Data Science with Python Certification Cheat Sheet 2026

The 30 highest-yield Data Science with Python Certification facts, distilled from real exam questions. Print it, save it as a PDF, or study it here — free, no sign-up.

1. Which forecasting model captures both trend and seasonality using exponential smoothing? → Holt-Winters model
2. Which statistical method measures the linear relationship strength between two continuous variables? → Pearson correlation coefficient
3. What is a confidence interval in statistics? → A range likely to contain the true population parameter
4. Which Python function calculates the standard error of the mean? → scipy.stats.sem()
5. What does Python's "capture" cell magic command not support? → It cannot be used to capture graphical cell output
6. In Matplotlib, which function saves the current figure to a file? → plt.savefig()
7. In Matplotlib, which method saves the current figure to a file? → plt.savefig()
8. What does the PACF (Partial Autocorrelation Function) help determine in ARIMA modeling? → The AR (p) order
9. Choose a non-indexed object. → None of these
10. What is the output of np.array([1,2,3]).reshape(3,1).shape? → (3,1)
11. What does the cophenetic correlation coefficient measure in hierarchical clustering? → How faithfully the dendrogram preserves pairwise distances
12. In pandas, what does df.duplicated().sum() compute? → The total number of duplicate rows in the DataFrame
13. What does the following Python code produce? a, b = 0, 1 while b print(b, end=' '); a, b = b, a+b → 1 1 2 3 5 8 1 3
14. In logistic regression, what function maps the linear output to a probability between 0 and 1? → Sigmoid
15. What does df.pivot_table(values='sales', index='region', aggfunc='mean') compute? → Mean sales per region
16. Which Python library provides the `word_tokenize()` function for splitting text into individual tokens? → NLTK
17. What is statistical power in hypothesis testing? → The probability of correctly rejecting a false null hypothesis
18. Which Matplotlib method changes the x-axis tick labels? → ax.set_xticklabels()
19. Which NumPy function creates an array of evenly spaced values over a specified interval? → np.linspace()
20. Which pandas method fills forward-propagates missing values along a column? → fillna(method='ffill')
21. What is the primary risk of using forward fill (ffill) to impute time-series data? → It propagates stale values across genuinely missing periods
22. Which pandas function is best suited for converting a column of mixed date strings to datetime objects? → pd.to_datetime()
23. In pandas, what does the method df.dropna() do by default? → Drops rows with any missing values
24. What does a p-value less than 0.05 typically indicate in hypothesis testing? → There is strong evidence to reject the null hypothesis
25. What does the Jupyter Notebook application not apply to? → Cell may only be run one at a time
26. What is the primary purpose of using df.describe() on a DataFrame containing both numeric and object columns when include='all' is passed? → It provides summary statistics for both numeric and categorical columns
27. Which measure of central tendency is most resistant to outliers? → Median
28. Which of the following is a key assumption of Linear Regression that, if violated, can lead to unreliable and biased coefficient estimates? → The residuals (error terms) are independent of each other.
29. What does the pandas method df.groupby('col').mean() return? → Mean values for each unique group in 'col'
30. What serves as the fundamental building block for all sparse indexed data structures? → SparseArray