How do I plot a beautiful scatter plot with linear regression?

Question

I want to make a beautiful scatter plot with linear regression line using the data given below. I was able to create a scatter plot but am not satisfied with how it looks. Additionally, I want to plot a linear regression line on the data.

My data and code are below:

x            y
117.00      111.0
107.00      110.0
77.22        78.0
112.00       95.4
149.00      150.0
121.00      121.0
121.61      120.0
111.54      140.0
73.00        72.0
70.47       000.0
66.3         72.0
113.00      131.0
81.00        81.0
72.00        00.0
74.20        98.0
84.24        90.0
86.60        88.0
99.00        97.0
90.00       102.0
85.00       000.0
138.0       135.0
96.00        93.0

import numpy as np
import matplotlib.pyplot as plt
print(plt.style.available)
from sklearn.linear_model import LinearRegression
plt.style.use('ggplot')

data = np.loadtxt('test_data',  dtype=float, skiprows=1,usecols=(0,1))

x=data[:,0]
y=data[:,1]
plt.xlim(20,200)
plt.ylim(20,200)

plt.scatter(x,y, marker="o",)
plt.show()

Answer 1

Please check the snippet. You can use numpy.polyfit() with degree=1 to calculate slope and y-intercept of line to y=m*x+c

import numpy as np
import matplotlib.pyplot as plt
plt.style.use('ggplot')
data = np.loadtxt('test_data.txt',  dtype=float, skiprows=1,usecols=(0,1))
x=data[:,0]
y=data[:,1]

plt.xlim(20,200)
plt.ylim(20,200)

plt.scatter(x,y, marker="o",)

m, b = np.polyfit(x, y, 1)
plt.plot(x, m*x + b)

plt.show()

Edit1: Based on your comment, I added more points and now graph seems like this and it seems it passes via points.

To set transparency to points you can use alpha argument . You can set range between 0 and 1 to change transparency. Here I set alpha=0.5

plt.scatter(x,y, marker="o",alpha=0.5) Edit2: Based on @tmdavison suggestion

import numpy as np
import matplotlib.pyplot as plt
plt.style.use('ggplot')
data = np.loadtxt('test_data.txt',  dtype=float, skiprows=1,usecols=(0,1))
x=data[:,0]
y=data[:,1]
x2 = np.arange(0, 200)
plt.xlim(20,200)
plt.ylim(20,200)

plt.scatter(x,y, marker="o",)

m, b = np.polyfit(x, y, 1)
plt.plot(x2, m*x2 + b)

plt.show()