I am trying to plot a multi line plot using sns but only keeping the US line in red while the other countries are in grey
This is what I have so far:
df = px.data.gapminder()
sns.lineplot(x = 'year', y = 'pop', data = df, hue = 'country', color = 'grey', dashes = False, legend = False)
But this does not change the lines to grey. I was thinking that after this, I could add in US line by itself in red.....
You can use pandas groupby to plot:
fig,ax=plt.subplots()
for c,d in df.groupby('country'):
color = 'red' if c=='US' else 'grey'
d.plot(x='year',y='pop', ax=ax, color=color)
ax.legend().remove()
output:
Or you can define a specific palette as a dictionary:
palette = {c:'red' if c=='US' else 'grey' for c in df.country.unique()}
sns.lineplot(x='year', y='pop', data=df, hue='country',
palette=palette, legend=False)
Output:
You can use the palette parameter to pass custom colors for the lines to sns.lineplot, for example:
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = pd.DataFrame({'year': [2018, 2019, 2020, 2018, 2019, 2020, 2018, 2019, 2020, ],
'pop': [325, 328, 332, 125, 127, 132, 36, 37, 38],
'country': ['USA', 'USA', 'USA', 'Mexico', 'Mexico', 'Mexico',
'Canada', 'Canada', 'Canada']})
colors = ['red', 'grey', 'grey']
sns.lineplot(x='year', y='pop', data=df, hue='country',
palette=colors, legend=False)
plt.ylim(0, 350)
plt.xticks([2018, 2019, 2020]);
It could still be useful to have a legend though, so you may also want to consider tinkering with the alpha values (the last values in the tuples below) to highlight the USA.
red = (1, 0, 0, 1)
green = (0, 0.5, 0, 0.2)
blue = (0, 0, 1, 0.2)
colors = [red, green, blue]
sns.lineplot(x='year', y='pop', data=df, hue='country',
palette=colors)
plt.ylim(0, 350)
plt.xticks([2018, 2019, 2020]);
