[FIXED] How to set individual color for every Group in a 2D scatter plot

Issue

How do i get the same color for every group A,B,C... ?

this is my code:

import matplotlib.pyplot as plt
import numpy as np

# Data
group_labels = ['A', 'B', 'C', 'D', 'E', 'F', 'G']

data = [
    [0.735721594, 0.619603837, 0.87785673, 0.482125754, 0.0894892, 0.133485767, 0.995450247],
    [0.666117198, 0.52923401, 0.499589112, 0.096963416, 0.308461174, 0.130418723, 0.195501054],
    [0.696378042, 0.437459297, 0.033071186, 0.645614608, 0.99425186, 0.097360026, 0.354376981],
    [0.552392974, 0.668845104, 0.079569268, 0.455465795, 0.353141333, 0.147198273, 0.249947862],
    [0.591065904, 0.34886412, 0.821742243, 0.008845512, 0.259947361, 0.063514992, 0.040540063],
    [0.016209069, 0.092671819, 0.195080351, 0.886493551, 0.745661888, 0.504613173, 0.593546542],
    [0.536218451, 0.466140392, 0.721903277, 0.426671591, 0.648579902, 0.823047029, 0.922809018]
]

# Transpose the data to have groups on the x-axis
data = np.array(data).T

# Create a 2D scatter plot with unique colors for each data point
color_map = plt.cm.get_cmap('tab10', len(group_labels))  # Choose a color map
for i in range(len(group_labels)):
    colors = color_map(np.linspace(0, 1, len(data[i])))
    for j in range(len(data[i])):
        plt.scatter(group_labels[i], data[i][j], label=f'Group {group_labels[i]}', marker='o', s=50, c=colors[j])

# Customize the plot
plt.xticks(rotation=0)
plt.ylabel('Y Values')
plt.tight_layout()

# Show the plot
plt.show()

and this is the result:

How do i get the same color for every group A,B,C... ?

Solution

An easy solution is to use seaborn.scatterplot. I'm using pandas to manipulate the data (melt) and then plotting.

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

# Data
group_labels = ['A', 'B', 'C', 'D', 'E', 'F', 'G']

data = [
    [0.735721594, 0.619603837, 0.87785673, 0.482125754, 0.0894892, 0.133485767, 0.995450247],
    [0.666117198, 0.52923401, 0.499589112, 0.096963416, 0.308461174, 0.130418723, 0.195501054],
    [0.696378042, 0.437459297, 0.033071186, 0.645614608, 0.99425186, 0.097360026, 0.354376981],
    [0.552392974, 0.668845104, 0.079569268, 0.455465795, 0.353141333, 0.147198273, 0.249947862],
    [0.591065904, 0.34886412, 0.821742243, 0.008845512, 0.259947361, 0.063514992, 0.040540063],
    [0.016209069, 0.092671819, 0.195080351, 0.886493551, 0.745661888, 0.504613173, 0.593546542],
    [0.536218451, 0.466140392, 0.721903277, 0.426671591, 0.648579902, 0.823047029, 0.922809018]
]

# Use pandas dataframe; melt and then plot
df = pd.DataFrame(data, columns = group_labels)
df = df.melt(value_vars=group_labels)
sns.scatterplot(df,x='variable', y='value', hue='variable', legend=False )

Plot:

Answered By - Suraj Shourie