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Site updated at 2015-09-07 01:40:37 UTC
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‎2015/04/09/2d-histogram-options.html‎

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# Learn about API authentication here: https://plot.ly/julia/getting-started
2-
# Find your api_key here: https://plot.ly/settings/api
1+
% Learn about API authentication here: https://plot.ly/matlab/getting-started
2+
% Find your api_key here: https://plot.ly/settings/api
33

4-
using Plotly
4+
x = randn(500,1);
5+
y = randn(500,1)+1;
56

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x = randn(500)
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y = randn(500)+1
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data = [
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[
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"x" => x,
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"y" => y,
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"histnorm" => "probability",
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"autobinx" => false,
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"xbins" => [
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"start" => -3,
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"end" => 3,
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"size" => 0.1
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],
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"autobiny" => false,
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"ybins" => [
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"start" => -2.5,
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"end" => 4,
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"size" => 0.1
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],
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"colorscale" => {[0, "rgb(12,51,131)"],[0.25, "rgb(10,136,186)"],[0.5, "rgb(242,211,56)"],[0.75, "rgb(242,143,56)"],[1, "rgb(217,30,30)"]},
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"type" => "histogram2d"
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]
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]
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response = Plotly.plot(data, ["filename" => "2d-histogram-options", "fileopt" => "overwrite"])
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plot_url = response["url"]
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data = {...
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struct(...
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'x', x, ...
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'y', y, ...
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'histnorm', 'probability', ...
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'autobinx', false, ...
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'xbins', struct(...
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'start', -3, ...
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'end', 3, ...
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'size', 0.1), ...
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'autobiny', false, ...
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'ybins', struct(...
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'start', -2.5, ...
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'end', 4, ...
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'size', 0.1), ...
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'colorscale', { { {0, 'rgb(12,51,131)'},{0.25, 'rgb(10,136,186)'},{0.5, 'rgb(242,211,56)'},{0.75, 'rgb(242,143,56)'},{1, 'rgb(217,30,30)'} } }, ...
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'type', 'histogram2d')...
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};
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response = plotly(data, struct('filename', '2d-histogram-options', 'fileopt', 'overwrite'));
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plot_url = response.url

‎2015/04/09/2d-histogram-scatter.html‎

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Original file line numberDiff line numberDiff line change
@@ -1,44 +1,42 @@
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var x0 = [];
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var y0 = [];
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var x1 = [];
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var y1 = [];
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for (var i = 0; i < 500; i ++) {
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x0[i] = Math.random() / 5 * 0.5;
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y0[i] = Math.random() / 5 * 0.5;
8-
}
1+
# Learn about API authentication here: https://plot.ly/julia/getting-started
2+
# Find your api_key here: https://plot.ly/settings/api
93

10-
for (var i = 0; i < 50; i ++) {
11-
x1[i] = Math.random();
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y1[i] = Math.random() + 1;
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}
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using Plotly
145

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var x = [x0, x1]
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var y = [y0, y1]
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x0 = randn(100)/5. + 0.5
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y0 = randn(100)/5. + 0.5
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x1 = rand(50)
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y1 = rand(50) + 1.0
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var trace1 = {
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x: x0,
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y: y0,
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mode: 'markers',
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marker: {
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symbol: 'circle',
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opacity: 0.7
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},
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type: 'scatter'
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};
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var trace2 = {
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x: x1,
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y: y1,
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mode: 'markers',
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marker: {
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symbol: 'square',
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opacity: 0.7
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},
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type: 'scatter'
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};
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var trace3 = {
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x: x,
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y: y,
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type: 'histogram2d'
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};
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var data = [trace1, trace2, trace3];
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Plotly.newPlot('myDiv', data);
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x = [x0; x1]
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y = [y0; y1]
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14+
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trace1 = [
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"x" => x0,
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"y" => y0,
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"mode" => "markers",
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"marker" => [
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"symbol" => "circle",
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"opacity" => 0.7
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],
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"type" => "scatter"
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]
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trace2 = [
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"x" => x1,
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"y" => y1,
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"mode" => "markers",
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"marker" => [
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"symbol" => "square",
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"opacity" => 0.7
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],
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"type" => "scatter"
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]
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trace3 = [
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"x" => x,
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"y" => y,
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"type" => "histogram2d"
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]
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data = [trace1, trace2, trace3]
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response = Plotly.plot(data, ["filename" => "2d-histogram-scatter", "fileopt" => "overwrite"])
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plot_url = response["url"]

‎2015/04/09/2d-histogram.html‎

Lines changed: 18 additions & 15 deletions
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@@ -1,15 +1,18 @@
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var x = [];
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var y = [];
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for (var i = 0; i < 500; i ++) {
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x[i] = Math.random();
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y[i] = Math.random() + 1;
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}
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var data = [
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{
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x: x,
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y: y,
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type: 'histogram2d'
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}
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];
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Plotly.newPlot('myDiv', data);
1+
# Learn about API authentication here: https://plot.ly/julia/getting-started
2+
# Find your api_key here: https://plot.ly/settings/api
3+
4+
using Plotly
5+
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x = randn(500)
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y = randn(500)+1
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9+
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data = [
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[
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"x" => x,
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"y" => y,
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"type" => "histogram2d"
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]
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]
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response = Plotly.plot(data, ["filename" => "2d-histogram", "fileopt" => "overwrite"])
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plot_url = response["url"]

‎2015/04/09/2dhistogram-contour-subplots.html‎

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Original file line numberDiff line numberDiff line change
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# Learn about API authentication here: https://plot.ly/pandas/getting-started
1+
# Learn about API authentication here: https://plot.ly/python/getting-started
22
# Find your api_key here: https://plot.ly/settings/api
33

44
import plotly.plotly as py
55
from plotly.graph_objs import *
6-
import pandas as pd
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import numpy as np
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import colorlover as cl
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from scipy.stats import gaussian_kde
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df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/iris.csv')
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df.head()
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scl = cl.scales['9']['seq']['Blues']
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colorscale = [ [ float(i)/float(len(scl)-1), scl[i] ] for i in range(len(scl)) ]
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colorscale
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def kde_scipy(x, x_grid, bandwidth=0.2 ):
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kde = gaussian_kde(x, bw_method=bandwidth / x.std(ddof=1) )
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return kde.evaluate(x_grid)
7+
import numpy as np
218

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x_grid = np.linspace(df['SepalWidth'].min(), df['SepalWidth'].max(), 100)
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y_grid = np.linspace(df['PetalLength'].min(), df['PetalLength'].max(), 100)
9+
t = np.linspace(-1,1.2,2000)
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x = (t**3)+(0.3*np.random.randn(2000))
11+
y = (t**6)+(0.3*np.random.randn(2000))
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trace1 = Histogram2dContour(
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x=df['SepalWidth'],
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y=df['PetalLength'],
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trace1 = Scatter(
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x=x,
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y=y,
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mode='markers',
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name='points',
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marker=Marker(
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color='rgb(102,0,0)',
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size=2,
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opacity=0.4
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)
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)
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trace2 = Histogram2dContour(
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x=x,
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y=y,
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name='density',
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ncontours=20,
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colorscale=colorscale,
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colorscale='Hot',
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reversescale=True,
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showscale=False
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)
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trace2 = Histogram(
34-
x=df['SepalWidth'],
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trace3 = Histogram(
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x=x,
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name='x density',
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yaxis='y2',
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histnorm='probability density',
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marker=Marker(color='rgb(217, 217, 217)'),
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nbinsx=25
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)
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trace2s = Scatter(
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x=x_grid,
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y=kde_scipy( df['SepalWidth'].as_matrix(), x_grid ),
44-
yaxis='y2',
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line = Line( color='rgb(31, 119, 180)' ),
46-
fill='tonexty',
36+
marker=Marker(
37+
color='rgb(102,0,0)'
38+
),
39+
yaxis='y2'
4740
)
48-
trace3 = Histogram(
49-
y=df['PetalLength'],
41+
trace4 = Histogram(
42+
y=y,
5043
name='y density',
51-
xaxis='x2',
52-
histnorm='probability density',
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marker=Marker(color='rgb(217, 217, 217)'),
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nbinsy=50
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)
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trace3s = Scatter(
57-
y=y_grid,
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x=kde_scipy( df['PetalLength'].as_matrix(), y_grid ),
59-
xaxis='x2',
60-
line = Line( color='rgb(31, 119, 180)' ),
61-
fill='tonextx',
44+
marker=Marker(
45+
color='rgb(102,0,0)'
46+
),
47+
xaxis='x2'
6248
)
63-
64-
data = Data([trace1, trace2, trace2s, trace3, trace3s])
65-
49+
data = Data([trace1, trace2, trace3, trace4])
6650
layout = Layout(
6751
showlegend=False,
6852
autosize=False,
69-
width=700,
70-
height=700,
53+
width=600,
54+
height=550,
55+
xaxis=XAxis(
56+
domain=[0, 0.85],
57+
showgrid=False,
58+
zeroline=False
59+
),
60+
yaxis=YAxis(
61+
domain=[0, 0.85],
62+
showgrid=False,
63+
zeroline=False
64+
),
65+
margin=Margin(
66+
t=50
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),
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hovermode='closest',
7269
bargap=0,
73-
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xaxis=XAxis(domain=[0, 0.746], linewidth=2, linecolor='#444', title='SepalWidth',
75-
showgrid=False, zeroline=False, ticks='', showline=True, mirror=True),
76-
77-
yaxis=YAxis(domain=[0, 0.746],linewidth=2,linecolor='#444', title='PetalLength',
78-
showgrid=False, zeroline=False, ticks='', showline=True, mirror=True),
79-
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xaxis2=XAxis( domain=[0.75, 1], showgrid=False, zeroline=False, ticks='',
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showticklabels=False ),
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yaxis2=YAxis( domain=[0.75, 1], showgrid=False, zeroline=False, ticks='',
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showticklabels=False ),
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xaxis2=XAxis(
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domain=[0.85, 1],
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showgrid=False,
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zeroline=False
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),
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yaxis2=YAxis(
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domain=[0.85, 1],
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showgrid=False,
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zeroline=False
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)
8580
)
86-
8781
fig = Figure(data=data, layout=layout)
88-
89-
# IPython notebook
90-
# py.iplot(fig, filename='pandas-2d-density-plot', height=700)
91-
92-
url = py.plot(fig, filename='pandas-2d-density-plot')
82+
plot_url = py.plot(fig, filename='2dhistogram-2d-density-plot-subplots')

‎2015/04/09/Blackbody-heatmap.html‎

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‎2015/04/09/Bluered-heatmap.html‎

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Original file line numberDiff line numberDiff line change
@@ -1,9 +1,17 @@
1+
// Learn about API authentication here: https://plot.ly/nodejs/getting-started
2+
// Find your api_key here: https://plot.ly/settings/api
3+
4+
require('plotly')(username, api_key);
5+
16
var data = [
27
{
38
z: [[2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51], [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52], [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53], [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54], [6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55], [7, 8, 9, 10, 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69, 70], [22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71], [23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72], [24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73], [25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74], [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75], [27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76], [28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77], [29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78], [30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79], [31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80], [32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81], [33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82], [34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83], [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84], [36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85], [37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86], [38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87], [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88], [40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89], [41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90], [42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91], [43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92], [44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93], [45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94], [46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95], [47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96], [48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97], [49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98], [50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99], [51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100]],
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colorscale: 'Bluered',
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type: 'heatmap'
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colorscale: "Bluered",
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type: "heatmap"
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}
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];
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var layout = {title: 'Bluered'};
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Plotly.newPlot('myDiv', data, layout);
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var layout = {title: "Bluered"};
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var graphOptions = {layout: layout, filename: "Bluered-heatmap", fileopt: "overwrite"};
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plotly.plot(data, graphOptions, function (err, msg) {
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console.log(msg);
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});

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