data-merging
There are 1 repository under data-merging topic.
Datawithabhishek / Google-Play-Store-Data-Analysis
Exploring Google Play Store apps dataset to identify key factors for app engagement and success, revealing correlations between reviews, installs, categories, ratings, and user preferences.
Language:Jupyter Notebook 4Shahrukh2016 / Play-store-review-analysis-EDA
Exploring Google Play Store apps dataset to identify key factors for app engagement and success, revealing correlations between reviews, installs, categories, ratings, and user preferences.
category-analysiscorrelation-analysiscritical-thinkingdata-cleaningdata-manipulationdata-mergingdata-visualizationexploratory-data-analysisfeature-engineeringmachine-learningmatplotlibnumpypandasproblem-solvingpythonseabornsentiment-analysisstatistical-analysistrend-identificationdata-integrity-maintenanceLanguage:Jupyter Notebook 4- ouroboros-db
i5heu / ouroboros-db
A versioned, distributed key-value store designed with a focus on data integrity. Each value boasts a comprehensive history, ensuring eventual consistency across the system. It features seamless merging capabilities to harmonize divergent data states.
Language:Go 2 - essential-guide-to-pandas
imarranz / essential-guide-to-pandas
A comprehensive guide to mastering Pandas for data analysis, featuring practical examples, real-world case studies, and step-by-step tutorials. For general information, see
Language:Jupyter Notebook 2 AchrafSL / Exploring-Airbnb-Market-Trends-Datacamp
Combine Airbnb data from CSV, Excel, and TSV files to analyze prices, reviews, and room types in NYC’s rental market using pandas.
Language:Jupyter Notebook 1Ashif-khan033 / Play-Store-Apps-Review-Analysis-EDA
Exploring Google Play Store apps dataset to identify key factors for app engagement and success, revealing correlations between reviews, installs, categories, ratings, and user preferences.
Language:Jupyter Notebook 1HeiderJeffer / Evaluating-Rule-Offsetting-Schemes-for-Sustainable-Policy-Growth-in-Modern-Democracies
Python Java. Research Proposal RP
Language:Jupyter Notebook 1Nour-Sadek / HR-Data-Analyst
This project provided practice with the pandas library and data analysis
Language:Python 1shrey1216 / Statistical-Analysis-of-Independent-and-Dependent-Variables-Data-Merging-Missing-Data-Imputation
Data Analysis: Merge, Impute, and Interpret
srimallipudi / Estimating-Optimal-Cash-Levels-for-Firms-Using-SAS
This comprehensive analysis delves into the crucial role of cash holdings in determining a firm's future performance and market dynamics.
Language:SAS 1sumit-sinha9 / Google-Play-Store-Apps-Analysis
Exploring Google Play Store apps dataset to identify key factors for app engagement and success, revealing correlations between reviews, installs, categories, ratings, and user preferences.
Language:Jupyter Notebook 1x1ao4 / doc-merger
通过 python 脚本将两个相对不完整的文档合并为一个完整的文档 / merge two relatively incomplete documents into one complete document via python script
Language:Python 1- Language:R 0
Deepubhatt / Sustainable-Growth-Strategy-Analysis
Analyzed the World Economic Indicator Dataset to investigate the factors driving sustainable economic growth in countries and regions. Delivered insights on strategies for achieving long-term economic stability.
0EricaYanoshak / athletic_sales_analysis
Analyzed athletic sales data using Pandas, employing techniques like concatenation, joins, groupby, and pivot tables to identify top-performing regions, retailers, and product categories. The project highlighted advanced data combination and reshaping skills to uncover key sales insights.
Language:Jupyter Notebook 0Developed a movie recommendation system by sourcing data from the New York Times Article Search and The Movie Database APIs. Extracted, merged, and cleaned data to create a comprehensive dataset, enabling users to find movie reviews and related titles based on their preferences.
Language:Jupyter Notebook 0kathisnehith / Medicare-IP-hospital-Analysis
In-depth Data analysis and visualization of Medicare inpatient hospital data.
0rajesh9943 / Fitbit-User-Activity-Heart-Rate-and-Sleep-Monitoring-December-2016-A-Crowdsourced-Dataset
In a distributed survey conducted via Amazon Mechanical Turk between December 3rd and 5th, 2016, data was collected from 30 Fitbit users. These users consented to sharing their minute-level physical activity, heart rate, and sleep monitoring data.
Language:Jupyter Notebook 0RLAlpha49 / AniSearch-Model
AniSearchModel leverages Sentence-BERT (SBERT) models to generate embeddings for synopses, enabling the calculation of semantic similarities between descriptions. This allows users to find the most similar anime or manga based on a given description.
Language:Python 0Sarashic / Data-Analysis-Using-Python
Data Analysis with the Pandas Library 📊
Language:Python 0Yalai92 / MASTER_ACADEMIC_PROJECTS
This repository is dedicated to showcasing the academic projects completed during my Master in Data Science & AI. The main objective is to show a collection of projects in various data science fields, including: data cleaning & preprocessing, data analysis, data visualization, machine learning, clustering, among others.
Language:Jupyter Notebook 0Yuval-barak / Data-Analysis-Using-Python
Data Analysis with the Pandas Library 📊
Language:Python 0Cardman08 / CSV-SQL-TableMerger
Merge CSV/TXT/SQL files for harmonized ELN import; supports joins and preview with export
Language:R- Data-Wrangling
madhurimarawat / Data-Wrangling
This repository contains experiments on data wrangling techniques, focusing on methods for handling missing values, filtering, aggregation, and more.
codesdata-aggregationdata-concatenationdata-conversiondata-filteringdata-mergingdata-preprocessingdata-reshapingdata-samplingdata-visualizationdata-wranglingdata-wrangling-workflowdate-time-processingdetailed-documentationhandling-missing-valuesjupyter-notebookmarkdownoutputpythontext-data-processingLanguage:Jupyter Notebook Sedimark / InteroperabilityEnabler
Interoperability enabler component for SEDIMARK
Language:PythonZihanYin12138 / 2023-09-Victoria-Real-Estate-Analysis-and-Prediction
An end-to-end data science project analyzing internal and external drivers of rental prices across Victoria, Australia. The project includes web scraping, data preprocessing, geospatial integration, exploratory data analysis, and predictive modeling. Built using Python, Pandas, GeoPandas, Scikit-learn, and web scraping frameworks.
Language:HTML
