Panel.sum()
is used to return the sum of values for the requested axis.
Syntax: Panel.sum (axis = None, skipna = None, level = None, numeric_only = None, min_count = 0, ** kwargs)
Parameters:
axis: {items (0), major_axis (1), minor_axis (2)}
skipna: Exclude NA / null values when computing the result.
level: If the axis is a MultiIndex, count along a particular level , collapsing into a DataFrame
numeric_only: Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data.
min_count: The required number of valid values to perform the operation.
Returns: DataFrame or Panel
Code # 1:
# pandas module import import pandas as pd import numpy as np df1 = pd.DataFrame ({ ’a’ : [ ’Geeks’ , ’For’ , ’ geeks’ , ’f or’ , ’real’ ], ’b’ : [ 11 , 1.025 , 333 , 114.48 , 1333 ]}) data = { ’ item1’ : df1, ’item2’ : df1 } # create a panel panel = pd.Panel.from_d ict (data, orient = ’minor’ ) print (panel [ ’b’ ], ’ ’ ) print ( "" , panel [ ’b’ ]. sum (axis = 0 )) |
Output:
Code # 2:
# import pandas module import pandas as pd import numpy as np df1 = pd.DataFrame ({ ’a’ : [ ’ Geeks’ , ’For’ , ’geeks’ , ’for’ , ’ real’ ], ’b’ : [ 33.0 , - 152.140 , 3.0133 , 114.48 , 13.033 ]}) data = { ’item1’ : df1, ’item2’ : df1} # create a panel panel = pd.Panel.from_dict (data, orient = ’minor’ ) print (panel [ ’b’ ], ’’ ) print ( "" , panel [ ’b’ ]. sum (axis = 1 )) |
Output:
Code # 3:
# 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 < code class = "keyword"> = pd.Panel.from_dict (data, orient = ’minor’ ) print (panel [ ’b’ ], ’ ’ ) print ( " " , panel [ ’ b’ ]. sum (axis = 1 )) |
Output:
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