This project is doing an analysis with R for "Human Activity Recognition Using Data set".

Whole data set comes from kaggle-gpu-images

For more explanation,please read "README.txt" and "features_info.txt" in the package of the data set.

1: Load the data in RStudio

2: Merge data sets Merge the training and the test sets to create one data set.

3: Mean and standard deviation Create two new columns, containing the mean and standard deviation for each measurement respectively.

4: Add new variables Create variables called ActivityLabel and ActivityName that label all observations with the corresponding activity labels and names respectively

5: Create tidy data set 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.

1.For detail of data processing procedure,please read "CodeBook.md".

2.Some explanations for the data manipulation methods

• In merging section,I used a new column "train_test" as an identifier in all new merged dataframes.Then people still can identify which data record comes from train or from test.
• Subject_all,y_all and xdata_all will finally merge together to form into a new dataframe "subject_activity_features_all",which can be used to create a tidy dataframe for task 5.So I just put "train_test" column into y_train and y_test.
• For measurement data files such as "body_acc_x_train.txt",I add "train_test" column into related dataframes when I read thme into R.
• For task 3, I used related feature variables in xall_data to generate two columns of the mean and standard deviation for two kinds of dataframe:the body acceleration signal and the angular velocity vector. I did not find related features in xall_data for the total acceleration signal. *To do task 4,I create a new column "activity_name" for y_all,and merge subject_all,y_all and xdata_all into subject_activity_features_all. *To generate a tidy dataframe,I used aggregate function on subject_activity_features_all to create a tidy data set:tidy_data,and write it to a output .csv file"tidy_data.csv".