We’re going to use the free Anaconda Python distribution.

The Anaconda distribution includes Jupyter Lab, which is a web-based interactive development environment that is useful for doing data analysis and visualization.

Python basics:

  • variables, dynamic typing
  • lists
  • loops
  • conditions
  • functions

IPython notebook from class session (.ipynb)

a = 5
print(a)

5

from math import *


print(e)
print(pi)

2.718281828459045
3.141592653589793

print(cos(pi))

-1.0

a = 5 
print(a)
a = 7.2
print(a)
a = "hello"
print(a)

5
7.2
hello

things = [5, 7.2, "hello"]
print(things)
print(things[0])
print(things[1])
print(things[-1])  # negative indices!
print(things[0:2])    # slices

[5, 7.2, 'hello']
5
7.2
hello
[5, 7.2]

for a in things:
    print(a)
    print("blah")

5
blah
7.2
blah
hello
blah

if things[0] > 10:
    print("big")
elif things[0] > 4:    # else if
    print("medium")
else:
    print("small")
    

medium

print(2*3)
print(2+3)
print(2**3) # exponent

6
5
8

# print a geometric sequence
# 1, 2, 4, 8, 16, 32, ...

value = 1

for i in range(10):   #  [0, 1, ..., 9]
    print(value)
    value *= 2        # recursive definition



1
2
4
8
16
32
64
128
256
512

# explicit definition

for i in range(10):
    print(2**i)


1
2
4
8
16
32
64
128
256
512

# sum from 1 to n

n = 5
total = 0

for i in range(1, n+1):
    total += i
    
print(total)


15

# function

def sum(n):
    total = 0
    
    for i in range(1, n+1):
        total += i
        
    return total


print(sum(5))
print(sum(100))



15
5050

# fizz buzz
# print a sequence
# Fibonacci sequence
# factorial function

Python basics:

Exploratory data analysis: