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 markersimport 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.scatterplot(data=df, x="x", y="y", s=200)
plt.show()
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 textYou can also specify the additional parameters such as horizontalalignment
, size
, color
, weight
to design your text.
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.scatterplot(data=df, x="x", y="y", s=200)
plt.text(x=1.7, y=15, s="A", weight="bold")
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:
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.scatterplot(data=df, x="x", y="y", s=200)
# 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],
ha='left',
weight='bold'
)
plt.show()
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