so this code should generate $5$ graphs but it only generates $4$ graphs and these errors keeps coming up that you see on the picture. I need figure $5$ graph to come up$.$ Could you please amek sure that all the errors are gone and all $5$ graphs that includes figure for come up$.$ Please use matlab to fix the code.

clearclc$\%\%$ EGME $205$: Digital Computation Project$\%\%$ Part $1$: Randomly Generated Data$\%$ Step $1$: First we need a date vector from January $1$st$,2024$ to December $31$st$,2024$start$\_$date $=$ datetime$(2024,1,1)$;end$\_$date $=$ datetime$(2024,12,31)$;date$\_$vector $=$ start$\_$date:end$\_$date;$\%$ Step $2$: Trying to find associated days of the weekdays$\_$of$\_$week $=$ day$($date$\_$vector, 'name'$)$;$\%$ Step $3$: Here is how to make a random temperature vectortemperature$\_$max $=120$;temperature$\_$min $=55$;temperature$\_$vector $=($temperature$\_$max $-$ temperature$\_$min$)*$ rand$($size$($date$\_$vector$))+$ temperature$\_$min;$\%$ Step $4$: Creating a string for the weekend daysweekend$\_$days $=$ string$($date$\_$vector$($weekday$($date$\_$vector$)==1|$ weekday$($date$\_$vector$)==7))$;$\%$ Step $5$: Development of more substance to the report$\%($a$)$ Here is a linear plot for weekends in which the temperature is over $100$weekend$\_$indices $=$ find$($temperature$\_$vector $>100$ & $($weekday$($date$\_$vector$)==1|$ weekday$($date$\_$vector$)==7))$;figure;plot$($date$\_$vector$($weekend$\_$indices$),$ temperature$\_$vector$($weekend$\_$indices$),\text{'}-$o$\text{'})$;title$(\text{'}$Weekend Temperatures over $100\text{'})$;xlabel$(\text{'}$Date$\text{'})$;ylabel$(\text{'}$Temperature$\text{'})$;$\%($b$)$ This section is a bar plot showing how many times the temperature is below $85$ in each monthmonths $=$ unique$($month$($date$\_$vector$))$;temperature$\_$below$\_85\_$count $=$ zeros$($size$($months$))$;for i $=1$:numel$($months$)$month$\_$indices $=$ find$($month$($date$\_$vector$)==$ months$($i$))$;temperature$\_$below$\_85\_$count$($i$)=$ sum$($temperature$\_$vector$($month$\_$indices$)<mtext\; id="EditorElement\_1757037"></mtext><mn\; id="EditorElement\_1757038">8</mn><mn\; id="EditorElement\_1757039">5</mn><mi\; id="EditorElement\_1757040">)</mi>$;endfigure;bar$($months$,$ temperature$\_$below$\_85\_$count$)$;title$(\text{'}$Count of Days with Temperature Below $85$ in Each Month'$)$;xlabel$(\text{'}$Month$\text{'})$;ylabel$(\text{'}$Count$\text{'})$;$\%($c$)$ Here we have two linear plots showing the maximum and minimum temperature in each monthmax$\_$temperature$\_$monthly $=$ accumarray$($month$($date$\_$vector$)\text{'},$ temperature$\_$vector', $[],$ @max$)$;min$\_$temperature$\_$monthly $=$ accumarray$($month$($date$\_$vector$)\text{'},$ temperature$\_$vector', $[],$ @min$)$;figure;plot$($months$,$ max$\_$temperature$\_$monthly, $\text{'}-$o$\text{'},$ 'DisplayName', 'Max Temperature'$)$;hold on;plot$($months$,$ min$\_$temperature$\_$monthly, $\text{'}-$o$\text{'},$ 'DisplayName', 'Min Temperature'$)$;hold off;title$(\text{'}$Monthly Maximum and Minimum Temperatures'$)$;xlabel$(\text{'}$Month$\text{'})$;ylabel$(\text{'}$Temperature$\text{'})$;legend$(\text{'}$Location$\text{'},$ 'best'$)$;$\%\%$ Part $2$: Imported Data$\%$ Step $1$: Import the two datasets and combine them into one global datasetdata$1=$ readtable$(\text{'}2021\_$Cars$\_$Aggregated.csv$\text{'})$; $\%$ Import the first datasetdata$2=$ readtable$(\text{'}2021.$Vans$\_$Aggregated.csv$\text{'})$; $\%$ Import the second dataset$\%$ Combine the datasetscombined$\_$data $=[$data$1$; data$2]$;$\%$ Step $2$a: Create a bar chart showing how many cars use distinct fuel types$\%$ Preprocess data: remove missing or empty values from 'FuelType' columnvalid$\_$indices $=$ ~ismissing$($combined$\_$data.FuelType$)$ & ~strcmp$($combined$\_$data.FuelType, $\text{'}\text{'})$;$\%$ Filter the combined data based on valid indicesvalid$\_$fuel$\_$data $=$ combined$\_$data$($valid$\_$indices, :$)$;$\%$ Get unique fuel types and count occurrences$[$fuel$\_$types, ~$,$ fuel$\_$type$\_$indices$]=$ unique$($valid$\_$fuel$\_$data.FuelType$)$;fuel$\_$counts $=$ histcounts$($fuel$\_$type$\_$indices, $1$:numel$($fuel$\_$types$)+1)$;$\%$ Plot the bar chartfigure;bar$(1$:numel$($fuel$\_$types$),$ fuel$\_$counts$)$;title$(\text{'}$Number of Cars Using Distinct Fuel Types'$)$;xlabel$(\text{'}$Fuel Type'$)$;ylabel$(\text{'}$Number of Cars'$)$;xticks$(1$:numel$($fuel$\_$types$))$;xticklabels$($fuel$\_$types$)$;$\%$ Step $2$b: Create a scatter plot showing the weighted CO$2$ Percentage for each car$[$sorted$\_$manufacturers, manufacturer$\_$indices$]=$ sort$($combined$\_$data.Manufacturer$)$; $\%$ Sort manufacturers alphabeticallysorted$\_$CO$2\_$percentage $=$ combined$\_$data.CO$2\_$Percentage$($manufacturer$\_$indices$)$; $\%$ Sort CO$2$ Percentage accordingly$\%$ Plot scatter plotfigure;scatter$(1$:numel$($sorted$\_$CO$2\_$percentage$),$ sorted$\_$CO$2\_$percentage$)$;hold on;$\%$ Fit a polynomial of degree $2$x$\_$values $=(1$:numel$($sorted$\_$CO$2\_$percentage$))\text{'}$; $\%$ Ensure x$\_$values is a column vectorsorted$\_$CO$2\_$percentage $=$ sorted$\_$CO$2\_$percentage$($:$)$; $\%$ Convert to column vectorp $=$ polyfit$($x$\_$values, sorted$\_$CO$2\_$percentage, $2)$;y$\_$fit $=$ polyval$($p$,$ x$\_$values$)$;plot$($x$\_$values, y$\_$fit, $\text{'}$r$--\text{'},$ 'LineWidth', $2)$;title$(\text{'}$Weighted CO$2$ Percentage for Each Car $($Sorted by Manufacturer$)\text{'})$;xlabel$(\text{'}$Car $($Sorted by Manufacturer$)\text{'})$;ylabel$(\text{'}$Weighted CO$2$ Percentage'$)$;legend$(\text{'}$Data Points', 'Line of Best Fit $($Degree $2)\text{'},$ 'Location', 'best'$)$;hold off;