#$2.$Build an app that will take a file number and read in one of the PPG Data$\_$#$.$csv files and determine what percentage of each file's mean normalized magnitude of Acceleration is in a period of at least $3$ seconds long with the Normalized Magnitude being within the threshold. Use a moving window of $3$ sec $(300$ samples$)$ to find low$-$activity sections. Assign the low$-$activity sections a value of $1$ and all other periods, the high$-$activity sections, a value of $0.$ Note the high$-$activity sections can be less than $300$ samples. Be sure to drop the first $8$ rows of data from the pandas data frame to eliminate the corrupted "warm$-$up$"$ data at the beginning of each data file.

Show graphically when magnitude is within or not within the low$-$activity range. See Plot $4$ example $($note this example was done on multiple files put together and used instead a $10$ second window.

You App should build the file path to read using an integer input variable that is the file number.

Simplified Grading Scheme:

$10$ pts for completely correct solution with good coding practices

$7$ pts for an incorrect solution but a solid attempt and good coding

$5$ pts for a reasonable attempt

$0$ pts for no attempt or a trivial attempt.

#$3.$

Starting with the solution for HW#$2$ add an additional section of code that calculates the BPM heart rate only for beats where there is exactly $1$ peak in between the adjacent troughs. Now recalculate this new heart rate, BPM$2,$ and display it's average and standard deviation for the ~$40$ second interval $($output to console with $2$ decimal places and properly labeled$).$ do this for file number $9.$ You only need to do this for the IR channel $($remembering that IR and red are mislabeled$).$