How to plot data from multiple dataframes with seaborn relplot

Question

I want to plot two lines on the same set of axes. It seems sns.relplot is creating a facetted figure, and I don't know how to specify that I want the second line on the same facet as the first.

Here's a MWE

import numpy as np
import pandas as pd
import seaborn as sns

x = np.random.uniform(low = 1, high = 10, size = 20)

df1 = pd.DataFrame({'x': x, 'y1': 2 * x, 'type': 'a'})
df2 = pd.DataFrame({'x': x, 'y2': 3 * x, 'type': 'b'})

sns.relplot(data = df1, x = 'x', y = 'y1', kind = 'line', hue = 'type', palette = ['red'])
sns.relplot(data = df2, x = 'x', y = 'y2', kind = 'line', hue = 'type', palette = ['blue'])

How do I get the red and blue lines on the same plot? I've not had luck with different permutations of map.

Answer 1

• seaborn.relplot is a FacetGrid, the dataframes should be combined to plot them together
  • Figure-level interface for drawing relational plots onto a FacetGrid.
    • This function provides access to several different axes-level functions that show the relationship between two variables with semantic mappings of subsets. The kind parameter selects the underlying axes-level function to use:
      • scatterplot() (with kind="scatter"; the default)
      • lineplot() (with kind="line")
• Tested in python 3.8.12, pandas 1.3.4, matplotlib 3.4.3, seaborn 0.11.2

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

np.random.seed(2022)  # to create the same sample data
x = np.random.uniform(low=1, high=10, size=20)

df1 = pd.DataFrame({'x': x, 'y1': 2 * x, 'type': 'a'})
df2 = pd.DataFrame({'x': x, 'y2': 3 * x, 'type': 'b'}).rename(columns={'y2': 'y1'})

df = pd.concat([df1, df2], ignore_index=True)

# plot df
g = sns.relplot(data=df, x='x', y='y1', kind='line', hue='type', palette=['red', 'blue'])

Alternatives

• Create a separate seaborn.lineplot for each dataframe.

np.random.seed(2022)
x = np.random.uniform(low = 1, high = 10, size = 20)

df1 = pd.DataFrame({'x': x, 'y1': 2 * x, 'type': 'a'})
df2 = pd.DataFrame({'x': x, 'y2': 3 * x, 'type': 'b'})

fig, ax = plt.subplots(figsize=(5, 5))

sns.lineplot(data=df1, x='x', y='y1', label='a', ax=ax)
sns.lineplot(data=df2, x='x', y='y2', label='b', ax=ax)

• Plot the dataframes directly, without seaborn

ax = df1.plot(x='x', figsize=(5, 5))
df2.plot(x='x', ax=ax)