normalize | Normalizes nested JSON and Denormalizes normalized data | JSON Processing library

i have tried the below code to normalize JSON, but getting error - " AttributeError: 'int' object has no attribute 'values'"

Code:

I have a list of titles that I need to normalize. For example, if a title contains 'CTO', it needs to be changed to 'Chief Technology Officer'. However, I only want to replace 'CTO' if there is no letter directly to the left or right of 'CTO'. For example, 'Director' contains 'cto'. I obviously wouldn't want this to be replaced. However, I do want it to be replaced in situations where the title is 'Founder/CTO' or 'CTO/Founder'.

Is there a way to check if a letter is before 'CXO' using regex? Or what would be the best way to accomplish this task?

EDIT: My code is as follows...

I have a python code that I can add multiple rectangles on a QGraphicsScene.

I have put example dataset (df), expected output (df2) and my code so far below. I have a df where some rows in column i2 contain a list - in the json format, which need exploding and reinserting back into the df, from the row in which they were extracted. But the need to be inputted into a different column (i1). i need to extract a unique identifier (the 'id_2' value) from the string and insert that into the id_2 column.

in my code so far i am parsing the json-like data with pd.normalize, and then inserting the original string from the column i1 onto the top of the extracted strings (it should be much more clear if you take a look below) and then reinsert them based on the index. But I have to specify the index, which is not good. I would like it to be less dependent on manual input of indices in case it changes in the future with more of these nested cells or somehow the index changes.

Any suggestions are very welcome, thanks so much

example data

I have the following dataset and I want to compute all possible combinations of cross-tabulations in the most efficient way, I have been able to calculate pairs against one master variable, but not for all possibilities (i have popped what i mean in below). Is there a way to get this all in loop that could handle any number of columns? Thanks so much!

data

i'm trying to use Custom Directives in vue.js 3 from the documentation, and i use the example that in the documentation but i've these errors:

• 'Vue' is not defined.

and when i remove "vue" from the Directive code these errors show in the console:

• Uncaught (in promise) TypeError: Cannot read property 'created' of undefined
• Uncaught (in promise) TypeError: Cannot read property 'parentNode' of null

I think these error cuz i use vue version 3 but i'm using Custom Directives that in Vue vesion 3 from documentation

main js:

I have a pyTorch-code to train a model that should be able to detect placeholder-images among product-images. I didn't write the code by myself as I am very unexperienced with CNNs and Machine Learning.

My boss told me to calculate the f1-score for that model and i found out that the formula for that is ((precision * recall)/(precision + recall)) but I don't know how I get precision and recall. Is someone able to tell me how I can get those two parameters from that following code? (Sorry for the long piece of code, but I didn't really know what is necessary and what isn't)

I'm sorry for the basic question but I'm struggling a bit with 3NF. This is the table I'm talking about:

User (Nickname, Email, Password, Name, Surname, DocumentId, Telephone, Avatar, Biography)

I think this table is not normalized in the third normal form because there are several functional dependencies due to the two candidate keys (DocumentId and Telephone):

• DocumentId -> Nickname, Email, Password, Name, Surname, Telephone, Avatar, Biography
• Telephone -> Nickname, Email, Password, Name, Surname, DocumentId, Avatar, Biography

Am I wrong? I am not so sure about the correctness of these functional dependencies. Are they correct? Also, how can I normalize this table?

Edit:

To specify, 2 users can't have the same DocumentId, the same Email and the same telephone number.

So this should be another functional dependency:

• Email -> Nickname, Password, Name, Surname, DocumentId, Avatar, Biography, Telephone

I have a uniform in my fragment shader and when I try to get the value of the location of the uniform, it returns null.

I checked the spelling and I don't find any spelling error and this uniform is also used in the shader code.

My error is:

error in getUniformLocation([object WebGLProgram], materialAmbient): uniform 'materialAmbient' does not exist in WebGLProgram("unnamed")

This is my code in WebGL to get a uniform location.