pandas.core.groupby.DataFrameGroupBy.diff¶
-
DataFrameGroupBy.
diff
¶ 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).
New in version 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