numpy.log10() in Python

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

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# 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))

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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











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# 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()   



















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Output : 


out_array :  [ 0.          0.30103     0.47712125  0.60205999  0.69897   ]


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References : 

https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.log10.html#numpy.log10

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