# Working With Data
Examples to accompany 
[Stata for Researchers](https://www.ssc.wisc.edu/sscc/pubs/sfr-data.htm)

## `generate` / `replace`
Let's start with

```
help generate
```

and our basic form is

`generate` *newvar* `=` *expression*

Where *expressions* can take a huge variety of forms: a
mix of *variable names*, *constants*, *operators* and *functions*.

Using the `auto` data set, calculate an inflation-adjusted price
for each car type.  See 
[BLS Inflation Calculator](https://www.bls.gov/data/inflation_calculator.htm).

```{stata}
sysuse auto
generate price2017 = 3.94*price
* check, this is a linear transformation
scatter price2017 price
```

### Conditional Values
Suppose we wanted to calculate the current price in Euros, but just
for foreign cars.

```s
generate europrice = .81*price2017 if foreign==1
* check means
summarize *price* 
```

### Replacing Values
Suppose you wanted to recode `weight` in Scientific Units. You
might try

```s
generate weight = weight/2.2
```

But that gives you an error.  In general, if you want to write
over existing data (or files), you need to say `replace`.  In
this case, `replace` is a command name (in other cases, it
is an option keyword).

```s
replace weight = weight/2.2
* check, correlation with price is the same
* oops! can't check because we overwrote our data!
corr weight price2017
```

### Missing Values
Suppose you want to reverse the repair scale:  instead of 1 being
a poor repair record, 5 should be the worst value.  You could do

```s
generate repairs = 6 - rep78
* check, crosstab
tabulate rep78 repairs, missing
```

Notice that a missing input value becomes a missing output value.

## `recode`

## `egen`

## Details
### Mathematical Expressions
### Logical Expressions
### Probability and Random Numbers
### Dates and Times
### String Expression
#### String Conversions(`real()`)

### Conversions
#### `encode` / `decode`
#### `destring` / `tostring`