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‎docs/api/stats.md‎

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::: ggplotly.stats.stat_qq_line.stat_qq_line
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options:
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show_root_heading: true
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## stat_contour
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::: ggplotly.stats.stat_contour.stat_contour
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options:
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show_root_heading: true

‎docs/guide/geoms.ipynb‎

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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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"# Geoms\n",
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"\n",
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"Geoms (geometric objects) are the visual elements that represent your data. ggplotly provides 34 geoms for different visualization types."
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"source": "# Geoms\n\nGeoms (geometric objects) are the visual elements that represent your data. ggplotly provides 44 geoms for different visualization types."
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"metadata": {},
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"## Complete Geom List\n",
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"\n",
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"| Geom | Description |\n",
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"|------|-------------|\n",
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"| `geom_point` | Scatter plots |\n",
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"| `geom_line` | Line plots (sorted by x) |\n",
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"| `geom_path` | Path plots (data order) |\n",
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"| `geom_bar` | Bar charts |\n",
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"| `geom_col` | Column charts |\n",
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"| `geom_histogram` | Histograms |\n",
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"| `geom_boxplot` | Box plots |\n",
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"| `geom_violin` | Violin plots |\n",
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"| `geom_density` | Density plots |\n",
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"| `geom_area` | Area plots |\n",
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"| `geom_ribbon` | Ribbon plots |\n",
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"| `geom_smooth` | Smoothed lines |\n",
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"| `geom_tile` | Heatmaps |\n",
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"| `geom_text` | Text labels |\n",
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"| `geom_errorbar` | Error bars |\n",
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"| `geom_segment` | Line segments |\n",
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"| `geom_step` | Step plots |\n",
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"| `geom_rug` | Rug plots |\n",
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"| `geom_jitter` | Jittered points |\n",
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"| `geom_vline` | Vertical lines |\n",
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"| `geom_hline` | Horizontal lines |\n",
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"| `geom_abline` | Diagonal lines |\n",
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"| `geom_contour` | Contour lines |\n",
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"| `geom_contour_filled` | Filled contours |\n",
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"| `geom_map` | Choropleth maps |\n",
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"| `geom_sf` | Simple features |\n",
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"| `geom_point_map` | Map points |\n",
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"| `geom_range` | Range plots |\n",
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"| `geom_edgebundle` | Edge bundling |\n",
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"| `geom_searoute` | Sea routes |\n",
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"| `geom_point_3d` | 3D points |\n",
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"| `geom_surface` | 3D surfaces |\n",
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"| `geom_wireframe` | 3D wireframes |\n",
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"| `geom_candlestick` | Candlesticks |\n",
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"| `geom_ohlc` | OHLC charts |"
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]
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"source": "## Complete Geom List\n\n| Geom | Description |\n|------|-------------|\n| `geom_point` | Scatter plots |\n| `geom_line` | Line plots (sorted by x) |\n| `geom_lines` | Multi-series line plots |\n| `geom_path` | Path plots (data order) |\n| `geom_bar` | Bar charts |\n| `geom_col` | Column charts |\n| `geom_histogram` | Histograms |\n| `geom_boxplot` | Box plots |\n| `geom_violin` | Violin plots |\n| `geom_density` | Density plots |\n| `geom_area` | Area plots |\n| `geom_ribbon` | Ribbon plots |\n| `geom_smooth` | Smoothed lines |\n| `geom_tile` | Heatmaps |\n| `geom_text` | Text labels |\n| `geom_errorbar` | Error bars |\n| `geom_segment` | Line segments |\n| `geom_step` | Step plots |\n| `geom_rug` | Rug plots |\n| `geom_jitter` | Jittered points |\n| `geom_vline` | Vertical lines |\n| `geom_hline` | Horizontal lines |\n| `geom_abline` | Diagonal lines |\n| `geom_contour` | Contour lines |\n| `geom_contour_filled` | Filled contours |\n| `geom_map` | Choropleth maps |\n| `geom_sf` | Simple features |\n| `geom_range` | Range plots |\n| `geom_edgebundle` | Edge bundling |\n| `geom_searoute` | Sea routes |\n| `geom_fanchart` | Fan charts for uncertainty |\n| `geom_point_3d` | 3D points |\n| `geom_surface` | 3D surfaces |\n| `geom_wireframe` | 3D wireframes |\n| `geom_candlestick` | Candlestick charts |\n| `geom_ohlc` | OHLC charts |\n| `geom_waterfall` | Waterfall charts |\n| `geom_sankey` | Sankey flow diagrams |\n| `geom_stl` | STL decomposition plots |\n| `geom_acf` | Autocorrelation plots |\n| `geom_pacf` | Partial autocorrelation plots |\n| `geom_norm` | Normal distribution overlay |\n| `geom_qq` | Q-Q plots |\n| `geom_qq_line` | Q-Q reference line |"
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}

‎docs/index.ipynb‎

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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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"source": "# ggplotly\n\nA data visualization library for Python that combines the **grammar of graphics** from ggplot2 with the **interactivity** of Plotly.\n\n## Why ggplotly?\n\n- **Familiar syntax** - If you know ggplot2 from R, you'll feel right at home\n- **Interactive plots** - Powered by Plotly for zooming, panning, and hover tooltips\n- **Jupyter-friendly** - Plots render automatically in notebooks\n- **Comprehensive** - 113+ ggplot2-equivalent functions\n\n## Quick Example"
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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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"source": "## Installation\n\n```bash\npip install ggplotly\n```\n\n## What's Included\n\n| Category | Count | Examples |\n|----------|-------|----------|\n| **Geoms** | 44 | `geom_point`, `geom_line`, `geom_bar`, `geom_boxplot`, `geom_map` |\n| **Scales** | 17 | `scale_color_manual`, `scale_fill_gradient`, `scale_x_log10` |\n| **Themes** | 9 | `theme_minimal`, `theme_dark`, `theme_bbc`, `theme_nytimes` |\n| **Stats** | 13 | `stat_smooth`, `stat_count`, `stat_density` |\n| **Coords** | 4 | `coord_flip`, `coord_polar`, `coord_sf` |\n| **Facets** | 2 | `facet_wrap`, `facet_grid` |\n\n## Gallery\n\nExplore examples organized by visualization type:\n\n- **[Basic Charts](gallery/basic.ipynb)** - Scatter, line, bar, histograms, box plots\n- **[Statistical](gallery/statistical.ipynb)** - Smoothing, density, error bars, summaries\n- **[Time Series](gallery/timeseries.ipynb)** - Date axes, range plots, candlesticks, OHLC\n- **[Geographic Maps](gallery/maps.ipynb)** - Choropleths, projections, point maps\n- **[3D Visualizations](gallery/3d.ipynb)** - Scatter, surfaces, wireframes\n- **[Network Graphs](gallery/networks.ipynb)** - Edge bundling, sea routes\n- **[Multi-Panel (Facets)](gallery/facets.ipynb)** - Small multiples, facet_wrap, facet_grid\n- **[Theming](gallery/theming.ipynb)** - Custom themes, publication-ready styling\n\n## Coming from R?\n\nggplotly aims for API compatibility with ggplot2. Most code translates directly:\n\n**R (ggplot2):**\n```r\nggplot(mpg, aes(x = displ, y = hwy, color = class)) +\n geom_point() +\n theme_minimal() +\n labs(title = \"Fuel Efficiency\")\n```\n\n**Python (ggplotly):**\n```python\nggplot(mpg, aes(x='displ', y='hwy', color='class')) + \\\n geom_point() + \\\n theme_minimal() + \\\n labs(title='Fuel Efficiency')\n```\n\nThe main differences:\n\n- Column names are strings: `x='column'` not `x = column`\n- Use `\\` or parentheses for line continuation\n- Import with `from ggplotly import *`"
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]
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}

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