# variable assignment
# https://www.digitalocean.com/community/tutorials/how-to-use-variables-in-python-3

# strings -- enclose in single or double quotes, just make sure they match


# numbers



# the print function



# booleans



"""
Explanation: Python fundamentals
A quick introduction to the Python programming language and Jupyter notebooks. (We're using Python 3, not Python 2.)
Basic data types and the print() function
End of explanation
"""


# addition


# subtraction


# multiplication


# division


# etc.

"""
Explanation: Basic math
You can do basic math with Python. (You can also do more advanced math.)
End of explanation
"""


# create a list: name, hometown, age
# an item's position in the list is the key thing


# create another list of mixed data


# use len() to get the number of items in the list




# use square brackets [] to access items in a list
# (counting starts at zero in Python)

# get the first item



# you can do negative indexing to get items from the end of your list

# get the last item



# Use colons to get a range of items in a list

# get the first two items
# the last number in a list slice is the first list item that's ~not~ included in the result



# if you leave the last number off, it takes the item at the first number's index and everything afterward
# get everything from the third item onward



# Use append() to add things to a list



# Use pop() to remove items from the end of a list



# use join() to join items from a list into a string with a delimiter of your choosing




"""
Explanation: Lists
A comma-separated collection of items between square brackets: []. Python keeps track of the order of things inside a list.
End of explanation
"""




# Access items in a dictionary using square brackets and the key (typically a string)



# You can also use the `get()` method to retrieve values
# you can optionally provide a second argument as the default value
# if the key doesn't exist (otherwise defaults to `None`)



# Use the .keys() method to get the keys of a dictionary


# Use the .values() method to get the values


# add items to a dictionary using square brackets, the name of the key (typically a string)
# and set the value like you'd set a variable, with =



# delete an item from a dictionary with `del`



"""
Explanation: Dictionaries
A data structure that maps keys to values inside curly brackets: {}. Items in the dictionary are separated by commas. Python does not keep track of the order of items in a dictionary; if you need to keep track of insertion order, use an OrderedDict instead.
End of explanation
"""


# date in m/d/yyyy format


# split out individual pieces of the date
# using a shortcut method to assign variables to the resulting list


# reshuffle as yyyy-mm-dd using .format()
# use a formatting option (:0>2) to left-pad month/day numbers with a zero




# construct a greeting template


"""
Explanation: Commenting your code
Python skips lines that begin with a hashtag # -- these lines are used to write comments to help explain the code to others (and to your future self).
Multi-line comments are enclosed between triple quotes: """   """
Comparison operators
When you want to compare values, you can use these symbols:

&lt; means less than
&gt; means greater than
== means equal
&gt;= means greater than or equal
&lt;= means less than or equal
!= means not equal

String functions
Python has a number of built-in methods to work with strings. They're useful if, say, you're using Python to clean data. Here are a few of them:
strip()
Call strip() on a string to remove whitespace from either side. It's like using the =TRIM() function in Excel.
upper() and lower()
Call .upper() on a string to make the characters uppercase. Call .lower() on a string to make the characters lowercase. This can be useful when testing strings for equality.
replace()
Use .replace() to substitute bits of text.
split()
Use .split() to split a string on some delimiter. If you don't specify a delimiter, it uses a single space as the default.
zfill()
Among other things, you can use .zfill() to add zero padding -- for instance, if you're working with ZIP code data that was saved as a number somewhere and you've lost the leading zeroes for that handful of ZIP codes that begin with 0.
Note: .zfill() is a string method, so if you want to apply it to a number, you'll need to first coerce it to a string with str().
slicing
Like lists, strings are iterables, so you can use slicing to grab chunks.
startswith(), endswith() and in
If you need to test whether a string starts with a series of characters, use .startswith(). If you need to test whether a string ends with a series of characters, use .endswith(). If you need to test whether a string is part of another string -- or a list of strings -- use .in().
These are case sensitive, so you'd typically .upper() or .lower() the strings you're comparing to ensure an apples-to-apples comparison.
String formatting
Using curly brackets with the various options available to the .format() method, you can create string templates for your data. Some examples:
End of explanation
"""


# two strings of numbers


# what happens when you add them without coercing?


# coerce to integer, then add them


"""
Explanation: Type coercion
Consider:
```python
this is a number, can't do string-y things to it
age = 32
this is a string, can't do number-y things to it
age = '32'
```
There are several functions you can use to coerce a value of one type to a value of another type. Here are a couple of them:

int() tries to convert to an integer
str() tries to convert to a string
float() tries to convert to a float
End of explanation
"""


