  # Plot visualization with pandas and siborn

NumPy | Python Methods and Functions

A box plot consists of 5 things.

• minimal
• First quartile or 25%
• Median (second quartile) or 50%
• Third quartile or 75%
• maximum

Draw a plot frame with pandas:

One way to plot a boxplot using pandas

` # import the desired library `

` import ` ` numpy as np `

` import ` ` pandas as pd `

` import ` ` matplotlib.pyplot as plt `

`% ` ` matplotlib inline `

` # load dataset `

` df ` ` = ` ` pd.read_csv (` ` "tips.csv" ` `) `

` # display 5 rows of dataset `
` df.head () ` Conspiracy ` days subject to total_bill . `

` df.boxplot (by = `day` , column = [ ` total_bill` ], grid = False ) `

` ` Boxplot by ` size ` best regards ` tip `.

 ` df.boxplot (by ` ` = ` ` `size` ` `, column ` ` = ` ` [` `` tip` ` `], grid ` ` = ` ` False ` `) ` Draw a box using the Seaborn library:

Syntax:
` seaborn.boxplot (x = None, y = None, hue = None, data = None, order = None, hue_order = None, orient = None, color = None, palette = None, saturation = 0.75, width = 0.8, dodge = True, fliersize = 5, linewidth = None, whis = 1.5, notch = False, ax = None, ** kwargs) `

Parameters:
x = feature of dataset
y = feature of dataset
hu e = feature of dataset
data = datafram or full dataset
color = color name

Let`s see how to create a boxed plot using the Seaborn library.

Information about a set of "hints."

` `

 ` # load dataset ` ` tips ` ` = ` ` sns.load_dataset (` ` `tips` ` `) ` ` `  ` tips.head () `

` ` Plot ` days ` with ` total_bill `.

 ` # Draw a vertical checkpoint grouped ` ` # by categorical variable: ` ` sns .set_style (` ` "whitegrid" ` `) ` ` `  ` sns.boxplot (x ` ` = ` ` `day` ` `, y ` ` = ` `` total_bill` ` `, data ` ` = ` ` tips) ` Let`s take the first rectangle, that is, the blue rectangle plot of the shape, and figure out the following statistical things:

• Bottom black horizontal plot line blue rectangle is the minimum value
• First black horizontal rectangular line on the blue rectangle chart — First quartile or 25%
• Second black rectangular horizontal line in the blue rectangle plot represents the Second quartile or 50% or median.
• The third black horizontal rectangular line of the blue rectangle represents the third quartile or 75%
• The maximum value of the top black horizontal line of the rectangle in the blue border
• Small diamond shapes in the blue rectangle plot represent outliers or erroneous data.