JSON practice (1)

JSON is built on two structures: objects and arrays. To help you experiment with these, two JSON strings are included in the sample code. It's up to you to change them appropriately and then call jsonlite's fromJSON() function on them each time.

Deze oefening maakt deel uit van de cursus

Intermediate Importing Data in R

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Oefeninstructies

Change the assignment of json1 such that the R vector after conversion contains the numbers 1 up to 6, in ascending order. Next, call fromJSON() on json1.
Adapt the code for json2 such that it's converted to a named list with two elements: a, containing the numbers 1, 2 and 3 and b, containing the numbers 4, 5 and 6. Next, call fromJSON() on json2.

Praktische interactieve oefening

Probeer deze oefening eens door deze voorbeeldcode in te vullen.

# jsonlite is already loaded

# Challenge 1
json1 <- '[1, 2, 4, 6]'


# Challenge 2
json2 <- '{"a": [1, 2, 3]}'

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Deze oefening maakt deel uit van de cursus

Intermediate Importing Data in R

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Begin de cursus gratis

Many companies store their information in relational databases. The R community has also developed R packages to get data from these architectures. You'll learn how to connect to a database and how to retrieve data from it.

Exercise 1: Connect to a database Exercise 2: Establish a connection Exercise 3: Inspect the connection Exercise 4: Import table data Exercise 5: List the database tables Exercise 6: Import users Exercise 7: Import all tables Exercise 8: How do the tables relate?

Importing an entire table from a database while you might only need a tiny bit of information seems like a lot of unncessary work. In this chapter, you'll learn about SQL queries, which will help you make things more efficient by performing some computations on the database side.

Exercise 1: SQL Queries from inside R Exercise 2: Query tweater (1)Exercise 3: Query tweater (2)Exercise 4: Query tweater (3)Exercise 5: Query tweater (4)Exercise 6: Join the query madness!Exercise 7: DBI internals Exercise 8: Send - Fetch - Clear Exercise 9: Be polite and ...

More and more of the information that data scientists are using resides on the web. Importing this data into R requires an understanding of the protocols used on the web. In this chapter, you'll get a crash course in HTTP and learn to perform your own HTTP requests from inside R.

Exercise 1: HTTP Exercise 2: Import flat files from the web Exercise 3: Secure importing Exercise 4: Downloading files Exercise 5: Import Excel files from the web Exercise 6: Downloading any file, secure or not Exercise 7: Reading a text file from the web Exercise 8: HTTP? httr! (1)Exercise 9: HTTP? httr! (2)

Importing data from the web is one thing; actually being able to extract useful information is another. Learn more about the JSON format to get one step closer to web domination.

Exercise 1: APIs & JSON Exercise 2: From JSON to R Exercise 3: Import JSON data from API Exercise 4: OMDb API Exercise 5: JSON & jsonlite Exercise 6: JSON practice (1)

Huidige oefening

Exercise 7: JSON practice (2)Exercise 8: toJSON()Exercise 9: Minify and prettify

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Exercise 1: haven Exercise 2: Import SAS data with haven Exercise 3: Import STATA data with haven Exercise 4: What does the graphic tell?Exercise 5: Import SPSS data with haven Exercise 6: Factorize, round two Exercise 7: foreign Exercise 8: Import STATA data with foreign (1)Exercise 9: Import STATA data with foreign (2)Exercise 10: Do you know your data?Exercise 11: Import SPSS data with foreign (1)Exercise 12: Excursion: Correlation Exercise 13: Import SPSS data with foreign (2)