DOC: Improve the docstring of pandas.DataFrame.append()
Checklist for the pandas documentation sprint (ignore this if you are doing
an unrelated PR):

- [x] PR title is "DOC: update the <your-function-or-method> docstring"
- [x] The validation script passes: `scripts/validate_docstrings.py <your-function-or-method>`
- [x] The PEP8 style check passes: `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [x] The html version looks good: `python doc/make.py --single <your-function-or-method>`
- [x] It has been proofread on language by another sprint participant

Please include the output of the validation script below between the "```" ticks:

```
################################################################################
##################### Docstring (pandas.DataFrame.append)  #####################
################################################################################

Append rows of `other` to the end of `caller`, returning a new object.

Columns not in other are added as new columns.

Parameters
----------
other : DataFrame or Series/dict-like object, or list of these
    The data to append.
ignore_index : boolean, default False
    If True, do not use the index labels.
verify_integrity : boolean, default False
    If True, raise ValueError on creating index with duplicates.

Returns
-------
appended : DataFrame

Notes
-----
If a list of dict/series is passed and the keys are all contained in
the DataFrame's index, the order of the columns in the resulting
DataFrame will be unchanged.

Iteratively appending rows to a DataFrame can be more computationally
intensive than a single concatenate. A better solution is to append
those rows to a list and then concatenate the list with the original
DataFrame all at once.

See also
--------
pandas.concat : General function to concatenate DataFrame, Series
    or Panel objects

Examples
--------

>>> df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'))
>>> df
   A  B
0  1  2
1  3  4
>>> df2 = pd.DataFrame([[5, 6], [7, 8]], columns=list('AB'))
>>> df.append(df2)
   A  B
0  1  2
1  3  4
0  5  6
1  7  8

With `ignore_index` set to True:

>>> df.append(df2, ignore_index=True)
   A  B
0  1  2
1  3  4
2  5  6
3  7  8

The following, while not recommended methods for generating DataFrames,
show two ways to generate a DataFrame from multiple data sources.

Less efficient:

>>> df = pd.DataFrame(columns=['A'])
>>> for i in range(5):
...     df = df.append({'A': i}, ignore_index=True)
>>> df
   A
0  0
1  1
2  2
3  3
4  4

More efficient:

>>> pd.concat([pd.DataFrame([i], columns=['A']) for i in range(5)],
...           ignore_index=True)
   A
0  0
1  1
2  2
3  3
4  4

################################################################################
################################## Validation ##################################
################################################################################
```

If the validation script still gives errors, but you think there is a good reason
to deviate in this case (and there are certainly such cases), please state this
explicitly.


