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Update

  • We Cleared round 1

Address Normalization

  • This was the round 1 problem statement of Xpressathon1.0 organized by Xpressbees
  • Performed Address Normalization on random addresses
  • Used python3

Problem Statement

Normalize unstructured raw Indian addresses by segregating personal information and address to a defined json structure. Addresses can contain spelling mistakes which need to be corrected and addresses need to be geocoded.

Our Idea

  • We fetched the pincode from each line of address.
  • Used those pincodes to get to know the City, State, Locality.
  • From this info we were able to get the geocodes.
  • We performed data sanitization to ensure that no misspelling exists.
  • We then finally outputed the collected data in json format.
  • This output was then written to a json file.

Libraries used

  • pgeocode
  • json
    These can easily be installed using "pip3 install library-name" in any code editor's terminal

How to run this application

  • Clone this repository to a code editor
  • Either open the file Address-normalization.py and then click on run icon of the code editor
  • Or in the terminal write:
    • python Address-normalization.py

Note

  • For the addresses that doesnot include a pincode or for addreses that weren't recognized by our library, our application returned "NaN".

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