I am attaching a csv file that contain all the pincodes for each ward 
extracted from this shape file. For e.g. "A" ward is part of Pincode 
numbers 400001, 400002, 3, 5, 9, 20, 21, 23, 39 etc.

Here is the python code used for this...
https://gist.github.com/shantanuo/05187dd23b96f5e92f6b

The shape file has 24 wards, for e.g. ward "A", ward "B" and so on. Each 
ward's boundaries are mentioned in the "shape" array. The python script 
will perform reverse lookup on each point and find the complete address 
(for e.g. Carnac Road, Ballard Estate, Masjid Bunder, Mumbai, Greater 
Bombay, Maharashtra, 400003, India). Pincode from this address can be 
extracted using regular expression. The unique, sorted pincodes for each 
ward can be exported to csv using indispensable python library called 
"pandas". 

I hope this helps someone.

-- Shantanu


On Wednesday, 13 January 2016 18:16:36 UTC+5:30, Devdatta Tengshe wrote:
>
> HI Abhay,
>
> Are you looking for Municipal wards? If so, here is the data.
>
>
> Regards,
> Devdatta
>
> On Tue, Jan 12, 2016 at 7:10 PM, Abhay Singh <[email protected] 
> <javascript:>> wrote:
>
>>
>> hi 
>> I am student of TISS, and working on project where i need mumbai 
>> shapefile ward wise. 
>> If anyone have can please share.
>>
>> Thanks and regards 
>>
>> Abhay 
>>
>> -- 
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,0,1
0,R/N,"[u'400066', u'400068', u'400092', u'400103']"
1,R/C,"[u'400066', u'400067', u'400092', u'400095', u'400101', u'400103']"
2,P/S,"[u'400053', u'400058', u'400059', u'400060', u'400062', u'400063', u'400064', u'400065', u'400076', u'400093', u'400097', u'400102', u'400104']"
3,P/N,"[u'400061', u'400063', u'400064', u'400065', u'400067', u'400095', u'400097', u'400100', u'400101']"
4,R/S,"[u'400064', u'400066', u'400067', u'400092', u'400095', u'400097', u'400100', u'400101', u'400103']"
5,A,"[u'400001', u'400002', u'400003', u'400005', u'400009', u'400020', u'400021', u'400023', u'400039']"
6,C,"[u'400002', u'400003', u'400004', u'400007', u'400008', u'400020']"
7,B,"[u'400001', u'400002', u'400003', u'400007', u'400008', u'400009', u'400010']"
8,E,"[u'400003', u'400004', u'400007', u'400008', u'400009', u'400010', u'400011', u'400012', u'400013', u'400015', u'400027', u'400033', u'400034']"
9,D,"[u'400002', u'400004', u'400006', u'400007', u'400008', u'400011', u'400020', u'400026', u'400034', u'400035']"
10,M/W,"[u'400022', u'400024', u'400031', u'400037', u'400071', u'400074', u'400075', u'400077', u'400079', u'400088', u'400089']"
11,L,"[u'400017', u'400022', u'400024', u'400037', u'400051', u'400055', u'400059', u'400069', u'400070', u'400071', u'400072', u'400076', u'400084', u'400086', u'400089', u'400098', u'400099']"
12,N,"[u'400043', u'400069', u'400071', u'400072', u'400075', u'400077', u'400079', u'400083', u'400084', u'400086', u'400089']"
13,S,"[u'400042', u'400059', u'400063', u'400065', u'400069', u'400072', u'400076', u'400078', u'400080', u'400081', u'400083', u'400086']"
14,H/E,"[u'400017', u'400022', u'400029', u'400046', u'400051', u'400052', u'400054', u'400055', u'400070', u'400098', u'400099']"
15,T,"[u'400042', u'400063', u'400065', u'400078', u'400080', u'400081', u'400601', u'400603', u'400604']"
16,M/E,"[u'400043', u'400071', u'400074', u'400075', u'400079', u'400088', u'400089', u'400703']"
17,G/N,"[u'400012', u'400013', u'400014', u'400016', u'400017', u'400019', u'400022', u'400025', u'400028', u'400040', u'400050', u'400051']"
18,F/S,"[u'400010', u'400012', u'400013', u'400014', u'400015', u'400027', u'400028', u'400031', u'400033']"
19,K/E,"[u'400029', u'400046', u'400047', u'400054', u'400055', u'400056', u'400057', u'400058', u'400059', u'400060', u'400063', u'400065', u'400069', u'400070', u'400072', u'400093', u'400099', u'400102']"
20,H/W,"[u'400017', u'400040', u'400049', u'400050', u'400051', u'400052', u'400054', u'400055']"
21,G/S,"[u'400008', u'400011', u'400012', u'400013', u'400018', u'400025', u'400026', u'400027', u'400028', u'400030', u'400034']"
22,F/N,"[u'400014', u'400015', u'400019', u'400022', u'400031', u'400037']"
23,K/W,"[u'400046', u'400047', u'400049', u'400053', u'400054', u'400056', u'400057', u'400058', u'400060', u'400061', u'400062', u'400069', u'400095', u'400102', u'400104']"

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