Need advice about which tool to choose?Ask the StackShare community!

Pandas

1.7K
1.3K
+ 1
23
xlwings

35
125
+ 1
0
Add tool

Pandas vs xlwings: What are the differences?

Introduction

In this article, we will discuss the key differences between Pandas and xlwings, two popular tools used for data manipulation and analysis in Python.

  1. Installation and Dependencies: Pandas is a Python library that can be easily installed using pip or conda, and it is dependent on other libraries such as NumPy. On the other hand, xlwings is an Excel add-in that requires installation on Windows or Mac environment, along with a license for advanced functionalities.

  2. Data Manipulation and Analysis: Pandas provides a powerful toolkit for manipulating and analyzing structured data, offering functionalities such as data cleaning, grouping, merging, and pivot tables. It has a comprehensive set of functions and methods for handling data efficiently. Xlwings, on the other hand, is primarily used for interacting with Excel and automating Excel tasks using Python. It allows accessing and modifying Excel workbooks, worksheets, and cells, but it does not provide the same level of data manipulation and analysis features as Pandas.

  3. Integration with Excel: Pandas can read and write Excel files using its read_excel and to_excel methods, but it does not have the ability to interact with Excel in real-time. Xlwings, on the other hand, provides direct integration with Excel, allowing users to manipulate and control Excel objects from Python. This includes automating processes, extracting data from Excel, and updating Excel documents with Python calculations.

  4. Performance: Pandas is designed to efficiently handle large datasets and provides optimized functions for data manipulation, which makes it suitable for handling big data analysis tasks. Xlwings, on the other hand, is more focused on Excel integration and automation, and it may not have the same level of performance as Pandas when it comes to data manipulation operations.

  5. Compatibility and Platform: Pandas is a cross-platform library and works on various operating systems, including Windows, Mac, and Linux. It can be used with different IDEs and text editors. Xlwings, on the other hand, is primarily designed for Windows and Mac environments, and it requires Excel installation to work. It is more suitable for users who frequently work with Excel in their data analysis tasks.

  6. Community and Ecosystem: Pandas has a large and active community of users and contributors, which means it has extensive documentation, third-party libraries, and online resources available. Xlwings, although not as popular as Pandas, also has an active community and provides documentation and examples to help users get started with Excel integration in their Python workflow.

In summary, while both Pandas and xlwings are useful tools for data manipulation and analysis, Pandas is more focused on providing comprehensive data manipulation and analysis functionalities, while xlwings is specialized in interacting with Excel and automating Excel tasks using Python.

Manage your open source components, licenses, and vulnerabilities
Learn More
Pros of Pandas
Pros of xlwings
  • 21
    Easy data frame management
  • 2
    Extensive file format compatibility
    Be the first to leave a pro

    Sign up to add or upvote prosMake informed product decisions

    Cons of Pandas
    Cons of xlwings
      Be the first to leave a con
      • 3
        Very slow and still needs VBA for UDFs

      Sign up to add or upvote consMake informed product decisions

      What is Pandas?

      Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.

      What is xlwings?

      Replace your VBA code with Python, a powerful yet easy-to-use programming language that is highly suited for numerical analysis. Supports Windows & Mac!

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use Pandas?
      What companies use xlwings?
      Manage your open source components, licenses, and vulnerabilities
      Learn More

      Sign up to get full access to all the companiesMake informed product decisions

      What tools integrate with Pandas?
      What tools integrate with xlwings?
        No integrations found

        Sign up to get full access to all the tool integrationsMake informed product decisions

        Blog Posts

        GitHubPythonReact+42
        49
        40862
        GitGitHubDocker+34
        29
        42630
        What are some alternatives to Pandas and xlwings?
        Panda
        Panda is a cloud-based platform that provides video and audio encoding infrastructure. It features lightning fast encoding, and broad support for a huge number of video and audio codecs. You can upload to Panda either from your own web application using our REST API, or by utilizing our easy to use web interface.<br>
        NumPy
        Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
        R Language
        R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.
        Apache Spark
        Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
        PySpark
        It is the collaboration of Apache Spark and Python. it is a Python API for Spark that lets you harness the simplicity of Python and the power of Apache Spark in order to tame Big Data.
        See all alternatives