tidyFitData:Coursera上获取和清理数据的编程项目

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  • 2022-06-15 03:22
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整洁的拟合数据 Coursera上获取和清理数据的编程项目 该项目的目的是展示您收集、处理和清理数据集的能力。 目标是准备可用于以后分析的整洁数据。 目前所有数据科学中最令人兴奋的领域之一是可穿戴计算——例如参见本文。 Fitbit、Nike 和 Jawbone Up 等公司正在竞相开发最先进的算法来吸引新用户。 从课程网站链接到的数据代表从三星 Galaxy S 智能手机的加速度计收集的数据。 获取数据的站点提供了完整的描述: 以下是该项目的数据: run_analysis.R 执行以下操作。 合并训练集和测试集以创建一个数据集。 仅提取每个测量值的平均值和标准偏差的测量值。 使用描述性活动名称来命名数据集中的活动 使用描述性变量名称适当地标记数据集。 根据步骤 4 中的数据集,创建第二个独立的 tidy 数据集,其中包含每个活动和每个主题的每个变量的平均值。
tidyFitData-master.zip
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内容介绍
# tidyFitData Programming project for Getting and Cleaning Data on Coursera The purpose of this project is to demonstrate your ability to collect, work with, and clean a data set. The goal is to prepare tidy data that can be used for later analysis. One of the most exciting areas in all of data science right now is wearable computing - see for example this article . Companies like Fitbit, Nike, and Jawbone Up are racing to develop the most advanced algorithms to attract new users. The data linked to from the course website represent data collected from the accelerometers from the Samsung Galaxy S smartphone. A full description is available at the site where the data was obtained: http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones Here are the data for the project: https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip run_analysis.R does the following. * Merges the training and the test sets to create one data set. * Extracts only the measurements on the mean and standard deviation for each measurement. * Uses descriptive activity names to name the activities in the data set * Appropriately labels the data set with descriptive variable names. * From the data set in step 4, creates a second, independent tidy data set with the average of each variable for each activity and each subject.
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