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    description: How to style markers in Python with Plotly.
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    name: Styling Markers
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---

### Add Marker Border

In order to make markers look more distinct, you can add a border to the markers. This can be achieved by adding the line property to the marker object.

Here is an example of adding a marker border to a faceted scatter plot created using Plotly Express.

```python
import plotly.express as px

iris = px.data.iris()
fig = px.scatter(iris, x="sepal_width", y="sepal_length", color="species")

fig.update_traces(marker=dict(size=12,
                              line=dict(width=2,
                                        color='DarkSlateGrey')),
                  selector=dict(mode='markers'))
fig.show()
```

Here is an example that creates an empty graph object figure, and then adds two scatter traces with a marker border.

```python
import plotly.graph_objects as go

# Generate example data
import numpy as np
np.random.seed(1)

x = np.random.uniform(low=3, high=6, size=(500,))
y = np.random.uniform(low=3, high=6, size=(500,))

# Build figure
fig = go.Figure()

# Add scatter trace with medium sized markers
fig.add_trace(
    go.Scatter(
        mode='markers',
        x=x,
        y=y,
        marker=dict(
            color='LightSkyBlue',
            size=20,
            line=dict(
                color='MediumPurple',
                width=2
            )
        ),
        showlegend=False
    )
)

# Add trace with large marker
fig.add_trace(
    go.Scatter(
        mode='markers',
        x=[2],
        y=[4.5],
        marker=dict(
            color='LightSkyBlue',
            size=120,
            line=dict(
                color='MediumPurple',
                width=12
            )
        ),
        showlegend=False
    )
)

fig.show()
```

Fully opaque, the default setting, is useful for non-overlapping markers. When many points overlap it can be hard to observe density.


### Opacity


Setting opacity outside the marker will set the opacity of the trace. Thus, it will allow greater visbility of additional traces but like fully opaque it is hard to distinguish density.

```python
import plotly.graph_objects as go

# Generate example data
import numpy as np

x = np.random.uniform(low=3, high=6, size=(500,))
y = np.random.uniform(low=3, high=4.5, size=(500,))
x2 = np.random.uniform(low=3, high=6, size=(500,))
y2 = np.random.uniform(low=4.5, high=6, size=(500,))

# Build figure
fig = go.Figure()

# Add first scatter trace with medium sized markers
fig.add_trace(
    go.Scatter(
        mode='markers',
        x=x,
        y=y,
        opacity=0.5,
        marker=dict(
            color='LightSkyBlue',
            size=20,
            line=dict(
                color='MediumPurple',
                width=2
            )
        ),
        name='Opacity 0.5'
    )
)

# Add second scatter trace with medium sized markers
# and opacity 1.0
fig.add_trace(
    go.Scatter(
        mode='markers',
        x=x2,
        y=y2,
        marker=dict(
            color='LightSkyBlue',
            size=20,
            line=dict(
                color='MediumPurple',
                width=2
            )
        ),
        name='Opacity 1.0'
    )
)

# Add trace with large markers
fig.add_trace(
    go.Scatter(
        mode='markers',
        x=[2, 2],
        y=[4.25, 4.75],
        opacity=0.5,
        marker=dict(
            color='LightSkyBlue',
            size=80,
            line=dict(
                color='MediumPurple',
                width=8
            )
        ),
        showlegend=False
    )
)

fig.show()

```

### Marker Opacity


To maximise visibility of density, it is recommended to set the opacity inside the marker `marker:{opacity:0.5}`. If mulitple traces exist with high density, consider using marker opacity in conjunction with trace opacity.

```python
import plotly.graph_objects as go

# Generate example data
import numpy as np

x = np.random.uniform(low=3, high=6, size=(500,))
y = np.random.uniform(low=3, high=6, size=(500,))

# Build figure
fig = go.Figure()

# Add scatter trace with medium sized markers
fig.add_trace(
    go.Scatter(
        mode='markers',
        x=x,
        y=y,
        marker=dict(
            color='LightSkyBlue',
            size=20,
            opacity=0.5,
            line=dict(
                color='MediumPurple',
                width=2
            )
        ),
        showlegend=False
    )
)


# Add trace with large markers
fig.add_trace(
    go.Scatter(
        mode='markers',
        x=[2, 2],
        y=[4.25, 4.75],
        marker=dict(
            color='LightSkyBlue',
            size=80,
            opacity=0.5,
            line=dict(
                color='MediumPurple',
                width=8
            )
        ),
        showlegend=False
    )
)

fig.show()

```

### Color Opacity


To maximise visibility of each point, set the color as an `rgba` string that includes an alpha value of 0.5.

This example sets the marker color to `'rgba(135, 206, 250, 0.5)'`. The rgb values of 135, 206, and 250 are from the definition of the `LightSkyBlue` named CSS color that is is used in the previous examples (See https://www.color-hex.com/color/87cefa). The marker line will remain opaque.

```python
import plotly.graph_objects as go

# Generate example data
import numpy as np

x = np.random.uniform(low=3, high=6, size=(500,))
y = np.random.uniform(low=3, high=6, size=(500,))


# Build figure
fig = go.Figure()

# Add scatter trace with medium sized markers
fig.add_trace(
    go.Scatter(
        mode='markers',
        x=x,
        y=y,
        marker=dict(
            color='rgba(135, 206, 250, 0.5)',
            size=20,
            line=dict(
                color='MediumPurple',
                width=2
            )
        ),
        showlegend=False
    )
)


# Add trace with large markers
fig.add_trace(
    go.Scatter(
        mode='markers',
        x=[2, 2],
        y=[4.25, 4.75],
        marker=dict(
            color='rgba(135, 206, 250, 0.5)',
            size=80,
            line=dict(
                color='MediumPurple',
                width=8
            )
        ),
        showlegend=False
    )
)

fig.show()

```

### Reference
See https://plot.ly/python/reference/ for more information and chart attribute options!