Basic scatterplot
You can create a basic scatterplot using regplot() function of seaborn library. The following parameters should be provided:
data: datasetx: positions of points on the X axisy: positions of points on the Y axisfit_reg: if True, show the linear regression fit linemarker: marker shapecolor: the color of markers
import pandas as pd
import numpy as np
import matplotlib.pylab as plt
import seaborn as sns
# Create dataframe
df = pd.DataFrame({
'x': [1, 1.5, 3, 4, 5],
'y': [5, 15, 5, 10, 2],
'group': ['A','other group','B','C','D']
})
sns.regplot(data=df, x="x", y="y", fit_reg=False, marker="+", color="skyblue")
plt.show()
Add one annotation
Once you have created the dataset and plotted the scatterplot with the previous code, you can use text() function of matplotlib to add annotation. The following parameters should be provided:
x: the position to place the text in x axisy: the position to place the text in y axiss: the text
You can also specify the additional parameters such as horizontalalignment, size, color, weight to design your text.
# basic plot
sns.regplot(data=df, x="x", y="y", fit_reg=False, marker="o", color="skyblue", scatter_kws={'s':400})
# add text annotation
plt.text(3+0.2, 4.5, "An annotation", horizontalalignment='left', size='medium', color='black', weight='semibold')
plt.show()
Use a loop to annotate each marker
If you want to annotate every markers, it is practical to use a loop as follow:
# basic plot
sns.regplot(data=df, x="x", y="y", fit_reg=False, marker="o", color="skyblue", scatter_kws={'s':400})
# add annotations one by one with a loop
for line in range(0,df.shape[0]):
plt.text(df.x[line]+0.2, df.y[line], df.group[line], horizontalalignment='left', size='medium', color='black', weight='semibold')
plt.show()
