time_series_map: Function maps time series flood data, either by gage or by...
In rodlammers/countyfloods: Quantify United States County-Level Flood Measurements

Description Usage Arguments Value Examples

Displays a state or multi-state map summarizing flood analysis results either by gage or county for each individual date with data.

1	time_series_map(flood_stats, category = "minor", filename = "")

`flood_stats`	Either a data frame of flood analysis results, by gage or by county, or a list of both data frames.
`category`	Character string of the flood magnitude category to be used for mapping (one of "minor", "moderate", "major", or "extreme"). This parameter only works when mapping county-level, rather than gage-level, values.
`filename`	Character string of the file path and beginning of name of where to save the individual images generated. For example, "C:/Desktop/TX" would produce image files saved as "TX_Gage_Map_Date.png" or "TX_County_Map_Date.png" where "Date" is replaced by the actual date. If no filename is provided, the images aren't saved but are displayed in the plot viewer.

For each date with data, a map of the state(s) analyzed showing counties and gages color coded based on flood magnitude, depending on the type of data in flood_stats. Gage flood thresholds are "None" (flood_ratio < 1), "Minor" (flood_ratio < 1.5), "Moderate" (flood_ratio < 2), "Major" (flood_ratio < 5), and "Extreme" (flood_ratio > 5). For county aggregate maps, flood exposure is assessed based on the percentage of gages in the county at or above a specified flood threshold. Exposure categories include "Low" (0 (20 (80

## Not run: 
#Use the time_series_flood function with option filter_data = FALSE to get data
  tx <- time_series_flood(state = "Texas", start_date = "2017-08-24", end_date =
        "2017-09-10", filter_data = FALSE)

#Returns a list of gage data and county data. Can map them individually or all at once

## End(Not run)