7 datasets found
  1. Bellabeat case study using R

    • kaggle.com
    Updated Oct 29, 2022
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    R. Naga Amrutha (2022). Bellabeat case study using R [Dataset]. https://www.kaggle.com/datasets/rnagaamrutha/bellabeatcasestudywithr/suggestions?status=pending&yourSuggestions=true
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 29, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    R. Naga Amrutha
    Description

    Dataset

    This dataset was created by R. Naga Amrutha

    Contents

  2. Google Capstone Project - BellaBeats

    • kaggle.com
    Updated Jan 5, 2023
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    Jason Porzelius (2023). Google Capstone Project - BellaBeats [Dataset]. https://www.kaggle.com/datasets/jasonporzelius/google-capstone-project-bellabeats
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 5, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Jason Porzelius
    Description

    Introduction: I have chosen to complete a data analysis project for the second course option, Bellabeats, Inc., using a locally hosted database program, Excel for both my data analysis and visualizations. This choice was made primarily because I live in a remote area and have limited bandwidth and inconsistent internet access. Therefore, completing a capstone project using web-based programs such as R Studio, SQL Workbench, or Google Sheets was not a feasible choice. I was further limited in which option to choose as the datasets for the ride-share project option were larger than my version of Excel would accept. In the scenario provided, I will be acting as a Junior Data Analyst in support of the Bellabeats, Inc. executive team and data analytics team. This combined team has decided to use an existing public dataset in hopes that the findings from that dataset might reveal insights which will assist in Bellabeat's marketing strategies for future growth. My task is to provide data driven insights to business tasks provided by the Bellabeats, Inc.'s executive and data analysis team. In order to accomplish this task, I will complete all parts of the Data Analysis Process (Ask, Prepare, Process, Analyze, Share, Act). In addition, I will break each part of the Data Analysis Process down into three sections to provide clarity and accountability. Those three sections are: Guiding Questions, Key Tasks, and Deliverables. For the sake of space and to avoid repetition, I will record the deliverables for each Key Task directly under the numbered Key Task using an asterisk (*) as an identifier.

    Section 1 - Ask: A. Guiding Questions: Who are the key stakeholders and what are their goals for the data analysis project? What is the business task that this data analysis project is attempting to solve?

    B. Key Tasks: Identify key stakeholders and their goals for the data analysis project *The key stakeholders for this project are as follows: -Urška Sršen and Sando Mur - co-founders of Bellabeats, Inc. -Bellabeats marketing analytics team. I am a member of this team. Identify the business task. *The business task is: -As provided by co-founder Urška Sršen, the business task for this project is to gain insight into how consumers are using their non-BellaBeats smart devices in order to guide upcoming marketing strategies for the company which will help drive future growth. Specifically, the researcher was tasked with applying insights driven by the data analysis process to 1 BellaBeats product and presenting those insights to BellaBeats stakeholders.

    Section 2 - Prepare: A. Guiding Questions: Where is the data stored and organized? Are there any problems with the data? How does the data help answer the business question?

    B. Key Tasks: Research and communicate the source of the data, and how it is stored/organized to stakeholders. *The data source used for our case study is FitBit Fitness Tracker Data. This dataset is stored in Kaggle and was made available through user Mobius in an open-source format. Therefore, the data is public and available to be copied, modified, and distributed, all without asking the user for permission. These datasets were generated by respondents to a distributed survey via Amazon Mechanical Turk reportedly (see credibility section directly below) between 03/12/2016 thru 05/12/2016. *Reportedly (see credibility section directly below), thirty eligible Fitbit users consented to the submission of personal tracker data, including output related to steps taken, calories burned, time spent sleeping, heart rate, and distance traveled. This data was broken down into minute, hour, and day level totals. This data is stored in 18 CSV documents. I downloaded all 18 documents into my local laptop and decided to use 2 documents for the purposes of this project as they were files which had merged activity and sleep data from the other documents. All unused documents were permanently deleted from the laptop. The 2 files used were: -sleepDaymerged.csv -dailyActivitymerged.csv Identify and communicate to stakeholders any problems found with the data related to credibility and bias. *As will be more specifically presented in the Process section, the data seems to have credibility issues related to the reported time frame of the data collected. The metadata seems to indicate that the data collected covered roughly 2 months of FitBit tracking. However, upon my initial data processing, I found that only 1 month of data was reported. *As will be more specifically presented in the Process section, the data has credibility issues related to the number of individuals who reported FitBit data. Specifically, the metadata communicates that 30 individual users agreed to report their tracking data. My initial data processing uncovered 33 individual IDs in the dailyActivity_merged dataset. *Due to the small number of participants (...

  3. Capstone project appendix

    • zenodo.org
    Updated Apr 24, 2025
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    caelainn mcgowran; caelainn mcgowran (2025). Capstone project appendix [Dataset]. http://doi.org/10.5281/zenodo.10777164
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    Dataset updated
    Apr 24, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    caelainn mcgowran; caelainn mcgowran
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Data sets and r studio code used for capstone project

  4. Google Data Analytics Capstone

    • kaggle.com
    Updated Aug 9, 2022
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    Reilly McCarthy (2022). Google Data Analytics Capstone [Dataset]. https://www.kaggle.com/datasets/reillymccarthy/google-data-analytics-capstone
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 9, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Reilly McCarthy
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Hello! Welcome to the Capstone project I have completed to earn my Data Analytics certificate through Google. I chose to complete this case study through RStudio desktop. The reason I did this is that R is the primary new concept I learned throughout this course. I wanted to embrace my curiosity and learn more about R through this project. In the beginning of this report I will provide the scenario of the case study I was given. After this I will walk you through my Data Analysis process based on the steps I learned in this course:

    1. Ask
    2. Prepare
    3. Process
    4. Analyze
    5. Share
    6. Act

    The data I used for this analysis comes from this FitBit data set: https://www.kaggle.com/datasets/arashnic/fitbit

    " This dataset generated by respondents to a distributed survey via Amazon Mechanical Turk between 03.12.2016-05.12.2016. Thirty eligible Fitbit users consented to the submission of personal tracker data, including minute-level output for physical activity, heart rate, and sleep monitoring. "

  5. Google Coursera Capstone-Cyclistic Data

    • kaggle.com
    Updated Jul 16, 2022
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    Bharat R (2022). Google Coursera Capstone-Cyclistic Data [Dataset]. http://doi.org/10.34740/kaggle/dsv/3949354
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 16, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Bharat R
    License

    https://cdla.io/permissive-1-0/https://cdla.io/permissive-1-0/

    Description

    The uploaded Dataset contains cyclistic from 2021/06 to 2022/05. The Data has been downloaded from the below link: https://divvy-tripdata.s3.amazonaws.com/index.html Licence information is given below: https://ride.divvybikes.com/data-license-agreement

    This data is downloaded as part of Google Professional Data Analytics Certification for the final Capstone Project.

    Data Cleaning activities carried out in the notebook:

    1. Mapped start and end station IDs from latitude and longitude data.
    2. Rows where Data is not available (NaN) has been removed.

    The final data can be used for analysis. Kindly let me know your comments

  6. d

    Data for: Integrating open education practices with data analysis of open...

    • search.dataone.org
    • data.niaid.nih.gov
    • +1more
    Updated Jul 27, 2024
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    Marja Bakermans (2024). Data for: Integrating open education practices with data analysis of open science in an undergraduate course [Dataset]. http://doi.org/10.5061/dryad.37pvmcvst
    Explore at:
    Dataset updated
    Jul 27, 2024
    Dataset provided by
    Dryad Digital Repository
    Authors
    Marja Bakermans
    Description

    The open science movement produces vast quantities of openly published data connected to journal articles, creating an enormous resource for educators to engage students in current topics and analyses. However, educators face challenges using these materials to meet course objectives. I present a case study using open science (published articles and their corresponding datasets) and open educational practices in a capstone course. While engaging in current topics of conservation, students trace connections in the research process, learn statistical analyses, and recreate analyses using the programming language R. I assessed the presence of best practices in open articles and datasets, examined student selection in the open grading policy, surveyed students on their perceived learning gains, and conducted a thematic analysis on student reflections. First, articles and datasets met just over half of the assessed fairness practices, but this increased with the publication date. There was a..., Article and dataset fairness To assess the utility of open articles and their datasets as an educational tool in an undergraduate academic setting, I measured the congruence of each pair to a set of best practices and guiding principles. I assessed ten guiding principles and best practices (Table 1), where each category was scored ‘1’ or ‘0’ based on whether it met that criteria, with a total possible score of ten. Open grading policies Students were allowed to specify the percentage weight for each assessment category in the course, including 1) six coding exercises (Exercises), 2) one lead exercise (Lead Exercise), 3) fourteen annotation assignments of readings (Annotations), 4) one final project (Final Project), 5) five discussion board posts and a statement of learning reflection (Discussion), and 6) attendance and participation (Participation). I examined if assessment categories (independent variable) were weighted (dependent variable) differently by students using an analysis of ..., , # Data for: Integrating open education practices with data analysis of open science in an undergraduate course

    Author: Marja H Bakermans Affiliation: Worcester Polytechnic Institute, 100 Institute Rd, Worcester, MA 01609 USA ORCID: https://orcid.org/0000-0002-4879-7771 Institutional IRB approval: IRB-24–0314

    Data and file overview

    The full dataset file called OEPandOSdata (.xlsx extension) contains 8 files. Below are descriptions of the name and contents of each file. NA = not applicable or no data available

    1. BestPracticesData.csv
      • Description: Data to assess the adherence of articles and datasets to open science best practices.
      • Column headers and descriptions:
        • Article: articles used in the study, numbered randomly
        • F1: Findable, Data are assigned a unique and persistent doi
        • F2: Findable, Metadata includes an identifier of data
        • F3: Findable, Data are registered in a searchable database
        • A1: ...
  7. BellaBeat Case

    • kaggle.com
    Updated Apr 21, 2025
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    Nilay işimtekin (2025). BellaBeat Case [Dataset]. https://www.kaggle.com/datasets/nilayiimtekin/bellabeat-case/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 21, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Nilay işimtekin
    Description

    This Dataset is about BellaBeat smart device products. Bellabeat is a successful small company, but they have the potential to become a larger player in the global smart device market. Analyzing fitness smart device will help us explore possible growth opportunities for the company. This Data analysis made by using R programming and Excel will help us identify the trends and make recommendations based on our analysis.

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R. Naga Amrutha (2022). Bellabeat case study using R [Dataset]. https://www.kaggle.com/datasets/rnagaamrutha/bellabeatcasestudywithr/suggestions?status=pending&yourSuggestions=true
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Bellabeat case study using R

Google Data Analytics Capstone Project

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Oct 29, 2022
Dataset provided by
Kagglehttp://kaggle.com/
Authors
R. Naga Amrutha
Description

Dataset

This dataset was created by R. Naga Amrutha

Contents

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