pandas.Series.diff#

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

First discrete difference of element.

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

Parameters:

periodsint, default 1

Periods to shift for calculating difference, accepts negativevalues.

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 usesoperator.xor() rather thanoperator.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    NaN1    0.02    1.03    1.04    2.05    3.0dtype: float64

Difference with 3rd previous row

>>>s.diff(periods=3)0    NaN1    NaN2    NaN3    2.04    4.05    6.0dtype: float64

Difference with following row

>>>s.diff(periods=-1)0    0.01   -1.02   -1.03   -2.04   -3.05    NaNdtype: float64

Overflow in input dtype

>>>s=pd.Series([1,0],dtype=np.uint8)>>>s.diff()0      NaN1    255.0dtype: float64