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![Executable Pseudocode >>> def quicksort(array): ... if len(array) <= 1: ... return array ... pivot = array.pop(len(array)/2) ... lt = [] ... gt = [] ... for item in array: ... if item < pivot: ... lt.append(item) ... else: ... gt.append(item) ... return quicksort(lt) + [pivot] + quicksort(gt)](https://image.slidesharecdn.com/whypython-131111112046-phpapp01/75/Why-Python-for-Statisticians-17-2048.jpg)
![Imperative >>> def sum(items): ... total = 0 ... for item in items: ... total = total + item ... return total >>> sum([2, 4, 8]) 14](https://image.slidesharecdn.com/whypython-131111112046-phpapp01/75/Why-Python-for-Statisticians-20-2048.jpg)
![OO >>> class Summer: ... def __init__(self): ... self.items = [] ... def add_item(self, item): ... self.items.append(item) ... def sum(self): ... return sum(self.items) >>> >>> >>> >>> 5 s = Summer() s.add_item(2) s.add_item(3) s.sum()](https://image.slidesharecdn.com/whypython-131111112046-phpapp01/75/Why-Python-for-Statisticians-21-2048.jpg)
![Functional >>> import operator >>> sum = lambda x: reduce(operator.add, x) >>> sum([4, 8, 22]) 34](https://image.slidesharecdn.com/whypython-131111112046-phpapp01/75/Why-Python-for-Statisticians-22-2048.jpg)
Uploaded byMatt Harrison
Why Python (for Statisticians)
The document discusses the advantages of Python as a general-purpose programming language, especially for data analysis and scientific applications. It highlights its extensive community support, built-in libraries, and multi-paradigm capabilities, while also addressing some limitations. Additionally, it mentions various Python libraries used for data science, including NumPy, SciPy, and Pandas.
Why Python (for Statisticians)
- 1. Why Python? (ForStats People) @__mharrison__ © 2013
- 2. About Me ● ● ● 12+ yearsPython Worked in Data Analysis, HA, Search, Open Source, BI, and Storage Author of multiple Python Books
- 3.
- 4. Book Treading on PythonVolume 1 meant to make people proficient in Python quickly
- 5.
- 6. General Purpose Language “I’drather do math in a general-purpose language than do general-purpose programming in a math language.” John D Cook
- 7. Who's Using Python? ● Startups(on HN) ● Data Scientists (Strata) ● Big Companies
- 8.
- 9. Open Source Free inboth senses of the word
- 10.
- 11. Large Community PyPi -PYthon Package Index ● Web ● Database ● GUI ● Scientific ● Network Programming ● Games
- 12.
- 13. Local ● utahpython.org - 2ndThurs. 7pm ● Utah Open Source Conference
- 14.
- 15. Optimizes for ProgrammerTime “We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil.” Donald Knuth
- 16. Executable Pseudocode function quicksort(array) iflength(array) ≤ 1 return array // an array of zero or one elements is already sorted select and remove a pivot element pivot from 'array' // see '#Choice of pivot' below create empty lists less and greater for each x in array if x ≤ pivot then append x to less' else append x to greater return concatenate(quicksort(less), list(pivot), quicksort(greater)) // two recursive calls http://en.wikipedia.org/wiki/Quicksort
- 17. Executable Pseudocode >>> defquicksort(array): ... if len(array) <= 1: ... return array ... pivot = array.pop(len(array)/2) ... lt = [] ... gt = [] ... for item in array: ... if item < pivot: ... lt.append(item) ... else: ... gt.append(item) ... return quicksort(lt) + [pivot] + quicksort(gt)
- 18. But... Python has Timsort.Optimized for real world (takes advantage of inherent order) and written in C. (Stolen by Java, Android, and Octave)
- 19.
- 20. Imperative >>> def sum(items): ... total= 0 ... for item in items: ... total = total + item ... return total >>> sum([2, 4, 8]) 14
- 21. OO >>> class Summer: ... def__init__(self): ... self.items = [] ... def add_item(self, item): ... self.items.append(item) ... def sum(self): ... return sum(self.items) >>> >>> >>> >>> 5 s = Summer() s.add_item(2) s.add_item(3) s.sum()
- 22. Functional >>> import operator >>>sum = lambda x: reduce(operator.add, x) >>> sum([4, 8, 22]) 34
- 23.
- 24. Slow Sometimes you haveto optimize. Good C integration
- 25. If it ain'tbroke don't fix it Don't replace existing solutions for fun
- 26. R has moredepth Though Python is catching up in some areas
- 27.
- 28. IPython Notebook ● Notebook w/integrated graphs
- 29. Libraries ● Numpy - matrixmath ● scipy - scientific libraries ● scipy.stats - stats ● statsmodel - modeling ● pandas - dataframe ● matplotlib - graphing ● scikit.learn - ml
- 30. That's all Questions? Tweetme For beginning Python secrets see Treading on Python Volume 1 @__mharrison__ http://hairysun.com