precip | Pegasus Repeatable Experiments for the Cloud in Python | AWS library

I am making a graph where i need to add the text label to my stat values in stat_poly_eq().

1. I need to add Tmax and Tmin, but i need the "max" and "min" as a subscript which i am not able to achieve.
2. I also need space between the words which i am obtaining using ~' '~ but when i do this the space between words is slightly larger than using (see image). Is there better way to provide the space?
3. In my graph, how do i make my whole legend "hollow" so that it doesnt sit over my line graph. I cannot move the legend to the corner because i need to align the legend lines with the three statistics text.

I would appreciate any help regarding these issues.

Reproducible example:

I was wondering if anyone could shed some light into how I can average this data:

I have a .nc file with data (dimensions: 2029,64,32) which relates to time, latitude and longitude. Using these commands I can plot individual timesteps:

I have multidimensional array which needs to be calculated with an imported function. (I am using jupyter notebook, so I exported the function to ipynb and imported it again) The function takes argument of 1 dimensional array.

I have very little experience with postgresql and was wondering how i can access certain fields from an array of json object so i can dynamically use them;

here is what the array i am trying to iterate looks like: ``

First time using python and can't seem to figure this out. I'm scraping data from a website and it's reading it as object class even though the values are numbers. I've tried all the ways described here but keep getting errors. I want the precip column to be numeric. I keep getting the following error code: ValueError: invalid literal for int() with base 10: '4.364.36'

Script with data scraping from website

I'm trying to dynamically render a list of DailyWeatherForecast, a Flutter StatelessWidget. The DailyWeatherForecast widget has some variables such as final String month and final double low, which intend to act as a single summarized forecast for a day as a narrow card. It has a constructor, and it works if I pass in hard-coded values to it from my main.dart. It looks and works great.

Information is pulled from an API though. So, I can't have this information hard-coded. See the code below for my approach:

I am getting a false convergence on a GAMM using mgcv::gamm when I try to fit models with corARMA functions for correlated error structures. The response data are amounts of precipitation, and are Gamma-distributed. The predictors are year and day-of-year ('julian'). I am fitting the model to the subset of observations for which precipitation occurred (i.e., I'm modelling only non-0 precipitation days). You will see there are a lot of NAs in the data, this is because I'm only interested in precipitation patterns of the summer season. I was advised by a colleague to pad the other dates with NAs instead of eliminating them (I was told the model might try to connect the end of august to the beginning of may in a cyclical pattern if I omitted the Sept-Apr dates).

The correlated error structures are meant to describe temporal autocorrelation, following the advice/process outlined in Gavin Simpson's excellent blog post . This code fit the model easily when I was working with R version 3.6.1, but after updating to 4.1.2 I am getting false convergence errors and "coefficient matrix not invertible" errors. I've tried changing some of the controls (mainly number of iterations) and that doesn't seem to help. I'm unsure of how to adjust controls for model convergence in this case (and of why an R update would cause this problem), and I don't know anything about the "coefficient matrix not invertible" error. Any advice or thoughts are much appreciated.

Link to download the data (too many rows to directly post)

Modelling without the autocorrelated error structure works fine:

I am trying to plot precipitation data from the National Weather Service. However, the data is by default set to a stereographic projection. I'd like to plot in a PlateCarree projection but I am having some difficulties. When I try and use the PlateCarree projection in Cartopy, it plots the maps but will not overlay the precipitation data. I'm assuming this means that I am not properly re-projecting the data from stereographic to PlateCarree. Is there anything specific I need to do in order to re-project the data correctly?

Here is the code that works with the stereographic projection:

'''

I'm working with a big XML files regarding the weather and I need somehow to get information from all nodes. Each XML consist in a month which contains every day divided in 10 minutes interval.

The XML looks like this but much longer: