Python for Data Analysis: Step-By-Step with Projects - Cleaning Text

Python for Data Analysis: Step-By-Step with Projects - Cleaning Text

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Hard

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This video tutorial covers methods for cleaning and standardizing tax data, focusing on address data in a dataset of New York taxi rides. It demonstrates using pandas for string processing, including converting text to lowercase, removing whitespace, and analyzing text lengths. The tutorial also introduces string indexing, slicing, and regular expressions for more advanced text manipulation.

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4 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

How can we filter addresses that contain the keyword 'airport'?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

Describe the process of replacing 'NY' with 'New York' in the address column.

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the purpose of using the 'startswith' and 'endswith' methods in string manipulation?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

What are regular expressions and how can they be used in data cleaning?

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