np.argmax is a NumPy function that returns the indices of the maximum values along a specified axis in an array. If the input array is multi-dimensional, you can specify the axis along which the maximum values are computed. Here’s a simple example: Output: In this example, np.argmax(arr) returns the index (position) of the maximum value…
np.argsort is a NumPy function that returns the indices that would sort an array along a specified axis. It performs an indirect sort on the input array and returns an array of indices that represent the sorted order of the elements. The returned indices can be used to construct a sorted version of the input…
To cap or clip outliers in a column, you can use the clip method in pandas. The clip method allows you to set a minimum and maximum threshold for the values in a DataFrame or a specific column. Here’s an example: Clipping is a simple method, and it’s important to consider the impact on your…
In Google Colab, you can use np.save to save NumPy arrays to your Google Drive. Here are the steps: Mount Google Drive Start by mounting your Google Drive. Run the following code and follow the instructions to authorize and mount your Google Drive:
hen you create a subset of a NumPy array and modify its values, it can affect the original array if the subset is actually a view of the original array rather than a copy. NumPy provides views to enhance performance and memory efficiency by avoiding unnecessary data copying. Understanding whether you’re working with a view…
umPy is a powerful numerical library in Python that provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these elements. It is a fundamental package for scientific computing in Python and is widely used in various domains such as data science, machine learning, signal processing, and…
