Fixing Issues with Iterating Over Lists and Generating Excel Files in Python

Understanding the Issue with Iterating Over a List of Objects and Generating an Excel File

As developers, we often encounter scenarios where we need to work with data that exists in various formats. In this case, we’re dealing with a list of objects, each representing a dog with attributes like ID, type, name, and age. Our goal is to generate an Excel file containing records of these dogs. However, when we execute the code, only the last record appears in the resulting Excel file, causing the previous records to overwrite each other.

Identifying the Problem

The problem lies in how we’re creating our DataFrame and writing it to the Excel file. Specifically, the issue arises from the fact that we’re using the same list (lisIDs and lisNames) to represent the dog’s ID and name for every iteration of the loop. This means that only the last value in these lists will be written to the Excel file.

Solution Overview

To resolve this problem, we need to create separate lists to store the dog’s ID and name for each iteration of the loop. We’ll also make sure to use these lists consistently when creating our DataFrame and writing it to the Excel file.

Step 1: Creating Separate Lists for Dog IDs and Names

First, let’s create two empty lists (lisIDs and lisNames) that will store the dog’s ID and name for each iteration of the loop.

# Import necessary libraries
import pandas as pd

# Define a class to represent a dog
class dog:
    def __init__(self, id, type, name, age):
        self.id = id
        self.type = type
        self.name = name
        self.age = age

# Initialize empty lists for dog IDs and names
lisIDs = []
lisNames = []

# Iterate over the range of 10 to create dogs
for i in range(10):
    # Create a new dog object with specific attributes
    newDog = dog(i, 'any', 'any2', i+1)
    
    # Append the dog's ID and name to their respective lists
    lisIDs.append(newDog.id)
    lisNames.append(newDog.name)

# Print the contents of the lists (optional)
print("Dog IDs:", lisIDs)
print("Dog Names:", lisNames)

Step 2: Creating a DataFrame from Separate Lists

Now that we have separate lists for dog IDs and names, let’s create a DataFrame using these lists.

# Create a DataFrame from the lists of dog IDs and names
df = pd.DataFrame({
    'dog ID': lisIDs,
    'dog Name': lisNames
})

# Print the contents of the DataFrame (optional)
print(df)

Step 3: Writing the DataFrame to an Excel File

Finally, let’s write our DataFrame to an Excel file using the pd.ExcelWriter class.

# Set up the file name and writer
fname = "StatisticsDogs.xlsx"
writer = pd.ExcelWriter(fname, engine='xlsxwriter')

# Write the DataFrame to the Excel file (sheet_name='Sheet1')
df.to_excel(writer, sheet_name='Sheet1', index=False)

# Close the writer
writer.save()

Combining the Code

Let’s combine all the steps into a single function.

def generate_excel_file():
    # Define a class to represent a dog
    class dog:
        def __init__(self, id, type, name, age):
            self.id = id
            self.type = type
            self.name = name
            self.age = age
    
    # Initialize empty lists for dog IDs and names
    lisIDs = []
    lisNames = []
    
    # Iterate over the range of 10 to create dogs
    for i in range(10):
        # Create a new dog object with specific attributes
        newDog = dog(i, 'any', 'any2', i+1)
        
        # Append the dog's ID and name to their respective lists
        lisIDs.append(newDog.id)
        lisNames.append(newDog.name)

    # Create a DataFrame from the lists of dog IDs and names
    df = pd.DataFrame({
        'dog ID': lisIDs,
        'dog Name': lisNames
    })

    # Set up the file name and writer
    fname = "StatisticsDogs.xlsx"
    writer = pd.ExcelWriter(fname, engine='xlsxwriter')

    # Write the DataFrame to the Excel file (sheet_name='Sheet1')
    df.to_excel(writer, sheet_name='Sheet1', index=False)

    # Close the writer
    writer.save()

# Call the function to generate the Excel file
generate_excel_file()

Explanation and Advice

In this solution, we’ve created separate lists for dog IDs and names. We then use these lists consistently when creating our DataFrame and writing it to the Excel file.

When working with data in Python, it’s essential to be mindful of how you’re storing and manipulating data. In this case, using separate lists to store the dog’s ID and name helped us avoid overwriting previous records.

To avoid similar issues in the future, remember to:

Use consistent naming conventions for variables and lists.
Be careful when creating new objects or appending values to existing ones.
Always double-check your code before running it to ensure accuracy.

By following these steps and best practices, you’ll be able to generate an Excel file containing records of your dog’s data.

Last modified on 2023-06-23