Nov 12, 2019 · Nov 4, 2019 · Nov 12, 2019
diff --git a/python/facet-plots.md b/python/facet-plots.md
    name: python
    nbconvert_exporter: python
    pygments_lexer: ipython3
    version: 3.6.7
    version: 3.6.8
  plotly:
    description: How to make Facet and Trellis Plots in Python with Plotly.
    display_as: statistical
 fig.show()
 ```

 ### Wrapping Column Facets

 When the facet dimension has a large number of unique values, it is possible to wrap columns using the `facet_col_wrap` argument.

 ```python
 import plotly.express as px
 df = px.data.gapminder()
 fig = px.scatter(df, x='gdpPercap', y='lifeExp', color='continent', size='pop',
                facet_col='year', facet_col_wrap=4)
 fig.show()
 ```

 ### Histogram Facet Grids

 ```python
       category_orders={"day": ["Thur", "Fri", "Sat", "Sun"], "time": ["Lunch", "Dinner"]})
 fig.show()
 ```

 ### Facets with independent axes

 By default, facet axes are linked together: zooming inside one of the facets will also zoom in the other facets. You can disable this behaviour when you use `facet_row` only, by disabling `matches` on the Y axes, or when using `facet_col` only, by disabling `matches` on the X axes. It is not recommended to use this approach when using `facet_row` and `facet_col` together, as in this case it becomes very hard to understand the labelling of axes and grid lines.

 ```python
 import plotly.express as px
 df = px.data.tips()
 fig = px.scatter(df, x="total_bill", y="tip", color='sex', facet_row="day")
 fig.update_yaxes(matches=None)
 fig.show()
 ```

 ```python
 import plotly.express as px
 df = px.data.tips()
 fig = px.scatter(df, x="total_bill", y="tip", color='sex', facet_col="day")
 fig.update_xaxes(matches=None)
 fig.show()
 ```

 ```python

 ```
Original file line number	Diff line number	Diff line change
Expand Up		@@ -20,7 +20,7 @@ jupyter:
		name: python
		nbconvert_exporter: python
		pygments_lexer: ipython3
		version: 3.6.7
		version: 3.6.8
		plotly:
		description: How to make Facet and Trellis Plots in Python with Plotly.
		display_as: statistical
Expand DownExpand Up		@@ -58,6 +58,18 @@ fig = px.bar(tips, x="size", y="total_bill", color="sex", facet_row="smoker")
		fig.show()
		```

		### Wrapping Column Facets

		When the facet dimension has a large number of unique values, it is possible to wrap columns using the `facet_col_wrap` argument.

		```python
		import plotly.express as px
		df = px.data.gapminder()
		fig = px.scatter(df, x='gdpPercap', y='lifeExp', color='continent', size='pop',
		facet_col='year', facet_col_wrap=4)
		fig.show()
		```

		### Histogram Facet Grids

		```python
Expand All		@@ -67,3 +79,27 @@ fig = px.histogram(tips, x="total_bill", y="tip", color="sex", facet_row="time",
		category_orders={"day": ["Thur", "Fri", "Sat", "Sun"], "time": ["Lunch", "Dinner"]})
		fig.show()
		```

		### Facets with independent axes

		By default, facet axes are linked together: zooming inside one of the facets will also zoom in the other facets. You can disable this behaviour when you use `facet_row` only, by disabling `matches` on the Y axes, or when using `facet_col` only, by disabling `matches` on the X axes. It is not recommended to use this approach when using `facet_row` and `facet_col` together, as in this case it becomes very hard to understand the labelling of axes and grid lines.

		```python
		import plotly.express as px
		df = px.data.tips()
		fig = px.scatter(df, x="total_bill", y="tip", color='sex', facet_row="day")
		fig.update_yaxes(matches=None)
		fig.show()
		```

		```python
		import plotly.express as px
		df = px.data.tips()
		fig = px.scatter(df, x="total_bill", y="tip", color='sex', facet_col="day")
		fig.update_xaxes(matches=None)
		fig.show()
		```

		```python

		```