Welcome! Before we go deeper into the world of R, it will be nice to have an understanding of how dates and times are created. This chapter will teach you enough to begin working with dates, but only scratches the surface of what you can do with them.

An introduction to dates in R

What day is it?

From char to date

Many dates

Date formats and extractor functions

Date formats (1)

Date formats (2)

Subtraction of dates

months() and weekdays() and quarters(), oh my!

Dates

Imagine you own stock in a company. If the stock goes above a certain price, you might want to sell. If the stock drops below a certain price, you might want to buy it while it's cheap! This kind of thinking can be implemented using operators and if statements. In this chapter, you will learn all about them, and create a program that tells you to buy or sell a stock.

Relational operators

Relational practice

Vectorized operations

Logical operators

And / Or

Not!

Logicals and subset()

All together now!

If statements

If this

If this, Else that

If this, Else If that, Else that other thing

Can you If inside an If?

ifelse()

If Statements and Operators

Loops can be useful for doing the same operation to each element of your data structure. In this chapter you will learn all about repeat, while, and for loops!

Repeat loops

Repeat, repeat, repeat

When to break?

While loops

While with a print

While with a plot

Break it

For loops

Loop over a vector

Loop over data frame rows

Loop over matrix elements

Break and next

Loops

If data structures like data frames and vectors are how you hold your data, functions are how you tell R what to do with your data. In this chapter, you will learn about using built-in functions, creating your own unique functions, and you will finish off with a brief introduction to packages.

What are functions?

Function help and documentation

Optional arguments

Functions in functions

Writing functions

Your first function

Multiple arguments (1)

Multiple arguments (2)

Function scope (1)

Function scope (2)

Packages

tidyquant package

Functions

A popular alternative to loops in R are the apply functions. These are often more readable than loops, and are incredibly useful for scaling the data science workflow to perform a complicated calculation on any number of observations. Learn about them here!

Mengapa menggunakan apply?

lapply() pada list

lapply() pada data frame

Argumen FUN

sapply() - sederhanakan!

sapply() vs. lapply()

Gagal menyederhanakan

vapply() - tentukan keluaran Anda!

vapply() vs. sapply()

Lebih lanjut tentang vapply()

Fungsi anonim

Selamat

Apply

Jika Anda menikmati kursus Pengantar R untuk Keuangan, Anda akan menyukai R Tingkat Menengah untuk Keuangan. Di sini, Anda akan mempelajari dasar-dasar cara kerja tanggal dan waktu di R—keahlian penting untuk sisa kursus. Langkah berikutnya, Anda akan menjelajahi dunia if statement, loop, dan function. Ini adalah konsep yang kuat dan esensial dalam perangkat kerja setiap data scientist di bidang keuangan. Terakhir, kita akan bekerja dengan keluarga fungsi apply sebagai alternatif tervektorisasi untuk loop. Dan tentu saja, semua contoh akan terkait keuangan! Selamat belajar!

Introduction to R for Finance

Pelajari tanggal di R, eksplorasi if, loop, dan fungsi. Praktikkan dengan contoh keuangan.

R Tingkat Menengah untuk Keuangan

Pelajari cara kerja tanggal dalam R, dan jelajahi dunia pernyataan if, loop, dan fungsi menggunakan contoh-contoh keuangan.

vapply() - tentukan keluaran Anda!

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