Polar chart with limit and anomalous points

Question

Consider the following data frame,

d = {'Score': [0.25, 0.52, 0.26, 0.22, 0.31, 2.45, 3.68, 41.3, 87, 91], 
     'Thr1': 16.5,
     'Thr2': 45.5,  
     'Anomaly':[0, 0, 0, 0, 0, 0, 0, 1, 1, 1]}

df = pd.DataFrame(data = d)

What I m trying to do is to plot a polar chart, with a dotted line for threshold or multiple dotted lines for multiple thresholds and different color for the anomalies. What I ve got so far is,

r = df['Score']
theta = df.index.values
fig = plt.figure()
ax = fig.add_subplot(111, projection = 'polar')
c = ax.scatter(theta, r)

I cannot get the threshold though and change the color of the anomalous points. Any ideas?

https://stackoverflow.com/questions/43109397/adding-color-to-polar-scatter-plot-data-points — BENY, Nov 24 '17 at 16:29
What are you expecting to get? Something like [this](https://i.stack.imgur.com/lcTTm.png) — varren, Nov 27 '17 at 09:16
@varren exactly but the first point which is outside the first limit should be say... yellow — Sotos, Nov 27 '17 at 09:18

Reblochon Masque · Accepted Answer · 2017-11-30T03:35:03.783

You need to draw a dashed line at the threshold level, to indicate where the threshold is. (a line will appear as a circle on a polar plot).

Then you need to segregate the values to plot on the scatter plot, based whether or not they are below, between, or above the thresholds, and color the points accordingly.

import matplotlib
matplotlib.use('TkAgg')

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


dataset = {'Score': [0.25, 0.52, 0.26, 0.22, 0.31, 2.45, 3.68, 41.3, 87, 91], 
           'Thr1': 16.5,
           'Thr2': 45.5,  
           'Anomaly':[0, 0, 0, 0, 0, 0, 0, 1, 1, 1]}

df = pd.DataFrame(data=dataset)

scores = df['Score']
theta, thr_1, thr_2 = df.index.values, dataset['Thr1'], dataset['Thr2']

fig = plt.figure()
ax = fig.add_subplot(111, projection='polar')

# assigns a color to each point based on their relative value to the thresholds
colors = ['b' if val < thr_1 else 'y' if val < thr_2 else 'r' for val in scores]
point_cloud = ax.scatter(theta, scores, color=colors, marker='o')

# Drawing the threshold dash lines (with alpha value 1/2)
theta_xs, thr_y1, thr_y2 = np.linspace(0, 2*np.pi, 20), [thr_1] * 20, [thr_2] * 20
thr_line_1 = ax.plot(theta_xs, thr_y1, color='blue', linestyle='--', alpha=0.5)
thr_line_2 = ax.plot(theta_xs, thr_y2, color='green', linestyle='--', alpha=0.5)

plt.show()

Thanks. Very readable version. Could the dotted threshold lines be defferent colors as well? — Sotos, Nov 27 '17 at 09:51
You are welcome; yes, you can set the color for each threshold (and the alpha value too, or the line style, thickness, etc...) by changing the relevant kwargs. I added a comment in the code. — Reblochon Masque, Nov 27 '17 at 09:58

varren · Answer 2 · 2017-11-27T11:12:57.793

Well, i'm not exactly sure that it is what you want, because i never used Anomaly part of your dataset, and just take color info from Score array

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.colors as c
d = {'Score': [0.25, 0.52, 0.26, 0.22, 0.31, 2.45, 3.68, 41.3, 87, 91],
     'Thr1': 16.5,
     'Thr2': 45.5,
     'Anomaly': [0, 0, 0, 0, 0, 0, 0, 1, 1, 1]}

df = pd.DataFrame(data = d)

r = df['Score']
theta = df.index.values
fig = plt.figure()
ax = fig.add_subplot(111, projection = 'polar')

#Add thresholds
ax.plot(np.linspace(0, 2*np.pi, 100), np.ones(100)*d['Thr1'], c='g', ls='--')
ax.plot(np.linspace(0, 2*np.pi, 100), np.ones(100)*d['Thr2'], c='r', ls='--')

#Add colors
colors = ['g' if v < d['Thr1'] else 'y' if v < d['Thr2'] else "r" for v in r]
sc = ax.scatter(theta, r, c=colors)

plt.show()

Thank you very much. It does not have to use the anomaly column of the df. Once you capture values greater than the thresholds and recolor them then that's all I need — Sotos, Nov 27 '17 at 09:51

Polar chart with limit and anomalous points

2 Answers2