Python | Pandas Panel.clip_upper ()



Panel.clip_upper() is used to return a copy of the input with truncated values ​​above the specified values.

Syntax: Panel.clip_upper (threshold, axis = None, inplace = False)

Parameters:
threshold: float or array_like
axis: Align object with threshold along the given axis.
inplace: Whether to perform the operation in place on the data

Returns: same type as input.

Panel creation:

# 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_dic t (data, orient = `minor` )

print (panel, "" )

Exit :

Code # 1: Using clip_upper ()

# 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, "" )

print (panel [ `b` ], `` )

 

 

df2 = pd.DataFrame ({ `b` : np.random.randn ( 5 )})

print (panel [ `b` ] .clip_upper (df2 [ `b` ], axis = 0 ))

Output:

Code # 2: Using clip_upper ()

# create an empty panel

import pandas as pd

import numpy as np

 

data = { ` Item1` : pd.DataFrame (np. random.randn ( 7 , 4 )), 

`Item2` : pd.DataFrame (np.random.randn ( 4 , 5 ))}

 

pen = pd.Panel (data)

print (pen [ `Item1` ], ` ` )

 

p = pen [ ` Item1` ] [ 0 ]. clip_upper (np.random.randn ( 7 ))

print (p)

Output: