halflife | Half-Life 1 engine based games | Game Engine library

I have time-series data of asset return. Return data frame index are dates and columns are asset names.

I have a text file formatted like this

I'm trying to smooth the closing price with a customer alpha but it does not seem to work. I receive the following message below

I'd like to deal with an input error without defining what the success criteria is i.e. only loop back round the user input turns out to be incorrect. All of the examples I can find require a definition of success.

Rather than list all the possible units as "success" criteria, I'd rather set up the else function to send the user back to the beginning and enter valid units.

I have the following code which uses pint (a scientific unit handling module) which throws and error if a user enters hl_units which is not recognised. This simply kicks the user out of the program on error with a message about what went wrong. I'd like the user to be sent back to re-input if possible.

Basically I load the excel file into a pandas dataframe here:

I have gone from 0 to python 3 in a couple of days, however, I am stuck and would appreciate some help

I had to design a program to calculate radioactive decay (which was a big task for me)

here

I have implemented a simple code which simulates cell life. For some cases it works fine, but for others, it gives a SIGABRT out of range error in line 72(as highlighted). The code essentially takes a vector of cell numbers as input. Then it creates two new vectors, celllife and time vectors, in which it stores the lifetime of the cell and the time elapsed to compare the cell's life. For example, if cell life vectors are

I want to be able to create an aggregate groupby column that is created from an aggregate function that depends on more than just one column of the original dataframe. For example (in this case), I want to compute the exponentially weighted mean of a list of assets with a given half life.

Here is an example where I compute the mean and std from the built in functions and the mean from a lambda function ...

I have labeled event (time series) data where the events occur at random intervals for a given label. I would like to compute the within group ewma and add it to the dataframe as a new column "X1_EWMA". Here's the code so far: