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dmat/CleaningDataProject

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CleaningDataProject

This README files explains how the run_analysis.R is implemented to complete the project work

First, it reads features.txt file to get descriptive variable names. Then a subset of variable names that has mean or std is filtered This is to meet the requirement for Step 4.

The next step is to read the training data and merge Subject, Activity and Feature data frames.

Next, the test data set is read and merged Subject, Activity and Feature data frames

Once both Test and Training data set is prepared with Subject, Activity and Feature variables, both test and Training data frames were merged to one data frame called mData During the merge, only the feature variable with mean or std is inlcuded

Then the merged data frame is sorted by Subject

Then the data frame is grouped by Subject and Activity and average of Feature variable is calculated. The summary result is the written to a file called project_step5_result.txt

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