set_title('logarithmic scale for y axes') # xy轴对数刻度 ax = plt.subplot2grid((2, 2), (1, 1), colspan=1) ax.scatter(x, y, s=60, alpha=0.7, edgecolors="k") ax.set_xscale("log") ax.set_yscale("log") ax.set_title('logarithmic scale for x/y axes') fig.tight_layout(...
在matplotlib绘图时,通过set_xscale和set_yscale这两个函数,可以轻松对坐标系进行坐标放缩,并且提供了4个基础的放缩模板,分别是linear, log, symlog, logit。 import numpy as np import matplotlib.pyplot as plt xs = np.linspace(-5,5,1000) labels = ['linear', 'log', 'symlog', 'logit'] fig = pl...
importmatplotlib.pyplotasplt# 创建一个图形图像fig,ax=plt.subplots()# 设置x轴和y轴为对数坐标轴ax.set_xscale("log")ax.set_yscale("log")# 绘制数据x=[1,10,100,1000]# x轴数据y=[1,2,3,4]# y轴数据ax.plot(x,y)# 绘制折线图# 显示图形plt.show() 1. 2. 3. 4. 5. 6. 7. 8. ...
sns.countplot(pcp_interval['interval'],palette='Set1') for p in ax.patches: ax.annotate('{:.2f}%'.format(100*p.get_height()/len(pcp_interval['interval'])), (p.get_x() + 0.1, p.get_height() + 100)) ax.set_yscale("log") plt.title('pv-cart-pay路径用户消费时间间隔') outpu...
代码具体实现如下: package com.zuoyan.algorithm; public class FindMinMax { //Mai...
ax.set_yscale("log") 设置x轴的刻度增量: 代码语言:txt 复制 ax.xaxis.set_major_locator(plt.LogLocator(base=10.0, subs=(1.0,))) 这里的base参数表示刻度的基数,subs参数表示刻度的增量。 设置y轴的刻度增量: 代码语言:txt 复制 ax.yaxis.set_major_locator(plt.LogLocator(base=10.0, subs=(1.0,))...
ax2.set_title(r'Linear plot of $ {10}^{x} $ ') ax2.set_ylabel(r'$ {y} = {10}^{x} $') plt.grid(b=True, which='both', axis='both') ax3 = fig.add_subplot(2, 2, 3) ax3.plot(x, z, color='green') ax3.set_yscale('log') #对数标度 ...
ax1.set_yscale('log') #两个坐标轴和主次刻度打开网格显示 plt.grid(b=True, which='both', axis='both') ax2 = fig.add_subplot(2,2,2) ax2.plot(x,y,color='r') ax2.set_yscale('linear') plt.grid(b=True, which='both', axis='both') ...
ax.set_yscale("log") sns.countplot(dau3_cumsum.values,palette='Set1') forpinax.patches: ax.annotate('{:.2f}%'.format(100*p.get_height/len(dau3_cumsum.values)), (p.get_x + 0.2, p.get_height + 100)) plt.title('高活跃用户累计活跃天数分布') ...
1. import matplotlib.pyplotaspltimport numpyasnpdef scatterplot(x_data, y_data, x_label="", y_label="", title="", color = "r", yscale_log=False): 2. 3. #Createthe plot object 4. _, ax = plt.subplots() # Plot the data,setthesize(s), color and transparency (alpha) ...