Pandas Concepts: Difference between revisions
(→Series) |
No edit summary |
||
Line 11: | Line 11: | ||
=Series= | =Series= | ||
{{Internal| | {{Internal|Pandas_Series|Series}} | ||
=Axis= | =Axis= | ||
Line 23: | Line 23: | ||
Reported as <code> datetime64[ns]</code>. What is this? | Reported as <code> datetime64[ns]</code>. What is this? | ||
Also see {{Internal| | Also see {{Internal|Pandas_Series#Create_a_Time_Series_from_CSV|Create a Time Series from CSV}} | ||
</font> | </font> |
Revision as of 18:35, 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
Axis
Both DataFrames and Series use the concept of axis. Formally define. By default, an axis comprises of monotonically increasing integers with step 1, from 0 to length - 1
Data Types
String
Datetime
TO PROCESS: https://pandas.pydata.org/docs/reference/api/pandas.Timestamp.html#pandas.Timestamp
Reported as datetime64[ns]
. What is this?
Also see