How to avoid overlapping of labels in scatter plot

Question

My Dataframe looks like this:

 Driving Power Dependence Power F1 9.0 15.0 F2 14.0 14.0 F3 15.0 13.0 F4 16.0 1.0 F5 15.0 15.0 F6 15.0 15.0 F7 15.0 13.0 F8 12.0 15.0 F9 15.0 15.0 F10 15.0 15.0 F11 14.0 12.0 F12 11.0 15.0 F13 15.0 15.0 F14 15.0 10.0 F15 15.0 13.0 F16 1.0 16.0

I plotted above data using the following code:

#data Frame for x, y x = prom['Dependence Power'] y = prom['Driving Power'] n = ['F1','F2','F3','F4','F5','F6','F7','F8','F9','F10','F11','F12','F13','F14','F15','F16'] ########################################## plt.scatter(x, y, color="red") plt.xlim([0, 18]) plt.ylim([0, 18]) for i, txt in enumerate(n): plt.annotate(txt, (x[i], y[i]), fontsize=8, rotation=0) plt.ylabel('Driving Power', fontweight='bold') plt.xlabel('Dependence Power', fontweight='bold') plt.title("MICMAC Analysis", fontsize = 13,fontweight='bold') plt.grid() #axis lines plt.axhline(y=8, xmin=0, xmax=32) plt.axvline(x=9, ymin=0, ymax=32) plt.text(10, 10, 'Driving Factors') plt.text(2,10,'Linkage Factors') plt.text(2,4, "Autonomous Factors") plt.text(10,4,'Dependent Factors') #plt.savefig('micmac.png') plt.show()

I figure looks Okay but there are certain annotations overlapped for example, see label 'F15' and 'F18' on 1st quadrant, there must be labels 'F3','F7','F15' instead of 'F15' and 'F5','F6','F9','F10','F13' instead of 'F18'

Output I need like this:

Is the plot you provided what you want or what you are currently getting from your code? Would be better if you included your own plot as well — Abhigyan
– Abhigyan, Commented Mar 23, 2022 at 8:17

r-beginners · Accepted Answer · 2022-03-23 09:28:22Z

There may be several approaches, create a data frame for the annotation, group by column value and list the indexes. Set annotations in the created data frame. In this data example, more strings overlap, so we change the offset values only for the indices we do not want to overlap.

import matplotlib.pyplot as plt import pandas as pd import numpy as np import io data = ''' "Driving Power" "Dependence Power" F1 9.0 15.0 F2 14.0 14.0 F3 15.0 13.0 F4 16.0 1.0 F5 15.0 15.0 F6 15.0 15.0 F7 15.0 13.0 F8 12.0 15.0 F9 15.0 15.0 F10 15.0 15.0 F11 14.0 12.0 F12 11.0 15.0 F13 15.0 15.0 F14 15.0 10.0 F15 15.0 13.0 F16 1.0 16.0 ''' prom = pd.read_csv(io.StringIO(data), delim_whitespace=True) x = prom['Dependence Power'] y = prom['Driving Power'] n = ['F1','F2','F3','F4','F5','F6','F7','F8','F9','F10','F11','F12','F13','F14','F15','F16'] prom = prom.reset_index(drop=False).groupby(['Driving Power','Dependence Power'])['index'].apply(list).reset_index() plt.scatter(x, y, color="red") plt.xlim([0, 18]) plt.ylim([0, 18]) for i,row in prom.iterrows(): offset = 0.2 if i == 8 else 0.4 plt.annotate(','.join(row['index']), (row['Dependence Power'], row['Driving Power']), xytext=(row['Dependence Power'],row['Driving Power']+offset), fontsize=8) # for i, txt in enumerate(n): # plt.annotate(txt, (x[i], y[i]), fontsize=8, rotation=0) plt.ylabel('Driving Power', fontweight='bold') plt.xlabel('Dependence Power', fontweight='bold') plt.title("MICMAC Analysis", fontsize = 13,fontweight='bold') plt.grid() #axis lines plt.axhline(y=8, xmin=0, xmax=32) plt.axvline(x=9, ymin=0, ymax=32) plt.text(10, 10, 'Driving Factors') plt.text(2,10,'Linkage Factors') plt.text(2,4, "Autonomous Factors") plt.text(10,4,'Dependent Factors') #plt.savefig('micmac.png') plt.show()

Francesco Gualdi · Accepted Answer · 2022-12-08 14:38:19Z

Hi I just developed a library called overlab it can be installed via pip. Basically it moves the labels in spiral around the point to annotate until they don't overlap with any of the labels in the text.

Here is the result applied to your case:

import overlab as ol #data Frame for x, y x = prom['Dependence Power'] y = prom['Driving Power'] n = ['F1','F2','F3','F4','F5','F6','F7','F8','F9','F10','F11','F12','F13','F14','F15','F16'] ########################################## fig,ax =plt.subplots() ax.scatter(x, y, color="red") ol.annotate(x,y,n,ax=ax,fontsize=8, rotation=0) plt.xlim([0, 18]) plt.ylim([0, 18]) plt.ylabel('Driving Power', fontweight='bold') plt.xlabel('Dependence Power', fontweight='bold') plt.title("MICMAC Analysis", fontsize = 13,fontweight='bold') plt.grid() #axis lines plt.axhline(y=8, xmin=0, xmax=32) plt.axvline(x=9, ymin=0, ymax=32) plt.text(10, 10, 'Driving Factors') plt.text(2,10,'Linkage Factors') plt.text(2,4, "Autonomous Factors") plt.text(10,4,'Dependent Factors') #plt.savefig('micmac.png') plt.show()

Link to the result (I still cannot post images)

Hope it helps!

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