![](\"assets/bokeh-transparent.png\"){kind=spacer}
\n",
" \n",
" | \n",
" \n",
" \n",
" \n",
" | \n",
" \n",
" Bokeh 教程\n", " | \n",
"
![](\"assets/datashader_examples.png\")
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 什么时候 *不要* 使用 datashader\n",
"\n",
"* 绘制小于1e5或1e6的数据点\n",
"* *每个* 数据点都很重要; 标准Bokeh将渲染所有数据点\n",
"* 对于 *每个* 数据点提供完全交互（悬停工具）\n",
"\n",
"## 什么时候 *要* 使用 datashader\n",
"\n",
"* 确实是 *大数据*，而Bokeh/Matplotlib力不从心时\n",
"* 当 *分布* 比单个点更重要\n",
"* 当您进行抽样或分档以更好地理解数据的 *分布*\n",
"\n",
"# datashader 怎么工作?\n",
"\n",
"![](\"https://raw.githubusercontent.com/bokeh/datashader/master/docs/images/pipeline2.png\")
\n",
"\n",
"* Bokeh这样的工具直接将数据映射为 HTML/JavaScript 图表\n",
"* datashader将数据渲染成一个屏幕尺寸的聚合数组，从该数组可以构建一个图像，然后嵌入到Bokeh图中\n",
"* 只有固定大小的图像需要发送到浏览器，所以使得数百万甚至数十亿个数据点成为可能\n",
"* 每一步自动调整到数据，但可以自定义\n",
"\n",
"# datashader 支持的可视化\n",
"\n",
"Datashader 目前支持：\n",
"\n",
"* 散列图/热图\n",
"* 时间序列\n",
"* 连接点（轨迹）\n",
"* 栅格\n",
"\n",
"在各种情况下，输出都可轻松嵌入到Bokeh图中，并可为在notebook或应用程序中进行平移和缩放提供交互式重采样。 可以从聚合数组中生成图例/悬停信息，从而提供交互性。\n",
"\n",
"# 真实地可视化大数据\n",
"\n",
"一旦数据足够大以至于难以辨别个别点，以可靠的方式构建可视化至关重要，以忠实地揭示您的系统数据的底层分布。 例如，以下所有这些图都显示相同的数据 -- 它们中哪一个是真正的分布？\n",
"\n",
"![](\"assets/5_gaussians_3_ways.png\")
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"让我们把它找出来！ 上述图像中的数据是通过对五个正态（高斯）分布求和来创建的，如下所示："
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"| \n", " | cat | \n", "val | \n", "x | \n", "y | \n", "
|---|---|---|---|---|
| 49995 | \n", "d5 | \n", "50 | \n", "-1.397579 | \n", "0.610189 | \n", "
| 49996 | \n", "d5 | \n", "50 | \n", "-2.649610 | \n", "3.080821 | \n", "
| 49997 | \n", "d5 | \n", "50 | \n", "1.933360 | \n", "0.243676 | \n", "
| 49998 | \n", "d5 | \n", "50 | \n", "4.306374 | \n", "1.032139 | \n", "
| 49999 | \n", "d5 | \n", "50 | \n", "-0.493567 | \n", "-2.242669 | \n", "
![](\"assets/5_gaussians_labeled.png\")
\n",
"\n",
"让我们依次查看 datashader 管道中的每个阶段，以查看如何构建这样的图像以及如何控制和嵌入到Bokeh图中。\n",
"\n",
"# Projection and Aggregation（映射和聚合）\n",
"\n",
"datashader 管道的第一个阶段是决定：\n",
"\n",
"* 您想要在x和y轴上绘制哪些变量\n",
"* 你想要将这些值聚合到多大的数组中\n",
"* 该数组应覆盖哪些数据值范围，以及\n",
"* 你想用什么“降维”功能进行聚合"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\\n\"+\n", " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", " \"
\\n\"+\n", " \"\\n\"+\n",
" \"from bokeh.resources import INLINE\\n\"+\n",
" \"output_notebook(resources=INLINE)\\n\"+\n",
" \"\\n\"+\n",
" \"\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"
\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"