Plots Distribuition

 

Firs see the histogram

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

# Load the data
df = pd.read_csv('nft.csv')
# Extract feature we're interested in
data = df['release_year']

# Generate histogram/distribution plot
sns.displot(data)
plt.savefig('hist1.png')
plt.show()


data = df['release_year']
sns.displot(data, discrete = True, kde = True)
plt.savefig('dist_hist.png')
plt.show()

See the histogram with Distribution Curve

Like these we can combine histogram and distribution curve to understand things better

Code to join plot:

df.dropna(inplace=True)  # to drop null value otherwise, seaborn has trouble to convert null
sns.jointplot(x = "rating", y = "release_year", data = df)
plt.savefig('joint.png')
plt.show()

Sea born is very easy to plot thes types of charts