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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "H.plot.scatter()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plotly Figure object\n", "\n", "If you want to further manipulate the figures, you can return them from\n", "the function as-is using the `raw` keyword." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "plotly.graph_objs._figure.Figure" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "figure = H.plot.scatter(raw=True)\n", "type(figure)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2D histograms" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "H2 = normal_h2()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "scrolled": true }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Default is heatmap\n", "H2.plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Collections" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "from physt import collection\n", "\n", "collection = collection({\n", " \"small\": np.random.normal(160, 20, 600),\n", " \"tall\": np.random.normal(180, 20, 1000),\n", " \"huge\": np.random.normal(200, 20, 400),\n", " \"gigantic\": np.random.normal(220, 20, 200)\n", "}, \"human\")" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "mode": "lines", "name": "small", "type": "scatter", "x": [ 85, 95, 105, 115, 125, 135, 145, 155, 165, 175, 185, 195, 205, 215, 225, 235, 245, 255, 265, 275 ], "y": [ 1, 1, 3, 12, 20, 45, 84, 126, 121, 91, 61, 18, 9, 6, 2, 0, 0, 0, 0, 0 ] }, { 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