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4 cards from this section. Quick, good the night before a test.
What does the df.shape attribute return?
Think about how many rows and columns are in your DataFrame.
What information does df.info() provide?
Consider what details are needed to understand the data structure.
What does the method value_counts() do in a Pandas DataFrame?
Think about how you can summarize categorical data.
True or False: The describe() method works only with numeric data types.
Consider what types of data you usually summarize with this method.
Given a DataFrame with mixed data types, write a Python function using Pandas to return the shape, info, and describe methods for the data.
Consider what initial analyses you would need for a thorough overview.
Imagine a scenario where a column in your DataFrame has excessive missing values. Propose a strategy to handle this before conducting any analysis.
Assess the impact of missing data on analysis quality.
6 more questions in this section. Enroll free to practise them all.
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