Rename package and accessor.py

Author: FBumann

README.md

@@ -1,22 +1,22 @@
-# xarray-plotly
+# xarray_plotly
 
 **Interactive Plotly Express plotting accessor for xarray**
 
-[![PyPI version](https://badge.fury.io/py/xarray-plotly.svg)](https://badge.fury.io/py/xarray-plotly)
-[![Python](https://img.shields.io/pypi/pyversions/xarray-plotly.svg)](https://pypi.org/project/xarray-plotly/)
+[![PyPI version](https://badge.fury.io/py/xarray_plotly.svg)](https://badge.fury.io/py/xarray_plotly)
+[![Python](https://img.shields.io/pypi/pyversions/xarray_plotly.svg)](https://pypi.org/project/xarray_plotly/)
 
-xarray-plotly provides a `pxplot` accessor for xarray DataArray objects that enables interactive plotting using Plotly Express with automatic dimension-to-slot assignment.
+xarray_plotly provides a `plotly` accessor for xarray DataArray objects that enables interactive plotting using Plotly Express with automatic dimension-to-slot assignment.
 
 ## Installation
 
 ```bash
-pip install xarray-plotly
+pip install xarray_plotly
 ```
 
 Or with uv:
 
 ```bash
-uv add xarray-plotly
+uv add xarray_plotly
 ```
 
 ## Quick Start
@@ -40,7 +40,7 @@ da = xr.DataArray(
 
 # Create an interactive line plot
 # Dimensions auto-assign: time→x, city→color, scenario→facet_col
-fig = da.pxplot.line()
+fig = da.plotly.line()
 fig.show()
 
 # Easy customization
@@ -62,13 +62,13 @@ Dimensions are automatically assigned to plot "slots" based on their order:
 ```python
 # dims: (time, city, scenario)
 # auto-assigns: time→x, city→color, scenario→facet_col
-da.pxplot.line()
+da.plotly.line()
 
 # Override with explicit assignments
-da.pxplot.line(x="time", color="scenario", facet_col="city")
+da.plotly.line(x="time", color="scenario", facet_col="city")
 
 # Skip a slot with None
-da.pxplot.line(color=None)  # time→x, city→facet_col
+da.plotly.line(color=None)  # time→x, city→facet_col
 ```
 
 ## Available Methods
@@ -84,7 +84,7 @@ da.pxplot.line(color=None)  # time→x, city→facet_col
 
 ## Documentation
 
-Full documentation with examples: [https://felix.github.io/xarray-plotly](https://felix.github.io/xarray-plotly)
+Full documentation with examples: [https://felix.github.io/xarray_plotly](https://felix.github.io/xarray_plotly)
 
 ## License
 

docs/examples/advanced.ipynb

@@ -28,7 +28,7 @@
    "source": [
     "## Working with xarray Attributes\n",
     "\n",
-    "xarray-plotly automatically uses metadata from xarray attributes for labels:"
+    "xarray_plotly automatically uses metadata from xarray attributes for labels:"
    ]
   },
   {
@@ -57,7 +57,7 @@
     "da.coords[\"station\"].attrs = {\"long_name\": \"Measurement Station\"}\n",
     "\n",
     "# Labels are automatically extracted from attrs\n",
-    "fig = da.pxplot.line(title=\"Temperature with Auto-Labels\")\n",
+    "fig = da.plotly.line(title=\"Temperature with Auto-Labels\")\n",
     "fig"
    ]
   },
@@ -76,7 +76,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = da.pxplot.line(\n",
+    "fig = da.plotly.line(\n",
     "    labels={\n",
     "        \"temperature\": \"Temp (°C)\",\n",
     "        \"time\": \"Date\",\n",
@@ -117,7 +117,7 @@
     ")\n",
     "\n",
     "# Use line_dash for one dimension, color for another\n",
-    "fig = da_complex.sel(city=\"NYC\").pxplot.line(\n",
+    "fig = da_complex.sel(city=\"NYC\").plotly.line(\n",
     "    color=\"scenario\",\n",
     "    line_dash=\"model\",\n",
     "    title=\"Multiple Visual Encodings\",\n",
@@ -141,7 +141,7 @@
    "outputs": [],
    "source": [
     "# Average over model dimension\n",
-    "fig = da_complex.mean(\"model\").pxplot.line(\n",
+    "fig = da_complex.mean(\"model\").plotly.line(\n",
     "    facet_col=\"city\",\n",
     "    title=\"Ensemble Mean by City\",\n",
     ")\n",
@@ -155,7 +155,7 @@
    "outputs": [],
    "source": [
     "# Select a specific slice\n",
-    "fig = da_complex.sel(scenario=\"SSP5\", model=\"GCM-A\").pxplot.line(\n",
+    "fig = da_complex.sel(scenario=\"SSP5\", model=\"GCM-A\").plotly.line(\n",
     "    facet_col=\"city\",\n",
     "    title=\"SSP5 / GCM-A Projections\",\n",
     ")\n",
@@ -184,7 +184,7 @@
    "source": [
     "da_simple = da.sel(station=\"Urban\")\n",
     "\n",
-    "fig = da_simple.pxplot.line(\n",
+    "fig = da_simple.plotly.line(\n",
     "    template=\"plotly_dark\",\n",
     "    title=\"Dark Theme\",\n",
     ")\n",
@@ -206,7 +206,7 @@
    "source": [
     "import plotly.express as px\n",
     "\n",
-    "fig = da.pxplot.line(\n",
+    "fig = da.plotly.line(\n",
     "    color_discrete_sequence=px.colors.qualitative.Set2,\n",
     "    title=\"Custom Color Palette\",\n",
     ")\n",
@@ -233,7 +233,7 @@
     ")\n",
     "\n",
     "# Diverging colorscale centered at zero\n",
-    "fig = da_2d.pxplot.imshow(\n",
+    "fig = da_2d.plotly.imshow(\n",
     "    color_continuous_scale=\"RdBu_r\",\n",
     "    color_continuous_midpoint=0,\n",
     "    title=\"Diverging Colorscale\",\n",
@@ -256,7 +256,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = da.pxplot.line()\n",
+    "fig = da.plotly.line()\n",
     "\n",
     "# Add horizontal reference line\n",
     "fig.add_hline(y=15, line_dash=\"dash\", line_color=\"gray\", annotation_text=\"Reference\")\n",
@@ -289,7 +289,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = da.pxplot.line()\n",
+    "fig = da.plotly.line()\n",
     "\n",
     "# Make all lines thicker\n",
     "fig.update_traces(line_width=3)\n",
@@ -349,7 +349,7 @@
     "# Rolling mean\n",
     "da_smooth = da.rolling(time=7, center=True).mean()\n",
     "\n",
-    "fig = da_smooth.pxplot.line(\n",
+    "fig = da_smooth.plotly.line(\n",
     "    title=\"7-Day Rolling Mean\",\n",
     ")\n",
     "fig"
@@ -374,7 +374,7 @@
     "\n",
     "monthly_mean = da_monthly.groupby(\"time.month\").mean()\n",
     "\n",
-    "fig = monthly_mean.pxplot.line(\n",
+    "fig = monthly_mean.plotly.line(\n",
     "    title=\"Monthly Climatology\",\n",
     ")\n",
     "fig.update_xaxes(tickmode=\"array\", tickvals=list(range(1, 13)), \n",

docs/examples/plot-types.ipynb

@@ -6,7 +6,7 @@
    "source": [
     "# Plot Types\n",
     "\n",
-    "This notebook demonstrates all the plot types available in xarray-plotly."
+    "This notebook demonstrates all the plot types available in xarray_plotly."
    ]
   },
   {
@@ -88,7 +88,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = da_ts.pxplot.line(title=\"Line Plot\")\n",
+    "fig = da_ts.plotly.line(title=\"Line Plot\")\n",
     "fig"
    ]
   },
@@ -105,7 +105,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = da_ts.pxplot.line(markers=True, title=\"Line Plot with Markers\")\n",
+    "fig = da_ts.plotly.line(markers=True, title=\"Line Plot with Markers\")\n",
     "fig"
    ]
   },
@@ -124,7 +124,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = da_cat.pxplot.bar(title=\"Stacked Bar Chart\")\n",
+    "fig = da_cat.plotly.bar(title=\"Stacked Bar Chart\")\n",
     "fig"
    ]
   },
@@ -141,7 +141,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = da_cat.pxplot.bar(barmode=\"group\", title=\"Grouped Bar Chart\")\n",
+    "fig = da_cat.plotly.bar(barmode=\"group\", title=\"Grouped Bar Chart\")\n",
     "fig"
    ]
   },
@@ -171,7 +171,7 @@
     "    name=\"energy\",\n",
     ")\n",
     "\n",
-    "fig = da_positive.pxplot.area(title=\"Stacked Area Chart\")\n",
+    "fig = da_positive.plotly.area(title=\"Stacked Area Chart\")\n",
     "fig"
    ]
   },
@@ -190,7 +190,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = da_ts.pxplot.scatter(title=\"Scatter Plot\")\n",
+    "fig = da_ts.plotly.scatter(title=\"Scatter Plot\")\n",
     "fig"
    ]
   },
@@ -209,7 +209,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = da_2d.pxplot.scatter(x=\"lon\", y=\"lat\", color=\"value\", title=\"Lat/Lon Scatter\")\n",
+    "fig = da_2d.plotly.scatter(x=\"lon\", y=\"lat\", color=\"value\", title=\"Lat/Lon Scatter\")\n",
     "fig"
    ]
   },
@@ -236,7 +236,7 @@
     "    name=\"response\",\n",
     ")\n",
     "\n",
-    "fig = da_dist.pxplot.box(title=\"Box Plot\")\n",
+    "fig = da_dist.plotly.box(title=\"Box Plot\")\n",
     "fig"
    ]
   },
@@ -255,7 +255,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = da_2d.pxplot.imshow(title=\"Heatmap\")\n",
+    "fig = da_2d.plotly.imshow(title=\"Heatmap\")\n",
     "fig"
    ]
   },
@@ -272,7 +272,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = da_2d.pxplot.imshow(\n",
+    "fig = da_2d.plotly.imshow(\n",
     "    color_continuous_scale=\"Viridis\",\n",
     "    title=\"Heatmap with Viridis colorscale\",\n",
     ")\n",
@@ -306,7 +306,7 @@
     "    name=\"value\",\n",
     ")\n",
     "\n",
-    "fig = da_3d.pxplot.line(\n",
+    "fig = da_3d.plotly.line(\n",
     "    facet_col=\"city\",\n",
     "    facet_row=\"scenario\",\n",
     "    title=\"Faceted Line Plot\",\n",
@@ -341,7 +341,7 @@
     "    name=\"sales\",\n",
     ")\n",
     "\n",
-    "fig = da_monthly.pxplot.bar(\n",
+    "fig = da_monthly.plotly.bar(\n",
     "    x=\"product\",\n",
     "    animation_frame=\"month\",\n",
     "    title=\"Monthly Sales (Animated)\",\n",