x = [1, 2, 3, 4, 5, 6]

print(len(x))
print(x[:3])
print(x[-2:])

x.extend([7, 8])
print(x)

x.append(9)
print(x)

y = [10, 11, 12]

listOfLists = [x, y]

print(listOfLists)

6
[1, 2, 3]
[5, 6]
[1, 2, 3, 4, 5, 6, 7, 8, 7, 8]
[1, 2, 3, 4, 5, 6, 7, 8, 7, 8, 9, 9]
[[1, 2, 3, 4, 5, 6, 7, 8, 7, 8, 9, 9], [10, 11, 12]]

x = (1, 2, 3)
print(len(x))

y = (4, 5, 6)
print(y[2])

listOfTuples = [x, y]
print(listOfTuples)

(age, income) = "32,120000".split(',')
print(age)
print(income)

3
6
[(1, 2, 3), (4, 5, 6)]
32
120000

# Like a map or hash table in other languages
captains = {}
captains["Enterprise"] = "Kirk"
captains["Enterprise D"] = "Picard"
captains["Deep Space Nine"] = "Sisko"
captains["Voyager"] = "Janeway"

print(captains["Voyager"])

print(captains.get("Enterprise"))

print(captains.get("NX-01"))

# Iterate the keys
for ship in captains:
    print(ship + ": " + captains[ship])

Janeway
Kirk
None

Enterprise: Kirk
Enterprise D: Picard
Deep Space Nine: Sisko
Voyager: Janeway

def SquareIt(x):
    return x * x

print(SquareIt(2))

#You can pass functions around as parameters
def DoSomething(f, x):
    return f(x)

print(DoSomething(SquareIt, 3))

#Lambda functions let you inline simple functions
print(DoSomething(lambda x: x * x * x, 3))

4
9
27

for x in range(10):
    if (x == 1):
        continue
    if (x > 5):
        break
    print(x)

x = 0
while (x < 5):
    print(x)
    x += 1

0
2
3
4
5

0
1
2
3
4

import pandas as pd

df = pd.read_csv("../assets/PastHires.csv")
df.head(5)
df.tail(4)

df.shape
df.size
len(df)
df.columns

(13, 7)
91
13
Index(['Years Experience', 'Employed?', 'Previous employers',
       'Level of Education', 'Top-tier school', 'Interned', 'Hired'],
      dtype='object')

df['Hired'][:5]

0    Y
1    Y
2    N
3    Y
4    N
Name: Hired, dtype: object

df[['Years Experience', 'Hired']]

df.sort_values(['Years Experience'])

degree_counts = df['Level of Education'].value_counts()
degree_counts

Level of Education
BS     7
PhD    4
MS     2
Name: count, dtype: int64

degree_counts.plot(kind='bar')