import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

df= pd.read_csv('mushroom.csv')
df.head()

	class	cap-shape	cap-color	stem-height	stem-width	habitat	season
0	p	x	o	16.95	17.09	d	w
1	p	x	o	17.99	18.19	d	u
2	p	x	o	17.80	17.74	d	w
3	p	f	e	15.77	15.98	d	w
4	p	x	o	16.53	17.20	d	w

#1. histplot
plt.figure(figsize=(5,3))
sns.countplot(data= df, x='class', hue= 'class', palette={'p':'red', 'e':'green'})
plt.title('Class Distribution')
plt.xlabel('Class')
plt.show()

# 2 realtionship between stem height and width
plt.figure(figsize=(8,4))
sns.jointplot(data=df, x='stem-height', y='stem-width', kind='reg')
plt.show()

<Figure size 800x400 with 0 Axes>

#3 edible and poisonous mushrooms are distribution among the
#distribution stem height and stem width
plt.figure(figsize=(6,5))
sns.scatterplot(data=df, x='stem-height', y='stem-width', hue='class',
                palette={'p':'red', 'e':'green'}, marker='x', s=50)
plt.show()

there's a strong positive correlation showing that edible mushrooms tend to be longer and thicker, and vice versa with non edible mushrooms.

#4 stem height distributed across season using kde plot
plt.figure(figsize=(5,3))
sns.kdeplot(data=df, x='stem-height',hue= 'season', fill=True)
plt.show()

# 5 visualization of distribution of stem height
plt.figure(figsize=(5,3))
sns.histplot(data=df, x='stem-height', kde=True)
plt.show()

#6 visualization of the median of stem height over variable 'class'
sns.catplot(data=df, y='stem-height', x='class', kind= 'box', hue= 'class',
            palette={'p':'red', 'e':'green'})
plt.grid(axis= 'y', linewidth=0.5, linestyle='--', color= 'blue')
plt.xticks(rotation=20)
plt.show()

the medians are about the same for both classes

#7 visualization of stem height is distributed across habitat
plt.figure(figsize=(5,3))
sns.catplot(data=df, x='habitat', y='stem-height', kind='box', hue='habitat')
plt.grid(axis= 'y', linewidth=0.5, linestyle='--', color= 'blue')
plt.xticks(rotation=20)
plt.show()

<Figure size 500x300 with 0 Axes>