它接受两个一维数组作为输入,返回两个二维数组,分别表示X和Y坐标。 importnumpyasnpimportmatplotlib.pyplotaspltfrommpl_toolkits.mplot3dimportAxes3D# 生成网格数据x=np.linspace(-5,5,50)y=np.linspace(-5,5,50)X,Y=np.meshgrid(x,y)# 计算Z值Z=np.sin(np.sqrt(X**2+Y**2))# 创建3D图形fig=pl...
import matplotlib.pyplot as plt x = np.linspace(-3,3,50) y1 = 2*x + 1 y2 = x**2 plt.plot(x,y1) plt.plot(x,y2,color='red',linewidth=2,linestyle='--') 1. 2. 3. 4. 5. 6. 7. 2 默认样式 3 获取坐标轴 在matplotlib的图中,默认有四个轴,两个横轴和两个竖轴,可以通过ax...
预置效果函数如下: frompathlibimportPathimportmatplotlibimportmatplotlib.pyplotaspltimportnumpyasnpimportpandasaspdfrommatplotlib.colorsimportLinearSegmentedColormapfromplottableimportColumnDefinition,Table# 调用预置绘图函数fromplottable.plotsimportimage,monochrome_image,circled_image,bar,percentile_bars,percentile_stars...
import matplotlib.dates as md ax = mp.gca() # 设置刻度定位器 ax.xaxis.set_major_locator(md.WeekdayLocator(byweekday=)) # 每周一一个主刻度 ax.xaxis.set_major_formatter(md.DateFormatter('%Y-%m-%d')) # 设置主刻度日期的格式 ax.xaxis.set_minor_locator(md.DayLocator()) # 每天一个次...
import matplotlib.pyplot as plt import numpy as np fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(9, 4)) # Fixing random state for reproducibility np.random.seed(19680801) # generate some random test data all_data = [np.random.normal(0, std, 100) for std in range(6, 10)]...
Matplotlib 可以绘制线图、散点图、等高线图、条形图、柱状图、3D 图形、甚至是图形动画等等。 matplotlib.pyplot.plot 可选参数列表 Markers 点的类型 参考 https://www.runoob.com/matplotlib/matplotlib-tutorial.html https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html...
import matplotlib.pyplot as plt line1, = plt.plot([1,2,3], label="Line 1", linestyle='--') line2, = plt.plot([3,2,1], label="Line 2", linewidth=4) # 为第一个线条创建图例 first_legend = plt.legend(handles=[line1], loc=1) # 手动将图例添加到当前轴域 ax = plt.gca()....
import numpy as np import matplotlib.pyplot as plt from matplotlib import colors x = np.linspace(-0.5, 2.0, 101) y = np.linspace(-0.5, 2.0, 101) z = np.zeros((101, 101)) E = 0.0 for i in range(len(x)): for j in range(len(y)): z[i,j] = -max(y[j]+0.2+E, 0.5-...
还是使用鸢尾花iris数据集:Python可视化|matplotlib10-绘制散点图scatter #导入本帖要用到的库,声明如下:importmatplotlib.pyplotaspltimportnumpyasnpimportpandasaspdimportpalettablefrompandasimportSeries,DataFramefromsklearnimportdatasetsimportseabornassnsimportpalettable#导入鸢尾花iris数据集(方法一)#该方法更有助于理...
import matplotlib import matplotlib.pyplot as plt import numpy as np import pandas as pd from plottable import ColumnDefinition, Table from plottable.formatters import decimal_to_percent,tickcross,signed_integer d = pd.DataFrame(np.random.random((5, 5)), columns=["A", "B", "C", "D", ...