pandas forms a core component of the Python data analysis corpus. The distinguishing feature of pandas is that the suite of data structures that it provides is naturally suited to data analysis, primarily the DataFrame and, to a lesser extent, series (1-D vectors) and panel (3D tables).
Simply put, pandas and statstools can be described as Python's answer to R, the data analysis and statistical programming language that provides both data structures, such as R-dataframes, and a rich statistical library for data analysis.
The benefits of pandas compared to using a language such as Java, C, or C++ for data analysis are manifold:
- Data representation: It can easily represent data in a form that's naturally suited for data analysis via its DataFrame and series data structures in a concise manner. Doing the equivalent in Java/C/C++ requires many lines...
