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The Data Wrangling Workshop
Whileahugeamountofdataisreadilyavailabletous,itisnotusefulinitsrawform.Fordatatobemeaningful,itmustbecuratedandrefined.Ifyou’reabeginner,thenTheDataWranglingWorkshopwillhelptobreakdowntheprocessforyou.You’llstartwiththebasicsandbuildyourknowledge,progressingfromthecoreaspectsbehinddatawrangling,tousingthemostpopulartoolsandtechniques.ThisbookstartsbyshowingyouhowtoworkwithdatastructuresusingPython.Throughexamplesandactivities,you’llunderstandwhyyoushouldstayawayfromtraditionalmethodsofdatacleaningusedinotherlanguagesandtakeadvantageofthespecializedpre-builtroutinesinPython.Later,you’lllearnhowtousethesamePythonbackendtoextractandtransformdatafromanarrayofsources,includingtheinternet,largedatabasevaults,andExcelfinancialtables.Tohelpyouprepareformorechallengingscenarios,thebookteachesyouhowtohandlemissingorincorrectdata,andreformatitbasedontherequirementsfromyourdownstreamanalyticstool.Bytheendofthisbook,youwillhavedevelopedasolidunderstandingofhowtoperformdatawranglingwithPython,andlearnedseveraltechniquesandbestpracticestoextract,clean,transform,andformatyourdataefficiently,fromadiversearrayofsources.
目錄(71章)
倒序
- 封面
- 版權(quán)信息
- Preface
- 1. Introduction to Data Wrangling with Python
- Introduction
- Importance of Data Wrangling
- Python for Data Wrangling
- Lists Sets Strings Tuples and Dictionaries
- List Functions
- Summary
- 2. Advanced Operations on Built-In Data Structures
- Introduction
- Advanced Data Structures
- Basic File Operations in Python
- Summary
- 3. Introduction to NumPy Pandas and Matplotlib
- Introduction
- NumPy Arrays
- Advanced Mathematical Operations
- Statistics and Visualization with NumPy and Pandas
- The Definition of Statistical Measures – Central Tendency and Spread
- Data Wrangling in Statistics and Visualization
- Summary
- 4. A Deep Dive into Data Wrangling with Python
- Introduction
- Subsetting Filtering and Grouping
- Detecting Outliers and Handling Missing Values
- Concatenating Merging and Joining
- Useful Methods of Pandas
- Summary
- 5. Getting Comfortable with Different Kinds of Data Sources
- Introduction
- Reading Data from Different Sources
- Introduction to Beautiful Soup 4 and Web Page Parsing
- Summary
- 6. Learning the Hidden Secrets of Data Wrangling
- Introduction
- Advanced List Comprehension and the zip Function
- Data Formatting
- Identifying and Cleaning Outliers
- Levenshtein Distance
- Summary
- 7. Advanced Web Scraping and Data Gathering
- Introduction
- The Requests and BeautifulSoup Libraries
- Reading Data from XML
- Reading Data from an API
- Fundamentals of Regular Expressions (RegEx)
- Summary
- 8. RDBMS and SQL
- Introduction
- Refresher of RDBMS and SQL
- Relation Mapping in Databases
- Joins
- Retrieving Specific Columns from a JOIN Query
- Summary
- 9. Applications in Business Use Cases and Conclusion of the Course
- Introduction
- Applying Your Knowledge to a Data Wrangling Task
- An Extension to Data Wrangling
- Summary
- Appendix
- 1. Introduction to Data Wrangling with Python
- 2. Advanced Operations on Built-In Data Structures
- 3. Introduction to NumPy Pandas and Matplotlib
- 4. A Deep Dive into Data Wrangling with Python
- 5. Getting Comfortable with Different Kinds of Data Sources
- 6. Learning the Hidden Secrets of Data Wrangling
- 7. Advanced Web Scraping and Data Gathering
- 8. RDBMS and SQL
- 9. Applications in Business Use Cases and Conclusion of the Course 更新時間:2021-06-18 18:12:06
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