Data Filtering
Data Science
| Beginner
- 11 videos | 56m 52s
- Includes Assessment
- Earns a Badge
Once data is gathered for data science, it is often in an unstructured or raw format and must be filtered for content and validity. Explore examples of practical tools and techniques for data filtering.
WHAT YOU WILL LEARN
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Identify common filtering techniques and toolsExtract date elements from common date formatsParse content types in http headersUse csvcut to filter csv dataUse sed to replace values in a text data streamDrop duplicate records from data
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Extract headers from a jpeg imageUse pdfgrep to extract data from searchable pdf filesDetect invalid or impossible data combinationsParse robots.txt from a web site to decide what should and shouldn't be crawled nor indexedDrop records from a csv file based on date range
IN THIS COURSE
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3m 24sIn this video, you will identify common filtering techniques and tools. FREE ACCESS
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6m 7sFind out how to extract date elements from common date formats. FREE ACCESS
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5m 11sIn this video, learn how to interpret content types in HTTP headers. FREE ACCESS
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4m 52sIn this video, you will learn how to use csvcut to filter out CSV data. FREE ACCESS
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6m 16sIn this video, you will use sed to replace values in a text data stream. FREE ACCESS
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4m 44sIn this video, you will learn how to drop duplicate records from data. FREE ACCESS
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6m 49sIn this video, you will learn how to extract headers from a jpeg image. FREE ACCESS
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4m 55sIn this video, find out how to use pdfgrep to extract data from searchable PDF files. FREE ACCESS
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5m 51sDuring this video, you will learn how to detect invalid or impossible data combinations. FREE ACCESS
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3m 21sFind out how to parse robots.txt from a web site to decide what should and shouldn't be crawled or indexed. FREE ACCESS
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5m 22sIn this video, you will learn how to drop records from a CSV file based on a date range. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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