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How can I disable the gradient color with kdeplot?

Time:01-14

When I run the below code, I get a figure with gradient color (from black to orange). Please look at the attached figure. Whereas I want to get a figure only with single color, orange (not figure with a gradient color). How can I do that?

My code:

#!/usr/bin/python3
import numpy as np
import pylab as plot
import matplotlib.pyplot as plt
import numpy, scipy, pylab, random
from matplotlib.ticker import MultipleLocator
import matplotlib as mpl
from matplotlib.ticker import MaxNLocator
import seaborn as sns
import pandas as pd

fig, ax = plt.subplots(figsize=(4, 2))

df = pd.read_csv('input.txt', sep="\s\s ", engine='python')
sns.kdeplot(data=df, label = "s1", color = "orange", cmap=None)
plt.xlabel('x', fontsize=7)
plt.ylabel('y', fontsize=7)

for axis in ['top','bottom','left','right']:
  ax.spines[axis].set_linewidth(0.5)

plt.savefig("plot.png", dpi=300, bbox_inches='tight')

input.txt:

   0.43082    0.45386
   0.35440    0.91632
   0.16962    0.85031
   0.07069    0.54742
   0.31648    1.06689
   0.57874    1.17532
   0.18982    1.01678
   0.31012    0.54656
   0.31133    0.81658
   0.53612    0.50940
   0.36633    0.83130
   0.37021    0.74655
   0.28335    1.30949
   0.11517    0.63141
   0.24908    1.04403
  -0.28633    0.46673
  -0.13251    0.33448
  -0.00568    0.53939
  -0.03536    0.76191
   0.24695    0.92592

The output figure that I get is here: plot.png

CodePudding user response:

Using Seaborn v0.11.2.

Solution:

The expected output is obtained if you specify x and y arguments of enter image description here


sns.kdeplot plots distribution of each column in the data when data is passed to it without specifying x and y:

The code in the question throws an error:

AttributeError: 'Line2D' object has no property 'cmap'

If you now don't pass cmap to sns.kdeplot and use:

df = pd.read_csv('input.txt', sep="\s\s ", engine='python',)
sns.kdeplot(data=df, label = "s1", color="orange")

it returns (notice the legend labels of the line plots):

enter image description here

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