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Learn MorePros of Pandas
Pros of React
Pros of Pandas
- Easy data frame management21
- Extensive file format compatibility2
Pros of React
- Components837
- Virtual dom673
- Performance578
- Simplicity509
- Composable442
- Data flow186
- Declarative166
- Isn't an mvc framework128
- Reactive updates120
- Explicit app state115
- JSX50
- Learn once, write everywhere29
- Easy to Use22
- Uni-directional data flow21
- Works great with Flux Architecture17
- Great perfomance11
- Javascript10
- Built by Facebook9
- TypeScript support8
- Scalable6
- Server Side Rendering6
- Speed6
- Easy to start5
- Feels like the 90s5
- Hooks5
- Awesome5
- Cross-platform5
- Closer to standard JavaScript and HTML than others5
- Easy as Lego5
- Functional5
- Excellent Documentation5
- Props5
- Scales super well4
- Allows creating single page applications4
- Sdfsdfsdf4
- Start simple4
- Strong Community4
- Super easy4
- Server side views4
- Fancy third party tools4
- Rich ecosystem3
- Has arrow functions3
- Very gentle learning curve3
- Beautiful and Neat Component Management3
- Just the View of MVC3
- Simple, easy to reason about and makes you productive3
- Fast evolving3
- SSR3
- Great migration pathway for older systems3
- Simple3
- Has functional components3
- Every decision architecture wise makes sense3
- Sharable2
- Permissively-licensed2
- HTML-like2
- Image upload2
- Recharts2
- Fragments2
- Split your UI into components with one true state2
- React hooks1
- Datatables1
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Cons of Pandas
Cons of React
Cons of Pandas
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Cons of React
- Requires discipline to keep architecture organized41
- No predefined way to structure your app30
- Need to be familiar with lots of third party packages29
- JSX13
- Not enterprise friendly10
- One-way binding only6
- State consistency with backend neglected3
- Bad Documentation3
- Error boundary is needed2
- Paradigms change too fast2
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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 React?
Lots of people use React as the V in MVC. Since React makes no assumptions about the rest of your technology stack, it's easy to try it out on a small feature in an existing project.
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What companies use Pandas?
What companies use React?
What companies use Pandas?
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What tools integrate with Pandas?
What tools integrate with React?
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What are some alternatives to Pandas and React?
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.