Part 16: Data Manipulation in Data Validation and Quality Control

Here is the continuation and completion of your provided code snippets:

python
 
1    4 5 pending unknown -1
2
3==================================================
4After replacement:
5 customer_id status region rating
60 1 Active North 5.0
71 2 Active South 4.0
82 3 Active None <NA>
93 4 Inactive West 3.0
104 5 pending None <NA>
11
12==================================================
13Multiple replacements:
14Before:
15 product price
160 iPhone 999
171 iphone 999
182 IPHONE 999
193 Galaxy 899
204 galaxy 899
21
22After:
23 product price
240 iPhone 999
251 iPhone 999
262 iPhone 999
273 Galaxy 899
284 Galaxy 899

Explanation and Additional Notes:

Standardizing Status Values

• The status column had inconsistent capitalization. We used a dictionary to map all variations of 'active' to the standardized form 'Active'.

Handling Invalid Region Entries

• For the region column, we replaced entries like 'N/A' and 'unknown' with None, indicating missing or invalid data.

Read the full article at Towards AI - Medium

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