snippets for Parsons "Intro to Python" training

snippets.py

# Here's some data to play with!

data = [
    {'first_name': 'Megan', 'last_name': 'Rapinoe', 'age': '37', 'date_updated': '1674121763'}, 
    {'first_name': 'Tobin', 'last_name': 'Heath', 'age': '34', 'date_updated': '1664121763'}, 
    {'first_name': 'Crystal', 'last_name': 'Dunn', 'age': '31', 'date_updated': '1664121763'}, 
    {'first_name': 'Midge', 'last_name': 'Purce', 'age': '26', 'date_updated': '1664121763'}, 
    {'first_name': 'Sophia', 'last_name': 'Smith', 'age': '23', 'date_updated': '1664121763'}
]

# This is a list of dictionaries, which are filled with strings.

# (Lists and dictionaries can hold different types of things, including other lists and dictionaries!)

# We can access them like this:

midge_age = data[4]["age"]     # Note: zero-indexing, different ways to access list and dictionary



# what if you look for a key that's not there?

midge_vote = data[4]["voter_status"]   # oh no an error!

midge_vote = data[4].get("voter_status")  # returns None

midge_vote = data[4].get("voter_status", "unknown")  # can set a default value



print(type(midge_age))  # check types  (note: nesting print and type here)

new_variable = int(midge_age)  # convert types
print(type(new_variable))   

# Python built-in types: integer, string, boolean, float, list, dict, object, None

# One common but more complex type is datetimes

import datetime   # imports are a thing!

result = datetime.datetime.fromtimestamp(data[0]["date_updated"])
print(type(result))



for person in data:  # iterating through a list gives the whole item
    print(person)

for column_name in data[0]:  # iterating through a dictionary just gives the key
    print(column_name)

for column_value in data[0].values():   # get values instead
    print(column_value)

for column_name, column_value in data[0].items():  # get both!
    print(column_name, column_value)



# Fancy way to do this in Python: "comprehensions"

ages = [person["age"] for person in data]

data_dict = { person["last_name"]: [person["first_name"], person["age"]] for person in data }



# What if you want to select some things and not others? 

for person in data:
    if int(person["age"]) > 30:
        print(f"{person['first_name'] person['last_name'] is over 30!}")      # hey, f-strings!
    else:
        print(f"{person['first_name'] person['last_name'] is under 30!}")     

# Add conditions with "elif":

for person in data:
    if int(person["age"]) > 30:
        print(f"{person['first_name'] person['last_name'] is over 30!}")      # hey, f-strings!
    elif int(person["age"]) > 25:
        print(f"{person['first_name'] person['last_name'] is over 25 but under 30!}")    
    else:
        print(f"{person['first_name'] person['last_name'] is under 30!}")  

# Note: sometimes we "refactor" to remove redundant bits, like so:

for person in data:
    age_string = ""
    if int(person["age"]) > 30:
        age_string = "over 30"    
    elif int(person["age"]) > 25:
        age_string = "over 25 but under 30"    
    else:
        age_string ="under 30"  
    print(f"{person['first_name'] person['last_name'] is {age_string}}!")

# See also: continue, break

# You can use if/else with comprehensions!

ages_over_30 = [person["age"] for person in data if int(person["age"]) > 30]



# Move things into functions

def create_age_string(person):

    age_string = ""
    if int(person["age"]) > 30:
        age_string = "over 30"    
    elif int(person["age"]) > 25:
        age_string = "over 25 but under 30"    
    else:
        age_string ="under 30"  

    return f"{person['first_name'] person['last_name'] is {age_string}}!"


for person in data:
    print(create_age_string(person))


# Can set multiple inputs, default values, keyword arguments, etc



# Loading data from an external file like a csv.


# Version 1: With Python Standard Library

import csv


with open('data.csv') as csvfile:
    reader = csv.DictReader(csvfile)
    data = list(reader)

print(data)


# Version 2: With Parsons

from parsons import Table
import datetime

data = Table.from_csv(".data.csv")

print(data)