Pandas DataFrame cummin() Method
Example
Return the cumulative minimum value of each row:
import pandas as pd
data = [[10, 18, 11], [13, 15, 8], [9, 20, 3]]
df = pd.DataFrame(data)
print(df.cummin())
Try it Yourself »
Definition and Usage
The cummin() method returns a DataFrame with
the cumulative minimum values.
The cummin() method goes through the values
in the DataFrame, from the top, row by row, replacing the values with the
lowest value yet for each column, ending up with a DataFrame where the last row
contains only the lowest value from each column.
If the axis parameter is set to axes='columns',
the method goes through the values, column by column, and ends up with a
DataFrame where the last columns contains only the lowest value from each row.
Syntax
dataframe.cummin(axis, skipna, args, kwargs)
Parameters
The
axis
and skipna parameters are
keyword arguments.
| Parameter | Value | Description |
|---|---|---|
| axis | 0 |
Optional, default 0, specifies the axis to run the accumulation over. |
| skip_na | True |
Optional, default True. Set to False if the result should NOT skip NULL values |
| args | Optional. These arguments has no effect, but could be accepted by a NumPy function | |
| kwargs | Optional, keyword arguments. These arguments has no effect, but could be accepted by a NumPy function |
Return Value
A DataFrame object.
This function does NOT make changes to the original DataFrame object.
