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PUBLISHED ON: MARCH 15, 2021

# Pandas DataFrame cummin() Method

In this tutorial, we will learn the Python pandas `DataFrame.cummin()` method. It gives a cumulative minimum over a DataFrame or Series axis. It returns a DataFrame or Series of the same size containing the `cumulative minimum`.

The below shows the syntax of the Python pandas `DataFrame.cummin()` method.

### Syntax

``DataFrame.cummin(axis=None, skipna=True, *args, **kwargs)``

### Parameters:

axis: {0 or ‘index’, 1 or ‘columns’}, default 0. The index or the name of the axis. 0 is equivalent to None or ‘index’.

skipna: bool, default True. Exclude NA/null values. If an entire row/column is NA, the result will be NA.

*args, **kwargs: Additional keywords have no effect but might be accepted for compatibility with NumPy.

## Example 1: Finding the cumulative minimum of the DataFrame

The below example shows how to find the cumulative minimum of the DataFrame over the index axis using the `DataFrame.cummin()` method.

``````import pandas as pd
# Creating the dataframe
df = pd.DataFrame({"A":[1, 2, 8, 4], "B":[9, 10, 7, 8], "C":[9, 10, 11, 12],"D":[13, 16, 15, 16]})
print(df)
print("-----------Finding cumulative minimum-------")
print(df.cummin(axis = 0))``````

Once we run the program we will get the following output.

A B C D
0 1 9 9 13
1 2 10 10 16
2 8 7 11 15
3 4 8 12 16
-----------Finding cumulative minimum-------
A B C D
0 1 9 9 13
1 1 9 9 13
2 1 7 9 13
3 1 7 9 13

## Example 2: Finding the cumulative minimum of the DataFrame

The below example shows how to find the cumulative minimum of the DataFrame over the column axis using the `DataFrame.cummin()` method.

``````import pandas as pd
# Creating the dataframe
df = pd.DataFrame({"A":[1, 2, 8, 4], "B":[9, 10, 7, 8], "C":[9, 10, 11, 12],"D":[13, 16, 15, 16]})
print(df)
print("-----------Finding cumulative minimum-------")
print(df.cummin(axis = 1))``````

Once we run the program we will get the following output.

A B C D
0 1 9 9 13
1 2 10 10 16
2 8 7 11 15
3 4 8 12 16
-----------Finding cumulative minimum-------
A B C D
0 1 1 1 1
1 2 2 2 2
2 8 7 7 7
3 4 4 4 4

## Example 3: Finding the cumulative minimum of the DataFrame

The below example shows how to find the cumulative minimum of the DataFrame with null values over the index axis using the `DataFrame.cummin()` method.

``````import pandas as pd
# Creating the dataframe
df = pd.DataFrame({"A":[1, 2, 8, 4], "B":[9, None, 7, 8], "C":[9, 10, None, 12],"D":[None, 16, 15, 16]})
print(df)
print("-----------Finding cumulative minimum-------")
print(df.cummin(skipna=False))``````

Once we run the program we will get the following output.

A B C D
0 1 9.0 9.0 NaN
1 2 NaN 10.0 16.0
2 8 7.0 NaN 15.0
3 4 8.0 12.0 16.0
-----------Finding cumulative minimum-------
A B C D
0 1 9.0 9.0 NaN
1 1 NaN 9.0 NaN
2 1 NaN NaN NaN
3 1 NaN NaN NaN

### Conclusion

In this tutorial, we learned the Python pandas `DataFrame.cummin()` method. We learned the syntax, parameters and by solving examples we understood the `DataFrame.cummin()` method.

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