pandas.Series.diff#

Series.diff(periods=1)[source]#

First discrete difference of element.

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

For boolean dtypes, this uses operator.xor() rather than operator.sub(). The result is calculated according to current dtype in Series, however dtype of the result is always float64.

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