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How to use the DataFrame.combine() method in pandas

Salman Yousaf

Overview

A Python library, pandas, is specially used for data manipulation and analysis. It provides multiple built-in methods for manipulating tables into DataFrames. In this shot, we are going to discuss the combine() method from the DataFrame module of this library.

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The DataFrame.combine() method is used to combine a DataFrame with the other DataFrame by using func to get element-wise combined columns. The dimensions of the resulting DataFrame will be the union of these DataFrames.

Syntax


DataFrame.combine(other, func, fill_value=None, overwrite=True)

Parameters

It takes the following argument values.

  • other: Another DataFrame to combine element-wise.
  • func: A function that takes two pandas series as inputs and returns a scaler series. It helps to combine two DataFrames.
  • fill_value=None: The value to fill empty or NaNs before merging two columns. Its default value is None.
  • overwrite=True: If overwrite is set to True, columns in self will be overwritten with NaNs in other. Its default value is True.

Return value

The pandas DataFrame returns a combination of two self and other DataFrames.

Explanation

In this code snippet, we are going to elaborate on how the combine() method can be used in different scenarios.

# load pandas module in program
import pandas as pd
# creating two DataFrames
df1 = pd.DataFrame({'A': [1,2,3], 'B': [0,-1,4]})
df2 = pd.DataFrame({'A': [0,2,1], 'B': [-3,4,9]})
smaller = lambda s1, s2: s1 if s1.sum() < s2.sum() else s2
df1.combine(df2, func=smaller)
print(df1)
# creating another two dataframes to check the functionality of fill_value
df3 = pd.DataFrame({'A': [0, 0], 'B': [None, 4]})
df4 = pd.DataFrame({'A': [1, 1], 'B': [3, 3]})
df1.combine(df4, smaller, fill_value=-5)
print(df3)

Explanation

  • Lines 1–5: We import the pandas library as pd in the program. In lines 4 and 5, we create two data frames df1 and df2.
  • Line 6: We define a lambda function used to broadcast input values. It returns s1 if s1.sum() < s2.sum(). Otherwise, it returns s2.
  • Line 7: We invoke pandas.combine() to merge two DataFrames, such as df1 & df2.
  • Lines 10 and 11: We create new DataFrames df3 and df4.
  • Line 12: We then invoke pandas.combine() to merge df3 and df4. It's taking df4, smaller, and fill_value=-5 as arguments. In case of missing values, it will be replaced with -5.

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