numpy.log10() in Python Last Updated : 29 Nov, 2018 Comments Improve Suggest changes Like Article Like Report About : numpy.log10(arr, out = None, *, where = True, casting = 'same_kind', order = 'K', dtype = None, ufunc 'log10') : This mathematical function helps user to calculate Base-10 logarithm of x where x belongs to all the input array elements. Parameters : array : [array_like]Input array or object. out : [ndarray, optional]Output array with same dimensions as Input array, placed with result. **kwargs : allows you to pass keyword variable length of argument to a function. It is used when we want to handle named argument in a function. where : [array_like, optional]True value means to calculate the universal functions(ufunc) at that position, False value means to leave the value in the output alone. Return : An array with Base-10 logarithmic value of x; where x belongs to all elements of input array. Code 1 : Working Python3 # Python program explaining # log10() function import numpy as np in_array = [1, 3, 5, 10**8] print ("Input array : ", in_array) out_array = np.log10(in_array) print ("Output array : ", out_array) print("\nnp.log10(4**4) : ", np.log10(100**4)) print("np.log10(2**8) : ", np.log10(10**8)) Output : Input array : [1, 3, 5, 100000000] Output array : [ 0. 0.47712125 0.69897 8. ] np.log10(4**4) : 8.0 np.log10(2**8) : 8.0 Code 2 : Graphical representation Python3 # Python program showing # Graphical representation of # log10() function import numpy as np import matplotlib.pyplot as plt in_array = [1, 2, 3, 4, 5] out_array = np.log10(in_array) print ("out_array : ", out_array) plt.plot(in_array, in_array, color = 'blue', marker = "*") # red for numpy.log10() plt.plot(out_array, in_array, color = 'red', marker = "o") plt.title("numpy.log10()") plt.xlabel("out_array") plt.ylabel("in_array") plt.show() Output : out_array : [ 0. 0.30103 0.47712125 0.60205999 0.69897 ] References : https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.log10.html#numpy.log10 . Comment More infoAdvertise with us Next Article numpy.log10() in Python M mohit gupta_omg :) Follow Improve Article Tags : Python Python-numpy Python numpy-Mathematical Function Practice Tags : python Similar Reads numpy.log() in Python The numpy.log() is a mathematical function that helps user to calculate Natural logarithm of x where x belongs to all the input array elements. Natural logarithm log is the inverse of the exp(), so that log(exp(x)) = x. The natural logarithm is log in base e. Syntax :numpy.log(x[, out] = ufunc 'log1 4 min read numpy.log1p() in Python numpy.log1p(arr, out = None, *, where = True, casting = 'same_kind', order = 'K', dtype = None, ufunc 'log1p') : This mathematical function helps user to calculate natural logarithmic value of x+1 where x belongs to all the input array elements. log1p is reverse of exp(x) - 1. Parameters : array : [ 2 min read numpy.log2() in Python numpy.log2(arr, out = None, *, where = True, casting = 'same_kind', order = 'K', dtype = None, ufunc 'log1p') : This mathematical function helps user to calculate Base-2 logarithm of x where x belongs to all the input array elements. Parameters : array : [array_like]Input array or object. out : [nda 2 min read numpy.logspace() in Python The numpy.logspace() function returns number spaces evenly w.r.t interval on a log scale. Syntax :  numpy.logspace(start, stop, num = 50, endpoint = True, base = 10.0, dtype = None) Parameters : -> start : [float] start(base ** start) of interval range. -> stop : [float] end(base ** stop) of 2 min read numpy.logaddexp() in Python numpy.logaddexp() function is used to calculate Logarithm of the sum of exponentiations of the inputs. This function is useful in statistics where the calculated probabilities of events may be so small as to exceed the range of normal floating point numbers. In such cases, the logarithm of the calcu 2 min read Like