Advance Function Of Numpy | Applied Python #10

In this video, we continue our NumPy series and explore some useful advanced NumPy functions for efficient data manipulation and analysis. Data Science Trainer Mohit Pyasi demonstrates how different NumPy functions can be used to apply conditions, select values, control data ranges, count unique elements, sort arrays, find index positions, access specific elements, and combine or reshape arrays. By the end of this video, you’ll have a practical understanding of several powerful NumPy functions that are useful for Data Science, Data Analysis, and Machine Learning. What We Will Learn Today: Using np.where() for conditional operations Using np.select() for multiple conditions Using np.clip() to set data boundaries Finding unique values and their counts with np.unique() Counting occurrences using np.bincount() Sorting arrays using np.sort() Finding index positions with np.argsort() Finding maximum and minimum index positions Accessing array elements using np.take() Combining arrays using np.concatenate() Reshaping arrays using reshape() Horizontal and vertical stacking with np.hstack() and np.vstack() Video Chapters / Timestamps: 00:00 - Introduction to Advanced NumPy Functions 01:03 - Creating NumPy Arrays 02:04 - np.where() for Conditions 03:38 - np.select() for Multiple Conditions 06:18 - np.clip() for Data Boundaries 08:00 - np.unique() & Counting Values 10:24 - np.bincount() 11:25 - np.argsort() & Index Positions 14:15 - argmax(), argmin() & Sorting 15:46 - np.take() Function 16:41 - Concatenating & Reshaping Arrays 19:21 - hstack() & vstack() 20:14 - Advanced NumPy Functions Recap Who Is This Video For? This tutorial is ideal for students and beginners learning Python, NumPy, Data Science, and Machine Learning who want to move beyond basic NumPy operations and learn practical functions for working with arrays and data. These functions can help you perform conditional operations, data manipulation, sorting, counting, indexing, reshaping, and array combination more efficiently. Next Video In the next video, we’ll continue exploring more useful Python and NumPy concepts to strengthen your foundation for Data Science and Machine Learning. If you found this tutorial helpful, LIKE the video, share your questions in the COMMENTS, and SUBSCRIBE to Recruired for more practical tutorials on Python, NumPy, Data Science, Machine Learning, AI, and emerging technologies. #numpy #python #numpytutorial #datascience #machinelearning #pythonprogramming #dataanalysis #ai #pythontutorial #dataanalytics #learnpython #ArrayProgramming #programming #Recruired For More info You can Visit : https://ricr.in/ Explore our Other Course: https://ricr.in/courses Book For Demo Class: https://ricr.in/demo