Please write a program that would read battery time series data provided in $5$ attached csv files $($one file per battery$)$ and calculate:$1.$ Monthly average of percentage time for which Battery $001($data set under $001.$csv$)$ has its PW$\_$AvailableChargePower greater than or equal to its rated capacity of $3300$ W$.$ We call this metric $$charge power availability$.$ It signifies $\%$ time for which battery can charge at its rated$$v$1-10-10-2020$capacity if commanded to do so$.$ Please use a visualization of your choice to represent the output of this data. The audience for the visualization would be both a technical and non$-$technical audience.$2.$ Monthly charge power availability for Battery $001$ but excluding data points where charge power is below its rated value due to battery close to getting full $($i$.$e$.$ SOE $>90\%).$ Also, please provide a visualization to show the new monthly charge power availability.$3.$ Extend questions $2$ above to calculate monthly charge power availability for all $5$ batteries combined and again excluding data points where charge power is below its rated value due to battery close to getting full. Please provide a visualization to show this combined monthly charge power availability.$$We would strongly prefer the program to use Python but you can choose to write it in a language of your choice. Please send us back your output visualizations and your source code including readme instructions on how to run that code.