#

# Copyright 2017 Dave Langer

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

# http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

#

#

# This R source code file corresponds to video 6 of the YouTube series

# "R Programming for Excel Users" located at the following URL:

# https://youtu.be/Wam5xSsGVn8

#

# Load the data and take a look at the structure

# NOTE - Be sure to set your working directory!

titanic_train <- read.csv("titanic_train.csv")

str(titanic_train)

# Subset the data for the Age variable (i.e., the 6th column)

titanic_train[7, 6]

titanic_train[1:10, 6]

# Subset the data for the Age, SibSp, and Parch variables

# (i.e., the 6th, 7th, and 8th columns)

titanic_train[2:25, 6:8]

# Perform vector-based summation first 10 Age values

sum(titanic_train[1:10, 6], na.rm = TRUE)

# Perform vector-based summation on all Age values,

# the second parameter is required to ignore missing values!

sum(titanic_train$Age, na.rm = TRUE)

# Add a new column for the size of the family using a

# vectorized calculation

titanic_train$FamilySize <- 1 + titanic_train$SibSp + titanic_train$Parch

View(titanic_train)

# Add a new column to the data frame

titanic_train$AgeMissing <- ""

View(titanic_train)

# Update the new column to reflect reality

titanic_train$AgeMissing <- ifelse(is.na(titanic_train$Age),

"Y",

"N")

View(titanic_train)

# Start investigating the nature of the Age column

summary(titanic_train$Age)

# More summary statistics for Age column

sd(titanic_train$Age, na.rm = TRUE)

median(titanic_train$Age, na.rm = TRUE)

var(titanic_train$Age, na.rm = TRUE)

sum(titanic_train$Age, na.rm = TRUE)

length(titanic_train$Age)

AgeTemp <- titanic_train$Age[!is.na(titanic_train$Age)]

length(AgeTemp)

# Slice Age data by Gender

FemaleAge <- titanic_train$Age[titanic_train$Sex == "female"]

summary(FemaleAge)

sd(FemaleAge, na.rm = TRUE)

MaleAge <- titanic_train$Age[titanic_train$Sex == "male"]

summary(MaleAge)

sd(MaleAge, na.rm = TRUE)

# Slice entire data frame by Sex

female_train <- titanic_train[titanic_train$Sex == "female",]

View(female_train)

male_train <- titanic_train[titanic_train$Sex == "male",]

View(male_train)

# Further slice data frame by Pclass of 1

female_1st_train <- female_train[female_train$Pclass == 1,]

View(female_1st_train)

summary(female_1st_train$Age)

male_1st_train <- male_train[male_train$Pclass == 1,]

View(male_1st_train)

summary(male_1st_train$Age)

# Can combine in a single step

female_1st_train <- titanic_train[(titanic_train$Sex == "female" & titanic_train$Pclass == 1),]

male_1st_train <- titanic_train[titanic_train$Sex == "male" &

titanic_train$Pclass == 1,]

# Subset to only the columns I'm interested in by column position

names(titanic_train)

my_subset_1 <- titanic_train[, c(2, 3, 5, 6, 7, 8, 10, 13, 14)]

View(my_subset_1)

# The following code is equivalent to the my_subset_1 code

my_subset_2 <- titanic_train[, c(2:3, 5:8, 10, 13:14)]

View(my_subset_2)

# I can also filter rows and columns by position

my_rows <- c(1:50, 67, 69, 84, 100:891)

my_features <- c(2:3, 5:8, 10, 13:14)

my_subset_3 <- titanic_train[my_rows, my_features]

View(my_subset_3)

# Subset to only the columns I'm interested in by column name

my_features <- c("Survived", "Pclass", "Sex", "Age", "SibSp", "Parch", "Fare", "FamilySize", "AgeMissing")

my_subset_4 <- titanic_train[, my_features]

View(my_subset_4)

# The following code is equivalent to the my_subset_4 code

my_features <- names(titanic_train)

my_features <- my_features[-c(1, 4, 9, 11, 12)]

my_features

my_subset_5 <- titanic_train[, my_features]

View(my_subset_5)

# Subset to only the columns I'm interested in

my_rows <- c(51:66, 68, 70:83, 85:99)

my_features <- names(titanic_train)[-c(1, 4, 9, 11, 12)]

my_features

my_subset_6 <- titanic_train[-my_rows, my_features]

View(my_subset_6)