by Suf | Sep 14, 2024 | Data Science, Python, Tips
Introduction When working with Python and manipulating data, you might often use libraries like NumPy and Pandas. However, combining these libraries or mistakenly using one in place of another can result in errors. One such common error is the following:...
by Suf | Sep 14, 2024 | Data Science, Programming, Python, Tips
When working with file handling in Python, a common error encountered is the AttributeError: ‘_io.TextIOWrapper’ object has no attribute ‘encode’. This typically occurs when you’re trying to call the .encode() method on a file object,...
by Suf | Sep 14, 2024 | Data Science, Python, Tips
Python’s scikit-learn library is a popular toolkit for machine learning, but sometimes you may encounter an error like: ModuleNotFoundError: No module named ‘sklearn.datasets.samples_generator’ This error occurs when the samples_generator module is not...
by Suf | Jan 15, 2022 | Data Science, Programming, Python, Tips
NaN stands for Not a Number. You may encounter the error ValueError: cannot convert float NaN to integer when attempting to convert a column in a Pandas DataFrame from a float to an integer, and the column contains NaN values. You can solve this error by either...
by Suf | Jan 8, 2022 | Data Science, Programming, Python, Tips
The numpy.where() function returns the elements in two arrays depending on a conditional statement. You can use this function to locate specific elements within an array that match the conditions you specify. We can also perform operations on those elements that...
by Suf | Dec 26, 2021 | Data Science, Programming, Python, Tips
Indexing is an essential tool for storing and handling large and complex datasets with rows and columns. In Python, we use index values within square brackets to perform the indexing. If we try to access an index beyond the dimensions of the dataset, we will raise the...
