Quantopian

Question 1

You can print lines you want with the word print

Answer 1

True

Question 2

In python, what is pandas?

Answer 2

A library

Question 3

If I gave numpy the alias “np”, and I imported some data and named it “sample”, how would I calculate the mean and standard deviation of the data using numpy?

Answer 3

np.mean(sample), np.std(sample)

Question 4

In Quantopian’s IPython interface, what is one of the functions that can be used to pull some real price data?

Answer 4

get_pricing()

Question 5

What is one of the functions that can be used to calculate returns?

Answer 5

pct_change()

Question 6

If I wanted to calculate the 100 day moving average using daily data, I can use pandas built-in tools to do so. The data is loaded in and named “price_data”. Assuming I load in pandas with the alias “pd”, then what would be the correct way to write the function to calculate the 100 day moving average using pandas?

Answer 6

pd.rolling_mean(price_data, window=100)

Question 7

If “”” This text is enclosed between the triple quotes “”” then it is referred to as

Answer 7

a string

Question 8

13.198 is what type of variable in Python?

Answer 8

Float

Question 9

What happens to the number 13.198 when I run the following code,

int(13.198)

Answer 9

Truncate any digits after the decimal point

Question 10

What will running the following code in Python create?

[1, ‘This’, 3, ‘that’]

Answer 10

List

Question 11

What can the colon symbol be used to slice in Python?

Answer 11

List

Question 12

If I wanted to grab the last item from a list in Python, which line of code would I need to run? Assume the name of the list is defined as X.

Answer 12

X[-1]

Question 13

You can change any part of a tuple because it is immutable.

Answer 13

False

Question 14

If I have two different variables, X and Y, and I wanted to know if they are the same, I would run the following code

print (X == Y)

Answer 14

True

Question 15

What are the two main components that make up a dictionary in Python?

Answer 15

Key and Value

Question 16

Numpy arrays can be created with multiple dimensions

Answer 16

True

Question 17

Assume an array is defined as “tmp”. Which line of code would we need to run to get the dimensions of the array?

Answer 17

tmp.shape

Question 18

A slice of an array will select a group of elements starting from the first element specified up to, and including, the last element indicated.

Answer 18

False

Question 19

If I wanted to select the first row of a 2-d array, I would execute which of the following code? Assume the array is defined as “tmp”.

Answer 19

tmp[0,:]

Question 20

Assume you have a set of returns and weights such that the weights are between 0 and 1, and sum to 1. Which line of code would return the expected return of your portfolio? Assume you load the numpy library in as np, define average returns as “mean_returns”, and weights as “weights”.

Answer 20

np.dot(weights, mean_returns)

Question 21

Assume you define weights as “weights”, average returns as “mean_returns”, the covariance of returns as “cov”, and you load the numpy library in as np. How would I use this information to calculate the volatility of my portfolio?

Answer 21

np.dot(np.dot(weights, cov), weights.T)

Question 22

A pandas Series is a 1-dimensional array with labels that can contain any data type.

Answer 22

True

Question 23

Every Series has a name.

Answer 23

True

Question 24

If you have a sample of daily data and the index is in DatetimeIndex format, which line of code would allow me to convert the daily data to monthly data? Assume the daily data is defined as “x”.

Answer 24

x.resample(‘M’)

Question 25

Assume I have return data that has some missing values (‘NaN’). Which line of code will replace the missing values with the average returns? Assume you define the returns data as “x”.

Answer 25

x.fillna(x.mean())

Question 26

The .dropna() function will automatically replace NaN values with the average

Answer 26

False

Question 27

If you wanted to print the summary statistics for your returns data, defined as “x”, how would you do so?

Answer 27

x.describe()

Question 28

If you are given a set of price data, defined as “x”, how would you calculate the multiplicative returns using pandas built-in methods simultaneously dropping the first set of missing values?

Answer 28

x.pct_change()[1:]

Question 29

Assume you have a set of monthly pricing data defined as “x” and you load in the pandas library as pd. Which pandas built-in function allows you to calculate the 12 month rolling average price?

Answer 29

pd.rolling_mean(x, 12)

Question 30

If you have monthly pricing data defined as “x” and you load in the pandas library as pd. Which line of code would calculate the 12 month rolling volatility?

Answer 30

pd.rolling_std(x, 365)

Question 31

If you have a pandas DataFrame defined as “df” and you want the average of each column, which line of code would you run?

Answer 31

df.mean(axis=0)

Question 32

Assume you have a pandas DataFrame defined as “df”. If you wanted to access the names of the columns, you would run which line of code?

Answer 32

df.columns

Question 33

To get the standard deviation from a pandas DataFrame defined as “df”, I could run which of the following lines of code?

Answer 33

df.std()