I am passing a column called petrol['tax'] of a dataframe to a function using .apply which returns 1st quartile. I am trying to use the below code but it throws me this error 'float' object has no attribute 'quantile'.
def Quartile(petrol_attrib):
return petrol_attrib.quantile(.25)
petrol['tax'].apply(Quartile)
I need help to implement this.
df = pd.DataFrame(np.array([[1, 1], [2, 10], [3, 100], [4, 100]]),
columns=['a', 'b'])
Now you can use the quantile function in pandas. Make sure you using the numbers between 0 and 1. Here an example below:
df.a.quantile(0.5)
3.25
You can apply the function to the whole dataframe
The apply function serializes the object that is passed to it and performs the function on each element individually. You can call quantile() on a DataFrame or a Series (unlike some other answers have stated) but you can't call it on a float. You are effectively trying to call quantile() on every element of the Series, since each element in the series is a float and .quantile() doesn't work on floats, that's why you are getting an error.
I recommend simply calling petrol['tax'].quantile(.25) directly. However, if you prefer to keep your custom function, just pass the Series to it directly rather than using .apply(): Quartile(petrol['tax'])
You can use the quartile function on a data frame, not series. You can use the same method by writing petrol[['tax']] instead of petrol['tax']. The version below is the modified one:
def Quartile(petrol_attrib):
return petrol_attrib.quantile(.25)
petrol[['tax']].apply(Quartile)
qcut