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

Pandas

1.4K
1.1K
+ 1
20
xlwings

26
104
+ 1
0
Add tool
Get Advice from developers at your company using Private StackShare. Sign up for Private StackShare.
Learn More
Pros of Pandas
Pros of xlwings
  • 19
    Easy data frame management
  • 1
    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?
      See which teams inside your own company are using Pandas or xlwings.
      Sign up for Private StackShareLearn 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
        48
        39772
        GitHubGitDocker+34
        29
        41434
        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