




































Asian Review of Environmental 

and Earth Sciences 
ISSN: 2313-8173 
Vol. 2, No. 2, 35-41, 2015 

http://www.asianonlinejournals.com/index.php/AREES 

 
 

 

* Corresponding Author 

 

 

35 

 

Rural Non-Agricultural Working Force and Levels of 

Development in Uttar Pradesh: A Regional Analysis (India)  
 

Shafiqullah
1* 

--- Sana Asma
2
 

 
1
Department of Geography Faculty of Science, Aligarh Muslim University Aligarh, India  

2 
Research Scholar (UGC-SRF), Department of Geography Faculty of Science, Aligarh Muslim University Aligarh, India 

 

Abstract 
 

 

 

 

 

 

 

 

 

 

 
 

 

 
This work is licensed under a Creative Commons Attribution 3.0 License 

Asian Online Journal Publishing Group 

 

Contents 
1. Introduction ............................................................................................................................................................................... 36 

2. Data and Method ....................................................................................................................................................................... 37 

3. Conclusion .................................................................................................................................................................................. 40 

References ...................................................................................................................................................................................... 40 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

The present paper investigate the trends of rural non-agricultural working force over the period of 1971 to 

2011, the regional variations in the rural non-agricultural working force and the relationship between rural 

non-agricultural working force and levels of development among the districts of Uttar Pradesh. The 

regional variations in the distribution of workforce in rural non-agricultural sectors are quite notable. The 

general picture emerged that there is a gradual increase of main workforce in non-agricultural sector 

from north-western to south-eastern parts of Uttar Pradesh. The distribution of female main 

workforce in non-agricultural workforce depicts that there is a gradual decrease from west to south-

east. The statistical analysis leads to conclusion that agriculture, population growth and health facilities 

are the chief determinants but the magnitudes of their effects are dissimilar.  
 

     Keywords: Working force, Agriculture, Population growth, Health facilities, Magnitude, Development.  

 

http://creativecommons.org/licenses/by/3.0/


Asian Review of Environmental and Earth Sciences, 2015, 2(2): 35-41 

 

 

 

 

36 

 

1. Introduction 
Since the early 1970s attention has been paid to the significance of the non-agricultural sector in the rural Indian 

economy. The census on occupational classification of workers [1] provided a far more detailed picture of the 

composition of the nonagricultural workers in rural areas. Workers were classified into about one hundred 

occupational groups, along with their further subdivisions. The data allowed grouping of the rural workers in four 

classes: (a) workers engaged in producing goods and providing services to local population, (b) government instituted 

workers giving educational, medical, transportation and such like services to the people,  (c) workers engaged in non-

agricultural production and services oriented to non-local markets, and (d) adventurous workers, such as technical 

personnel, administrative staff and proprietors working on various development projects in rural areas. 

The economy of rural areas in India is predominantly based on agriculture and other activities related to 

agriculture sector.  Hence an overwhelming majority of rural population mainly depends on agriculture sector both 

for its employment and livelihood.  At the same time various non-agricultural activities are also playing an important 

role in providing the opportunities of employment and incomes to the labourforce belonging to both farming and 

non-farming households.  Though, the nature of employment as available either in agricultural or non-agricultural 

activities is measured for a shorter duration. As per 2011 Census, nearly one-fourth of the rural work force (main 

workers) was reported to be employed in non-agricultural pursuits.  

The non-agricultural activities include all economic activities other than crop production and allied agricultural 

activities such as animal husbandry, plantations, fishing, forestry, etc. Rural non-agricultural economic activities 

consist of wide ranging various traditional and modern manufacturing industries, mining and quarrying, construction, 

trading, transport, storage and communication, hostelling and those rendering community and personal services. The 

non-agricultural work may often be undertaken as a secondary activity. This view of the rural populations exclusive 

dependence on agriculture has began to change in the past few years. The reflection in the shift of workforce from 

agriculture sector to non-agriculture sector has been well visualized in almost all the states in India.  

Occupational diversification away from agriculture in favour of non-agriculture activities in the rural economy 

has generated a lot of interest among researchers. The issue is whether the declining share of agriculture in 

employment reflects maturing of positive growth forces in the economy or a result of adverse trends in the agrarian 

sector resulting in the growing inability of agriculture to further absorb the expanding labourforce. Many studies 

make important contributions in the scrutiny of the nature of employment in the rural non-agricultural sector 

especially at the all-India level [2-6]. 

However, there are no such significant studies carried out for Uttar Pradesh (U.P.) in particular, which is the 

most populous state in the country.  One sixth of the World’s population lives in India and one-sixth of India’s 

population lives in Uttar Pradesh. Its share in total area of the Country is 7.3 per cent. The predominance of rural 

population makes the state economy primarily agrarian. The State’s two thirds of the total workers are still engaged 

in agriculture and allied activities. The economic development and income of the people in the state depend largely 

on its agricultural base. However, the state has lately witnessed rapid industrialization after liberalization and 

globalization of the national economy.  

After consolidation of hilly districts and some plain areas into a separate state of Uttarakhand, Uttar Pradesh now 

largely consists of fertile plain of Ganga basin in part. At present it extends between 23
0 

52' and 30° 24' N latitudes 

and 77
0 
05' and 84° 38' E longitudes. The state shares international border with Nepal and Tibet in northeast, with the 

Indian states of Himachal Pradesh in northwest, Haryana, Rajasthan and Delhi in west and  Madhya Pradesh and 

Chattisgarh in south, and  Bihar and Jharkhand in southwest (Figure 1).  

 

 
Fig-1. Based on Census of India, 2011 

 

Geographically, the location of Uttar Pradesh and its climate are conducive to earn livelihood from agriculture 

and diversification of its economy. The state is well known for success in the green revolution and for the highest 

production of food-grains and sugarcane in the country. However, the poverty is widespread in the state as it has the 

highest number of people below poverty line (about 32 per cent) as compared to the other states. It lags behind not 



Asian Review of Environmental and Earth Sciences, 2015, 2(2): 35-41 

 

 

 

 

37 

 

only in economic progress but in terms of indicators of human development as well. The state has wide variations in 

the level of development, we can expect that factors driving non-agricultural workforce growth would also vary. It is 

likely that in the most developed western region, diversification of workforce away from agriculture would reflect 

the role of demand –pull factors generated by agricultural dynamism, while in the western, eastern and southern 

regions distress-push can play a role in increasing the volume of non-agricultural workforce. A study of rural non-

agricultural workforce is crucial to an understanding of the regional pattern of diversification of rural economy. The 

magnitude and direction of shift from agriculture to non –agriculture is worth investigation and equally essential is to 

probe into the role of diverse factors in the process.   

In the light of the above facts, an attempt has been made to study the ‘Rural non-agricultural working force and 

levels of development in Uttar Pradesh’ under three main sections. In the section I, we analyze the trends of rural 

non-agricultural working force over the period of 1971 to 2011. Section II explains the regional variations in the 

rural non-agricultural working force and the section III finds out the relationship between rural non-agricultural 

working force and levels of development among the districts of Uttar Pradesh.  

 

2. Data and Method 
The study is mainly based on the secondary sources of data obtained from the Office of the Registrar General of 

India and Census Commissioner, Government of India, New Delhi and the State Planning Institute, Uttar Pradesh, 

Lucknow. The district has been taken as a unit of analysis due to: firstly, a fairly satisfactory data base is available at 

this level, secondly, it offers better facilities for formulation and implementation of plans as it has a definite 

administrative set up and fairly well defined geographical boundaries and finally, there is better possibility of co-

ordination of micro-level planning at district level.  

For the identification of the levels of development and its correlates 39 variables have been selected (Table 1). 

For this purpose the district wise value of each indicator is standardized with the help of ‘z’ score technique which is 

also known as 'zi' value or 'z' score. 

   Xij-Xi 

Zij =  

     δXj 

Where:  

Zij= standardized value of the variable i in district j 

Xij = actual value of variable i in district j  

Xi = mean value of the variable i in all districts  

δ Xj = Standard Deviation (δ) of variables in all districts 

After working out the 'z' score of all the indicators, composite score (C.S.) for each district has been calculated 

with the following algebraic expression:  

     ΣZij 

CS =  

       N 

Where, C.S. is composite score, N refers to the number of variables, ΣZij  indicate ‘Z’ scores of all variables i in 

district j. The positive values relating to district's score show high level of development and negative values the low 

level of development.  

The correlation co-efficient between livestock and levels of development has been computed on the basis of the 

Karl Pearson's correlation co-efficient (r) method.  

 

2.1. Trends of Rural Non-Agricultural Working Force  
Uttar Pradesh is predominantly an agricultural state. Hence, a very low percentage of rural workforce is 

engaged in the non-agricultural sector. The share of rural workforce in non-agricultural sector has increased 

considerably over the decades at national level as well as state of Uttar Pradesh. Table 2 reveals that the 

percentage of non-agricultural workforce improved from 12.30 per cent in 1971 to 24.33 per cent in 2001 

and rose further to 27.85 per cent in 2011 in the state. At the national level, around one-seventh of the rural 

workforce was engaged in non-agricultural sector in 1971 which is increased by 25 per cent points in 2011 

(39.32 per cent). During 1981-2011, the percentage of rural non-agricultural workforce has been gradually 

increased by nearly 20 per cent points both in the state and country.  

 
Table-2.Trends of Rural Non-Agricultural Workforce (Main), Uttar Pradesh and India, 1971-2011 

Census 

Year 

Uttar Pradesh India 

Rural Male Female Rural Male Female 

1971 12.30 12.90 7.40 15.20 16.30 10.6 

1981 13.68 14.11 9.55 19.02 20.84 12.73 

1991 15.52 16.54 8.62 19.97 22.45 12.59 

2001 24.33 24.63 22.63 29.37 31.66 22.95 

2011 27.85 26.27 35.52 39.32 38.18 40.84 
Source: Census of India, 1981, 1991, 2001 and 2011. 

 

When the share is computed for male and female workforce separately, it is found that the share in rural 

non-agricultural workforce has increased and the difference between sexes remained more or less similar. 

The percentage of male workforce in non-agricultural sector has increased during the period 1971-2011 from 

16.3 to 38.18 per cent and from to 12.90 to 26.27 per cent respectively in India and Uttar Pradesh. The 

female workforce in Uttar Pradesh increased continuously from 7.40 per cent in 1971 to 35.52 per cent in 

2011. India has also made a remarkable increase in female workforce during the same period.    



Asian Review of Environmental and Earth Sciences, 2015, 2(2): 35-41 

 

 

 

 

38 

 

In the case of both male and female rural non-agricultural workforce the percentage was almost static 

during 1981-2011, but there has been a significant increase during the period 2001-2011 both in the country 

and state. However, the inequality in the percentage of male and female rural non-agricultural workforce 

remained more or less same during the reference period (Table-2).    

 

 
Fig-2. Based on Census of India, 1981, 1991 , 2001 and 2011. 

 

2.2. Rural Non-Agricultural Workforce (Main) 
The regional distribution of main non-agricultural workforce during the decade 2001-2011 is 

observed to be wide with maximum percentage of 57.51 in SantRavidas Nagar and a minimum of 12.80 

in Badaun district giving an average of 27.85 per cent for the state. The distribution of the percentage of 

main non-agricultural workforce in rural population among the districts may conveniently be arranged 

into five grades of below 16, 16-24, 24-32, 32-40, and 40 and over (Table 3). 

 
Table-3.Category wise Distribution of Rural Non-Agricultural Work Force, Uttar Pradesh, 2011 

Category % age No. of Districts % to total Districts 

Very High 40 and Over 12 16.90 

High 32-40 13 18.31 

Medium 24-32 15 21.13 

Low 16-24 22 30.98 

Very Low Below 16 99 12.68 

                                                                71 100.00 
Source: Census of India, 1981, 1991 and 2001. 

 

Considering the above mentioned five grades separately, we find that the districts under the first grade of 

40 and over form three small but identifiable regions (Fig. 3). Two of them are found in the eastern region 

and one in the western plain region. About 18 per cent districts of the state lies under the high percentage 

grade and are found in two pockets. One region, relatively big in size occurs in the in the south-western part 

includes Bulandshahr, Hathras, Aligarh, Agra, Firozabad and Mathura districts, second lies in the north-

western part comprising the districts of Saharanpur, Bijnor and Muzaffarnagar. The districts with percentage 

very close to the state average (27.85 per cent) occupying about 21 cent districts are scatteredly distributed 

over the state and fail to form a notable region in the state. About 31 per cent districts falling under the low 

percentage grade constitute a longitudinal zone which extends from Siddhrathnagar in the east to Jhansi in 

the south and Etah in the west. Only nine districts fall under the very low percentage grade constitute a 

continuous prominent region in the north-eastern and western parts which runs from Balrampur in the east to 

Budaun in the west. The other two districts of the same grade are detached from the main region. 

The general picture emerged from this discussion is that there is a gradual increase of main workforce in 

non-agricultural sector from north-western to south-eastern parts of Uttar Pradesh.  

 

2.3. Male Non-Agricultural Workforce 
The regional distribution of male main workforce in non-agricultural sector of rural population is very 

similar to that of the main non-agricultural workforce.  

Among the districts its proportion varies from 10.16 per cent in Budaun to 59.34 per cent in SantRavidas 

Nagar districts with a state average of 26.27 per cent.  

 
Table-4. Categorywise Distribution of Male Non-Agricultural Workforce, Uttar Pradesh, 2011 

Category % age No. of Districts % to total Districts 

Very High 40 and Over 10 14.08 

High 32-40 11 15.49 

Medium 24-32 18 25.35 

Low 16-24 16 22.54 

Very Low Below 16 16 22.54 

                                                           71 100.00 
Source: Census of India, 1981, 1991 and 2001. 



Asian Review of Environmental and Earth Sciences, 2015, 2(2): 35-41 

 

 

 

 

39 

 

The graded distribution of male main workforce in non-agricultural sectors of rural population as 

depicted in Fig. 4 shows that about one-fourth districts of the state fall under very low percentage grade 

(below 16 per cent) form a prominent region in the north-eastern and western part of the state. The other 

districts of similar grade are scattered too sporadically to form a distinct region. On the other hand, there are 

four small but definable regions of high percentage grade found in the eastern and western parts of the state. 

Eighteen districts of the state fall under the grade of very close to the state average, eleven of them form a 

notable region in the eastern part of the study area. The other districts of the same grade are scattered and do 

not form any notable region. About 23 per cent districts fall under the low grade and form a number of small 

pockets of which a prominent region occurs in the south-western part. There are three regions of high 

percentage grade (32-40 per cent) which combinedly cover more than one-fifth of the districts of the state 

form a number of identifiable regions. Among them one relatively big size occur in the southern part of the 

state. The general pattern is marked by gradual increase from west to south and to east in Uttar Pradesh.   

 

2.4. Female Non-Agricultural Work Force 
The pattern of regional distribution of female main non-agricultural workforce is quite different from that 

of general and male rural workforce. It varies from 12.82 per cent to 61.36 per cent giving an average of 

35.52 per cent for the state. 

 
Table-5. Categorywise Distribution of Female Main Non-Agricultural Workforce, Uttar Pradesh, 2011 

Category % age No. of Districts % to total Districts 

Very High 50 and Over 14 19.72 

High 42-50 14 19.72 

Medium 34-42 14 19.72 

Low 26-34 13 18.30 

Very Low Below 26 16 22.54 

                                                  71 100.00 

 

Fig. 5 shows that the districts falling under the very high percentage grade of 50 and over constitute a 

longitudinal belt which extends from Muzaffarnagar in the north to Agra in the south. The other districts of 

same grade are too scattered to constitute a single continuous region in the state. On the contrary, the 

maximum number of districts (16) fall under the very low grade (below 26 per cent) and mainly concentrated 

in the eastern and southern parts which are separated by the region of high slab. About 20 per cent districts 

fall under the grade 42-50 per cent. These districts are grouped into a number of small regions of which the 

most prominent one occurs in the extreme eastern part comprising Ballia, Mau and Deoria districts. The 

medium grade districts (34-42 per cent) constitute two discontinuous regions: one region, relatively large in 

size lies in the north-western part and the other in the eastern part. The low percentage grade is observed in 

the eastern part with a compact region comprised of eight districts. The other districts of this grade fail to 

form a notable region in the study area.  

The overall distribution depicts that there is a gradual decrease of female main workforce in non-

agricultural sectors from west to south-east.    

 

2.5. The Simple Correlation between Rural Non-Agricultural Workforce and Independent Variables 
In the present investigation, relationships have been sought between rural non-agricultural workforce and thirty 

nine variables of the districts of Uttar Pradesh.  Selection of each variable is based on an ability to develop a rational 

hypothesis of relationship between the variables and non-agricultural workforce.  

Table 1 reveals that sixteen variables out of thirty nine are significant at confidence level of 99 per cent, though 

the actual magnitudes of their coefficients are different. X1 (literacy Rate, r=0.521), X2 (Rural Literacy Rate, 

r=0.511), X4 (Male Literacy Rate, r=0.591), X5 (Female Literacy Rate, r=0.440), X7 (Educational Institute/ Student 

Ratio, r=0.568), X10 (Percentage of Urban Population, r=0.391), X12 (Population Density, r=0.731), X19 (No. of 

Persons Engaged in Registered Factories / Lakh Population, r=0.399), X20 (Employees in Public Sectors (Govt) / 

Lakh Population, r=0.306), X27 (Percentage of Net Irrigated Area to Net Sown Area, r=0.387) and X36 (Percentage of 

Villages with Linked Road, r=0.335) are found to have direct relationship with rural non-agricultural workforce (Y1). 

The variables X11 (Percentage of Rural Population, r= -0.382), X22 (Land Utilization, r= -0.401), X23 (Total Cropped 

Area, r= - 0.367), X28 (Person / Cultivated Area, r= -0.5.67) and X38 (No. of Post Office/ lakh Population, r= -0.351) 

turn out to have a significant inverse relationship with Y1. The variables which are significant and well above the 

stipulatedly acceptable 95 per cent level of confidence are: X8, X20, X31, X33 and X34. Only two variables have inverse 

relationship with Y1. Table also shows that male rural non-agricultural workforce (Y2) has similar reciprocal 

relationship between the same variables as has been found for Y1.  

Only ten variables are highly significant at 99 per cent level of confidence in their relationship with female non-

agricultural workforce (Y3). Among them six variables namely: X1, X2, X5, X10, X12 and X27 are positively associated 

with Y3. Remaining four variables X11 (Percentage of Rural Population, r= -0.373), X28 (Person / Cultivated Area, r= -

0.417), X34 (No. of Doctors per Lakh Population, r= -0.390) and X38 (No. of Post Office/ lakh Population, r= -0.372) 

are negatively associated with Y3.  Six variables are namely: X4, X13, X16, X19, X26, and X36   are significant at 95 per cent 

level of confidence except X13 and X16. Remaining four variables are positively associated with Y3.  

This explanation leads to conclusion that agriculture, population growth and health facilities are the chief 

determinants but the magnitudes of their effects are dissimilar. 

 

 

 



Asian Review of Environmental and Earth Sciences, 2015, 2(2): 35-41 

 

 

 

 

40 

 

Table-1. Co-efficient of Correlation for Non-Agricultural Workforce (Total, Male and Female), and its Correlates Uttar Pradesh, 2001 

 

Variables 

 

Correlates 

Correlation  of Coefficient  Non-Agricultural 

Workforce 

Y1 Y2 Y3 

X1 Literacy Rate  0.521* 0.501* 0.356* 

X2 Rural Literacy Rate  0.511* 0.490* 0.366* 

X3 Urban Literacy Rate  0.167 0.197 -0.201 

X4 Male Literacy Rate  0.591* 0.587* 0.277** 

X5 Female Literacy Rate  0.440* 0.407* 0.397* 

X6 Teacher/Pupil Ratio  0.171 0.193 0.005 

X7 Educational Institute/ Student Ratio  0.568* 0.586* 0.202 

X8 Teacher/Student Ratio  0.289** 0.308* 0.085 

X9 Population Growth (1991-2001)  0.210 0.207 0.124 

X10 Percentage of Urban Population  0.391* 0.354* 0.380* 

X11 Percentage of Rural Population  -0.382* -0.347* -0.373* 

X12 Population Density  0.713* 0.702* 0.355* 

X13 Sex Ratio  0.185 0.234 -0.273** 

X14 Percentage of Hindu Population to total Pop. 0.058 0.082 -0.100 

X15 Percentage of Muslim Population to total Pop. -0.022 -0.056 0.173 

X16 Scheduled Caste Pop to Total Population  -0.131 -0.106 -0.236** 

X17 Population below Poverty Line  0.065 0.078 -0.077 

X18 Per Capita Income (at Current Price)  0.216 0.187 0.227 

X19 No. of Persons Engaged in Registered Factories / 

Lakh Population  

0.399* 0.369* 0.287** 

X20 Employees in Public Sectors (Govt) / Lakh Pop. 0.306** 0.307* 0.116 

X21 No. of Livestock Population / Lakh Population  -0.114 -0.108 -0.099 

X22 Land Utilization  -0.401* -0.391* -0.217 

X23 Total Cropped Area  -0.367* -0.379* -0.046 

X24 %tage of Net Sown Area to total Reporting Area  -0.062 -0.033 -0.190 

X25 Area Sown more than once  -0.218 -0.238** 0.104 

X26 Cropping Intensity  0.106 0.077 0.291** 

X27 Percentage of Net Irrigated Area to Net Sown Area  0.387* 0.333* 0.602* 

X28 Person / Cultivated Area  -0.567* -0.543* -0.417* 

X29 Average Size of Land Holding  -0.186 -0.193 -0.071 

X30 No. of Tractors / 1000 ha. of Cultivated Land  0.068 0.044 0.132 

X31 Food Production (mt)  -0.286** -0.295** 0.022 

X32 No. of Medical(Allopathic) Institution/ lakh Pop. 0.151 0.152 0.090 

X33 No. of Beds in Hospitals/ Dispensaries (Allopathic)/ 

Lakh Population  

0.296** 0.292** 0.152 

X34 No. of Doctors per Lakh Population  -0.266** -0.227 -0.390* 

X35 No. of Family Welfare Clinic / Centres/ Lakh Pop -0.078 -0.054 -0.146 

X36 Percentage of Villages with Linked Road  0.335* 0.309* 0.253** 

X37 Percentage of Electrified Villages to Inhabitant 

Villages  

0.127 0.143 0.002 

X38 No. of Post Office/ lakh Population  -0.351* -0.329* -0.372* 

X39 No. of Telegraph Offices / Telephone Exchange 

/Lakh Population  

0.038 0.047 -0.013 

* Significant at 1% level of confidence.   ** Significant at 5 % level of confidence. 

 

3. Conclusion 
The percentage of non-agricultural workforce improved from 12.3 per cent in 1971 to 13.78 per cent in 

1981 and rose further to 27.85 per cent in 2011 in the state. In the case of both male and female rural non-

agricultural work force, the percentage was almost static during 1981-2011, but there has been a significant 

increase during the period 2001-2011 both in the country and state. The regional variations in the distribution of 

workforce in rural non-agricultural sectors are quite notable. The general picture emerged that there is a gradual 

increase of main workforce in non-agricultural sector from north-western to south-eastern parts of Uttar 

Pradesh. The distribution of female main workforce in non-agricultural workforce depicts that there is a 

gradual decrease from west to south-east. The statistical analysis leads to conclusion that agriculture, population 

growth and health facilities are the chief determinants but the magnitudes of their effects are dissimilar.  

In the light of the above discussion the effort should be made for development of less developed areas, so that 

they may come up at par with developed areas, and the concept of planning with social justice proves successfully.  

 

References 
[1] Census of India, "Series 22, U.P," Final Report, Population Table, Lucknow, 2004, 2001. 

[2] Mellor and U. Lele, "Growth linkages of the new foodgrain technologies," Indian Journal of Agricultural Economics, vol. 28, pp. 33-

55, 1973. 

[3] W. Mellor John, The new economics of growth-a strategy for India and the developing world, a twentieth century fund study. Ithaca, 

New York: Cornell University Press, 1976. 

[4] J. Unni, "Regional variation in rural non-agricultural employment: An exploratory analysis," Economic and Political Weekly, vol. 26, 

pp. 109-122, 1991. 

[5] A. Vaidyanathan, "Labour use in rural India: A study of spatial and temporal variations," Economic and Political Weekly, vol. 21, pp. 

A130-146, 1986. 



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41 

 

[6] M. Hossain, "Credit for alleviation of rural poverty: The Grameen bank in Bangladesh," International Food Policy Research Institute 

(IFPRI), Research Report 65. Washington, DC1988. 

 

 
  

Fig-3. Based on Census of India, 2011                                                            Fig-4. Based on Census of India, 2011                                                          Fig-5.  Based on Census of India, 2011                                                             

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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