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...
by Suf | Dec 19, 2021 | Data Science, Programming, Python, Tips
numpy is a Python library for manipulating and numerical analysis of large, multi-dimensional arrays. Numpy’s N-dimensional arrays or ndarray is like any regular python array; you access its contents using indexing. To retrieve an item from a ndarray, you must...
by Suf | Dec 9, 2021 | Data Science, Programming, Python, Tips
Hamming distance is a type of string metric for finding how similar two binary data strings are. If the strings are equal in length, Hamming distance determines the number of bit positions different between them. We can also describe Hamming distance as the minimum...
by Suf | Dec 8, 2021 | Data Science, Programming, Python, Tips
Distances measures are essential tools for machine learning. A distance measure is a score that summarises how different two objects are in the problem domain. Usually, we calculate distance measures on rows of data, like strings representing text documents. Specific...
