dlookr (version 0.5.2)

diagnose_report.tbl_dbi: Reporting the information of data diagnosis for table of the DBMS

Description

The diagnose_report() report the information for diagnosing the quality of the DBMS table through tbl_dbi

Usage

# S3 method for tbl_dbi
diagnose_report(
  .data,
  output_format = c("pdf", "html"),
  output_file = NULL,
  output_dir = tempdir(),
  font_family = NULL,
  in_database = FALSE,
  collect_size = Inf,
  ...
)

Arguments

.data

a tbl_dbi.

output_format

report output type. Choose either "pdf" and "html". "pdf" create pdf file by knitr::knit(). "html" create html file by rmarkdown::render().

output_file

name of generated file. default is NULL.

output_dir

name of directory to generate report file. default is tempdir().

font_family

character. font family name for figure in pdf.

in_database

Specifies whether to perform in-database operations. If TRUE, most operations are performed in the DBMS. if FALSE, table data is taken in R and operated in-memory. Not yet supported in_database = TRUE.

collect_size

a integer. The number of data samples from the DBMS to R. Applies only if in_database = FALSE.

...

arguments to be passed to methods.

Reported information

Reported from the data diagnosis is as follows.

• Diagnose Data

  • Overview of Diagnosis

    • List of all variables quality

    • Diagnosis of missing data

    • Diagnosis of unique data(Text and Category)

    • Diagnosis of unique data(Numerical)

  • Detailed data diagnosis

    • Diagnosis of categorical variables

    • Diagnosis of numerical variables

    • List of numerical diagnosis (zero)

    • List of numerical diagnosis (minus)

• Diagnose Outliers

  • Overview of Diagnosis

    • Diagnosis of numerical variable outliers

    • Detailed outliers diagnosis

See vignette("diagonosis") for an introduction to these concepts.

Details

Generate generalized data diagnostic reports automatically. You can choose to output to pdf and html files. This is useful for diagnosing a data frame with a large number of variables than data with a small number of variables. For pdf output, Korean Gothic font must be installed in Korean operating system.

See Also

diagnose_report.data.frame.

Examples

# NOT RUN {
if (FALSE) {
library(dplyr)

# Generate data for the example
heartfailure2 <- heartfailure
heartfailure2[sample(seq(NROW(heartfailure2)), 20), "platelets"] <- NA
heartfailure2[sample(seq(NROW(heartfailure2)), 5), "smoking"] <- NA

# connect DBMS
# con_sqlite <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")

# copy heartfailure2 to the DBMS with a table named TB_HEARTFAILURE
# copy_to(con_sqlite, heartfailure2, name = "TB_HEARTFAILURE", overwrite = TRUE)

# reporting the diagnosis information -------------------------
# create pdf file. file name is DataDiagnosis_Report.pdf
# con_sqlite %>% 
#   tbl("TB_HEARTFAILURE") %>% 
#   diagnose_report()
  
# create pdf file. file name is Diagn.pdf, and collect size is 350
# con_sqlite %>% 
#   tbl("TB_HEARTFAILURE") %>% 
#   diagnose_report(collect_size = 350, output_file = "Diagn.pdf")

# create html file. file name is Diagnosis_Report.html
# con_sqlite %>% 
#   tbl("TB_HEARTFAILURE") %>% 
#   diagnose_report(output_format = "html")

# create html file. file name is Diagn.html
# con_sqlite %>% 
#   tbl("TB_HEARTFAILURE") %>% 
#   diagnose_report(output_format = "html", output_file = "Diagn.html")
  
# Disconnect DBMS   
# DBI::dbDisconnect(con_sqlite)
}

# }