python_data_science_lesson_2.py

# Python Data Science lesson 2

# strings
greeting = "Hello, World!"
print(greeting)

# a string is a sequence of characters
print(greeting[0]) #=> 'H'

# index starts with 0, so index 5 is the 6th character
print(greeting[5]) #=> ','

#len() returns the length of a string
len(greeting) #=> 13

# lists
list = [1, 2, 3] 

# lists are zero indexed too
print(list[0]) #=> 1

# len() can also return the length of a list 
len(list) #=> 3

# lists can include different types of values
list = [1, 2, 'apple'] 
print(list)

# you can refer to an individual item in a list
print(list[0]) #=> 1
print(list[1]) #=> 2
print(list[2]) #=> 'apple'

# you can slice a list 
print(list[0:2]) #=> [1, 2]

# but the second value is not zero indexed
print(list[0:3]) #=> [1, 2, 'apple']

# you can add items to a list
list.append('banana') 
print(list) #=> [1, 2, 'apple', 'banana']

# you can insert an item at a certain position
list.insert(2, 'banana')
print(list) => [1, 2, 'banana', 'apple', 'banana']

# you can iterate through a list
  for i in list: 
    print(item) 

# and conditionally modify a list
for i in range(len(list)): 
	print(i, list[i]) 
		if (list[i] == 'banana'): 
			list.insert(i+1, 'orange') 

# it doesn't add after last item because the list size has increased but range has already been calculated

## Homework 1: Correct this loop to add orange after both instances of banana
## don't just correct it by doing this: 
list.append('orange') 

## Homework: Once you have a list that looks like this: 
[1, 2, 'banana', 'orange', 'apple', 'banana', 'orange']
## create a function that removes bananas from the list, so it looks like this:
[1, 2, 'orange', 'apple', 'orange']

#### use enumerate to return both the index and an item

for i, item in enumerate(list): 
	print(i, item) 
	if(str(item) == 'banana'): 
		print('removing banana at ', i) 
		list.pop(i)

# i, item is a tuple
# a tuple is an ordered list of related items
# Think of it like a row in a database

# Talk about items() and iteritems() for a dictionary and how it relates to enumerate()

# Talk about the difference between tabular data that is row based vs columnar based
# Row based is good for finding a single record: 
# SQL databases are typically row based
# 	select name, age, weight from people;

# Column based is good for doing analytics over all records
#   tell me the percentage of people who are overweight
#	with the definition of height < 72 inches and weight > 200 pounds

# You have to scan every row and aggregate with SQL, but you only have to load a single column to get all people over 200lb

# That's why data structures like Pandas DataFrame are so useful
# as opposed to looping through all records
# DataFrame is like a pivot table in a spreadsheet so that you can look at data either way, more efficiently