Create Histogram(s)

Usage

TADA_Histogram(.data, id_cols = c("TADA.ComparableDataIdentifier"))

Arguments

.data: TADA dataframe containing the data downloaded from the WQP, where each row represents a unique data record. Dataframe must include the columns 'TADA.ComparableDataIdentifier', 'TADA.ResultMeasureValue', and 'TADA.ResultMeasure.MeasureUnitCode' to run this function. 'TADA.ComparableDataIdentifier' can be added to the data frame by running the function TADA_HarmonizeSynonyms(). The user can include additional grouping columns in the id_cols input. If more than one group exists in the dataframe (i.e. two or more unique comparable data identifiers), the function creates a list of plots, where each list element name is a unique group identifier.
id_cols: The column(S) in the dataframe used to identify the unique groups to be plotted. Defaults to 'TADA.ComparableDataIdentifier'.

Value

A list of plotly histogram figures showing the distribution of sample values for each data group.

Examples

# Load example dataframe:
utils::data(Data_6Tribes_5y_Harmonized)

# Create a histogram for each comparable data group (TADA.ComparableDataIdentifier)
# in the input dataframe:
TADA_Histogram(Data_6Tribes_5y_Harmonized, id_cols = "TADA.ComparableDataIdentifier")
#> $`ALKALINITY, TOTAL TOTAL AS CACO3 PCU`
#> 
#> $`ALKALINITY TOTAL AS CACO3 UG/L`
#> 
#> $`AMMONIA UNFILTERED AS N MG/L`
#> 
#> $`AMMONIUM UNFILTERED AS N MG/L`
#> 
#> $`APPARENT COLOR TOTAL PCU`
#> 
#> $`CONDITION CLASS (DISSOLVED OXYGEN (DO)) %`
#> 
#> $`COUNT COUNT`
#> 
#> $`DEPTH, SECCHI DISK DEPTH M`
#> 
#> $`DEPTH, SNOW COVER IN`
#> 
#> $`DISCHARGE, RIVER/STREAM CFS`
#> 
#> $`DISSOLVED OXYGEN (DO) MG/L`
#> 
#> $`DISSOLVED OXYGEN SATURATION %`
#> 
#> $`DISSOLVED OXYGEN UPTAKE UG/L`
#> 
#> $`ESCHERICHIA COLI CFU/100ML`
#> 
#> $`ESCHERICHIA COLI UNFILTERED CFU/100ML`
#> 
#> $`EXTRACTABLE ORGANIC MATTER (EOM) %`
#> 
#> $`EXTRACTABLE ORGANIC MATTER (EOM) G/M2`
#> 
#> $`HARDNESS, CARBONATE AS CACO3 UG/L`
#> 
#> $`HARDNESS, CARBONATE UG/L`
#> 
#> $`HARDNESS, CARBONATE TOTAL AS CACO3 UG/L`
#> 
#> $`HARDNESS, CARBONATE TOTAL UG/L`
#> 
#> $`HEIGHT, GAGE M`
#> 
#> $`LOONS, VISUAL OBSERVATION COUNT`
#> 
#> $`NITRATE + NITRITE FILTERED AS N MG/L`
#> 
#> $`NITRATE + NITRITE UNFILTERED AS N MG/L`
#> 
#> $`NITRATE UNFILTERED AS N MG/L`
#> 
#> $`NITRITE UNFILTERED AS N MG/L`
#> 
#> $`ORTHOPHOSPHATE FILTERED AS P UG/L`
#> 
#> $`ORTHOPHOSPHATE UNFILTERED AS P UG/L`
#> 
#> $`PERIPHYTON G/M2`
#> 
#> $PH
#> 
#> $`PRESSURE G/M2`
#> 
#> $`PRESSURE MMHG`
#> 
#> $`RADIUM-226 PCI/L`
#> 
#> $`RADIUM-226 TOTAL PCI/L`
#> 
#> $`RADIUM-228 PCI/L`
#> 
#> $`RESISTIVITY US/CM`
#> 
#> $`SULFATE TOTAL AS SO4 UG/L`
#> 
#> $`TEMPERATURE DEG C`
#> 
#> $`TOTAL HARDNESS TOTAL AS CACO3 MG/L`
#> 
#> $`TOTAL KJELDAHL NITROGEN (ORGANIC N & NH3) UNFILTERED AS N MG/L`
#> 
#> $`TOTAL NITROGEN, MIXED FORMS UNFILTERED AS N MG/L`
#> 
#> $`TOTAL PHOSPHORUS, MIXED FORMS FILTERED AS P UG/L`
#> 
#> $`TOTAL PHOSPHORUS, MIXED FORMS UNFILTERED AS P UG/L`
#> 
#> $`TRANSPARENCY, SECCHI TUBE WITH DISK IN`
#> 
#> $`TRITIUM PCI/L`
#> 
#> $`VOLATILE SUSPENDED SOLIDS TOTAL UG/L`
#> 
#> $`WIND VELOCITY M/SEC`
#> 

# Create a single histogram using defaults. The input dataframe in this example
# is filtered so it includes only one TADA.ComparableDataIdentifier
df <- dplyr::filter(
  Data_6Tribes_5y_Harmonized,
  TADA.ComparableDataIdentifier ==
    "TOTAL PHOSPHORUS, MIXED FORMS_UNFILTERED_AS P_UG/L"
)
TADA_Histogram(df, id_cols = "TADA.ComparableDataIdentifier")


# Create multiple histograms with additional grouping columns and view the first
# plot in list. In this example, we will group by both TADA.ComparableDataIdentifier
# and MonitoringLocationTypeName (e.g. stream, reservoir, canal, etc.)
# Load example dataframe:
utils::data(Data_Nutrients_UT)
Histogram_output <- TADA_Histogram(Data_Nutrients_UT,
  id_cols = c(
    "TADA.ComparableDataIdentifier",
    "MonitoringLocationTypeName"
  )
)
#> Plotting function removed 2582 results where TADA.ResultMeasureValue = NA. These results cannot be plotted.
# This example generates 46 histograms
Histogram_output[[10]]

Histogram_output[[25]]

Histogram_output[[30]]