psyosphere (version 0.1.6)

des_mean: Calculate normal and weighted means while excluding gaps in data

Description

Calculate normal and weighted means while excluding gaps in data

Usage

des_mean(
  tracks, ctarget, cweight = "", cgaps = "", cname = "mean", drop = TRUE,
  t_id = "id", des_df = ""
)

Arguments

tracks

psyo. Data frame with tracks.

ctarget

character. Column name of tracks that contains the variable for the calculation.

cweight

character. Column name of tracks that contains the weight for the calculation.

cgaps

character. Column name of tracks that marks gaps with TRUE.

cname

character. Column name of the returned calculation result.

drop

logical. If TRUE and only one observation is returned drop the data frame and collapse the return value to a vector.

t_id

character or numeric. Column name in tracks that identifies the separate tracks.

des_df

data frame. Function results will be merge with this data frame.

Value

Data frame

id

id of the track

mean

calculated mean of the track

Credit

If you use 'psyosphere' for commercial use or research, please support us by include one off the following references:

• MIT license: "psyosphere" by B. Ziepert, E. G. Ufkes & P. W. de Vries from https://CRAN.R-project.org/package=psyosphere

• APA: Ziepert, B., Ufkes, E., & de Vries, P. W. (2018). psyosphere: Analyse GPS Data. Retrieved from https://CRAN.R-project.org/package=psyosphere

• APA: Vries, P., Ziepert, B., & Ufkes, E. (2016). "De psychologie van bewegingen GPS-technologie voor de analyse van natuurlijk gedrag." Tijdschrift voor Human Factors 2: 11-15.

See Also

des_summary, des_duplicates, des_first, des_last, des_length, des_max, des_min, des_sd, des_sum

Examples

# NOT RUN {
# Get example data
data(psyo_rounds2)
psyo_rounds2 <- psyo_rounds2[ c(1:5,11:15) ,]

# clean-up data
psyo_rounds2 <- average_duplicates(psyo_rounds2)

# Add gap segments
psyo_rounds2 <- t_time_difference(psyo_rounds2)
psyo_rounds2 <- mark_time_gaps(psyo_rounds2)

# Add speed
psyo_rounds2 <- t_speed(psyo_rounds2)

# Calculate different means
normal <- des_mean(psyo_rounds2, "speed", cname = "normal")

weighted <- des_mean(
  psyo_rounds2, "speed", cweight = "time_difference", cname = "weighted"
)

segmented <- des_mean(
  psyo_rounds2, "speed", cgaps= "time_gap", cname = "segmented"
)

segmented_weighted <- des_mean(
  psyo_rounds2,
  "speed",
  cweight = "time_difference",
  cgaps = "time_gap",
  cname = "segmented_weighted"
)

# }