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‎docs/gallery/3d.ipynb‎

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‎docs/gallery/basic.ipynb‎

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‎docs/gallery/facets.ipynb‎

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‎docs/gallery/maps.ipynb‎

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‎docs/gallery/networks.ipynb‎

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‎docs/gallery/statistical.ipynb‎

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‎docs/gallery/theming.ipynb‎

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‎docs/gallery/timeseries.ipynb‎

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‎docs/getting-started.ipynb‎

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‎docs/index.ipynb‎

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{
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"nbformat": 4,
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"nbformat_minor": 5,
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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}
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"nbformat": 4,
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"nbformat_minor": 5,
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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}
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},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# ggplotly\n",
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"\n",
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"A data visualization library for Python that combines the **grammar of graphics** from ggplot2 with the **interactivity** of Plotly.\n",
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"\n",
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"## Why ggplotly?\n",
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"\n",
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"- **Familiar syntax** - If you know ggplot2 from R, you'll feel right at home\n",
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"- **Interactive plots** - Powered by Plotly for zooming, panning, and hover tooltips\n",
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"- **Jupyter-friendly** - Plots render automatically in notebooks\n",
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"- **Comprehensive** - 90+ ggplot2-equivalent functions\n",
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"\n",
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"## Quick Example"
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]
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},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# ggplotly\n",
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"\n",
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"A data visualization library for Python that combines the **grammar of graphics** from ggplot2 with the **interactivity** of Plotly.\n",
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"\n",
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"## Why ggplotly?\n",
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"\n",
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"- **Familiar syntax** - If you know ggplot2 from R, you'll feel right at home\n",
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"- **Interactive plots** - Powered by Plotly for zooming, panning, and hover tooltips\n",
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"- **Jupyter-friendly** - Plots render automatically in notebooks\n",
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"- **Comprehensive** - 90+ ggplot2-equivalent functions\n",
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"\n",
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"## Quick Example"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from ggplotly import *\n",
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"import pandas as pd\n",
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"\n",
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"df = pd.DataFrame({\n",
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" 'x': [1, 2, 3, 4, 5],\n",
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" 'y': [1, 4, 9, 16, 25],\n",
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" 'group': ['A', 'A', 'B', 'B', 'B']\n",
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"})\n",
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"\n",
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"# Simple scatter plot with color mapping\n",
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"ggplot(df, aes(x='x', y='y', color='group')) + geom_point(size=10) + theme_minimal()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Installation\n",
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"\n",
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"```bash\n",
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"pip install ggplotly\n",
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"```\n",
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"\n",
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"## What's Included\n",
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"\n",
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"| Category | Count | Examples |\n",
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"|----------|-------|----------|\n",
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"| **Geoms** | 34 | `geom_point`, `geom_line`, `geom_bar`, `geom_boxplot`, `geom_map` |\n",
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"| **Scales** | 17 | `scale_color_manual`, `scale_fill_gradient`, `scale_x_log10` |\n",
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"| **Themes** | 9 | `theme_minimal`, `theme_dark`, `theme_bbc`, `theme_nytimes` |\n",
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"| **Stats** | 7 | `stat_smooth`, `stat_count`, `stat_density` |\n",
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"| **Coords** | 4 | `coord_flip`, `coord_polar`, `coord_sf` |\n",
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"| **Facets** | 2 | `facet_wrap`, `facet_grid` |\n",
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"\n",
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"## Gallery\n",
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"\n",
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"Explore examples organized by visualization type:\n",
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"\n",
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"- **[Basic Charts](gallery/basic.ipynb)** - Scatter, line, bar, histograms, box plots\n",
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"- **[Statistical](gallery/statistical.ipynb)** - Smoothing, density, error bars, summaries\n",
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"- **[Time Series](gallery/timeseries.ipynb)** - Date axes, range plots, candlesticks, OHLC\n",
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"- **[Geographic Maps](gallery/maps.ipynb)** - Choropleths, projections, point maps\n",
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"- **[3D Visualizations](gallery/3d.ipynb)** - Scatter, surfaces, wireframes\n",
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"- **[Network Graphs](gallery/networks.ipynb)** - Edge bundling, sea routes\n",
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"- **[Multi-Panel (Facets)](gallery/facets.ipynb)** - Small multiples, facet_wrap, facet_grid\n",
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"- **[Theming](gallery/theming.ipynb)** - Custom themes, publication-ready styling\n",
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"\n",
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"## Coming from R?\n",
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"\n",
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"ggplotly aims for API compatibility with ggplot2. Most code translates directly:\n",
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"\n",
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"**R (ggplot2):**\n",
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"```r\n",
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"ggplot(mpg, aes(x = displ, y = hwy, color = class)) +\n",
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" geom_point() +\n",
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" theme_minimal() +\n",
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" labs(title = \"Fuel Efficiency\")\n",
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"```\n",
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"\n",
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"**Python (ggplotly):**\n",
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"```python\n",
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"ggplot(mpg, aes(x='displ', y='hwy', color='class')) + \\\n",
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" geom_point() + \\\n",
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" theme_minimal() + \\\n",
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" labs(title='Fuel Efficiency')\n",
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"```\n",
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"\n",
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"The main differences:\n",
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"\n",
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"- Column names are strings: `x='column'` not `x = column`\n",
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"- Use `\\` or parentheses for line continuation\n",
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"- Import with `from ggplotly import *`"
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]
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}
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]
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": "from ggplotly import *\nimport pandas as pd\n\ndf = pd.DataFrame({\n 'x': [1, 2, 3, 4, 5],\n 'y': [1, 4, 9, 16, 25],\n 'group': ['A', 'A', 'B', 'B', 'B']\n})\n\n# Simple scatter plot with color mapping\n(ggplot(df, aes(x='x', y='y', color='group')) + geom_point(size=10) + theme_minimal()).draw()"
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Installation\n",
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"\n",
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"```bash\n",
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"pip install ggplotly\n",
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"```\n",
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"\n",
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"## What's Included\n",
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"\n",
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"| Category | Count | Examples |\n",
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"|----------|-------|----------|\n",
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"| **Geoms** | 34 | `geom_point`, `geom_line`, `geom_bar`, `geom_boxplot`, `geom_map` |\n",
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"| **Scales** | 17 | `scale_color_manual`, `scale_fill_gradient`, `scale_x_log10` |\n",
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"| **Themes** | 9 | `theme_minimal`, `theme_dark`, `theme_bbc`, `theme_nytimes` |\n",
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"| **Stats** | 7 | `stat_smooth`, `stat_count`, `stat_density` |\n",
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"| **Coords** | 4 | `coord_flip`, `coord_polar`, `coord_sf` |\n",
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"| **Facets** | 2 | `facet_wrap`, `facet_grid` |\n",
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"\n",
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"## Gallery\n",
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"\n",
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"Explore examples organized by visualization type:\n",
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"\n",
62+
"- **[Basic Charts](gallery/basic.ipynb)** - Scatter, line, bar, histograms, box plots\n",
63+
"- **[Statistical](gallery/statistical.ipynb)** - Smoothing, density, error bars, summaries\n",
64+
"- **[Time Series](gallery/timeseries.ipynb)** - Date axes, range plots, candlesticks, OHLC\n",
65+
"- **[Geographic Maps](gallery/maps.ipynb)** - Choropleths, projections, point maps\n",
66+
"- **[3D Visualizations](gallery/3d.ipynb)** - Scatter, surfaces, wireframes\n",
67+
"- **[Network Graphs](gallery/networks.ipynb)** - Edge bundling, sea routes\n",
68+
"- **[Multi-Panel (Facets)](gallery/facets.ipynb)** - Small multiples, facet_wrap, facet_grid\n",
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"- **[Theming](gallery/theming.ipynb)** - Custom themes, publication-ready styling\n",
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"\n",
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"## Coming from R?\n",
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"\n",
73+
"ggplotly aims for API compatibility with ggplot2. Most code translates directly:\n",
74+
"\n",
75+
"**R (ggplot2):**\n",
76+
"```r\n",
77+
"ggplot(mpg, aes(x = displ, y = hwy, color = class)) +\n",
78+
" geom_point() +\n",
79+
" theme_minimal() +\n",
80+
" labs(title = \"Fuel Efficiency\")\n",
81+
"```\n",
82+
"\n",
83+
"**Python (ggplotly):**\n",
84+
"```python\n",
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"ggplot(mpg, aes(x='displ', y='hwy', color='class')) + \\\n",
86+
" geom_point() + \\\n",
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" theme_minimal() + \\\n",
88+
" labs(title='Fuel Efficiency')\n",
89+
"```\n",
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"\n",
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"The main differences:\n",
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"\n",
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"- Column names are strings: `x='column'` not `x = column`\n",
94+
"- Use `\\` or parentheses for line continuation\n",
95+
"- Import with `from ggplotly import *`"
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]
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}
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]
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}

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