Data Wrangling with Pandas — Quiz | Data Analytics using Python

Question 1

Which selector picks rows and columns by their LABEL?

A .iloc

B .loc

C .at_position

D .pick

Question 2

How do you combine two filter conditions in Pandas?

A df[cond1 and cond2]

B df[(cond1) & (cond2)]

C df[cond1 + cond2]

D df.both(...)

Question 3

What does df.isna().sum() tell you?

A The total of all numbers

B The count of missing values per column

C The number of rows

D The data types

Question 4

Why often fill missing numbers with the MEDIAN rather than the mean?

A It is faster

B The median resists outliers

C Pandas requires it

D It is always larger

Question 5

Which converts a text column to numbers, turning bad values into NaN?

A col.astype(int)

B pd.to_numeric(col, errors='coerce')

C col.number()

D int(col)

Question 6

Which accessor cleans a whole text column at once (e.g. strip, lower)?

A .text

B .str

C .clean

D .string

Question 7

A LEFT join (how='left') keeps…

A only matching rows

B every row from the left table plus matches from the right

C only the right table

D no rows

Question 8

Which function stacks two DataFrames with the same columns?

A pd.merge()

B pd.concat([df1, df2])

C pd.join()

D pd.stack()

Question 9

Which pattern answers 'total sales per region'?

A df.sum()

B df.groupby('region')['amount'].sum()

C df.region.total()

D df.pivot()

Question 10

pivot_table() is most like which spreadsheet feature?

A VLOOKUP

B A PivotTable / cross-tab

C Conditional formatting

D A macro

Question 11

melt() converts data from…

A long to wide

B wide to long (tidy)

C rows to columns only

D text to numbers

Question 12

After setting a datetime index, which call rolls daily data up to monthly totals?

A resample('M').sum()

B groupby('M')

C rolling('M')

D monthly()