ENH: .to_latex(longtable=True) latex caption and label support
- [ ] closes #xxxx
- [ ] tests added / passed
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry

When creating a latex table with `DataFrame.to_latex(longtable=False)` the output is written inside a latex `tabular` environment and stored in some file like `pandas_tabular.tex`; the user can conveniently typeset the table in a main `report.tex` file complete with caption and label as follows:

```tex
\begin{table}
\caption{the caption}
\label{the label}
\input{pandas_tabular.tex}
\end{table}
```

This is good because the `pandas_tabular.tex` file can be re-created and the main `report.tex` simply needs to be recompiled to get the updated output.

The problem when creating a latex [longtable](https://ctan.org/pkg/longtable) with `DataFrame.to_latex(longtable=True)` is the caption and label need to go inside the latex `longtable` environment which is stored in a some file like `pandas_longtable.tex`.  The latex `longtable` environment does not go inside a `table` environment like the `tabular` environment does; this means that setting the caption and label requires the user to edit the `pandas_longtable.tex` file after its creation.  This does not support an automated workflow like we have with the `tabular` environment.

**This PR adds caption and label support to `DataFrame.to_latex(longtable=True)` with the arguments `lt_caption` and `lt_label`.  Example usage is described below.**  

The following python code creates some data in a `DataFrame` and writes it to disk in `tabular` and `longtable` latex environments:


```python
import numpy as np
import pandas as pd


# create some example data with more rows than would fit on a single page
df = pd.DataFrame(np.random.randn(60,3))

# write the first 5 rows to regular table in a latex tabular environment
df.head().to_latex(
    'pandas_tabular.tex',
)

# write the whole table in the latex longtable environment c/w caption and label
df.to_latex(
    'pandas_longtable.tex',
    longtable=True,
    lt_caption='table in \\texttt{longtable} environment',
    lt_label='tab:longtable',
)
```

The following latex code is contained in a main `report.tex` and is used to typset both tables:

```tex
\documentclass{article}

\usepackage{longtable}
\usepackage{booktabs}

\begin{document}

% typeset the table in the tabular environment
Table \ref{tab:tabular}	is a \texttt{tabular} and has 5 rows:
\begin{table}[h]	
\centering	
\caption{table in \texttt{tabular} environment}
\label{tab:tabular}
\input{pandas_tabular.tex}	
\end{table}

% typeset the table in the longtable environment
Table \ref{tab:longtable} is a \texttt{longtable} and has 60 rows:
\input{pandas_longtable.tex}
\end{document}
```

Using `DataFrame.to_latex(longtable=True)` with the new arguments `lt_caption` and `lt_label` means we don't have to edit `pandas_longtable.tex` after its creation to get the caption and label working.  This functionality also works with `Series.to_latex(longtable=True)`.

PDF output is shown below:

![image](https://user-images.githubusercontent.com/36767735/52894669-0cf2a100-316b-11e9-8003-54298d8982cb.png)

