I have columns of numbers and I would need to remove only one min. and one max. and then calculate the average of the numbers that remain. The hitch is that the min/max could be anywhere in the column and some rows may be blank (null) or have a zero, or the column might have only 3 values. All numbers will be between 0 and 100. For example:
Value Property 80 H 30.5 D 40 A 30.5 A 72 H 56 D 64.2 H
If there is more than one min or max, only one can be removed.
To calculate the minimum and maximum of a column, I did as follows:
maximum = df['Value'].max() minimum = df['Value'].min()
In the condition for calculating this average, I also included the condition where it is not null and where it is not equal to zero. However, I do not know how to remove only one max and one min, and add information on greater than 3 rows/values.
I hope you can provide some help/tips on this.
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Answer
If the objective is to calculate the average without one min and one max, you can just do
(df['Value'].sum() - df['Value'].min() - df['Value'].max())/(len(df)-2)
which outputs 52.54 for your data. Note that this will ignore NaNs etc. This will not modify your df which, if I read the question right, was not the objective anyway