ss

import pandas as pd

train_pd = pd.read_csv("train.csv")
# print(train_pd)
select_pd = train_pd.loc[:,['Sold Price', 'Listed Price']]
select_pd = select_pd.iloc[:1000, :]
print(select_pd)

import matplotlib.pyplot as plt
import seaborn as sns
plt.figure(figsize=(20,20))
axes = sns.scatterplot(data=select_pd, x='Sold Price', y='Listed Price')
# for i in range(select_pd.shape[0]):
#     if select_pd.at[i, 'Listed Price'] > 0.5:
#         axes.text(select_pd.at[i, 'Sold Price']+0.02, select_pd.at[i, 'Listed Price'], i, horizontalalignment='left', size='medium', color='black', weight='semibold')
plt.show()