Have you spent hours, pulling your hair out trying to figure out how to access datasets in R? Once imported to a variable, columns from a dataset (eg: CSV) can be very tricky to access. Sometimes columns contain spaces, funky characters or other incosistencies. Here are some examples on how to access the data from CSV and JSON datasets.

CSV

1. Read File: csvDataset<-read.csv("Global Carbon Emissions Record 1751-2013")

2. Access Columns: csvDataset$Total.carbon.emissions.from.fossil.fuel.consumption.and.cement.production..million.metric.tons.of.C.

As you can see here, the blank spaces AND parantheses got replaced by a period . .This is actually pretty useful because you can just use the period for other special characters, helping you get to variables faster.

You can always head(csvDataset) to look at the column names (and first few rows) to get the actual column names used to call them.

JSON

For JSON, we’re going to load an external library.

1. Load rjson library: library(rjson)
2. Read File: jsonDataset<-fromJSON(file="city_country_meteor.json")
3. Access an Object: jsonDataset[1] (gives you the first object)

Link to datasets and example R notebook: https://www.datazar.com/project/p556632b8-4760-4d16-b787-2dbe74b3b1a4/files

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