Plot all columns from dataframe without having to define them in Plotly - plot

Question

I would like to plot in Plotly all columns from dataframe without having to define them.
The required is the same functionality in Plotly as here in matplotlib.
import glob
import pandas as pd
df = pd.DataFrame({
'A': ['15','21','30'],
'M': ['12','24','31'],
'I': ['28','32','10']})
%matplotlib inline
from matplotlib import pyplot as plt
df=df.astype(float)
df.plot()
Here is my code for Plotly, but as I said, I have no idea how to plot all the columns automatically. The once I have noticed is also, that in Plotly the X-axis needs to be defined, but with this restriction I can live.
import plotly.express as px
import pandas as pd
import numpy as np
import os
# data
df = pd.DataFrame({
'ID': ['1','2','3'],
'A': ['15','21','30'],
'M': ['12','24','31'],
'I': ['28','32','10']})
df_long=pd.melt(df , id_vars=['ID'], value_vars=['A', 'M' , 'I'])
fig = px.line(df_long, x='ID', y='value', color='variable')
fig.show()
How can I define how to plot in Plotly all the columns automatically?

Answer 1

Okay, i have found the solution to my problem:
df_long=pd.melt(df , id_vars=['ID'])
instead of:
df_long=pd.melt(df , id_vars=['ID'], value_vars=['A', 'M' , 'I'])
Column(s) to unpivot. If not specified, uses all columns that are not set as id_vars.