woe | Performance analysis functions , plot ROC curve

I am currently struggling with a problem I am having with rest calls to an AWS s3 API hosted by a rados/ceph gateway.

For reasons I wont go into, I can't use an SDK that is provided to talk to it, which would solve all of my woes - I'm recreating some of the more simple jobs I need via CURL - which in the most part work, I can make buckets, delete them, add objects, create roles but my newest problem is bucket policies, both GET for them and PUT. I receive a 403 every time and I cannot figure out why.

What I have attempted to do is use another box with an SDK that talks to the API (boto3) and the AWS s3API calls to do the same thing and they work perfectly fine with the users Access and Secret key, so I do not think its an account thing.

Using the logs from the SDK jobs, I have attempted to recreate everything that is being sent, headers, payload etc...

Now I can only think that as a 403 maybe its the Auth4 strategy but .... this strategy works for every other job I need to do.

Code:

I am having no end of trouble installing loom-truffle-provider.

node = v14.18.1 npm = 6.14.15 Linux Ubuntu 20.04

I can try installing locally or globally. Both fail with below error:

I have this panda dataframe:

and I need to add a color gradient fill in the WoE column, so that it looks like this:

Does anyone know if and how to do that?

I would like the plot to show, from left to right on the x axis, an increasing line. So, the x axis needs to be in this order:

J H G C A B E F D I K L

Then the line would be increasing from left to right.

I'm using the category encoder package in Python to use the Weight of Evidence encoder.

After I define an encoder object and fit it to data, the columns I wanted to encode are correctly replaced by their Weight of Evidence (WoE) values, according to which category they belong to.

So my question is, how can I obtain the mapping defined by the encoder? For example, let's say I have a variable with categories "A", "B" and "C". The respective WoE values could be 0.2, -0.4 and 0.02. But how can I know that 0.2 corresponds to the category "A"?

I tried acessing the "mapping" attribute, by using:

I have an MS Project VSTO add-in I'm working on. I created a WPF form and I want to click a button and show a indeterminate progress bar on the UI while a method runs. I was able to achieve this by wrapping the method in a Task.Run(), the only problem is running the method asynchronously seems to be about 30 times slower than running it normally. The method I'm calling interacts with objects from the Office.Interop.MSProject library, so I'm not sure if this is an Office or COM thing that's causing my performance woes.

I am creating an osgi component like this:

I have an excel table which has 4 columns - Index, Bin, WoR, feature_name. The table shows the Bin ranges and the weight of evidence (WoE) for several variables var1 to varn.

I have imported the excel into a pandas dataframe and would like to extract the lower and upper limits into separate columns as shown in the table below. I wrote the code below to perform this function. However I get 98.5 and 99.5 for lower_limit and upper_limit respectively. So this code is not working. Any suggestions where I might be doing it wrong?

The final goal of this exercise is to automatically generate python code which has list of macros (def) to bin the variables. If there is a better approach, I would like to hear that as well.

I have a pyspark sc initialized.