A data analyst has a DataFrame of security alerts with columns 'severity' (high, medium, low) and 'count'. They want to sort the alerts by severity in the order high, medium, low, not alphabetically. Which approach achieves this?

df['severity'] = pd.Categorical(df['severity'], categories=['high', 'medium', 'low'], ordered=True); df.sort_values('severity')

A data analyst has a DataFrame with a 'time' column (datetime) and a 'value' column. The analyst wants to create a time-series plot with a rolling mean overlay to smooth short-term fluctuations. Which approach should be used?

Use seaborn's lineplot with the raw data and no rolling mean.

Use pandas' plot.rolling(window=7).mean() directly on the DataFrame.

Plot the original data with plt.plot, then compute the rolling mean with df['value'].rolling(window=7).mean() and plot it on the same axes.

Plot only the rolling mean without the original data.

A data analyst has a DataFrame of sales transactions with columns 'product', 'region', and 'revenue'. The analyst wants to create a new DataFrame that shows the total revenue per product per region, with products as rows and regions as columns. Which pandas operation should be used?

df.pivot(index='product', columns='region', values='revenue')

df.groupby('product')['revenue'].sum()

df.pivot_table(index='product', columns='region', values='revenue', aggfunc='sum')

df.groupby(['product', 'region'])['revenue'].sum().unstack()

A threat researcher has a DataFrame of malware hash submissions with columns 'family', 'country', and 'count'. The researcher wants to find the top 3 malware families by total count, but only for submissions from a specific set of countries. Which pandas operation sequence should be used?

Sort the DataFrame by 'count' descending, then filter to the countries of interest, and take the first 3 rows.

Use df.nlargest(3, 'count') on the entire DataFrame, then filter to the countries of interest.

Filter the DataFrame to the countries of interest, then group by 'family', aggregate 'count' with sum, sort descending, and take the first 3 rows.

Group by 'family', aggregate 'count' with sum, then filter the grouped result to the countries of interest, and sort descending.

GIAC Python Coder

Domain 4Objective 1

Data Analysis with Python GPYC Practice Questions (Page 6)

Part of the Data Analysis domain, which makes up ~9% of our current practice bank. GIAC (SANS) does not publish an official question count, but from its 120-minute exam (~50–80 total, ~5–7 in this domain), expect 5–7 from this objective — we provide 33 practice questions to prepare you well beyond it. (estimate)

33questions here

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5concepts

Questions 26–30

26foundation · easy
Which pandas method is used to handle missing values by filling them with a specified value?
Select an answer first
27application · medium
A data analyst has a DataFrame of security alerts with columns 'severity' (high, medium, low) and 'count'. They want to sort the alerts by severity in the order high, medium, low, not alphabetically. Which approach achieves this?
Select an answer first
28expert · hard
A data analyst has a DataFrame with a 'time' column (datetime) and a 'value' column. The analyst wants to create a time-series plot with a rolling mean overlay to smooth short-term fluctuations. Which approach should be used?
Select an answer first
29application · medium
A data analyst has a DataFrame of sales transactions with columns 'product', 'region', and 'revenue'. The analyst wants to create a new DataFrame that shows the total revenue per product per region, with products as rows and regions as columns. Which pandas operation should be used?
Select an answer first
30application · medium
A threat researcher has a DataFrame of malware hash submissions with columns 'family', 'country', and 'count'. The researcher wants to find the top 3 malware families by total count, but only for submissions from a specific set of countries. Which pandas operation sequence should be used?
Select an answer first

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