Amazon product dataset
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.
The above is the detailed content of Amazon product dataset. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Pythonlistsarepartofthestandardlibrary,whilearraysarenot.Listsarebuilt-in,versatile,andusedforstoringcollections,whereasarraysareprovidedbythearraymoduleandlesscommonlyusedduetolimitedfunctionality.

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.
