How to apply a linestyle to a specific line in Seaborn lineplot?

Question

I have the a dataframe where in the column Products there are many different items, let's show only a few:

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

data = np.array([[1, 1, 570], [2, 1, 650], [1, 2, 27], [2, 2, 64], [1, 3, 125], [2, 3, 216],  
                  [1, 'item_1', 343], [2, 'item_1', 340], [1, 'item_2', 343], [2, 'item_2', 345]])
df = pd.DataFrame(data=data, columns=["Flag", "Products", "Value"])

I'm using Seaborn to get the following lineplot:

sns.set_theme()
sns.set_style("ticks")
sns.set_context("paper")

fig1, ax1 = plt.subplots()
sns.lineplot(data=df, x="Flag", y="Value", 
             hue="Products", style="Products", ax=ax1)
plt.legend(bbox_to_anchor=(1.02, 1),borderaxespad=0)
fig1.tight_layout()

In this way all the lines have a style "chosen" by Seaborn, but I need to set a specific color and a line style (not dashed) for the products named 'item_1' and 'item_2'. Up to now I have found the following solution:

palette = {c:'red' if c=='item_1' else 'blue' for c in df.Products.unique()}
sns.lineplot(data=df, x="Flag", y="Value", 
             hue="Products", style="Products", palette=palette, ax=ax1)

So, I can set the red color for the item_1 only, but all the other lines are blue, while I'd like to:

• set the red color and not-dashed lines for both items_1 and items_2
• set another color palette (e.g. bright) for all the other lines

Is it possible to do that?

Answer 1

palette= and dashes= can be passed a dictionary mapping levels of the column used to different colors/styles.

You can generate these dictionaries by hand or programmatically (depending on how many levels you have).

for instance, the color palette:

#color palette
cmap = sns.color_palette("bright")
palette = {key:value for key,value in zip(data[hue_col].unique(), cmap)}
palette['item_1'] = 'red'
palette['item_2'] = 'red'

output:

{'1': (0.00784313725490196, 0.24313725490196078, 1.0),
'2': (1.0, 0.48627450980392156, 0.0),
'3': (0.10196078431372549, 0.788235294117647, 0.2196078431372549),
'item_1': 'red,
'item_2': 'red'}

we give each level a different color from the "bright" palette, and we can fix some values by hand if needed (although do keep in mind that there is a color very similar to red in the bright palette already, so there might be some possible confusion).

The same can be done for the dash style:

#style palette
dash_list = sns._core.unique_dashes(data[style_col].unique().size+1)
style = {key:value for key,value in zip(data[style_col].unique(), dash_list[1:])}
style['item_1'] = ''  # empty string means solid
style['item_2'] = ''

output:

{'1': (4, 1.5),
'2': (1, 1),
'3': (3, 1.25, 1.5, 1.25),
'item_1': '',
'item_2': ''}

Here I use one of seaborn's private functions (use at your own risk, could change at any time), to generate a list of dash styles, and then manually set the particular levels I want to have a solid line. I request one too many items in dash_list because the first element is always a solid line, and I want to reserve solid lines for item_1 and item_2.

full code:

data = df
x_col = 'Flag'
y_col = "Value"
hue_col = "Products"
style_col = "Products"

#color palette
cmap = sns.color_palette("bright")
palette = {key:value for key,value in zip(data[hue_col].unique(), cmap)}
palette['item_1'] = 'red'
palette['item_2'] = 'red'


#style palette
dash_list = sns._core.unique_dashes(data[style_col].unique().size+1)
style = {key:value for key,value in zip(data[style_col].unique(), dash_list[1:])}
style['item_1'] = ''  # empty string means solid
style['item_2'] = ''

sns.set_theme()
sns.set_style("ticks")
sns.set_context("paper")

fig1, ax1 = plt.subplots()
sns.lineplot(data=df, x=x_col, y=y_col, 
             hue=hue_col, palette=palette,
             style=style_col, dashes=style,
             ax=ax1)
plt.legend(bbox_to_anchor=(1.02, 1),borderaxespad=0)
fig1.tight_layout()