import numpy as np 创建x和y数据 x = np.linspace(0, 10, 100)y = np.sin(x) 绘制折线图 plt.plot(x, y)plt.title(‘Simple Line Plot’) # 添加标题plt.xlabel(‘X Axis Label’) # 添加x轴标签plt.ylabel(‘Y Axis Label’) # 添加y轴标签plt.legend() # 添加图例plt.show() # 显示图...
plot(x, y) Python Copy输出:示例2import matplotlib.pyplot as plt x =['Geeks', 'for', 'geeks', 'tutorials'] y =[1, 2, 3, 4] # Adding space between label and # axis by setting labelpad plt.ylabel('Numbers label', labelpad = 50) plt.plot(x, y) Python Copy输出:...
fontdict:将字体样式添加到标签 labelpad:这有助于我们设置标签和轴之间的间距 范例1: importmatplotlib.pyplotasplt# setting x valuesx =['Geeks','for','geeks','tutorials']# Setting y valuesy =[1,2,3,4]# Adding label on the y-axisplt.ylabel('Numbers label')# plotting the graphplt.plot(x...
y = [2, 3, 5, 7, 11] labels = ['A', 'B', 'C', 'D', 'E'] # 绘制散点图并添加标签 sns.scatterplot(x, y) for i, label in enumerate(labels): plt.text(x[i], y[i], label) # 添加标题和标签 plt.title('Scatter Plot with Labels') plt.xlabel('X-axis') plt.ylabel('...
上述例子的axis()命令传入一列参数[xmin,xmax,ymin,ymax],指定坐标轴的x,y轴的最大最小值(viewport of the exes) 假如matplotlib只限制于处理这种普通的数据列表格式的数据,那它对数值处理(numeric processing)的作用将非常小。一般来说,你会使用numpy数组。事实上,所有序列都在内部被转换为numpy数组.下面这个例...
本文对下图中坐标轴(axis),刻度值(trick label),刻度(tricks),子图标题(title),图标题(suptitle),坐标轴标题(xlabel,ylabel),网格线(grid)等参数的详细设置,不过相对于官网还只是冰山一角。…
x_label = "X Axis" y_label = "Y_axis" title_text_obj = plt.title(title, fontsize=DEFAULT_FONT_SIZE, verticalalignment="bottom") title_text_obj.set_path_effects([patheffects.withSimplePatchShadow()]) pe = patheffects.withSimplePatchShadow(offset=DEFAULT_OFFSET_XY, shadow_rgbFace=DEFAULT...
#axes.labelweight: normal # weight of the x and y labels #axes.labelcolor: black #xaxis.labellocation: center # alignment of the xaxis label: {left, right, center} 底层相关函数为：Axes.set_xlabel(xlabel, fontdict=None, labelpad=None, *, loc=None, **kwargs)Axes.get_xlabel()案例...
plt.xlabel('X-axis Label') plt.ylabel('Y-axis Label') # 显示图表 plt.show() 3. 绘制柱状图 柱状图是一种用于比较不同类别之间数据差异的图表。 python # 对数据进行分组和聚合(例如,计算每个类别的平均值) grouped_data = data.groupby('category_column')['value_column'].mean() ...
y2 = [40,-10,45]# plotting the given graphplt.semilogx(x2, y2, nonposx ="mask", color ="green", linewidth =4)# set the titleplt.title("MASKED")# set y axis labelplt.ylabel('---y---')# set x axis labelplt.xlabel('---x---')# plot with gridplt.grid(True)# show th...