The problem is for Leet Code Intersection of Two Arrays. when I run code, it gave me no error and was working just fine giving the correct output. But when I try to submit, it gave me some weird error. I don't have any idea where and what the issue is.
This is my solution:
and this is the error I am getting in Leet Code on submitting:
[![runtime error](https://i.stack.imgur.com/4vaug.jpg)](https://i.stack.imgur.com/4vaug.jpg)
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Getting a syntax error and not sure why. Trying to loadca dataframe. Please can someone help. Thanks
If you are getting started with programming, jupyter can be counter intuitive at some points, I assume that's not your first cell in the notebook, so be sure to run the previous ones where the definition for titanic_df/titanic_csv is loaded.
The error you are getting says NameError, not SyntaxError, and it is informing you that a variable called titanic_csv does not exist.
A screenshot of my code with error
I am following the tutorial seen at https://www.youtube.com/watch?v=7SVv07QXO5M&ab_channel=HackersRealm
The exact code I am following is here: https://github.com/aswintechguy/Reinforcement-Learning-Projects/blob/main/Cartpole%20Balance%20-%20OpenAI%20Gym%20-%20Reinforcement%20Learning/CartPole%20Balance%20-%20OpenAI%20Gym%20-%20Reinforcement%20Learning.ipynb
Not sure what I am doing wrong but the guy doing the tutorial had no issues so I'm not sure how to troubleshoot this. I'm also doing this in a Jupyter Notebook. Any ideas what I might be doing wrong here?
I have seen similar error, in my case i got this error when i ran the env.close() and tried running again, i'm suspecting, this was the reason for my error, because once env.close() has been called there is no environment to perform rest of the operations so I had to re-run the cell to create the environment to try it again. Im assuming this may have been your case.
Try running the cell with make environment and retry the cell which throws u the error.
So I keep getting an error message in R when I try to use the bias function here's what my code looks like so far:
install.packages("SimDesign")
library(SimDesign)
actual_temp<-c(68.3,70,72.4,71,67,70)
predicted_temp<-c(67.9,69,71,5,70,67,69)
bias(actual_temp, predicted_temp)
And here's the error message I get when I run the code:
Error in bias(actual_temp, predicted_temp) :
ncol(estimate) == length(parameter) is not TRUE
I've tried figuring out if my syntax is off (I'm a novice so I'm never 100% sure). I then tried copy-pasting the error into the search bar and came up with nothing. If anyone has an idea of how to fix this that would be great in case it's a problem I run into again in the future.
Edit: I tried again with some different data and it worked just fine. Is there something in this specific instance you can identify that's making it not work?
While running my script, I get the following error message during a code that creates a dozen plots in ggplot2 as part of an anlaysis:
Error in grid.Call.graphics(C_setviewport, vp, TRUE) :
non-finite location and/or size for viewport
The error message crashes the code. Interestingly, changing nothing and running the code again will resolve the problem, and it will work just fine. Sometimes, it will crash while creating a different plot.
I haven't been able to find any documentation on why this is happening.
There should be no error, and sometimes it works as expected.
Apologies if there is an obvious answer to this question, but I haven't found one.
All I'm looking for is the error equivalent of warnings() - I want to run a script, then get a list of all the errors that occurred when running the script.
Have had a look at traceback() and it seems like it might do what I want - the help file says "The default display is of the stack of the last uncaught error" - but can't figure out how to make it return all uncaught errors rather than just the last one.
My suggestion would be, save the script (e.g. script.R) then run the whole script using source('script.R'). This will stop at every error. If you just want to see if errors exist, this will be a good way to do it.