simulated_returns = np.random.normal(mean, std, size=(len(data), num_simulations)) # Calculate portfolio values for each scenario portfolio_values = (data["Close"].iloc[-1] * (1 + simulated_returns)).cumprod() # Convert portfolio_values into a DataFrame portfolio_values = pd.DataFrame(p...
simulated_returns = np.random.normal(mean, std, size=(len(data), num_simulations)) # Calculate portfolio values for each scenario portfolio_values = (data["Close"].iloc[-1] * (1 + simulated_returns)).cumprod() # Convert portfolio_values into a DataFrame portfolio_values = pd.DataFrame(p...
standard deviation：标准差 ，也称均方差（mean square error），是各数据偏离平均数的距离的平均数，它是离均差平方和平均后的方根，用σ表示。标准差是方差的算术平方根。标准差能反映一个数据集的离散程度。平均数相同的，标准差未必相同。 m...
arr = np.array([1, 2, 3, 4, 5]) # Calculating mean and standard deviation mean_value = np.mean(arr) std_dev = np.std(arr) print(f'Mean: {mean_value}, Standard Deviation: {std_dev}') 2. Pandas Pandas 是一个 Python 数据操作和分析库,提供 DataFrame 等数据结构,以实现高效的数据...
In the following example, we are importing the math library and calculating the standard deviation of the dataset by applying sqrt() built-in method on its variance.Open Compiler import math #declare the dataset list dataset = [2, 3, 4, 1, 2, 5] #find the mean of dataset sm=0 for ...
python可以算开根号么?我实在是初学。。。不好意思 赞 回复 the lost 2008-10-11 20:02:30 平方根 import math math.sqrt(x) math模块里面有一些常用的数学运算的函数,具体的请参考相应的文档 赞 回复 元创 (我的专业是打酱油) 2008-10-12 01:33:40 http://www.astro.cornell.edu/staff/loredo...
Meaning that most of the values are within the range of 37.85 from the mean value, which is 77.4. As you can see, a higher standard deviation indicates that the values are spread out over a wider range. The NumPy module has a method to calculate the standard deviation: ...
代码:defcalculate_ichimoku_cloud(df):# Tenkan-sen (Conversion Line)nine_period_high = df['high'].rolling(window=9).max() nine_period_low = df['low'].rolling(window=9).min() df['tenkan_sen'] = (nine_period_high + nine_period_low) /2# Kijun-sen (Base Line)twenty_six_period_hi...
# set the mu and sigma parameters of the distribution heights_mean = 170 heights_sd = 10 # instantiate the random variable object heights_rv = stats.norm( loc = heights_mean, # mean of the distribution scale = heights_sd # standard deviation ) 前面的代码创建了正态分布的随机变量,其概率...
(name='max_cycle'), left_on='unit_nb', right_index=True) # Calculate remaining useful life for each row remaining_useful_life = result_frame["max_cycle"] - result_frame["time_cycle"] result_frame["RUL"] = remaining_useful_life # drop max_cycle as it's no longer needed result_...