could you provide python and R code and explanation to the following; $1.$ Load the data, calculate the percentage of missing data, calculate basic statistics $($e$.$g$.,$ mean, variance, Lskewness, etc.$),$ calculate probability dry, and plot the time series.

$2.$ Calculate annual maxima series at an hourly scale

$3.$ Aggregate the hourly precipitation to $3-$hr$,6-$hr$,12-$hr$,1-$day, $7-$day, and $15-$day time scales and calculate

basic statistics, probability dry, and annual maxima series at these scales. Comment on the changing

statistics.

$4.$ Fit a distribution to the annual maxima series and justify why you chose that distribution

$5.$ What are the other methods to obtain extreme events $($other than annual maxima$)$ and what are the

advantages and disadvantages of each method?

$6.$ Prepare Intensity$-$Duration$-$Frequency $($IDF$)$ relationships for this station and comment on changing

precipitation over the time scale

$7.$ Using the IDF relationships, construct a synthetic hydrograph and calculate the runoff at an arbitrary basin

$($assume required parameters, such as area of the basin, etc., to construct the hydrograph$)$ for hourly

precipitation.

$8.$ Note down the uncertainties possible in the runoff during this process $($hint: uncertainty with the

assumption of the probability distribution, data errors, missing values, etc.$)$

$9.$ If the same process is to be repeated in $10,000$ precipitation files, how do you automate the code $($that is$,$

from reading the data, obtaining IDF relationships, constructing synthetic hydrographs, and obtaining

runoff$)?$

$10.$ Calculate the autocorrelation structure for different time scales and comment on the changing

autocorrelation

$11.$ Calculate the scaling $($simple$)$ relationship of precipitation for this station Comment on

the type of scaling.