updates

R/ids_query_data.R

@@ -1,7 +1,8 @@
 utils::globalVariables(c("data_last_updated","api_code", "wb_creditor_name", "wb_debtor_country_name"))
 
-#' ids_query_data
-#' Gets debt information for a given country (debtor) that it owes to any creditor.
+#' @title Query debt data
+#' @description
+#' Query debt information for a given country (debtor) that it owes to any creditor.
 #' The default creditors are both China and the World
 #'
 #' @param etl_object An `etl` object

README.Rmd

@@ -102,7 +102,7 @@ unique_time %>% head() %>% kable()
 We create an ETL object by specifying a string that defines the object's class, and use the package `idswb` to gain access to the relevant data.
 ```{r}
 # ceating an object
-idswb_ob <-etl("idswb", dir = getwd())
+# idswb_ob <-etl("idswb", dir = getwd())
 
 ```
 
@@ -114,7 +114,7 @@ idswb_ob <-etl("idswb", dir = getwd())
 
 The first step here is to acquire data
 ```{r}
-idswb_ob %>% etl_extract()
+# idswb_ob %>% etl_extract()
 ```
 
 ```{r}
@@ -124,7 +124,7 @@ idswb_ob %>% etl_extract()
 
 This data might require conversion from its original format into files that are appropriate for SQL import, typically in CSV format.
 ```{r}
-idswb_ob %>% etl_transform()
+# idswb_ob %>% etl_transform()
 ```
 
 ```{r}
@@ -134,14 +134,14 @@ idswb_ob %>% etl_transform()
 
 Fill the SQL database with the processed data.
 ```{r}
-idswb_ob %>% etl_load()
+# idswb_ob %>% etl_load()
 ```
 
 ```{r}
 
 ```
 We can still perform the steps above at once
-```{r eval=FALSE}
+```{r message = FALSE, warning=FALSE}
 # ceating an object
 idswb_ob <-etl("idswb", dir = getwd())
 
@@ -156,6 +156,10 @@ idswb_ob %>%
 
 ```{r}
 
+```
+## Using etl_create method
+```{r}
+# idswb_ob %>% etl_create()
 ```
 
 ```{r}
@@ -167,46 +171,35 @@ We can now query debt of a given country that it owes to both China and the Worl
 
 `Query 1:`
 ```{r}
-dplyr::tbl(idswb_ob, "ids_wb") %>% 
-  # query data
-  dplyr::filter(wb_debtor_country_name == "Kenya",
-         wb_creditor_name %in% c("China","World"),
-         api_code %in% c("DT.DOD.BLAT.CD",
-                         "DT.DOD.PBND.CD",
-                         'DT.DOD.MLAT.CD',
-                         "DT.DOD.PROP.CD",
-                         "DT.DOD.PCBK.CD",
-                         "DT.DOD.DPPG.CD")) %>% 
-  dplyr::collect() %>% 
-  # gather data
-  gather(key = year,value = debt,-c(api_code, data_last_updated, series_full_name, wb_debtor_country_name, wb_debtor_country_id,  
-                                    wb_creditor_name, wb_creditor_id)) %>% 
-  filter(year == 2022) %>% 
-  mutate(data_last_updated = as_datetime(as.numeric(data_last_updated))) %>% 
+# inputs specificatio
+series <- c("DT.DOD.BLAT.CD","DT.DOD.PBND.CD",'DT.DOD.MLAT.CD',"DT.DOD.PROP.CD","DT.DOD.PCBK.CD","DT.DOD.DPPG.CD")
+debtor <- "Kenya"
+creditor <- c("China","World")
+
+# Querying data
+ids_query_data(etl_object = idswb_ob, debtor = debtor, creditor = creditor, series = series) %>% 
+  filter(year == "2022") %>% 
   knitr::kable()
+
 ```
 
 ```{r}
 
 ```
 `Query 2:`
 ```{r}
-dplyr::tbl(idswb_ob, "ids_wb") %>% 
-  # query data
-  dplyr::filter(wb_debtor_country_name == "Nigeria",
-         wb_creditor_name %in% c("China","World"),
-         api_code %in% c("DT.DOD.BLAT.CD",
-                         "DT.DOD.PBND.CD",
-                         'DT.DOD.MLAT.CD',
-                         "DT.DOD.PROP.CD",
-                         "DT.DOD.PCBK.CD",
-                         "DT.DOD.DPPG.CD")) %>% 
-  dplyr::collect() %>% 
-  # gather data
-  gather(key = year,value = debt,-c(api_code, data_last_updated, series_full_name, wb_debtor_country_name, wb_debtor_country_id,  
-                                    wb_creditor_name, wb_creditor_id)) %>% 
-  filter(year == 2022) %>% 
-  mutate(data_last_updated = as_datetime(as.numeric(data_last_updated))) %>% 
+# inputs specificatio
+series <- c("DT.DOD.BLAT.CD","DT.DOD.PBND.CD",'DT.DOD.MLAT.CD',"DT.DOD.PROP.CD","DT.DOD.PCBK.CD","DT.DOD.DPPG.CD")
+debtor <- "Nigeria"
+creditor <- c("China","World")
+
+# Querying data
+ids_query_data(etl_object = idswb_ob, debtor = debtor, creditor = creditor, series = series) %>% 
+  filter(year == "2022") %>% 
   knitr::kable()
 ```
 
+```{r}
+
+```
+