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ASHRAE - The first step: EDA with Python In this competition we will develop models to predict the energy usage in each building. The dataset contains 1450+ buildings information. Different buildings may have different types of meters. Before we start to build a model, we should have some intuition about the data first. So using visualization tools such as Seaborn we can be more familiar with the data we can get. If you find this notebook interesting or useful, please do not hesitate to vote for me! 1 Start from Here 1.1 Loading Data import pandas as pd import numpy as np import matplotlib .

import numpy as np import pandas as pd import matplotlib . pyplot as plt df1 = pd . DataFrame ( { 'A' : [ 1 , 2 , 3 ] , 'B' : [ 4 , 5 , 6 ] , 'C' : [ 7 , 8 , 9 ] } ) fig , axes = plt . subplots ( 1 , 2 , figsize = ( 10 , 6 ) ) df1 . plot ( kind = 'bar' , colormap = 'Blues_r' , stacked = True , grid = True , ax = axes [ 0 ] ) df1 . plot ( kind = 'bar' , colormap = 'Reds_r' , stacked = False , grid = True , ax = axes [ 1 ] ) 来源： CSDN 作者： chaoqichaoluoe 链接： https://blog.csdn.net/chaoqichaoluoe/article/details/104119280

文章目录 matplotlib jupyter matplotlib Pyplot’s state-machine environment behaves similarly to MATLAB and should be most familiar to users with MATLAB experience. figure The whole figure. The figure keeps track of all the child Axes, a smattering of ‘special’ artists (titles, figure legends, etc), and the canvas. (Don’t worry too much about the canvas, it is crucial as it is the object that actually does the drawing to get you your plot, but as the user it is more-or-less invisible to you). A figure can have any number of Axes, but to be useful should have at least one. Axes This is what you think

关键函数—— plt.boxplot() 快速示例—— import matplotlib . pyplot as plt fig , axes = plt . subplot ( ) axes . boxplot ( list ) # list是要画箱线图的一组数据，假设定义过了 plt . show ( ) LET’S GO NOW >>> 0. 导入库并定义 import matplotlib . pyplot as plt 1. 生成坐标(画板figure、轴axes) figure , axes = plt . subplots ( ) 如要生成 n行m列 个坐标图，只需 plt.subplots(nrows=n, ncols=m) 还可以通过 plt.subplots(figsize=(5,4)) 设定图纸大小 2. 根据数据绘图 假设数据就是最普通的列表：list1, list2, …… （不一定非要用numpy的ndarray格式） ①画一组数据的箱线图： axes . boxplot ( list1 , labels = [ '自定义轴标签名字' ] ) ②画多组数据的箱线图（同一个坐标图上）： axes . boxplot ( [ list1 , list2 , list3 ] , labels = [ 'apples' , 'pears' , 'bananas

利用纯m文件生成ui之简单版canny边缘提取 布局部分 %get the cannyedge of the pictures. %调用说明： %选择自己图片并且导入点击按钮即可(测试版) % 版本号V1.0，编写于2019年12月12号 作者：neverland！ %% h = figure('menubar','none',... 'NumberTitle','off',... 'Name','20177740--neverland的课程设计',... %窗口对象 'Position',[300 120 1000 800],... 'tag','figure1'); %坐标轴1 axes1 = axes('Units','pixels',... 'Parent',h,... 'position',[100 200 300 350],... 'XTick',[],... 'YTick',[],... 'Box','on',... 'tag','ax0'); %坐标轴2 axes2 = axes('Units','pixels',... 'Parent',h,... 'Position',[600 200 300 350],... 'XTick',[],... 'YTick',[],... 'Box','on',... 'tag','ax1'); %菜单作为控制按钮,选择原始图像