Array Methods and Attributes
Contents
Array Methods and Attributes#
In this section we will look at some methods and attributes that arrays have. This is not a complete list, but rather highlighting things you may find useful.
Let’s start off by creating a fairly large array, for example a collection of human height measurements:
heights = np.array(
[ 2.13159377, 1.8864508 , 1.63504183, 1.71173878, 1.78826872,
1.60621813, 1.74630706, 2.11123384, 1.54212979, 1.39184441,
1.7919224 , 1.80299245, 1.73770464, 1.95233673, 1.47179093,
1.70506609, 1.41194434, 2.05643464, 1.8262583 , 1.47764985,
1.61362183, 1.65600316, 1.42078883, 1.78059602, 1.80600655,
1.91634004, 1.82746488, 1.82688072, 1.82053352, 1.84882458,
1.80672297, 1.4646136 , 1.71033286, 1.83272236, 1.97074545,
1.96265325, 1.39817665, 1.55933323, 1.59111903, 1.53108805,
1.33635392, 1.74971951, 1.56885338, 1.6614742 , 1.70868504,
1.58476337, 1.69233894, 1.73520641, 1.71248418, 1.75484377])
To get the number of elements in an array, we can use the size
attribute:
print('The size of the heights array:', heights.size)
The size of the heights array: 50
For 1 dimensional arrays this is gives us the same value as using len()
, but for multidimensional arrays, len()
will not return the total number of elements.
Minimum and Maximum Values#
You can use the min()
and max()
methods to get the minimum and maximum values of an array respectively.
print('Minimum height:', heights.min())
print('Maximum height', heights.max())
Minimum height: 1.33635392
Maximum height 2.13159377
Again, this gives you similar results to the functions in the Standard Library, but is the only option for arrays of higher dimensions.
Statistical Functions#
NumPy provides us with some basic statistical functions out of the box. For example the mean()
(arithmetic mean or average) and std()
(standard deviation).
print('Average height: ', heights.mean())
print('Standard deviation of heights: ', heights.std())
Average height: 1.712684356
Standard deviation of heights: 0.18476698650385862
print('Average height:', np.mean(heights))
print('Standard deviation of heights:', np.std(heights))
print('Maximum height:', np.max(heights))
print('Mimimum height:', np.min(heights))
Average height: 1.712684356
Standard deviation of heights: 0.18476698650385862
Maximum height: 2.13159377
Mimimum height: 1.33635392