Solve the following set of problems using Python and submit the code file

with extension $.$ipynb.

$1.$ Read $$Sensor readings, with temperature, light, humidity every $5$ minutes at $8$

locations $($trial$,2014$ to $2015)$ and print the feature name with numbers of missing

entries.

$2.$ Fill in the missing entries. For filling any feature, you can use either the mean or

median value of the feature values from observed entries. Explain the reason behind

your choice and print replacement value of each feature.

$3.$ Use a histogram to show the distribution of the variable $$location$.$ Explain the

distribution and show how many locations are there in total.

$4.$ Encode the categorical variable $$location$"$ using an appropriate encoding approach

and display the encoded values. Justify your selection of encoding approaches.

$5.$ Apply the min$-$max scaling on features $"[$boardtype$,$ boardid $,$temp$\_$max, temp$\_$min,

temp$\_$avg,light$\_$max, light$\_$min,light$\_$avg, humidity$\_$min, humidity$\_$max,

humidity$\_$avg$]".$ Plot distribution of first six features before and after scaling. Is there

any difference? Please explain.