Vfrdtyky

The situation:

I have a pandas dataframe where I have some data about the production of a product. The product is produced in 3 phases. The phases are not fixed meaning that their cycles (the time till last) is changing. During the production phases, at each cycle the temperature of the product is measured.

Please see the table below:

The problem:

I need to calculate the slope for each cycle of each phase for each product. I also need to add it to the dataframe in a new column called "Slope". The one you can see, highlighted in yellow was added by me manually in an excel file. The real dataset contains hundreds of parameters (not only temperatures) so in reality I need to calculate the slope for many, many columns, therefore I tried to define a function.

My solution is not working at all:

This is the code I tried, but it does not work. I am trying to catch the first and last row for the given product, for the given phase. And then get the temperature data and the difference of these two rows. And this way I could calculate the slope.
This is all I could come up with so far (I created another column called: "Max_cylce_no", this stores the maximum amount of the cycle for each phase):

temp_at_start=-1



def slope(col_name):

    global temp_at_start

    start_cycle_no = 1

    if row["Cycle"]==1:

        temp_at_start =row["Temperature"]

        start_row = df.index(row)





    cycle_numbers = row["Max_cylce_no"] 

    last_cycle_row = cycle_numbers + start_row





    last_temp = df.loc[last_cycle_row, "Temperature"]

And the way I would like to apply it:

df.apply(slope("Temperature"), axis=1)

Unfortunatelly I get a NameError right away saying that: name 'row' is not defined.

Could you please help me and show me the right direction on how to solve this problem. It gives me a really hard time. :(

Thank you in advance!

I believe you need GroupBy.transform with subtract last value with first and divide by length:

f = lambda x: (x.iloc[-1] - x.iloc[0]) / len(x)

df['new'] = df.groupby(['Product_no','Phase_no'])['Temperature'].transform(f)