Python | Pandas Panel.cummin ()

NumPy | Python Methods and Functions

Panel.cummin() is used to return a DataFrame or Series of the same size containing the cumulative minimum.

Syntax : Panel.cummin (axis = None, skipna = True, * args, ** kwargs)

Parameters:
axis: The index or the name of the axis. 0 is equivalent to None or `index`.
skipna: Exclude NA / null values. If an entire row / column is NA, the result will be NA.

Returns: Cummin of DataFrame or Panel

Code # 1:

# pandas module import

import pandas as pd 

import numpy as np

 

df1 = pd.DataFrame ({ ` a` : [ `Geeks` , ` For` , `geeks` , ` for` , `real` ], 

`b` : [ 11 , 1.025 , 333 , 114.48 , 1333 ]})

 

data = { ` item1` : df1, `item2` : df1}

 
# panel creation

panel = pd.Panel .from_dict (data, orient = `minor` )

 

print (panel [ `b` ])

 

print ( "" , panel [ `b` ]. cummin (axis = 0 ))

Output:

Code # 2:

Output:





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# pandas module import

import pandas as pd 

import numpy as np

  

df1 = pd.DataFrame ({ `a` : [ ` Geeks` , `For` , ` geeks` ], 

`b` : np.random.randn ( 3 )})

 

data = { `item1` : df1, ` item2` : df1}

 
# create a panel

panel = pd.Panel.from_dict (data, orient = `minor` )

 

print (panel [ ` b` ])

 

 

df2 = pd.DataFrame ({ `b` : [ 11 , 12 , 13 ]})

print ( " " , panel [ ` b` ]. cummin (axis = 0 ))