转 HighCharts笔记之: Bar Chart】的更多相关文章

最近需要做一些Web图标,研究了几个开源的第三方工具后,最后决定使用HighCharts开发: Highcharts 是一个用纯JavaScript编写的一个图表库, 能够很简单便捷的在web网站或是web应用程序添加有交互性的图表,并且免费提供给个人学习.个人网站和非商业用途使用.目前HighCharts支持 的图表类型有曲线图.区域图.柱状图.饼状图.散状点图和综合图表. HighCharts界面美观,由于使用JavaScript编写,所以不需要像Flash和Java那样需要插件才可以运行,…
1. 条形图(Bar Chart)需要的数据格式类型如下: ["Luke Skywalker", "Darth Vader", "Yoda", "Princess Leia"] [2, 4, 1, 1] 2. Bar Chart代码示例: $(function () { $('#container').highcharts({ chart: { type: 'bar' }, xAxis: { categories: ['Jan…
Natural Language Processing with Python Chapter 4.8 colors = 'rgbcmyk' # red, green, blue, cyan, magenta, yellow, black def bar_chart(categories, words, counts): "Plot a bar chart showing counts for each word by category" import pylab ind = pyla…
Matplotlib之Bar Chart: import numpy as np import matplotlib.pyplot as plt data = [[300, 200, 250, 150, 280], [300, 166, 203, 250, 225], [100, 110, 115, 150, 112], [300, 200, 250, 150, 280], [20, 30, 15, 10, 12], [20, 10, 10, 10, 20]] columns = ('Monda…
2.2Organizing Qualitative Data The number of times a particular distinct value occurs is called its frequency (or count) Relative-Frequency Distribution:百分比 Note: Relative-frequency distributions are better than frequency distributions for comparing…
应用统计学 对类别数据要分类处理: Bar chart复式条形图便于对比: Pareto chart:对类别变量依据频数高低排列: Pie chart:饼图用于一个样本,可以区分类别数据 doughnut chart:环形图用于多个样本,可以区别类别数据 顺序数据:通过计算cumulative percentages向上向下累计,这两者可有不同的解释 线图可以多类方便的放在一张图上,便于比较 对数值型数据要分组处理: 单变量分组:该变量必须是离散值且数量少 组距分组: 等距分组eg:10-20:…
def bar_chart_generator():     l = [1,2,3,4,5]     h = [20, 14, 38, 27, 9]     w = [0.1, 0.2, 0.3, 0.4, 0.5]     b = [1,2,3,4,5]       fig = plt.figure()     ax = fig.add_subplot(111)     rects = ax.bar(l, h, w, b,                    color='#ffff00',…
---恢复内容开始--- 以“3D BarChart”为例. 1.Select a theme.(选择一个主题模板) 2.Set up categories and groups.(设置类型和组) 3.You can set values from the inspector.(你可以从检查面板中设置值) 4.Creat a new script.(创建一个新脚本) Note:(1)Names should be as defined in the editor (名字应该在编辑器中被定义过)…
Example import matplotlib.pyplot as plt import plotly.plotly as py # Learn about API authentication here: https://plot.ly/python/getting-started # Find your api_key here: https://plot.ly/settings/api y = [3, 10, 7, 5, 3, 4.5, 6, 8.1] N = len(y) x = r…
这里利用Nathan Yau所著的<鲜活的数据:数据可视化指南>一书中的数据,学习画图. 数据地址:http://datasets.flowingdata.com/hot-dog-contest-winners.csv (用于普通柱形图) http://datasets.flowingdata.com/hot-dog-places.csv (用于堆积柱形图和横向柱形图) 准备工作:先导入matplotlib和pandas,用pandas读取csv文件,然后创建一个图像和一个坐标轴 import…