Machine Learning

The error “ValueError: can only compare identically-labeled series objects” comes in Pandas and specifically when we are dealing with series. This error is quite frustrating when we are new to pandas and performing data analysis. Understanding ValueError: can only compare identically-labeled series objects with code examples. We get “ValueError: Can only compare identically-labeled Series objects”

The Hugging Face ‘datasets’ library has changed the way data scientists and machine learning developers access and manage datasets. One of the common issues that users face is the `NotImplementedError: loading a dataset cached in a LocalFileSystem is not supported`. This kind of error can really be frustrating when we are in the middle of

Python is used in various fields from web development to data science. As it is also technology, Python can sometimes encounter errors that can be frustrating for developers. One of these errors is the Fatal Error: init_import_size: Failed to import the site module.” In this blog post, we will explore what causes this error and

The error message “NotImplementedError: Cannot copy out of meta tensor; no data!” commonly occurs when we are working with PyTorch models that are initialized on the meta device but are being transferred to a different device (like CPU or GPU) without the necessary data being loaded. This error comes in various contexts and particularly when

Unboundlocalerror local variable referenced before assignment is a common error when we are dealing with variable scope within functions. The cause of the error is referring to a local variable before it has been assigned a value. In this blog we will see the error code snippet with Unboundlocalerror local variable referenced before assignment and

Missing data is a common problem in data science domain. When we are collecting raw data from the environment we get lot of missing values. In Pandas missing values are typically represented as nan (Not a Number). Dropping rows with nan values helps us to maintain the integrity of our analysis by ensuring that only

Understanding pandas dataframe append deprecated. Recent deprecation of ‘DataFrame.append’ method in Pandas has created a discussion point amongst data scientists and developers. As we move to Pandas 2.0, this method is no longer recommend to be used which leads developers to use ‘pandas.concat’ for appending data. By using ‘pandas.concat’ we enhance performance in data manipulation

Author: JKPython Developer | 5+ years programming production systems“I write about real Python problems I’ve encountered in projects and how to fix them.” Summary: The writeup shows real world techniques for extracting text between strings, characters, words and delimiters in Python. These are common requirements of data cleaning, data wrangling and text preprocessing tasks. In