Week 1 Challenge

Loading Data and Creating a Network

Challenge Overview

Today’s challenge is to

1. read in a dataset, and

2. create a network object

Code

library(tidyverse)

── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
✔ ggplot2 3.4.1     ✔ purrr   1.0.1
✔ tibble  3.1.8     ✔ dplyr   1.1.0
✔ tidyr   1.3.0     ✔ stringr 1.5.0
✔ readr   2.1.4     ✔ forcats 1.0.0
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

Load the Data

Read in one (or more) of the following data sets, using the correct R package and command.

• got_like_dislike.csv

Find the _data folder, located inside the posts folder. Then you can read in the data, using base read.csv or read_csv standard tidy read command to read Comma Separated Values files or, alternatively, read the data in directly from loading a package.

Code

got_like_dislike <- read_csv("_data/got/got_like_dislike.csv")

Rows: 46 Columns: 49
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr  (3): Current house, Former house, Name
dbl (46): Lysa Arryn, Petyr Baelish, Joffrey Baratheon, Margaery Tyrell, Ren...

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

The dataset has 46 rows and 49 columns

Create a Network

Load the package igraph and create an igraph object (i.e. a graph or network) in the form of an edge list. The command may vary whether the data is given as a list of connections or an adjacency matrix. Is the network directed or undirected; weighted or unweighted; unimodal or bipartite? Can you plot it?

Code

library(igraph)

Attaching package: 'igraph'

The following objects are masked from 'package:dplyr':

    as_data_frame, groups, union

The following objects are masked from 'package:purrr':

    compose, simplify

The following object is masked from 'package:tidyr':

    crossing

The following object is masked from 'package:tibble':

    as_data_frame

The following objects are masked from 'package:stats':

    decompose, spectrum

The following object is masked from 'package:base':

    union

From the below commands we know that the data is undirected, unmweighted and unimodal.

The plot is below:

Code

got_like_dislike.ig <- graph_from_data_frame(got_like_dislike, directed = FALSE)

Warning in graph_from_data_frame(got_like_dislike, directed = FALSE): In `d'
`NA' elements were replaced with string "NA"

Code

is_directed(got_like_dislike.ig)

[1] FALSE

Code

is_weighted(got_like_dislike.ig)

[1] FALSE

Code

is_bipartite(got_like_dislike.ig)

[1] FALSE

Code

plot.igraph(got_like_dislike.ig)