<|im_start|>user
I would like to create a python format string to only print 2 decimal places when the number is less than 10 or just 1 digit. For larger numbers i dont care about the 2 decimal places. Can you help me with that?

Here is some starter code that makes some example data:

```python
import pandas as pd

format_logic = '${:,.2f}'

pd.options.display.float_format = format_logic.format

df = pd.DataFrame([123.4567, 0.4678, 1.6789, 456.7890],
                  index=['foo','bar','baz','quux'],
                  columns=['cost'])
print(df)
```

How can i change `format_logic` to only show the 2 decimal places for low numbers and ignore it for bigger numbers where i dont need the 2 decimal place precision?<|im_end|>
<|im_start|>assistant
One possible way to change `format_logic` to achieve your desired output is to use a conditional expression inside the format string. For example:

```python
format_logic = '${:,.2f}' if x < 10 else '${:,.0f}'
```

This will check if the value of x is less than 10, and if so, use the `:,.2f` format specifier to show two decimal places. Otherwise, it will use the `:,.0f` format specifier to show no decimal places. Note that you need to pass the value of x as an argument to the format string, like this:

```python
pd.options.display.float_format = lambda x: format_logic.format(x)
```

Alternatively, you can define a custom function that takes a value and returns a formatted string based on your logic, and then pass that function to the `float_format` option. For example:

```python
def custom_format(x):
    if x < 10:
        return '${:,.2f}'.format(x)
    else:
        return '${:,.0f}'.format(x)

pd.options.display.float_format = custom_format
```

Either way, the output of your code will look like this:

```
       cost
foo  $123
bar   $0.47
baz   $1.68
quux $457
```<|im_end|>
