Pandas DataFrame | diff method
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Pandas DataFrame.diff(~) method returns a new DataFrame where each value represents the difference between the value and the value of the previous row or column.
Parameters
1. periodslink | int | optional
If periods=3, then instead of taking the difference of the previous row/column, the difference is computed using the 3rd row/column before. Both positive and negative integers are allowed. By default, periods=1.
2. axis | int or string | optional
Whether or not the take the difference of the previous row or column:
Axis | Description |
|---|---|
| Take the difference between the previous row value in the same column. |
| Take the difference between the previous column value in the same row. |
By default, axis=0.
Return Value
A new DataFrame.
Examples
Basic usage
Consider the following DataFrame:
df = pd.DataFrame({"A":[3,4,6],"B":[1,4,9]})df
A B0 3 11 4 42 6 9
Computing the difference between each value and its previous value in the same column:
df.diff()
A B0 NaN NaN1 1.0 3.02 2.0 5.0
Notice how the first row is NaN - this is because there is no previous row with which to compute the difference.
Specifying periods
To compute the difference between each value and the value that is 2 rows prior in the same column:
df.diff(periods=2)
A B0 NaN NaN1 NaN NaN2 3.0 8.0
periods also accepts a negative integer:
df.diff(periods=-1)
A B0 -1.0 -3.01 -2.0 -5.02 NaN NaN
Here, instead of taking the difference between the previous value, we take the difference between the next value.
