This is the assignment for 4th week of the 3rd course in DataScience specialization by Johns Hopkins.
- run_analysis.R:The only script in the project the performs all the requirements for the project
- Codebook.md:the code book the describes the variables.
The script consists of 3 main parts:
- Getting the data ready: in this part the script downloads the zipped file and unzip it.
- Reading the data: in this section we simply read the .txt files from the downloaded folder.
- Performing the requirements: performing the 5 steps required which will be listed in the following:
1-Merging data together: after reading the data from each file, it's time to merge the data togther by merging the train and the test then binding both with each other making a full dataframe.
2-Extracting measurements for mean and std: in this step we only pick the mean and standrad deviation features from our dataset and leave everything else.
3/4-Renaming activities/features in the tidy dataframe: It's time to give meaningful names to our dataset, by renaming the columns refering to activities and our features as they contain a lot of abbriviations that might be confusing to others.
5-creating the second tidy dataset: The last requirement and the final dataset , is another one that is grouped by certain columns that contains means for all features for each of the grouped columns.
The last part is just writing the dataset to a file.