Select Dots to Color
Previous posts on controlling marker features and mapping categorical values to colors covered setting marker colors globally or by category.
Here, we'll demonstrate how to control each marker's color individually. This example uses a dataset with random points. To manage the colors, we add a column specifying the color for each marker (data point).
# libraries
import pandas as pd
import numpy as np
import matplotlib.pylab as plt
import seaborn as sns
colors = ['#9b59b6', '#3498db']
# Create data frame with randomly selected x and y positions
df = pd.DataFrame(np.random.random((100,2)), columns=["x","y"])
# Add a column: the color depends on x and y values, but you can use any function you want
is_selected_dot = (df['x']>0.6) & (df['y']>0.6)
df['color']= np.where(is_selected_dot==True , colors[0], colors[1])
# plot
sns.set_style("darkgrid")
sns.scatterplot(
data=df,
x="x",
y="y",
color=df['color'],
s=400,
alpha=0.8,
)
plt.show()
Access more colors with pypalettes
You can easily way more palette colors with pypalettes. In this case we use the get_hex() function with the "Acadia" palette, and keep the first 2 colors of it.
If you haven't already, install this library with pip install pypalettes
# libraries
import pandas as pd
import numpy as np
import matplotlib.pylab as plt
import seaborn as sns
from pypalettes import get_hex
colors = get_hex("Acadia", keep_first_n=2)
# Create data frame with randomly selected x and y positions
df = pd.DataFrame(np.random.random((100,2)), columns=["x","y"])
# Add a column: the color depends on x and y values, but you can use any function you want
is_selected_dot = (df['x']>0.6) & (df['y']>0.6)
df['color']= np.where(is_selected_dot==True , colors[0], colors[1])
# plot
sns.set_style("darkgrid")
sns.scatterplot(
data=df,
x="x",
y="y",
color=df['color'],
edgecolor="black",
s=400,
alpha=0.8,
)
plt.show()
Going further
This post explains how to customize the appearance of the markers in a scatter plot with seaborn.
You might be interested in
- how to visualize linear regression
- how to create a bubble plot, a kind of scatter plot where the size of the marker is proportional to a third variable
- how to colors dots according to a variable.
