[Python-checkins] cpython (3.6): Further refinements to the examples and recipes for the random module
raymond.hettinger
python-checkins at python.org
Thu Nov 17 03:45:57 EST 2016
https://hg.python.org/cpython/rev/e699f3a004ea
changeset: 105176:e699f3a004ea
branch: 3.6
parent: 105174:d616304b82aa
user: Raymond Hettinger <python at rcn.com>
date: Thu Nov 17 00:45:35 2016 -0800
summary:
Further refinements to the examples and recipes for the random module
files:
Doc/library/random.rst | 45 +++++++++++++++++++----------
1 files changed, 29 insertions(+), 16 deletions(-)
diff --git a/Doc/library/random.rst b/Doc/library/random.rst
--- a/Doc/library/random.rst
+++ b/Doc/library/random.rst
@@ -322,36 +322,49 @@
Examples and Recipes
--------------------
-Basic usage::
+Basic examples::
- >>> random.random() # Random float x, 0.0 <= x < 1.0
+ >>> random() # Random float: 0.0 <= x < 1.0
0.37444887175646646
- >>> random.uniform(1, 10) # Random float x, 1.0 <= x < 10.0
- 1.1800146073117523
+ >>> uniform(2, 10) # Random float: 2.0 <= x < 10.0
+ 3.1800146073117523
- >>> random.randrange(10) # Integer from 0 to 9
+ >>> expovariate(1/5) # Interval between arrivals averaging 5 seconds
+ 5.148957571865031
+
+ >>> randrange(10) # Integer from 0 to 9
7
- >>> random.randrange(0, 101, 2) # Even integer from 0 to 100
+ >>> randrange(0, 101, 2) # Even integer from 0 to 100 inclusive
26
- >>> random.choice('abcdefghij') # Single random element
+ >>> choice('abcdefghij') # Single random element from a sequence
'c'
- >>> deck = ['jack', 'queen', 'king', 'ace']
- >>> shuffle(deck)
+ >>> deck = 'ace two three four'.split()
+ >>> shuffle(deck) # Shuffle a list
>>> deck
- ['king', 'queen', 'ace', 'jack']
+ ['four', 'two', 'ace', 'three']
- >>> random.sample([1, 2, 3, 4, 5], k=3) # Three samples without replacement
- [4, 1, 5]
+ >>> sample([10, 20, 30, 40, 50], k=4) # Four samples without replacement
+ [40, 10, 50, 30]
- >>> # Six weighted samples with replacement
+Simulations::
+
+ # Six roulette wheel spins (weighted sampling with replacement)
>>> choices(['red', 'black', 'green'], [18, 18, 2], k=6)
['red', 'green', 'black', 'black', 'red', 'black']
- # Probability of getting 5 or more heads from 7 spins
+ # Deal 20 cards without replacement from a deck of 52
+ # playing cards and determine the proportion of cards
+ # with a ten-value (i.e. a ten, jack, queen, or king).
+ >>> deck = collections.Counter(tens=16, low_cards=36)
+ >>> seen = sample(list(deck.elements()), k=20)
+ >>> print(seen.count('tens') / 20)
+ 0.15
+
+ # Estimate the probability of getting 5 or more heads from 7 spins
# of a biased coin that settles on heads 60% of the time.
>>> n = 10000
>>> cw = [0.60, 1.00]
@@ -360,8 +373,8 @@
Example of `statistical bootstrapping
<https://en.wikipedia.org/wiki/Bootstrapping_(statistics)>`_ using resampling
-with replacement to estimate a confidence interval for the mean of a small
-sample of size five::
+with replacement to estimate a confidence interval for the mean of a sample of
+size five::
# http://statistics.about.com/od/Applications/a/Example-Of-Bootstrapping.htm
from statistics import mean
--
Repository URL: https://hg.python.org/cpython
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