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Pandas VS ThingSpeak

Compare Pandas VS ThingSpeak and see what are their differences

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Contents:
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  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.

ThingSpeak logo ThingSpeak

Open source data platform for the Internet of Things. ThingSpeak Features
  • Pandas Landing page
    Landing page //
    2023-05-12
  • ThingSpeak Landing page
    Landing page //
    2021-07-26

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.

ThingSpeak features and specs

  • Ease of Use
    ThingSpeak provides a user-friendly interface and extensive documentation, making it suitable for users with varying levels of technical expertise.
  • Real-time Data Processing
    It allows real-time data collection, analysis, and visualization, which can be beneficial for applications that require immediate feedback.
  • Integration with MATLAB
    Seamless integration with MATLAB allows users to leverage MATLAB's powerful data analysis and visualization tools for more advanced analysis.
  • API Support
    ThingSpeak provides RESTful APIs, making it easier to collect, store, and retrieve data from IoT devices and other sources.
  • Free Tier
    Offers a free tier for users to start with basic usage, which is useful for small projects or initial experimentation.
  • Community Support
    A broad community of users means more available resources such as tutorials, forums, and shared projects for learning and troubleshooting.

Possible disadvantages of ThingSpeak

  • Limited Free Tier
    The free version has limitations on the number of channels and data storage, which might not be sufficient for larger projects.
  • Dependence on Internet
    Requires a constant internet connection to transmit data to the cloud, which could be a drawback in remote or unstable network environments.
  • Data Privacy
    As a cloud-based service, data control and privacy can be concerns, especially for sensitive or proprietary information.
  • Limited Advanced Features
    Advanced data analytics features are relatively basic compared to more comprehensive IoT platforms, which might limit its use for more complex requirements.
  • Cost for Pro Features
    To access more advanced features and larger data capacities, a paid plan is required, which may not be cost-effective for all users.
  • Latency
    For applications requiring ultra-low latency, using a cloud service can introduce delays that might be unacceptable.

Analysis of Pandas

Overall verdict

  • Pandas is highly recommended for tasks involving data manipulation and analysis, especially for those working with tabular data. Its efficiency and ease of use make it a staple in the data science toolkit.

Why this product is good

  • Pandas is widely considered a good library for data manipulation and analysis due to its powerful data structures, like DataFrames and Series, which make it easy to work with structured data. It provides a wide array of functions for data cleaning, transformation, and aggregation, which are essential tasks in data analysis. Furthermore, Pandas seamlessly integrates with other libraries in the Python ecosystem, making it a versatile tool for data scientists and analysts. Its extensive documentation and strong community support also contribute to its reputation as a reliable tool for data analysis tasks.

Recommended for

    Pandas is particularly recommended for data scientists, analysts, and engineers who need to perform data cleaning, transformation, and analysis as part of their work. It is also suitable for academics and researchers dealing with data in various formats and needing powerful tools for their data-driven research.

Analysis of ThingSpeak

Overall verdict

  • Whether ThingSpeak is 'good' largely depends on user needs and project requirements. It is considered a good choice for those who require a straightforward, robust platform for IoT projects and appreciate its integration with MATLAB. However, users with very advanced or custom requirements might find its features limiting compared to other more extensive IoT platforms.

Why this product is good

  • ThingSpeak is a popular IoT (Internet of Things) platform that allows users to collect, visualize, and analyze live data streams from devices or sensors over the internet. It is favored for its ease of use, integration capabilities, and support for MATLAB analytics, which provides advanced data analysis and visualization tools. It is also compatible with various hardware platforms like Arduino, Raspberry Pi, and more, making it accessible for both hobbyists and professionals.

Recommended for

  • Students and educators looking to learn and teach IoT concepts
  • Hobbyists interested in creating simple IoT projects
  • Developers seeking an easy-to-use platform for quick prototyping
  • Professionals who require MATLAB's analytical features for data analysis
  • Organizations looking for reliable data logging and visualization solutions

Pandas videos

+ Add

Ozzy Man Reviews: Pandas

More videos:

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

ThingSpeak videos

+ Add

How to Analyze IoT Data in ThingSpeak

More videos:

  • Review - Review Higrow Board ESP32 and Aplication on Thingspeak #IoT #ESP32
  • Tutorial - How to Use ThingSpeak with Arduino

Category Popularity

0-100% (relative to Pandas and ThingSpeak)

Pandas

ThingSpeak

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Data Dashboard
33 33%
Data Dashboard
67% 67
Data Science Tools
100 100%
Data Science Tools
0% 0
IoT Platform
0 0%
IoT Platform
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 ThingSpeak

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

ThingSpeak Reviews

Best IoT Platforms in 2022 for Small Business
ThingSpeak is an IoT platform that uses channels to store data sent from apps or devices. A special feature of ThingSpeak is that you can create your own channel to collect the analyzed data hence giving a great level of flexibility to the users. You can also collect the data from the public (for example, ThingSpeak channel 12397 – Weather Station) and configure to write...
Source: www.fogwing.io
Open Source Internet of Things (IoT) Platforms
Known as the cloud IoT platform with MATLAB analytics, ThingSpeak allows you to aggregate, analyze, and visualize live data streams. IoT devices send their live data directly to ThingSpeak. From there, you create instant visualizations and can send alerts using web services. Essentially, however, you write and execute MATLAB code to do your data preparation, visualization...
Source: jansutris10.medium.com
14 of the Best IoT Platforms to Watch in 2021
ThingSpeak is a 100% analytics platform which supports advanced developer applications in environmental monitoring, energy, and smart farming. All the analysis is done on Matlab, and you can utilize the data insights for really cool stuff. For example, connecting an IoT device to Twitter and sending alerts. The best part is that using data for a certain interval is free....
Source: www.iottechtrends.com

Social recommendations and mentions

Based on our record, Pandas seems to be a lot more popular than ThingSpeak. While we know about 219 links to Pandas, we've tracked only 9 mentions of ThingSpeak. 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 / about 2 months 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 / 2 months 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 / 2 months 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 / 4 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 / 10 months ago
View more

ThingSpeak mentions (9)

  • Kotlin/ Thingspeak Interfacing.
    First of all, you need to ask yourself how familiar you are with MatLab. Then from a dev point of view, could you use an API to reference cloud data then apply analytics. Great intro to IoT. I can see that company going far in 5-10 and may invest based on trajectory. Https://thingspeak.com. Source: almost 2 years ago
  • Google sheets and esp32
    You can use solutions like thingspeak https://thingspeak.com/. Source: over 2 years ago
  • Help me check my circuit for my self-sustaining water meter
    I'm not sure yet. Maybe something custom, but probably not. I was thinking about Thingspeak before. Source: over 2 years ago
  • Displaying readings to website?
    I haven't got around to MQTT yet, but as an easy interim solution I recommend ThingSpeak https://thingspeak.com/ as you can set up an account for free and getting an ESP to send data to it is trivial. Plus you can access it via the web, or embed their graphs and dials into a webpage. The graphics are a bit meh though. Source: over 2 years ago
  • i have an idea for a database+arduino+matlab, i need some help plz
    ThingSpeak for IoT Projects Data collection in the cloud with advanced data analysis using MATLAB Https://thingspeak.com/. Source: over 2 years ago
View more

What are some alternatives?

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

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

AWS IoT - Easily and securely connect devices to the cloud.

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

Blynk.io - We make internet of things simple

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

Azure IoT Hub - Manage billions of IoT devices with Azure IoT Hub, a cloud platform that lets you easily connect, monitor, provision, and configure IoT devices.

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