A notebook to analyze Amazon Recommendation Review Dataset.

Last update: Aug 22, 2022

Related tags

Data Analysis amazon recommendation amazon-dataset amazon-beauty

Overview

Amazon Recommendation Review Dataset Analyzer

A notebook to analyze Amazon Recommendation Review Dataset.

Features

Calculates distinct user count, distinct item count and total review count as basic stats.

Removes users with less than 5 reviews, then caluclates basic stats for filtered dataset.

Calculates mean and median review count per user, then plots a boxplot for review count per user.

Calculates average review point per user, then plots a boxplot for it.

Calculates mean and median review count per item, then plots a boxplot for review count per item.

Calculates average review point per item, then plots a boxplot for it.

Calculates word count per review, then plots a boxplot for it.

Calculates total word count in all reviews of the item, then plots a boxplot for it.

Calculates total word count in all reviews of the user, then plots a boxplot for it.

References:

1.J. McAuley and J. Leskovec. Hidden factors and hidden topics: understanding rating dimensions with review text. RecSys, 2013.

2.http://jmcauley.ucsd.edu/data/amazon/

Owner

isleki

isleki

GitHub Repository

track your GitHub statistics

GitHub-Stalker track your github statistics 👀 features find new followers or unfollowers find who got a star on your project or remove stars find who

34 Nov 18, 2022

Employee Turnover Analysis

Employee Turnover Analysis Submission to the DataCamp competition "Can you help reduce employee turnover?"

1 Feb 13, 2022

This is a repo documenting the best practices in PySpark.

Spark-Syntax This is a public repo documenting all of the "best practices" of writing PySpark code from what I have learnt from working with PySpark f

447 Dec 25, 2022

INF42 - Topological Data Analysis

TDA INF421(Conception et analyse d'algorithmes) Projet : Topological Data Analysis SphereMin Etant donné un nuage des points, ce programme contient de

2 Jan 07, 2022

:truck: Agile Data Preparation Workflows made easy with dask, cudf, dask_cudf and pyspark

To launch a live notebook server to test optimus using binder or Colab, click on one of the following badges: Optimus is the missing framework to prof

1.3k Dec 30, 2022

An Indexer that works out-of-the-box when you have less than 100K stored Documents

U100KIndexer An Indexer that works out-of-the-box when you have less than 100K stored Documents. U100K means under 100K. At 100K stored Documents with

7 Mar 15, 2022

BAyesian Model-Building Interface (Bambi) in Python.

Bambi BAyesian Model-Building Interface in Python Overview Bambi is a high-level Bayesian model-building interface written in Python. It's built on to

861 Dec 29, 2022

Anomaly Detection with R

AnomalyDetection R package AnomalyDetection is an open-source R package to detect anomalies which is robust, from a statistical standpoint, in the pre

3.5k Dec 27, 2022

scikit-survival is a Python module for survival analysis built on top of scikit-learn.

scikit-survival scikit-survival is a Python module for survival analysis built on top of scikit-learn. It allows doing survival analysis while utilizi

876 Jan 04, 2023

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

Description Kats is a toolkit to analyze time series data, a lightweight, easy-to-use, and generalizable framework to perform time series analysis. Ti

4.1k Jan 09, 2023

Python Project on Pro Data Analysis Track

Udacity-BikeShare-Project: Python Project on Pro Data Analysis Track Basic Data Exploration with pandas on Bikeshare Data Basic Udacity project using

0 Nov 10, 2021

BinTuner is a cost-efficient auto-tuning framework, which can deliver a near-optimal binary code that reveals much more differences than -Ox settings.

BinTuner is a cost-efficient auto-tuning framework, which can deliver a near-optimal binary code that reveals much more differences than -Ox settings. it also can assist the binary code analysis rese

42 Dec 16, 2022

Convert monolithic Jupyter notebooks into Ploomber pipelines.

Soorgeon Join our community | Newsletter | Contact us | Blog | Website | YouTube Convert monolithic Jupyter notebooks into Ploomber pipelines. soorgeo

65 Dec 16, 2022

Collections of pydantic models

pydantic-collections The pydantic-collections package provides BaseCollectionModel class that allows you to manipulate collections of pydantic models

20 Dec 26, 2022

A Python package for modular causal inference analysis and model evaluations

Causal Inference 360 A Python package for inferring causal effects from observational data. Description Causal inference analysis enables estimating t

506 Dec 19, 2022

Pip install minimal-pandas-api-for-polars

Minimal Pandas API for Polars Install From PyPI: pip install minimal-pandas-api-for-polars Example Usage (see tests/test_minimal_pandas_api_for_polars

6 Oct 16, 2022

Shot notebooks resuming the main functions of GeoPandas

Shot notebooks resuming the main functions of GeoPandas, 2 notebooks written as Exercises to apply these functions.

1 Jan 12, 2022

Project under the certification "Data Analysis with Python" on FreeCodeCamp

Sea Level Predictor Assignment You will anaylize a dataset of the global average sea level change since 1880. You will use the data to predict the sea

3 Jan 31, 2022

Time ranges with python

timeranges Time ranges. Read the Docs Installation pip timeranges is available on pip: pip install timeranges GitHub You can also install the latest v

2 Sep 01, 2022

PandaPy has the speed of NumPy and the usability of Pandas 10x to 50x faster (by @firmai)

PandaPy "I came across PandaPy last week and have already used it in my current project. It is a fascinating Python library with a lot of potential to

527 Jan 02, 2023