python tool output help?

[Matthew]

ive created a density plot using python, and ive managed to print out a series of data points that define the shape of the density plot

i can make it print into the alteryx runtime log, but i cannot make it output through the Alteryx.Write() function

the problem is that i am getting the data points from a loop statement and i dont know how to compile it into a single DataFrame to pass to the write function..

can someone please help?

[TheOC]

hey @Matthew 

You will need to initialise a dataframe prior to the loop, and then append the new data to the dataframe, each iteration of the loop using the following:
https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.append.html 

Hope this helps,
TheOC

[Matthew]

Thank you, I'll give it another try

I have tried this already though. The challenge I'm running into is I can't seem to figure out how to size the data frame to fit the data.. each iteration of the loop appears to contain an entire array of values (one complete layer of the density map)

[Matthew]

I'm getting very close. But two problems remain:

1. It's rounding the value in the 'contourlabel' column.. but i don't understand how or why, because that label is a concatenated string
2. Each contour layer is exiting the python tool as a concatenated array of values.. i can account for this by transforming it in Alteryx.. but i would much rather have it come out of the python tool with each XY pair as a separate row... (and not in scientific notation)

[PhilipMannering]

Hi @Matthew 

Do you want the data points, or is it ultimately just the plot that you want to keep?

[Matthew]

hey @PhilipMannering i still need the original datapoints, but i can always union them together after the macro processes the curves

edit: i see what youre asking.. yes i need the data points that make up each contour. i want to treat each layer as its own spatial object.. in fact, i'm hoping to get even more control over those layers.. i'd love to specify the confidence interval that each layer represents

[KorkuSep]

the solution to the Alteryx Python output problem is with numpy package, the key is to call the np.bool = np.bool_ after you import numpy into your notebook as seen in the image attached. This should solve problem 😎.