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Pranav Kumar

Data Analyst
About Pranav
BlinkitWhispers – Uncovering Hidden Customer Pain Points
BlinkitWhispers – Uncovering Hidden Customer Pain PointsScraped and analyzed Blinkit customer complaints from LinkedIn and Twitter using Selenium, LLaMA 3, and Python. Extracted key issues, products, and resolutions using LLMs, and visualized trends in sentiment, urgency, and complaint types.
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BlinkitWhispers – Uncovering Hidden Customer Pain Points
BlinkitWhispers – Uncovering Hidden Customer Pain PointsScraped and analyzed Blinkit customer complaints from LinkedIn and Twitter using Selenium, LLaMA 3, and Python. Extracted key issues, products, and resolutions using LLMs, and visualized trends in sentiment, urgency, and complaint types.
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A Comprehensive Market Study for AtliQ Motor’s Entry into the Indian EV Market
A Comprehensive Market Study for AtliQ Motor’s Entry into the Indian EV MarketDesigned an interactive dashboard for AtliQ Motors to analyze KPIs and provide insights into EV sales, market penetration, and growth trends in India. Used Power Query, DAX, and MySQL for data preprocessing and analysis and created dynamic visualizations.
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A Comprehensive Market Study for AtliQ Motor’s Entry into the Indian EV Market
A Comprehensive Market Study for AtliQ Motor’s Entry into the Indian EV MarketDesigned an interactive dashboard for AtliQ Motors to analyze KPIs and provide insights into EV sales, market penetration, and growth trends in India. Used Power Query, DAX, and MySQL for data preprocessing and analysis and created dynamic visualizations.
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Driving Insights: Exploratory Data Analytics for GoodCabs' Growth
Driving Insights: Exploratory Data Analytics for GoodCabs' GrowthDriving Insights: Exploratory Data Analytics for GoodCabs' Growth" is a data-driven project designed to analyze and improve the performance of GoodCabs, a cab service company operating in tier-2 cities in India.
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Driving Insights: Exploratory Data Analytics for GoodCabs' Growth
Driving Insights: Exploratory Data Analytics for GoodCabs' GrowthDriving Insights: Exploratory Data Analytics for GoodCabs' Growth" is a data-driven project designed to analyze and improve the performance of GoodCabs, a cab service company operating in tier-2 cities in India.
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IPL Performance Insights: 2021-2023
IPL Performance Insights: 2021-2023I built a Power BI dashboard with drill-through insights for Sports Basics analyzing 3 IPL seasons (2021-2023). Key metrics: 65,000+ runs, 2,300+ wickets. Tools: Python, MySQL, Power BI.
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IPL Performance Insights: 2021-2023
IPL Performance Insights: 2021-2023I built a Power BI dashboard with drill-through insights for Sports Basics analyzing 3 IPL seasons (2021-2023). Key metrics: 65,000+ runs, 2,300+ wickets. Tools: Python, MySQL, Power BI.
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Customer Complaint Analysis using Social Media Scraping
Customer Complaint Analysis using Social Media ScrapingExtracted Blinkit complaints from Twitter & LinkedIn using Selenium & BeautifulSoup. Handled dynamic login, post parsing, and engagement metrics to enable sentiment analysis and issue categorization for actionable customer insights.
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Customer Complaint Analysis using Social Media Scraping
Customer Complaint Analysis using Social Media ScrapingExtracted Blinkit complaints from Twitter & LinkedIn using Selenium & BeautifulSoup. Handled dynamic login, post parsing, and engagement metrics to enable sentiment analysis and issue categorization for actionable customer insights.
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Lok Sabha Elections 2024 Analysis for AtliQ Media
Lok Sabha Elections 2024 Analysis for AtliQ MediaDesigned an interactive Power BI dashboard for AtliQ Media to analyze the 2014 and 2019 Lok Sabha elections, emphasizing party performance, voter turnout, and demographic trends. Used Python for data manipulation and advanced visualizations.
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Lok Sabha Elections 2024 Analysis for AtliQ Media
Lok Sabha Elections 2024 Analysis for AtliQ MediaDesigned an interactive Power BI dashboard for AtliQ Media to analyze the 2014 and 2019 Lok Sabha elections, emphasizing party performance, voter turnout, and demographic trends. Used Python for data manipulation and advanced visualizations.
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Automated Flipkart Product Data Scraper
Automated Flipkart Product Data ScraperDeveloped a Python-based web scraper for Flipkart using Selenium, BeautifulSoup, tqdm, and Pandas to automate product data extraction. The scraper efficiently handles multi-page navigation, infinite scrolling, and stores structured data for analysis.
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Automated Flipkart Product Data Scraper
Automated Flipkart Product Data ScraperDeveloped a Python-based web scraper for Flipkart using Selenium, BeautifulSoup, tqdm, and Pandas to automate product data extraction. The scraper efficiently handles multi-page navigation, infinite scrolling, and stores structured data for analysis.
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Medals, Moments, and Milestones: A Timeline of the Olympic Games
Medals, Moments, and Milestones: A Timeline of the Olympic GamesDeveloped an interactive Power BI dashboard visualizing the Olympic Games' history with dynamic features like medal counts, milestones, and data storytelling. Utilized field parameters, conditional formatting, and interactive filters for a compelling user
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Medals, Moments, and Milestones: A Timeline of the Olympic Games
Medals, Moments, and Milestones: A Timeline of the Olympic GamesDeveloped an interactive Power BI dashboard visualizing the Olympic Games' history with dynamic features like medal counts, milestones, and data storytelling. Utilized field parameters, conditional formatting, and interactive filters for a compelling user
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Medical Insurance Charge Prediction Model
Medical Insurance Charge Prediction ModelDeveloped a Multiple Linear Regression model to predict medical insurance charges using features like age, BMI, and smoking habits. Included data preprocessing, EDA, feature engineering, and log transformation to improve model accuracy and stability.
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Medical Insurance Charge Prediction Model
Medical Insurance Charge Prediction ModelDeveloped a Multiple Linear Regression model to predict medical insurance charges using features like age, BMI, and smoking habits. Included data preprocessing, EDA, feature engineering, and log transformation to improve model accuracy and stability.
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Bike Rental Demand Prediction
Bike Rental Demand PredictionDeveloped a machine learning model to predict bike rental demand using weather, time, and environmental data. Applied EDA, feature engineering, and optimized Random Forest Regressor, achieving an R² of 0.72. Demonstrates end-to-end ML workflow proficiency
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Bike Rental Demand Prediction
Bike Rental Demand PredictionDeveloped a machine learning model to predict bike rental demand using weather, time, and environmental data. Applied EDA, feature engineering, and optimized Random Forest Regressor, achieving an R² of 0.72. Demonstrates end-to-end ML workflow proficiency
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