Example 1: Determining the Standard Deviation of the Single DataFrame Column The following example is used to determine the standard deviation of the single DataFrame column. The “df.std()” computes the standard deviation of the single column “score_1”. Here is a code: import pandas import...
The higher the value of the standard deviation of returns, the higher will be the volatility of returns. High volatility means that high risk was apparent during the investment period. For a fund that has an average return of 7.5% and returns in its subperiods were 13%, 11%, 2%, 6%, ...
But this trick won't work for computing the standard deviation. My final attempts were : df.get_values().mean() df.get_values().std() Except that in the latter case, it uses mean() and std() function from numpy. It's not a problem for the mean, but it is for std, as ...
Step 1 − Create a function to find the standard deviation. Step 2 − In this function, find the site of the array using the count property. Step 3 − Use for loop to iterate through each element of the array and find their sum. Step 4 − Calculate the mean by dividing the ...
calc.median(my_data, value_var): The weighted median ofvalue_var, equivalent to.quantile(...)whereq=0.5. calc.std(my_data, value_var): The weighted standard deviation ofvalue_var. calc.distribution(my_data, value_var): The weighted proportions ofvalue_var, interpretingvalue_varas categories...