Panel.clip() is used to trim values at the input threshold. Thresholds can be single or massive.
Syntax: Panel.clip (lower = None, upper = None, axis = None, inplace = False, * args, ** kwargs)
Parameters: Parameters:
lower: Minimum threshold value. All values below this threshold will be set to it.
upper: Maximum threshold value. All values above this threshold will be set to it.
axis: Align object with lower and upper along the given axis.
inplace: Whether to perform the operation in place on the data.
Returns: [Series or DataFrame] Same type as calling object with the values outside the clip boundaries replaced.
Code # 1: Create a panel with from_dict ()
| # 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 < / code> (panel) |
Output:
Code # 2: Using the clip () function
| # 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’ ]. clip (df2 [ ’b’ ], axis = 0 )) |
Output:
Code # 3: Using the clip () function
| # pandas module import import pandas as pd import numpy as np df1 = pd.DataFrame ({ ’a’ : [ ’Geeks’ , ’ For’ , ’geeks’ , ’real’ ], ’b’ : [ - 11 , + 1.025 , - 114.48 , 1333 ]}) data = { ’item1’ : df1, ’ item2’ : df1}
# create a panel panel = pd.Panel.from_dict (data, orient = ’minor’ ) print (panel [ ’b’ ], ’ ’ ) print (panel [ ’ b’ ]. clip ( - 4 , 6 )) |
Output:
