QMB3302 TEST
Imagine we have a dataframe, df. What would be the purpose of df.loc[1] - answerto
look from/ retrieve value from df
what is the shape of the following numPy array? - answer(2, 2, 2, 2)
numPy allows us to do more complicated math on lists and other data structures, and is
used in most of the more advances modules used (eg.pandas) T/F - answerTrue
pandas allows multiple different data types (like objects and numbers) in a single table -
answerTrue
for pandas to work, data must be formatted as lists before imported T/F - answerFalse
Relative path definition - answerthe path FROM where you code is in your current
working directory TO where your data is
can pandas work with complicated dates? - answerYes
Do datasets need something in common to be joined (a key) - answerYes
Can Pandas join two dataframes together? - answerYes
Two ways to indicate missing data in set - answermask and sentinel value
mask - answerglobally indicates missing values
can be boolean array or something else
sentinel value - answera value that when evaluated by the loop expression causes the
loop to terminate
indicates missing entry
Pandas uses this
can be data specific convention or more global, such as indicating missing value with
NaN
Pandas use of missing data is constrained by - answerreliance on NumPy package, no
built in notion of NA values for non-floating data types
Use of None - answerfirst sentinel value in pandas, object that is used for missing
values in arrays. Can ONLY be used w objects (can't perform sums or mean)
NaN - answerspecial floating value, can be used with computations
Imagine we have a dataframe, df. What would be the purpose of df.loc[1] - answerto
look from/ retrieve value from df
what is the shape of the following numPy array? - answer(2, 2, 2, 2)
numPy allows us to do more complicated math on lists and other data structures, and is
used in most of the more advances modules used (eg.pandas) T/F - answerTrue
pandas allows multiple different data types (like objects and numbers) in a single table -
answerTrue
for pandas to work, data must be formatted as lists before imported T/F - answerFalse
Relative path definition - answerthe path FROM where you code is in your current
working directory TO where your data is
can pandas work with complicated dates? - answerYes
Do datasets need something in common to be joined (a key) - answerYes
Can Pandas join two dataframes together? - answerYes
Two ways to indicate missing data in set - answermask and sentinel value
mask - answerglobally indicates missing values
can be boolean array or something else
sentinel value - answera value that when evaluated by the loop expression causes the
loop to terminate
indicates missing entry
Pandas uses this
can be data specific convention or more global, such as indicating missing value with
NaN
Pandas use of missing data is constrained by - answerreliance on NumPy package, no
built in notion of NA values for non-floating data types
Use of None - answerfirst sentinel value in pandas, object that is used for missing
values in arrays. Can ONLY be used w objects (can't perform sums or mean)
NaN - answerspecial floating value, can be used with computations
