Pandas DataFrame diff() Method
pandas diff() is used to find the difference of a DataFrame element compared with another element in the DataFrame (default is element in the same column of the previous row).
Syntax: DataFrame.diff(periods=1, axis=0)
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).
Returns: DataFrame or Series of the same size and shape as the input.
# Example: diff
import pandas as pd# Create a dataframe
df = pd.DataFrame({'A': [1, 2, 3, 4, 5, 6],
'B': [1, 1, 2, 3, 5, 8],
'C': [1, 4, 9, 16, 25, 36]})
print(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
Calculate the difference between the current and a shifted row.
The default is to shift by one row
step by step:
1. current row: 2, 1, 4
2. shifted row: 1, 1, 1
3. difference: 1, 0, 3# Calculate the difference between the current and a shifted rowprint(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
Calculate the difference between the current and a shifted row of period 2.
period 2 means the difference between the current row and the row 2 rows before it.
step by step:
1. current row: 6, 8, 36
2. shifted row: 4, 3, 16
3. difference: 2, 5, 20# Calculate the difference between the current and a shifted row of period 2print(df.diff(periods=2))>>>
A B C
0 NaN NaN NaN
1 NaN NaN NaN
2 2.0 1.0 8.0
3 2.0 2.0 12.0
4 2.0 3.0 16.0
5 2.0 5.0 20.0
Calculate the difference between the current and a shifted row of axis 1.
axis=1 means column wise operation and axis=0 means row wise operation.
step by step for axis 1 and period 2
1. current column: 1, 4, 9, 16, 25, 36
2. shifted column: 1, 2, 3, 4, 5, 6
3. difference: 0, 2, 6, 12, 20, 30# Calculate the difference between the current and a shifted row of axis 1 and period 2print(df.diff(periods=2, axis=1))>>>
A B C
0 NaN NaN 0
1 NaN NaN 2
2 NaN NaN 6
3 NaN NaN 12
4 NaN NaN 20
5 NaN NaN 30
