importmatplotlib.pyplotaspltimportnumpyasnp np.random.seed(42)data=np.random.normal(100,20,1000)fig,ax=plt.subplots()ax.set_title('Data distribution with mean - how2matplotlib.com')ax.hist(data,bins=30,alpha=0.7)ax.axhline(y=np.mean(data),color='r',linestyle='--',label='Mean')ax....
importmatplotlib.pyplotaspltfrommatplotlib.collectionsimportLineCollectionfrommatplotlibimportcolorsasmcolorsimportnumpyasnp# In order to efficiently plot many lines in a single set of axes,# Matplotlib has the ability to add the lines all at once. Here is a# simple example showing how it is done....
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.random.randn(1000,1)) # use the plot function plt.plot(...
Method 3: Using Matplotlib’s title() method: Seaborn leverages Matplotlib to render various plots. Hence, it becomes easy to utilize Matplotlib’s title() method for specifying the title for the plot. The code snippet below can explain how to use it. import seaborn as sns import pandas as...
# Data Visualization using Python # Controling line width import numpy as np import matplotlib.pyplot as plt x1 = np.linspace(0.0, 2.0) x2 = np.linspace(0.0, 2.0) y1 = np.sin(2 * np.pi * x1) * np.exp(-x1) y2 = np.cos(2 * np.pi * x2) plt.plot(x1, y1, 'b') plt...
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...
importnumpyasnpimportmatplotlib.pyplotasplt x=np.linspace(0.0,5.0)y=x*x# default Plotplt.subplot(2,1,1)plt.plot(x,y,'o-')plt.title('Dot-Line Plot (1)')plt.ylabel('Square')plt.xlabel('numbers')plt.show()# Smaller dotplt.subplot(2,1,2)plt.plot(x,y,'.-')plt.title('Dot-Lin...
准备工作:先导入matplotlib和pandas,用pandas读取csv文件,然后创建一个图像和一个坐标轴 importpandasaspd frommatplotlibimportpyplotasplt unemployment=pd.read_csv(r"http://datasets.flowingdata.com/unemployment-rate-1948-2010.csv") fig,ax=plt.subplots() ...
一种方法是创建一个Line2D对象列表,并在循环中使用set_data。注意,ax.plot()总是返回一个行列表,即使只打印一行。 import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation import numpy as np x = np.linspace(0, 2 * np.pi, 100) ...
import numpy as np import matplotlib.pyplot as plt x = np.array([1., 2., 3., 4., 5.]) y = np.array([1., 3., 2., 3., 5.]) x_mean = np.mean(x) y_mean = np.mean(y) num = 0.0 # 分子 d = 0.0 # 分母