capsize | Capistrano extension for managing and running your app | AWS library

According to matplotlib documentation, the method matplotlib.pyplot.bar() returns a

"container with all the bars and optionally errorbars"

(https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.bar.html)

I have created a bar plot with the following code:

I'm currently running with a little bit of trouble with regards to setting a range of colors for my errors bars. Apparently, it looks like there are two error bars imposed to one another. One is color Orange while the other is Red. For reference, I followed the steps from this post: Setting Different error bar colors in bar plot in matplotlib and tweaked to fit in. Is there a way to resolve the small issue?

I'll also include the .csv file for usage. At the moment, the code runs like this:

How do I replace the dot with a comma on my x and y-axis?

I created a plot using:

Question: (Solution at bottom)

I have an array of data, that I wish to plot a graph of then fit an exponential decay model over that is weighted by 1/uncertainty^2 (here the variable is called ampserr). Running the code will produce the graph, but not fit the model and produces the error message:

unsupported operand type(s) for ^: 'list' and 'float'

I saw on other questions that, (i think) i need to use a for loop to somehow run over every item in the array, but wasn't really sure how to do that. The code is a few hundred lines long and pretty hard to break up, so I'll just post the bit that's most relevant but it won't work on it's own. Happy to post the full code if someone wants though. To clarify, ampserr is not an integer value. Anyone able to help me get past this error?

Code:

I have a model trained with multiple LayerNormalization layers, and I am unsure if a simple weight transfer works properly when activating dropout for prediction. This is the code I am using:

I have some radioactive decay data, which has uncertainties in both x and y. The graph itself is all good to go, but I need to plot the exponential decay curve and return the report from the fitting, to find the half-life, and reduced chi^2.

The code for the graph is:

I plot seaborn.barplot with hue on several categories.

I want the errobar to have the same color line the bar itself - how can I do this?

I call it with a data frame like this, I have four huse categories:

sns.barplot(y = '$T_i$', x = 'algo', hue = 'pricing', data = df, alpha = 0.0, ci = 100, capsize = 0.1)

I found errcolor = 'black' in kwargs, but it changes it for all bars, regardless of hue.

I have some difficulties converting a Mat OpenCV matrix (2D) into a 1D array in OpenCV. I am implementing my code in C++ with Visual Studio and my environment is Windows 10. This is my code