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    Home / Central Data Catalog / DDI-IND-NSSO-66-SCHEDULE-1.0T1 / variable [F20]
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
220448
Downloads
21340
  • 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: Demographic and other particulars of household members

Overview

Valid: 468519
Invalid: 0
Type: Discrete
Start: 40
End: 43
Width: 4
Range: -
Format: character

Questions and instructions

Categories
Value Category Cases
0000 35356
7.5%
0014 42
0%
0024 53
0%
0030 42
0%
0046 33
0%
0093 86
0%
0100 48
0%
0110 Jammu 3787
0.8%
0111 Udhampur 1525
0.3%
0120 Srinagar 3228
0.7%
0121 Anantnag 3426
0.7%
0122 Baramula 2482
0.5%
0130 43
0%
0170 34
0%
0182 46
0%
0210 Shimla 2796
0.6%
0211 Bilaspur 2001
0.4%
0212 Dharamshala 2262
0.5%
0213 Mandi 1840
0.4%
0231 115
0%
0282 43
0%
0310 2204
0.5%
0311 Amritsar 1531
0.3%
0312 Firozpur 2980
0.6%
0313 Hoshiarpur 1776
0.4%
0320 Ludhiana 2617
0.6%
0321 Bathinda 1170
0.2%
0322 Patiala 2504
0.5%
0330 46
0%
0331 38
0%
0380 47
0%
0500 33
0%
0510 Dehradun 4820
1%
0511 Almora 3557
0.8%
0610 Chandigarh 1608
0.3%
0611 Ambala 2455
0.5%
0612 Bhiwani 1705
0.4%
0613 Hisar 2115
0.5%
0614 Karnal 3018
0.6%
0615 Rohtak 3372
0.7%
0706 34
0%
0710 Delhi 3309
0.7%
0810 Ajmer 2238
0.5%
0811 Jodhpur 3429
0.7%
0812 Udaipur 3393
0.7%
0820 Jaipur 5451
1.2%
0821 Alwar 2133
0.5%
0822 Ganganagar 1988
0.4%
0823 Kota 3005
0.6%
0910 Agra 4811
1%
0911 Aligarh 2842
0.6%
0912 Meerut 2777
0.6%
0920 Allahabad 2480
0.5%
0921 Azamgarh 3742
0.8%
0922 Faizabad 2833
0.6%
0923 Gorakhpur 4510
1%
0924 Varanasi 3840
0.8%
0930 Bareilly 3180
0.7%
0931 Moradabad 3338
0.7%
0932 Saharanpur 2079
0.4%
0933 Sitapur 2427
0.5%
0940 Lucknow 2485
0.5%
0941 Fatehpur 2369
0.5%
0942 Gonda 2634
0.6%
0943 Jhansi 2670
0.6%
0944 Kanpur 1452
0.3%
1010 Muzaffarpur 3699
0.8%
1011 Darbhanga 2996
0.6%
1012 Motihari 3175
0.7%
1013 Purnia 4071
0.9%
1020 Patna 4961
1.1%
1021 Bhagalpur 2309
0.5%
1022 Gaya 2549
0.5%
1050 53
0%
1110 Gangtok 3023
0.6%
1210 199
0%
1211 65
0%
1281 41
0%
1310 Kohima 5107
1.1%
1311 Imphal 37
0%
1400 48
0%
1410 222
0%
1420 46
0%
1513 32
0%
1710 Shillong 3997
0.9%
1711 Tura 2502
0.5%
1712 Agartala 0
0%
1810 Guwahati 5576
1.2%
1811 Silchar 3132
0.7%
1820 Dibrugarh 1301
0.3%
1821 Jorhat 3471
0.7%
1822 Tezpur 3530
0.8%
1900 45
0%
1910 Barddhaman 2386
0.5%
1911 Bankura 1957
0.4%
1912 Chinsura 2998
0.6%
1913 Medinipur 2710
0.6%
1919 31
0%
1920 Kolkata 6483
1.4%
1921 Howrah 1480
0.3%
1930 Maldah 2644
0.6%
1931 Barhampur 2375
0.5%
1932 Siliguri 2603
0.6%
2010 Ranchi 4111
0.9%
2011 Dumka 3173
0.7%
2012 Hazaribag 4392
0.9%
2013 Jamshedpur 1855
0.4%
2019 37
0%
2021 27
0%
2110 Bhubaneswar 2148
0.5%
2111 Baripada 2186
0.5%
2112 Berhampur 2087
0.4%
2113 Cuttack 4820
1%
2120 Sambalpur 3563
0.8%
2121 Bhawanipatna 2932
0.6%
2210 Raipur 3685
0.8%
2211 Ambikapur 2294
0.5%
2212 Bilaspur 2145
0.5%
2213 Durg 2317
0.5%
2222 46
0%
2224 31
0%
2310 Bhopal 2591
0.6%
2311 Chhindwara 2230
0.5%
2312 Indore 1432
0.3%
2313 Khandwa 1987
0.4%
2320 Gwalior 2194
0.5%
2321 Ratlam 1929
0.4%
2322 Shivpuri 2078
0.4%
2323 Ujjain 2343
0.5%
2330 Jabalpur 1720
0.4%
2331 Rewa 3062
0.7%
2332 Sagar 2041
0.4%
2410 Ahmedabad 2233
0.5%
2411 Bhavnagar 1460
0.3%
2412 Jamnagar 1002
0.2%
2413 Rajkot 1806
0.4%
2414 Surendranagar 876
0.2%
2420 Baroda 3378
0.7%
2421 Mahesana 1461
0.3%
2422 Nadiad 1560
0.3%
2423 Surat 1737
0.4%
2424 Valsad 2293
0.5%
2620 32
0%
2710 Aurangabad 2777
0.6%
2711 Jalgaon 2736
0.6%
2712 Nanded 3305
0.7%
2713 Nashik 1971
0.4%
2720 Mumbai 3495
0.7%
2721 Thane 3125
0.7%
2722 37
0%
2730 Nagpur 4148
0.9%
2731 Akola 2042
0.4%
2732 Amravati 2094
0.4%
2740 Pune 5418
1.2%
2741 Kolhapur 2791
0.6%
2742 Solapur 2244
0.5%
2790 46
0%
2810 Cuddapah 2504
0.5%
2811 Anantapur 1310
0.3%
2812 Guntur 1320
0.3%
2813 Kurnool 1370
0.3%
2814 Nellore 1820
0.4%
2820 Hyderabad 5757
1.2%
2821 Karimnagar 2061
0.4%
2822 Nizamabad 1736
0.4%
2823 Warangal 1946
0.4%
2830 Vijayawada 2390
0.5%
2831 Kakinada 1526
0.3%
2832 Visakhapatnam 2955
0.6%
2874 31
0%
2910 Bangalore 4129
0.9%
2911 Mangalore 1418
0.3%
2912 Mysore 1807
0.4%
2913 Shimoga 1591
0.3%
2920 Hubli 2890
0.6%
2921 Belgaum 2162
0.5%
2922 Bellary 2446
0.5%
2923 Gulbarga 1605
0.3%
2924 50
0%
3010 Panaji 1902
0.4%
310 Jalandhar 0
0%
3210 Kozhikode 4392
0.9%
3211 Kannur 2751
0.6%
3212 Palakkad 1504
0.3%
3213 Thrissur 1779
0.4%
3220 Thiruvanantha- puram 1798
0.4%
3221 Kochi 2785
0.6%
3222 Kollam 3000
0.6%
3223 Kottayam 1524
0.3%
3310 Coimbatore 2735
0.6%
3311 Dharmapuri 1152
0.2%
3312 Salem 1663
0.4%
3313 Tiruchirappalli 2615
0.6%
3320 Chennai 3616
0.8%
3321 Cuddalore 1835
0.4%
3322 Vellore 2196
0.5%
3323 Pondicherry 1987
0.4%
3330 Madurai 2214
0.5%
3331 Thanjavur 1874
0.4%
3332 Tirunelveli 2495
0.5%
3333 Virudhunagar 1804
0.4%
3510 Port Blair 2248
0.5%
7710 29
0%
8713 45
0%
9101 42
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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