pandas.core.groupby.SeriesGroupBy.diff#

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

First discrete difference of element.

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

Parameters:

periodsint, default 1: Periods to shift for calculating difference, accepts negative values.

Returns:

Series or DataFrame: First differences.

See also

Series.groupby: Apply a function groupby to a Series.
DataFrame.groupby: Apply a function groupby to each row or column of a DataFrame.

Examples

For SeriesGroupBy:

>>> lst = ["a", "a", "a", "b", "b", "b"]
>>> ser = pd.Series([7, 2, 8, 4, 3, 3], index=lst)
>>> ser
a 7
a 2
a 8
b 4
b 3
b 3
dtype: int64
>>> ser.groupby(level=0).diff()
a NaN
a -5.0
a 6.0
b NaN
b -1.0
b 0.0
dtype: float64

For DataFrameGroupBy:

>>> data = {"a": [1, 3, 5, 7, 7, 8, 3], "b": [1, 4, 8, 4, 4, 2, 1]}
>>> df = pd.DataFrame(
...  data, index=["dog", "dog", "dog", "mouse", "mouse", "mouse", "mouse"]
... )
>>> df
 a b
 dog 1 1
 dog 3 4
 dog 5 8
mouse 7 4
mouse 7 4
mouse 8 2
mouse 3 1
>>> df.groupby(level=0).diff()
 a b
 dog NaN NaN
 dog 2.0 3.0
 dog 2.0 4.0
mouse NaN NaN
mouse 0.0 0.0
mouse 1.0 -2.0
mouse -5.0 -1.0

pandas.core.groupby.SeriesGroupBy.diff#

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