ENH: add logfmt support
[logfmt](https://www.brandur.org/logfmt) is a structured log format similar to JSON lines, but much simpler. Each line has a format `column1=value1 column2=value2 ...`. Pandas already has support for JSON lines, which can be read with `pd.read_json(path, lines=True)`, but to read logfmt logs a conversion is needed.

I have been using [agrind](https://github.com/rcoh/angle-grinder) to convert logs to JSON lines, but it is an additional step that I would like to eliminate from my workflow. You can see an example at https://gitlab.com/nsnam/ns-3-dev/-/merge_requests/303

Besides, I would like to use logfmt as an output format for simple computational experiments (think C/Fortran without dependencies), because it is easier to maintain one line of code that outputs keys and values interleaved, in contrast to maintaining the code to output headers and code to output values separately. And logfmt becomes easier to read than CSV as the number of columns grows. Compare
```
node=1 throughput=63.0 delay=52.0 x=0.0 y=5.0
node=2 throughput=100.0 delay=35.0 x=5.0 y=5.0
```
to
```
node,throughput,delay,x,y
1,63.0,52.0,0.0,5.0
2,100.0,35.0,5.0,5.0
```

To read logfmt directly with pandas, I want a function `pd.read_logfmt()` that can be used in place of `pd.read_csv()` and `pd.read_json()` in described above cases.
