world bank data EDA
2025-04-16
load package
library("tidyverse")
library("here")
library("beeswarm")
library("ggplot2") we are looking at income, gender, where people use digital transference
1.Income distribution by gender
micro_aus <- read.csv(here("data","micro_aus.csv"))
glimpse(micro_aus)## Rows: 1,000
## Columns: 83
## $ economy <chr> "Australia", "Australia", "Australia", "Australia"…
## $ economycode <chr> "AUS", "AUS", "AUS", "AUS", "AUS", "AUS", "AUS", "…
## $ wpid_random <int> 160288803, 151789780, 148625405, 192142847, 169882…
## $ wgt <dbl> 1.2575536, 1.2669981, 0.1833565, 0.8274972, 1.0198…
## $ female <int> 2, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2,…
## $ age <int> 61, 22, 66, 84, 30, 67, 20, 69, 40, 47, 81, 91, 36…
## $ educ <int> 2, 3, 3, 1, 3, 2, 5, 2, 3, 3, 3, 2, 3, 3, 2, 3, 2,…
## $ inc_q <int> 5, 1, 4, 5, 4, 3, 4, 4, 1, 2, 4, 1, 1, 3, 1, 4, 1,…
## $ emp_in <int> 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 1, 2, 2, 2,…
## $ urbanicity_f2f <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ account <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ account_fin <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ fin2 <int> 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ fin4 <int> 1, 1, 1, NA, 1, 1, 4, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1…
## $ fin5 <int> 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 2,…
## $ fin6 <int> 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1,…
## $ fin7 <int> 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2, 2, 1, 2, 1, 1,…
## $ fin8 <int> 1, NA, 1, 1, 1, 1, NA, 1, 2, 1, NA, NA, NA, 1, NA,…
## $ fin8b <int> 2, NA, 1, 1, 1, 1, NA, 1, 1, 1, NA, NA, NA, 1, NA,…
## $ fin9 <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1,…
## $ fin9a <int> 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, NA, 1, 1…
## $ fin10 <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1,…
## $ fin10a <int> 1, 1, 1, 1, 1, 1, 4, 1, 1, 1, 1, 1, 1, 1, NA, 1, 1…
## $ fin10b <int> 1, 1, 1, 1, 1, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2,…
## $ fin11_1 <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin11a <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin11b <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin11c <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin11d <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin11e <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin11f <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin11g <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin11h <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin13a <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin13b <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin13c <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin13d <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin14_1 <int> 2, 1, 1, 2, 2, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ fin14a <int> 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 2, 2, 1, 1, 2, 1, 2,…
## $ fin14a1 <int> 1, 1, 1, 2, 1, 2, 1, 1, 1, 2, 2, 2, 1, 2, 2, 1, 2,…
## $ fin14b <int> 1, 1, 2, 2, 1, 1, 2, 1, 1, 2, 2, 2, 1, 1, 2, 1, 2,…
## $ fin16 <int> 2, 2, 1, 2, 1, 2, 2, 1, 2, 1, 1, 2, 1, 2, 1, 2, 2,…
## $ fin17a <int> 1, 1, 1, 2, 1, 2, 2, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2,…
## $ fin17a1 <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin20 <int> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2,…
## $ fin22a <int> 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ fin22b <int> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ fin24 <int> 6, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 4, 1, 1, 1,…
## $ fin24a <int> 2, 3, 3, 3, 3, 2, 3, 3, 2, 2, 3, 3, 1, 3, 2, 2, 3,…
## $ fin24b <int> 1, 3, 3, 3, 3, 2, 2, 3, 2, 1, 3, 3, 1, 3, 2, 2, 3,…
## $ fin30 <int> 1, 1, 1, 2, 1, 1, 2, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1,…
## $ fin31a <int> 1, 1, 1, NA, 1, 1, NA, 1, 1, NA, 1, 1, 1, 1, 1, 1,…
## $ fin31b <int> 2, 1, 2, NA, 2, 2, NA, 2, 2, NA, 2, 2, 1, 2, 2, 2,…
## $ fin31c <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin32 <int> 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 2, 2, 2, 1, 2, 2, 2,…
## $ fin33 <int> 2, 2, 1, NA, 2, NA, 2, NA, 1, NA, NA, NA, NA, 2, N…
## $ fin34a <int> 1, 1, 1, NA, 1, NA, 1, NA, 1, NA, NA, NA, NA, 1, N…
## $ fin34b <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin34d <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin34e <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin37 <int> 2, 1, 1, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ fin38 <int> 2, 2, 1, 1, 2, 2, 2, 1, 2, 2, 1, 1, 2, 2, 1, 2, 1,…
## $ fin39a <int> NA, 1, 1, 2, NA, NA, 1, 1, 1, NA, 1, 1, NA, NA, 1,…
## $ fin39b <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ fin39d <int> NA, NA, NA, 2, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ fin39e <int> NA, NA, NA, 2, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ fin44a <int> 2, 3, 3, 3, 3, 2, 3, 3, 2, 2, 3, 3, 3, 3, 1, 2, 3,…
## $ fin44b <int> 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 3, 3, 1, 3, 1, 2, 3,…
## $ fin44c <int> 2, 3, 3, 3, 3, 3, 3, 3, 2, 2, 3, 3, 3, 3, 2, 3, 3,…
## $ fin44d <int> 3, 3, 3, 4, 2, 3, 3, 3, 2, 3, 4, 3, 3, 3, 4, 3, 3,…
## $ fin45 <int> 1, NA, NA, NA, NA, NA, NA, NA, 3, 1, NA, NA, NA, N…
## $ saved <int> 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0,…
## $ borrowed <int> 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1,…
## $ receive_wages <int> 1, 1, 1, 4, 1, 4, 1, 4, 1, 4, 4, 4, 4, 1, 4, 4, 4,…
## $ receive_transfers <int> 4, 1, 1, 4, 4, 4, 1, 1, 1, 4, 4, 4, 4, 4, 4, 4, 4,…
## $ receive_pension <int> 4, 4, 1, 3, 4, 4, 4, 1, 4, 4, 1, 1, 4, 4, 1, 4, 1,…
## $ receive_agriculture <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ pay_utilities <int> 1, 1, 1, 4, 1, 1, 4, 1, 1, 4, 1, 1, 1, 1, 1, 1, 1,…
## $ remittances <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ mobileowner <int> 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1,…
## $ internetaccess <int> 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1,…
## $ anydigpayment <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ merchantpay_dig <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…micro_aus$female <- factor(micro_aus$female, levels = c(1, 2), labels = c("Female", "Male"))
micro_aus %>%
select(female,inc_q) %>%
rename(income = inc_q) %>%
na.omit() %>%
ggplot(aes(x = female, y = income )) +
geom_boxplot() +
labs(x = "Gender", y = "Income", title = "Income Distribution by Gender")
2.income and whether pay things online relationship filtered by gender
filtered by >3 we donn’t have data for fin4a = use debit card in-store so we are using fin4 = use debit card instead
micro_aus$account_fin <- as.factor(micro_aus$account_fin)
micro_aus$fin4 <- as.factor(micro_aus$fin4)
micro_aus$fin14a <- as.factor(micro_aus$fin14a)
# 整理数据
micro_aus_clean <- micro_aus %>%
filter(!is.na(female), !is.na(inc_q), !is.na(fin4), !is.na(fin14a)) %>%
mutate(
female = factor(female, levels = c("Female", "Male")),
inc_q = factor(inc_q, levels = 1:5, labels = paste0("Q", 1:5)),
fin4 = factor(fin4, levels = c(1, 2), labels = c("Debit: Yes", "Debit: No")),
fin14a = factor(fin14a, levels = c(1, 2), labels = c("Online: Yes", "Online: No"))
) %>%
pivot_longer(cols = c(fin4, fin14a), names_to = "payment_type", values_to = "payment_status")
ggplot(micro_aus_clean, aes(x = payment_status, fill = inc_q)) +
geom_bar(position = "dodge") +
facet_wrap(~ female) +
labs(
title = "Payment Behavior by Gender and Income Quintile",
x = "Payment Method & Response",
y = "Count",
fill = "Income Quintile") +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
## cda from the graph - the overall usage of debit card is always higher
than online. - male tend to pay more by both debit card and online as
they become wealthier. -the female within q2 income spend money the most
than any other quntile income level; as women’s income grow higher, the
gap between using debit card and online payment seems to become smaller,
compared with the larger preference of using credit card among women in
q1 income class. -women spent more money than men in all income quntile
level except Q5. (may consider it with domestic care–>spend money for
the family, pregnancy etc.)
3. where people use digital payment by gender- 14a1 14a2 14b
select(female,fin14_1,inc_q,fin14a)