In pandas, which function is used to calculate the correlation between columns in DataFrame df?

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BlackTom AI · Accepted Answer

When assessing which pandas function computes correlations between columns in a DataFrame, we need to match the operation to the appropriate built-in method.
Option 1: 'df.corr()' — This is the standard pandas DataFrame method to compute pairwise correlation of columns, returning a correlation matrix. It uses Pearson correlation by default and can be adjusted with parameters like method='spearman' or 'kendall' if different correlation measures are needed.
Option 2: 'df.std()' — This function returns the standard deviation of each column, not their pairwise correlations. It measures dispersion rather than relational similarity between columns, so it does not answer the correlation question.
Option 3: 'df.correlation()' — There is no DataFrame method literally named 'correlation' in pandas. Attempting to call this would raise an AttributeError in typical usage, since the correct method is 'corr'. This option misrepresents the API.
Option 4: 'df.regression()' — There is no standard pandas DataFrame method called 'regression' for computing correlations between columns. Regression analysis is a different statistical procedure requiring separate modeling functions, not a simple correlation matrix calculation.
In summary, the operation described—calculating the correlation between columns in a DataFrame—maps to the DataFrame.corr() method, which yields a matrix of pairwise correlations across all columns. The other options either compute different statistics or refer to non-existent methods in the pandas API.

ACCN-3290-02Sp25 Week 2 Quiz

In pandas, which function is used to calculate the correlation between columns in DataFrame df?

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