Evaluate a string describing operations on DataFrame columns

Overview

The eval() function is used to perform an evaluation to a string describing operations on the columns of a given DataFrame.

Syntax

DataFrame.eval(expr, inplace=False, **kwargs)[source]
Syntax for the eval() function in pandas

Parameters

  • expr: This is a string expression to be evaluated.
  • inplace: This takes a boolean value indicating if the operation is to be performed on the original DataFrame.
  • **kwargs: These are the keywords that have no effect but may be accepted for compatibility with NumPy.

Return value

This function returns a DataFrame holding the results from the evaluation.

Example

# A code to illustrate the cummax() function in Pandas



# importing the pandas library

import pandas as pd



# creating a dataframe

df = pd.DataFrame([[1,2],

                   [3,4]],

                   columns=list('AB'))

# printing the dataframe

print(df)



# performing addition of A and B

print("Addition")

print(df.eval('A + B'))



# performing subtraction of A and B

print("Subtraction")

print(df.eval('A - B'))

Explanation

  • Line 4: We import the pandas library.
  • Lines 7–9: We create a dataframe, df.
  • Line 11: We print the dataframe, df.
  • Line 15: We use the eval() function to evaluate a string expression (addition) for the columns of the DataFrame. We print the result to the console.
  • Line 19: We use the eval() function to evaluate a string expression (subtraction) for the columns of the DataFrame. We print the result to the console.

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