Python | Pandas Panel.sum ()

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:

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 < code class = "keyword"> = pd.Panel.from_dict (data, orient = `minor` )

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

print ( " " , panel [ ` b` ]. sum (axis = 1 ))