How to Split Input Based on Comparing Two Dataframes in Pandas Using Regular Expressions

How to Split the Input Based on Comparing Two Dataframes in Pandas

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In this article, we will discuss how to split an input based on comparing two dataframes in pandas. We will cover the basics of working with dataframes and how to use regular expressions to compare strings.

Introduction

Pandas is a powerful library for data manipulation and analysis in Python. One of its most useful features is the ability to work with dataframes, which are two-dimensional tables of data with columns of potentially different types.

In this article, we will show you how to split an input based on comparing two dataframes in pandas. We will use a simple example to demonstrate the concept and provide more detailed explanations and examples as needed.

The Problem

The problem is that we have two dataframes: df1 and df2. df1 contains the input data, while df2 contains the keyword table with the desired output format. We want to compare each row in df1 with the corresponding row in df2 based on the Name_Extension column.

The Solution

To solve this problem, we can use a simple loop to iterate over each row in df1. For each row, we can check if the Name_Extension value matches any of the values in df2. If it does, we can split the input string into two parts using the matched keyword.

Example Code

import pandas as pd

# Create sample dataframes
df1 = pd.DataFrame({
    'Original_Input': ['LARIDENT SRL', 'MIZUHO Corporation Gosen Factory', 'ZIMMER MANUFACTURING BV'],
    'Cleansed_Input': ['Cleaned Input 1', 'Cleaned Input 2', 'Cleaned Input 3']
})

df2 = pd.DataFrame({
    'Name_Extension': ['co llc', 'Pvt ltd', 'Corp'],
    'Company_Type': ['Company LLC', 'Private Limited', 'Corporation']
})

# Function to split input string
def split_input(input_str, keyword):
    matches = re.search(r'[^&gt;]*?\s+' + str(keyword).strip(), str(input_str).strip(), re.I)
    if matches:
        splits = input_str.str.split(str(keyword), re.I)
        return splits[0]
    else:
        return None

# Apply function to each row in df1
df1['Core_Input'] = df1.apply(lambda row: split_input(row['Cleansed_Input'], row['Name_Extension']), axis=1)

# Merge with df2 based on Name_Extension and Company_Type
df3 = pd.merge(df1, df2, on='Name_Extension', how='left')

# Print result
print(df3)

Explanation

In this example code, we define a function split_input that takes an input string and a keyword as arguments. The function uses regular expressions to search for the keyword in the input string.

If the keyword is found, the function splits the input string into two parts using the matched keyword.

We then apply this function to each row in df1 using the apply method.

Next, we merge df1 with df2 based on the Name_Extension column using the merge method.

Finally, we print the resulting dataframe df3, which contains the split input values and the corresponding company type.

Conclusion

In this article, we demonstrated how to split an input based on comparing two dataframes in pandas. We used regular expressions to compare strings and applied a function to each row in one of the dataframes.

This technique can be useful for various data manipulation tasks, such as text processing or data cleaning. By mastering regular expressions and data manipulation techniques in pandas, you can become more efficient in your work with data.

Last modified on 2025-03-31