Group By Two Variables and then Create New Column which is the Value of One Variable Based on the Value of Another Variable in Python (pandas)

In this section, we will discuss how to group by two variables and create a new column that contains the value of one variable based on the value of another variable in pandas.

Problem Statement

The problem statement is as follows:

• We have data with columns sbj, num_item, visit, and height.
• We want to create a new column called baseline_height which is set to the value of height at baseline for each group of sbj and num_item.

Code Fails

The provided code fails in several ways. Here are some of the issues:

• The use of incorrect syntax for grouping by multiple columns.
• Incorrect use of logical operators (==, !=) with pandas Series.

Solution

To solve this problem, we will follow these steps:

1. Sort the data by sbj, num_item, and visit to ensure that the “Baseline” always appears before the different days (“Day 7”, “Day 14”, etc.).

2. Set the baseline_height column to the value of height.

3. Use the groupby method along with the transform method to populate baseline_height with the first value for each group of sbj, num_item.

Code Implementation

Here is the Python code that implements these steps:

import pandas as pd

# Create a sample dataframe
data = {
    'sbj': [1, 1, 1, 2, 2, 2],
    'num_item': [1, 1, 2, 1, 2, 2],
    'visit': ['Baseline', 'Day 7', 'Baseline', 'Day 7', 'Baseline', 'Day 14'],
    'height': [1.5, 2.0, 1.0, 1.0, 3.0, 4.0]
}

df = pd.DataFrame(data)

# Sort the data by sbj, num_item, and visit
df.sort_values(['sbj', 'num_item', 'visit'])

# Set baseline_height to height
df['baseline_height'] = df['height']

# Use groupby and transform to populate baseline_height with first value for each group of sbj, num_item
df['baseline_height'] = df.groupby(by=['sbj', 'num_item']).baseline_height.transform('first')

print(df)

Output

The output will be the sorted dataframe with the baseline_height column populated:

This solution sorts the data by sbj, num_item, and visit to ensure that the “Baseline” always appears before the different days (“Day 7”, “Day 14”, etc.), sets the baseline_height column to the value of height, and uses the groupby method along with the transform method to populate baseline_height with the first value for each group of sbj, num_item.

Last modified on 2023-12-23