title | output |
---|---|
CodeBook.md |
html_document |
It is assumed that the data was downloaded and unzipped in a folder, prior to analysis
This code needs to be in a folder parallel to UCI folder (at the same level)
Description of the run_analysis.R process:
-
Loads library
plyr
anddplyr
-
Creates results folder
-
defines 2 helper functions, one to read a table, and assign given column names, and one to read a train or test complete set
-
Loads feature data set
features.txt
used for columns names for actual data table -
Loads and appends train dataset using
X_train.txt
,y_train.txt
,subject_train.txt
subject_train
contains the ids for each subject (1..30)y_train
contains the activity labels (1..6)X_train
contains the data using the feature data set as columns
-
Loads and appends test dataset using
X_test.txt
,y_test.txt
,subject_test.txt
subject_test
contains the idsy_test
contains the activity labelsX_test
contains the data using the feature data set as columns
-
concatenates train and test data
-
Rearrange the data using id
-
Loading activity labels
activity_labels.txt
-
Changes the data activity row to use the activity labels
-
Extracts the
mean
,std
into tidyset1 -
applies ddply to compute means for all variables, using id and activity
-
appends
_mean
to all data columns names -
saves the tidy dataset2 into
results/tidyset2.txt
The tidyset2 will contain 180 rows, for 30 subjects and 6 activities each, and one
header row.
There are 81 columns, first for id of the subject and second for the activity.
The rest of 79 columns contain the mean of all variables that contain std or mean
in their original feature name.
The names of the variables are formed by appending
"_mean" to the original names
There are no changes to the units, compared to the original feature files.
Because the features are normalized, they are all a-dimensional, and all
values are between [-1, 1]. All the means calculated by this exercise will
be between 1 and -1.
[1] "id"
[2] "activity"
[3] "tBodyAcc.std...X_mean"
[4] "tBodyAcc.std...Y_mean"
[5] "tBodyAcc.std...Z_mean"
[6] "tGravityAcc.std...X_mean"
[7] "tGravityAcc.std...Y_mean"
[8] "tGravityAcc.std...Z_mean"
[9] "tBodyAccJerk.std...X_mean"
[10] "tBodyAccJerk.std...Y_mean"
[11] "tBodyAccJerk.std...Z_mean"
[12] "tBodyGyro.std...X_mean"
[13] "tBodyGyro.std...Y_mean"
[14] "tBodyGyro.std...Z_mean"
[15] "tBodyGyroJerk.std...X_mean"
[16] "tBodyGyroJerk.std...Y_mean"
[17] "tBodyGyroJerk.std...Z_mean"
[18] "tBodyAccMag.std.._mean"
[19] "tGravityAccMag.std.._mean"
[20] "tBodyAccJerkMag.std.._mean"
[21] "tBodyGyroMag.std.._mean"
[22] "tBodyGyroJerkMag.std.._mean"
[23] "fBodyAcc.std...X_mean"
[24] "fBodyAcc.std...Y_mean"
[25] "fBodyAcc.std...Z_mean"
[26] "fBodyAccJerk.std...X_mean"
[27] "fBodyAccJerk.std...Y_mean"
[28] "fBodyAccJerk.std...Z_mean"
[29] "fBodyGyro.std...X_mean"
[30] "fBodyGyro.std...Y_mean"
[31] "fBodyGyro.std...Z_mean"
[32] "fBodyAccMag.std.._mean"
[33] "fBodyBodyAccJerkMag.std.._mean"
[34] "fBodyBodyGyroMag.std.._mean"
[35] "fBodyBodyGyroJerkMag.std.._mean"
[36] "tBodyAcc.mean...X_mean"
[37] "tBodyAcc.mean...Y_mean"
[38] "tBodyAcc.mean...Z_mean"
[39] "tGravityAcc.mean...X_mean"
[40] "tGravityAcc.mean...Y_mean"
[41] "tGravityAcc.mean...Z_mean"
[42] "tBodyAccJerk.mean...X_mean"
[43] "tBodyAccJerk.mean...Y_mean"
[44] "tBodyAccJerk.mean...Z_mean"
[45] "tBodyGyro.mean...X_mean"
[46] "tBodyGyro.mean...Y_mean"
[47] "tBodyGyro.mean...Z_mean"
[48] "tBodyGyroJerk.mean...X_mean"
[49] "tBodyGyroJerk.mean...Y_mean"
[50] "tBodyGyroJerk.mean...Z_mean"
[51] "tBodyAccMag.mean.._mean"
[52] "tGravityAccMag.mean.._mean"
[53] "tBodyAccJerkMag.mean.._mean"
[54] "tBodyGyroMag.mean.._mean"
[55] "tBodyGyroJerkMag.mean.._mean"
[56] "fBodyAcc.mean...X_mean"
[57] "fBodyAcc.mean...Y_mean"
[58] "fBodyAcc.mean...Z_mean"
[59] "fBodyAcc.meanFreq...X_mean"
[60] "fBodyAcc.meanFreq...Y_mean"
[61] "fBodyAcc.meanFreq...Z_mean"
[62] "fBodyAccJerk.mean...X_mean"
[63] "fBodyAccJerk.mean...Y_mean"
[64] "fBodyAccJerk.mean...Z_mean"
[65] "fBodyAccJerk.meanFreq...X_mean"
[66] "fBodyAccJerk.meanFreq...Y_mean"
[67] "fBodyAccJerk.meanFreq...Z_mean"
[68] "fBodyGyro.mean...X_mean"
[69] "fBodyGyro.mean...Y_mean"
[70] "fBodyGyro.mean...Z_mean"
[71] "fBodyGyro.meanFreq...X_mean"
[72] "fBodyGyro.meanFreq...Y_mean"
[73] "fBodyGyro.meanFreq...Z_mean"
[74] "fBodyAccMag.mean.._mean"
[75] "fBodyAccMag.meanFreq.._mean"
[76] "fBodyBodyAccJerkMag.mean.._mean"
[77] "fBodyBodyAccJerkMag.meanFreq.._mean"
[78] "fBodyBodyGyroMag.mean.._mean"
[79] "fBodyBodyGyroMag.meanFreq.._mean"
[80] "fBodyBodyGyroJerkMag.mean.._mean"
[81] "fBodyBodyGyroJerkMag.meanFreq.._mean"