How to define a function that calculates the BMI from dataframe

[DavidGG]

I need to define a function that will calculate and return out of dataframe that includes columns "Height" and "Weight", the BMI of each row.

Here is the code that i wrote:

def BMI(DataFrame):
    df=pd.DataFrame
    return 'Weight'/'Height'**2

But when I try to run that function with:

data.apply(BMI,axis=1)

when "data" is my dataframe,

the result is an error:

Error:
Traceback (most recent call last):
  File "<input>", line 1, in <module>
  File "D:\Python Projects\venv\lib\site-packages\pandas\core\frame.py", line 6487, in apply
    return op.get_result()
  File "D:\Python Projects\venv\lib\site-packages\pandas\core\apply.py", line 151, in get_result
    return self.apply_standard()
  File "D:\Python Projects\venv\lib\site-packages\pandas\core\apply.py", line 257, in apply_standard
    self.apply_series_generator()
  File "D:\Python Projects\venv\lib\site-packages\pandas\core\apply.py", line 286, in apply_series_generator
    results[i] = self.f(v)
  File "<input>", line 3, in BMI
TypeError: ("'type' object is not subscriptable", 'occurred at index 0')

What went wrong with my code?

[heiner55]

#!/usr/bin/python3
import pandas as pd

data = [
  { 'h': 1.80, 'w': 80 },
  { 'h': 1.70, 'w': 90 },
  { 'h': 1.60, 'w': 60 },
]

df = pd.DataFrame(data)
print(df)
print("------------------")

def BMI(data):
    return data['w'] / data['h']**2

df['bmi'] = df.apply(BMI, axis=1)
print(df)

Output:
     h   w
0  1.8  80
1  1.7  90
2  1.6  60
------------------
     h   w        bmi
0  1.8  80  24.691358
1  1.7  90  31.141869
2  1.6  60  23.437500

[volcano63]

#!/usr/bin/python3
import pandas as pd

data = [
  { 'h': 1.80, 'w': 80 },
  { 'h': 1.70, 'w': 90 },
  { 'h': 1.60, 'w': 60 },
]

df = pd.DataFrame(data)
print(df)
print("------------------")

def BMI(data):
    return data['w'] / data['h']**2

df['bmi'] = df.apply(BMI, axis=1)
print(df)

Output:
     h   w
0  1.8  80
1  1.7  90
2  1.6  60
------------------
     h   w        bmi
0  1.8  80  24.691358
1  1.7  90  31.141869
2  1.6  60  23.437500

There are better ways with pandas - you can operate on rows/columns directly

df['bmi'] = df.w / df.h ** 2

Output:
	h	w	bmi
0	1.8	80	24.691358
1	1.7	90	31.141869
2	1.6	60	23.437500