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CodeBook.Rmd
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---
dataReporter: yes
title: Codeboook for summary data calculated from the UCI HAR data set for the Coursera Course 'Getting and Cleaning Data'
subtitle: "Autogenerated data summary from dataReporter"
date: 2021-12-31 16:41:30
output:
md_document:
variant: markdown_github
geometry: margin=2cm
documentclass: article
header-includes:
- \newcommand{\fullline}{\noindent\makebox[\linewidth]{\rule{\textwidth}{0.4pt}}}
- \renewcommand\familydefault{\sfdefault}
- \newcommand{\bminione}{\begin{minipage}{0.75 \textwidth}}
- \newcommand{\bminitwo}{\begin{minipage}{0.25 \textwidth}}
- \newcommand{\emini}{\end{minipage}}
---
```{r , echo=FALSE, include=FALSE, warning=FALSE, message=FALSE, error=FALSE}
library("ggplot2")
library("pander")
```
```{r 'visualFunctions', echo=FALSE, include=FALSE, warning=FALSE, message=FALSE, error=FALSE}
ggAggHist <- getFromNamespace("ggAggHist", "dataReporter")
ggAggBarplot <- getFromNamespace("ggAggBarplot", "dataReporter")
```
# Data report overview
The data set examined has the following dimensions:
---------------------------------
Feature Result
------------------------ --------
Number of observations 180
Number of variables 74
---------------------------------
# Data manipulation summary
The data set was originally sourced from UCI HAR and tidied into the presented format. The training and test data sets were processed in parallel by associating activity names to levels as described in activity_labels.txt and cleaning up variable names (extended descriptions added to labels after merging) before identifying and extracting only variables for which the mean and standard deviations are present. The combined data set was then used to calculate the average of each variable (mean and standard deviation) for each activity and subject.
# Codebook summary table
------------------------------------------------------------------------------------------------------------------------
Label Variable Class # unique Missing Description
values
------------------- ------------------------------------------------------- --------- ---------- --------- -------------
subject **[subject]** factor 30 0.00 %
activity **[activity]** factor 6 0.00 %
Time domain **[t\_body\_acc\_mean\_x]** numeric 180 0.00 %
body-component
accelerometer
mean (x)
Time domain **[t\_body\_acc\_mean\_y]** numeric 180 0.00 %
body-component
accelerometer
mean (y)
Time domain **[t\_body\_acc\_mean\_z]** numeric 180 0.00 %
body-component
accelerometer
mean (z)
Time domain **[t\_body\_acc\_std\_x]** numeric 180 0.00 %
body-component
accelerometer
std (x)
Time domain **[t\_body\_acc\_std\_y]** numeric 180 0.00 %
body-component
accelerometer
std (y)
Time domain **[t\_body\_acc\_std\_z]** numeric 180 0.00 %
body-component
accelerometer
std (z)
Time domain **[t\_gravity\_acc\_mean\_x]** numeric 180 0.00 %
gravity-component
accelerometer
mean (x)
Time domain **[t\_gravity\_acc\_mean\_y]** numeric 180 0.00 %
gravity-component
accelerometer
mean (y)
Time domain **[t\_gravity\_acc\_mean\_z]** numeric 180 0.00 %
gravity-component
accelerometer
mean (z)
Time domain **[t\_gravity\_acc\_std\_x]** numeric 180 0.00 %
gravity-component
accelerometer
std (x)
Time domain **[t\_gravity\_acc\_std\_y]** numeric 180 0.00 %
gravity-component
accelerometer
std (y)
Time domain **[t\_gravity\_acc\_std\_z]** numeric 180 0.00 %
gravity-component
accelerometer
std (z)
Time domain **[t\_body\_acc\_jerk\_mean\_x]** numeric 180 0.00 %
body-component
accelerometer
jerk mean
(x)
Time domain **[t\_body\_acc\_jerk\_mean\_y]** numeric 180 0.00 %
body-component
accelerometer
jerk mean
(y)
Time domain **[t\_body\_acc\_jerk\_mean\_z]** numeric 180 0.00 %
body-component
accelerometer
jerk mean
(z)
Time domain **[t\_body\_acc\_jerk\_std\_x]** numeric 180 0.00 %
body-component
accelerometer
jerk std (x)
Time domain **[t\_body\_acc\_jerk\_std\_y]** numeric 180 0.00 %
body-component
accelerometer
jerk std (y)
Time domain **[t\_body\_acc\_jerk\_std\_z]** numeric 180 0.00 %
body-component
accelerometer
jerk std (z)
Time domain **[t\_body\_gyro\_mean\_x]** numeric 180 0.00 %
body-component
gyroscopic
mean (x)
Time domain **[t\_body\_gyro\_mean\_y]** numeric 180 0.00 %
body-component
gyroscopic
mean (y)
Time domain **[t\_body\_gyro\_mean\_z]** numeric 180 0.00 %
body-component
gyroscopic
mean (z)
Time domain **[t\_body\_gyro\_std\_x]** numeric 180 0.00 %
body-component
gyroscopic
std (x)
Time domain **[t\_body\_gyro\_std\_y]** numeric 180 0.00 %
body-component
gyroscopic
std (y)
Time domain **[t\_body\_gyro\_std\_z]** numeric 180 0.00 %
body-component
gyroscopic
std (z)
Time domain **[t\_body\_gyro\_jerk\_mean\_x]** numeric 180 0.00 %
body-component
gyroscopic
jerk mean
(x)
Time domain **[t\_body\_gyro\_jerk\_mean\_y]** numeric 180 0.00 %
body-component
gyroscopic
jerk mean
(y)
Time domain **[t\_body\_gyro\_jerk\_mean\_z]** numeric 180 0.00 %
body-component
gyroscopic
jerk mean
(z)
Time domain **[t\_body\_gyro\_jerk\_std\_x]** numeric 180 0.00 %
body-component
gyroscopic
jerk std (x)
Time domain **[t\_body\_gyro\_jerk\_std\_y]** numeric 180 0.00 %
body-component
gyroscopic
jerk std (y)
Time domain **[t\_body\_gyro\_jerk\_std\_z]** numeric 180 0.00 %
body-component
gyroscopic
jerk std (z)
Time domain **[t\_body\_acc\_mag\_mean]** numeric 180 0.00 %
body-component
accelerometer
magnitude
mean
Time domain **[t\_body\_acc\_mag\_std]** numeric 180 0.00 %
body-component
accelerometer
magnitude
std
Time domain **[t\_gravity\_acc\_mag\_mean]** numeric 180 0.00 %
gravity-component
accelerometer
magnitude
mean
Time domain **[t\_gravity\_acc\_mag\_std]** numeric 180 0.00 %
gravity-component
accelerometer
magnitude
std
Time domain **[t\_body\_acc\_jerk\_mag\_mean]** numeric 180 0.00 %
body-component
accelerometer
jerk
magnitude
mean
Time domain **[t\_body\_acc\_jerk\_mag\_std]** numeric 180 0.00 %
body-component
accelerometer
jerk
magnitude
std
Time domain **[t\_body\_gyro\_mag\_mean]** numeric 180 0.00 %
body-component
gyroscopic
magnitude
mean
Time domain **[t\_body\_gyro\_mag\_std]** numeric 180 0.00 %
body-component
gyroscopic
magnitude
std
Time domain **[t\_body\_gyro\_jerk\_mag\_mean]** numeric 180 0.00 %
body-component
gyroscopic
jerk
magnitude
mean
Time domain **[t\_body\_gyro\_jerk\_mag\_std]** numeric 180 0.00 %
body-component
gyroscopic
jerk
magnitude
std
Frequency **[f\_body\_acc\_mean\_x]** numeric 180 0.00 %
domain
body-component
accelerometer
mean (x)
Frequency **[f\_body\_acc\_mean\_y]** numeric 180 0.00 %
domain
body-component
accelerometer
mean (y)
Frequency **[f\_body\_acc\_mean\_z]** numeric 180 0.00 %
domain
body-component
accelerometer
mean (z)
Frequency **[f\_body\_acc\_std\_x]** numeric 180 0.00 %
domain
body-component
accelerometer
std (x)
Frequency **[f\_body\_acc\_std\_y]** numeric 180 0.00 %
domain
body-component
accelerometer
std (y)
Frequency **[f\_body\_acc\_std\_z]** numeric 180 0.00 %
domain
body-component
accelerometer
std (z)
Frequency **[f\_body\_acc\_jerk\_mean\_x]** numeric 180 0.00 %
domain
body-component
accelerometer
jerk mean
(x)
Frequency **[f\_body\_acc\_jerk\_mean\_y]** numeric 180 0.00 %
domain
body-component
accelerometer
jerk mean
(y)
Frequency **[f\_body\_acc\_jerk\_mean\_z]** numeric 180 0.00 %
domain
body-component
accelerometer
jerk mean
(z)
Frequency **[f\_body\_acc\_jerk\_std\_x]** numeric 180 0.00 %
domain
body-component
accelerometer
jerk std (x)
Frequency **[f\_body\_acc\_jerk\_std\_y]** numeric 180 0.00 %
domain
body-component
accelerometer
jerk std (y)
Frequency **[f\_body\_acc\_jerk\_std\_z]** numeric 180 0.00 %
domain
body-component
accelerometer
jerk std (z)
Frequency **[f\_body\_gyro\_mean\_x]** numeric 180 0.00 %
domain
body-component
gyroscopic
mean (x)
Frequency **[f\_body\_gyro\_mean\_y]** numeric 180 0.00 %
domain
body-component
gyroscopic
mean (y)
Frequency **[f\_body\_gyro\_mean\_z]** numeric 180 0.00 %
domain
body-component
gyroscopic
mean (z)
Frequency **[f\_body\_gyro\_std\_x]** numeric 180 0.00 %
domain
body-component
gyroscopic
std (x)
Frequency **[f\_body\_gyro\_std\_y]** numeric 180 0.00 %
domain
body-component
gyroscopic
std (y)
Frequency **[f\_body\_gyro\_std\_z]** numeric 180 0.00 %
domain
body-component
gyroscopic
std (z)
Frequency **[f\_body\_acc\_mag\_mean]** numeric 180 0.00 %
domain
body-component
accelerometer
magnitude
mean
Frequency **[f\_body\_acc\_mag\_std]** numeric 180 0.00 %
domain
body-component
accelerometer
magnitude
std
Frequency **[f\_body\_body\_acc\_jerk\_mag\_mean]** numeric 180 0.00 %
domain
body-component
accelerometer
jerk
magnitude
mean
Frequency **[f\_body\_body\_acc\_jerk\_mag\_std]** numeric 180 0.00 %
domain
body-component
accelerometer
jerk
magnitude
std
Frequency **[f\_body\_body\_gyro\_mag\_mean]** numeric 180 0.00 %
domain
body-component
gyroscopic
magnitude
mean
Frequency **[f\_body\_body\_gyro\_mag\_std]** numeric 180 0.00 %
domain
body-component
gyroscopic
magnitude
std
Frequency **[f\_body\_body\_gyro\_jerk\_mag\_mean]** numeric 180 0.00 %
domain
body-component
gyroscopic
jerk
magnitude
mean
Frequency **[f\_body\_body\_gyro\_jerk\_mag\_std]** numeric 180 0.00 %
domain
body-component
gyroscopic
jerk
magnitude
std
Time domain **[angle\_t\_body\_acc\_jerk\_mean\_gravity\_mean]** numeric 180 0.00 %
angle
between the
body-component
accelerometer
jerk mean
and the
gravity-component
mean
Time domain **[angle\_t\_body\_gyro\_mean\_gravity\_mean]** numeric 180 0.00 %
angle
between the
body-component
gyroscopic
mean and the
gravity-component
mean
Time domain **[angle\_t\_body\_gyro\_jerk\_mean\_gravity\_mean]** numeric 180 0.00 %
angle
between the
body-component
gyroscopic
jerk mean
and the
gravity-component
mean
Angle (x) **[angle\_x\_gravity\_mean]** numeric 180 0.00 %
for the
gravity-component
mean
Angle (y) **[angle\_y\_gravity\_mean]** numeric 180 0.00 %
for the
gravity-component
mean
Angle (z) **[angle\_z\_gravity\_mean]** numeric 180 0.00 %
for the
gravity-component
mean
------------------------------------------------------------------------------------------------------------------------
# Variable list
## subject
*subject*
\bminione
-----------------------------------
Feature Result
------------------------- ---------
Variable type factor
Number of missing obs. 0 (0 %)
Number of unique values 30
Mode "1"
Reference category 1
-----------------------------------
\emini
\bminitwo
```{r 'Var-1-subject', echo=FALSE, fig.width=4, fig.height=3, message=FALSE, warning=FALSE}
ggAggBarplot(data = structure(list(x = structure(1:30, .Label = c("1",
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13",
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24",
"25", "26", "27", "28", "29", "30"), class = "factor"), y = c(6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L)), class = "data.frame", row.names = c(NA,
-30L)), vnam = "subject")
```
\emini
- Observed factor levels: \"1\", \"10\", \"11\", \"12\", \"13\", \"14\", \"15\", \"16\", \"17\", \"18\", \"19\", \"2\", \"20\", \"21\", \"22\", \"23\", \"24\", \"25\", \"26\", \"27\", \"28\", \"29\", \"3\", \"30\", \"4\", \"5\", \"6\", \"7\", \"8\", \"9\".
\fullline
## activity
*activity*
\bminione
-------------------------------------
Feature Result
------------------------- -----------
Variable type factor
Number of missing obs. 0 (0 %)
Number of unique values 6
Mode "walking"
Reference category walking
-------------------------------------
\emini
\bminitwo
```{r 'Var-2-activity', echo=FALSE, fig.width=4, fig.height=3, message=FALSE, warning=FALSE}
ggAggBarplot(data = structure(list(x = structure(1:6, .Label = c("walking",
"walking_upstairs", "walking_downstairs", "sitting", "standing",
"laying"), class = "factor"), y = c(30L, 30L, 30L, 30L, 30L,
30L)), class = "data.frame", row.names = c(NA, -6L)), vnam = "activity")
```
\emini
- Observed factor levels: \"laying\", \"sitting\", \"standing\", \"walking\", \"walking_downstairs\", \"walking_upstairs\".
\fullline
## t\_body\_acc\_mean\_x
*Time domain body-component accelerometer mean (x)*
\bminione
--------------------------------------
Feature Result
------------------------- ------------
Variable type numeric
Number of missing obs. 0 (0 %)
Number of unique values 180
Median 0.28
1st and 3rd quartiles 0.27; 0.28
Min. and max. 0.22; 0.3
--------------------------------------
\emini
\bminitwo
```{r 'Var-3-t-body-acc-mean-x', echo=FALSE, fig.width=4, fig.height=3, message=FALSE, warning=FALSE}
ggAggHist(data = structure(list(xmin = c(0.22, 0.23, 0.24, 0.25,
0.26, 0.27, 0.28, 0.29, 0.3), xmax = c(0.23, 0.24, 0.25, 0.26,
0.27, 0.28, 0.29, 0.3, 0.31), ymin = c(0, 0, 0, 0, 0, 0, 0, 0,
0), ymax = c(1L, 2L, 7L, 11L, 21L, 93L, 30L, 14L, 1L)), class = "data.frame", row.names = c(NA,
-9L)), vnam = "t_body_acc_mean_x")
```
\emini
\fullline
## t\_body\_acc\_mean\_y
*Time domain body-component accelerometer mean (y)*
\bminione
----------------------------------------
Feature Result
------------------------- --------------
Variable type numeric
Number of missing obs. 0 (0 %)
Number of unique values 180
Median -0.02
1st and 3rd quartiles -0.02; -0.01
Min. and max. -0.04; 0
----------------------------------------
\emini
\bminitwo
```{r 'Var-4-t-body-acc-mean-y', echo=FALSE, fig.width=4, fig.height=3, message=FALSE, warning=FALSE}
ggAggHist(data = structure(list(xmin = c(-0.045, -0.04, -0.035,
-0.03, -0.025, -0.02, -0.015, -0.01, -0.005), xmax = c(-0.04,
-0.035, -0.03, -0.025, -0.02, -0.015, -0.01, -0.005, 0), ymin = c(0,
0, 0, 0, 0, 0, 0, 0, 0), ymax = c(1L, 0L, 6L, 15L, 25L, 87L,
30L, 14L, 2L)), class = "data.frame", row.names = c(NA, -9L)),
vnam = "t_body_acc_mean_y")
```
\emini
\fullline
## t\_body\_acc\_mean\_z
*Time domain body-component accelerometer mean (z)*
\bminione
----------------------------------------
Feature Result
------------------------- --------------
Variable type numeric
Number of missing obs. 0 (0 %)
Number of unique values 180
Median -0.11
1st and 3rd quartiles -0.11; -0.1
Min. and max. -0.15; -0.08
----------------------------------------
\emini
\bminitwo
```{r 'Var-5-t-body-acc-mean-z', echo=FALSE, fig.width=4, fig.height=3, message=FALSE, warning=FALSE}
ggAggHist(data = structure(list(xmin = c(-0.16, -0.15, -0.14,
-0.13, -0.12, -0.11, -0.1, -0.09, -0.08), xmax = c(-0.15, -0.14,
-0.13, -0.12, -0.11, -0.1, -0.09, -0.08, -0.07), ymin = c(0,
0, 0, 0, 0, 0, 0, 0, 0), ymax = c(2L, 1L, 2L, 15L, 48L, 92L,
16L, 3L, 1L)), class = "data.frame", row.names = c(NA, -9L)),
vnam = "t_body_acc_mean_z")
```
\emini
\fullline
## t\_body\_acc\_std\_x
*Time domain body-component accelerometer std (x)*
\bminione
---------------------------------------
Feature Result
------------------------- -------------
Variable type numeric
Number of missing obs. 0 (0 %)
Number of unique values 180
Median -0.75
1st and 3rd quartiles -0.98; -0.2
Min. and max. -1; 0.63
---------------------------------------
\emini
\bminitwo
```{r 'Var-6-t-body-acc-std-x', echo=FALSE, fig.width=4, fig.height=3, message=FALSE, warning=FALSE}
ggAggHist(data = structure(list(xmin = c(-1, -0.8, -0.6, -0.4,
-0.2, 0, 0.2, 0.4, 0.6), xmax = c(-0.8, -0.6, -0.4, -0.2, 0,
0.2, 0.4, 0.6, 0.8), ymin = c(0, 0, 0, 0, 0, 0, 0, 0, 0), ymax = c(90L,
0L, 8L, 37L, 20L, 16L, 7L, 1L, 1L)), class = "data.frame", row.names = c(NA,
-9L)), vnam = "t_body_acc_std_x")
```
\emini
\fullline
## t\_body\_acc\_std\_y
*Time domain body-component accelerometer std (y)*
\bminione
----------------------------------------
Feature Result
------------------------- --------------
Variable type numeric
Number of missing obs. 0 (0 %)
Number of unique values 180
Median -0.51
1st and 3rd quartiles -0.94; -0.03
Min. and max. -0.99; 0.62
----------------------------------------
\emini
\bminitwo
```{r 'Var-7-t-body-acc-std-y', echo=FALSE, fig.width=4, fig.height=3, message=FALSE, warning=FALSE}
ggAggHist(data = structure(list(xmin = c(-1, -0.8, -0.6, -0.4,
-0.2, 0, 0.2, 0.4, 0.6), xmax = c(-0.8, -0.6, -0.4, -0.2, 0,
0.2, 0.4, 0.6, 0.8), ymin = c(0, 0, 0, 0, 0, 0, 0, 0, 0), ymax = c(89L,
1L, 0L, 10L, 43L, 24L, 10L, 2L, 1L)), class = "data.frame", row.names = c(NA,
-9L)), vnam = "t_body_acc_std_y")
```
\emini
\fullline
## t\_body\_acc\_std\_z
*Time domain body-component accelerometer std (z)*
\bminione
----------------------------------------
Feature Result
------------------------- --------------
Variable type numeric
Number of missing obs. 0 (0 %)
Number of unique values 180
Median -0.65
1st and 3rd quartiles -0.95; -0.23
Min. and max. -0.99; 0.61
----------------------------------------
\emini
\bminitwo
```{r 'Var-8-t-body-acc-std-z', echo=FALSE, fig.width=4, fig.height=3, message=FALSE, warning=FALSE}
ggAggHist(data = structure(list(xmin = c(-1, -0.8, -0.6, -0.4,
-0.2, 0, 0.2, 0.4, 0.6), xmax = c(-0.8, -0.6, -0.4, -0.2, 0,
0.2, 0.4, 0.6, 0.8), ymin = c(0, 0, 0, 0, 0, 0, 0, 0, 0), ymax = c(89L,
1L, 15L, 42L, 20L, 10L, 1L, 1L, 1L)), class = "data.frame", row.names = c(NA,
-9L)), vnam = "t_body_acc_std_z")
```
\emini
\fullline
## t\_gravity\_acc\_mean\_x
*Time domain gravity-component accelerometer mean (x)*
\bminione
---------------------------------------
Feature Result
------------------------- -------------
Variable type numeric
Number of missing obs. 0 (0 %)
Number of unique values 180
Median 0.92
1st and 3rd quartiles 0.84; 0.94
Min. and max. -0.68; 0.97
---------------------------------------
\emini
\bminitwo
```{r 'Var-9-t-gravity-acc-mean-x', echo=FALSE, fig.width=4, fig.height=3, message=FALSE, warning=FALSE}
ggAggHist(data = structure(list(xmin = c(-0.8, -0.6, -0.4, -0.2,
0, 0.2, 0.4, 0.6, 0.8), xmax = c(-0.6, -0.4, -0.2, 0, 0.2, 0.4,
0.6, 0.8, 1), ymin = c(0, 0, 0, 0, 0, 0, 0, 0, 0), ymax = c(2L,
13L, 9L, 6L, 0L, 0L, 1L, 6L, 143L)), class = "data.frame", row.names = c(NA,
-9L)), vnam = "t_gravity_acc_mean_x")
```
\emini
\fullline
## t\_gravity\_acc\_mean\_y
*Time domain gravity-component accelerometer mean (y)*
\bminione
---------------------------------------
Feature Result
------------------------- -------------
Variable type numeric
Number of missing obs. 0 (0 %)
Number of unique values 180
Median -0.13
1st and 3rd quartiles -0.23; 0.09
Min. and max. -0.48; 0.96
---------------------------------------
\emini
\bminitwo
```{r 'Var-10-t-gravity-acc-mean-y', echo=FALSE, fig.width=4, fig.height=3, message=FALSE, warning=FALSE}
ggAggHist(data = structure(list(xmin = c(-0.6, -0.4, -0.2, 0,
0.2, 0.4, 0.6, 0.8), xmax = c(-0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8,
1), ymin = c(0, 0, 0, 0, 0, 0, 0, 0), ymax = c(3L, 66L, 61L,
14L, 11L, 5L, 10L, 10L)), class = "data.frame", row.names = c(NA,
-8L)), vnam = "t_gravity_acc_mean_y")
```
\emini
\fullline
## t\_gravity\_acc\_mean\_z
*Time domain gravity-component accelerometer mean (z)*
\bminione
---------------------------------------
Feature Result
------------------------- -------------
Variable type numeric
Number of missing obs. 0 (0 %)
Number of unique values 180
Median 0.02
1st and 3rd quartiles -0.12; 0.15
Min. and max. -0.5; 0.96
---------------------------------------
\emini
\bminitwo
```{r 'Var-11-t-gravity-acc-mean-z', echo=FALSE, fig.width=4, fig.height=3, message=FALSE, warning=FALSE}
ggAggHist(data = structure(list(xmin = c(-0.6, -0.4, -0.2, 0,
0.2, 0.4, 0.6, 0.8), xmax = c(-0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8,
1), ymin = c(0, 0, 0, 0, 0, 0, 0, 0), ymax = c(3L, 18L, 60L,
63L, 13L, 7L, 10L, 6L)), class = "data.frame", row.names = c(NA,
-8L)), vnam = "t_gravity_acc_mean_z")
```
\emini
\fullline
## t\_gravity\_acc\_std\_x
*Time domain gravity-component accelerometer std (x)*
\bminione
----------------------------------------
Feature Result
------------------------- --------------
Variable type numeric
Number of missing obs. 0 (0 %)
Number of unique values 180
Median -0.97
1st and 3rd quartiles -0.98; -0.95
Min. and max. -1; -0.83
----------------------------------------
\emini
\bminitwo
```{r 'Var-12-t-gravity-acc-std-x', echo=FALSE, fig.width=4, fig.height=3, message=FALSE, warning=FALSE}
ggAggHist(data = structure(list(xmin = c(-1, -0.98, -0.96, -0.94,
-0.92, -0.9, -0.88, -0.86, -0.84), xmax = c(-0.98, -0.96, -0.94,
-0.92, -0.9, -0.88, -0.86, -0.84, -0.82), ymin = c(0, 0, 0, 0,
0, 0, 0, 0, 0), ymax = c(55L, 52L, 52L, 12L, 4L, 3L, 1L, 0L,
1L)), class = "data.frame", row.names = c(NA, -9L)), vnam = "t_gravity_acc_std_x")
```
\emini
\fullline
## t\_gravity\_acc\_std\_y
*Time domain gravity-component accelerometer std (y)*
\bminione
----------------------------------------
Feature Result
------------------------- --------------
Variable type numeric
Number of missing obs. 0 (0 %)
Number of unique values 180
Median -0.96
1st and 3rd quartiles -0.97; -0.94
Min. and max. -0.99; -0.64
----------------------------------------