Python Numpy/Scipy help - 2D Table Generation

[Frozennova]

Spent some time looking at Numpy for this but I'm totally lost on the method of achieving the result I'm looking for. Coding itself isn't the issue.

And hopefully I can explain this in a way someone can understand...

• The end result should be a 2d table/array.
• X-axis of the table/array are pre-defined bins/values
• The Y-axis should be populated with an average value as read from the input CSV file
• Y-axis values need to be interpolated between the bins

 

[Frozennova]

It isn't quite clear what the issue is here - what have you attempted and where are you getting stuck?

So you want an array to contain some average values - presumably the mean of some values read from the csv file. Each column in the array represents a different value of your independent variable x and presumably is populated with this average of your dependent variable y value in one of the rows and the x values in the other row? So you want an array with two rows and however many columns you need for the x values?

Now you mention interpolation - are you looking to plot the data or is it that for some of the x values you need for the table are you missing corresponding y values? There are a a bunch of interpolation methods available in scipy - though the question of which to use isn't really a programming one.

Where are you actually getting stuck here - creating the array? Calculating an average/mean y value for each x? (Plotting data? if appropriate) Interpolation?

I'm struggling knowing where to start at all

The CSV file will contain Data Points A & B, I then want to generate a list of averages of Data point B for specific values for Data point A.

Generating averages is easy enough to do, but I need to limit the resulting output from potentially 1000 values for Data point A down to a specific set of limited values (32-64)

And while typing this out I think I have just figured it out