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Python | Pandas Panel.cummin ()

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 ))