![]() Powerful, flexible group by functionality to perform.Ignore the labels and let Series, DataFrame, etc. Automatic and explicit data alignment: objects canīe explicitly aligned to a set of labels, or the user can simply.Size mutability: columns can be inserted andĭeleted from DataFrame and higher dimensional.NaN, NA, or NaT) in floating point as well as non-floating point data Easy handling of missing data (represented as.Here are just a few of the things that pandas does well: The broader goal of becoming the most powerful and flexible open source dataĪnalysis / manipulation tool available in any language. It aims to be the fundamental high-level building block forĭoing practical, real world data analysis in Python. Structures designed to make working with "relational" or "labeled" data bothĮasy and intuitive. Pandas is a Python package that provides fast, flexible, and expressive data It uses.Pandas: powerful Python data analysis toolkit The Pallets organization develops and supports Flask and the libraries * Running on (Press CTRL+C to quit) Contributingįor guidance on setting up a development environment and how to make aĬontribution to Flask, see the contributing guidelines. ![]() ![]() route ( "/" ) def hello (): return "Hello, World!" $ flask run Install and update using pip: $ pip install -U Flask A Simple Example # save this as app.py from flask import Flask app = Flask ( _name_ ). There are many extensions provided by theĬommunity that make adding new functionality easy. ![]() It is up to the developer to choose the tools and It began as a simple wrapper around WerkzeugĪnd Jinja and has become one of the most popular Python webįlask offers suggestions, but doesn’t enforce any dependencies or To make getting started quick and easy, with the ability to scale up toĬomplex applications. Flask is a lightweight WSGI web application framework. ![]()
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