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  2. Python | Pandas Panel.sum ()

Python | Pandas Panel.sum ()

NumPy | Python Methods and Functions

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 ))