Pandas is an open-source popular python data analysis library which provides high-performance data manipulation and analysis using its powerful data structures. The DataFrame is one of these structures.
Python with Pandas is used in a wide range of fields such as finance, economics, Statistics, analytics, etc.
Features of pandas :
- handling of data : It provides a really fast and efficient way to manage and explore data using dataframe and manipulate it efficiently.
- Deals with missing data : Pandas handles the missing values properly so it will not affect our study results.
- Cleaning the data : Data is really messy, and to get it ready for analysis over such data, We clean our data for the accurate result, and Pandas has that feature.
- It support multiples file format : Data can be in any format such as JSON, CSV,Excel, HDF5, XML, HTML, Imageas and this make python best among all other libraries.
- Visualization : Pandas have an in-built feature to plot your data and see the various kinds of visualization.
- Merging of datasets : Pandas helps to merge various datasets efficiently so that we can perform our manipulation on data without any problems and analyze the data.
- Pandas Supports : Pandas easily collaborate with other python package such as numpy and matplolib.
Python doesn't come with Pandas Package . Pandas built top of numpy. Before go with pandas make sure numpy is already install. To install numpy use follwing command.
pip install numpy
Afte installing the numpy, Now install the pandas using following command.
pip install pandas
Note : If you install Anaconda Python Library, Pandas will be installed by default.