{"id":4323,"date":"2022-08-09T10:16:20","date_gmt":"2022-08-09T10:16:20","guid":{"rendered":"https:\/\/www.pythontutorial.net\/?page_id=4323"},"modified":"2022-08-10T04:11:43","modified_gmt":"2022-08-10T04:11:43","slug":"numpy-std","status":"publish","type":"page","link":"https:\/\/www.pythontutorial.net\/python-numpy\/numpy-std\/","title":{"rendered":"NumPy std()"},"content":{"rendered":"\n

Summary<\/strong>: in this tutorial, you’ll learn how to use the numpy std()<\/code> function to calculate the standard deviation.<\/p>\n\n\n\n

Standard deviation measures how spread out the elements of an array is. The more spread out elements is, the greater their standard deviation.<\/p>\n\n\n\n

Standard deviation is the square root of the variance. To calculate the variance, check out the numpy var() function tutorial<\/a>.<\/p>\n\n\n\n

To calculate standard deviation, you can use the numpy std()<\/code> function as follows:<\/p>\n\n\n

numpy.std(a, axis=None<\/span>, dtype=None<\/span>, out=None<\/span>, ddof=0<\/span>, keepdims=<no value>, *, where=<no value>)<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
The std()<\/code> function has many parameters but we’ll focus on only the first one in this tutorial.<\/p>\n\n\n\n
NumPy std() function example #<\/a><\/h2>\n\n\n\n
Suppose you have a list of trees with the broadest crown. The first column displays the tree name and the second column shows its corresponding diameter in feet:<\/p>\n\n\n\n
Tree Name<\/th>Diameter (Feet)<\/th><\/tr><\/thead>
Thimmamma Marrimanu<\/td>591<\/td><\/tr>
Monkira Monster<\/td>239<\/td><\/tr>
Oriental Plane Tree at Corsham Court<\/td>210<\/td><\/tr>
Saman de Guere<\/td>207<\/td><\/tr>
The Big Tree<\/td>201<\/td><\/tr>
Shugborough Yew<\/td>182<\/td><\/tr>
Moreton Bay Fig Tree<\/td>176<\/td><\/tr>
The Pechanga Great Oak<\/td>176<\/td><\/tr>
El Gigante<\/td>175<\/td><\/tr>
Benaroon<\/td>170<\/td><\/tr>
The E. O. Hunt Oak<\/td>170<\/td><\/tr>
The Lansdowne Sycamore<\/td>169<\/td><\/tr>
The Glencoe Tree<\/td>168<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
The following example uses the std()<\/code> function to calculate the standard deviation of the diameters of the above trees:<\/p>\n\n\n
import<\/span> numpy as<\/span> np\n\n\ndiameters = np.array([591<\/span>, 239<\/span>, 210<\/span>, 207<\/span>, 201<\/span>, 182<\/span>,\n                      176<\/span>, 176<\/span>, 175<\/span>, 170<\/span>, 170<\/span>, 169<\/span>, 168<\/span>, ])\nresult = np.std(diameters)\nprint(round(result, 1<\/span>))<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
Output:<\/p>\n\n\n
109.6<\/span><\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
How it works.<\/p>\n\n\n\n
First, create an array that holds the diameters of trees:<\/p>\n\n\n
diameters = np.array([591<\/span>, 239<\/span>, 210<\/span>, 207<\/span>, 201<\/span>, 182<\/span>,\n                      176<\/span>, 176<\/span>, 175<\/span>, 170<\/span>, 170<\/span>, 169<\/span>, 168<\/span>, ])<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
Second, calculate the standard deviation of diameters using the std()<\/code> function:<\/p>\n\n\n
result = np.std(diameters)<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
Third, round the standard deviation and display it:<\/p>\n\n\n
print(round(result, 1<\/span>))<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n
By using the standard deviation, we have a “standard” way of knowing which trees have a normal diameter, and which trees have large or small diameters.<\/p>\n\n\n\n
Summary #<\/a><\/h2>\n\n\n\n
  • Use the numpy std()<\/code> function to calculate the standard deviation.<\/li><\/ul>\n
    \n\t
    \n\t\t
    Was this tutorial helpful ?<\/div>\n\t\t
    \n\t\t\t\n\t\t\t\t\n\t\t\t\t\t<\/path>\n\t\t\t\t<\/svg>\n\t\t\t\t Yes <\/span>\n\t\t\t<\/button>\n\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t<\/path>\n\t\t\t\t<\/svg>\n\t\t\t\t No <\/span>\n\t\t\t<\/button>\n\t\t<\/div>\n\t<\/header>\n\n\t
    \n\t\t
    \n\t\t\t
    <\/div>\n\t\t\t