errorbar函数的作用是在plot函数的基础上,在数据点位置绘制误差棒 函数: matplotlib.pyplot.errorbar(x, y, yerr=None, xerr=None, fmt='', ecolor=None, elinewidth=None, capsize=None, barsabove=False, lolims=False, uplims=False, xlolims=False, xuplims=False, errorevery=1, capthick=None, *...
plt.errorbar(x_values, y_values + 3, yerr=y_error_large, fmt='^', color='green', ecolor='purple', capsize=5, label='Data Set 2') # 添加标题和标签 plt.title('Multiple Error Bars') plt.xlabel('X-axis') plt.ylabel('Y-axis') # 添加图例 plt.legend() # 显示图像 plt.show()...
matplotlib.pyplot.bar 可以画柱状图,其中的关键字参数 yerr 可以添加 error bar, 关键字参数 bottom 可以摞起来。 以下代码据说源自官网,我是从这里拷贝:https://blog.csdn.net/qq_42935317/article/details/115672473 # a stacked bar plot with errorbarsimportnumpyasnpimportmatplotlib.pyplotasplt N =5menMeans...
import matplotlib.pyplot as pltimport numpy as np# 准备数据x = np.linspace(0, 10, 100)y1 = np.sin(x)y2 = np.cos(x)# 创建堆叠面积图plt.stackplot(x, y1, y2, labels=['Sin', 'Cos'], alpha=0.5)plt.xlabel('X-axis')plt.ylabel('Y-axis')plt.title('Stacked Area Plot')plt.leg...
plt.errorbar(x, ymean, yerror, color='tab:blue', ecolor='tab:blue', capsize=3, linewidth=1, label='mean with error bars') plt.legend() plt.show() 反对 回复 2021-12-17 www说 TA贡献1775条经验 获得超8个赞 您只能使用 matplot lib 执行此操作,如下所示: def plot_with_error_band...
title('水平条形图') # 指定顺序 height_order, bars_order = zip(*sorted(zip(height, bars), reverse=False)) # 自定义顺序 plt.subplot(3, 3, 2) plt.barh(y_pos, height_order) plt.yticks(y_pos, bars_order) plt.title('指定顺序') # 自定义颜色 plt.subplot(3, 3, 3) plt.bar(x_...
Width of the “caps” on error bars. 注:代码可左右滑动,下同 importseabornassns sns.set_style("whitegrid") tips=sns.load_dataset("tips")#载入自带数据集 #x轴为分类变量day,y轴为数值变量total_bill,利用颜色再对sex分类 ax=sns.barplot(x="day",y="total_bill",hue="sex",data=tips) ...
A bar chart with error bars is shown below. Note the labels on the x-axis and the error bars at the top of each bar. In order to build this plot, we need a couple of things: AssetDescription Python (version 3.6) Run the program Anaconda Prompt create the virtual environment and insta...
plt.ylabel("Y-Axis",fontsize=18) for value in range(150): update_y_value = np.sin(x-2.5*value) plot1.set_xdata(x) plot1.set_ydata(update_y_value) figure.canvas.draw() figure.canvas.flush_events() time.sleep(0.1)# Displayplt.show() ...
') | | bar(self, x=None, y=None, **kwargs) | Vertical bar plot. | | A bar plot is a plot that presents categorical data with | rectangular bars with lengths proportional to the values that they | represent. A bar plot shows comparisons among discrete categories. One | axis of ...