What Is Data Wrangling? The Key to Clean Data (VIDEO)
January 27, 2025
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2,748 already enrolled
Recommended experience
Intermediate level
RStudio and R Markdown, Perform data manipulation and visualization using R, Prior experience with time series analysis
Recommended experience
Intermediate level
RStudio and R Markdown, Perform data manipulation and visualization using R, Prior experience with time series analysis
Describe data to answer key questions to uncover insights
Fit well-validated time series models for forecasting future rental bikes demands
Provide analytic insights and data-driven recommendations
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In this project, you’ll help a bike rental company enhance its fleet management and pricing strategy by building a daily bike rental forecasting model using time series analysis techniques in R. Your objectives include loading, cleaning, processing, and analyzing daily rental transaction data, and developing and evaluating time series models for the most accurate predictions.
The company will use your validated forecasting model to determine the optimal number of bikes to keep in each station and set dynamic pricing based on predicted demand. Upon completion, you’ll be able to demonstrate your ability to perform a comprehensive data analysis project that involves answering critical business questions, extensive data visualization, and model selection. There isn’t just one right approach or solution in this scenario, which means you can create a truly unique project that helps you stand out to employers. ROLE: Data Analyst SKILLS: R, RStudio, Data Analysis, Data Modelling, Time Series Modelling, Data Interpretation PREREQUISITES: Load, clean, explore, manipulate, and visualize data using R Write code in RStudio and R Markdown Knowledge of time series
This project requires you to independently complete the following steps:
Load and explore the data
Create interactive time series plots
Smooth time series data
Decompose and assess the stationarity of time series data
Fit and forecast time series data using ARIMA models
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