Supporting Statistical Analysis for Research

## 4.4 Dropping unneeded variables

These exercises use the `PSID.csv` data set that was imported in the prior section.

1. Import the `PSID.csv` data set.

``library(tidyverse)``
``````psid_path <- file.path("..", "datasets", "PSID.csv")
psid_in <- read_csv(psid_path, col_types = cols())``````
``Warning: Missing column names filled in: 'X1' [1]``
``````psid_in <-
rename(
psid_in,
obs_num = X1,
intvw_num = intnum,
person_id = persnum,
marital_status = married
)

psid <- psid_in
glimpse(psid)``````
``````Observations: 4,856
Variables: 9
\$ obs_num        <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, ...
\$ intvw_num      <dbl> 4, 4, 4, 4, 5, 6, 6, 7, 7, 7, 10, 10, 10, 11, 1...
\$ person_id      <dbl> 4, 6, 7, 173, 2, 4, 172, 4, 170, 171, 3, 171, 1...
\$ age            <dbl> 39, 35, 33, 39, 47, 44, 38, 38, 39, 37, 48, 47,...
\$ educatn        <dbl> 12, 12, 12, 10, 9, 12, 16, 9, 12, 11, 13, 12, 1...
\$ earnings       <dbl> 77250, 12000, 8000, 15000, 6500, 6500, 7000, 50...
\$ hours          <dbl> 2940, 2040, 693, 1904, 1683, 2024, 1144, 2080, ...
\$ kids           <dbl> 2, 2, 1, 2, 5, 2, 3, 4, 3, 5, 98, 3, 0, 0, 2, 0...
\$ marital_status <chr> "married", "divorced", "married", "married", "m...``````
2. Drop the first variable in the data frame. You may have renamed it after it was loaded.

``psid <- select(psid, -obs_num)``
3. Make the age variable the first variable in the data frame.

``psid <- select(psid, age, everything())``