Summing the Values in an Array

• Python itself can do sum of all values in an array using the built-in sum function.

# In[1]
L = np.random.random(100)
sum(L)

# Out[1]
47.23340327381991

---

# In[2]
np.sum(L)

# Out[2]
47.23340327381991

• Numpy's sum function is quite similar to Python's function, and the result is the same.
• However, Numpy's version of the operation is computed much more quickly.

# In[3]
big_array=np.random.rand(1000000)
%timeit sum(big_array)
%timeit np.sum(big_array)

# Out[3]
498 ms ± 66.5 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
2.06 ms ± 246 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)

Minimum and Maximum

• Python has built-in functions min and max, and Numpy's corresponding functions have similar syntax, but operate much more quickly

# In[4]
min(big_array), max(big_array)

# Out[4]
(8.237773400088244e-07, 0.999999693122087)

---

# In[5]
np.min(big_array), np.max(big_array)

# Out[5]
(8.237773400088244e-07, 0.999999693122087)

---

# In[6]
%timeit min(big_array)
%timeit np.min(big_array)

# Out[6]
310 ms ± 83.5 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
1.31 ms ± 195 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)

• For min, max, and several other Numpy aggregates, a shorter syntax is to use methods of the array object itself

#In[7]
print(big_array.min(),big_array.max(),big_array.sum())

# Out[7]
8.237773400088244e-07 0.999999693122087 499601.2436555182

Multidimensional Aggregates

# In[8]
M=np.random.randint(0,10,(3,4))
print(M)

# Out[8]
[[7 9 2 7]
 [1 0 5 2]
 [7 5 9 5]]

• Aggregation functions take an additional argument specifying the axis along which the aggregate is computed.

# In[9]
M.min(axis=0)

# Out[9]
array([1, 0, 2, 2])

• The function returns four values, corresponding to the four columns of numbers.
• Similary, we can find the maximun value within each row

# In[10]
M.max(axis=1)

# Out[10]
array([9, 5, 9])

Other Aggregation Functions

Useful Aggregation functions available in Numpy

Function	NaN-safe version	Description
np.sum	np.nansum	Compute sum of elements
np.prod	np.nanprod	Compute product of elements
np.mean	np.nanmean	Compute mean of elements
np.std	np.nanstd	Compute standard deviation
np.var	np.nanvar	Compute variance
np.min	np.nanmin	Find minimum value
np.max	np.nanmax	Find maximum value
np.argmin	np.nanargmin	Find index of minimum value
np.argmax	np.nanargmax	Find index of maximum value
np.median	np.nanmedian	Compute median of elelments
np.percentile	np.nanpercentile	Compute rank-based statistics of elements
np.any	N/A	Evaluate whether any elements are true
np.all	N/A	Evaluate whether all elements are true