wind = 'Southeast'

def describe_the_wind():
  return f'The wind blows from the {wind}'

describe_the_wind()

def describe_the_wind(wind):
  return f'The wind blows from the {wind}'

describe_the_wind('Northeast')

WINDS = ['Northeast', 'Northwest', 'Southeast', 'Southwest']
WIND = WINDS[0]

def change_wind():
  global WIND
  WIND = WINDS[(WINDS.index(WIND) + 1)%3]
  
WIND

change_wind()
WIND

for _ in WINDS:
  print(WIND)
  change_wind()

def change_wind(wind_index):
  winds = ['Northeast', 'Northwest', 'Southeast', 'Southwest']
  return winds[wind_index]

print( change_wind(0) )
print( change_wind(1) )
print( change_wind(2) )
print( change_wind(3) )

def change_mutable_data(data):
  '''A function which changes
  mutable data.'''
  data['owner'] = 'White Star Line'

  
d = {"vehicle": "ship", "owner": "Joseph Bruce Ismay"}

change_mutable_data(d)
d

d = {"vehicle": "ship", "owner": "Joseph Bruce Ismay"}

def change_owner(data):
  new_data = data.copy()
  new_data['owner'] = 'White Star Line'
  return new_data


changed = change_owner(d)
changed

import pandas as pd
moby_dick_quotes = [
    """It is not down on any map; true places never are.""",
    """
    Consider the subtleness of the sea; how its most dreaded creatures glide under water, unapparent for the most part, and treacherously hidden beneath the loveliest tints of azure. Consider also the devilish brilliance and beauty of many of its most remorseless tribes, as the dainty embellished shape of many species of sharks. Consider, once more, the universal cannibalism of the sea; all whose creatures prey upon each other, carrying on eternal war since the world began. 
    Consider all this; and then turn to the green, gentle, and most docile earth; consider them both, the sea and the land; and do you not find a strange analogy to something in yourself? For as this appalling ocean surrounds the verdant land, so in the soul of man there lies one insular Tahiti, full of peace and joy, but encompassed by all the horrors of the half-known life. God keep thee! Push not off from that isle, thou canst never return!
    """,
    """
    The sea had jeeringly kept his finite body up, but drowned the infinite of his soul. Not drowned entirely, though. Rather carried down alive to wondrous depths, where strange shapes of the unwarped primal world glided to and fro before his passive eyes; and the miser-merman, Wisdom, revealed his hoarded heaps; and among the joyous, heartless, ever-juvenile eternities, Pip saw the multitudinous, God-omnipresent, coral insects, that out of the firmament of waters heaved the colossal orbs. He saw God’s foot upon the treadle of the loom, and spoke it; and therefore his shipmates called him mad. So man’s insanity is heaven’s sense; and wandering from all mortal reason, man comes at last to that celestial thought, which, to reason, is absurd and frantic; and weal or woe, feels then uncompromised, indifferent as his God.
    """
]
df = pd.DataFrame(moby_dick_quotes)
df.columns = ["quotes"]
df.head()

def classify_religious(column):
  """Creates Religion Feature"""
  
  if "God" in column:
    return "Religious"
  return "Secular"

df["quote_type"] = df["quotes"].apply(classify_religious)
df.head()
  

def count_flower_petals(d):
  return f"{d} petals counted so far"

counts = map(count_flower_petals, [0,1,2,3,4,5])


list(counts)

l1 = [0,1,2,3,4]
l2 = [10,9,8,7,6]

def multi(d1, d2):
  return d1 * d2

result = map(multi, l1, l2)
print( list(result) )

initial_balance = 10000
debits = [20, 40, 300, 3000, 1, 234]


balance = initial_balance

for debit in debits:
  balance -= debit
  
balance

inital_balance = 10000
debits = [20, 40, 300, 3000, 1, 234]
from functools import reduce

def minus(a, b):
  return a - b

balance = reduce(minus, debits, initial_balance)
balance

inital_balance = 10000
debits = [20, 40, 300, 3000, 1, 234]

from functools import reduce
import operator

print( reduce(operator.sub, debits, initial_balance) )

characters = ['C', 'b', 'c', 'A', 'b','P', 'g', 'S']

def cap(a):
  return a.isupper()

retval = filter(cap, characters)

list(retval)

names = ['tim', 'tiger', 'tabassum', 'theodora', 'tanya']

capd = []

for name in names:
  capd.append(name.title())
  
capd

names = ['tim', 'tiger', 'tabassum', 'theodora', 'tanya']

capd = [x.title() for x in names]

capd

def count_flower_petals(d):
  return f"{d} petals counted so far"

counts = map(count_flower_petals, [0,1,2,3,4,5])

list(counts)

[f"{x} petals counted so far" for x in [0,1,2,3,4,5]]

characters = ['C', 'b', 'c', 'A', 'b','P', 'g', 'S']

def cap(a):
  return a.isupper()

retval = filter(cap, characters)

list(retval)

characters = ['C', 'b', 'c', 'A', 'b','P', 'g', 'S']

[x for x in characters if x.isupper()]

horts = [ 32.0, 54.12, 12.4, 89.09]
verts = [ 15.9, -34.21, 45.54, 90]

[ f'x: {x} y: {y}' for x,y in zip(horts, verts) ]

list(zip(horts, verts))

list_of_lists = [[1,2,3], [4,5,6], [7,8,9]]


[x for y in list_of_lists for x in y]

# Integers greater than and with 3 as a factor divided by 2


[y for y in range(20)]

[y for y in range(20) if y%3==0]

[x//2 for x in [y for y in range(20) if y%3==0] if x > 3]

rows = [{'name': 'barry', 'id': 1},
        {'name': 'henry', 'id': 3},
        {'name': 'suzy', 'id': 2}]

{ x['name']: x['id'] for x in rows}