pandas python Reviews & Product Details

At the heart of the Pandas library is the data frame, which makes using the Pandas framework interoperable from a skills-building standpoint. Not only will learning the methods in Pandas be valuable within Python, but you can quickly transfer your knowledge of the framework to R or even Spark (for big data applications). Further, the framework itself implemented in Python is beneficial for data analysis, providing numerous helper functions on the data frame object, that include aggregation methods, standard statistical calculation methods, and handy join/merge, and subsetting functionality that all data analysts will likely use. On top of that, it is built on top of Numpy for easy transference between those types for more heavy-duty/actual work or even pushing it up to a higher level of abstraction for more data-viz/communications/analysis work. Review collected by and hosted on G2.com.

There's not much to dislike, except perhaps memory and some run-time constraints. By adding a lot of 'extra' structure on top of the NumPy array, the data frame isn't the most efficient data type, but what you get is worth the extra resources needed to run it, though maybe not at extreme scale (several dozen gigs or more than a couple million rows depending on how many columns of data is included in your frame). Review collected by and hosted on G2.com.

The best thing about pandas library in python is, it provides vast functionality to manipulate the data in all the angle. It processes the CSV files with great speed. it provide the facility to process all kind of data, either from file, json file, from databases etc. Review collected by and hosted on G2.com.

What I not like about pandas is on the large dataset, it occupies a lot of memory, and because of that, it hangs the system due to full memory error. Review collected by and hosted on G2.com.

An excellent python module that can be used for data analysis. It can be easily manipulated by converting the data into a table structure very easily. It is installed with matplotlib. It supports many different file types. Excel, CSV, Pickle.. It is very ideal for processing rows and columns, expanding data, data sorting, filtering, label-based classification, data cleaning. Review collected by and hosted on G2.com.

I can't find the letter "i" by filtering after reducing the "i" character with lower. So I fix my data first and then load it into the data frame. Review collected by and hosted on G2.com.

Pandas makes it easy to manipulate data in data frames. Review collected by and hosted on G2.com.

Sometimes the options and features available can be limited. Review collected by and hosted on G2.com.

The features of this library to handle the data if fabulous and with easy function read and write the data and also searching is also good in the data frame converted by panda. Review collected by and hosted on G2.com.

The speed of all operations is a bit slower and with millions o data reading this took lots of time but with the Modin package, we can increase the operational speeds by 3 times. Review collected by and hosted on G2.com.

The best thing i like about Pandas is how fast and easily it handles huge set of Data in and organize it according to our need. also coding in panda is very fast, I can do a lot of work in very little time. Review collected by and hosted on G2.com.

there is not much to dislike about pandas except it has a very complex syntax. and it is a little difficult to learn for beginners. Review collected by and hosted on G2.com.

Ready optimized implementations for basic statistical calculations like central tendancy measures and quantiles. Review collected by and hosted on G2.com.

Though the library is excellent, it is still not optimized enough to be used on big data. Review collected by and hosted on G2.com.

the way that pandas work with datas, and organize them Review collected by and hosted on G2.com.

I dislike the way that you need put on python script Review collected by and hosted on G2.com.

It makes it easy to work with large datasets. Review collected by and hosted on G2.com.

The pandas package is a different ecosystem from vanilla Python. It takes some investment to learn and make full use of it. Review collected by and hosted on G2.com.

I found an easy way to manage my data, just writing few lines of code. Review collected by and hosted on G2.com.

I don't like the way how I can develop graphs, should be more attractive like seaborn. Review collected by and hosted on G2.com.