Skip to main content

TypeError: list indices must be integers or slices, not str

Introduction:
This error generally occur for very simple issues. The error normally translates to python saying that, you are trying to access a string index of a list; which is impossible as lists are indexed by integers and not by strings.

Recreation of the issue:
So this can be caused by something as simple as food = list['abc']. But the problem is that we often write complex codes and therefore we don't easily find out this mistake.
This sort of mistake if you are seeing in your code, please check that most probably you are passing a list in a place where there should be a dataframe or at least a dictionary.
I have several times encountered this error in real coding scenarios. One of them have been where I wrote a condition statement inside a dataframe and this issue came. Later on, I found out that the variable I thought was a dataframe was in fact misspelled and actually was referring to a list I created one line above.
Conclusion:
So, it is important to examine the line where the error is coming and then please check the type of the variables involved in the error. Probably this should solve your issue.
You can check this stackOverFlow link for similar issues.
Thanks for reading this post.
Labels:

Comments

Post a Comment

Popular posts from this blog

Spacy errors and their solutions

 Introduction: There are a bunch of errors in spacy, which never makes sense until you get to the depth of it. In this post, we will analyze the attribute error E046 and why it occurs. (1) AttributeError: [E046] Can't retrieve unregistered extension attribute 'tag_name'. Did you forget to call the set_extension method? Let's first understand what the error means on superficial level. There is a tag_name extension in your code. i.e. from a doc object, probably you are calling doc._.tag_name. But spacy suggests to you that probably you forgot to call the set_extension method. So what to do from here? The problem in hand is that your extension is not created where it should have been created. Now in general this means that your pipeline is incorrect at some level.  So how should you solve it? Look into the pipeline of your spacy language object. Chances are that the pipeline component which creates the extension is not included in the pipeline. To check the pipe eleme...
Post a Comment
Read more

20 Must-Know Math Puzzles for Data Science Interviews: Test Your Problem-Solving Skills

Introduction:   When preparing for a data science interview, brushing up on your coding and statistical knowledge is crucial—but math puzzles also play a significant role. Many interviewers use puzzles to assess how candidates approach complex problems, test their logical reasoning, and gauge their problem-solving efficiency. These puzzles are often designed to test not only your knowledge of math but also your ability to think critically and creatively. Here, we've compiled 20 challenging yet exciting math puzzles to help you prepare for data science interviews. We’ll walk you through each puzzle, followed by an explanation of the solution. 1. The Missing Dollar Puzzle Puzzle: Three friends check into a hotel room that costs $30. They each contribute $10. Later, the hotel realizes there was an error and the room actually costs $25. The hotel gives $5 back to the bellboy to return to the friends, but the bellboy, being dishonest, pockets $2 and gives $1 back to each friend. No...
Post a Comment
Read more

GAM model : PyGAM package details Analysis and possible issue resolving

Introduction:                  picture credit to peter laurinec. I have been studying about PyGAM package for last couple of days. Now, I am planning to thoroughly analyze the code of PyGAM package with necessary description of GAM model and sources whenever necessary. This is going to be a long post and very much technical in nature. Pre-requisites: For understanding the coding part of PyGAM package, first you have to learn what is a GAM model. GAM stands for generalized additive model, i.e. it is a type of statistical modeling where a target variable Y is roughly represented by additive combination of set of different functions. In formula it can be written as: g(E[Y]) = f 1 (x 1 ) + f 2 (x 2 ) + f 3 (x 3 ,x 4 )+...etc where g is called a link function and f are different types of functions. In technical terms, in GAM model, theoretically expectation of the link transformed target variable is assume...
Post a Comment
Read more