thus see that the average age for Blonde people is 20.

If you want to retrieve this particular value you can do :

df.groupby("Hair colour").mean()["Age"]["Blonde"]

Upvotes: 0

Valdi_Bo
Valdi_Bo

Reputation: 31011

Run:

df[df['Hair colour'] == 'Blonde'].Age.mean()

Details:

  • df['Hair colour'] == 'Blonde' - generates a Series of bool type, stating whether the current row has Blonde hair.
  • df[…] - get rows meeting the above condition.
  • Age - from the above rows take only Age column.
  • mean() - compute the mean age.

Upvotes: 0

Michael Kopp
Michael Kopp

Reputation: 1711

You get this error because you use df(..). This is the python syntax to call a function. You probably want df[..] instead.

To answer your question:

(
    df  # given your data
      [df["Hair colour"] == "Blonde"]  # only look at blonde people
    ["Age"]  # for those in the Age column
    .mean()  # and compute the mean
)

Upvotes: 1

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