This content originally appeared on DEV Community and was authored by victor_dalet
Hi, I found a dataset of Amazon products in Kaggle and decided to find a relationship between price and star rating.
Full code in :
https://github.com/victordalet/Kaggle_analysis/tree/feat/amazon_products
I - Preparing data
To do this, I use SQLAlchemy to convert the csv file into a small database, and plotly to display the information.
pip install SQLAlchemy
pip install plotly
In the following script, I extract the data and obtain :
- ratio between price and number of stars
- final rating and number of stars
- price and number of stars
import pandas as pd
from sqlalchemy import create_engine, text
import plotly.express as px
class Main:
def __init__(self):
self.result = None
self.connection = None
self.engine = create_engine("sqlite:///my_database.db", echo=False)
self.df = pd.read_csv("amazon_product.csv")
self.df.to_sql("products", self.engine, index=False, if_exists="append")
self.get_data()
self.transform_data()
self.display_graph()
self.get_data_number_start_and_price()
self.transform_data()
self.display_graph()
self.get_data_number_start_and_start()
self.display_graph()
def get_data(self):
self.connection = self.engine.connect()
query = text(
"SELECT product_price, product_star_rating FROM products where product_price != '$0.00'"
)
self.result = self.connection.execute(query).fetchall()
def get_data_number_start_and_price(self):
query = text(
"SELECT product_price, product_num_ratings FROM products where product_price != '$0.00'"
)
self.result = self.connection.execute(query).fetchall()
def get_data_number_start_and_start(self):
query = text(
"SELECT product_star_rating, product_num_ratings FROM products where product_price != '$0.00'"
)
self.result = self.connection.execute(query).fetchall()
for i in range(len(self.result)):
self.result[i] = [self.result[i][0], self.result[i][1]]
def transform_data(self):
for i in range(len(self.result)):
self.result[i] = [float(self.result[i][0].split("$")[1]), self.result[i][1]]
def display_graph(self):
fig = px.scatter(
self.result, x=0, y=1, title="Amazon Product Price vs Star Rating"
)
fig.show()
Main()
II - Result
Price and notation
Price and number of notation
Notation and number of opinion
III - Conclusion
We can see, there's not necessarily a relationship between price and rating, but the higher the price, the lower the rating, and the more reviews, the higher the rating.
Which seems logical, since if a product is bought a lot, it means it's popular.
This content originally appeared on DEV Community and was authored by victor_dalet
victor_dalet | Sciencx (2024-08-25T17:38:26+00:00) Amazon product dataset. Retrieved from https://www.scien.cx/2024/08/25/amazon-product-dataset/
Please log in to upload a file.
There are no updates yet.
Click the Upload button above to add an update.