NumPy is one of the most popular library in Python that is used in the field of science and engineering. NumPy APIs are used in other popular libraries like Pandas, SciPy, Matplotlib, scikit-learn, scikit-image, etc. Read our Python NumPy tutorials with real examples in PythonGuides.com.
While I was working on a data analysis project, I needed to import a CSV file with some missing values and custom delimiters. The usual pandas read_csv() wasn’t flexible enough for my specific requirements. That’s when np.genfromtxt() came to my rescue! In this article, I’ll cover how to use NumPy’s genfromtxt() function to load data … Read more >>
Recently, I was working on a data analysis project where I needed to reset the index of a NumPy array after filtering out some values. The issue is, there’s no direct “reset_index()” method in NumPy like we have in pandas. So we need a workaround. In this article, I’ll cover several simple ways you can … Read more >>
When I was working on a data science project where I needed to normalize a large dataset by dividing each value by a constant scaling factor. The issue is, manually looping through large arrays is inefficient and slow. NumPy provides vectorized operations that make this task remarkably simple. In this article, I’ll cover multiple ways … Read more >>
I was working on a data analysis project where I needed to frequently share NumPy arrays with colleagues. Copying and pasting these arrays manually was becoming tedious and error-prone. The challenge was finding an efficient way to copy NumPy arrays directly to the clipboard for easy sharing or transferring to other applications like Excel or … Read more >>
NumPy random numbers come from a generator you create once and then ask for values: The older np.random.rand() and np.random.randint() still work and appear in most tutorials. They differ in one respect that matters, covered further down. Starting with the question most people arrive with: a random number in a given range. Output is from … Read more >>
I was working on a data analysis project where I needed to count the number of non-zero values in a NumPy array. I was looking for a quick and efficient way to do this without writing loops or complex logic. That’s when I discovered the np.count_nonzero() function in NumPy. In this article, I’ll share how … Read more >>
While I was working on a data analysis project where I needed to rank NBA player statistics in descending order. The challenge was to maintain the original data while creating an index of the highest-to-lowest values. In Python, NumPy’s argsort() function is perfect for this task, but by default, it sorts in ascending order. In … Read more >>
When working with data in Python, I often need to extract specific values from arrays based on certain conditions. NumPy makes this process incredibly efficient, especially when dealing with 2D arrays (matrices). In this article, I will show you 6 practical methods to filter 2D arrays by condition in NumPy. These techniques have saved me … Read more >>
When working with NumPy arrays, I often need to replace specific values based on their indices. Whether I’m cleaning data for machine learning models or updating values in a financial analysis, knowing how to replace array elements efficiently is important. In this article, I’ll show you several easy methods to replace values in NumPy arrays … Read more >>
np.add.at adds values into an array at the indices you give it, and it applies every index even when one repeats. That repetition is the entire point. Plain array[indices] += values quietly keeps only the last write for any index that appears more than once. Below I show that difference, the 2D form, and how … Read more >>
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