Is much of your time spent doing tedious tasks such as cleaning dirty data, accounting for lost data, and preparing data to be used by others? If so, then having the right tools makes a critical difference, and will be a great investment as you grow your data science expertise.
The book starts by highlighting the importance of data cleaning in data science, and will show you how to reap rewards from reforming your cleaning process. Next, you will cement your knowledge of the basic concepts that the rest of the book relies on: file formats, data types, and character encodings. You will also learn how to extract and clean data stored in RDBMS, web files, and PDF documents, through practical examples.
At the end of the book, you will be given a chance to tackle a couple of real-world projects.
|Course Length||8 hours 9 minutes|
|Date Of Publication||24 May 2015|
|Step one – download and examine Sentiment140|
|Step two – clean for database import|
|Step three – import the data into MySQL in a single table|
|Step four – clean the & character|
|Step five – clean other mystery characters|
|Step seven – separate user mentions, hashtags, and URLs|
|Step eight – cleaning for lookup tables|