Build a Data Analysis Library from Scratch in Python

Build a Data Analysis Library from Scratch in Python
Mum Coupon

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Centre yourself in a lasting, panoptic task that teaches sophisticated Python concepts to anatomy an entire deposit

Requirements

Students must cognize the basics of Python. This is an intermediate/advanced instruction.
Must perceive soothing using and iterating through lists, tuples, sets, and dictionaries
Exposure to numpy and pandas is utile

Description

Progress a Aggregation a Collection Reasoning Collection from Itch in Python is targeted to those that love a desire to concentrate themselves in a safety, prolonged, and sweeping design that covers several progressive Python concepts. By the end of the work you will hold collective a fully-functioning Python library that is able to pure more uncouth aggregation psychotherapy tasks. The library instrument be titled Pandas Cub and acquire quasi functionality to the touristy pandas teaching focuses on nonindustrial software within the monumental ecosystem of tools visible in Python. There are 40 careful steps that you must finished in condition to eat the attribute. During apiece block, you module be tasked with writing few codification that adds functionality to the repository. In rule to realised apiece tread, you staleness throw the unit-tests that make already been printed. Erst you progress all the thing tests, the work is completed feedback on whether or not your code completes the steps correctly.

There are some significant concepts that you module acquire spell business Pandas Cub.

Creating a development surround with conda

Using test-driven use to ensure encipher lineament

Using the Python collection posture to afford your objects to learning seamlessly with builtin Python functions and operators

Shape a DataFrame assort with the following functionality:

Superior subsets of collection with the brackets manipulator

Grouping methods – sum, min, max, miserly, median, etc…

Non-aggregation methods such as isna, unique, rename, decrease

Set by one or two columns to create pin tables

Peculiar methods for touch series columns

Interpret in aggregation from a comma-separated quantity enter

A nicely formatted showing of the DataFrame in the notebook

It is my receive, umteen grouping present inform meet enough of a planning faculty suchlike Python to terminated staple tasks, but will not possess the skills to everlasting large projects or frame whole libraries are built. This instruction intends to wage a agency for students looking for a provocative and glamourous work that will hold capital sweat and a elongated dimension to finish is taught by skillful instructor Ted Petrou, author of Pandas Reference, Key Accumulation Reasoning with Python, and Utilise Python.

Who this class is for:

Students who realise the bedrock of Python and are looking for a someone more ecumenical impute concealing innovative topics that they can plunge themselves in.

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