how to plot scatter plot with python seaborn package
seaborn is a package specially used for statistical data visualization, comparable to the ggplot2 package in R language. This article introduces the use of seaborn to draw scatter plots.
environments¶
- python3.9
- win10 64bit
- seaborn==0.11.1
- matplotlib==3.3.4
- pandas==1.2.1
data¶
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
# Settings
pd.options.display.notebook_repr_html=False # Table display
plt.rcParams['figure.dpi'] = 75 # resolution
sns.set_theme(style='darkgrid') # theme
load data¶
# change path to your own data path
tips=pd.read_csv(r'https://gitee.com/nicedouble/seaborn-data/raw/master/tips.csv')
tips.head()
total_bill tip sex smoker day time size
0 16.99 1.01 Female No Sun Dinner 2
1 10.34 1.66 Male No Sun Dinner 3
2 21.01 3.50 Male No Sun Dinner 3
3 23.68 3.31 Male No Sun Dinner 2
4 24.59 3.61 Female No Sun Dinner 4
plot¶
In seaborn, the functions for drawing scatter plots are scatterplot and relplot.
The easiest way for seaborn to draw a scatter plot is to use the scatterplot method, specifying the data parameter and the x and y parameters.
# Scatter chart
sns.scatterplot(data=tips,x='total_bill',y='tip')
plt.show()
Add the hue parameter and set the group color of the points.
sns.scatterplot(data=tips,x='total_bill',y='tip',hue='time')
plt.show()
Add the style parameter to set the grouping style of points.
sns.scatterplot(data=tips,x='total_bill',y='tip',style='sex')
plt.show()
Add the size parameter to set the grouping size of points.
sns.scatterplot(data=tips,x='total_bill',y='tip',size='size')
plt.show()
You can set multiple parameters of hue, style, and size at the same time:
sns.scatterplot(data=tips,x='total_bill',y='tip',hue='time',size='size')
plt.show()
The faceted scatter plot is drawn by the relplot method, you need to set kind="scatter", and then use the col, row parameters to facet.
