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Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Attaching package: 'reshape2'
The following object is masked from 'package:tidyr':
smiths
Loading required package: ggplot2
Attaching package: 'GGally'
The following object is masked from 'package:dplyr':
nasa
Attaching package: 'plotly'
The following object is masked from 'package:ggplot2':
last_plot
The following object is masked from 'package:stats':
filter
The following object is masked from 'package:graphics':
layout
Parsed with column specification:
cols(
`Client number` = col_double(),
`Client Full Name` = col_character(),
Employee = col_character(),
ACO_Num = col_character(),
ACO = col_double(),
Gender = col_character(),
Race = col_character(),
Ethnicity = col_character(),
`Marital Status` = col_character(),
Age = col_double(),
`Educational Level` = col_character(),
`Employment Status` = col_character()
)
Parsed with column specification:
cols(
`Client number` = col_double(),
`Client Full Name` = col_character(),
Employee = col_character(),
ACO_Num = col_character(),
ACO = col_double(),
Gender = col_character(),
Race = col_character(),
Ethnicity = col_character(),
`Marital Status` = col_character(),
Age = col_double(),
`Educational Level` = col_character(),
`Employment Status` = col_character()
)
Parsed with column specification:
cols(
`Employee name` = col_character(),
ACO_NUM = col_double(),
ACO = col_double(),
`Client number` = col_double(),
`Client full name` = col_character(),
`Activity date` = col_character(),
Problem = col_character(),
PB_NUM = col_character(),
Category = col_character(),
CAT_NUM = col_character(),
Target = col_character(),
TAR_NUM = col_character(),
Intervention = col_character()
)
Parsed with column specification:
cols(
`Employee name` = col_character(),
ACO_NUM = col_double(),
ACO = col_double(),
`Client number` = col_double(),
`Client full name` = col_character(),
`Activity date` = col_character(),
Problem = col_character(),
PB_NUM = col_character(),
Category = col_character(),
CAT_NUM = col_character(),
Target = col_character(),
TAR_NUM = col_character(),
Intervention = col_character()
)
Parsed with column specification:
cols(
`Client number` = col_character(),
`Client full name` = col_character(),
`Employee name` = col_character(),
ACO_NUM = col_character(),
ACO = col_double(),
`Activity date` = col_character(),
Problem = col_character(),
PB_NUM = col_character(),
K = col_double(),
B = col_double(),
S = col_double()
)
Parsed with column specification:
cols(
`Client number` = col_character(),
`Client full name` = col_character(),
`Employee name` = col_character(),
ACO_NUM = col_character(),
ACO = col_double(),
`Activity date` = col_character(),
Problem = col_character(),
PB_NUM = col_character(),
K = col_double(),
B = col_double(),
S = col_double()
)
Parsed with column specification:
cols(
.default = col_double(),
`Client Full Name` = col_character(),
`Employee Name` = col_character(),
ACO_NUM = col_character()
)
See spec(...) for full column specifications.
Parsed with column specification:
cols(
.default = col_double(),
`Client Full Name` = col_character(),
`Employee Name` = col_character(),
ACO_NUM = col_character()
)
See spec(...) for full column specifications.
| Group | mean_K | mean_S | mean_B |
|---|---|---|---|
| 1 | 2.610526 | 2.692105 | 2.642105 |
| 2 | 2.701923 | 2.663461 | 3.076923 |
| 3 | 2.403061 | 2.443878 | 2.326531 |
| 4A | 2.423077 | 2.961539 | 2.980769 |
| 4B | 2.931034 | 3.000000 | 2.827586 |
| 5 | 2.941489 | 3.595745 | 3.319149 |
| Group | Avg_Age |
|---|---|
| 1 | 41.85000 |
| 2 | 47.22917 |
| 3 | 49.04082 |
| 4A | 39.86364 |
| 4B | 39.10000 |
| 5 | 52.71667 |