Ploty, single multicolored line

I have a data frame with a date and two columns.

This is not the real data. The plot is actually working better here than with my real data. In my real data, the 3 lines are continuous, over here at least two additional lines are broken.

How to get one line that changes color instead of three separate lines?

The data looks like this:

c1 shows when p1 is rising or falling. I want to plot p1 colored by c1. I don't want multiple lines.

import pandas as pd
import plotly.express as px

import pandas as pd

data = {
  "date": ['2021/01/07', '2021/01/08', '2021/01/11', '2021/01/12','2021/01/13','2021/01/14','2021/01/15'],
  "p1": [2, 4, 6, 6,4, 2,2],
  "c1":[0,1,1,0,-1,-1,0]}
df = pd.DataFrame(data)

df['date1'] = pd.to_datetime(df['date'])


fig=px.line(df, x='date1',y='p1',color='c1')
#fig=px.line(df, x='Date',y='t1')
#fig=px.line(df, x='date1',y='p1',facet_col='c1')
fig.show()

Plotly doesn't support this functionality natively but you can plot separate lines for each unique 'c1' value and then join them together, for example:

import pandas as pd
import plotly.graph_objects as go

data = {
    "date": ['2021/01/07', '2021/01/08', '2021/01/11', '2021/01/12','2021/01/13','2021/01/14','2021/01/15'],
    "p1": [2, 4, 6, 6, 4, 2, 2],
    "c1":[0, 1, 1, 0, -1, -1, 0]
}
df = pd.DataFrame(data)

df['date'] = pd.to_datetime(df['date'])

colors = {0: 'blue', 1: 'green', -1: 'red'} 

fig = go.Figure()

for c1_val in df['c1'].unique():
    df_sub = df[df['c1'] == c1_val]
    fig.add_trace(go.Scatter(x=df_sub['date'], y=df_sub['p1'], mode='lines', line=dict(color=colors[c1_val])))

fig.show()

I hope this helps.