In [1]:

    

library(tidyverse)
library(forcats) # factors munging
library(stringr) # string manipulation
library(ggthemes) # visualization
options(repr.plot.width=7, repr.plot.height=5)


    

    




Loading tidyverse: ggplot2
Loading tidyverse: tibble
Loading tidyverse: tidyr
Loading tidyverse: readr
Loading tidyverse: purrr
Loading tidyverse: dplyr
Conflicts with tidy packages ---------------------------------------------------
filter(): dplyr, stats
lag():    dplyr, stats

In [2]:

    

# Help

?read_csv


    

In [3]:

    

titanic <- read_csv("data/train.csv")


    

    




Parsed with column specification:
cols(
  PassengerId = col_integer(),
  Survived = col_integer(),
  Pclass = col_integer(),
  Name = col_character(),
  Sex = col_character(),
  Age = col_double(),
  SibSp = col_integer(),
  Parch = col_integer(),
  Ticket = col_character(),
  Fare = col_double(),
  Cabin = col_character(),
  Embarked = col_character()
)

In [4]:

    

head(titanic)


    

    






PassengerId
Survived
Pclass
Name
Sex
Age
SibSp
Parch
Ticket
Fare
Cabin
Embarked

	
1                                                  
0                                                  
3                                                  
Braund, Mr. Owen Harris                            
male                                               
22                                                 
1                                                  
0                                                  
A/5 21171                                          
 7.2500                                            
NA                                                 
S                                                  
	
2                                                  
1                                                  
1                                                  
Cumings, Mrs. John Bradley (Florence Briggs Thayer)
female                                             
38                                                 
1                                                  
0                                                  
PC 17599                                           
71.2833                                            
C85                                                
C                                                  
	
3                                                  
1                                                  
3                                                  
Heikkinen, Miss. Laina                             
female                                             
26                                                 
0                                                  
0                                                  
STON/O2. 3101282                                   
 7.9250                                            
NA                                                 
S                                                  
	
4                                                  
1                                                  
1                                                  
Futrelle, Mrs. Jacques Heath (Lily May Peel)       
female                                             
35                                                 
1                                                  
0                                                  
113803                                             
53.1000                                            
C123                                               
S                                                  
	
5                                                  
0                                                  
3                                                  
Allen, Mr. William Henry                           
male                                               
35                                                 
0                                                  
0                                                  
373450                                             
 8.0500                                            
NA                                                 
S                                                  
	
6                                                  
0                                                  
3                                                  
Moran, Mr. James                                   
male                                               
NA                                                 
0                                                  
0                                                  
330877                                             
 8.4583                                            
NA                                                 
Q                                                  

In [5]:

    

summary(titanic)


    

    






  PassengerId       Survived          Pclass          Name          
 Min.   :  1.0   Min.   :0.0000   Min.   :1.000   Length:891        
 1st Qu.:223.5   1st Qu.:0.0000   1st Qu.:2.000   Class :character  
 Median :446.0   Median :0.0000   Median :3.000   Mode  :character  
 Mean   :446.0   Mean   :0.3838   Mean   :2.309                     
 3rd Qu.:668.5   3rd Qu.:1.0000   3rd Qu.:3.000                     
 Max.   :891.0   Max.   :1.0000   Max.   :3.000                     
                                                                    
     Sex                 Age            SibSp           Parch       
 Length:891         Min.   : 0.42   Min.   :0.000   Min.   :0.0000  
 Class :character   1st Qu.:20.12   1st Qu.:0.000   1st Qu.:0.0000  
 Mode  :character   Median :28.00   Median :0.000   Median :0.0000  
                    Mean   :29.70   Mean   :0.523   Mean   :0.3816  
                    3rd Qu.:38.00   3rd Qu.:1.000   3rd Qu.:0.0000  
                    Max.   :80.00   Max.   :8.000   Max.   :6.0000  
                    NA's   :177                                     
    Ticket               Fare           Cabin             Embarked        
 Length:891         Min.   :  0.00   Length:891         Length:891        
 Class :character   1st Qu.:  7.91   Class :character   Class :character  
 Mode  :character   Median : 14.45   Mode  :character   Mode  :character  
                    Mean   : 32.20                                        
                    3rd Qu.: 31.00                                        
                    Max.   :512.33                                        
                                                                          

In [6]:

    

summarise(titanic, SurvivalRate = sum(Survived) / nrow(titanic))


    

    






SurvivalRate

	
0.3838384

In [7]:

    

mean(titanic$Age, na.rm = TRUE)


    

    





29.6991176470588

In [8]:

    

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


    

    





211.019124746308

In [9]:

    

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


    

    





14.526497332334

In [10]:

    

sqrt(var(titanic$Age, na.rm = TRUE))


    

    





14.526497332334

In [32]:

    

first_class <- titanic %>% 
    select(Age, Pclass) %>%
    filter(Pclass == 1)


    

In [34]:

    

mean(first_class$Age, na.rm = TRUE)


    

    





38.2334408602151

In [36]:

    

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


    

    





14.8028558964505

In [11]:

    

plot(density(titanic$Age, na.rm = TRUE))


    

In [12]:

    

titanic %>%
    ggplot(aes(Age)) +
    geom_density() +
    ggtitle("Age distribution") +
    theme_hc() +
    scale_colour_hc()


    

    




Warning message:
“Removed 177 rows containing non-finite values (stat_density).”





    










    

In [38]:

    

first_class %>%
    ggplot(aes(Age)) +
    geom_density() +
    ggtitle("Age distribution (1st class)") +
    theme_hc() +
    scale_colour_hc()


    

    




Warning message:
“Removed 30 rows containing non-finite values (stat_density).”





    










    

In [24]:

    

cor(titanic$Age, titanic$Fare, use = "complete.obs")


    

    





0.0960666917690389

In [25]:

    

titanic %>%
    ggplot(aes(Age, Fare)) +
    geom_point() +
    theme_hc() +
    scale_colour_hc()


    

    




Warning message:
“Removed 177 rows containing missing values (geom_point).”





    










    

In [15]:

    

titanic <- titanic %>%
                mutate(Survived = factor(Survived)) %>%
                mutate(Survived = fct_recode(Survived, "No" = "0", "Yes" = "1"))


    

In [16]:

    

titanic <- titanic %>%
        mutate(Sex = factor(Sex)) %>%
        mutate(Sex = fct_recode(Sex, "Female" = "female", "Male" = "male"))


    

In [20]:

    

titanic %>% 
    ggplot(aes(Sex, fill=Survived)) +
    geom_bar(position = "fill") +
    ylab("Survival Rate") +
    geom_hline(yintercept = 0.3838384, col = "white", lty = 2) +
    ggtitle("Survival Rate by Gender") +
    theme_hc() +
    scale_colour_hc()


    

In [21]:

    

titanic <- titanic %>%
    mutate(Pclass = factor(Pclass))


    

In [26]:

    

titanic %>%
    ggplot(aes(Fare, fill=Pclass)) +
    geom_density(alpha = 0.5) +
    scale_x_log10() +
    facet_wrap(~ Survived, ncol = 1) +
    theme_hc() +
    scale_colour_hc()


    

    




Warning message:
“Transformation introduced infinite values in continuous x-axis”Warning message:
“Removed 15 rows containing non-finite values (stat_density).”





    










    

In [ ]:

    

test <- read_csv("data/test.csv")
model <- tibble(PassengerID = test$PassengerId, Survived = ifelse(test$Sex == 'female', 1, 0))
write_csv(model, "models/females_survive.csv")