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I tried to reinstall one of my old vue projects on my new computer (on Windows 10) with npm but I came across this error :

I have a very particular set of logic I am attempting to implement into Python which is clearly beyond my current understanding.

I will outlay the concept in steps, then post the code attempts below:

1. Identify if the value within two separate columns qualifies (>= and <= 0.5) - if this is True then .append() the value of the third column (at the exact same Datetime index the test was passed) to a separate time Series object.
2. ELIF: identify if the value within the first two columns qualifies (<= and >= 0.5) - if this is True then .append() the value of the fourth column (at the exact same Datetime index the test was passed) to a separate time series object (the same one from the first test).
3. the final object is a separate time series object which holds values from column 3 and column 4 in chronological order from when each test was passed.

Here are the codes I have attempted thus far:

I have two tables:

I just coded a model similar to this:

and this is the code:

I have built an auto encoder in Keras, that accepts multiple inputs and the same umber of outputs that I would like to convert into a variational auto encoder. I am having trouble to combine the loss of the difference between input and output and the loss of the variational part.

The auto encoder should be used for a data set containing both numeric and categorical data. To do so I normalize the numerical columns and 1-hot-encode the categorical columns. Since the resulting categorical vectors and the numerical vectors require different loss functions (mean-sqaured-error for the numerical, and categorical cross-entropy for the categorical columns) and the very large 1-hot encoding vectors would dominate the loss as compared to the small numerical columns, I have decided to put each column as its own input vector. Thus my auto encoder accepts a set of input vectors generates output vectors of the same number and shapes.

This is a setup for two numeric inputs and two categorical ones with 20 and 30 wide 1-hot encoding:

I am trying to train a cnn-lstm model, my sample image sizes are 640x640.

I have a GTX 1080 ti 11GB.

I am using Keras with tensorflow backend.

Here is the model.

I have below dataframe, want to separate date and text from the field "Indicator_NameB" and I have written function "String_Year_Pick_V2"

Data:

The navigation buttons on a GitHub hosted website don't take me to the page, and I am unsure how to fix it.

I am very new to GitHub, but am looking to make a webpage for the lab I work in. I found an existing lab webpage (https://github.com/KordingLab/KordingLab.github.io) that allows you to make forks and edit it for your own purposes, which was a great base. I've since changed the repository name but now when I load the page, the navigation buttons don't go to the pages automatically. My website name is myusername.github.io/repository, while when I click the "people" page navigation button, it tries to go to myusername.github.io/people which doesn't exist.

I can manually type in myusername.github.io/repository/people, and the page will come out. Obviously along the way of changing in my teams name while editing, I have messed this up a bit.

The outlay of the original website is kordinglab.com/people, which doesn't include the repository name which is why I think it won't navigate to include the repository. I've had a look through the code, but as I am a bit inexperienced, I can't find how to change it, or where it is controlled.

How can I fix it so the nav buttons actually go to the pages?

https://github.com/KordingLab/KordingLab.github.io provides all the code used in the original and working version. I would be more specific if I knew which file I was looking for, sorry.

After a lot of trial and error, I have developed my first python package and got it to the point where it is uploaded to PyPI test. I can then install it and import it in Spyder as intended. However, in order to use it, I need to call it using the package name and the module name in a format such as this: