使用堆积柱形图时,用bottom参数传值的方式控制柱形的值,使后绘制的柱形位于先绘制的柱形之上,代码示例如下: plt.bar(x,y1,tick_label = ['a','b','c','d','e'],width = bar_width) plt.bar(x,y2,bottom = y1,width = bar_width) plt.show() 1. 2. 3. 带有误差棒的堆积柱形图绘制如下图...
point_y = np.array([2,8,4,12]) plt.plot(point_y, marker ='*'); image-20240820225857015 画红色线: point_y = np.array([2,8,4,10]) plt.plot(point_y,'ro-')# o is a mareker and r is a red plt.show() image-20240821223734590 画绿色虚线:...
1. 散点图 >>> import numpy as np >>> x = np.array([1, 2, 3, 4]) >>> y = np.array([1, 2, 3, 4]) >>> plt.plot(x,y,'o') 1. 2. 3. 4. 输出结果如下 2. 散点图和直线图的叠加 >>> plt.plot(x,y,marker='o', linestyle='--', linewidth=2) 1. 输出结果如下...
from pyg2plot import Plot# 创建柱状图实例bar = Plot("Bar")line = Plot("Line")# 定义数据data = [ {"x": "A", "y": 10}, {"x": "B", "y": 20}, {"x": "C", "y": 30}]# 设置柱状图数据bar.setData(data)# 设置折线图数据line.setData(data)# 实现联动bar.on('plot...
>>>importnumpyasnp>>>x=np.array([1,2,3,4])>>>y=np.array([1,2,3,4])>>>plt.plot(x,y,'o') 输出结果如下 2. 散点图和直线图的叠加 代码语言:javascript 代码运行次数:0 运行 AI代码解释 >>>plt.plot(x,y,marker='o',linestyle='--',linewidth=2) ...
scalars are supported as well (equivalent to an array with constant value). The parameters can also be2-dimensional. Then, the columns represent separate data sets. fmt : str, optional A format string, e.g.'ro'forred circles. See the *Notes*sectionfora full description of the format strin...
import numpy as np # 简单绘制波士顿行政区划 ax = gplt.polyplot(df=boston_zip_codes, projection=gcrs.AlbersEqualArea(), edgecolor='lightgrey', linewidths=0.5) ax = gplt.pointplot(df=boston_airbnb_listings, ax=ax, # 叠加图层 linewidths=0.2, # 散点轮廓宽度 scale='price', #以price作为色...
0.导语1.预备知识1.1 np.arange()1.2 numpy.random.uniform()1.3 zip()2.bar绘制3.散点图4.3D图5.参考文章6.作者的话 0.导语 上次出了一篇matlibplot基础篇,本篇来主要学习matlibplot的各种图绘制!下面一起来嗨吧!!! 1.预备知识 1.1 np.arange() np.arange()返回的是numpy.ndarray() 三个参数(first,...
import numpy as np import time from math import * plt.ion() #开启interactive mode 成功的关键函数 plt.figure(1) t = [0] t_now = 0 m = [sin(t_now)] for i in range(2000): plt.clf() #清空画布上的所有内容 t_now = i*0.1 ...
import numpy as np import pandas as pd import matplotlib.pyplot as plt plt.rcParams['font.sans-serif'] = ['SimHei']#字体微软雅黑 plt.subplot(1,1,1)#建立一个坐标系 #指明x和y值 x = np.array(["东区","南区","西区","北区"]) ...