Problem with plotting frequencies "L" and "S"
IO am opening new issue as i solved what is wrong with https://github.com/pydata/pandas/issues/7760 .
So, i have two sets of data one with frequency 1 second:
http://pastebin.com/HenYJxdV
And other with frequency 0.1 second (100 miliseconds):
http://pastebin.com/HenYJxdV

I wanted to plot them on same axe so i did:

```
seriesA=dfA["more"]
seriesB=dfB["less"]

plt.figure()
seriesA.plot()
seriesB.plot()
```

which yielded error seen in linked issue.
But having simmilar data, from the same source, of the same type it often was plotted corectly.
What caused this, and what was the difference since data was from the same source ?
Two things:
1.First: 
line 1515 in tools\plotting.py

```
return Period(x[0], freq).to_timestamp(tz=x.tz) == x[0]
```

This line caused different behaviour of plotting function for different set of data, but only for datas with milisecond frequency (seriesB.plot())
How different ? 
When the x[0] is

```
 Timestamp: 2001-01-01 09:12:13.200000
```

then Period(x[0], freq).to_timestamp(tz=x.tz) is:

```
Timestamp: 2001-01-01 09:12:13.200000002
```

which causes the comparison to return False value, but having x[0]:

```
 Timestamp: 2001-01-01 09:03:11.500000
```

we have expression Period(x[0], freq).to_timestamp(tz=x.tz) being set to:

```
 Timestamp: 2001-01-01 09:03:11.500000
```

Which returns True.
Suprisingly it plotted correctly in the first case, when that line returns false (ex. Timestamp: 2001-01-01 09:12:13.200000002)
Because call stack goes way back to line 1539 same file:

```
if self._is_ts_plot():
```

and caused self._is_ts_plot() to be False, which cause pandas not to try detect frequency and try to convert it but simply plot it.

2.Second:
line 92 of tseries\plotting.py

```
def _maybe_resample(series, ax, freq, plotf, kwargs):
    ax_freq = _get_ax_freq(ax)
    if ax_freq is not None and freq != ax_freq:
        if frequencies.is_superperiod(freq, ax_freq):  # upsample input
            series = series.copy()
            series.index = series.index.asfreq(ax_freq, how='s')
            freq = ax_freq
        elif _is_sup(freq, ax_freq):  # one is weekly
            how = kwargs.pop('how', 'last')
            series = series.resample('D', how=how).dropna()
            series = series.resample(ax_freq, how=how).dropna()
            freq = ax_freq
        elif frequencies.is_subperiod(freq, ax_freq) or _is_sub(freq, ax_freq):
            _upsample_others(ax, freq, plotf, kwargs)
            ax_freq = freq
        else:  # pragma: no cover
            raise ValueError('Incompatible frequency conversion')
    return freq, ax_freq, series
```

this function for the set of data which does not plot (the one with  Timestamp: 2001-01-01 09:03:11.500000) goes through all the conditions and goes to the last "else"
with 

```
ax_freq = "S"
freq = "L"
```

None of the functions handles the frequency "L". 
I presume that it should be handled in

```
frequencies.is_subperiod(freq, ax_freq)
```

but as you can see here https://github.com/pydata/pandas/blob/790d6464130fe9448739e48678f466d5452992ca/pandas/tseries/frequencies.py#L904
it is not done.

Anyway, as i presume fixing problem with sampling may be tricky, i'd like to suggest an option (if it does not exist) which could allow pandas not to look for periods, or treat it as timeseries, but simply plot it.
Something like 

```
seriesB.plot(please_oh_please_make_this_thing_plot=True)
```

which would cause to not treat it as timeseries and forced 
`self._is_ts_plot():` to be false.
