pyplot as plt import numpy as np # create data values=np.cumsum(np.random.randn(1000,1)) # use the plot function plt.plot(values) (2)Seaborn customization使用seaborn # libraries import matplotlib.pyplot as plt import numpy as np import seaborn as sns # create data values=np.cumsum(np....
plot(values) (2)Seaborn customization使用seaborn 代码语言:javascript 代码运行次数:0 运行 AI代码解释 # libraries import matplotlib.pyplot as plt import numpy as np import seaborn as sns # create data values=np.cumsum(np.random.randn(1000,1)) # use the plot function plt.plot(values) (3)设置...
Method 1: Using set() method: In the set() method, we have to pass the xlabel and ylabel parameter values to determine the labels for the x and y axes. Here is a code snippet showing how to use it. import seaborn as sns import numpy as np import matplotlib.pyplot as plt import pa...
# 创建随机数据x=np.linspace(0,10,100)# 从0到10生成100个点y=np.sin(x)# 计算x每个点的正弦值# 绘制线条line=plt.plot(x,y,label='Sine Wave',color='blue')# 绘制正弦波 1. 2. 3. 4. 5. 6. 这里,我们使用numpy.linspace()生成从0到10等间隔的100个数,并通过np.sin()计算其正弦值。然后...
importmatplotlib.pyplotaspltimportmatplotlib.datesasmdatesimportdatetimeimportnumpyasnp# 创建示例数据dates=[datetime.datetime(2023,1,1)+datetime.timedelta(days=i)foriinrange(365)]values=np.random.randn(365).cumsum()# 创建图表plt.figure(figsize=(12,6))plt.plot(dates,values)# 添加多个自定义样式的...
from matplotlib.collectionsimportLineCollectionimportnumpyasnp n_colors=8n_datapoints=60# plot legend data_x=range(n_colors)data_color=range(n_colors)fig,ax=plt.subplots(figsize=(10,2))rects=ax.bar(data_x,[1]*n_colors,color=plt.cm.tab20(data_color),alpha=1)plt.xticks(data_x)fig,ax=...
from pyfolio.plotting import plot_rolling_returns, plot_rolling_sharpe from pyfolio.timeseries import forecast_cone_bootstrap 这里我们将导入各种用于数据操作和数据分析的库,例如 pandas、numpy 和 matplotlib。它还从 zipline 库导入函数和类,用于回测交易策略。正如您在我们的代码中看到的,我们定义了一个管道,...
importmatplotlib.pyplotaspltimportnumpyasnp np.random.seed(42)x=np.linspace(0,10,100)y=np.sin(x)+np.random.normal(0,0.1,100)fig,ax=plt.subplots()ax.plot(x,y)ax.axhline(y=0.5,color='r',linestyle='--',label='Upper Threshold')ax.axhline(y=-0.5,color='g',linestyle='--',label...
import numpy as np # 创建数据 # Linespace创建一定范围内的图线。-2到2之间等分100个点 x = np.linspace(-2, 2, 100) #y = 3 * x + 4 y1 = 3 * x + 4 y2 = x ** 3 # 创建图像 #plt.plot(x, y) plt.plot(x, y1)
y = np.sin(x)# Create a line plotplt.plot(x, y)# Add labels and titleplt.xlabel('Time (s)') plt.ylabel('Amplitude') plt.title('Sine Wave')# Show the plotplt.show() Copy Let's break down what's happening in this code. First, we import the NumPy library, which is a powerf...