Data Analysis with Python Flashcards
7 cards from real Data Science with Python Certification practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Data Analysis with Python flashcards as text
Which pandas method fills forward-propagates missing values along a column?
Answer: fillna(method='ffill')
ffill (forward fill) propagates the last valid observation forward to replace NaN values.
What does df.pivot_table(values='sales', index='region', aggfunc='mean') return?
Answer: Mean sales value per region
pivot_table with aggfunc='mean' computes the mean of the values column grouped by the index.
Which NumPy function stacks arrays vertically (row-wise)?
Answer: np.vstack
np.vstack stacks a sequence of arrays along the first (vertical) axis, equivalent to concatenate with axis=0.
In pandas, what is the result of df.groupby('dept')['salary'].transform('mean')?
Answer: A Series with each row replaced by its department's mean salary
transform broadcasts the group-level aggregation back to the original DataFrame's shape.
Which method converts a pandas Series of strings to datetime objects?
Answer: pd.to_datetime(Series)
pd.to_datetime() is the standard function for parsing strings or numbers into datetime objects.
What does the .str.contains() method return when applied to a pandas Series?
Answer: A boolean Series indicating pattern matches
.str.contains() returns a boolean Series that is True where the pattern is found.
Which pandas function computes pairwise correlation between all numeric columns?
Answer: df.corr()
df.corr() returns a DataFrame of pairwise Pearson (or other) correlation coefficients between all numeric columns.
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