python - Extracting columns as vectors from pandas groupby

Question

I created this table using pandas' groupby function and want to extract each column as vector/array
df_duration_means = df.groupby('Duration').mean()

	Interest	Loan amount	LTV
Duration
6	0.107500	274000.000000	0.652500
9	0.112500	510500.000000	0.580000
12	0.105345	276632.758621	0.595517
15	0.080000	81000.000000	0.678000
18	0.109167	516557.666667	0.455867
24	0.101500	374500.000000	0.554800

question from:https://stackoverflow.com/questions/65927748/extracting-columns-as-vectors-from-pandas-groupby

Answer 1

Try .reset_index() first, and then use method .tolist(). Like this:

df_duration_means = df_duration_means.reset_index()
duration = df_duration_means.index.tolist()
interest = df_duration_means['Interest'].tolist()
loan_amount = df_duration_means['Loan amount'].tolist()
ltv = df_duration_means['LTV'].tolist()

And then, use duration, interest, loan_amount, and ltv as an input into plotly

EDIT: There is simpler solution using plotly.express:

import plotly.express as px 
df_duration_means = df_duration_means.reset_index()
fig = px.line(df_duration_means, x=df_duration_means.index, y=['Interest', 'Loan amount', 'LTV'])