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Pandas VS Highcharts

Compare Pandas VS Highcharts and see what are their differences

Draxlr
Turn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface. featured
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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Pandas logo Pandas

Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Highcharts logo Highcharts

A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application
  • Pandas Landing page
    Landing page //
    2023-05-12
  • Highcharts Landing page
    Landing page //
    2023-03-16

Pandas features and specs

  • Data Wrangling
    Pandas offers robust tools for manipulating, cleaning, and transforming data, making it easier to prepare data for analysis.
  • Flexible Data Structures
    Pandas provides two primary data structures: Series and DataFrame, which are flexible and offer powerful capabilities for handling various types of datasets.
  • Integration with Other Libraries
    Pandas integrates seamlessly with other Python libraries such as NumPy, Matplotlib, and SciPy, facilitating comprehensive data analysis workflows.
  • Performance with Data Size
    For data sizes that fit into memory, Pandas performs excellently with operations and computations being highly optimized.
  • Rich Feature Set
    Pandas provides a wide array of functionalities, including but not limited to group-by operations, merging and joining data sets, time-series functionality, and input/output tools.
  • Community and Documentation
    Pandas has a strong community and extensive documentation, offering a wealth of tutorials, examples, and support for new and experienced users alike.

Possible disadvantages of Pandas

  • Memory Consumption
    Pandas can become memory inefficient with very large datasets because it relies heavily on in-memory operations.
  • Single-threaded
    Many Pandas operations are single-threaded, which can lead to performance bottlenecks when handling very large datasets.
  • Steep Learning Curve
    For users who are new to data analysis or Pandas, there can be a steep learning curve due to its extensive capabilities and complex syntax at times.
  • Less Suitable for Real-time Analytics
    Pandas is not designed for real-time analytics and is better suited for batch processing due to its in-memory operations and single-threaded nature.
  • Error Handling
    Error messages in Pandas can sometimes be cryptic and hard to interpret, making debugging a challenge for users.

Highcharts features and specs

  • Customization
    Highcharts provides extensive options to customize chart appearance and functionality, allowing for a tailored and specific data visualization experience.
  • Cross-Browser Compatibility
    Highcharts ensures compatibility across a wide range of browsers, making charts accessible to users regardless of their browser preferences.
  • Wide Range of Chart Types
    Offers a broad spectrum of chart types, including line, bar, pie, scatter, and more, catering to various data visualization needs.
  • Interactive Features
    Includes numerous interactive features such as tooltips, zooming, and clickable points, enhancing user engagement with the data.
  • Strong Community and Support
    Has an active community and provides extensive documentation, forums, and professional support options to assist users in overcoming challenges.
  • Performance
    Optimized for high performance, allowing for the rendering of large datasets without significant lag or performance issues.
  • Exporting and Sharing
    Built-in options for exporting charts to various formats (PNG, JPEG, PDF, etc.) and sharing them easily.

Possible disadvantages of Highcharts

  • Cost
    Highcharts is not free for commercial use, which may be a drawback for small businesses or individual developers with limited budgets.
  • Steep Learning Curve
    Despite comprehensive documentation, the abundance of features and customization options can result in a steeper learning curve for new users.
  • Dependency on JavaScript
    As a JavaScript library, Highcharts requires a solid understanding of JavaScript, making it less accessible for developers not familiar with the language.
  • Limited Free Support
    While there is a free support forum, professional support options are paid, which can be a limitation for users needing urgent assistance without extra costs.
  • Mobile Responsiveness
    Although Highcharts provides some support for mobile responsiveness, achieving optimal performance and displays on all device types may require additional customization.

Pandas videos

+ Add

Ozzy Man Reviews: Pandas

More videos:

  • Review - Ozzy Man Reviews: PANDAS Part 2
  • Review - Trash Pandas Review with Sam Healey

Highcharts videos

+ Add

Angular 2 & HighCharts Quick-Tip: Dynamic Data & Draggable Points (2016)

More videos:

  • Tutorial - How to define the custom colors for Highcharts?
  • Review - Data Visualization HighCharts

Category Popularity

0-100% (relative to Pandas and Highcharts)

Pandas

Highcharts

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Data Dashboard
27 27%
Data Dashboard
73% 73
Data Science Tools
100 100%
Data Science Tools
0% 0
Data Visualization
0 0%
Data Visualization
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Pandas and Highcharts

Pandas Reviews

25 Python Frameworks to Master
Pandas is a powerful and flexible open-source library used to perform data analysis in Python. It provides high-performance data structures (i.e., the famous DataFrame) and data analysis tools that make it easy to work with structured data.
Source: kinsta.com
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When it comes to ETL, you can do almost anything with Pandas if you're willing to put in the time. Plus, pandas is extraordinarily easy to run. You can set up a simple script to load data from a Postgre table, transform and clean that data, and then write that data to another Postgre table.
Source: www.xplenty.com

Highcharts Reviews

6 JavaScript Charting Libraries for Powerful Data Visualizations in 2023
However, you might need to pay for additional packages to get exactly what you’re looking for. The Highcharts Core package includes all the essentials (like line, bar, area, and pie charts) but Maps, Gantt, and Stock chart packages are all extra. In terms of cost, this makes Highcharts somewhat less scalable, depending on the budget available for your project.
Source: embeddable.com
15 JavaScript Libraries for Creating Beautiful Charts
Highcharts is another very popular library for building graphs. It comes loaded with many different types of cool animations that are sufficient to attract many eyeballs to your website. Just like other libraries, Highcharts comes with many pre-built graphs like spline, area, areaspline, column, bar, pie, scatter, etc. The charts are responsive and mobile-ready. Besides,...
Source: www.sitepoint.com
Best Data Visualization Tools
For companies that want to embed interactive visualizations in their online content, look no further than Datawrapper. Highcharts is another great option for embedding interactive content into your sites, though it’s not as easy for non-specialists as Datawrapper.
Source: neilpatel.com
Top 10 JavaScript Charting Libraries for Every Data Visualization Need
Highcharts is one of the most comprehensive and popular JavaScript charting libraries based on HTML5, rendering in SVG/VML. It is lightweight, supports a wide range of diverse chart types, and ensures high performance.
Source: hackernoon.com
The Best Data Visualization Tools - Top 30 BI Software
Highcharts is a battle-tested SVG-based, multi-platform charting library that has been actively developed since 2009. Its JavaScript API integrates easily, and features robust documentation, advanced responsiveness and industry-leading accessibility support. You can add interactive, mobile-optimized charts to your web and mobile projects. Charts are rendered in SVG and a VML...
Source: improvado.io

Social recommendations and mentions

Based on our record, Pandas seems to be more popular. It has been mentiond 219 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Pandas mentions (219)

  • Top Programming Languages for AI Development in 2025
    Libraries for data science and deep learning that are always changing. - Source: dev.to / 11 days ago
  • How to import sample data into a Python notebook on watsonx.ai and other questions…
    # Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / 27 days ago
  • How I Hacked Uber’s Hidden API to Download 4379 Rides
    As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / about 1 month ago
  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
  • Sample Super Store Analysis Using Python & Pandas
    This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 9 months ago
View more

Highcharts mentions (0)

We have not tracked any mentions of Highcharts yet. Tracking of Highcharts recommendations started around Mar 2021.

What are some alternatives?

When comparing Pandas and Highcharts, you can also consider the following products

NumPy - NumPy is the fundamental package for scientific computing with Python

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Chart.js - Easy, object oriented client side graphs for designers and developers.

OpenCV - OpenCV is the world's biggest computer vision library

Google Charts - Interactive charts for browsers and mobile devices.

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