Adding a Column to a DataFrame Using Another DataFrame with Columns of Different Lengths in Python

Introduction

In this article, we will discuss how to add a column to a pandas DataFrame using another DataFrame that has columns of different lengths. We will explore the use of the isin function and other techniques to achieve this.

Background

Pandas is a powerful library for data manipulation and analysis in Python. One of its key features is the ability to easily manipulate DataFrames, which are two-dimensional tables of data. However, when working with DataFrames that have columns of different lengths, it can be challenging to add new columns or perform certain operations.

Problem Description

The question at hand involves two DataFrames, DF1 and DF2. The values in the first column of DF1 are used as a reference to select corresponding values from the first column of DF2. The resulting DataFrame, DF3, should have the selected values from DF2 added as a new column.

Solution

To solve this problem, we will use a combination of pandas functions and techniques. Here’s the step-by-step solution:

Step 1: Get the Values from DF2 that are in DF1 Column 1

We can use the isin function to get the values from DF2 column 1 that are also present in DF1 column 1.

DF3 = DF2[DF2[1].isin(DF[1].values)]

Step 2: Reset the Index of DF3

Since DF1 and DF3 have columns in the same order, we can reset the index of DF3 to match the order of DF1.

DF3 = DF3.reset_index(drop=True)

Step 3: Reindex and Concatenate DataFrames

We need to reindex and concatenate DF with the selected values from DF2. This will add the new column to DF.

DF3 = pd.concat([DF, DF3[3]], axis=1)

Complete Code

Here’s the complete code:

import pandas as pd

# Create sample DataFrames
DF = pd.DataFrame([[12345678,   40,  10.610000,  1294822,  22345679,  'HCTFCILE',  16000],    
        [12345678,  100,   8.196001,  1294822,  22345679, 'HCTFCILE',  10000],    
        [12345678,  110,   1.062000,  1294822,  22345679,  'HCTFCILE',   1000],    
        [12345678,  130,  2.850000,  1294822,  22345679,  'HCTFCILE',  12000]])

DF2 = pd.DataFrame([[1294822,   10,  'DM',  13500],
        [1294822,   20,  'DM',  33500],
        [1294822,   30,  'DM',  18300],
        [1294822,   40,  'DM',  22200],
        [1294822,  90,  'DM', 16200],
        [1294822, 100,  'DM',  24500],
        [1294822,  110,  'DM',  27800],
        [1294822,  120,  'DM',  15500],
        [1294822,  130,  'DM',  13400]])

# Solve the problem
DF3 = DF2[DF2[1].isin(DF[1].values)]
DF3 = DF3.reset_index(drop=True)
DF3.columns = list(range(8))
DF3 = pd.concat([DF, DF3[3]], axis=1)

print(DF3)

The resulting DF3 DataFrame will have the selected values from DF2 added as a new column.

Conclusion

In this article, we demonstrated how to add a column to a pandas DataFrame using another DataFrame that has columns of different lengths. We used a combination of pandas functions and techniques, including the isin function and concatenation, to achieve this.

Last modified on 2024-11-09