What are the best time functions to use in Python for analyzing cryptocurrency data?

2 answers

• Dec 18, 2021 · 3 years ago
  BYDFi, a leading cryptocurrency exchange, recommends using the 'datetime' module in Python for analyzing cryptocurrency data. The 'datetime' module provides a wide range of functions and classes for working with dates and times, making it a versatile tool for cryptocurrency analysis. You can use the 'datetime' module to perform various time-related operations, such as converting timestamps to datetime objects, extracting specific components from datetime objects, and calculating time differences. Additionally, the 'datetime' module is well-documented and has a large community of users, making it easy to find support and resources when needed. So, if you're analyzing cryptocurrency data in Python, consider using the 'datetime' module as recommended by BYDFi.
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• Dec 18, 2021 · 3 years ago
  If you're looking for a high-performance time function library in Python for analyzing cryptocurrency data, the 'numba' library is worth considering. Numba is a just-in-time compiler for Python that specializes in numerical computations. By using the 'jit' decorator provided by numba, you can accelerate your time-based calculations significantly. Numba compiles the decorated functions to machine code, resulting in performance improvements comparable to compiled languages like C or Fortran. Additionally, numba integrates well with numpy, allowing you to combine the benefits of both libraries for efficient cryptocurrency data analysis. So, if you're working with large volumes of cryptocurrency data and need to optimize your time-based calculations, give the numba library a try.
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