Need help with the assignment below. Only on Step 1 and Step2 in section work. Please see the attached document

Need help with the assignment below. Only on Step 1 and Step2 in section work. Please see the attached document
Eastern Illinois University Department of Mathematics and Computer Science CSM 4370 – Topics in Computer Science ` Assignment 1 : Rectangular Dataset Due date: September 21 , 2021 Get a feel for data and where to find them . Get your hands dirty with JavaScript and D3.js 1. Online tutorials ➢ JavaScript: W3Schools.com ➢ D3: freeCodeCamp , D3 website , github makeBarChart ScottMurray exampleHub Some Good Sources for Data Kaggle – lots of data for data science Illinois Open Data – all kinds of data related to Illinois operations Kaiser Foundation – numerous data related to public health Data.gov – open data site with US government data Forbes – site with links to data sites Data Quest – another site with links to data sites Quandl – mostly financial and economics data Open Data Inception – map w/data portals around the world World Bank – collection of global development data 2. Notes on Dataset ▪ Avoid datasets where the majority o f data is categorical (not overly exciting for binning, clustering, and so on) ▪ If an attribute is categorical it should have at least 6 categories o Some important variables may have fewer levels, such as gender (OK) ▪ Convert textual categories into numbers b y assigning a numerical ID ▪ Aim for datasets with more than 500 data points and 8 attributes ▪ If your dataset is larger, pick 500 sample points at random (for now) ▪ If you have too many attributes keep the ones of interest (prefer quantitative attributes) Eastern Illinois University Department of Mathematics and Computer Science CSM 4370 – Topics in Computer Science ` ▪ If the data set has text, images, video, logs, etc. convert them to numbers via appropriate mechanism as discussed in class (this would be an advanced task, so you may want to avoid data like this) ▪ Produce a spreadsheet of rows (data items) and attributes (co lumns) 3. Various Notes Fusing data from two (or more) sources can yield interesting datasets ▪ You would have the same data points, just more attributes –> the attributes from both datasets ▪ Goal: find two or more datasets that can bring deeper and more compre hensive insight, broadening the theme Examples: ▪ A dataset with crime data for all US States + datasets with state -wise average incomes, education levels, or unemployment rates might provide interesting insights on the causes of certain crimes ▪ A dataset with the weather per day at a set of cities + a dataset that has the on -time performances per day for the airports in these cities may provide insight on the reasons for the time delays 4. work Step 1: Get some CSV -based data (also see previous sli des) ▪ at least 250 data points, but ideally at least 500 ▪ at least 15 dimensions (fuse datasets to achieve this) ▪ good mix of numerical and categorical variables Step 2: Your D3 -based visual interface should be able to ▪ present a menu to allow users to select a variable and update chart ▪ draw a bar chart if a categorical variable is selected ▪ draw a histogram if a numerical variable is selected (bin it into a fixed range (equi -width) of your choice) Eastern Illinois University Department of Mathematics and Computer Science CSM 4370 – Topics in Computer Science ` ▪ on mouse -over display the bar’s value above the bar in re d color ▪ on mouse -over also color the bar in red to highlight it ▪ mouse (with left mouse button down) move left (right) should decrease (increase) bin width/size (for numerical variables only) ▪ produce a scatterplot of two selected variables (use a radio butt on to determine which of the two variable axes is to be loaded) *Note: Don’t forget to o label the axes (variable names) o label the x -axis (bin range midpoints or category label) o label the y -axis (number of items) Step 3: Your plotly -based visual interface should do ▪ present a menu to allow users to select a variable and update chart ▪ draw a bar chart if a categorical variable is selected ▪ draw a histogram if a numerical variable is selected (bin it into a fixed range (equi -width) of your choice) ▪ prod uce a pie chart of the selected variable (make sure you have no more than 5 -6 slices, sum the smaller ones into a single ‘others’ slice) ▪ produce a scatterplot of two selected variables (use a radio button to determine which of the two variable axes is to b e loaded) *Note: Don’t forget to o label the axes (variable names) o label the x -axis (bin range midpoints or category label) o label the y -axis (number of items) Step 5: Upload the following to Blackboard: ▪ Voice -narrated video file that shows all features of yo ur software in action ▪ 2–3-page report o name the source(s) of the dataset(s) with URL Eastern Illinois University Department of Mathematics and Computer Science CSM 4370 – Topics in Computer Science ` o describe the attributes o write why you thought these data are interesting o mention anything noteworthy about implementation (beyond the video) ▪ zip file with all source code ▪ excel sheet with the fused data