figureimagemarkerplotsubplot 1. pyplot模块 1.1. color的值 blue 1.2. Marker的值 point marker 1.3. LineStyles的值 solid line style 例子: 'b' # blue markers with default shape 'ro' # red circles 'g-' # green solid line '--' # dashed line with default color 'k^:' # black triangle_...
plt.plot()调整颜色与风格 Markers Line Styles Colors 从点到线 误差线 plt.errorbar() 连续误差线 三维数据可视化 plt.imshow() 图例的设置 图例位置legend loc参数 点的大小图例 多个图例的设置 自定义彩条 plt.colorbar.colorbar() cmap展示 范围较大的处理 离散色标 坐标轴设置 大小刻度线 影藏刻度或标签...
It's a shortcut string notation described in the *Notes* section below. >>> plot(x, y) # plot x and y using default line style and color >>> plot(x, y, 'bo') # plot x and y using blue circle markers >>> plot(y) # plot y using x as index array 0..N-1 >>> plot(...
>>> plot(x, y) # plot x and y using default line style and color >>> plot(x, y, 'bo') # plot x and y using blue circle markers >>> plot(y) # plot y using x as index array 0..N-1 >>> plot(y, 'r+') # ditto, but with red plusses You can use `.Line2D` prope...
plt.plot(xpoints, ypoints) plt.show() Result: Try it Yourself » The x-axis is the horizontal axis. The y-axis is the vertical axis.Plotting Without LineTo plot only the markers, you can use shortcut string notation parameter 'o', which means 'rings'.Example...
2.Bar Plot 条形图显示具有与其表示的值成比例的矩形高度或长度条的分类数据。 代码语言:javascript 代码运行次数:0 运行 AI代码解释 # Bar plot.# Importing matplotlib to plot the graphs.importmatplotlib.pyplotasplt # Importing pandasforusing pandas dataframes.importpandasaspd ...
函数定义:(Plot y versus x as lines and/or markers 说的很清楚很局限,这个函数就是绘制2D图 x versus y的,线图或者点图,别的干不了。) 1 2 3 matplotlib.pyplot.plot(*args, scalex=True, scaley=True, data=None,**kwargs) plot([x], y, [fmt],*, data=None,**kwargs) ...
ax = sns.scatterplot(data=plot_df, x="x", y="y", hue='VP', palette='Spectral', style="label", markers=['^', 'o'], s=100) ax.set(xlabel=None, ylabel=None) ax.set_aspect('equal', 'datalim') # sns.move_legend(ax, bbox_to_anchor=(1.01, 1.01), loc='upper left') ...
0 - This is a modal window. No compatible source was found for this media. The output obtained is as shown below − Print Page Previous Next Advertisements
x = np.linspace(0, 2 * np.pi, 30) y1, y2 = np.sin(x), np.cos(x) titles = ["Simple legend", "Legend with more and larger markers", "Legend outside the figure frame", "Legend with a title but no frame", "Legend with face & edge color", "Legend with adjusted size & sp...