Data Filtering
Data Science
11 Videos | 1h 1m 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 tools
extract date elements from common date formats
parse content types in HTTP headers
use csvcut to filter CSV data
use sed to replace values in a text data stream
drop duplicate records from data -
extract headers from a jpeg image
use pdfgrep to extract data from searchable pdf files
detect invalid or impossible data combinations
parse robots.txt from a web site to decide what should and shouldn't be crawled nor indexed
drop records from a CSV file based on date range
IN THIS COURSE
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1.Data Filtering Techniques and Tools3m 24sUP NEXT
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2.Processing Date Formats6m 7s
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3.Filtering HTTP Headers5m 11s
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4.Filtering CSV Data4m 52s
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5.Replacing Values with sed6m 16s
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6.Dropping Duplicate Data4m 44s
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7.Working with JPEG Headers6m 49s
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8.Filtering PDF Files4m 55s
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9.Filtering for Invalid Data5m 51s
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10.Exercise: Cull Old Data3m 21s
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11.Parsing robots.txt5m 22s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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