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    Home / Central Data Catalog / DDI-IND-NSSO-66-SCHEDULE-1.0T1 / variable [V539]
central

Household Consumer Expenditure Type-1, July 2009 - June 2010
NSS 66th Round

India, 2009 - 2010
Get Microdata
Reference ID
DDI-IND-NSSO-66-SCHEDULE-1.0T1
Producer(s)
National Sample Survey Office,NSSO
Collections
Household Consumption Expenditure
Metadata
DDI/XML JSON
Created on
Jan 18, 2018
Last modified
Mar 27, 2019
Page views
220671
Downloads
21366
  • Study Description
  • Data Dictionary
  • Downloads
  • Get Microdata
  • Data files
  • Identification
    of Sample
    Household
  • Household
    Characteristics
  • Demographic and
    other
    particulars of
    household
    members
  • Consumption of
    cereals,
    pulses, milk
    and milk
    products, sugar
    and salt during
    the last 30
    days
  • Summary of
    comsumer
    expenditure
  • Consumption of
    clothing,
    bedding and
    footwear during
    last 30 and
    365 days
  • Expenditure on
    education and
    medical
    (institutional)
    goods and
    services
  • Expenditure for
    purchase and
    construction
    (including
    repair and
    maintenance) of
    durable goods
    for domestic
    use
  • Expenditure on
    miscellaneous
    goods and
    services
    including
    medical
    (non-institutional),
    rents and taxes
    during the last
    30 days

FOD Sub-Region (FOD_Sub_Region)

Data file: Expenditure on education and medical (institutional) goods and services

Overview

Valid: 362073
Invalid: 0
Type: Discrete
Start: 42
End: 45
Width: 4
Range: -
Format: character

Questions and instructions

Categories
Value Category Cases
0000 32782
9.1%
0014 31
0%
0024 31
0%
0030 39
0%
0046 32
0%
0093 64
0%
0100 70
0%
0110 Jammu 3217
0.9%
0111 Udhampur 1284
0.4%
0120 Srinagar 2082
0.6%
0121 Anantnag 3115
0.9%
0122 Baramula 2195
0.6%
0130 38
0%
0170 15
0%
0182 32
0%
0210 Shimla 1975
0.5%
0211 Bilaspur 1705
0.5%
0212 Dharamshala 1477
0.4%
0213 Mandi 1292
0.4%
0231 100
0%
0282 21
0%
0310 1638
0.5%
0311 Amritsar 1012
0.3%
0312 Firozpur 2435
0.7%
0313 Hoshiarpur 1353
0.4%
0320 Ludhiana 1632
0.5%
0321 Bathinda 861
0.2%
0322 Patiala 1907
0.5%
0330 18
0%
0331 32
0%
0380 40
0%
0500 41
0%
0510 Dehradun 3689
1%
0511 Almora 2614
0.7%
0610 Chandigarh 1418
0.4%
0611 Ambala 1934
0.5%
0612 Bhiwani 1477
0.4%
0613 Hisar 1583
0.4%
0614 Karnal 2409
0.7%
0615 Rohtak 2698
0.7%
0706 35
0%
0710 Delhi 3029
0.8%
0810 Ajmer 1353
0.4%
0811 Jodhpur 1854
0.5%
0812 Udaipur 2555
0.7%
0820 Jaipur 3612
1%
0821 Alwar 1381
0.4%
0822 Ganganagar 1226
0.3%
0823 Kota 2269
0.6%
0910 Agra 3396
0.9%
0911 Aligarh 2059
0.6%
0912 Meerut 2080
0.6%
0920 Allahabad 1552
0.4%
0921 Azamgarh 2070
0.6%
0922 Faizabad 1801
0.5%
0923 Gorakhpur 2608
0.7%
0924 Varanasi 2436
0.7%
0930 Bareilly 1638
0.5%
0931 Moradabad 1586
0.4%
0932 Saharanpur 1211
0.3%
0933 Sitapur 1143
0.3%
0940 Lucknow 1477
0.4%
0941 Fatehpur 1506
0.4%
0942 Gonda 1377
0.4%
0943 Jhansi 1947
0.5%
0944 Kanpur 1097
0.3%
1010 Muzaffarpur 2390
0.7%
1011 Darbhanga 1683
0.5%
1012 Motihari 1632
0.5%
1013 Purnia 2668
0.7%
1020 Patna 3239
0.9%
1021 Bhagalpur 1385
0.4%
1022 Gaya 1590
0.4%
1050 47
0%
1110 Gangtok 2591
0.7%
1210 138
0%
1211 33
0%
1281 38
0%
1310 Kohima 4797
1.3%
1311 Imphal 35
0%
1400 39
0%
1410 248
0.1%
1420 26
0%
1513 21
0%
1710 Shillong 3595
1%
1711 Tura 2580
0.7%
1712 Agartala 0
0%
1810 Guwahati 4495
1.2%
1811 Silchar 2099
0.6%
1820 Dibrugarh 1038
0.3%
1821 Jorhat 3710
1%
1822 Tezpur 3195
0.9%
1900 50
0%
1910 Barddhaman 1833
0.5%
1911 Bankura 1221
0.3%
1912 Chinsura 3050
0.8%
1913 Medinipur 2352
0.6%
1919 22
0%
1920 Kolkata 6242
1.7%
1921 Howrah 1355
0.4%
1930 Maldah 2635
0.7%
1931 Barhampur 1924
0.5%
1932 Siliguri 2320
0.6%
2010 Ranchi 3160
0.9%
2011 Dumka 1863
0.5%
2012 Hazaribag 2976
0.8%
2013 Jamshedpur 1031
0.3%
2019 40
0%
2021 14
0%
2110 Bhubaneswar 1294
0.4%
2111 Baripada 1402
0.4%
2112 Berhampur 1457
0.4%
2113 Cuttack 3313
0.9%
2120 Sambalpur 2332
0.6%
2121 Bhawanipatna 1635
0.5%
2210 Raipur 1859
0.5%
2211 Ambikapur 2359
0.7%
2212 Bilaspur 1518
0.4%
2213 Durg 1482
0.4%
2222 24
0%
2224 39
0%
2310 Bhopal 1939
0.5%
2311 Chhindwara 1419
0.4%
2312 Indore 1218
0.3%
2313 Khandwa 1109
0.3%
2320 Gwalior 1609
0.4%
2321 Ratlam 1773
0.5%
2322 Shivpuri 1538
0.4%
2323 Ujjain 1732
0.5%
2330 Jabalpur 1144
0.3%
2331 Rewa 2170
0.6%
2332 Sagar 1255
0.3%
2410 Ahmedabad 1845
0.5%
2411 Bhavnagar 990
0.3%
2412 Jamnagar 799
0.2%
2413 Rajkot 1275
0.4%
2414 Surendranagar 652
0.2%
2420 Baroda 2500
0.7%
2421 Mahesana 1052
0.3%
2422 Nadiad 1129
0.3%
2423 Surat 1376
0.4%
2424 Valsad 1466
0.4%
2620 43
0%
2710 Aurangabad 2163
0.6%
2711 Jalgaon 1558
0.4%
2712 Nanded 2595
0.7%
2713 Nashik 1818
0.5%
2720 Mumbai 3780
1%
2721 Thane 3380
0.9%
2722 43
0%
2730 Nagpur 3217
0.9%
2731 Akola 1572
0.4%
2732 Amravati 1635
0.5%
2740 Pune 4862
1.3%
2741 Kolhapur 2468
0.7%
2742 Solapur 2083
0.6%
2790 28
0%
2810 Cuddapah 1817
0.5%
2811 Anantapur 863
0.2%
2812 Guntur 1033
0.3%
2813 Kurnool 677
0.2%
2814 Nellore 1389
0.4%
2820 Hyderabad 4242
1.2%
2821 Karimnagar 1386
0.4%
2822 Nizamabad 1177
0.3%
2823 Warangal 2078
0.6%
2830 Vijayawada 1740
0.5%
2831 Kakinada 1016
0.3%
2832 Visakhapatnam 2082
0.6%
2874 21
0%
2910 Bangalore 3238
0.9%
2911 Mangalore 1259
0.3%
2912 Mysore 1343
0.4%
2913 Shimoga 1112
0.3%
2920 Hubli 1562
0.4%
2921 Belgaum 1323
0.4%
2922 Bellary 1372
0.4%
2923 Gulbarga 1464
0.4%
2924 29
0%
3010 Panaji 1820
0.5%
310 Jalandhar 0
0%
3210 Kozhikode 4428
1.2%
3211 Kannur 2474
0.7%
3212 Palakkad 1588
0.4%
3213 Thrissur 1934
0.5%
3220 Thiruvanantha- puram 2233
0.6%
3221 Kochi 2655
0.7%
3222 Kollam 4122
1.1%
3223 Kottayam 2017
0.6%
3310 Coimbatore 2904
0.8%
3311 Dharmapuri 757
0.2%
3312 Salem 1229
0.3%
3313 Tiruchirappalli 2019
0.6%
3320 Chennai 3244
0.9%
3321 Cuddalore 1143
0.3%
3322 Vellore 1773
0.5%
3323 Pondicherry 1654
0.5%
3330 Madurai 1569
0.4%
3331 Thanjavur 1217
0.3%
3332 Tirunelveli 1902
0.5%
3333 Virudhunagar 1326
0.4%
3510 Port Blair 1695
0.5%
7710 35
0%
8713 56
0%
9101 21
0%
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
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