tweaks to minor-ticks docs

Author: nicolaskruchten

doc/python/axes.md

@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.9.0
+    version: 3.9.7
   plotly:
     description: How to adjust axes properties in Python - axes titles, styling and
       coloring axes and grid lines, ticks, tick labels and more.
@@ -386,12 +386,10 @@ fig.show()
 
 _new in 5.8_
 
-You can position and style minor ticks on a Cartesian axis using `minor`. This takes a `dict` of properties to apply to minor ticks. Available properties include: `tickmode`, `tickvals`, `tickcolor`, `ticklen`, `tickwidth`, `dtick`, `tick0`, `nticks`, `ticks`, `showgrid`, `gridcolor`, `griddash`, and `gridwidth`.
+You can position and style minor ticks on a Cartesian axis using the `minor` attribute. This takes a `dict` of properties to apply to minor ticks. See the [figure reference](https://plotly.com/python/reference/layout/xaxis/#layout-xaxis-minor) for full details on the accepted keys in this dict.
 
 In the following example, we add minor ticks to the x-axis and then to the y-axis. For the y-axis we add ticks on the inside: `ticks="inside"`. On the x-axis we've specified some additional properties to style the minor ticks, setting the length of the ticks with `ticklen` and the color with `tickcolor`. We've also turned on grid lines for the x-axis minor ticks using `showgrid`.
 
-Note: Minor ticks and grid lines are not currently supported on color bars, ternary plots, polar charts, geo plots, or on multi-categorical, or 3D axes.
-
 ```python
 import plotly.express as px
 import pandas as pd
@@ -401,7 +399,7 @@ fig = px.scatter(df, x="total_bill", y="tip", color="sex")
 
 
 fig.update_xaxes(minor=dict(ticklen=6, tickcolor="black", showgrid=True))
-fig.update_yaxes(minor=dict(ticks="inside"))
+fig.update_yaxes(minor_ticks="inside")
 
 fig.show()
 ```
@@ -492,15 +490,14 @@ fig.show()
 
 _new in 5.8_
 
-By default grid lines are `solid`. Set the `griddash` property to change this style. In this example we display the x-axis grid lines as `dot`. It can also be set to `dash`, `longdash`, `dashdot`, or `longdashdot`.
+By default grid lines are `solid`. Set the `griddash` property to change this style. In this example we display the x-axis grid lines as `dash` and the minor grid lines as `dot`. Other allowable values are `longdash`, `dashdot`, or `longdashdot`.
 
 ```python
 import plotly.express as px
 df = px.data.iris()
 
 fig = px.scatter(df, x="sepal_width", y="sepal_length", facet_col="species")
-fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='LightPink', griddash='dot')
-fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='LightPink')
+fig.update_xaxes(gridcolor='black', griddash='dash', minor_griddash="dot")
 
 fig.show()
 ```

doc/python/log-plot.md

@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.9.0
+    version: 3.9.7
   plotly:
     description: How to make Log plots in Python with Plotly.
     display_as: scientific
@@ -64,7 +64,7 @@ fig.show()
 
 _new in 5.8_
 
-You can position and style minor ticks using `minor`. This takes a `dict` of properties to apply to minor ticks. Available properties include: `tickmode`, `tickvals`, `tickcolor`, `ticklen`, `tickwidth`, `dtick`, `tick0`, `nticks`, `ticks`, `showgrid`, `gridcolor`, `griddash`, and `gridwidth`. 
+You can position and style minor ticks using `minor`. This takes a `dict` of properties to apply to minor ticks. See the [figure reference](https://plotly.com/python/reference/layout/xaxis/#layout-xaxis-minor) for full details on the accepted keys in this dict.
 
 In this example we set the tick length with `ticklen`, add the ticks on the inside with `ticks="inside"`, and turn grid lines on with `howgrid=True`.
 
@@ -75,7 +75,7 @@ df = px.data.gapminder().query("year == 2007")
 fig = px.scatter(df, x="gdpPercap", y="lifeExp", hover_name="country",
                  log_x=True, range_x=[1,100000], range_y=[0,100])
 
-fig.update_xaxes(minor=dict(ticks="inside", ticklen=6, showgrid=True))# {"ticks": "inside", "ticklen": 6, "showgrid": True})
+fig.update_xaxes(minor=dict(ticks="inside", ticklen=6, showgrid=True))
 
 fig.show()
 ```

doc/python/time-series.md

@@ -20,7 +20,7 @@ jupyter:
     name: python
     nbconvert_exporter: python
     pygments_lexer: ipython3
-    version: 3.9.0
+    version: 3.9.7
   plotly:
     description: How to plot date and time in python.
     display_as: financial
@@ -139,9 +139,9 @@ fig.show()
 
 _new in 5.8_
 
-You can add minor ticks to an axis with `minor`. This takes a `dict` of properties to apply to minor ticks. Available properties include: `tickmode`, `tickvals`, `tickcolor`, `ticklen`, `tickwidth`, `dtick`, `tick0`, `nticks`, `ticks`, `showgrid`, `gridcolor`, `griddash`, and `gridwidth`.
+You can add minor ticks to an axis with `minor`. This takes a `dict` of properties to apply to minor ticks. See the [figure reference](https://plotly.com/python/reference/layout/xaxis/#layout-xaxis-minor) for full details on the accepted keys in this dict.
 
-In this example, we've added minor ticks to the inside of the x-axis and turned on grid lines.
+In this example, we've added minor ticks to the inside of the x-axis and turned on minor grid lines.
 
 ```python
 import pandas as pd
@@ -159,7 +159,7 @@ fig.show()
 
 _new in 5.8_
 
-You can set `dtick` on `minor` to control the spacing for minor ticks and grid lines. In the following example, by setting `dtick=7*24*3.6e6` (the number of milliseconds in a week) and setting `tick0="2016-07-04"` (the first Monday in our data), a minor tick and grid line is displayed for the start of each week. When zoomed out, we can see where each month and week begins and ends.
+You can set `dtick` on `minor` to control the spacing for minor ticks and grid lines. In the following example, by setting `dtick=7*24*60*60*1000` (the number of milliseconds in a week) and setting `tick0="2016-07-043"` (the first Sunday in our data), a minor tick and grid line is displayed for the start of each week. When zoomed out, we can see where each month and week begins and ends.
 
 ```python
 import pandas as pd
@@ -169,7 +169,17 @@ df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finan
 df = df.loc[(df["Date"] >= "2016-07-01") & (df["Date"] <= "2016-12-01")]
 
 fig = px.line(df, x='Date', y='AAPL.High')
-fig.update_xaxes(ticks= "outside", ticklabelmode= "period", tickcolor= "black", tickwidth=2, ticklen=10, minor=dict(ticks="outside", dtick=7*24*3.6e6,  tick0="2016-07-04", griddash='dot', gridcolor='pink'))
+fig.update_xaxes(ticks= "outside",
+                 ticklabelmode= "period", 
+                 tickcolor= "black", 
+                 ticklen=10, 
+                 minor=dict(
+                     ticklen=4,  
+                     dtick=7*24*60*60*1000,  
+                     tick0="2016-07-03", 
+                     griddash='dot', 
+                     gridcolor='white')
+                )
 
 fig.show()
 ```