5 Best Ways to Split a Given List and Insert It Into an Excel File Using Python

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πŸ’‘ Problem Formulation: Python users often need to take a list of data, split it appropriately, and insert it into an Excel spreadsheet. For example, given a list [‘John Doe’, ‘Tech’, 50000, ‘Jane Smith’, ‘Marketing’, 60000], the goal is to divide it into rows or columns and populate an Excel file, where each row contains the details of one employee.

Method 1: Using pandas.DataFrame with ExcelWriter

This method involves creating a pandas DataFrame by reshaping the list into the desired format and then utilizing the ExcelWriter function to insert the DataFrame into an Excel file. This is advantageous due to pandas’ powerful data manipulation capabilities.

Here’s an example:

import pandas as pd

# Given list to insert into Excel
data_list = ['John Doe', 'Tech', 50000, 'Jane Smith', 'Marketing', 60000]
reshaped_data = [data_list[i:i+3] for i in range(0, len(data_list), 3)]

# Create a pandas DataFrame
df = pd.DataFrame(reshaped_data, columns=['Name', 'Department', 'Salary'])

# Write the DataFrame to an Excel file
with pd.ExcelWriter('employees.xlsx') as writer:
    df.to_excel(writer, index=False)

Output: An Excel file ’employees.xlsx’ with the data properly split into rows and saved.

This snippet takes the list ‘data_list’, splits it into sublists of length three, turns it into a pandas DataFrame and writes it to an Excel file without the index. The ExcelWriter context manager is used for efficient saving.

Method 2: Using Openpyxl for Fine-Grained Control

Openpyxl is an Excel handling library that allows for more fine-grained control over Excel worksheets. It’s best for complex Excel operations, like formatting, but also works great for inserting lists.

Here’s an example:

from openpyxl import Workbook

# Create a new workbook and select the active worksheet
wb = Workbook()
ws = wb.active

# Given list to insert into Excel
data_list = ['John Doe', 'Tech', 50000, 'Jane Smith', 'Marketing', 60000]

# Append rows to the worksheet
for i in range(0, len(data_list), 3):
    ws.append(data_list[i:i + 3])

# Save the workbook
wb.save('employees.xlsx')

Output: An Excel file ’employees.xlsx’ with the list’s data inserted row by row.

In this code, we initialize a new Excel workbook, select the active sheet, and append each sublist of three elements from ‘data_list’ as a new row to the sheet. Then, we save the workbook to an Excel file.

Method 3: Using xlsxwriter with Explicit Cell Positioning

Xlsxwriter is a Python module for writing files in the Excel 2007+ XLSX file format. It can be used to write text, numbers, and formulas to multiple worksheets and provides features for more explicit cell positioning.

Here’s an example:

import xlsxwriter

# Create a new Excel file and add a worksheet
workbook = xlsxwriter.Workbook('employees.xlsx')
worksheet = workbook.add_worksheet()

# Given list to insert into Excel
data_list = ['John Doe', 'Tech', 50000, 'Jane Smith', 'Marketing', 60000]

# Start from the first cell
row = 0
col = 0

# Iterate over the data and write it out row by row
for index in range(0, len(data_list), 3):
    for item in data_list[index:index+3]:
        worksheet.write(row, col, item)
        col += 1
    row += 1
    col = 0

# Close the workbook
workbook.close()

Output: An Excel file ’employees.xlsx’ with cells populated with the list’s data.

In the provided example, the ‘xlsxwriter’ module is used to create a new workbook and add a worksheet to it. The ‘data_list’ is then written to the sheet, cell by cell, with explicit row and column counters to ensure the correct placement of data.

Method 4: Using csv module to Create a CSV File

If compatibility with older versions of Excel or other spreadsheet software is required, using Python’s built-in CSV module to create a CSV file might be a suitable method. It is less direct than working with Excel files, but CSV files are widely used and can be opened with any spreadsheet software.

Here’s an example:

import csv

# Given list to insert into CSV
data_list = ['John Doe', 'Tech', 50000, 'Jane Smith', 'Marketing', 60000]

# Open a CSV file for writing
with open('employees.csv', 'w', newline='') as file:
    writer = csv.writer(file)

    # Write each sublist of three items as a row in the CSV file
    for i in range(0, len(data_list), 3):
        writer.writerow(data_list[i:i + 3])

Output: A CSV file ’employees.csv’ that, when opened with Excel, shows the list’s data in rows.

This code creates a CSV file with Python’s csv.writer and writes rows of data after slicing the ‘data_list’ into sublists.

Bonus One-Liner Method 5: A Simple Python One-Liner with pandas

For simplicity and quick tasks, using a one-liner in pandas can be a time-saver. Note that this method assumes that the list structure is known and consistent.

Here’s an example:

pd.DataFrame([data_list[i:i+3] for i in range(0, len(data_list), 3)]).to_excel('employees.xlsx', index=False)

Output: An Excel file ’employees.xlsx’ created with a single line of code.

This one-liner utilizes list comprehension to reshape the ‘data_list’ and immediately writes it to an Excel file using pandas’ to_excel function without including the DataFrame’s index.

Summary/Discussion

  • Method 1: Using pandas.DataFrame with ExcelWriter. Strengths: Utilizes powerful pandas functions, easy to manipulate data before exporting. Weaknesses: Requires pandas installation, may be overkill for simple tasks.
  • Method 2: Using Openpyxl for Fine-Grained Control. Strengths: Offers detailed control over Excel file operations. Weaknesses: Might have a steeper learning curve, performance overhead on large files.
  • Method 3: Using xlsxwriter with Explicit Cell Positioning. Strengths: Good for precise positioning and formatting in Excel. Weaknesses: Can be verbose for simple operations, requires xlsxwriter installation.
  • Method 4: Using csv module to Create a CSV File. Strengths: Simple and doesn’t require third-party modules, high compatibility. Weaknesses: Doesn’t directly create an Excel file, limited functionality compared to Excel-specific libraries.
  • Method 5: A Simple Python One-Liner with pandas. Strengths: Quick and concise for small tasks. Weaknesses: Limited to straightforward cases, less control over the output.