Create two $2-$dimensional NumPy array of $2$ rows and $5$ columns with values ranging from $-5$ to $5($inclusive$)$ with a step size of $1($Hint: Use np$.$reshape$(),$ np$.$array$())(25$ points

a$.$ Compute the Euclidean distance for each point $\backslash ((\backslash$mathrm$\{$X$\},\backslash$mathrm$\{$Y$\})\backslash )$ from the origin $\backslash ((0,0)\backslash ).($Hint: euclidean distance $\backslash (\backslash$left$.=\backslash$operatorname$\{$sqrt$\}\backslash$left$(($x $2-$x $1)^\{\backslash$wedge$\}2+($y $2-$y $1)^\{\backslash$wedge$\}2\backslash$right$)\backslash$right$)\backslash ).$ Expected output is a $2$ X $5$ numpy array, with each value representing the distance from the origin

$($give them the sample matrices$)$

b$.$ Create a new $2-$Dimensional array Z with same number of rows and columns and use Conditional Logic for array operations to:

$-$ Assign $\backslash ($ Z$[$i$,$ j$]=1\backslash )$ for points whose distance is less than $5.$

$-$ Assign $\backslash ($ Z$[$i$,$ j$]=2\backslash )$ for points whose distance is between $5$ and $10.$

$-$ Assign $\backslash ($ Z$[$i$,$ j$]=3\backslash )$ for points whose distance is greater than $10.$

c$.$ Find and print the minimum value, maximum value, cumulative sum, cumulative product, arithmetic mean, sum, standard deviation, variance, Indices of Minimum and and Maximum Elements of the Array Z$.$