Pandas Mastery Quiz — Quiz

File I/O, time series, reshaping and performance techniques in pandas. · 10 questions

Question 1 of 10

Which argument makes `pd.read_csv` interpret 05/04/2025 as 5 April 2025?

amonthfirst=Falsebdayfirst=Truecformat='US'dparse_dates=False

Question 2 of 10

What does `pd.read_excel('file.xlsx', sheet_name=None)` return?

aOnly the first sheetbA list of column namescA dict mapping sheet names to DataFramesdThe number of sheets

Question 3 of 10

Which method converts a wide table (one column per month) into long format?

ameltbpivotcunstackdexplode

Question 4 of 10

Which dtype is best for a column with only 5 distinct payment modes repeated across millions of rows?

aobjectbfloat64cstringdcategory

Question 5 of 10

What does this code return?

s = df.set_index("date")["amount"]
s.resample("ME").sum()

aTotal amount for each calendar month, labelled by month endbThe mean amount per weekcThe row with the largest amountdA TypeError because ME is invalid

Question 6 of 10

`df.pivot(index='branch', columns='month', values='sales')` raises `ValueError: Index contains duplicate entries`. What is the fix?

aUse df.melt insteadbUse pd.pivot_table with an aggfunc such as 'sum'cSort the DataFrame firstdConvert month to category

Question 7 of 10

Why does `df.to_csv('out.csv')` often produce an `Unnamed: 0` column when read back?

aCSV cannot store integersbThe encoding is wrongcThe index was written as a column; use index=Falsedpandas adds a checksum column

Question 8 of 10

Which is the fastest way to create a column that is `amount * 0.1` for members and 0 otherwise?

adf.apply(lambda r: ..., axis=1)bA for loop with iterrows()cdf.itertuples() with a listdnp.where(df['member'], df['amount'] * 0.1, 0)

Question 9 of 10

What does this produce?

g = df.groupby(["branch", "category"])["amount"].sum()
t = g.unstack("category", fill_value=0)

aA long Series with a 3-level indexbA DataFrame with branches as rows and categories as columnscA DataFrame with categories as rows and branches as columnsdAn error because unstack needs a DataFrame

Question 10 of 10

Which statement about `df[df['city'] == 'Pune']['amount'] = 0` is correct?

aIt reliably sets Pune amounts to 0bIt raises a SyntaxErrorcIt deletes Pune rowsdIt may modify a temporary copy, leaving df unchanged; use df.loc[mask, 'amount'] = 0