TAS Descriptive statistics

We will be going through

Step 1: Loading Packages

library(tidyverse)
library(readxl)
library(ggplot2)

Step 2: Import the data

TAS_original_data_new <- read_excel("C:/ZZ_SherMay/TAS_original_data_new.xlsx")

Step 3: Preview the data

view(TAS_original_data_new)
head(TAS_original_data_new)
## # A tibble: 6 × 101
##     TAS TAS05 TAS09 TAS15 ER30001 ER30002 ER32000 ER32006 ER33801 ER33802
##   <dbl> <dbl> <dbl> <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
## 1     1    NA     1    NA       4      37       1       2    1288       3
## 2     1    NA     1    NA       4      38       2       2    6880       2
## 3     2    NA     1     1       4      39       2       2     289       3
## 4     1    NA    NA     1       4      41       2       2    1157       3
## 5     2     1     1    NA       4     180       2       3     771       2
## 6     2     1     1    NA       5      32       2       2     624       3
## # ℹ 91 more variables: ER33803 <dbl>, TA050001 <dbl>, TA050044 <dbl>,
## #   TA050047 <dbl>, TA050050 <dbl>, TA050065 <dbl>, TA050066 <dbl>,
## #   TA050067 <dbl>, TA050070 <dbl>, TA050071 <dbl>, TA050127 <dbl>,
## #   TA050128 <dbl>, TA050129 <dbl>, TA050130 <dbl>, TA050573 <dbl>,
## #   TA050574 <dbl>, TA050575 <dbl>, TA050594 <dbl>, TA050595 <dbl>,
## #   TA050639 <dbl>, TA050663 <dbl>, TA050664 <dbl>, TA050665 <dbl>,
## #   TA050670 <dbl>, TA050675 <dbl>, TA050676 <dbl>, TA050884 <dbl>, …

Step 4: Age

2005

18 years old graduate

age_18_05 <- TAS_original_data_new %>% select(TA050575) %>% filter(TA050575 > 0) %>% drop_na() %>% mutate(Age_18_graduate_05 = 2005-(TA050575-18))
knitr::kable(age_18_05 %>% count(Age_18_graduate_05), align = "cc")
Age_18_graduate_05 n
18 179
19 169
20 164
21 83
22 2
23 2 
ggplot(data=age_18_05) + geom_bar(mapping = aes(x= Age_18_graduate_05))+  labs(x ='Age', y='count', title = 'Age 2005')

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2009

18 years old graduate

age_18_09 <- TAS_original_data_new %>% select(TA090592) %>% filter(TA090592 > 0) %>% drop_na() %>% mutate(Age_18_graduate_09 = 2009-(TA090592-18))
knitr::kable(age_18_09 %>% count(Age_18_graduate_09), align = "cc")
Age_18_graduate_09 n
18 195
19 172
20 166
21 172
22 183
23 161
24 153
25 84
26 2
27 1
28 1 
ggplot(data=age_18_09) + geom_bar(mapping = aes(x= Age_18_graduate_09))+  labs(x ='Age', y='count', title = 'Age 2009')

2015

18 years old graduate

age_18_15 <- TAS_original_data_new %>% select(TA150703) %>% filter(TA150703 > 0) %>% drop_na() %>% mutate(Age_18_graduate_15 = 2015-(TA150703-18))
knitr::kable(age_18_15 %>% count(Age_18_graduate_15), align = "cc")
Age_18_graduate_15 n
18 91
19 163
20 36
21 32
22 146
23 93
24 55
25 37
26 31
27 15
29 1
32 1 
ggplot(data=age_18_15) + geom_bar(mapping = aes(x= Age_18_graduate_15))+  labs(x ='Age', y='count', title = 'Age 2015')