Most used functions in NumPy
Useful functions in NumPy for Data Science and Machine Learning
Numpy is one of the most used and popular python library which is used for many purposes along with data analysis and support for data structures.
In this article, we will discuss the most popular and widely used numpy functions, which will definitely save us time and provide us with more insights into the dataset.
Importing the libraries
Now we will import numpy as shown below. If your system does not have these libraries installed, you may get them using the pip command.
Array
Array function can create an array. We can create an array by providing a list i.e. np.array(list).
Reshape
Reshape function is used to reshape the array into the provided shape. We can use this function by array.reshape(new shape).
Sort
Sort function can sort the array in ascending or descending order. We can sort our array by array.sort().
Unique
Unique function return all the unique elements present in the list. We can use this function by np.unique(array).
Arange
Arange function creates an integer array with evenly spaced intervals. We can use this function by np.arange(low,high,interval).
Linspace
Linespace function creates a float array with evenly spaced numbers. We can use this function by np.linspace(low,high,interval).
Put
Put functions replaces the value present in the array by new values. We can use this function by np.put(array, position, new value).
Min and Max
Min and Max function returns the minimum and maximum value in the array. We can use np.min(array) and np.max(array).
Sum
Sum function returns the sum of elements present in the array. We can use this function by np.sum(array).
Around
Around function rounds off the provided number to appropriate integer. We can use this function by np.around(array).
Random integers
Random function is used to return an array of given size between the provided range. We can use this function by np.random.randint(initial value, final value, size).
Random shuffle
Random shuffle function is used to shuffle an array and return an array with shuffled elements. We can shuffle our array by np.random.shuffle(array).
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Conclusion
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