Python basic data types

One step back: here we look at the built-in data types which are available without loading any modules.

Built-in data types and operations

There are four distinct numeric types:

In addition, Booleans are a subtype of plain integers

Boolean

Boolean (logical) types

Operations

x + y           sum of x and y
x - y           difference of x and y   
x * y           product of x and y      
x / y           quotient of x and y
x // y          (floored) quotient of x and y
x % y           remainder of x / y
-x              x negated       
+x              x unchanged     
abs(x)          absolute value or magnitude of x        
int(x)          x converted to integer
long(x)         x converted to long integer 
float(x)        x converted to floating point   
complex(re,im)  a complex number with real part re, 
                imaginary part im. im defaults to zero
c.conjugate()   conjugate of the complex number c
x ** y          x to the power y

Boolean Operations: and, or, not

x or y          if x is false, then y, else x 
x and y         if x is false, then x, else y 
not x           if x is false, then True, else False    

Comparisons

<               strictly less than      
<=              less than or equal      
>               strictly greater than   
>=              greater than or equal   
==              equal   
!=              not equal       

is              object identity         

Sequence types

Operations

x in s  True if an item of s is equal to x, else False  
x not in s      False if an item of s is equal to x, 
        else True       
s + t   the concatenation of s and t    
s[i]    i'th item of s
s[i:j]  slice of s from i to j  
s[i:j:k] slice of s from i to j with step k
len(s)  length of s     
min(s)  smallest item of s      
max(s)  largest item of s       

Variables, assignment

The assignment statement = creates new variables and gives them values

a=2
l=9**1000L
S='Hello'
f=1e5

Lists and tuples

In [5]: a=[1,2,3]
In [6]: b=(1,2,3)

In [7]: a[0]
Out[7]: 1

In [8]: b[0]
Out[8]: 1

In [9]: a[0]=4

In [10]: a
Out[10]: [4, 2, 3]

In [11]: b[0]=4
---------------------------------------------------------------------------
exceptions.TypeError 

Indexing and slicing

In [1]: a=range(10)

In [2]: a
Out[2]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

In [3]: a[0:4]
Out[3]: [0, 1, 2, 3]

In [4]: a[4:]
Out[4]: [4, 5, 6, 7, 8, 9]

In [5]: a[:4]
Out[5]: [0, 1, 2, 3]

In [6]: a[:-1]
Out[6]: [0, 1, 2, 3, 4, 5, 6, 7, 8]

In [7]: s='Hello world'
In [8]: s[:5]
Out[8]: 'Hello'

In [9]: a=tuple(range(10))
In [10]: a[0:4]
Out[10]: (0, 1, 2, 3)

List built-in functions (methods)

In [72]: L=['C','A','B']
In [73]: L.sort()

In [74]: L
Out[74]: ['A', 'B', 'C']

In [75]: L.pop()
Out[75]: 'C'

In [76]: L
Out[76]: ['A', 'B']

In [77]: L.insert(1,'C')

In [78]: L
Out[78]: ['A', 'C', 'B']

Nested data structures

In [84]: a=range(10)
In [85]: b=range(0,10,2)
In [86]: b
Out[86]: [0, 2, 4, 6, 8]

In [87]: c=[a,b]

In [88]: c
Out[88]: [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 2, 4, 6, 8]]

In [91]: c[0]
Out[91]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

In [92]: c[1]
Out[92]: [0, 2, 4, 6, 8]

In [93]: c[0][0:4]
Out[93]: [0, 1, 2, 3]

In [94]: c[1][0:4]
Out[94]: [0, 2, 4, 6]

Dictionary

In [95]: D={}
In [96]: D['a']=range(10)
In [97]: D['b']=range(0,10,2)

In [98]: D
Out[98]: {'a': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], 'b': [0, 2, 4, 6, 8]}

In [99]: D['a']
Out[99]: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

In [100]: D.keys()
Out[100]: ['a', 'b']

Loops

In [106]: a=['Hund','Katze','Maus']
In [108]: for i in a:
   .....:     print i
   .....:
Hund
Katze
Maus

In [111]: for i,j in enumerate(a):
   .....:     print i,j
   .....:
0 Hund
1 Katze
2 Maus

Control statements

In [116]: if a==1:
   .....:     print 'a=1'
   .....: else:
   .....:     print 'a != 1'
   .....:
a=1

LehreWiki: PythonQuickstart/Python basics (last edited 2013-04-04 08:20:46 by anonymous)