NumPy is a library for scientific computing in Python. It provides tools for working with arrays of data, including functions for mathematical operations, linear algebra, and random number generation.
👉🏻One of the key features of NumPy is its array data structure, which is similar to a list but allows for more efficient mathematical operations on large datasets. NumPy arrays can be created from existing data, such as lists or tuples, using the np.array() function.
👉🏻Once an array has been created, it can be manipulated using various NumPy functions. For example, the np.mean() function can be used to compute the mean of an array, and the np.random.rand() function can be used to generate random numbers.
👉🏻In addition to its array data structure, NumPy also provides a wide range of mathematical functions for working with arrays, such as linear algebra operations, statistical functions, and trigonometric functions. These functions can be applied to arrays element-wise, allowing for efficient computation on large datasets.
Overall, NumPy is a powerful library for working with arrays of data in Python, and is widely used in the fields of scientific computing, data science, and machine learning.
NumPy is a library for scientific computing in Python. It provides tools for working with arrays of data, including functions for mathematical operations, linear algebra, and random number generation.
👉🏻One of the key features of NumPy is its array data structure, which is similar to a list but allows for more efficient mathematical operations on large datasets. NumPy arrays can be created from existing data, such as lists or tuples, using the np.array() function.
👉🏻Once an array has been created, it can be manipulated using various NumPy functions. For example, the np.mean() function can be used to compute the mean of an array, and the np.random.rand() function can be used to generate random numbers.
👉🏻In addition to its array data structure, NumPy also provides a wide range of mathematical functions for working with arrays, such as linear algebra operations, statistical functions, and trigonometric functions. These functions can be applied to arrays element-wise, allowing for efficient computation on large datasets.
Overall, NumPy is a powerful library for working with arrays of data in Python, and is widely used in the fields of scientific computing, data science, and machine learning.
Traders also expressed uncertainty about the situation with China Evergrande, as the indebted property company has not provided clarification about a key interest payment.In economic news, the Commerce Department reported an unexpected increase in U.S. new home sales in August.Crude oil prices climbed Friday and front-month WTI oil futures contracts saw gains for a fifth straight week amid tighter supplies. West Texas Intermediate Crude oil futures for November rose $0.68 or 0.9 percent at 73.98 a barrel. WTI Crude futures gained 2.8 percent for the week.
How to Invest in Bitcoin?
Like a stock, you can buy and hold Bitcoin as an investment. You can even now do so in special retirement accounts called Bitcoin IRAs. No matter where you choose to hold your Bitcoin, people’s philosophies on how to invest it vary: Some buy and hold long term, some buy and aim to sell after a price rally, and others bet on its price decreasing. Bitcoin’s price over time has experienced big price swings, going as low as $5,165 and as high as $28,990 in 2020 alone. “I think in some places, people might be using Bitcoin to pay for things, but the truth is that it’s an asset that looks like it’s going to be increasing in value relatively quickly for some time,” Marquez says. “So why would you sell something that’s going to be worth so much more next year than it is today? The majority of people that hold it are long-term investors.”
