问题

如何在plotly中获得一条单一连接线，并使用不同的颜色？

下面的图表显示了解决方案的尝试。然而，线在点10和点90之间有一个不美观的中断。如何根据分类变量拥有单一线并使用多种颜色，而不会中断？

import numpy as np
import random
import pandas as pd
import plotly.express as px

white_noise = np.array([random.gauss(mu=0.0, sigma=1.0) for x in range(100)])
rw = white_noise.cumsum()
rw_df = pd.DataFrame({
    'random_walk': rw, 
    'color': 10*['black'] + 50 * ['blue'] + 40*['black'], 
    'x': range(100)
})

fig = px.line(rw_df, x='x', y='random_walk', color='color')
fig.show()

[![enter image description here][1]][1]

  [1]: https://i.stack.imgur.com/eelrG.png

<details>
<summary>英文:</summary>

How can I get a single connected line in `plotly` with different colors?

The plot below shows an attempt at a solution.  However, the line has an ugly break between point 10 and point 90.  How can I have a single line with multiple colors according to a categorical variable without breaking?[![enter image description here][1]][1]

import numpy as np
import random
import pandas as pd
import plotly.express as px

white_noise = np.array([random.gauss(mu=0.0, sigma=1.0) for x in range(100)])
rw = white_noise.cumsum()
rw_df = pd.DataFrame({
'random_walk': rw,
'color': 10*['black'] + 50 * ['blue'] + 40*['black'],
'x': range(100)
})```

fig = px.line(rw_df, x='x', y='random_walk', color='color')
fig.show()

  [1]: https://i.stack.imgur.com/eelrG.png

</details>


# 答案1
**得分**: 1

以下是您要翻译的代码部分：

```python
import numpy as np
import random
import pandas as pd
import plotly.express as px

white_noise = np.array([random.gauss(mu=0.0, sigma=1.0) for x in range(100)])
rw = white_noise.cumsum()
rw_df = pd.DataFrame({
    'random_walk': rw, 
    'color': 10*['black'] + 50 * ['blue'] + 40*['black'], 
    'x': range(100)
})

## 将数据框拆分为一组颜色相同的数据框
rw_df['group']=rw_df['color'].ne(rw_df['color'].shift()).cumsum()
rw_df
rw_df = rw_df.groupby('group')
dfs = []
for name, data in rw_df:
    dfs.append(data)

## 绘制第一条线 - dfs[0]    
fig = px.line(dfs[0], x='x', y='random_walk')
fig.update_traces(line_color=dfs[0]['color'].iloc[0])

## 对于数组中的其他线条，绘制新的线条
for i in range(1, len(dfs)):
    fig.add_scatter(x=dfs[i]["x"], y=dfs[i]["random_walk"], 
                    line_color=dfs[i]['color'].iloc[0], 
                    name=dfs[i]['color'].iloc[0])
    
fig.show()

import numpy as np
import random
import pandas as pd
import plotly.express as px

white_noise = np.array([random.gauss(mu=0.0, sigma=1.0) for x in range(100)])
rw = white_noise.cumsum()
rw_df = pd.DataFrame({
    'random_walk': rw, 
    'color': 10*['black'] + 50 * ['blue'] + 40*['black'], 
    'x': range(100)
})

## Break your dataframe into an array of smaller dataframes, each with single color
rw_df['group']=rw_df['color'].ne(rw_df['color'].shift()).cumsum()
rw_df
rw_df = rw_df.groupby('group')
dfs = []
for name, data in rw_df:
    dfs.append(data)

## Plot the first line - dfs[0]    
fig = px.line(dfs[0], x='x', y='random_walk')
fig.update_traces(line_color=dfs[0]['color'].iloc[0])

## For other lines in array, plot new line
for i in range(1, len(dfs)):
    fig.add_scatter(x=dfs[i]["x"], y=dfs[i]["random_walk"], 
                    line_color=dfs[i]['color'].iloc[0], 
                    name=dfs[i]['color'].iloc[0])
    
fig.show()