Pandas Data frame for Python data analysis
What is Pandas DataFrame?
Pandas, as we might already know, is a library for Python data analysis. It enables Python to process spreadsheet data with fast loading and it also gives Python the power to manipulate, align and merge functionality along with others. Pandas have introduced two new types of data to Python one is Series and the other is DataFrame to give it the edge. DataFrame allows you to represent the whole data or spreadsheet which is a rectangular type of data and series, on the other hand, represents a single column of the DataFrame. You could imagine Pandas DataFrame as a dictionary or a collection of series data.
Why should one use Pandas DataFrame when working with a programming language like Python?
There is no doubt that Python is a wonderful language for data analysis mainly because it has specific data-focused packages. Pandas is one those packages and has made analysing and importing data much easier than other packages. Pandas provide you with the fast, flexible and expressive structure of data which is designed to work perfectly and intuitively with “relational” or “labelled” data. Pandas are aiming to be the basic block for doing high-level, practical and real-world data analysis in Python. Pandas have built its packages on NumPy and Matplolib to provide a single, convenient tool to work with most of your data analysis visually.
Why should someone use a programming language like Python and a data analysis tool like Pandas in the first place?
The simple answer is that it gives you the advantage of reproducible and automation. If you need to perform a particular set of analysis on more than one sets of data or repetitively then a programming language like Python has the ability to automate this analysis on those multiple data sets. There are programming languages available with their own macro functionality but users are reluctant to use this. Another important factor is that not all spreadsheet programs could be used in all operating systems. When a user performs data analysis using a programming language it forces him/her to keep a running record of all the steps of analysis performed on the data sets. Spreadsheet programmes are not to be criticized but while there are programming languages like Python available on the market then it just makes sense to use this for better efficiency and speed.
Pandas DataFrame gives you the advantage of –
- do programming with ease
- takes minimum time to develop and for code maintenance
- working with the modular and object-oriented framework
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