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Python efficiency can be improved by optimizing code, using built-in functions, and avoiding unnecessary loops.
Use built-in functions like map, filter, and list comprehensions instead of loops for better performance.
Avoid unnecessary loops by optimizing code and reducing redundant operations.
Consider using libraries like NumPy for efficient handling of large datasets.
Profile your code using tools like cProfile to ident
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posted on 17 Dec 2024
I applied via LinkedIn and was interviewed before Dec 2023. There were 3 interview rounds.
Python list comprehension, SQL joins,
I was interviewed before May 2023.
Project focused on learning the basics of NumPy and Pandas in Python.
Studying NumPy arrays and their operations
Exploring Pandas data structures like Series and DataFrames
Practicing data manipulation and analysis using NumPy and Pandas functions
posted on 17 Dec 2024
I applied via LinkedIn and was interviewed before Dec 2023. There were 3 interview rounds.
Python list comprehension, SQL joins,
I was interviewed before May 2023.
Project focused on learning the basics of NumPy and Pandas in Python.
Studying NumPy arrays and their operations
Exploring Pandas data structures like Series and DataFrames
Practicing data manipulation and analysis using NumPy and Pandas functions
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