{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Overview\n",
"This notebook demonstrates how to use DataShader to display large datasets inside a plotly `FigureWidget`. Change callbacks are used to recompute the datashader image whenever the axis range or figure size changes"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Imports"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# core\n",
"import io\n",
"import base64 \n",
"import time\n",
"\n",
"# pandas\n",
"import pandas as pd\n",
"\n",
"# numpy\n",
"import numpy as np\n",
"\n",
"# scikit learn\n",
"from sklearn import datasets\n",
"\n",
"# datashader\n",
"import datashader as ds\n",
"import datashader.transfer_functions as tf\n",
"from datashader.colors import inferno"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Generate dataset\n",
"We will create a large dataset by duplicating the Iris dataset many times with random noise"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" sepal_length | \n",
" sepal_width | \n",
" petal_length | \n",
" petal_width | \n",
"
\n",
" \n",
" \n",
" \n",
" | count | \n",
" 1.050000e+06 | \n",
" 1.050000e+06 | \n",
" 1.050000e+06 | \n",
" 1.050000e+06 | \n",
"
\n",
" \n",
" | mean | \n",
" 5.843271e+00 | \n",
" 3.053854e+00 | \n",
" 3.758803e+00 | \n",
" 1.198912e+00 | \n",
"
\n",
" \n",
" | std | \n",
" 8.493378e-01 | \n",
" 4.763162e-01 | \n",
" 1.769648e+00 | \n",
" 7.867648e-01 | \n",
"
\n",
" \n",
" | min | \n",
" 3.559033e+00 | \n",
" 1.114488e+00 | \n",
" 2.296150e-01 | \n",
" -8.285020e-01 | \n",
"
\n",
" \n",
" | 25% | \n",
" 5.155895e+00 | \n",
" 2.740263e+00 | \n",
" 1.638386e+00 | \n",
" 3.924995e-01 | \n",
"
\n",
" \n",
" | 50% | \n",
" 5.802342e+00 | \n",
" 3.033030e+00 | \n",
" 4.306771e+00 | \n",
" 1.316363e+00 | \n",
"
\n",
" \n",
" | 75% | \n",
" 6.444157e+00 | \n",
" 3.345420e+00 | \n",
" 5.142291e+00 | \n",
" 1.829025e+00 | \n",
"
\n",
" \n",
" | max | \n",
" 8.717877e+00 | \n",
" 5.090993e+00 | \n",
" 7.581433e+00 | \n",
" 3.250024e+00 | \n",
"
\n",
" \n",
"
\n",
"