The explanation for each column is as given below:

$1)$ price $-$ price in US dollars $($$$326$ $$18,823)$

$2)$ carat $-$ weight of the diamond $(0\mathrm{.}25\mathrm{.}01)$

$3)$ cut $-$ quality of the cut $($Fair$,$ Good, Very Good, Premium, Ideal$)$

$4)$ color $-$ diamond colour, from J $($worst$)$ to D $($best$)$

$5)$ clarity $-$ a measurement of how clear the diamond is $($I$1($worst$),$ SI$2,$ SI$1,$ VS$2,$ VS$1,$ VVS$2,$ VVS$1,$ IF $($best$))$

$6)$ x $-$ length in mm $(010\mathrm{.}74)$

$7)$ y $-$ width in mm $(058\mathrm{.}9)$

$8)$ z $-$ depth in mm $(031\mathrm{.}8)$

$9)$ depth $-$ total depth percentage $=$ z $/$ mean$($x$,$ y$)=2*$ z $/($x $+$ y$)(4379)$

$10)$ table $-$ width of top of diamond relative to widest point $(4395)$

Task $1$

i$)$ Load the "diamonds" dataset from the Seaborn package to an object.

ii$)$ Find the datatype of the object into which you have loaded the "diamonds" dataset.

iii$)$ View the top $5$ and bottom $5$ rows of the data.

iv$)$ Get the dimensions of the data. Find the number of rows and columns in the data.

v$)$ Display the structure of the data $$ all column names along with their data types.

vi$)$ Display the summary statistics of all the columns in your data.

Hint: Explore the functions available in pandas dataframe to perform tasks iii$-$vi$.$