pandas.Series.diff

Series.diff(periods=1)

First discrete difference of Series elements.

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

Parameters:

periodsint, default 1

Periods to shift for calculating difference, accepts negative values.

Returns:

Series

First differences of the Series.

See also

Series.pct_change

Percent change over given number of periods.

Series.shift

Shift index by desired number of periods with an optional time freq.

DataFrame.diff

First discrete difference of object.

Notes

Equivalent to self - self.shift(periods), except that boolean dtypes use operator.xor() rather than operator.sub(); the result dtype follows from that operation.

In particular, because the leading periods positions are filled with a missing value, NumPy integer dtypes are cast to floating and NumPy bool to object.

Examples

Difference with previous row

>>> s = pd.Series([1, 1, 2, 3, 5, 8])
>>> s.diff()
0    NaN
1    0.0
2    1.0
3    1.0
4    2.0
5    3.0
dtype: float64

Difference with 3rd previous row

>>> s.diff(periods=3)
0    NaN
1    NaN
2    NaN
3    2.0
4    4.0
5    6.0
dtype: float64

Difference with following row

>>> s.diff(periods=-1)
0    0.0
1   -1.0
2   -1.0
3   -2.0
4   -3.0
5    NaN
dtype: float64

Overflow in input dtype

>>> s = pd.Series([1, 0], dtype=np.uint8)
>>> s.diff()
0      NaN
1    255.0
dtype: float64