What's that argument?
Function Bobunction
Tables, tables, tables
Stats...
100
len(____)
What is an array?
100
min()
What is finding the minimum?
100
The code that will produce an array of all Pokemon types.
What is pokemon.column('Type')?
100
What is the chance of picking an ace of hearts in a standard deck of 52 cards?
What is 1/52?
200
tbl.select(____, ____, ...)
What is a column name? (or string)
200
round()
What is round a number or array of numbers to the nearest integer?
200
What is the code that will produce a table with only water type Pokemon?
pokemon.where('Type', are.equal_to('Water'))
200
What is the chance of pulling an ace of hearts, and then without putting that card back, pulling a king of hearts from a standard deck of cards in that order?
1/52 * 1/51
300
tbl.with_columns(____, ____)
What is a column name and values? (or string(s) and array(s))
300
np.arange(5, 906, 5)
What is creates an array from 5 to 905, incrementing in values of 5?
300
What is the code that will produce a table with Pokemon whose Speed is strictly less than 100?
pokemon.where('Speed', are.below(100))
300
If a die is rolled three times, what are the chances that all three rolls will be the same?
What is 1/12?
400
tbl.group(____, ____)
What is a column or columns and a function?
400
def mystery_function():
print("Hello world!)
return 5
What is prints Hello world! and returns 5?
400
What is the code that will result in the number of Pokemon whose speed are strictly less than 100?
pokemon.where('Speed', are.below(100)).num_rows
400
If you were given a list of 5000 students, and you surveyed the first 100 students, what type of sample would result from this technique?
What is a deterministic sample?
500
tbl.pivot(____, ____, ____, ____)
What is column A, column B, the values to be aggregated, and the function to perform the aggregation?
500
def mystery_function(array):
for i in array:
sum = sum + array.item(i)
return sum / len(sum)
What is returns the mean value of an array?
500
Return a table that has the average HP for every Type in every Generation.
pokemon.select('Type', 'Generation', 'HP').group(['Type', 'Generation'], np.mean)
OR
pokemon.pivot('Type', 'Generation', 'HP', np.mean)
500
Suppose our class of 20 students were to roll a die. What are the chances that no one rolls a 6?
What is (1 - 1/6)20 ?