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Pandas VS Exist

Compare Pandas VS Exist and see what are their differences

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Pandas logo Pandas

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

Exist logo Exist

Track everything in one place, understand your life.
  • Pandas Landing page
    Landing page //
    2023-05-12
  • Exist Landing page
    Landing page //
    2022-07-19

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.

Exist features and specs

  • Comprehensive Data Integration
    Exist integrates data from various services such as fitness trackers, social media, sleep monitors, and more, allowing for a wide range of data collection and analysis.
  • Personal Insights
    It provides personalized insights and correlations based on the data collected, helping users to better understand their habits and improve their lifestyle.
  • Custom Tracking
    Users can create custom tags to track specific activities or behaviors that are important to them, offering a high degree of personalization.
  • API Access
    Exist offers an API, enabling users to create custom integrations and extend the platform's functionality.
  • Mobile App Availability
    Exist is available as a mobile app, making it easy for users to input and check their data on the go.

Possible disadvantages of Exist

  • Subscription Cost
    Exist requires a paid subscription after the initial trial period, which may be a barrier for some users.
  • Privacy Concerns
    Collecting and integrating a wide range of personal data can raise privacy concerns, especially if the service is ever compromised.
  • Data Overload
    The sheer amount of data available can be overwhelming for some users, making it challenging to identify the most relevant insights.
  • Learning Curve
    New users may face a learning curve as they try to navigate the platform and make the best use of its features.
  • Limited Free Features
    The free version offers limited functionality, which may not be sufficient for users looking to fully explore the platform before committing to a subscription.

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.

Pandas videos

Ozzy Man Reviews: Pandas

More videos:

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

Exist videos

Exist - Board Game Review

More videos:

  • Review - Exist Review
  • Review - Daiwa Exist Spinning Reel [Review & Unboxing]

Category Popularity

0-100% (relative to Pandas and Exist)
Data Science And Machine Learning
Habit Building
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Productivity
0 0%
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 Exist

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

Exist Reviews

We have no reviews of Exist yet.
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Social recommendations and mentions

Based on our record, Pandas should be more popular than Exist. 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 / 29 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 / about 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 / about 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 / 9 months ago
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Exist mentions (43)

  • Apple courier may have stolen 2 MacBooks, () Apple is not going to help
    As someone who has been on and off the Degoogle train (I ran full LineageOS without Google Play at one point) and is now pretty deep in iOS territory, I'd say the main thing for me has been email. I've used https://www.fastmail.com for a great deal of years now, which is also home to my calendar as well so there's nothing much of value tied to my Google account. YouTube subscriptions would be annoying to lose but... - Source: Hacker News / 7 months ago
  • Ask HN: Tell us about your project that's not done yet but you want feedback on
    You may want to look into https://exist.io/. It's a very indie developer duo out of Australia (IIRC). And also IIRC they were looking for a buyer on Twitter some time ago. - Source: Hacker News / almost 2 years ago
  • Ask HN: Anyone using or working on a life dashboard?
    I have used this previously when tracking health metrics and I couldn't much else that had integrations. https://exist.io/. - Source: Hacker News / almost 2 years ago
  • Tracking Apps
    Hey guys, thinking of tracking wellness metrics such as sleep water intake etc to a dashboard/app. The main tools I have found are Exist.io, Gyrosco.pe, and conjure.so. For those of you who have tried them I would love to know what are the pros and cons with each one? Or if you have any better ones any help is greatly appreciated! Source: almost 2 years ago
  • Best apps to use
    Hey guys, thinking of transporting my quantified self journey to a dashboard/app. The main tools I have found are Exist.io, Gyrosco.pe, and conjure.so. For those of you who have tried them I would love to know what are the pros and cons with each one? Source: almost 2 years ago
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What are some alternatives?

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

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

Gyroscope - Gyroscope is a personalized dashboard for tracking your life.

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

Habitica - Habitica is a free habit building and productivity application.

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

HabitBull - HabitBull