This project analyzes an Uber drive dataset to extract insights about ride patterns, trip purposes, and distance distributions. The goal is to understand how Uber trips are utilized and to visualize key trends in ride data.

Uber Technologies, Inc., commonly known as Uber, is an American technology company. Its services include ride-hailing, food delivery, package delivery, couriers, freight transportation, and, through a partnership with Lime, electric bicycle and motorized scooter rental.

Uber drives analysis

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Data Analysis Practice using python

The project is based on the trips made by Uber drivers. Different aspects of the trip are analysed by using different functions in Python.

Here i have done a detailed data analysis on uber ride dataset collected from Kaggle

🚗 Analyze Uber trip data to uncover travel patterns, peak times, and trip purposes, delivering insights for informed business decisions.

This is Python Portfolio Data Analysis Project using Uber dataset from kaggle.

Data Science

Driver churn analysis based on Uber dataset using big data tools such as Hive, PySpark, Pig, Hbase, and MongoDB.

The project is based on the trips made by Uber drivers. Here, we are analyzing different aspects of the trips by doing Exploratory Data Analysis.

This is a python oriented data manipulation and visualization project on the data set provided by Uber .The main python libraries such as Numpy and Pandas as used for data manipulation along with various visualization libraries.

Data Visualization and Analysis of Uber Drives Using Python.

Utilized Python, Pandas, and NumPy for data preprocessing and feature engineering. Applied K-Means clustering to segment drivers based on ride metrics. Used Seaborn and Matplotlib for data visualization. Conducted business analysis to derive actionable insights for driver retention, dynamic pricing, and performance optimization.

On working this Project ,I have gathered some amazing insights from the dataset of 'Uber Drive'. I have used Jupyter Notebook to perform data analysis and visualization.

Analysis for Uber drives

uber drive analysis project

Python for Data Science Project: Analyzes Uber trip data to identify travel patterns, popular routes, trip purposes, and business vs. personal usage using Python, Pandas, and Seaborn for data analysis and visualization.

Uber Drive Data Analysis Project

Data Analysis on Uber Drive

EDA Analysis on Income of Uber Driver.

Exploratory Data Analysis for Uber Drives

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An analysis of Uber drives made using various python libraries

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Analyzing a dataset of Uber trips.

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This Uber Drives dataset contains 1,155 Uber drives from the USA, Sri Lanka and Pakistan during the year 2016. The total distance covered in these drives is 12,204 miles.