# Introduction to Python¶

## Variables¶

In [2]:
#A variable stores a piece of data and gives it a name

#answer contained an integer because we gave it an integer!

is_it_thursday = True
is_it_wednesday = False

#these both are 'booleans' or true/false values

pi_approx = 3.1415

#This will be a floating point number, or a number containing digits after the decimal point

my_name = "Jacob"
#This is a string datatype, the name coming from a string of characters

#Data doesn't have to be a singular unit

#p.s., we can print all of these with a print command. For Example:
print(pi_approx)

42
3.1415


### More Complicated Data Types¶

In [3]:
#What if we want to store many integers? We need a list!
prices = [10, 20, 30, 40, 50]

#This is a way to define a list in place. We can also make an empty list and add to it.
colors = []

colors.append("Green")
colors.append("Blue")
colors.append("Red")

print(colors)

#We can also add unlike data to a list
prices.append("Sixty")

#As an exercise, look up lists in python and find out how to add in the middle of a list!

print(prices)
#We can access a specific element of a list too:

print(colors[0])
print(colors[2])

#Notice here how the first element of the list is index 0, not 1!
#Languages like MATLAB are 1 indexed, be careful!

['Green', 'Blue', 'Red']
[10, 20, 30, 40, 50, 'Sixty']
Green
Red


### Using Variables¶

In [4]:
float1 = 5.75
float2 = 2.25
#Addition, subtraction, multiplication, division are as you expect

print(float1 + float2)
print(float1 - float2)
print(float1 * float2)
print(float1 / float2)

#Here's an interesting one that showed up in the first homework in 2017. Modulus:
print(5 % 2)

8.0
3.5
12.9375
2.5555555555555554
1


### Importing in Python: Math and plotting¶

In [7]:
#Just about every standard math function on a calculator has a python equivalent pre made.
#however, they are from the 'math' package in python. Let's add that package!
import math
print(math.log(float1))
print(math.exp(float2))
print(math.pow(2,5))
# There is a quicker way to write exponents if you want:
print(2.0**5.0)

#We can plot easily in Python like in matlab, just import the relevant package!
%matplotlib inline
import matplotlib.pyplot as plt

x_vals = [-2, -1, 0, 1, 2]
y_vals = [-4, -2, 0, 2, 4]
plt.plot(x_vals, y_vals)

1.749199854809259
9.487735836358526
32.0
32.0

Out[7]:
[<matplotlib.lines.Line2D at 0x115181f28>]

### Loops in Python¶

In [6]:
#Repeat code until a conditional statement ends the loop

#Let's try printing a list
fib = [1, 1, 2, 3, 5, 8]

#While loops are the basic type
i = 0
while(i < len(fib)):
print(fib[i])
i = i + 1

#In matlab, to do the same thing you would have the conditional as: counter < (length(fib) + 1)
#This is because matlab starts indexing at 1, and python starts at 0.

#The above type of loop is so common that the 'for' loop is the way to write it faster.

print("Let's try that again")
#This is most similar to for loops in matlab
for i in range(0, len(fib)) :
print(fib[i])

print("One more time:")
#Or you can do so even neater
for e in fib:
print(e)

1
1
2
3
5
8
Let's try that again
1
1
2
3
5
8
One more time:
1
1
2
3
5
8