Dataset Class

I want to make my life easier. Less copying code snippets from example scripts.

Below is an example workflow that would make QC'ing solar radiation data even easier!

```python
ds = solarpy.DataSet.from_t16("filename.csv", freq='1min', map_variables=True)
ds = solarpy.DataSet.from_bsrn_ftp(station="cab", start=, end, username, password)
ds = solarpy.DataSet.from_bsrn_file(filename)

ds.calculate_solarposition(method="nrel-numpy")

ds.calculate_clearsky(method='cams', email='redacted@gmail.com')

ds.calculate_horizon()

ds.calculate_quality_flags()

# clean slicing that returns a new SolarDataset rather than a raw DataFrame slice, preserving meta
ds.select(start, end)
ds.resample(freq='h').mean()

fig, ax = ds.plot_shading_heatmap(parameter='ghi')
fig, ax = ds.plot_bsrn_limit(component="ghi")
fig, axes = ds.multiplot()
```

Solar position and other derived variables could also be lazily computed, i.e., only computed when an action is executed that requires it.