python how to format data for use with seaborn

1# Short answer:
2# You have to make a pandas dataframe with labeled data from all 
3# samples essentially concatenated together in the same columns.
4
5# Example process:
6# Say you're starting with 2 samples with x and y data in lists:
7sample_1_x = [1,2,1,1.6,1.4,3,2,0.9,2.2,2.6,3,2]
8sample_1_y = [2,2,1.5,1.6,1.4,3,2,3,2.2,2.6,3,2]
9sample_2_x = [1,1.7,1,1.6,1.4,3,2,1,2.2,2.6,3,2.1]
10sample_2_y = [2,3,1,1.6,1.7,3,2,0.9,2.3,2.6,2.5,2]
11
12# First, import packages and make sample-specific pandas dataframes:
13import pandas as pd
14import seaborn as sns
15import matplotlib.pyplot as plt
16
17sample_1_df = pd.DataFrame({'x':sample_1_x, 'y':sample_1_y})
18sample_2_df = pd.DataFrame({'x':sample_2_x, 'y':sample_2_y})
19
20# Second, add a column of labels to distinguish data later on:
21sample_1_df['labels'] = 'Sample_1'
22sample_2_df['labels'] = 'Sample_2'
23
24# Concatenate the dataframes together:
25vertical_concat = pd.concat([sample_1_df, sample_2_df], axis=0)
26
27# View final format:
28vertical_concat
29	x	y	labels
300	1.0	2.0	Sample_1
311	2.0	2.0	Sample_1
322	1.0	1.5	Sample_1
33.	.	.	.
34.	.	.	.
35.	.	.	.
360	1.0	2.0	Sample_2
371	1.7	3.0	Sample_2
382	1.0	1.0	Sample_2
39
40# Make plots in which samples are distinguished by their labels:
41sns.scatterplot(data=vertical_concat, x='x', y='y', hue='labels')