提问人：SWeatherby 提问时间：10/10/2023 更新时间：10/11/2023 访问量：29
尝试创建一个列表，我可以循环选择特定数据
Trying to create a list that I can loop through selecting specifc data
问：
我不确定为什么当我尝试从以下代码中调用数据时，我得到 NULL 值。我也没有收到错误消息，所以我不太确定从哪里开始解决这个问题。
我希望能够将其放入数据框/表中，但是在这一点上，我希望能够获得 2019 年的总死亡人数和/或获得特定年份每个州的死亡总数。
企图：
years <- c(2018, 2019, 2020, 2021)
yearly_totals <- list()
state_totals <- list()
mcod_totals <- list()
age_range_totals <- list()
for (year in years) {
yr_data <- mcod_df[mcod_df$year == year, ]
# lists for storage
yearly_totals[[as.character(year)]] <- sum(yr_data$deaths)
state_totals[[as.character(year)]] <- yr_data %>%
group_by(state = state) %>%
summarise(total_deaths = sum(deaths))
mcod_totals[[as.character(year)]] <- yr_data %>%
group_by(mcod = multiple_cause_of_death) %>%
summarise(tot_mcod = sum(deaths))
age_range_totals[[as.character(year)]] <- yr_data %>%
group_by(state, age_range = five_year_age_groups) %>%
summarise(age_range_tot = sum(deaths))
}
致电：
yearly_totals[["2020"]]
state_totals[["2020"]]
cat("State Totals for 2020:\n")
print(state_totals[["2020"]], row.names = FALSE)
结果：
> yearly_totals[["2020"]]
NULL
> state_totals[["2020"]]
NULL
> print(state_totals[["2020"]], row.names = FALSE)
NULL
答：
0赞
SWeatherby
10/11/2023
#1
事实证明，我没有考虑数据中的 NULL/NA 值。更新/更正了以下代码：
years <- c(2018, 2019, 2020, 2021)
yearly_totals <- list()
state_totals <- list()
mcod_totals <- list()
age_range_totals <- list()
for (year in years) {
yr_data <- mcod_df[mcod_df$year == year, ]
##### skip year if no data
if (nrow(yr_data) == 0) {
cat("No data for year", year, "\n")
next
}
##### Lists to store results w/ consideration for NA/NULL values
yearly_totals[[as.character(year)]] <- sum(yr_data$deaths)
state_totals[[as.character(year)]] <- yr_data %>%
filter(!is.na(state)) %>%
group_by(state = state) %>%
summarise(total_deaths = sum(deaths, na.rm = TRUE))
mcod_totals[[as.character(year)]] <- yr_data %>%
filter(!is.na(multiple_cause_of_death)) %>%
group_by(mcod = multiple_cause_of_death) %>%
summarise(tot_mcod = sum(deaths, na.rm = TRUE))
age_range_totals[[as.character(year)]] <- yr_data %>%
filter(!is.na(state) & !is.na(five_year_age_groups)) %>%
group_by(state, age_range = five_year_age_groups) %>%
summarise(age_range_tot = sum(deaths, na.rm = TRUE))
}
评论
yr_datayr_data[year]