Download In: x - UCF Complex Adaptive Systems Laboratory

MSDA Computer Programming
Bridge Course
Ozlem Garibay
Chathika Gunaratne
Outline
• Concepts and hands on exercises
• Sessions
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Introductions, installation, intro to python
Data types,
Functions and Methods
Packages,
Numpy
Plotting with Matplotlib
Pandas
Review/Test
Intro to Python
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Interpreter, No compiling
Portable, free
No need to define vars
Object Oriented and functional
Good for rapid prototyping, Numeric and
Scientific Programming, internet scripting, system
programming, gaming, imaging, data mining, etc.
• Operators: intuitive, overloaded
– +: concatenate and plus
– *: repeat and multiply
Python Installation
• What you need:
– Python
– Terminal
– Text editor(textwrangler)
• Installation
– https://docs.google.com/document/d/1ICODI2rT4
IXay8TN1P5DjqxMyDKxv81o_s2aBkmrVw/edit?usp=sharing
Python Shell
• To run from the shell:
– python
– x=‘MSDA inaugural cohort’
– len(x); x[5]
– y=‘ hi’; z=5
– x+y
– x+y+z
– x+y+str(z)
• Multi=line commands:
>>> for x in 'spam':
print(x)
Python Script
• Python script
– Indentation is important.
– Hello.py
import sys # import modules (functions)
def main():
print ‘Hello there’, sys.argv[1]
# to call the main() function
if __name__==‘__main__’:
main()
– python hello.py arg1 arg2 arg3 …
OR
– ./hello.py arg1 arg2 arg3 …
• python: to start a Python shell and ctrl-D to exit
Example
Python Help
• To get help
– help(function_name)
• help(del) or ?del
– Search online
– dir(object)
• Common functions:
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Print(a)
Type(a)
Len(a)
Sorted(a)
• Programs>Modules>Statements>Expressions>Objects
Intro to Python
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If control statement (if, elif, else)
if withdraw >balance:
return(false)
else:
balance-=withdraw
return(true)
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for loop
>>> for c in 'spam':
print(c.upper())
S
P
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M
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while loop
>>> x=4
>>> while x>0:
print('spam!'*x)
x-=1
spam!spam!spam!spam!
spam!spam!spam!
spam!spam!
spam!
Data Types
• Dynamically and strongly typed
• Single Value:
– Numbers
• Int: integer
• Float : real number
– Bool: true or false
– Str: string
• Multiple Value:
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List [a, b, c]
Dictionary
Tuple
File
Set
Numbers
• >>>a=5
• >>>a*3
15
• >>>a**2
25
• >>>Import math
• >>>math.pi
3.1415…
• >>>math.sqrt(49)
7
• >>>import random
• >>>random.random() # generate a random number
• >>>random.choice([2,1,7,9,5]) #randomly select from the list
Strings
• >>>s=‘spam’
• >>>s[0]
‘s‘
• >>>len(s)
4
• >>>S.replace(‘pa’, ’xyz’)
‘sxyzm’
• >>>s
‘spam’
• >>>s.isalpha()
True
• >>>s.upper()
‘SPAM’
• >>>s=‘aaa,bbb,ccc,ddd’
• >>>s.split(‘,’)
[‘aaa’, ‘bbb’, ‘ccc’, ‘ddd’]
• ‘%s pizza and %s please’ %(‘cheese’, ‘coke’)
Lists
• Indexing: Zero indexed
– Fam=[“mary”, 52, “john”, 55, “jeff”, 15, “sally”, 10]
Index
Negative index
0
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7
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-6
-5
-4
-3
-2
-1
Fam[5]=15
Fam[2]=“john”
Fam[-1]=10
Fam[-6]=“john”
• Slicing:
– Fam=[“mary”, 52, “john”, 55, “jeff”, 15, “sally”, 10]
Index
0
1
2
Fam[3:6]=[55, ”jeff”, 15]
3
4
5
[start: end]
Inclusive Exclusive
Fam[:6]=[“mary”, 52, “john”, 55, ”jeff”, 15]
Fam[3:]=[55, ”jeff”, 15, “sally”, 10]
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Lists
• Fam=[52, 55, 15, 10]
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>>> del Fam[1]
>>> Fam
[52, 15, 10]
>>> Fam.pop(1)
55
>>> Fam
[52, 15, 10]
>>> Fam.sort()
>>> Fam
[10, 15, 52]
>>> Fam.reverse()
>>> Fam
[52, 15, 10]
List - Nesting
• In: house=[['hallway', 11.25],
['kitchen', 18.0],
['living room', 20.0],
['bedroom', 10.75],
['bathroom', 9.5]]
• In: house[-1][1:]
• Out: [9.5]
• >>>col1=[i[0] for i in house]
Manipulating List
• In: x=['a', 'b', 'c']
– Changing
• In: x[0]=‘t’
• x=[‘t', 'b', 'c']
– Adding
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In: x=x + [‘z‘]
[‘t', 'b', 'c’, ‘z’]
In: x.append(‘r’)
[‘t', 'b', 'c’, ‘z’, ’r’]
• y=x
– y=[‘b', ‘c', ‘z']
– x and y point to the same list.
x
[‘b', ‘c', ‘z']
y
Copying List
• y=list(x) or y=x[:]
• Two copies of the list, x and y points to two
separate lists
• x[0]=‘k’
x
[‘b', ‘c', ‘z']
y
[‘b', ‘c', ‘z']
• x=[‘k', ‘c', ‘z']
• y=[‘b', ‘c', ‘z']
Example
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>>> L=range(3, 17, 3)
>>> L
[3, 6, 9, 12, 15]
Filter out the odd numbers
>>> [L[i] for i in range(5) if L[i] %2==0]
[6, 12]
Example
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Create a 4 x 4 matrix and collect a diagonal from the matrix.
>>> m=range(6,10); l=range(16,20); k=range(26,30)
>>> m
[6, 7, 8, 9]
>>> z=[l,m,k,n]
>>> z
[[16, 17, 18, 19], [6, 7, 8, 9], [26, 27, 28, 29], [7, 8, 9, 10]]
>>> d=[z[i][i] for i in [3,2,1,0]]
>>> d
[10, 28, 7, 16]
Dictionaries
• Mapping
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Stores objects by key instead of relative position.
>>> D1={}
>>> D1['name']='Bob'
>>> D1['age']=40
>>> D1['gender']='M'
>>> D1
{'gender': 'M', 'age': 40, 'name': 'Bob'}
>>> D2=dict(name='Lisa', age=25, gender='F')
>>> D2
{'gender': 'F', 'age': 25, 'name': 'Lisa'}
>>> D3=dict(zip(['name','age','gender'],['Sally',63,'F']))
>>> D3
{'gender': 'F', 'age': 63, 'name': 'Sally'}
Dictionaries
• >>> record={'name':{'first':'bob', 'last': 'smith'}, 'age':
40, 'job':['dev', 'mgr']}
• >>> record
• {'job': ['dev', 'mgr'], 'age': 40, 'name': {'last': 'smith',
'first': 'bob'}}
• >>> record['name']
• {'last': 'smith', 'first': 'bob'}
• >>> record['name']['last']
• 'smith'
• >>> record['job'][-1]
• 'mgr'
Tuples
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Sequences similar to list
Immutable similar to string
Supports arbirary types and nesting
Allows to preserve integrity
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T=(1,2,3,4)
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len(T)
Out[2]: 4
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T+(5,6)
Out[3]: (1, 2, 3, 4, 5, 6)
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T
Out[4]: (1, 2, 3, 4)
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T.index(4)
Out[6]: 3
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T.count(4)
Out[7]: 1
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T[0]
Out[5]: 1
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T[0]=2
TypeError: 'tuple' object does not
support item assignment
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T.append(2)
AttributeError: 'tuple' object has no
attribute 'append'
Files
• Read/write
• Text,audio,excel,email
• f=open('firstfile.txt', 'w')
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ls
08/04/2016 11:01 AM <DIR>
.
08/04/2016 11:01 AM <DIR>
..
08/04/2016 10:48 AM
283,147 bridge_august1.pptx
08/04/2016 11:01 AM
0 firstfile.txt
08/02/2016 11:49 AM <DIR>
google-python-exercises
08/01/2016 01:17 PM <DIR>
overview
5 File(s)
502,233 bytes
4 Dir(s) 17,767,260,160 bytes free
• f.write('first file\n write example')
Files
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f.close()
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filecontect=f.read()
ValueError: I/O operation on closed file
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f=open('firstfile.txt')
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filecontext=f.read()
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filecontext
Out[22]: 'first file\n write example'
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print(filecontext)
first file
write example
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filecontext.split()
Out[24]: ['first', 'file', 'write', 'example']
Sets
• Unordered collections of unique and
immutable objects.
• Neither sequence nor mapping
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>>> X=set('spam')
>>> Y={'h','a','m'}
>>> X,Y
(set(['a', 'p', 's', 'm']), set(['a', 'h', 'm']))
>>> X&Y
# intersection
set(['a', 'm'])
>>> X|Y
##union
set(['a', 'p', 's', 'h', 'm'])
>>> X-Y
set(['p', 's'])
>>> X>Y
#superset?
False
>>> l=[1,2,1,3,1] #filter out duplicate
>>> l=list(set(l))
>>> l
[1, 2, 3]
>>> set('spam')-set('ham') # finding out differences in collections
set(['p', 's'])
>>> set('spam')==set('pams') #order neutral equality
True
>>> 'p' in set('spam')
True
Numerical Operators
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Operators: +,-,*,/,>>,**,& etc.
Functions: Pow, abs,round,int,float etc.
Modules: random, math etc.
>>>x=40; x/3
13
>>> x//3
13
>>> float(x)/3
13.333333333333334
>>> type(x)
<type 'int'>
>>> x=float(x)
>>> type(x)
<type 'float'>
Numerical Operators
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>>> x/3
13.333333333333334
>>> z=7
>>> x+y*z
71.5
>>> y
4.5
>>> (x+y)*z
311.5
>>> 1<2
True
>>> x>z>y
True
>>> z<x>y
True
>>> x!=y<z
True
Functions
• Piece of code to do a particular task.
– output = function_name(input1[,input2, …])
– max(), round(), str(), int(), type(), bool(), float(),
sorted()
– Ex: a=[20.0, 18.0, 11.25, 10.75, 9.5]
max(a) -> 20.0
– To get help
• help(function_name)
– help(max) or ?max
Methods
• Methods: Functions called on objects
• In python, eveything=object
• Object have methods associated with them
depending on type.
– Ex: fam=[“mary”, 52, “john”, 55, “jeff”, 15, “sally”, 10]
Index 0
1
2
3
4
5
6
7
In: fam.index(“john”) # call method index() on fam list object
Out: 2
In: fam.append(“jason”) # call method append() to add “jason” in
the list
In: fam
Out: mary”, 52, “john”, 55, “jeff”, 15, “sally”, 10, “jason”]
Example
Example
Example
Exercise List2
Example - Wordcount
Example - Wordcount
Example - Wordcount