Pub Quiz

Create your team

You can be from 3 to 5 people
Get a blue and a red pen and a sheet of paper
Write at the top of the paper:
- Your team name
- The names of the members of your team

How it works?

Questions

There will be 5 rounds
Each round has one question of each of the next categories:
1. What's the output of the script?
  - consider the latest version of CPython and libraries
2. PyData community
3. Which library is it?
4. Monty Python
5. Python version
6. Barcelona
For each answer write:
- The round
- The question
- In the format R1Q1
You can't check your phones, tablets, laptops... during the rounds

How it works

Answers

At the end of each round, we'll give the answers
Give your paper with the answers to the team next to you
Write in red the points:
- 0 for wrong answers
- 1 for right answers
- 3 for exceptionally good answers (we'll let you know)
At the end, add up all the answers, and report the total

Example

R9Q9 - Which library is it?

import who_am_i as wai


df = wai.read_csv('some_clean_data.csv',
                  parse_dates=True,
                  index_col='id')
df.describe()
df['val'].plot()

Write in your paper:

R1Q1: pandas

Points to other teams:

R1Q1: pandas 1

Round 1

R1Q1: What's the output?

>>> first, *middle, last = range(10)
>>> other = [last] * 8
>>> sum(zip(middle, other), tuple())[::2]

R1Q2: Community

Who is the creator of Pandas, and author of the book Python for Data Analysis?

R1Q3: Which library is it?

>>> import who_am_i as wai
>>> import numpy as np
>>>
>>> t = np.arange(0.0, 2.0, 0.01)
>>> s = 1 + np.sin(2 * np.pi * t)
>>> wai.plot(t, s)
>>> wai.xlabel('Some numbers')
>>> wai.ylabel('Sine')
>>> wai.title('Sine of some numbers')
>>> wai.grid(True)
>>> wai.show()

R1Q4: Monty Python

From which Monty Python movie is this frame?

R1Q5: Python version

Since which version of Python this is valid Python code?

>>> earth_radius = 6_371
>>> print(f'The radius of earth is {earth_radius}')

R1Q6: Python Barcelona

How many meetups, the Barcelona Python Meetup has held until today?

Round 1: Answers

R1Q1: What's the output?

>>> first, *middle, last = range(10)
>>> other = [2] * 8
>>> sum(zip(middle, other), tuple())[::2]

(1, 2, 3, 4, 5, 6, 7, 8) → 3

[1, 2, 3, 4, 5, 6, 7, 8] → 1

R1Q1: What's the output?

>>> first, *middle, last = range(10)
>>> first
0
>>> middle
[1, 2, 3, 4, 5, 6, 7, 8]
>>> last
9

>>> other = [last] * 8
>>> other
[9, 9, 9, 9, 9, 9, 9, 9]

>>> zip_val = list(zip(middle, other))
>>> zip_val
[(1, 9), (2, 9), (3, 9), (4, 9), (5, 9), (6, 9), (7, 9), (8, 9)]

>>> sum_val = sum(zip_val, tuple())
>>> sum_val
(1, 9, 2, 9, 3, 9, 4, 9, 5, 9, 6, 9, 7, 9, 8, 9)

>>> sum_val[::2]
(1, 2, 3, 4, 5, 6, 7, 8)

>>> sum(zip(middle, other), tuple())[::2]
(1, 2, 3, 4, 5, 6, 7, 8)

R1Q2: Community

Who is the creator of Pandas, and author of the book Python for Data Analysis?

Wes McKinney → 3

With wrong spelling → 1

R1Q3: Which library is it?

>>> import who_am_i as wai
>>> import numpy as np
>>>
>>> t = np.arange(0.0, 2.0, 0.01)
>>> s = 1 + np.sin(2 * np.pi * t)
>>> wai.plot(t, s)
>>> wai.xlabel('Some numbers')
>>> wai.ylabel('Sine')
>>> wai.title('Sine of some numbers')
>>> wai.grid(True)
>>> wai.show()

matplotlib.pyplot → 3

matplotlib → 1

R1Q3: Which library is it?

>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>>
>>> t = np.arange(0.0, 2.0, 0.01)
>>> s = 1 + np.sin(2 * np.pi * t)
>>> plt.plot(t, s)
>>> plt.xlabel('Some numbers')
>>> plt.ylabel('Sine')
>>> plt.title('Sine of some numbers')
>>> plt.grid(True)
>>> plt.show()

R1Q4: Monty Python

From which Monty Python movie is this frame?

The meaning of life → 3

El sentido de la vida / El sentit de la vida → 3

R1Q5: Python version

Since which version of Python this is valid Python code?

>>> earth_radius = 6_371
>>> print(f'The radius of earth is {earth_radius}')

CPython 3.6 → 3

Returns 'The radius of earth is 6371' in Python 3.6, and SyntaxError in all previous version, because of the underscore in the number literal, and the f-string.

R1Q6: Python Barcelona

How many meetups, the Barcelona Python Meetup has held until today?

Exactly 100 → 3

Between 80 and 120 → 1



In [7]:

    
import itertools
import random
import bisect

candidates = [0, 99, 666, 22]
weights = [.33, .33, 99., .34]
cum_weights = itertools.accumulate(weights)
candidates[bisect.bisect(cum_weights, random.random() * cum_weights[-1])]









    



---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-7-76cc035203d4> in <module>()
      6 weights = [.33, .33, 99., .34]
      7 cum_weights = itertools.accumulate(weights)
----> 8 candidates[bisect.bisect(cum_weights, random.random() * cum_weights[-1])]

TypeError: 'itertools.accumulate' object is not subscriptable

Round 2

R2Q1: What's the output?

>>> import itertools
>>> import random
>>> import bisect
>>> 
>>> candidates = [0, 99, 666, 22]
>>> weights = [.33, .33, 99., .34]
>>> cum_weights = itertools.accumulate(weights)
>>> candidates[bisect.bisect(cum_weights, random.random() * cum_weights[-1])]

R2Q2: Community

Which of these projects is not a NumFOCUS fiscally sponsored project?

R2Q3: Which library is it?

>>> import who_am_i as wai
>>> import numpy as np
>>> from sklearn.pipeline import make_pipeline
>>> from sklearn.dummy import DummyClassifier
>>>
>>> X = np.array([[ 1., -1.,      2.],
...               [ 2.,  np.nan,  0.],
...               [ 0.,  1.,     -1.]])
>>> y = np.array([0., 1., 0.])
>>>
>>> clf = make_pipeline(wai.Imputer(),
...                     wai.StandardScaler(),
...                     DummyClassifier())
>>>
>>> clf.fit(X, y)
>>> clf.predict(np.array([[2., 0., -1.]]))

R2Q4: Monty Python

Which is the biggest enemy of the People's Front of Judea?

R2Q5: Python version

Which is the latest released version of Pandas?

R2Q6: Python Barcelona

Who was the founder of the Barcelona Python Meetup?

Round 2: Answers

R2Q1: What's the output?

>>> import itertools
>>> import random
>>> import bisect
>>> 
>>> candidates = [0, 99, 666, 22]
>>> weights = [.33, .33, 99., .34]
>>> cum_weights = list(itertools.accumulate(weights))
>>> cum_weights
[0.33, 0.66, 99.66, 100.0]
>>> random_number = random.random() * cum_weights[-1]
>>> # uniformly distributed between 0 and 100
>>> # 99% probability of being between 0.66 and 99.66
>>> random_number
58.95397201789591
>>> index = bisect.bisect(cum_weights, random_number)
>>> index
2
>>> candidates[index]
666

R2Q1: What's the output?

>>> import itertools
>>> import random
>>> import bisect
>>> 
>>> candidates = [0, 99, 666, 22]
>>> weights = [.33, .33, 99., .34]
>>> cum_weights = itertools.accumulate(weights)
>>> candidates[bisect.bisect(cum_weights, random.random() * cum_weights[-1])]
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-7-76cc035203d4> in <module>()
      6 weights = [.33, .33, 99., .34]
      7 cum_weights = itertools.accumulate(weights)
----> 8 candidates[bisect.bisect(cum_weights, random.random() * cum_weights[-1])]

TypeError: 'itertools.accumulate' object is not subscriptable

TypeError → 3

666 with 99% probability → 1

R2Q2: Community

Which of these projects is not a NumFOCUS fiscally sponsored project?

R2Q2: Community

Which of these projects is not a NumFOCUS fiscally sponsored project?

Gensim → 3

R2Q3: Which library is it?

>>> import who_am_i as wai
>>> import numpy as np
>>> from sklearn.pipeline import make_pipeline
>>> from sklearn.dummy import DummyClassifier
>>>
>>> X = np.array([[ 1., -1.,      2.],
...               [ 2.,  np.nan,  0.],
...               [ 0.,  1.,     -1.]])
>>> y = np.array([0., 1., 0.])
>>>
>>> clf = make_pipeline(wai.Imputer(),
...                     wai.StandardScaler(),
...                     DummyClassifier())
>>>
>>> clf.fit(X, y)
>>> clf.predict(np.array([[2., 0., -1.]]))

sklearn.preprocessing → 1

R2Q3: Which library is it?

>>> import sklearn.preprocessing
>>> import numpy as np
>>> from sklearn.pipeline import make_pipeline
>>> from sklearn.dummy import DummyClassifier
>>>
>>> X = np.array([[ 1., -1.,      2.],
...               [ 2.,  np.nan,  0.],
...               [ 0.,  1.,     -1.]])
>>> y = np.array([0., 1., 0.])
>>>
>>> clf = make_pipeline(sklearn.preprocessing.Imputer(),
...                     sklearn.preprocessing.StandardScaler(),
...                     DummyClassifier())
>>>
>>> clf.fit(X, y)
>>> clf.predict(np.array([[2., 0., -1.]]))
array([ 1.])

if you also knew the prediction is 1. → 3

R2Q4: Monty Python

Which is the biggest enemy of the People's Front of Judea?

The Judean People's Front → 3

The Romans → -1

R2Q5: Python version

Which is the latest released version of Pandas?

pandas 0.20.1 → 3

pandas 0.20 → 1

R1Q6: Python Barcelona

Who was the founder of the Barcelona Python Meetup?

Maik Röder → 5



In [ ]: