Tidyquant 包和 tibble 金融信息访问
Tidyquant package and tibble financial information access
我目前运行正在编写以下代码,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)
有点乱,但我可以从这里清理数据并进行一些计算。但是我想知道是否有使用 tidyquant
包的更有效的方法,因为我想 运行 这超过许多股票代码,并且当 quantmod
包不能 download/find 特定代码的财务信息。
我正在工作;
library(tidyquant)
library(dplyr)
symbols <- c("HOG", "GOOG", "GE")
stock_financials <- symbols %>%
tq_get(get = "financials")
stock_financials$annual
我可以看到数据是一个 tibble 中的一个 tibble,但是如何才能像以前一样提取信息,或者我怎样才能更轻松地访问 stock_financials$annual
的 tibble 数据?
修改和使用
filter(stock_financials, type == "BS") %>% unnest()
由此看来 似乎对我不起作用。
这是一个使用 tidyr
包中的 gather
和 unnest
的简单解决方案。一旦您执行了 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
我目前运行正在编写以下代码,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)
有点乱,但我可以从这里清理数据并进行一些计算。但是我想知道是否有使用 tidyquant
包的更有效的方法,因为我想 运行 这超过许多股票代码,并且当 quantmod
包不能 download/find 特定代码的财务信息。
我正在工作;
library(tidyquant)
library(dplyr)
symbols <- c("HOG", "GOOG", "GE")
stock_financials <- symbols %>%
tq_get(get = "financials")
stock_financials$annual
我可以看到数据是一个 tibble 中的一个 tibble,但是如何才能像以前一样提取信息,或者我怎样才能更轻松地访问 stock_financials$annual
的 tibble 数据?
修改和使用
filter(stock_financials, type == "BS") %>% unnest()
由此看来
这是一个使用 tidyr
包中的 gather
和 unnest
的简单解决方案。一旦您执行了 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