Visualization Seaborn

In this section, we’ll use seaborn, importing it as sns.

import seaborn as sns

We will use the following lists:

expenses = ['housing', 'tuition', 'transportation', 'supplies', 'food']
cost = [700, 1000, 200, 100, 500 ]
color_set = ['y', 'r', 'g', 'orange', 'navy']

Scatterplot

sns.scatterplot(x=[2,4,7],y=[10,4,6], color='r', s=100);

Lineplot

sns.lineplot(x=[2,4,7],y=[10,4,6], color='r');

Barplot

sns.barplot(x=cost, y=expenses);

Box Plot

sns.boxplot([8,7,3,2,1,5,6,7,8]);

Displot

• sns.displot() is used to generate histograms.

sns.displot([8,7,3,2,1,5,6,7,8,1,3,2,5]);

Histplot

sns.histplot() is used to generate histograms.

sns.histplot([8,7,3,2,1,5,6,7,8,1,3,2,5]);

Violinplot

sns.violinplot() is used to generate violinplots, which represent the distribution of the data.

sns.violinplot([8,7,3,2,1,5,6,7,8,1,3,2,5]);

Swarmplot

sns.swarmplot() is used to generate swarmplots, which represent the distribution of the data.

sns.swarmplot([8,7,3,2,1,5,6,7,8,1,3,3,3,3,3,3,3,3,3,2,5,5,5,5,5,5,5,5]);

sns.swarmplot([8,7,3,2,1,5,6,7,8,1,3,3,3,3,3,3,3,3,3,2,5,5,5,5,5,5,5,5], c='yellow');
sns.violinplot([8,7,3,2,1,5,6,7,8,1,3,3,3,3,3,3,3,3,3,2,5,5,5,5,5,5,5,5], color='red');

DataFrames

We will use the following dataset to perform visualization with Seaborn on a dataframe.

import pandas as pd
df_stock = pd.read_excel('https://raw.githubusercontent.com/datasmp/datasets/main/stock.xlsx')
df_stock.head()

	Date	APPLE	TESLA	AMAZON	VISA	SP500
0	2020-01-02	74.33	86.05	1898.01	189.66	3257.85
1	2020-01-03	73.61	88.60	1874.97	188.15	3234.85
2	2020-01-06	74.20	90.31	1902.88	187.74	3246.28
3	2020-01-07	73.85	93.81	1906.86	187.24	3237.18
4	2020-01-08	75.04	98.43	1891.97	190.45	3253.05

import seaborn as sns
sns.boxplot(data=df_stock);

# apple
sns.boxplot(data=df_stock['APPLE']);

sns.violinplot(data=df_stock.iloc[:,1:]);

sns.violinplot(data=df_stock['APPLE']);

sns.swarmplot(data=df_stock['AMAZON']);

sns.violinplot(data=df_stock['TESLA']);

sns.violinplot(data=df_stock['TESLA']);
sns.swarmplot(data=df_stock['TESLA'], color='orange');