Evaluate the sum of rows using the eval() function – Python Pandas

The eval() function can also be used to evaluate the sum of rows with the specified columns. At first, let us create a DataFrame with Product records −

dataFrame = pd.DataFrame({"Product": ["SmartTV", "ChromeCast", "Speaker", "Earphone"],"Opening_Stock": [300, 700, 1200, 1500],"Closing_Stock": [200, 500, 1000, 900]})

Finding sum using eval(). The resultant column with the sum is also mentioned in the eval(). The expression displays the sum formulae assigned to the resultant column −

dataFrame = dataFrame.eval('Result_Sum = Opening_Stock + Closing_Stock')

Example

Following is the complete code −

import pandas as pd

dataFrame = pd.DataFrame({"Product": ["SmartTV", "ChromeCast", "Speaker", "Earphone"],"Opening_Stock": [300, 700, 1200, 1500],"Closing_Stock": [200, 500, 1000, 900]})

print("DataFrame...\n",dataFrame)

# finding sum using eval()
# the resultant column with the sum is also mentioned in the eval()
# the expression displays the sum formulae assigned to the resultant column
dataFrame = dataFrame.eval('Result_Sum = Opening_Stock + Closing_Stock')
print("\nSumming rows...\n",dataFrame)

Output

This will produce the following output −

DataFrame...
      Product   Opening_Stock   Closing_Stock
0     SmartTV             300             200
1  ChromeCast             700             500
2     Speaker            1200            1000
3    Earphone            1500             900

Summing rows...
      Product   Opening_Stock   Closing_Stock   Result_Sum
0     SmartTV             300             200          500
1  ChromeCast             700             500         1200
2     Speaker            1200            1000         2200
3    Earphone            1500             900         2400