Pandas Concepts: Difference between revisions
Jump to navigation
Jump to search
Line 5: | Line 5: | ||
<code>pandas</code> is a Python package that provides fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. | <code>pandas</code> is a Python package that provides fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. | ||
Pandas is built in top of [[Numpy]]. | Pandas is built in top of [[Numpy Concepts#Overview|Numpy]]. | ||
=<span id='Data_Frame'></span>DataFrame= | =<span id='Data_Frame'></span>DataFrame= |
Revision as of 18:17, 8 October 2023
Internal
Overview
pandas
is a Python package that provides fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language.
Pandas is built in top of Numpy.
DataFrame
Series
Data Types
String
Datetime
TO PROCESS: https://pandas.pydata.org/docs/reference/api/pandas.Timestamp.html#pandas.Timestamp
Also see