Year-end Summary

2024回顾与2025展望

Hi buddy, time flies. It is really mundane, but thouse shining moments sustain the boring.

During the year 2024:

You changed your job, find your pleased field. You felt anxious when you were fired but after that you got your new job which is really nice. It is what it is.

You met a girl. You two went to some places really impressive, especially the first time.

You skied at the beginning of the year 2024 with your friends.

You have a really long road trip with your 3 dummy friends. You saw seas together and offshore fishing first time in your life. 

You saw the waves emit the blue light in midnight. People lighting bonfires on the beach and flags wiving in the wind.

You shower under a huge waterfall and then swim in front of it.

You have long talks with your old friends. Watch huge airpalnes flying overhead.

You rent a flat near your company.

You learn how to code.

Those sparks in the year 2024 light the year 2025.

Wish you a really nice new year in 2025.

I will always be  with you. 

function_year5 <- function(table_name, start_year, end_year, current_year){ remain <- current_year - floor((current_year - start_year)/5) * 5 year_names <- NULL for (i in start_year:end_year) { if((i - current_year)/5 - floor((i - current_year)/5) == 0){ if(i == remain){ temp <- paste(start_year, i, sep = '-') year_names <- append(year_names, temp) } else{ temp <- paste(i-4, i, sep = '-') year_names <- append(year_names, temp) } } } table_name <- as.data.frame(table_name) new_years <- seq(start_year,end_year,1) new_table <- as.data.frame(matrix(data = rep(0, length(year_names)*nrow(table_name)), ncol = length(year_names), nrow = nrow(table_name))) %>% as.data.frame() colnames(new_table) <- year_names j = 1 for (i in 1:(end_year - start_year + 1)){ if((new_years[i] - current_year)/5 - floor((new_years[i] - current_year)/5) != 0){ new_table[, year_names[j]] <- new_table[,year_names[j]] + table_name[,as.character(new_years[i])] } else{ if(j == 1){ new_table[,year_names[j]] <- (new_table[,year_names[j]] + table_name[,as.character(new_years[i])]) / (remain - start_year + 1) } else{ new_table[,year_names[j]] <- (new_table[,year_names[j]] + table_name[,as.character(new_years[i])]) / 5 } j = j + 1 } } return(new_table) } made_country_data<-function(data_select,sex_name,output,output_path,measure,order_list,population_all,location_ID, start_year, end_year, current_year){ data_select2 <- data_select[data_select$measure_name == measure, ] age_names <- unique(data_select2$age_name) for (region_name in order_list){ sex_keyword=tolower(sex_name) population <- population_all %>% filter(location_name %in% region_name & age_group_name %in% age_names & sex_name %in% sex_keyword & location_id %in% location_ID) population <- population[,-1]
07-04
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