Exploratory Data Analysis: Economic Performance of China
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China’s GDP growth rate for the second quarter was both lower than expected and the previous quarter. In addition, the performance of the China Fund has been significantly worse over the past year. Is China heading towards a recession?
Source code:
library(tidyverse) library(tidyquant) library(timetk) library(ggthemes) #The China Fund, Inc. (quarterly) (YoY) df_china_fund <- tq_get("CHN") %>% tq_transmute(select = close, mutate_fun = to.quarterly, col_rename = "chn") %>% #YoY returns mutate(chn = (chn / lag(chn, 4) - 1) %>% round(2)) %>% select(date, chn) %>% drop_na() #China Gross Domestic Product (GDP) YoY df_gdp_chn <- read_csv("https://raw.githubusercontent.com/mesdi/investingcom/main/china_gdp_yoy.csv") #Tidy GDP data df_gdp_tidy <- df_gdp_chn %>% janitor::clean_names() %>% select(date = release_date, gdp = actual) %>% mutate(date = #removing parentheses and the text within case_when(str_detect(date," \\(.*\\)") ~ str_remove(date," \\(.*\\)"), TRUE ~ date)) %>% mutate(date = parse_date(date, format = "%b %d, %Y") %>% #subtract a quarter from the date floor_date("quarter") %m-% months(3) %>% as.yearqtr(.), gdp = str_remove(gdp, "%") %>% as.numeric() / 100) #Merging all the data sets df_merged <- df_gdp_tidy %>% left_join(df_china_fund) %>% drop_na() #Plot df_merged %>% filter(date >= 2023) %>% ggplot(aes(date)) + geom_line(aes(y = gdp), size =1.5, color = "darkorange") + geom_area(aes(y = gdp), fill = "darkorange", alpha = 0.7) + geom_point(aes(y = gdp), size = 3, color = "darkorange") + geom_bar(aes(y = chn), stat = "identity", fill = "steelblue", alpha = 0.7) + scale_y_continuous(labels = scales::percent, limits = c(-0.30,0.10)) + scale_x_yearqtr(format = "%Y Q%q" , n = 6) + labs(x="", y ="", title = "China's Economic Performance", subtitle = "<span style = 'color:darkorange;'>China Gross Domestic Product (GDP)</span> <br> <span style = 'color:steelblue;'>The China Fund, Inc</span> <br> (Quarterly) (YoY)") + theme_wsj(base_family = "Bricolage Grotesque") + theme(plot.subtitle = ggtext::element_markdown(size = 12, face = "bold"))
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