Publications by Julian Adames-Ng
DATA 607 - Assignment 4b
Introduction When working with data, you should expect to spend a good amount of time in the clean-up process, but it is not always ‘messy’ or unreadable. For example, data can still be organized in a data-frame in a way that is readable, but at the same time it may not be useful in such presented formats. In these cases, we may have to transpo...
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DATA 605 - Homework #1
1. Geometric Transformation of Shapes Using Matrix Multiplication Context: In computer graphics and data visualization, geometric transformations are fundamental. These transformations, such as translation, scaling, rotation, and reflection, can be applied to shapes to manipulate their appearance. Task: Create a simple shape (like a square or tri...
9844 sym R (12090 sym/88 pcs) 11 img
DATA 607 - Assignment 4
#install.packages('dplyr') #install.packages('tidyr') #load dplyr and tidyr libraries library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union library(tidyr) Introduction ...
2596 sym R (16427 sym/41 pcs)
DATA 607 - Project 1
Introduction When working with data, sometimes it is not available in a readable or executable format. Even if the data is readable by the database management system, it may not be easy for a human to understand. In such situations, we would like to “tidy” our data. Some information in a data set may not be necessary in some situations. Removin...
10787 sym Python (27433 sym/71 pcs)
DATA 607 - Assignment 3
Introduction As we work with larger and more complicated data sets, it gets difficult to decipher information when the data isn’t represented in a readable way. We will use several tools to help manipulate text, filter data frames, and recognize patterns within data for the purpose of “tidying” up our data sets. # read in the data majors <- r...
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DATA 607 - Assignment 1
Introduction The author of the following article was interested in knowing how people liked their steaks prepared and whether their choice shed light to any aspect of their lifestyle. Although his investigation produced inconclusive results, his plan of action was to determine if risk-averse people were more likely to order their steak well done? T...
2394 sym Python (9335 sym/9 pcs)