$$

Open the Report.ipynb in this folder.

$$ Create a DataFrame that contains the data in balance.txt$.$

$$ Write the code needed to produce a report that provides the following

information:

$$ Compare the average income based on ethnicity.

$$ On average, do married or single people have a higher balance?

$$ What is the highest income in our dataset?

$$ What is the lowest income in our dataset?

$$ How many cards do we have recorded in our dataset? $($Hint: use

sum$())$

$$ How many females do we have information for vs how many males?

$($Hint: use count$().In[]$:

$In[]$:

$\frac{?}{?}$# Import pandas

Write the code needed to produce a report that provides the following information:

Compare the average income based on ethnicity.

On average, do married or single people have a higher balance?

What is the highest income in our dataset?

What is the lowest income in our dataset?

How many cards do we have recorded in our dataset? $($Hint: use sum$())$

How many females do we have information for vs how many males? $($Hint: use count $()$ for a list of all methods for computation of descriptive stats,

explore the pandas documentation$).$ "Balance" "Income" "Limit" "Rating" "Cards" "Age" "Education" "Gender" "Student" "Married" "Ethnicity"

$12\mathrm{.}240798476047414\mathrm{.}891360628323411$ "Male" $"$No$"$ "Yes" "Caucasian"

$23\mathrm{.}2833339223376106\mathrm{.}025664548338215$ "Female" "Yes" "Yes" "Asian"

$22\mathrm{.}5304088790893104\mathrm{.}593707551447111$ "Male" $"$No$""$No$"$ "Asian"

$27\mathrm{.}652810710665148\mathrm{.}924950468133611$ "Female" $"$No$""$No$"$ "Asian"

$16\mathrm{.}893978490488855\mathrm{.}882489735726816$ "Male" $"$No$"$ "Yes" "Caucasian"

$22\mathrm{.}486177612391380\mathrm{.}18804756947710$ "Male" $"$No$""$No$"$ "Caucasian"

$10\mathrm{.}574516436759520\mathrm{.}996338825923712$ "Female" $"$No$""$No$"$ "African American"

$14\mathrm{.}576204351288471\mathrm{.}40871145122879$ "Male" $"$No$""$No$"$ "Asian"

$7\mathrm{.}9380902950025215\mathrm{.}125330026656613$ "Female" $"$No$""$No$"$ "Caucasian"

$17\mathrm{.}756964869700771\mathrm{.}061681949134119$ "Female" "Yes" "Yes" "African American"

$13\mathrm{.}994989533288763\mathrm{.}095811758943014$ "Male" $"$No$"$ "Yes" "Caucasian"

$9\mathrm{.}4673077055935115\mathrm{.}045131113836416$ "Male" $"$No$""$No$"$ "Caucasian"

$19\mathrm{.}218800319270280\mathrm{.}61653083941577$ "Female" $"$No$"$ "Yes" "Asian"

$10\mathrm{.}698983739476443\mathrm{.}68269225111499$ "Male" $"$No$"$ "Yes" "Caucasian"

$9\mathrm{.}893532973868519\mathrm{.}144329126927513$ "Female" $"$No$""$No$"$ "African American"

$10\mathrm{.}045128133111420\mathrm{.}089252520035715$ "Female" $"$No$"$ "Yes" "African American"

$15\mathrm{.}248771948805953\mathrm{.}598371428637317$ "Female" $"$No$"$ "Yes" "African American"

$12\mathrm{.}960884748427536\mathrm{.}496437833936915$ "Female" $"$No$"$ "Yes" "Asian"

$11\mathrm{.}573778050705749\mathrm{.}5763844481289$ "Female" $"$No$"$ "Yes" "Asian"

$13\mathrm{.}236248932339642\mathrm{.}07966264792449$ "Male" $"$No$""$No$"$ "Asian"

$9\mathrm{.}8531004102590517\mathrm{.}7286023546316$ "Female" $"$No$""$No$"$ "Asian"

$13\mathrm{.}595776015492637\mathrm{.}348637845817217$ "Female" $"$No$""$No$"$ "Caucasian"

$9\mathrm{.}4165094391394320\mathrm{.}103263121336110$ "Male" $"$No$"$ "Yes" "African American"

$16\mathrm{.}302533422681464\mathrm{.}02751793985488$ "Male" $"$No$"$ "Yes" "African American"

$6\mathrm{.}1609481530147110\mathrm{.}742175715635715$ "Female" $"$No$""$No$"$ "Caucasian"

$8\mathrm{.}2325139512632914\mathrm{.}09432332652516$ "Female" $"$No$"$ "Yes" "African American"

$14\mathrm{.}959915539251842\mathrm{.}471362528964412$ "Female" "Yes" $"$No$"$ "Caucasian"

$12\mathrm{.}608460765659932\mathrm{.}793453433324416$ "Male" $"$No$""$No$"$ "African American"

$35\mathrm{.}2710114972418186\mathrm{.}6341341494924114$ "Female" $"$No$"$ "Yes" "African American"

$14\mathrm{.}007769590834326\mathrm{.}813561141145516$ "Female" $"$No$""$No$"$ "Caucasian"

$10\mathrm{.}201523484686734\mathrm{.}14256664134475$ "Female" $"$No$"$ "Yes" "Caucasian"

$11\mathrm{.}464864084439728\mathrm{.}941273321054316$ "Male" $"$No$"$ "Yes" "Asian"