How to plot multiple lines on the same y-axis using Plotly Express in Python

Not sure what type of line your looking for, but have you tried something like below

fig.add_scatter(x=df['Date'], y=df['AAPL.Low'],mode='lines')

On a standard scatter you can set the mode to be any combination of lines, markers and text.

Short answer:

fig = px.line(df, x='Date', y=df.columns[1:-6])

Where df.columns are the column names of the columns returned as a list, or a subset of the columns using, for example, df.columns[1:-6]

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The details

Your code works fine But if you specifically do not want to apply the (somewhat laborious) add_trace() function to each line, you can use px.line(). This used to require you to transform your data from a wide to long format. But not anymore, so just define an index and name the columns you'd like to plot. Or reference all or a subset of your dataframe columns through, for ecxample, y=df.columns[1:-6]

Code 1:

# imports
import plotly.express as px 
import pandas as pd 
import numpy as np 

# data
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')
fig = px.line(df, x='Date', y=df.columns[1:-6])

# Show plot 
fig.show()

Plot:

If you'd like to know how to do the same thing with data of a long format, here's how you do that too using pandas and plotly:

Code 2:

# imports
import plotly.express as px 
import pandas as pd 
import numpy as np 

# data
df_wide = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv')
df_long=pd.melt(df_wide, id_vars=['Date'], value_vars=['AAPL.Open', 'AAPL.High', 'AAPL.Low', 'AAPL.Close', 'mavg'])

# plotly 
fig = px.line(df_long, x='Date', y='value', color='variable')

# Show plot 
fig.show()