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

Metaflow

8
31
+ 1
0
Pandas

1.2K
1K
+ 1
20
Add tool

Pandas vs Metaflow: What are the differences?

Pandas: High-performance, easy-to-use data structures and data analysis tools for the Python programming language. Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more; Metaflow: Build and manage real-life data science projects with ease. It is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. It was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.

Pandas and Metaflow can be primarily classified as "Data Science" tools.

Some of the features offered by Pandas are:

  • Easy handling of missing data (represented as NaN) in floating point as well as non-floating point data
  • Size mutability: columns can be inserted and deleted from DataFrame and higher dimensional objects
  • Automatic and explicit data alignment: objects can be explicitly aligned to a set of labels, or the user can simply ignore the labels and let Series, DataFrame, etc. automatically align the data for you in computations

On the other hand, Metaflow provides the following key features:

  • End-to-end ML Platform
  • Model with your favorite tools
  • Powered by the AWS cloud

Pandas and Metaflow are both open source tools. Pandas with 24.6K GitHub stars and 9.91K forks on GitHub appears to be more popular than Metaflow with 3.18K GitHub stars and 230 GitHub forks.

Get Advice from developers at your company using Private StackShare. Sign up for Private StackShare.
Learn More
Pros of Metaflow
Pros of Pandas
    Be the first to leave a pro
    • 19
      Easy data frame management
    • 1
      Extensive file format compatibility

    Sign up to add or upvote prosMake informed product decisions

    - No public GitHub repository available -

    What is Metaflow?

    It is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. It was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning.

    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.

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

    What companies use Metaflow?
    What companies use Pandas?
    See which teams inside your own company are using Metaflow or Pandas.
    Sign up for Private StackShareLearn More

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

    What tools integrate with Metaflow?
    What tools integrate with Pandas?

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

    Blog Posts

    GitHubPythonReact+42
    47
    39555
    GitHubGitDocker+34
    29
    41161
    What are some alternatives to Metaflow and Pandas?
    Airflow
    Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
    Kubeflow
    The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.
    Luigi
    It is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
    TensorFlow
    TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
    MLflow
    MLflow is an open source platform for managing the end-to-end machine learning lifecycle.
    See all alternatives