How to sum specific rows Pandas dataframe

Pandas, Pandas-append

In this post, we are to learn, How to sum specific rows in Pandas dataframe or Pandas sum specific rows. The DataFrame.eval() ,loc(),iloc[] and sum() functions are used with example.To use the Pandas library, first, we have to install it on the local system by using the pip command “pip install pandas” and import it into our code by using “import pandas as pd” to use its functions

1. How to sum specific rows Pandas dataframe

The python eval() function evaluates the given expression and executes it if it is a valid python statement. In this example, we have used the eval() function to pass a sum expression to sum specific columns Admit_fee+Tution_Fee + Fee function.

#python program to sum specifc rows in Pandas dataframe
import pandas as pd

   
data = {
    'Name': ['Jack', 'Rack', 'Max', 'David'],
    'Marks':[97,97,100,100],
    'Admit_fee':[201,203,205,206],
    'Fee':[100,200,300,400],
    'Tution_Fee':[400,500,600,700]
}
 
dfobj = pd.DataFrame(data)

rows_sum = dfobj.eval('Sum = Admit_fee+Tution_Fee + Fee')
print(rows_sum)

Output

    Name  Marks  Admit_fee  Fee  Tution_Fee   Sum
0   Jack     97        201  100         400   701
1   Rack     97        203  200         500   903
2    Max    100        205  300         600  1105
3  David    100        206  400         700  1306

2. How to sum specific rows Pandas dataframe

In the above example, we have used the eval() function along with the loc[] property to sum specific rows of Pandas dataframe. We have labeled the index of the dataframe by using the index =[‘R1′,’R2′,’R3′,’R4’]. The loc[] is used to select the rows specific rows and the eval() function to sum these rows by evaluating an expression.

import pandas as pd

   
data = {
    'Name': ['Jack', 'Rack', 'Max', 'David'],
    'Marks':[97,97,100,100],
    'Admit_fee':[201,203,205,206],
    'Fee':[100,200,300,400],
    'Tution_Fee':[400,500,600,700]
}
 
dfobj = pd.DataFrame(data,index =['R1','R2','R3','R4'])

dfobj = dfobj.loc['R1':'R4'].eval('Sum = Admit_fee + Tution_Fee + Fee')

print(dfobj)

Output

     Name  Marks  Admit_fee  Fee  Tution_Fee   Sum
R1   Jack     97        201  100         400   701
R2   Rack     97        203  200         500   903
R3    Max    100        205  300         600  1105
R4  David    100        206  400         700  1306

3. How to sum specific rows Pandas dataframe using loc[]

The loc[] property is used to select the rows based on the rows label and the sum function is used to sum the selected specific rows. In this example, we have selected the rows based on the rows label using loc[‘R1′:’R4’] and the sum() function is to sum the rows.

import pandas as pd
   
data = {
    'Name': ['Jack', 'Rack', 'Max', 'David'],
    'Marks':[97,97,100,100],
    'Admit_fee':[201,203,205,206],
    'Fee':[100,200,300,400],
    'Tution_Fee':[400,500,600,700]
}
 
dfobj = pd.DataFrame(data,index =['R1','R2','R3','R4'])


dfobj['Total'] = dfobj.loc['R1':'R4',['Admit_fee','Fee','Tution_Fee']].sum(axis = 1)

print(dfobj)

Output

     Name  Marks  Admit_fee  Fee  Tution_Fee  Total
R1   Jack     97        201  100         400    701
R2   Rack     97        203  200         500    903
R3    Max    100        205  300         600   1105
R4  David    100        206  400         700   1306

4. How to sum specific rows Pandas dataframe using iloc[]

The pandas iloc[] is an integer-based index used to select rows by position. While creating a dataframe pd.DataFrame(data) does not pass the index parameter, the default index starts from 0 to a number of rows. So we have used iloc[] to select the rows the index position and the sum() function to sum these specific rows.

import pandas as pd   
data = {
    'Name': ['Jack', 'Rack', 'Max', 'David'],
    'Marks':[97,97,100,100],
    'Admit_fee':[201,203,205,206],
    'Fee':[100,200,300,400],
    'Tution_Fee':[400,500,600,700]
}
 
dfobj = pd.DataFrame(data)

dfobj['Sum'] = dfobj.iloc[[1,3]].sum(axis=1)


print(dfobj)

Output

    Name  Marks  Admit_fee  Fee  Tution_Fee     Sum
0   Jack     97        201  100         400     NaN
1   Rack     97        203  200         500  1000.0
2    Max    100        205  300         600     NaN
3  David    100        206  400         700  1406.0

Summary

In this post, we have learned How to sum specific rows in Pandas dataframe using eval(),iloc[], and loc[] sum() function with examples.eval() evaluate a python expression to sum,iloc[] based on index, loc[] is used to sum based on row label.

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