pandas python Pros and Cons

Usability and Graphical representation of various data sets Review collected by and hosted on G2.com.

Nothing much to dislike about, It's still developing hoping to mature enough to be the best Review collected by and hosted on G2.com.

It is easy to understand. It is perfect for small-sized data manipulation. Review collected by and hosted on G2.com.

It tends to be slower as the size of the data increases. Review collected by and hosted on G2.com.

It has multiple functions for dataset processing Review collected by and hosted on G2.com.

Syntax keeps changing with updates, so that causes some confusion sometimes Review collected by and hosted on G2.com.

Pandas python is very powerful library in python,Pandas has incredible features like data analysis for file's like CSV file , Excel file, json file, dollar file, .text file etc it will convert all file types into dataframe and you can do easily operation on this dataframe. Review collected by and hosted on G2.com.

I'm using pandas since 1 year and no dislike about pandas because it is very powerful library.but i want to say pandas only visualise the data into dataframe if we want to visualise the data then we need to use another library for this,but rather than pandas is very great Library Review collected by and hosted on G2.com.

- Ease of use

- Ease of Implementation

- Ease of Integration

- Versatility

- Updated library Review collected by and hosted on G2.com.

There is no dislikes that I can think of. Review collected by and hosted on G2.com.

DataFrames in Pandas are useful to handle and analyse data very efficiently. Also pandas provides built-in methods to filter and sort data, handle missing data. Pandas allows/supports reading data from excel, CSV fil e etc which is another advantage. Review collected by and hosted on G2.com.

Pandas has few weak areas. When large datasets are provided as inputs, Pandas encounter performance issues as interacting over large DataFrames and performing operations on them is time consuming. Review collected by and hosted on G2.com.

Pandas in Python have the ability to handle and manipulate large datasets with ease. It provides a rich set of functions and methods that make data cleaning, transformation, and analysis efficient and intuitive. Review collected by and hosted on G2.com.

Pandas work slowly for very large datasets, pandas data frames are mutable which means that can be changed anytime, this can be advantageous but can be confusing or wont work well if not handled properly Review collected by and hosted on G2.com.

Pandas is widely used for data manipulation and data analysis. We can read datasets files such as CSV, Excel and process those files. Panda has tabular data structures like dataframes, series. It has more functions for manipulation of data. Empty records are handled properly. Review collected by and hosted on G2.com.

Pandas consume more memory when working with larger datasets. That's why there are performance limitations. It is dependent on external libraries. Support and performance should be improved. Review collected by and hosted on G2.com.

Pandas can structure our data with a variety of extensions like pandas support html, xlsx,CSV extension etc. with pandas, we can also manipulate our data and analyze them Review collected by and hosted on G2.com.

Pandas has to work on their support center because some of problems are not solved in any other tools, like pandas os error Review collected by and hosted on G2.com.

-very flexyble

-a lot of support (community, chat, tutorial, courses,...)

-a great community at support to develop the library

-huge amount of projects, companies and people using it Review collected by and hosted on G2.com.

-very complex syntax, unnecessary

-very slow, great lack of performances

-great issues when using dataframes that does not fit in memory

-new versions does not guarantee that code developed with previous versions will work properly Review collected by and hosted on G2.com.