--- title: pandas python Reviews meta_title: 'pandas python Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 99 reviews by the users' company size, role or industry to find out how pandas python works for a business like yours. aggregate_rating: rating_value: 4.6 review_count: 99 scale: '5' date_modified: '2026-08-02' parent_category: name: Development url: https://www.g2.com/categories/development --- # pandas python Reviews **Vendor:** pandas python **Category:** [Component Libraries Software](https://www.g2.com/categories/component-libraries) **Average Rating:** 4.6/5.0 **Total Reviews:** 99 ## About pandas python Pandas is a powerful and flexible open-source Python library designed for data analysis and manipulation. It provides fast, efficient, and intuitive data structures, such as DataFrame and Series, which simplify handling structured (tabular, multidimensional, potentially heterogeneous) and time series data. Pandas aims to be the fundamental high-level building block for practical, real-world data analysis in Python, offering a wide range of functionalities to streamline data processing tasks. Key Features and Functionality: - Handling Missing Data: Pandas offers easy handling of missing data, represented as `NaN`, `NA`, or `NaT`, in both floating point and non-floating point data. - Size Mutability: Columns can be inserted and deleted from DataFrame and higher-dimensional objects, allowing for dynamic data manipulation. - Data Alignment: Automatic and explicit data alignment ensures that objects can be aligned to a set of labels, facilitating accurate computations. - Group By Operations: Powerful and flexible group by functionality enables split-apply-combine operations on datasets for both aggregating and transforming data. - Data Conversion: Simplifies converting differently-indexed data in other Python and NumPy data structures into DataFrame objects. - Indexing and Subsetting: Provides intelligent label-based slicing, fancy indexing, and subsetting of large datasets. - Merging and Joining: Facilitates intuitive merging and joining of datasets. - Reshaping and Pivoting: Offers flexible reshaping and pivoting of datasets. - Hierarchical Labeling: Supports hierarchical labeling of axes, allowing multiple labels per tick. - Robust I/O Tools: Includes robust tools for loading data from flat files (CSV and delimited), Excel files, databases, and saving/loading data from the ultrafast HDF5 format. - Time Series Functionality: Provides time series-specific functionality, including date range generation, frequency conversion, moving window statistics, and date shifting and lagging. Primary Value and User Solutions: Pandas addresses the challenges of data analysis by offering a comprehensive suite of tools that simplify the process of data manipulation, cleaning, and analysis. Its intuitive data structures and functions allow users to perform complex operations with minimal code, enhancing productivity and enabling efficient handling of large datasets. By providing seamless integration with other Python libraries and tools, Pandas serves as a cornerstone for data science workflows, empowering users to extract insights and make data-driven decisions effectively. ## pandas python Pros & Cons **What users like:** - Users value the **ease of data management** in pandas, simplifying analysis and visualization tasks daily. (2 reviews) - Users find **pandas easy to use** , benefiting from intuitive syntax and seamless integration for data analysis tasks. (2 reviews) - Users appreciate the **easy integrations** of pandas, making it essential for seamless data analysis and visualization tasks. (2 reviews) - Users appreciate the **coding efficiency** of pandas, finding its syntax easy and integration with structured data seamless. (1 reviews) - Users appreciate the **high design quality** of pandas Python, enabling effective usability and visualization of data sets. (1 reviews) - Users appreciate the **intuitive and powerful data manipulation** of pandas, enabling efficient operations in just a few lines. (1 reviews) - Features (1 reviews) - Installation Ease (1 reviews) - Integrations (1 reviews) - Time-saving (1 reviews) **What users dislike:** - Users experience **performance issues** with pandas, noting slow operation and high memory consumption on large datasets. (2 reviews) - Users find the **complex installation** of pandas Python to be time-consuming and challenging to implement effectively. (1 reviews) - Users often find the **difficulty** in handling large datasets and the steep learning curve frustrating. (1 reviews) - Users often face **integration issues** with pandas, especially when attempting to connect it efficiently to various data sources. (1 reviews) ## pandas python Reviews ### 1. Pandas Makes Structured Data Work Fast, Practical, and Readable **Rating:** 4.0/5.0 stars **Reviewed by:** Zharina F. | Data Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** April 12, 2026 **What do you like best about pandas python?** We need pandas because it makes working with structured data in Python practical, fast, and readable. Without pandas, most real‑world data tasks would be slow, error‑prone, and much more code‑heavy. **What do you dislike about pandas python?** Need some time and practice to intergrate **What problems is pandas python solving and how is that benefiting you?** ETL development Reading and cleaning data ### 2. Excellent Python Library for Data Manipulation **Rating:** 4.0/5.0 stars **Reviewed by:** ROSHAN S. | Small-Business (50 or fewer emp.) **Reviewed Date:** February 11, 2024 **What do you like best about pandas python?** It is easy to understand. It is perfect for small-sized data manipulation. **What do you dislike about pandas python?** It tends to be slower as the size of the data increases. **What problems is pandas python solving and how is that benefiting you?** I am using pandas to manipulate tabular data. It makes it easier to view the tabular data, and manipulate it how you see fit. I am performing data transformation using pandas in some of my ETL projects. ### 3. Manipulating data with pandas **Rating:** 4.0/5.0 stars **Reviewed by:** Pablo S. | Data Science Fellow, Small-Business (50 or fewer emp.) **Reviewed Date:** July 28, 2019 **What do you like best about pandas python?** Pandas makes it easy to manipulate data in data frames. **What do you dislike about pandas python?** Sometimes the options and features available can be limited. **Recommendations to others considering pandas python:** Works great with Jupiter notebook **What problems is pandas python solving and how is that benefiting you?** Viewing data trends and being able to make changes and manipulation to large datasets quickly. ### 4. Pandas **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Banking | Enterprise (> 1000 emp.) **Reviewed Date:** October 20, 2021 **What do you like best about pandas python?** For doing mathematical operations Analysis purpose **What do you dislike about pandas python?** Lack of more inbuilt functions. Better documentation in detai **Recommendations to others considering pandas python:** Easy to use, well updated library. **What problems is pandas python solving and how is that benefiting you?** Calculations Data analysis Data exporting and importing ### 5. Its ease of integration with the rest of my applications created in python is very practical **Rating:** 4.0/5.0 stars **Reviewed by:** Bpagadala P. | Small-Business (50 or fewer emp.) **Reviewed Date:** November 29, 2020 **What do you like best about pandas python?** Its ease of installation and integration with the rest of my applications created in python is something quite useful and practical, the fact that it allows me to perform data analysis in a much simpler, more precise and secure way is something that ultimately gives it A great plus to my developments, the fact that it supports a multiple number of files and files is something of great utility when I have the data in different file formats, so since it does not have exclusive use of a single format the data entry It can be much more comprehensive, its ease of use and implementation is so simple that even people who are not experts in data analysis can perform this type of task without any problem, the precision of the results is something really surprising and in fact allow making valuable decisions within the company. **What do you dislike about pandas python?** Its learning curve can be a bit slow at first, but nevertheless after you get used to using the application you realize that everything is really simple, easy and fast, sometimes it would get stuck, although I'm not sure if it was because of the application itself or because of my processor. **What problems is pandas python solving and how is that benefiting you?** It has been a very helpful option when I want to implement statistical data analysis options to my python developments in a much simpler and more precise way, which allows me to extend the type in a much simpler and more practical way of applications that I usually develop, allowing me to expand my professional services to another level. ### 6. Definitely a learning curve, but worth it if time **Rating:** 4.0/5.0 stars **Reviewed by:** Chloe' H. | Graduate Research Assistant, Small-Business (50 or fewer emp.) **Reviewed Date:** October 13, 2020 **What do you like best about pandas python?** This programming language has a learning curve for sure, but I really like that once you learn it, it’s pretty easy to remember. Pandas has a pretty simple language to write and code, but just like any other programming, you have to be careful about your language to get it to work properly. **What do you dislike about pandas python?** I dislike that it is hard to save my programming to a flash drive. I know it save son the internet but I do like a backup. **What problems is pandas python solving and how is that benefiting you?** It is so easy to run simulations with pandas because you can easily just run multiple simulations at one time that really help solve those questions. ### 7. Easy to use data import and analyzing tool **Rating:** 3.5/5.0 stars **Reviewed by:** Mehmed Buğrahan D. | Machine Learning Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** January 06, 2020 **What do you like best about pandas python?** Pandas is a great tool to visualize, import and analyze the data in many formats. Its support for different file formats and its self-explanatory commands makes it user-friendly even for an inexperienced user. Conversions from pandas dataframe to numpy arrays is also another great feature of Pandas since not all other python libraries have Pandas support. They have a really rich and useful documentation page. Its user base is huge compared to other similar libraries. Meaning you can find answer to your many questions. **What do you dislike about pandas python?** Pandas isn't great at memory handling. It imports all of the files even if you need just couple of rows from a file. It also doesn't support multiprocessing and its functions only runs on CPU, not GPU. Another thing that I don't like about Pandas is that its error messages. For instance, KeyError when it can't find the specified column in the dataframe. These kinds of errors must provide human-friendly errors instead of robotic messages like 'KeyError 'some_column'. **Recommendations to others considering pandas python:** I would highly recommend Pandas, especially for inexperienced users. It has a great documentation page and it is used by many people, meaning you can find answers to your many questions about the library. But keep in mind that its lack of support for multiprocessing makes it slower compared to some other libraries. **What problems is pandas python solving and how is that benefiting you?** I like to use Pandas in order to visualize and analyze the file before I do some memory heavy processes. This helps me to reduce the time by helping me to decide what I need to do beforehand. ### 8. Pandas **Rating:** 4.0/5.0 stars **Reviewed by:** abdal A. | Mid-Market (51-1000 emp.) **Reviewed Date:** January 22, 2020 **What do you like best about pandas python?** Pandas is easy use, can handle tabular data efficiently very fast. **What do you dislike about pandas python?** it is in memory operations so it takes more memory and needs high configuration for the operations **Recommendations to others considering pandas python:** pandas as very useful data transformations inbuilt which would to hours to code in other langauale **What problems is pandas python solving and how is that benefiting you?** i use pandas for performing various data operations during the data exploration stage ### 9. Pandas **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Telecommunications | Enterprise (> 1000 emp.) **Reviewed Date:** January 07, 2020 **What do you like best about pandas python?** Pandas requires less scripting as it as various inbuilt functions. It has an excellent ways for representating the data **What do you dislike about pandas python?** Pandas is very complex to learn and it has very poor documentation and very difficult syntax **Recommendations to others considering pandas python:** Pandas helps for the data analysis and data exploration **What problems is pandas python solving and how is that benefiting you?** Using Pandas we perform data analysis for the various machine learning algorithms ### 10. Great data science tool for advanced analytics **Rating:** 4.0/5.0 stars **Reviewed by:** Dorian N. | Data Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** June 28, 2019 **What do you like best about pandas python?** I like pandas library in python the best because it is a very easy way to load data and analyze large amounts of data in the programmatic environment. **What do you dislike about pandas python?** I dislike the pandas is an open source library and sometimes it is hard to understand the documentation that is written and available online. **What problems is pandas python solving and how is that benefiting you?** The problems I'm solving with pandas and Python is very. The first and main benefit is that I am able toTwo summary statistics on large amounts of data that previously would take a lot more time in other languages. ### 11. Library for data management and analytics in Python **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Internet | Mid-Market (51-1000 emp.) **Reviewed Date:** June 26, 2019 **What do you like best about pandas python?** I like pandas than most because it is a very easy to use library where I can quickly set up an analytic workflow and drive results from having very easy to use data structures. **What do you dislike about pandas python?** I dislike that the pandas is an open source tool that does not come with the most clear documentation. **What problems is pandas python solving and how is that benefiting you?** The problems I'm solving with pandas Is the need to drive large analytic workflows and gain summary statistics information from columnar data ### 12. The ultimate package for data manipulation **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Enterprise (> 1000 emp.) **Reviewed Date:** August 30, 2019 **What do you like best about pandas python?** The applicability, portability to other modules, extremely useful in data science applications **What do you dislike about pandas python?** Some operations are bit rigid. Flexibility options are few **What problems is pandas python solving and how is that benefiting you?** machine learning examples, trying to read from files. Benefits range from using data manipulation given a key-annotated data column ### 13. Good Package for Predictive Analytics parts in Python **Rating:** 4.0/5.0 stars **Reviewed by:** Nikhil G. | Part Time Trainer, Mid-Market (51-1000 emp.) **Reviewed Date:** January 27, 2019 **What do you like best about pandas python?** Best Package for Predicting the outcomes and Visualizing data , ease implementation of functions in python **What do you dislike about pandas python?** It lags in terms of accuracy where Programming Languages like R gives best result in terms of accuracy **Recommendations to others considering pandas python:** R Programming **What problems is pandas python solving and how is that benefiting you?** We have done Time Series Analysis on retail data set using pandas. ### 14. Pandas in Python **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in E-Learning | Small-Business (50 or fewer emp.) **Reviewed Date:** November 26, 2018 **What do you like best about pandas python?** Pandas library in python let's you work with your data in a data frame. It let's you play with the data and is an important library for data wrangling and data munging. **What do you dislike about pandas python?** It can only deal majorly with data frames. You'll have to import other libraries like numpy for any kind of arethmetic. However, it gets your basic work done. **What problems is pandas python solving and how is that benefiting you?** I've worked on many projects using pandas. It is almost in every Notebook and helps me clean my data in any project. ### 15. Easy to work with and fast! **Rating:** 4.0/5.0 stars **Reviewed by:** Morgan S. | Advisory Services - Consultant, Financial Services, Mid-Market (51-1000 emp.) **Reviewed Date:** September 19, 2018 **What do you like best about pandas python?** I like the flexibility in the use cases for my job. Many times I have to pivot and change on demand codes based on cross functional feedback. **What do you dislike about pandas python?** Color schemes that are more dark. Overall the product is great and we use it multiple times daily. **What problems is pandas python solving and how is that benefiting you?** This allows me to manipulated large data frames and run statistical analysis. This provides process improvement to talk a manual excel report into a few minutes of work. ### 16. Use python for API **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** February 22, 2019 **What do you like best about pandas python?** Simplicity and built in modules with many libraries **What do you dislike about pandas python?** Nothing as of now but may have more gui features **Recommendations to others considering pandas python:** Try it once **What problems is pandas python solving and how is that benefiting you?** Easy solutions for customers ### 17. Pandas in Python **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Education Management | Small-Business (50 or fewer emp.) **Reviewed Date:** October 31, 2018 **What do you like best about pandas python?** Pandas is a great module to work with in Python. It provides you with structures and data analysis tools for python programming. **What do you dislike about pandas python?** Only some specific commands can be run through this library. You need to import various different libraries to be able to use python properly. **What problems is pandas python solving and how is that benefiting you?** Pandas provides me with basic functions that I can execute with my data sets. It helps in cleaning, wrangling and munging the data. ### 18. Pandas **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Enterprise (> 1000 emp.) **Reviewed Date:** October 18, 2018 **What do you like best about pandas python?** Easy to use with large datasets in Python, easy to setup with Anaconda **What do you dislike about pandas python?** Pandas is very versatile, there is really nothing to "not like" about Pandas **What problems is pandas python solving and how is that benefiting you?** Streamline data analysis with large datasets. ## pandas python Discussions - [What is your experience with pandas for data analysis, and what features do you find most useful?](https://www.g2.com/discussions/what-is-your-experience-with-pandas-for-data-analysis-and-what-features-do-you-find-most-useful) - 1 comment, 1 upvote - [What is pandas python used for?](https://www.g2.com/discussions/what-is-pandas-python-used-for) - 1 comment - [View pandas python pricing details and edition comparison](https://www.g2.com/products/pandas-python/reviews?filters%5Bnps_score%5D%5B%5D=4§ion=pricing&secure%5Bexpires_at%5D=2026-08-03+21%3A09%3A28+-0500&secure%5Bsession_id%5D=de260ff4-7140-4593-b755-996a53721450&secure%5Btoken%5D=0734816a1d93c94f50381e505b3e101bf268a601ad32bd372808d55b4bcfcaa9&format=llm_user) ## pandas python Integrations - [PostgreSQL](https://www.g2.com/products/postgresql/reviews) - [Python](https://www.g2.com/products/python/reviews) - [PyTorch](https://www.g2.com/products/pytorch/reviews) - [Visual Studio](https://www.g2.com/products/visual-studio/reviews) ## pandas python Features **Functionality** - Language Contingency - Component Library - Unlocked Components **Management** - Framework Integration - Repository Management - Support ## Top pandas python Alternatives - [python xlrd](https://www.g2.com/products/python-xlrd/reviews) - 4.1/5.0 (20 reviews) - [Flutter](https://www.g2.com/products/flutter/reviews) - 4.6/5.0 (68 reviews) - [DevExpress](https://www.g2.com/products/devexpress/reviews) - 4.8/5.0 (112 reviews)