# Segmented Line

This type of chart provides a detailed visualization of data points categorized by varying segments on the y-axis. Each segment is delineated by a unique color, making it straightforward to distinguish between different data ranges or categories within the continuous line. The segmented line chart is especially beneficial when aiming to emphasize specific ranges or values in your data on the y-axis, facilitating rapid analysis of trends within those segments.

## The Method To Use <a href="#the-method-to-use.1" id="the-method-to-use.1"></a>

The method is `s.plt.segmented_line()`.

It must contain the following input variables:

```python
order: int, 
x: str, 
y: Union[str, List[str]],
data: Optional[Union[str, DataFrame, List[Dict]]],
```

Accepts the following input variables as optional:

```python
x_axis_name: Optional[str] = None, 
y_axis_name: Optional[str] = None,
rows_size: Optional[int] = None, 
cols_size: Optional[int] = None,
padding: Optional[List[int]] = None, 
title: Optional[str] = None,
marking_lines: Optional[List[int]] = None, # marks to separate the segments in y axis
range_colors: Optional[List[str]] = None,  # colors for each axis
option_modifications: Optional[Dict] = None,
variant: Optional[str] = None
```

## Examples <a href="#examples" id="examples"></a>

Both examples use this data set:

```python
beiging_aqi_len = 100
beiging_aqi = requests.get(
    url='https://echarts.apache.org/examples/'
        'data/asset/data/aqi-beijing.json').json()[-beiging_aqi_len:]
df = pd.DataFrame([
    {
        'date': beiging_aqi[i][0],
        'y': beiging_aqi[i][1],
        'y_displaced': beiging_aqi[(i + 10) % beiging_aqi_len][1],
        'y_multiplied': beiging_aqi[i][1] * 2,
    } for i in range(beiging_aqi_len)
])
```

The first example shows how to use the parameters `marking_lines` and `range_colors`:

<pre class="language-python"><code class="lang-python">s.plt.segmented_line(
    data=df, order=0, 
    x='date', y='y', 
    title="Beijing's Air Quality Index",
<strong>    marking_lines=[0, 50, 100, 150, 200, 300], 
</strong><strong>    range_colors=['green', 'yellow', 'orange', 'red', 'purple', 'maroon'],
</strong>    x_axis_name='Date', y_axis_name='AQI'
)
</code></pre>

<figure><img src="/files/6G7FTF8iW614Qdkk4yef" alt=""><figcaption><p>AQI Beijing, gotten from the echarts example</p></figcaption></figure>

The second example shows how the segments behave with multiple series, and the default configuration of colors:

```python
s.plt.segmented_line(
    data=df, order=0,
    x='date', y=['y', 'y_displaced', 'y_multiplied'],
    marking_lines=[0, 100, 200, 300, 450, 700]
)
```

<figure><img src="/files/iuMazpRwLqAqpjf5OaSG" alt=""><figcaption></figcaption></figure>

## Variants

By setting the parameter `variant` to the following values the appearance of the chart can be changed:

{% tabs %}
{% tab title="Clean" %}

<figure><img src="/files/JngIurCFAbsO6RxAtyNn" alt=""><figcaption><p>variant="clean"</p></figcaption></figure>
{% endtab %}

{% tab title="Minimal" %}

<figure><img src="/files/WbR54S1VKbH7XfRHjfRd" alt=""><figcaption><p>variant="minimal"</p></figcaption></figure>
{% endtab %}
{% endtabs %}

##


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