basque | execute shell commands from a SQLite function | Database library

I am new to programming in SAS and I have been investigating to be able to join a shp file downloaded from the INE with a store characterization file that contains two fields with X and Y coordinates.

I would like to make a map for each autonomous community, so far fine, I have managed to make a join between the "base" map that I have downloaded from the INE with my characterization data by census section and this I have represented on a map, so you can see the map of the Basque Country region and in red, the polygons where there are shops.

This is almost what I want, but I don't want the entire polygon to be colored, I just want a point to appear in the polygon where the store is exactly (X and Y coordinates) and I would also like that at the point, at pass the cursor to me of the information contained in the store characterization csv or the file downloaded from the INE.

I don't know if I have explained myself well, I hope so, how could I do this? Thank you very much in advance, if you can help me in this I would be very happy.

You can download the INE file that contains all the polygons in Spain with all the census sections on this page: https://www.ine.es/ss/Satellite?L=es_ES&c=Page&cid=1259952026632&p=1259952026632&pagename=ProductosYServicios%2FPYSLayout select the year 2021 and then go ahead.

I can't share the stores file, but it would work with any excel / csv that contains 2 fields, one with X coordinates and the other with Y coordinates.

https://ibb.co/26yqS8G In this image you can see what I have done with the code below

I would like something similar but instead of coloring the polygons where there are stores, the exact points where the stores are located appear and that point gives me information (which comes from from csv)

There are many related questions here about this issue, particulalry using left_join from dplyr , but I still can't figure it out.

All I want to do is return LanguageClean in Lookup based on a match to the Language column in df. If there is no match, simply return NA. I want LanguageClean added as a new column to df.

I can see that my code below is replicating the ID, but I don't want it to. The ID column is irrelevant for my purposes here, although I need to retain it in the final dataframe.

First of all, thank you in advance. I am struggling to get the following answer using an awk script:

Input: gawk -f script.awk file.csv

(I cannot use tail method at the end. Only the above.)

Desired Output:

The average age of 20 people who speak Spanish is 29.55 years.

Actual Output:

ActualOutput Picture

So basically, I only want to hide or eliminate that information and only showing the Desired output.

My script is the following (also in the picture):

I have a quite complex string that looks something like:

I quite new with xmlt, so I guess it is a simple issue. I want to flatten an xml but intead of having 3 occurences, I have 2 occurences with the second one having repeating elements corresponding to a grand child nodes

Input xml

I have const language array. i want all languages to be used as key of my schema object. i have dumbed my language array in constant and loop through it to get the value of each language and export it, now I am importing it to my schema and using it as key variable but I am getting above error language constant

I've got the following JSON file, translation.json, containing a key called "greeting" and a value containing the language the greeting is written in.

I am trying to deploy my Django project using Ubuntu and apache webserver. When I transferred my project to the Ubuntu web server and tested it in development, everything went fine. However when changed to production, I experienced file not found problem and I suspect this problem is related to my setings.py, but I am unable to troubleshoot it further. The error I see in production when accessing my site is:

While trying to find a good answer for my on google I stumbled on this:
https://www.pythonpool.com/matplotlib-figsize/
It showed and solved my problem perfectly - from this: