ts_line: Time Series for multiple monitors' temporal atmospheric data
In gmcginnis/AirVizR: Visualization Tools for Air Quality Data

Description Usage Arguments Value See Also Examples

Visualize temporal atmospheric data for multiple monitors, with optional minimum and maximum labels and a moving average. Relevant information (such as date ranges, averaging methods, facets, and min/max values in the set) will be reported autmatically in the visualization.

ts_line(
  dataset,
  variable_of_interest,
  add_extrema = TRUE,
  digits = 2,
  add_points = FALSE,
  add_average = TRUE,
  label_filter = c(""),
  cap_value = NA,
  cap_color = "green",
  single_column = FALSE,
  label_length = 10,
  avg_color = "darkgreen",
  min_color = "royalblue",
  max_color = "darkorange",
  location_data = data_meta
)

`dataset`	The hourly dataset to visualize
`variable_of_interest`	The variable of interest (not in quotation marks) which to visualize
`add_extrema`	Logical; label the extreme (minimum and maximum) valuess of the monitors of interest
`digits`	Numeric; the number of digits to report
`add_points`	Logical; add colored points for the `variable_of_interest`
`add_average`	Logical; add a seprate plot for the average of ALL monitors in a set, to be a line colored by avg_color
`label_filter`	Character list, optional (but recommended for large sets); list of monitor labels to be spotlighted (note: does NOT remove unspecified labels, which will remain as gray background lines)
`cap_value`	Numeric, optional; values at or above to be colored serpately from the regular continuous scale. See add_cap for more information.
`cap_color`	Character; color for values at or above the `cap_value`
`single_column`	Logical; plot the data all as a single column, making cross-comparisons for monitors at specific times easier
`label_length`	Character; applied if `single_column` is `TRUE`, the number of characters for which to wrap the monitor label
`avg_color, min_color, max_color`	Character; colors for the average line, minimum text label, and maximum text label, respectively
`location_data`	Data set containing latitude and longitude data

Data visualization: line graph time series spotlighting individual monitors, with background graphics representing the time series data for all other monitors in the set.

Other STAD visualizations: heatmap_cross(), heatmap_single(), map_oa(), map_stad(), ts_variation()

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ts_line(july_api_hourly, pm25_atm, label_filter = "\\bPSU\\b", location_data = july_api_meta)
ts_line(july_api_hourly, pm25_atm, label_filter = c("\\bPSU\\b"), add_points = TRUE, single_column = TRUE, add_average = FALSE, location_data = july_api_meta)