Publications by Datacamp - Jo Hardin
survival analysis in R
The term "survival analysis aka time-to-event data analysis What we will discuss in this course duration times death unemployment delivery of a letter cab pickup wait times Data sets we will be using GBSG2: time to death of 686 breast cancer patients data(GBSG2, package = "TH.data") UnempDur: time to re-employment of 3343 unemployed patient...
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network analysis in R
Nodes/vertices are connected via edges. a 1 in the adjacency matrix indicates an edge exists between nodes in the matrix each row represents an edge between two individual vertices in each column first number indicates number of vertices (7) second number indicates number of edges (7) final row shows all edges in the network number and which v...
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Intermediate R
Relational Operators Equality The most basic form of comparison is equality. Let’s briefly recap its syntax. The following statements all evaluate to TRUE (feel free to try them out in the console). 3 == (2 + 1) "intermediate" != "r" TRUE != FALSE "Rchitect" != "rchitect" Notice from the last expression that R is case sensitive: “R” is ...
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Introduction to the Tidyverse
The gapminder dataset Loading the gapminder and dplyr packages Before you can work with the gapminder dataset, you’ll need to load two R packages that contain the tools for working with it, then display the gapminder dataset so that you can see what it contains. This course introduces a lot of new concepts, so if you ever need a quick refreshe...
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Data Manipulation with dplyr
The counties dataset Chapter 1 verbs select() filter() arrange() mutate() If you want to see a few values from all the columns, you can use glimpse() library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ...
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Joining Data with dplyr
The inner_join verb Joining parts and part categories The inner_join is the key to bring tables together. To use it, you need to provide the two tables that must be joined and the columns on which they should be joined. In this exercise, you’ll join a list of LEGO parts, available as parts, with these parts’ corresponding categories, availab...
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Cleaning Data in R
Data type constraints Converting data types Throughout this chapter, you’ll be working with San Francisco bike share ride data called bike_share_rides. It contains information on start and end stations of each trip, the trip duration, and some user information. Before beginning to analyze any dataset, it’s important to take a look at the dif...
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Case Study: Exploratory Data Analysis in R
The United Nations Voting Dataset Filtering rows The vote column in the dataset has a number that represents that country’s vote: 1 = Yes 2 = Abstain 3 = No 8 = Not present 9 = Not a member One step of data cleaning is removing observations (rows) that you’re not interested in. In this case, you want to remove “Not present” and “Not ...
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Correlation and Regression in R
Visualizing bivariate relationships Bivariate relationships both variables are numerical response variable y, dependent explanatory variable something you think might be relate dto the response x, independent, predictor Bivariate relationships can think of boxplots as scatterplots… … but with discretized explanatory variable cut() fun...
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Unsupervised Learning in R
Welcome to the course! types of machine learning unsupervised learning finding structure in unlabeled data supervised learning making predictions based on labeled data predictions like regression or classification reinforcement learning Unsupervised learning - dimensionality reduction finding homogeneous subgroups within larger group cl...
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