What are the advanced features of Pandas compared to NumPy?
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What are the advanced features of Pandas compared to NumPy?
Pandas offers advanced data manipulation capabilities like DataFrames, time series analysis, and group operations, while NumPy focuses on numerical computations with arrays.
Can you explain how DataFrames work in Pandas?
DataFrames are 2-dimensional labeled data structures in Pandas, similar to spreadsheets, allowing for complex data manipulation and analysis.
What about handling missing data in both libraries?
Pandas provides built-in functions like fillna() and dropna() for handling missing data, while NumPy requires more manual handling using masks or conditions.
Which library is better for large datasets?
Pandas is generally better for large datasets due to its optimized performance and built-in functions for data analysis, while NumPy is more efficient for numerical computations.
Can you give an example of a time series analysis in Pandas?
Sure! In Pandas, you can use the resample() method to aggregate time series data, making it easy to analyze trends over time.
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