Tidyquant包和tibble金融信息访问
Tidyquant包和tibble金融信息访问
提问于 2018-03-08 15:24:09
我目前正在运行以下代码，以便从quantmod包中提取一些财务信息。
library(quantmod)
symbols <- c("HOG", "GOOG", "GE")
tickers <- new.env()
lapply(symbols, getFinancials, env=tickers)
BS <- data.frame(lapply(tickers, function(x) {viewFinancials(x, type= 'BS', period = 'A')}))
IS <- data.frame(lapply(tickers, function(x) {viewFinancials(x, type= 'IS', period = 'A')}))
CF <- data.frame(lapply(tickers, function(x) {viewFinancials(x, type= 'CF', period = 'A')}))
df <- rbind(BS, IS, CF)
df <- t(df)这有点混乱，但从这里开始，我可以清理数据并进行一些计算。但是，我想知道是否有一种更有效的方法使用tidyquant包，因为我想在许多代码符号上运行它，当quantmod包无法下载/查找特定代码的财务信息时，它正在崩溃。
我和他一起工作；
library(tidyquant)
library(dplyr)
symbols <- c("HOG", "GOOG", "GE")
stock_financials <- symbols %>%
tq_get(get = "financials")
stock_financials$annual我可以看到数据是tibble中的tibble，但是如何才能像以前那样提取信息，或者如何更容易地访问stock_financials$annual的tibble数据？
修改和使用
filter(stock_financials, type == "BS") %>% unnest()从这个角度来看，answer似乎不适合我。
回答 1
Stack Overflow用户
回答已采纳
发布于 2018-03-12 15:06:29
下面是使用gather和unnest的tidyr包的一个简单解决方案。一旦您完成了gather()和unnest()组合，您就可以过滤到任何部分和您想要的符号组合。
> library(tidyquant)
> library(dplyr)
>
> symbols <- c("HOG", "GOOG", "GE")
>
> stock_financials <- symbols %>%
+ tq_get(get = "financials")
>
> stock_financials
# A tibble: 9 x 4
symbol type annual quarter
<chr> <chr> <list> <list>
1 HOG BS <tibble [168 x 4]> <tibble [210 x 4]>
2 HOG CF <tibble [76 x 4]> <tibble [76 x 4]>
3 HOG IS <tibble [196 x 4]> <tibble [245 x 4]>
4 GOOG BS <tibble [168 x 4]> <tibble [210 x 4]>
5 GOOG CF <tibble [76 x 4]> <tibble [76 x 4]>
6 GOOG IS <tibble [196 x 4]> <tibble [245 x 4]>
7 GE BS <tibble [168 x 4]> <tibble [210 x 4]>
8 GE CF <tibble [76 x 4]> <tibble [76 x 4]>
9 GE IS <tibble [196 x 4]> <tibble [245 x 4]>
>
> stock_financials %>%
+ gather(key = "key", value = "value", annual, quarter) %>%
+ unnest()
# A tibble: 2,913 x 7
symbol type key group category date value
<chr> <chr> <chr> <int> <chr> <date> <dbl>
1 HOG BS annual 1 Cash & Equivalents 2017-12-31 688.
2 HOG BS annual 1 Cash & Equivalents 2016-12-31 760.
3 HOG BS annual 1 Cash & Equivalents 2015-12-31 722.
4 HOG BS annual 1 Cash & Equivalents 2014-12-31 907.
5 HOG BS annual 2 Short Term Investments 2017-12-31 0.
6 HOG BS annual 2 Short Term Investments 2016-12-31 5.52
7 HOG BS annual 2 Short Term Investments 2015-12-31 45.2
8 HOG BS annual 2 Short Term Investments 2014-12-31 57.3
9 HOG BS annual 3 Cash and Short Term Investments 2017-12-31 688.
10 HOG BS annual 3 Cash and Short Term Investments 2016-12-31 766.
# ... with 2,903 more rows页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/49176655
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