Using Matlab, clean the data:

$1.$ Clean $/$ Scrub the $11$ days worth of data to prepare for MATLAB input. Note one file per day. Keep it that way

Deliverable $\backslash$#$1$: Plot an analysis of the RPM$,$ min and max battery temp for each day

$1.$ Analyze each file in matlab

$1.$ Compute and output a single value for each day:

$1.$ max motor RPM

$2.$ min battery temp

$3.$ max battery temp

$2.$ The output should be displayed to the screen, clearly, and concisely.

$3.$ Generate a plot of the three characteristics above. $($one data point per day$),$

$1.$ The $\backslash ($ x $\backslash )$ axis should correspond to the day $\backslash$# in the sequence, $($or date, if you feel challenged$)$ in some clear manner.

$2.$ Use engineering judgement: choose the most appropriate plot type, colors, markers, etc. Use Hahn and MATLAB help to provide options.

$3.$ Do think about which values do relate to each other? Which values are on a similar scale? have similar meaning? Which values make sense to compare to each other while which values do not? Which presentation is clearer for other engineers? Management? A customer?

$4.$ Each $\backslash ($ X$,$ Y $\backslash )$ pair being plotted should have a correspondence of one $\backslash ($ X $\backslash )$ value to each day, so that if you have $11$ days worth of data... so then you have $\backslash (11$ X$,$ Y $\backslash )$ pairs per variable.

Deliverable $\backslash$#$2$: Combine All $11$ Days Into One Large Matrix within Matlab

$1.$ Construct a single large matrix with all the data and days in chronological order. Do not worry about missing data days for this exercise.

$2.$ Use this matrix for

Deliverable $\backslash$#$3$: Generate a figure of vehicle movements

$1.$ Using this large and complete data set, Generate a figure that shows the vehicle movements

$1.$ based on the latitude and longitude values in the data for the entire data set of $11$ days.

$2.$ If you are not sure what latitude and longitude mean, please look them up$.$

$3.$ Explore the plot types to determine the best way to solve this

Deliverable $\backslash$#$4$: Plot the battery temp for violations

$1.$ Analyze this large data set for battery temperature violations defined as:

$1.$ Hotter than $80$ F

$2.$ Colder than $45$ F

$3.$ In your code, count the number of data samples that violate each criteria per day.

$4.$ Using each actual temperature measurement, $\_$count$\_$ the number of hot violations and the number of cold violations

$5.$ When dealing with the lowest temp analysis for a day or similar, use the "Lowest Battery Temp" field. When dealing with the highest temp analysis for a day or similar, use the "Highest Battery Temp" field.

$6.$ Plot these counts of violations per day.

$1.$ Analyze RPM$,$ min and max battery temp for each day $\backslash$& plot

$2.$ Combine All $11$ Days Into One Large Matrix using Matlab

$3.$ Generate a figure of vehicle movements:

$4.$ Analyze the battery temp for violations and visualize

$1=$ requires analysis, math, and plot

$2=$ analysis and maybe math

$\backslash (3=\backslash )$ a new plot

$4=$ more analysis, math, and new plot

So we are looking at generating three different figures.

The Data:

$40829$FebMarch$11$Days.zip $\backslash (\backslash$downarrow $\backslash )$

About the data:

$-$ This is a compressed zip file.

$-$ If you don't have familiarity with compressed files, please use the internet to assist you, ask your friends, or post to the discussions.

$-$ You will want to download the zip file.

$-$ You will want to explicitly "extract" or "uncompress" all the files and make sure those files end up being in the same directory as your matlab scripts.

$-$ Then you will have the original $11$ files.

Cleaning The Data:

$1.$ you will need to

$1.$ open each file in excel

$2.$ remove offending rows and columns $($As we did in previous assignments$).$

$3.$ Save each CSV file. Tip: Save each file as the same file name it has but add $"\_$cleaned" at the end, before the csv$.$ For example:

$"40829\_2213\_2019-03-15\_402115704.$csv$"$ might become

$"40829\_2213\_2019-03-15\_402115704\_$cleaned.csv$".$ The cleaned version of the file is what you will "load" into MATLAB.

$4.$ Note: this step might seem like a royal pain and a waste of your time, but you'll have to trust me when I say this is exactly the sort of thing you might do in the real world.

$($I$\text{'}$ve posted $1$ excel image. There are $11$ of similar files.$)$