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May 11, 2022
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Minor tweaks #3726

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13 changes: 5 additions & 8 deletions doc/python/axes.md
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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: 3.9.0
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.
Expand Down Expand Up @@ -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.
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in general I don't like listing options in the prose docs, as these lists get stale. It's better to link to the reference if needed


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
Expand All @@ -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")
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when updating a single attribute or two, I try to favour 'magic underscores' like this, to remind folks this exists


fig.show()
```
Expand Down Expand Up @@ -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')
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this line wasn't really doing much for the docs so I dropped it

fig.update_xaxes(gridcolor='black', griddash='dash', minor_griddash="dot")
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the pink was not very attractive, and was hard to see IMO. also, showgrid is on by default in xaxes and gridwidth=1 by default. I try not to explicitly set the defaults in the docs, so folks don't think it's necessary.


fig.show()
```
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6 changes: 3 additions & 3 deletions doc/python/log-plot.md
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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: 3.9.0
version: 3.9.7
plotly:
description: How to make Log plots in Python with Plotly.
display_as: scientific
Expand Down Expand Up @@ -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`.

Expand All @@ -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()
```
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20 changes: 15 additions & 5 deletions doc/python/time-series.md
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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: 3.9.0
version: 3.9.7
plotly:
description: How to plot date and time in python.
display_as: financial
Expand Down Expand Up @@ -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
Expand All @@ -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
Expand All @@ -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",
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this was one huuuuge line that needed breaking up into indented code.

ticklabelmode= "period",
tickcolor= "black",
ticklen=10,
minor=dict(
ticklen=4,
dtick=7*24*60*60*1000,
tick0="2016-07-03",
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I changed this to sundays so that when you zoom in you don't get major ticks on sundays AND minor ticks on mondays ;)

griddash='dot',
gridcolor='white')
)

fig.show()
```
Expand Down