Google refine tutotial

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Google refine tutotial

  1. 1. Vinod Gupta School of Management, IIT Kharagpur Google Refine Tutorial April, 08 2012 Sathishwaran.R - 10BM60079 Vijaya Prabhu - 10BM60097This Tutorial was created using Google Refine Version 2.5 on a Windows 7 platform
  2. 2. Data Cleansing• Data cleansing is identifying the wrong or inaccurate records in the data set and making appropriate corrections to the records.• It involves identifying incomplete, inaccurate, and incorrect parts of data and then either replacing them with correct data or deleting the incorrect data• Data cleansing results in data which is consistent with the other standard data and is useful for performing various analysis• The error in the data could be due to data entry error by the user, failure during transmission of data or improper data definitions. 2
  3. 3. Need for Data Cleansing• Incorrect or inaccurate data may lead to false conclusions and can cause investments to be misdirected in finance.• Also government needs accurate data on population and census for directing the funds to the deserving areas.• Many organizations tap into customer information. If the data is not accurate, for eg. If the address is not accurate then the business runs the risk of send wrong information, thus losing customers. 3
  4. 4. Challenges Data Cleansing• Loss of Information: In many cases the record may be incomplete, hence the whole record may require to be deleted which leads to loss of information. It could become costly if huge number of data is deleted.• Maintenance of Data: Once the data is cleansed then any change in the data specification needs to affect only the new values. Hence data management solutions should be designed in such a way that the process of data entry and retrieval are altered to provide correct data.• Data cleansing is an iterative process which needs significant work in exploration and corrction of entries. 4
  5. 5. About Google Refine• Google Refine is a powerful tool that can be effectively used for data cleansing.• It helps in working with raw data, cleaning it up, transforming from one format to other, encompassing it with web services and linking it to databases.• It is very easy to use and has a web interface.• It is freely available and works well with any browser.• Google Refine is a desktop application and it runs a small web server on your system and we need to point our browser to the server to use refine. 5
  6. 6. Getting Started - Installation1. Download the zip file (appropriate Windows, Mac, Linux versions) from the link http://code.google.com/p/google- refine/wiki/Downloads?tm=22. Uncompress the files from the zip file.3. Run the “google-refine.exe” file.4. A command window opens and Google refine runs taking the user to the home page in the default browser. 6
  7. 7. Google Refine Homepage 7
  8. 8. Importing Data• Google Refine supports TSV, CSV, Excel (.xls and .xlsx), JSON, XML, and Google data document formats.• Once imported the data is in Google Refine’s own data format.• We have used TSV data on Disasters worldwide from 1900-2008 available from http://www.infochimps.com/datasets/disaster s-worldwide-from-1900-2008 for the tutorial. 8
  9. 9. Importing Data 9
  10. 10. Importing Data 10
  11. 11. DataUploaded Creating Project 11
  12. 12. Creating Project Project Created 12
  13. 13. Faceting• Faceting is about seeing the big picture and filtering based on rows to work on data you want to change in bulk.• We can create a facet for a column to get the details about that column and then we can filter to a subset of rows with a constraint.• We can perform text facet, Numeric facet, timeline facet and scatterplot facet. Also various customized facets can be designed. 13
  14. 14. Faceting 14
  15. 15. FacetingThe ColumnType has 18 unique options 15
  16. 16. Removing Redundancy Even thoughthey are of same type, shows asdifferent options due to case 16
  17. 17. Removing Redundancy 17
  18. 18. Removing Redundancy 18
  19. 19. Removing Redundancy 19
  20. 20. Removing RedundancyReduced to 15unique options 20
  21. 21. Numeric Faceting 21
  22. 22. Numeric FacetingHighly clustered towards low values 22
  23. 23. Numeric Faceting 23
  24. 24. Numeric Faceting 24
  25. 25. Numeric Faceting Cost column is blank and has no value 25
  26. 26. Numeric Faceting Calamities with low cost 26
  27. 27. Numeric Faceting Calamities with high cost 27
  28. 28. Clustering• Clustering is used to merge choices which look similar. 28
  29. 29. Clustering 29
  30. 30. ClusteringData Merged 30
  31. 31. Using Expressions• Expressions are used to transform existing data to create new data 31
  32. 32. Using Expressions 32
  33. 33. Using Expressions 33
  34. 34. Data Augmentation• Reconciliation option in Google refine allows data to be linked to web pages. Suppose we want details on the country where the calamity has struck we can perform the following steps 34
  35. 35. Reconciliation 35
  36. 36. Reconciliation 36
  37. 37. Reconciliation 37
  38. 38. Reconciliation 38
  39. 39. Reconciliation 39
  40. 40. Data Enrichment 40
  41. 41. Data Enrichment 41
  42. 42. Data Enrichment 42
  43. 43. Data Enrichment 43
  44. 44. Export 44
  45. 45. How to Use Twitter DataStep 1Step 2 45
  46. 46. Step 3 46
  47. 47. Step 4Step 5 47
  48. 48. Step 6 48
  49. 49. Step 7 Step 8 49
  50. 50. Output 50
  51. 51. Friends Events using Facebook data 51
  52. 52. Friends Events using Facebook data 52
  53. 53. Friends Events using Facebook data 53
  54. 54. Friends Events using Facebook data 54
  55. 55. Friends Events using Facebook data 55
  56. 56. Friends Events using Facebook data 56
  57. 57. Friends Events using Facebook data 57
  58. 58. Friends Events using Facebook data 58
  59. 59. Friends Events using Facebook data 59
  60. 60. Friends Events using Facebook data 60
  61. 61. Friends Events using Facebook data• After splitting the cell using separator },{ 61
  62. 62. Friends Events using Facebook data 62
  63. 63. Friends Events using Facebook data• After updating for other columns and rearranging it we get the events as 63
  64. 64. Thank You 64

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