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).
Periods to shift for calculating difference, accepts negative values.
Take difference over rows (0) or columns (1).
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.
Notes
For boolean dtypes, this uses operator.xor() rather than operator.sub().
operator.xor()
operator.sub()
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