def diff(self, periods=<NUM_LIT:1>, axis=<NUM_LIT:0>):
bm_axis = self._get_block_manager_axis(axis)<EOL>new_data = self._data.diff(n=periods, axis=bm_axis)<EOL>return self._constructor(new_data)<EOL>
First discrete difference of element.

Calculates the difference of a DataFrame element compared with another
element in the DataFrame (default is the element in the same column
of the previous row).

Parameters
----------
periods : int, default 1
    Periods to shift for calculating difference, accepts negative
    values.
axis : {0 or 'index', 1 or 'columns'}, default 0
    Take difference over rows (0) or columns (1).

    .. versionadded:: 0.16.1.

Returns
-------
DataFrame

See Also
--------
Series.diff: First discrete difference for a Series.
DataFrame.pct_change: Percent change over given number of periods.
DataFrame.shift: Shift index by desired number of periods with an
    optional time freq.

Examples
--------
Difference with previous row

>>> df = pd.DataFrame({'a': [1, 2, 3, 4, 5, 6],
...                    'b': [1, 1, 2, 3, 5, 8],
...                    'c': [1, 4, 9, 16, 25, 36]})
>>> df
   a  b   c
0  1  1   1
1  2  1   4
2  3  2   9
3  4  3  16
4  5  5  25
5  6  8  36

>>> df.diff()
     a    b     c
0  NaN  NaN   NaN
1  1.0  0.0   3.0
2  1.0  1.0   5.0
3  1.0  1.0   7.0
4  1.0  2.0   9.0
5  1.0  3.0  11.0

Difference with previous column

>>> df.diff(axis=1)
    a    b     c
0 NaN  0.0   0.0
1 NaN -1.0   3.0
2 NaN -1.0   7.0
3 NaN -1.0  13.0
4 NaN  0.0  20.0
5 NaN  2.0  28.0

Difference with 3rd previous row

>>> df.diff(periods=3)
     a    b     c
0  NaN  NaN   NaN
1  NaN  NaN   NaN
2  NaN  NaN   NaN
3  3.0  2.0  15.0
4  3.0  4.0  21.0
5  3.0  6.0  27.0

Difference with following row

>>> df.diff(periods=-1)
     a    b     c
0 -1.0  0.0  -3.0
1 -1.0 -1.0  -5.0
2 -1.0 -1.0  -7.0
3 -1.0 -2.0  -9.0
4 -1.0 -3.0 -11.0
5  NaN  NaN   NaN