In nandinigntr/MSDR: Mastering Software Development in R

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(magrittr)
library(dplyr)
library(readr)
library(kableExtra)
library(msdr)

Table of Contents

• 1. Introduction
• 2. Loading the Data
• 3. Creating New Features
• 4. Conversion Process
• 5. Cleaning Process
• 6. Example 1
• 7. Example 2

1. Introduction {#intro}

This function has two behaviours:

1) When you assign a file to load, and;

# Loading the 'signif.txt' file.
eq_clean_data(file_name = system.file("extdata", "signif.txt", package = "msdr"))

2) When you pipe a dataset already loaded.

# Pipe.
readr::read_delim("signif.txt",
                  delim = "\t") %>% eq_clean_data()

2. Loading the data {#load_data}

This function also loads the Earthquake database from NOAA.

# Path to the raw data.
raw_data_path <- system.file("extdata", "signif.txt", package = "msdr")
# Loading the dataset of Earthquake.
df <- readr::read_delim(file = raw_data_path,      
                        delim = '\t',              
                        col_names = TRUE,          
                        progress = FALSE,           
                        col_types = readr::cols())
# Printing the first 5 rows.
head(df) %>%
       select(I_D, YEAR, LOCATION_NAME, EQ_PRIMARY, TOTAL_DEATHS) %>% 
              kable()

As you can see, there are several observations with NA values.

3. Creating new features {#new_features}

The eq_clean_data creates the DATE variable binding the columns YEAR, MONTH, and DAY. All this using the Lubridate package.

# Creating a new feature.
df <- df %>%
       mutate(DATE = lubridate::ymd(paste(df$YEAR,      # YEAR column
                                          df$MONTH,     # MONTH column
                                          df$DAY,       # DAY column
                                          sep = "/")))  # YYYY/MM/DD

4. Conversion Process {#conversion}

I have converted the class of some features:

• TOTAL_DEATHS to numeric;
• EQ_PRIMARY to numeric;
• All NA's of TOTAL_DEATHS in zeros.

5. Cleaning Process {#cleaning}

I have removed:

• All observations flagged as Tsunami, and;
• All observations with no Date.

6. Example 1 {#example_1}

How to load a txt file.

# Load the package
library(msdr)
# Define as file_name the txt file.
df <- eq_clean_data(file_name = raw_data_path)
# Dimensions of the loaded dataframe.
dim(df)

7. Example 2 {#example_2}

Piping a dataset to the eq_clean_data.

# Load the package
library(msdr)
# Piping a read_delim with eq_clean_data.
readr::read_delim(raw_data_path,
                  delim = "\t") %>%

              eq_clean_data() -> df
# Dimensions of the loaded dataframe.
dim(df)

nandinigntr/MSDR documentation built on Jan. 1, 2021, 11:32 a.m.