DDI-KHM-NIS-CSES-2017-v1.0
Saint Lundy
2023-06-02
NADA
version 1.0 (June 2023) -The first documentation of the survey
Cambodia Socio-Economic Survey 2017
CSES 2017
KHM-NIS-CSES-2017-v1.0
National Institute of Statistics
Statistics Sweden
(c) 2023, National Institute of Statistics, Cambodia
NADA
Swedish International Development Agency
Royal Governmnet of Cambodia
Director, Demographic Statistics, Census and Survey Department
Data User Service Center
Director, ICT Department
Socio-Economic/Monitoring Survey [hh/sems]
The Cambodian Socio-Economic Survey 2012 (CSES) is the eleventh survey collecting data from household and individuals in Cambodia on different areas relating to poverty. The survey is conducted by the National Institute of Statistics (NIS) of the Ministry of Planning (MOP). The first Socio-Economic Survey was conducted in 1994 (CSES 1994). Since then the CSES has been conducted in 1996, 1997, 1999 and 2004. Since 2007 NIS conducts the CSES annually.
The CSES2004 was the fifth survey that was conducted and as a countrywide sample survey of villages and households in Cambodia. CSES2004 was the first survey with a collection of income and receipts, expenditure and consumption of own production in a diary were daily transactions are reported. The sample size in CSES2004 was 1,000 households every month. Since 2007 the Socio-Economic Survey is conducted every year with a sample size of 300 households every month (3,600 household annually). The annual surveys are undertaken as a part of the project, “Capacity Development for Socio-Economic Surveys and Planning” of the Royal Government of Cambodia. This project is supported and financed by Sida (The Swedish International Development Cooperation Agency). In 2009 the CSES was similar to CSES 2004 with a sample size of 1,000 households every month (12,000 households on annual basis).
For 2010 and 2011 the sample size was again brought down to 3,600. CSES 2012 had a slightly bigger sample size of 3,840.
The earlier CSES rounds have all made it possible to report sets of indicators on 8 main areas of social concern
• Demographic characteristics
• Housing
• Agriculture
• Education
• Labour Force
• Health and Nutrition
• Victimization
• Household Income and Consumption
In CSES 2010 some changes have been introduced in the household questionnaire. Most changes were minor except for the questions on current economic activity.
Version 1.0. - Edited data for internal use only
Living conditions in Cambodia have improved considerably between 1993 and 2004, the period
covered by the Cambodia Socioeconomic Surveys (CSES). Life expectancy at birth increased
from 52 to 60 years for men and from 56 to 65 years for women, mainly by rapidly
declining infant and child mortality. Material living conditions improved substantially according
to indicators on housing conditions and possession of durables. The differences in living
conditions are large between urban and rural areas. The standard of living is better in Phnom
Penh in almost all respects than in other urban areas, which in turn are better than the rural
areas. The present report cover main aspects on selected important subject matter areas.
Separate reports on poverty will be available in the last quarter of 2005.
The National Institute of Statistics (NIS) of the Ministry of Planning (MoP) conducted the
Cambodia Socio-Economic Survey 2003-2004 (CSES 2004). The UNDP, The World Bank
and the Swedish International Development Agency (Sida) sponsor the survey. Statistics
Sweden has provided the overall technical assistance. This is the fifth Cambodia Socio- Economic
Survey (CSES) conducted by the National Institute of Statistics, following the Socio
Economic Surveys in 1993/94, 1996, 1997, and 1999.
All information collected in CSES 2004 is strictly confidential and will be used for statistical
purpose only, in accordance with the 2005 Cambodian Law on Statistics.
The CSES 2004 enjoyed almost a 100 percent response rate. The high response rate together
with close and systematic fieldwork supervision by the core group members were a major
contribution for achieving high quality survey results.
Agriculture & Rural Development
Food (production, crisis)
Land (policy, resource management)
Coal
Electricity
Oil & Gas
Migration & Remittances
Health
HIV/AIDS
Malaria
Mental Health
Nutrition
Tuberculosis
Infrastructure
Transport
Water
Poverty
Private Sector Development
Public Sector
Children & Youth
Gender
Urban Development
The Cambodia Socio-Economic Survey (CSES) asks questions to a country wide sample of households and household members about housing conditions, education, economic activities, household production and income, household level and structure of consumption, health, victimization, etc. There are also questions related to people in the labour force, e.g. labour force participation.
Poverty reduction is a major commitment by the Royal Government of Cambodia. Accurate statistical information about the living standards of the population and the extent of poverty is an essential instrument to assist the Government in diagnosing the problems, in designing effective policies for reducing poverty and in monitoring and evaluating the progress of poverty reduction. The Millennium Development Goals (MDG) has been adopted by the Royal Government of Cambodia and a National Strategic Development Plan (NSDP) has been developed. The MDGs are also incorporated into the “Rectangular Strategy of Cambodia”.
Cambodia is still a predominantly rural and agricultural society. The vast majority of the population get their subsistence in households as self-employed in agriculture. The level of living is determined by the household's command over labour and resources for own-production in terms of land and livestock for agricultural activities, equipments and tools for fishing, forestry and construction activities and income-earning activities in the informal and formal sector. The CSES aims to estimate household income and consumption/expenditure as well as a number of other household and individual characteristics.
The main objective of the survey is to collect statistical information about living conditions of the Cambodian population and the extent of poverty. The survey can be used for identifying problems and making decisions based on statistical data.
The main user is the Royal Government of Cambodia (RGC) as the survey supports monitoring the National Strategic Development Plan (NSDP) by different socio-economic indicators. Other users are university researchers, analysts, international organizations e.g. the World Bank and NGO’s. The World Bank has published a report on poverty profile and social indicators using CSES 2007 data . In this regard, the CSES continues to serve all stakeholders involved as essential instruments in order to assist in diagnosing the problems and designing their most effective policies. The CSES micro data at NIS is available for research and analysis by external researchers after approval by Senior Minister of Planning. The interesting research questions that could be put to the data are many; NIS welcomes new research based on CSES data.
General Objectives:
CSES 2013 will continue the work started through CSES 2004 and the annual CSES 2007 to 2014 and would primarily aim at producing information needed for planning and policy making for reduction of poverty in Cambodia. Reduction of poverty has been given high priority in Cambodia's National Strategic Development Plan (NSDP 2009-2013). In addition to this, the survey data help in various other ways in developmental planning and policy making in the country. They would also prove useful for the production of National Accounts in Cambodia.
A long-term objective of the entire project is to build national capability in NIS for conducting socio-economic surveys and for utilizing survey data for planning for national development and social welfare.
Specific Objectives:
Among specific objectives, the following deserve special mention:
1) Obtain data on infrastructural facilities in villages, especially facilities for schooling and health care and associated problems.
2) Obtain data on retail prices of selected food, non-food and medicine items prevailing in the villages.
3) Collect data on utilization of education, housing and land ownership
4) Collect data on household assets and outstanding loans.
5) Collect data on household's construction activities.
6) Collect information on maternal health, child health/care.
7) Collect information on health care seeking and expenditure of the household members related to illness, injury and disability.
8) Collect information on economic activities including the economic activities for children aged between 5 and 17 years.
9) Collect information on victimization by the household
10) Collect information on the presence of the household members.
Cambodia
National Phnom Penh / Other Urban / Other Rural
Households
Individuals
All resident households in Cambodia
Sample survey data [ssd]
Briefly the CSES rounds have all made it possible to report sets of indicators on 8 main areas of social concern:
1. Demographic characteristics
2. Housing
3. Agriculture
4. Education
5. Labour Force
6. Health and Nutrition
7. Victimization
8. Household Income and Consumption
National Institute of Statistics
The sampling design in the CSES 2013 survey is a three-stage design. In stage one a sample of villages is selected, in stage two an Enumeration Area (EA) is selected from each village selected in stage one, and in stage three a sample of households is selected from each EA selected in stage two.
Stage 1: A random sample of PSUs was selected from each stratum. The sampling method was systematic PPS (PPS=sampling with probability proportional to size). The size measure used was the number of households in the PSU according to the sampling frame.
Stage 2. One EA was selected by Simple Random Sampling (SRS), in each village selected in stage 1.
Stage 3. In each selected EA a sample of 10 households was selected. The selection of households was done in the field by the supervisors/interviewers. All households in selected EAs were listed by the enumerator. The sample of households was then selected from the list by systematic sampling with a random start (the start value controlled by NIS).
For the details of sample selection please refer to the document "Process Description: Design and Select the Sample for CSES 2013"
Face-to-face [f2f]
Three different questionnaires or forms were used in the survey:
Form 1: Household listing sheets to be used in the sampling procedure in the enumeration areas.
Form 2: Village questionnaire answered by the village leader about economy and infrastructure, crop production, health, education, retail prices and sales prices of agriculture, employment and wages, and recruitment of children for work outside the village.
Form 3: Household questionnaire with questions for each household member, including modules on migration, education and literacy, housing conditions, crop production, household liabilities, durable goods, construction activities, nutrition, fertility and child care, child feeding and vaccination, health of children, mortality, current economic activity, health and illness, smoking, HIV/AIDS awareness, and victimization.
The interviewer is responsible for filling up Form 1 and Form 3 to respondents. . For Form 2, the supervisors will be asked to canvass this form. In case that the supervisors are absent for any reason, the interviewers may be also asked to help fill up this form (Form 2).
For the CSES 2012 a new CSES survey sample and questionnaire design was implemented. The data collection and field work have therefore been monitored closely. especially in the beginning of the year. The changes caused only minor problems in the data collection. The fieldwork operations and logistics have been running very well. A training on sub-national level for all supervisors and enumerators was held in the beginning of the year. The training was paid for by local cost. Now NIS has its own capacity to carry out the out the data collection process, but is financially supported diretly by Sida. The L T As have participated in a few fieldtrips to learn more about the data collection and to check whether the work is carried out as planned. The Subject Matter Staff (SMS) have also participated more in the field work than previous years. As a result, the enumerators' undrstanding of the questions ha improved and at the same time tha SMS has received information about possible questionnaire improvements. All these activities will lead to better quality in the data collection.
Interviewers and supervisors were initially divided into teams of five persons (one supervisor and four interviewers), making in total 50 teams for the fieldwork. Each month, 25 teams were working in the field with a workload of 10 households per interviewer. In urban areas, 4 PSUs were allocated to one team while in rural areas, 2 PSUs were allocated. The fieldwork plan was designed in order to gather around 60 households monthly per team.
For a given month, the team arrived in the village three days before the first day of the month to tend to preparatory tasks like discussing with village authorities, filling out the Household Listing Form, and thereafter sample those households to be interviewed.
The Village Form was filled out by the supervisor.
The Household Questionnaire had 16 sections that were filled out by the interviewer during the first visit to the household, and in the following four weeks according to the following scheme:
FIRST VISIT: Initial visit
WEEK 1: Education and literacy, Housing
WEEK 2: Household economic activities, Household liabilities, Household income from other sources, and other expenditures (partial non-food recall)
WEEK 3: Durable goods and other expenses, Construction activities in the past 12 months, Nutrition, Fertility and child care, Mortality
WEEK 4: Health check of children, Current economic activity, Health, HIV/AIDS, Victimization
Once the month ended, the team went back to the NIS headquarters in Phnom Penh.
Questionnaires from the same PSU was delivered to the Data Management team by the supervisor in a packet including all of the documents used and produced in the fieldwork, including maps, enumeration lists, questionnaires, diaries, etc. Before going to the villages, teams were briefed and introduced to minor adjustments of the interviewing procedure that had to be made as a result of monitoring activities and feed-back from the data processing.
The fieldwork started in Janury 2010 and was scheduled to end in December 2010.
Fifty (50) supervisors and 200 enumerators were recruited by NIS and trained for the fieldwork. The training took place in Phnom Penh and lasted three weeks for supervisors and two weeks for enumerators. Before the start of each fieldwork month, there were briefing and retraining sessions. Each fieldwork team included one supervisor and four enumerators. In urban areas one enumerator was responsible for one PSU and for interviewing 10 households, while in rural areas two enumerators were responsible for one PSU and for interviewing 20 households. In all, 125 enumerators and supervisors, divided into 25 teams, were carrying out the fieldwork at the same time. Two such team groups were formed and each team group alternated monthly.
Enumerator and Supervisor training
Initial training was provided during nine days for a group of 20-30 staff (not all were attending all the time). This training included a translation into Khmer of selected parts of the questionnaire, and a field test in a village outside Phnom Penh where the participants performed test interviews in 16 households. The experiences from this exercise were followed up during the course. The course also included general aspects on survey methodology and ways of controlling for errors. Many of the findings from this training served as input to later stages.
Prior to the start of the fieldwork intensive interviewer and supervisor training was carried out. The 200 interviewers and 50 supervisors recruited were split into two groups, each consisting of 100 interviewers and 25 supervisors. The two groups later alternated so that the first group did their fieldwork during odd survey months (i.e. November, January, March …) while the second group covered the even survey months (i.e. February, April …).
The training was designed with this in mind. Training of the first group was provided in English by a WB consultant and simultaneously interpreted in Khmer by the appointed NIS officer. The second group was trained by NIS only.
Common was that the supervisors were first trained during one week, and then jointly with their interviewers for two weeks. Before all fieldwork months the group in turn was gathered at the NIS to walk through the questionnaire and manuals in order to correct errors that were detected during the briefing sessions or the monitoring operations, and to learn how to handle any changes that were introduced to the survey instruments.
Any survey of the CSES dimensions needs a comprehensive system for quality management and monitoring. Only then can deviations from the target be tended to in time to avoid shortfalls. Interviewers and supervisors were initially divided into teams of five persons (one supervisor and four interviewers), making in total 50 teams for the fieldwork.
The CSES management group within NIS therefore set up a meticulous monitoring scheme to be implemented from the very beginning. The monitoring team did include at least five NIS staff. Commonly the DG of NIS has spent one week monthly while other top ranked NIS officers have been out for two weeks on average. At times other officials from NIS or the Ministry have participated.
Inspections entailed both announced and unannounced visits. Every team was visited at least twice during their fieldwork periods. The purposes of these visits were several. One important purpose was to get a disciplinary effect on supervisors and enumerators from their knowledge that such inspections must be expected throughout the fieldwork month, including also at the very end of the diary month. Also important was to give feedback and encouragement to fieldworkers and to complement training by advice and suggestions and to sort out any problem that had arisen in the course of fieldwork in the village. Another area of concern was to ensure that the household listing and sampling was done in accordance with the procedures that were devised.
In general, a supervisor is assigned to supervise several enumerators during the field operations. The major duties and responsibilities of a supervisor in relation to your work as enumerator are the following:
1.Your supervisor is responsible for ensuring that all the enumerators under him/her do the listing and enumeration work satisfactorily in time. He/she plans and organises the work in his/her area of supervision and sees to it that everything is conducted efficiently and completely.
2.Your supervisor is required to check your work as enumeration proceeds to make sure that you have done your work correctly and have followed the standard procedures laid down by the NIS. He will check all the questionnaires filled by you. You must show and submit your work to him/her and report to him/her the progress of your work and avoid committing the same errors again.
3.As part of his/her supervisory functions, your supervisor will visit the enumeration area assigned to you to check that you have completely covered your area in the listing operation. He may observe you when you are interviewing some respondents. He/she will also re-interview some of the households you have interviewed to check whether the information you have obtained are valid.
4.The supervisor may provide to you all necessary field supplies and questionnaires etc. As soon as you complete the enumeration, you must return all unused supplies and materials to him/her. Otherwise, you will not be given clearance to collect your final service fee payment at the end of your work.
The supervisor serves as a link between you and higher officials of the NIS. Just as he/she informs you of the instructions from NIS officials, you must inform him/her of any problem or difficulty that you experience. Seek his/her advice on how to deal with problems in the field as often as needed. He may help you establish contact with village leaders, commune leaders, and other representatives of the village.
Please refer to Technical Douments for details.
Sampling weights were computed for every stage. First stage weights (W1) were assigned to selected villages. With the PPS procedure employed villages were selected with different probabilities. Large villages are over-represented in the sample and, small villages are under-represented. In the calculattion of results (estimates) from the sample it must be ensured that there is compensate for this misrepresentation. The way to do that is to assign sampling weights to the selected villages (PSUs). The over-represented large villages should be down-weighted and the under-represented small villages should be up-weighted.
The second stage sampling weights W2 are calculated as the number of households in the village (according to the chairman) over the number of sampled households (10).
The household sampling weights (Wprel) are calculated by multiplying W1 by W2. All the sampled households in the village get the same household weight. These weights were then calibrated.
For a detailed discussion of the calculation of weights please refer to the document "Process Description: Design the Estimation Procedure and Calculate Sampling Weights for CSES 2013".
The NIS team commenced their work of checking and coding and coding in begining of February after the first month of fieldwork was completed. Supervisors from the field delivered questionaires to NIS. Sida project expert and NIS Survey Manager helped in solving relevant matters that become apparent when reviewing questionires on delivery.
The CSES 2013 enjoyed almost a 100 percent response rate. The high response rate together with close and systematic fieldwork supervision by the core group members were a major contribution for achieving high quality survey results.
In order to provide a basis for assessing the reliability or precision of CSES estimates, the estimation of the magnitude of sampling error in the survey data were computed. Since most of the estimates from the survey are in the form of weighted ratios, thus variances for ratio estimates are computed.
The Coefficients of Variation (CV) on national level estimates are generally below 4 percent. The exception is the CV for total value of assets where there are rather high CVs especially in the urban areas, which should be expected.
The CVs are somewhat higher in the urban and rural domains but still generally below 7 percent. For the five zones, the average CVs are in the range 5 to 13 percent with a few exceptions where the CVs are above 20 percent. For provinces the CVs for food consumption are 9 percent on average.
The sample take within Primary Sampling Units (PSU) was set to 10 households per PSU in the CSES 1999. When data on variances became available, it was possible to make crude calculations of the optimal sample take within PSU. Calculations on some of the central estimates in the CSES 1999 show that the design effects in most cases are in the range 1 to 5.
Intra-cluster correlation coefficients have been calculated based on the design effects. These correlation coefficients are somewhat high. The reason is that the characteristics that are measured tend to be concentrated (clustered) within the PSUs. The optimal sample size within PSUs under different assumptions on cost ratios and intra-cluster correlation coefficients was then calculated. The cost ratio is the average cost for adding a village to the sample divided by the average cost of including an extra household in the sample. In the CSES, it was chosen to adopt a fairly low cost ratio due to the fact that the interview time per household is long. Under this assumption the optimal sample size is probably around 10 households per village for many of the CSES indicators.
The main objective of the survey is to collect accurate statistical information about living
standards of the population and the extent of poverty as an essential instrument for identifying
problems and designing effective policies for reducing poverty, and in evaluating the progress
of poverty reduction.
Like the four previous survey rounds six main areas of social concern have been surveyed:
- Household level and the structure of consumption including poverty and nutrition
- Household production and cash income
- Education and access to schooling
- Health and access to medical care
- Housing and amenities
- Family and social relations
The CSES 2004 was carried out on a nationwide representative sample of 15,000 households
within 900 Primary Sampling Units (PSU) corresponding to 867 villages. It was designed to
provide information on social and economic conditions of households for policy studies on
poverty, household production, final consumption for the National Accounts, and weights for
the Consumer Price Index (CPI). It was divided into 15 monthly samples of 1,000 households
each in 60 PSUs from November-03 till January-05.
Using data for the 15 months, reliable estimates were produced for 11 individual provinces;
Bantey Meanchy, Battambang, Kampong Cham, Kampong Speu, Kampong Thom, Kandal,
Phnom Penh, Pery Veng, Siem Reap, Svay Rieng and Takeo. The other 13 provinces were
grouped according to zone:
Tonle Sap provinces: Kampong Chhnang and Pursat
Coastal provinces: Kampot, Sihanouk Ville, Kaoh Kong and Krong Keb
Plateau/Mountain: Kratie, Steung Treng, Rattanakiri, Mondol Kiri, Preah Vihear, Oddor
Meanchey, and Krong Pailin
The 1998 Population Census, carried out by NIS, was used as sampling frame in the sampling
design of the CSES 2004.
The survey covers private households with one or more persons. Nomadic households are
included in principal. Excluded are:
- People living in institutions (such as long term hospitals, prisons, monasteries, military
quarters)
- Diplomatic and UN households in the country
- Other foreigners in the country
- Armed forces residing in military bases
All information collected in the survey from village leaders and other representatives of sample villages and from sample households will be treated as strictly confidential and used for statistical purposes in social and economic planning. Information supplied by any person will not be used against him for taxation, investigation or any other legal purpose.
Director General
Cambodia Socio-Economic Survey 2012 (CSES 2012), National Institute of Statistics, Ministry of Planning, Cambodia
1. The data and other materials will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the National Institute of Statistics.
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the National Institute of Statistics.
4. No attempt will be made to produce links among datasets provided by the National Institute of Statistics, or among data from the National Institute of Statistics and other datasets that could identify individuals or organizations.
5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the National Institute of Statistics will cite the source of data in accordance with the Citation Requirement provided with each dataset.
6. An electronic copy of all reports and publications based on the requested data will be sent to the National Institute of Statistics.
The user of the data acknowledges that the National Institute of Statistics, Cambodia bears no responsibility for use of the data or for interpretations or inferences based upon such uses.
The main objective of the survey is to collect accurate statistical information about living
standards of the population and the extent of poverty as an essential instrument for identifying
problems and designing effective policies for reducing poverty, and in evaluating the progress
of poverty reduction.
Like the four previous survey rounds six main areas of social concern have been surveyed:
- Household level and the structure of consumption including poverty and nutrition
- Household production and cash income
- Education and access to schooling
- Health and access to medical care
- Housing and amenities
- Family and social relations
The CSES 2004 was carried out on a nationwide representative sample of 15,000 households
within 900 Primary Sampling Units (PSU) corresponding to 867 villages. It was designed to
provide information on social and economic conditions of households for policy studies on
poverty, household production, final consumption for the National Accounts, and weights for
the Consumer Price Index (CPI). It was divided into 15 monthly samples of 1,000 households
each in 60 PSUs from November-03 till January-05.
Using data for the 15 months, reliable estimates were produced for 11 individual provinces;
Bantey Meanchy, Battambang, Kampong Cham, Kampong Speu, Kampong Thom, Kandal,
Phnom Penh, Pery Veng, Siem Reap, Svay Rieng and Takeo. The other 13 provinces were
grouped according to zone:
Tonle Sap provinces: Kampong Chhnang and Pursat
Coastal provinces: Kampot, Sihanouk Ville, Kaoh Kong and Krong Keb
Plateau/Mountain: Kratie, Steung Treng, Rattanakiri, Mondol Kiri, Preah Vihear, Oddor
Meanchey, and Krong Pailin
The 1998 Population Census, carried out by NIS, was used as sampling frame in the sampling
design of the CSES 2004.
The survey covers private households with one or more persons. Nomadic households are
included in principal. Excluded are:
- People living in institutions (such as long term hospitals, prisons, monasteries, military
quarters)
- Diplomatic and UN households in the country
- Other foreigners in the country
- Armed forces residing in military bases
areainformation
384
16
hhconstruction
4232
25
hhcostcultivationcrops
2306
17
hhdurablegoods
39877
11
hhfishcultivation1
55
6
hhfishcultivation2
1573
3
hhfishcultivation3
2544
3
hhfoodconsumption
54814
5
hhforestryhunting1
5148
6
hhforestryhunting2
5296
3
hhhousing
3840
32
hhincomeothersource
98734
6
hhinventorycrops
1571
5
hhlandownership
3048
34
hhliabilities
1284
9
hhlivestock1
10133
14
hhlivestock2
3342
3
hhmembers
16909
21
hhnonagriculture1
1691
12
hhnonagriculture2
7723
8
hhnonagriculture3
2650
8
hhotherinfo
3840
44
hhproductioncrops
3295
12
hhrecallnonfood
40549
5
hhsalescrops
446
5
hhvulnerability
3840
60
households
3840
6
personecocurrent
15482
46
personeducation
16110
27
personhealthu2
540
19
personillness
16909
20
personmaternalhealth
1138
11
personviolencea
15482
4
weighthhpersons
3840
7
weighthhpersons
3840
7
weighthouseholds
3840
7
weightpersons
16909
7
384
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15004
15005
15006
15007
15008
15009
15010
15011
15012
16001
16002
16003
16004
16005
17001
17002
17003
17004
17005
17006
17007
17008
17009
17010
17011
17012
17013
17014
17015
17016
17017
17018
17019
17020
17021
17022
18001
18002
18003
18004
18005
18006
18007
19001
19002
19003
19004
20001
20002
20003
20004
20005
20006
20007
20008
20009
20010
20011
20012
20013
21001
21002
21003
21004
21005
21006
21007
21008
21009
21010
21011
21012
21013
21014
21015
21016
21017
21018
21019
21020
21021
21022
21023
21024
21025
22001
22002
22003
22004
22005
22006
23001
23002
24001
24002
384
01
02
03
04
05
06
07
08
09
10
12
13
14
15
16
17
18
19
20
21
22
23
24
384
Banteay Meanchey
Battambang
Kampong Cham
Kampong Chhnang
Kampong Speu
Kampong Thom
Kampot
Kandal
Kep
Koh Kong
Kratie
Oddar Meanchey
Pailin
Phnom Penh
Preah Sihanouk
Preah Vihear
Prey Veng
Pursat
Ratanak Kiri
Siemreap
Stung Treng
Svay Rieng
Takeo
Tboung Khmum
384
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
384
Aek Phnum
Angk Snuol
Angkor Borei
Angkor Chum
Aoral
Bakan
Banan
Banteay Ampil
Banteay Meas
Banteay Srei
Bar Kaev
Baray
Basedth
Batheay
Bati
Bavel
Borei Cholsar
Chamkar Leu
Chamkar Mon
Chantrea
Chetr Borei
Cheung Prey
Chhaeb
Chhloung
Chhuk
Chi Kraeng
Choam Khsant
Chol Kiri
Chong Kal
Dambae
Damnak Chang'aeur
Doun Penh
Kamchay Mear
Kampong Leaeng
Kampong Siem
Kampong Svay
Kampong Trabaek
Kampong Trach
Kampong Tralach
Kamrieng
Kandal Stueng
Kandieng
Kang Meas
Kanhchriech
Kaoh Andaet
Kaoh Soutin
Kaoh Thum
Khsach Kandal
Kien Svay
Kiri Vong
Kong Pisei
Koun Mom
Krakor
Kralanh
Krong Ban Lung
Krong Battambang
Krong Bavet
Krong Chbar Mon
Krong Doun Kaev
Krong Kaeb
Krong Kampong Cham
Krong Kampong Chhnang
Krong Kampot
Krong Kracheh
Krong Pailin
Krong Paoy Paet
Krong Preah Sihanouk
Krong Preah Vihear
Krong Prey Veng
Krong Pursat
Krong Samraong
Krong Serei Saophoan
Krong Siem Reab
Krong Stueng Saen
Krong Stueng Traeng
Krong Suong
Krong Svay Rieng
Krong Ta Khmau
Krouch Chhmar
Leuk Daek
Lvea Aem
Malai
Me Sang
Mean Chey
Memot
Mongkol Borei
Moung Ruessei
Odongk
Ou Reang Ov
Pea Reang
Peam Chor
Peam Ro
Phnom Proek
Phnum Kravanh
Phnum Sruoch
Ponhea Kraek
Popnhea Lueu
Pou Rieng
Pou Senchey
Prampir Meakkakra
Prasat Bakong
Prasat Ballangk
Preaek Prasab
Preah Netr Preah
Preah Sdach
Prey Chhor
Prey Kabbas
Prey Nob
Puok
Rolea B'ier
Romeas Haek
Rotonak Mondol
Ruessei Kaev
Rumduol
S'ang
Saensokh
Sameakki Mean Chey
Samlout
Samraong
Samraong Tong
Sandan
Sangkae
Santuk
Siem Bouk
Siem Pang
Snuol
Soutr Nikom
Srae Ambel
Srei Santhor
Srei Snam
Stoung
Stueng Trang
Svay Antor
Svay Chrum
Svay Leu
Svay Teab
Tboung Khmum
Thala Barivat
Thma Koul
Thma Puok
Thpong
Tram Kak
Treang
Tuek Chhou
Tuol Kouk
Veal Veaeng
384
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
21
384
Achar Leak
Akreiy Ksatv
Amleang
Andoung Khmer
Andoung Pou
Ang Ta Saom
Angk Prasat
Angk Sophy
Angkanh
Angkor Borei
Anlong Reab
Anlong Romiet
Anlong Samnar
Anlong Tnot
Anlong Vil
B'er
Baek Chan
Banteay Chhmar
Banteay Stoung
Baray
Basedth
Bavel
Boeng Bat Kandal
Boeng Beng
Boeng Kak Ti Muoy
Boeng Keng Kang Bei
Boeng Khyang
Boeng Kok
Boeng Nay
Boeng Prolit
Boeng Sala Khang Tboung
Boeng Salang
Boeng Thum
Boeng Trabaek
Boeng Tranh Khang Cheung
Boeng Tranh Khang Tboung
Boeng Tumpun
Bos Khnaor
Bos Leav
Chak Angrae Kraom
Chak Angrae Leu
Chakto Mukh
Cham
Chambak
Chamkar Samraong
Chantrea
Chantrei
Chaom Chau
Chaom Kravien
Chbar Mon
Chea Khlang
Cheang Tong
Cheung Kou
Cheung Roas
Chey
Chey Chummeah
Chhbar Ampov Ti Pir
Chhean Laeung
Chheu Teal
Chhloung
Chhuk
Chhuk Khsach
Chhuk Sa
Chi Phoch
Chikor
Chirou Ti Pir
Chob
Chongruk
Chrang Chamreh Ti Muoy
Chranouk
Chreav
Chres
Chrouy Changvar
Chumreah Pen
Daeum Mien
Dam Daek
Dambae
Damril
Dar
Doun Peng
Doun Sa
Doung
Doung Khpos
Kachanh
Kaeb
Kak
Kakaoh
Kamboul
Kampong Bay
Kampong Cham
Kampong Chhnang
Kampong Kor
Kampong Luong
Kampong Popil
Kampong Prang
Kampong Soeng
Kampong Svay
Kandaol Dom
Kantaok
Kantuot
Kaoh Chouram
Kaoh Dach
Kaoh Pir
Kaoh Roka
Kaoh Sampeay
Kaoh Thkov
Kaoh Trong
Kaong Kang
Kdoeang Reay
Khmuonh
Khpob Ta Nguon
Khsam
Khvav
Kien Sangkae
Kilomaetr Lekh Prammuoy
Kiri Voan
Kokir
Kokir Thum
Kor
Kouk Chak
Kouk Khmum
Kouk Mon
Kouk Romiet
Kouk Rovieng
Kouk Trab
Koun Kriel
Koun Satv
Kracheh
Krang Chek
Kranhung
Kraol Kou
Krapum Chhuk
Krasang
Labansiek
Lbaeuk
Leach
Leay Bour
Lveaeng Ruessei
Me Bon
Mlu Prey Muoy
Moha Sang
Ngan
Nirouth
Nitean
Norkor Pheas
Ou Ambel
Ou Mal
Ou Ruessei Ti Bei
Ou Ruessei Ti Buon
Ou Ruessei Ti Muoy
Ou Ruessei Ti Pir
Ou Rumduol
Ou Svay
Pea Reang
Peam Aek
Peam Kaoh Snar
Peam Mean Chey
Phlov Meas
Phnom Penh Thmei
Phnum Bat
Phsar Chas
Phsar Daeum Kor
Phsar Daeum Thkov
Phsar Depou Ti Muoy
Phsar Depou Ti Pir
Phsar Kandal Ti Pir
Phteah Kandal
Phteah Prey
Phum Thum
Pneay
Ponley
Popueus
Pou Chamraeun
Pou Mreal
Pou Rieng
Pouthi Reach
Prambei Mum
Preaek Hou
Preaek Khsay Kha
Preaek Krabau
Preaek Lieb
Preaek Luong
Preaek Phnov
Preaek Pra
Preaek Prasab
Preaek Ta Nong
Preaek Thmei
Preah Damrei
Preah Khae
Preah Sdach
Preak Netr Preah
Prey Chhlak
Prey Khla
Prey Nheat
Puk Ruessei
Puok
Reaksmei Sameakki
Ream
Ro'ang
Rohat Tuek
Roka Kaoh
Roka Khnong
Roka Koy
Roka Krau
Roka Thum
Roleab
Roleang Kreul
Roluos
Rotanak
Ruessei Lok
Rumchek
Saeng
Sakream
Sambuor
Sambuor Meas
Sameakki
Samlout
Sampov Pun
Samraong
Samraong Knong
Samraong Leu
Samraong Yea
Sangkae
Sangkat Angkaol
Sangkat Bavet
Sangkat Bei
Sangkat Buon
Sangkat Kampong Pranak
Sangkat Muoy
Sangkat Nimit
Sangkat Pailin
Sangkat Pal Hal
Sangkat Paoy Paet
Sangkat Pou Rieng (Kampong Leav)
Saom
Sasar Sdam
Seang Khveang
Seda
Sedthei
Sekong
Siem Reab
Sla Kram
Smaong Khang Tboung
Snam Preah
Snao
Snoeng
Snuol
Sopoar Tep
Sra'aem
Srae Ambel
Srae Char
Srae Thmei
Srayov
Stueng Mean chey
Suong
Svay Antor
Svay Kravan
Svay Luong
Svay Pak
Svay Pao
Svay Phluoh
Svay Rolum
Svay Romiet
Svay Rumpear
Svay Teab
Svay Tong Khang Tboung
Ta Kdol
Ta Khmau
Ta Lam
Ta Lou
Ta Mau
Ta Meun
Ta Phem
Ta Saen
Ta Suos
Tang Krang
Tang Krasang
Tang Krouch
Tbaeng Khpos
Thlea Prachum
Thma Kreae
Thma Pechr
Thma Pun
Tnaot Chum
Tnoat Chong Srang
Tonle Basak
Traeng Trayueng
Traeuy Sla
Tram Sasar
Trapeang Kong
Trapeang Kraham
Trapeang Krasang
Trapeang Sab
Trapeang Thum Khang Cheung
Trea
Tuek Chour
Tuek Kraham
Tuek L'ak Ti Bei
Tuek Thla
Tuol Lvea
Tuol Sangkae
Tuol Svay Prey Ti Muoy
Tuol Tumpung Ti Muoy
Vaot Ta Moem
Veal
Veal Pong
Veal Renh
Veal Sbov
Veal Vong
Veang Chas
Vihear Luong
Voat Angk Khang Cheung
Yutth Sameakki
384
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
25
26
29
384
Ampeaeng
Andoung Pou
Andoung Pring
Andoung Trach
Ang Cheung
Angkroang Ti Muoy
Anlong Samna
Anlong Veaeng
Anlong Vil
Annachet
Ba Khong Khang Kaeut
Bak Nim
Bak Trakuon
Baliley Pir
Ballangk
Banteay
Banteay Krang
Baoh
Bat Trach
Battachi
Bavet Kandal
Boeng K'aek
Boeng Khyang
Boeng Kok Ti Pir
Boeng Leach
Boeng Rae Khang Cheung
Boeng Snay
Boeng Ta Srei
Boeung Run
Bos
Bos Kokir
Bos Nhinh
Chachak Ti Muoy
Chak Lech
Chambak Khpos
Chamkar Samraong 2
Chamkar Thmei
Chanloh
Chea Khnang
Chek
Cheung Kou
Chheu Lving
Chheu Teal
Chhkae Koun
Chhlang Kat
Chi Kae
Chi Theang
Chipeay
Chob Ti Muoy
Chong Boeng Krau
Chong Kaoh
Chong Kausu
Chpoes
Chrab Veal
Chrak Trach
Chreav
Chres
Chrey Bet Meas
Chrey Laeung
Chrouy Snaeng Krabei Kraom
Daeum Chan Muoy
Daeum Slaeng
Daeum Slaeng Muoy
Daeum Trang
Damrei Phong
Damrel Ti Bei
Dangkieb Kdam
Dei Kraham
Dei Leu
Doun Chroam
Doun Iet
Doun Teav
Hang Khou Suon
Kaev Kamphleung
Kaev Krasang
Kampong Ampil
Kampong Bay Khang Cheung
Kampong Ko Muoy
Kampong Krasang
Kampong Popil
Kampong Preah
Kampong Sambuor
Kampong Svay
Kan Damra
Kandaek
Kandal
Kang Keng
Kantuot
Kaoh Chamkar
Kaoh Kandaor
Kaoh Krabei
Kaoh Thkov
Kaoh Traeng
Kaong Kang Ti Bei
Kau
Kbal Hong
Kbal Spean Pir
Kbal Tonsaong
Kdam Ha
Khchau
Khlaeng Poar Cheung
Khnar
Khsach
Khsat
Khtum
Khyaok Tboung
Kien Kaes Pir
Kla Koun Chas
Komar Reach
Kor
Kouk Chas
Kouk Rovieng
Kouk Srama
Kouk Taek
Kouk Thnong
Kouk Tnaot
Krabei Sa
Krachab
Kraham Ka
Krang Chheu Nieng
Krang Chres
Krang Serei
Kraoy Voat
Krasang
Krasang Chi Meae
Krasar Chet
Krouskrahom
Kruos
Lbaeuk
Leab Tong
Lek Buon
Lekh Pir
Liek
Luek
Lvea
Mean Chey
Mlu Prey
Mohar
Mphey Osakphea
Nimit Pir
Odongk
Ou Anlok
Ou Chrov
Ou Dem
Ou Romeat
Ou Svay
Ou Ta Prak
Ou Ta Puk Kraom
Ou Touch
Pal Hal
Paoy Kdoeang
Peal Nheaek Muoy
Peal Nheaek Pir
Peam Ros
Peanea Chuor
Peanicheakkam
Phlov Meas
Phnum Dei
Phnum Lonteah
Phnum Touch
Phum 1
Phum 10
Phum 12
Phum 13
Phum 2
Phum 3
Phum 4
Phum 5
Phum 6
Phum 7
Phum 8
Phum 9
Phum Bei
Phum Boeng Chhuk
Phum Chey Chumneah
Phum Dabpram
Phum Damnak Thum Muoy
Phum Khmuonh
Phum Khtor
Phum Kouk Khleang
Phum Kroal Kou
Phum La Kamboar
Phum Mean Chey
Phum Muoy
Phum Ou Baek K'am
Phum Phsar Touch
Phum Pir
Phum Pram
Phum Preaek Ta Long Pir
Phum Preaek Ta Nu
Phum Preaek Ta Pov
Phum Sansam Kosal 1
Phum Sansam Kosal 5
Phum Spean Khpos
Phum Svay Pak
Phum Ta Ngav
Phum Ta Ngav Kandal
Phum Ti Dabmuoy
Phum Ti Prambei
Phum Tnoat Chrum Buon
Phum Tnoat Chrum Pir
Phum Trapeang Chhuk 1
Phum Trapeang Rang Chas
Phum Trea
Phum Trea 1
Phum Trea 3
Phum Trea Bei
Phum Trea Muoy
Phum Tumnub
Phum Tuol Sangkae
Phum Tuol Sangkae 2
Pongro
Pou
Pou Chentam
Pou Mongkol
Pou Rieng Cheung
Pou Tbaeng
Prak Kdar
Pramoul Sokh
Prasat
Preaek
Preaek Chdaor
Preaek Ka Roatn
Preaek Kong
Preaek Krabau
Preaek Krouch
Preaek Moha Tep
Preaek Samraong 2
Preaek Ta Am
Preaek Ta Pov
Preaek Ta Tep
Preaek Tok
Preah Srae
Prek Ta Prov 1
Prey Ba Krong
Prey Boeng
Prey Chisak
Prey Kdei
Prey Mlob
Prey Moan
Prey Phdau
Prey Pou
Prey Prum
Prey Theat
Prey Veang
Puk Ruessei Kraom
Puk Yuk
Roka
Roka Khmuoch Cheung
Roka Kraom
Roka Thum
Roluos
Romon
Rotanak
Roung Masin
Ruessei Char
Ruessei Totueng
Rumchek
Rumchek 4
Rumduol
Rumloung
Saen Sokh 5
Sala Balat
Sala Srok Chas
Saloung
Sameakki
Samma
Sammakki
Sampir
Samraong Kanhchaoch
Sang Reang
Sangkruoh
Saray
Sen Rungroeung Muoy
Sla Kram
Slab Kdaong
Slab Ta Aon
Smach Daeng
Smau Khnhei
Snam Kur
Snoeng Lech
Snuol
Soeng
Sou Peng
Souchey
Souphi
Souriya
Spean Chreav
Srae Ambel
Srae Mkak
Srae Pring
Srae Thnal
Stueng Touch
Stung Khiev Techor
Suon Ampov Lech
Svay K'aer
Svay Yeang
Ta Chet
Ta Daeng Chas
Ta Du
Ta Kdol
Ta Meang
Ta Nob
Ta Pon
Ta Prach
Ta Sei
Ta Sraen
Ta Suon
Tboung
Thal
Thlok Yol
Thma Koul
Thma Pechr Ti Pir
Thma Reab
Thmei
Thmei Otdom
Thnal Dach
Thomcheat Techor Hun Sen
Thommeak Yutt
Ti Bei
Ti Muoy
Tongkaer
Tonloab
Trapeang Kak
Trapeang Kakaoh
Trapeang Khnar
Trapeang Kuy
Trapeang Prich
Trapeang Ruessei
Trapeang Rumduol
Trapeang Seh
Trapeang Thloeng
Trapeang Thloeng 1
Trapeang Thma
Trapeang Traeunh
Trapeang Veaeng
Tuek Chenh
Tuol
Tuol Baray
Tuol Ngouk
Tuol Tbaeng
Tuol Tumnob
Vat Romdol
Veal
Veal Pring Leu
Veal Ri Kaeut
Veal Sbov
Veal Thnal
Veal Thum
Veang
Voat Sla
Ya Sam
384
1
23
3.315
2.487
384
1
2
3
4
5
6
7
8
9
15
384
1
2
384
53
2526
411.326
374.306
384
1
2
3
4
5
6
7
8
9
10
11
12
384
52
3335
418.466
368.792
384
51
151
105.755
21.111
4232
4232
1
2
3
4
4232
1
2
3
4
381
3851
2
3
4
Sysmiss
4
4228
2
3
Sysmiss
4228
4
6
8000
55.722
149.113
4230
2
1
2
3
Sysmiss
4210
22
1941
2017
2003.85
10.314
4232
20000
2400000000
67053915.879
120185961.846
4232
1000
10000000
301284.499
489419.694
4232
1
2
59
4173
120000
2800000
976779.661
624244.207
4232
1
2
109
4123
1
2
3
Sysmiss
56
4176
1
2
3
4
5
6
7
8
9
10
11
12
Sysmiss
55
4177
2015
2016
2017
Sysmiss
48
4184
1
2
3
4
5
6
7
8
9
10
11
12
Sysmiss
48
4184
2016
2017
Sysmiss
57
4175
1
2
3
4
Sysmiss
95
4137
35200000
3483526.316
6224983.759
88
4144
72000000
11255045.455
16816605.174
86
4146
78000000
11009558.14
17870610.308
105
4127
8000000
203333.333
905681.763
104
4128
4000000
145865.385
608419.264
70
4162
32000000
2650714.286
5539571.04
2306
2306
1
2
2306
1
2
2306
9000000
219892.801
531848.651
2306
40000000
433152.363
1253787.622
2304
2
6160000
57816.84
227462.006
2305
1
2000000
2521.475
47293.04
2305
1
4930000
71899.306
221622.769
2306
1000000
31338.183
64217.665
2306
16000000
229948.807
544188.888
2305
1
18350000
294111.367
826113.927
2305
1
3600000
20523.21
154861.464
2303
3
80000
73.817
2134.432
2304
2
6000000
44644.314
192010.927
2304
2
860000
3578.993
25618.511
2304
2
24000000
40727.3
626884.274
2305
1
84300000
1448787.31
2934324.625
39877
39877
801
893
832.728
33.176
39876
1
1
80
2.035
1.739
39844
33
1
2
3
4
Sysmiss
769
39108
1
2
3
4
Sysmiss
7
39870
1
2
4
Sysmiss
2
39875
1
Sysmiss
5057
34820
1
2
3
4
5
6
7
8
9
10
11
Sysmiss
37487
2390
1
80
1.977
1.654
5057
34820
1400
100000000
1272299.209
5187061.329
37487
2390
1000
600000000
1054494.625
6810283.577
55
0200205
0201804
0300902
0302503
0302507
0302708
0303201
0303206
0303303
0400602
0500510
0601304
0700310
0700407
0700408
0700409
0800905
1000503
1000902
1400403
1400405
1400504
1401702
1402010
1402109
1500405
1700802
1701502
1701510
1800507
2000201
2000209
2000301
2000305
2000604
2000607
2000701
2000705
2000706
2000707
2000709
2000710
2001101
2001102
2001103
2001104
2001110
2100906
2101006
2101301
2102105
2102407
2102409
2102501
2102509
55
1
55
1
4
5
55
16
2500
159.836
352.818
55
240000
120000000
5065090.909
16198068.343
55
10000
1000000
135272.727
181476.501
1573
1573
1
2
3
4
5
6
7
8
9
10
11
12
1572
1
24000000
183533.651
1002983.703
2544
2544
1
2
3
4
5
6
7
2544
40000000
465567.453
1795624.73
54814
54814
1
22
10.041
6.199
54812
2
800000
13281.707
19664.58
54774
40
420000
1364.497
6299.934
54814
600000
14666.592
18166.148
5148
5148
1
2
3
4
5
6
7
8
9
10
5139
9
48000000
82227.865
1022160.054
5146
2
7200000
224875.942
259623.123
5144
4
720000
1941.096
14863.833
5146
2
1000
48000000
308929.382
1077696.448
5296
5296
1
2
3
4
5
6
7
5290
6
9000000
27240.113
260498.902
3840
3840
1
2
3
4
5
6
7
9
3840
6
720
51.406
34.29
3840
1
2
3
4
5
6
7
8
3840
1
2
3
4
5
6
7
8
9
3840
1
2
3
4
5
6
7
8
9
3840
1
2
3
4
5
6
7
8
9
3840
1
2
3
4
5
6
7
8
3840
1
2
3
4
5
6
7
8
9
10
11
12
13
3840
240000
14146.233
18510.388
3840
1
2
3
3268
572
1
2
Sysmiss
3268
572
1
2
Sysmiss
3268
572
1
2
Sysmiss
3268
572
1
2
Sysmiss
3268
572
1
2
Sysmiss
3840
1
2
3
4
5
6
7
8
3840
1
2
3
4
3840
200000
465.719
3808.241
3840
80000
1419.063
4380.727
3840
1
2
3
5
8
3840
1000000
48273.547
71571.903
3840
450000
14775.052
24076.34
3840
120000
176.25
2552.697
3840
340000
18010.443
21074.508
3840
600000
4286.875
13770.749
3840
90000
1445.234
6047.84
3840
45000
252.813
2252.781
3839
1
1
2
3
Sysmiss
125
3715
3200000
296952
386212.165
3722
118
5000
10000000
318979.312
462556.933
3840
1400000
1595.833
37929.002
98734
98734
1
503
148.645
179.599
98734
1
2
4827
93907
64000000
863967.785
2680957.52
4824
93910
48000000
357847.616
2508782.88
4827
93907
8
64000000
1221889.664
3631834.004
1571
1571
1
2
3
10
1568
3
53000
1809.592
4404.194
1571
38000
1369.785
1963.625
1568
3
10000
508.514
582.785
3048
3048
1
2
3
4
5
6
7
8
3048
20
500000
10264.392
16238.716
3048
1
2
3
4
2692
356
10
40000000
570351.688
1911943.292
2689
359
1
2
3
Sysmiss
2686
362
1
2
3
Sysmiss
225
2823
2
5050000
426079.262
842061.58
225
2823
1
2
3
Sysmiss
224
2824
1
2
3
Sysmiss
131
2917
72
24000000
924930.473
2864612.922
131
2917
1
2
Sysmiss
131
2917
1
2
3
Sysmiss
3044
4
1
2
3
5
6
7
8
9
10
Sysmiss
3047
1
1952
2017
1995.911
12.479
3048
1
2
3
4
5
6
7
8
436
2612
50000
140000000
10583627.294
16612846.057
3048
100000
960000000
23645063.648
52621288.2
3048
1
2
3
4
2032
1016
1
2
3
4
5
6
7
Sysmiss
2032
1016
1
2
3
4
5
6
8
Sysmiss
2037
1011
1
40
2.319
5.03
3048
1
99
5.642
18.862
3039
9
1
2
3
4
6
7
8
Sysmiss
37
3011
2
3
4
6
Sysmiss
3048
Sysmiss
3048
1
2
3
4
1283
1765
1
2
3
4
5
Sysmiss
33
3015
1
3
4
5
Sysmiss
4
3044
1
2
3
Sysmiss
3048
Sysmiss
3048
1
2
2756
292
1979
2017
1995.247
11.956
3048
1
2
3
1284
1284
1
2
3
1284
192
11.671
12.356
1205
79
120
18.544
14.976
1284
1
2
3
4
5
6
7
8
9
10
11
1284
1
2
3
4
5
6
7
8
9
10
1284
30000
600000000
17491436.916
38101975.143
1283
1
600000000
11068082.814
27970122.328
1283
1
10
1.838
1.08
10133
10133
1
2
3
4
5
6
7
8
9
10
10132
1
1
2
Sysmiss
3363
6770
2500
12.87
69.467
1343
8790
40
2.04
2.091
3362
6771
72000000
1911025.877
4013925.187
3362
6771
20000
25.833
355.381
3363
6770
58000000
819227.684
2716573.197
3361
6772
56000000
144746.266
1674589.923
3362
6771
9000000
65632.689
187193.783
3362
6771
2000000
4879.09
46924.799
3363
6770
89700000
41737.08
1560699.518
3361
6772
4000000
31905.772
94482.52
3361
6772
2400000
1652.782
55422.468
3342
3342
1
2
3
4
5
6
3342
91720000
275660.054
1747999.093
16909
16909
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16909
1
2
16904
5
1
31
13.282
8.044
16896
13
1
2
3
4
5
6
7
8
9
10
11
12
Sysmiss
16909
1919
2017
1986.51
20.123
16909
98
30.117
20.122
1427
15482
1
2
3
4
Sysmiss
16909
1
2
3
4
5
6
7
8
9
10
11
12
13
15
7140
9769
1
26
1.459
1.412
8553
8356
1
2
3
4
5
6
7
8
9
12
13
21
Sysmiss
12984
3925
1
2
3
4
Sysmiss
7229
9680
1
2
3
4
5
6
7
8
9
10
11
12
13
Sysmiss
16909
1
2
3
4
5
6
7
8
16909
1
2
16909
1
2
3
4
5
6
7
8
9
1059
15850
1
2
3
4
5
6
7
9
Sysmiss
771
16138
1
2
4
5
Sysmiss
16909
1
2
834
16075
51
29.504
16.624
16909
1691
1691
1
2
3
4
1691
0112
0120
0130
0141
0145
0146
0170
0320
0810
1010
1020
1060
1070
1100
1200
1310
1390
1410
1620
1810
2310
2390
2510
2590
3100
3210
3310
3510
3600
3830
4390
4510
4520
4540
4610
4620
4640
4650
4660
4690
4710
4720
4730
4740
4750
4760
4770
4780
4790
4920
5020
5510
5610
5810
6310
6410
6490
6610
6620
6810
7420
7720
7730
8210
8520
8530
8540
8610
8620
8690
9000
9490
9510
9520
9600
1690
1
1
2
3
4
5
6
7
8
9
11
Sysmiss
784
907
1
2
3
4
5
6
7
8
Sysmiss
162
1529
1
2
3
4
5
6
7
8
9
11
Sysmiss
31
1660
1
3
4
5
6
7
8
10
Sysmiss
7
1684
5
7
9
Sysmiss
1
1690
7
Sysmiss
1691
Sysmiss
1691
Sysmiss
1691
Sysmiss
7723
7723
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
7723
1680000000
8607199.094
45248899.707
2354
5369
432000000
3016708.284
20638274.558
1326
6397
240000000
565765.837
7955876.455
9
7714
30000000
5257555.556
10442637.779
9
7714
Sysmiss
9
7714
Sysmiss
2650
2650
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
2650
4894395000
34783328.151
140448746.857
816
1834
477360000
10866743.627
36990763.007
442
2208
261560000
2207164.027
15983770.634
6
2644
133718000
22286333.333
54590144.904
5
2645
Sysmiss
5
2645
Sysmiss
3840
3840
1
2
3840
1
2
80
3760
1
2
3
4
5
6
7
Sysmiss
3840
1
2
1931
1909
1
2
3
4
5
6
7
Sysmiss
2121
1719
1
2
Sysmiss
1931
1909
1
2
Sysmiss
1116
2724
1
Sysmiss
1116
2724
1
2
Sysmiss
1928
1912
1
2
Sysmiss
1116
2724
2
Sysmiss
1928
1912
1
2
Sysmiss
1116
2724
1
2
Sysmiss
3840
1
2
2116
1724
1
Sysmiss
2115
1725
Sysmiss
3840
1
2
3840
1
2
2110
1730
1
Sysmiss
3840
1
2
2115
1725
2
Sysmiss
2116
1724
2
Sysmiss
3840
1
2
3840
1
2
2114
1726
1
Sysmiss
2116
1724
1
Sysmiss
3840
1
2
2116
1724
Sysmiss
2114
1726
Sysmiss
2115
1725
2
Sysmiss
3840
1
2
3840
1
2
3839
1
1
2
Sysmiss
3840
1
2
3840
1
2
8
240
3600
1
2
3
4
6
8
Sysmiss
91
3749
1
2
3
4
6
Sysmiss
39
3801
1
2
3
4
6
8
Sysmiss
244
3596
1
2
3
4
5
8
Sysmiss
3840
Sysmiss
3840
1
2
3840
1
2
3840
1
2
3295
3295
1
2
3295
1
2
3
4
5
6
7
12
13
14
15
21
3295
1
2
3
4
5
6
7
13
21
3295
101
102
103
104
105
201
203
209
302
303
401
411
412
413
422
424
425
427
430
443
451
453
501
504
505
506
511
521
522
524
525
526
528
531
542
543
552
561
601
801
803
804
811
812
813
814
815
819
821
824
826
827
833
841
842
844
911
924
925
928
941
952
3295
15
300000
10043.739
13592.916
3295
300000
7896.046
11663.487
3295
1000000
3029.257
18494.749
3295
14286
31.942
325.322
3295
5000
23.908
176.765
3295
60000
1097.648
2932.762
3295
2000
2006
2010
2012
2013
2015
2016
2017
40549
40549
1
23
11.209
5.991
39795
754
92000000
484375.882
2113148.739
39768
781
4000000
2321.193
36053.687
40548
1
500
92000000
480208.346
2095321.94
446
0100204
0101107
0101303
0101306
0101308
0101402
0101403
0101506
0101507
0200104
0200105
0200107
0200205
0201101
0201108
0201304
0201305
0201308
0201309
0201310
0201606
0201701
0201801
0201804
0201809
0201810
0201901
0201910
0202001
0202002
0202003
0202005
0202006
0202009
0202202
0202203
0202205
0202207
0202208
0202209
0202210
0202301
0202302
0202303
0202304
0202305
0202306
0202307
0202308
0202309
0202401
0202403
0202405
0202406
0202407
0202408
0202409
0202410
0300301
0300302
0300303
0300304
0300501
0300502
0300503
0300504
0300505
0300506
0300509
0300510
0300703
0301001
0301003
0301006
0301009
0301010
0301301
0301302
0301303
0301304
0301305
0301307
0301308
0301309
0301310
0301406
0301409
0301501
0301507
0301508
0301509
0301601
0301604
0301605
0301609
0301703
0301709
0301801
0301803
0301806
0301807
0302002
0302003
0302005
0302006
0302007
0302008
0302009
0302102
0302107
0302109
0302110
0302303
0302306
0302307
0302308
0302310
0302408
0302505
0302508
0303001
0303006
0303007
0303010
0303101
0303104
0303105
0303106
0303109
0303204
0303208
0303209
0303210
0303303
0303304
0303306
0303309
0303310
0303504
0303506
0400206
0400402
0400801
0400903
0500108
0500706
0501202
0501203
0501410
0501602
0501607
0502301
0502302
0502304
0502305
0502306
0502307
0502308
0502309
0502502
0502505
0502506
0502609
0502905
0502908
0503104
0503105
0600202
0600207
0600301
0600304
0600305
0600306
0600310
0600503
0600509
0600702
0600703
0600706
0600707
0600801
0600802
0600803
0600804
0600805
0600806
0600807
0600809
0600902
0600905
0700202
0700204
0700408
0700409
0700606
0700610
0700708
0700710
0700801
0700802
0700806
0700809
0701005
0701006
0701008
0701010
0801101
0801102
0801104
0801105
0801206
0801603
0801604
0801608
0801610
0801802
0801808
0801907
0802303
0802401
0802404
0802405
0802406
0900102
0900103
0900108
1000207
1000301
1000302
1000304
1000305
1000308
1000309
1000401
1000402
1000403
1000405
1000406
1000409
1000410
1000501
1000503
1000506
1000507
1000509
1000602
1000603
1000605
1000607
1000608
1000609
1000610
1000701
1000702
1000703
1000707
1000709
1000710
1000802
1000804
1000805
1000806
1000807
1000903
1000905
1001007
1300204
1300205
1300207
1300305
1400809
1401008
1401107
1401305
1401409
1401901
1401902
1401907
1401909
1500801
1500803
1500904
1500905
1501001
1501003
1501005
1501006
1501008
1501202
1501203
1501204
1501206
1501208
1501209
1600101
1600104
1600202
1600209
1600301
1600302
1600303
1600304
1600305
1600306
1600307
1600308
1600309
1600310
1600401
1600402
1600403
1600404
1600405
1600406
1600407
1600408
1600409
1600410
1600501
1600502
1600504
1600507
1600510
1700802
1701602
1701907
1702101
1702103
1702104
1702107
1702109
1702110
1702202
1702203
1702204
1702205
1702206
1702209
1702210
1800409
1800601
1800608
1900109
1900110
1900406
2100204
2100208
2100706
2101003
2101005
2101301
2101302
2101305
2101804
2101907
2102105
2102509
2200102
2200104
2200105
2200106
2200107
2200108
2200110
2200201
2200202
2200203
2200204
2200208
2200209
2200210
2200301
2200302
2200303
2200306
2200307
2200308
2200309
2200310
2200404
2200406
2200407
2200408
2200409
2200502
2200505
2200506
2200507
2200510
2200601
2400101
2400102
2400106
2400107
2400109
2400110
2400203
446
1
2
3
4
446
101
104
201
203
209
302
303
401
411
412
413
422
424
425
427
430
443
451
501
505
506
511
521
522
524
525
526
528
531
542
552
561
601
801
803
804
811
815
819
821
824
826
827
833
841
842
911
924
925
928
941
446
15
1000000
8584.377
48557.762
446
100
900000
4929.26
42859.985
3840
3840
1
2
3
4
5
6
7
3839
1
1
5
6
7
8
9
10
Sysmiss
3840
1
2
3
4
5
7
1437
2403
1
3
4
5
7
9
Sysmiss
3839
1
1
2
3
4
5
6
7
Sysmiss
2106
1734
1
2
3
4
5
9
Sysmiss
3840
1
2
3
4
5
6
7
2868
972
1
2
3
4
5
6
7
8
9
Sysmiss
3839
1
1
2
3
4
5
6
7
Sysmiss
3807
33
1
2
3
4
5
7
9
Sysmiss
3840
1
2
3
4
5
6
7
3658
182
1
3
4
5
7
9
Sysmiss
3840
1
2
3
4
2487
1353
1
3
4
5
6
9
Sysmiss
3840
1
2
3
4
5
6
7
3231
609
1
2
3
5
6
9
10
Sysmiss
3839
1
1
2
3
4
5
6
7
Sysmiss
1587
2253
1
2
3
4
5
8
9
Sysmiss
3840
1
2
3
4
5
6
7
3749
91
1
2
3
4
5
6
8
9
Sysmiss
3840
1
2
3
4
5
6
7
3817
23
1
2
3
4
5
7
9
Sysmiss
3839
1
1
2
3
4
5
6
7
Sysmiss
3029
811
1
2
3
4
5
6
7
9
Sysmiss
3840
1
2
3
4
5
6
7
1643
2197
1
4
5
6
9
Sysmiss
3840
1
2
3
4
5
6
7
3799
41
1
2
3
5
7
8
9
Sysmiss
3840
1
2
3
4
5
6
7
2417
1423
1
2
3
5
9
Sysmiss
3840
1
2
3
4
5
6
7
3831
9
1
2
5
7
9
Sysmiss
3840
1
2
3
4
5
6
7
2283
1557
1
2
3
5
7
9
Sysmiss
3840
1
2
3
5
7
281
3559
1
2
3
5
9
Sysmiss
3840
1
2
3
4
5
6
7
3840
1
2
3
4
5
7
3840
1
2
3
5
7
3840
1
2
4
5
3840
1
2
4
3840
1
34
3806
1
2
3
Sysmiss
34
3806
1
2
3
Sysmiss
34
3806
1
2
3
Sysmiss
34
3806
1
2
3
Sysmiss
34
3806
1
2
3
Sysmiss
34
3806
1
2
Sysmiss
34
3806
1
2
3
Sysmiss
34
3806
1
2
3
Sysmiss
34
3806
1
2
3
Sysmiss
34
3806
1
2
Sysmiss
3840
1
2
3
3840
1
2
3
3840
1
2
3840
1
2
3840
1
2
3840
1
2
3840
1
2
3840
3840
01001
01002
01003
01004
01005
01006
01007
01008
01009
01010
01011
01012
01013
01014
01015
01016
02001
02002
02003
02004
02005
02006
02007
02008
02009
02010
02011
02012
02013
02014
02015
02016
02017
02018
02019
02020
02021
02022
02023
02024
03001
03002
03003
03004
03005
03006
03007
03008
03009
03010
03011
03012
03013
03014
03015
03016
03017
03018
03019
03020
03021
03022
03023
03024
03025
03026
03027
03028
03029
03030
03031
03032
03033
03034
03035
03036
04001
04002
04003
04004
04005
04006
04007
04008
04009
04010
04011
04012
05001
05002
05003
05004
05005
05006
05007
05008
05009
05010
05011
05012
05013
05014
05015
05016
05017
05018
05019
05020
05021
05022
05023
05024
05025
05026
05027
05028
05029
05030
05031
05032
06001
06002
06003
06004
06005
06006
06007
06008
06009
06010
06011
06012
06013
07001
07002
07003
07004
07005
07006
07007
07008
07009
07010
08001
08002
08003
08004
08005
08006
08007
08008
08009
08010
08011
08012
08013
08014
08015
08016
08017
08018
08019
08020
08021
08022
08023
08024
09001
10001
10002
10003
10004
10005
10006
10007
10008
10009
10010
12001
12002
12003
12004
12005
12006
12007
12008
12009
12010
12011
12012
12013
12014
12015
12016
12017
12018
12019
12020
12021
12022
12023
12024
12025
12026
12027
12028
12029
12030
12031
12032
12033
12034
12035
12036
12037
12038
12039
12040
12041
12042
12043
12044
12045
12046
12047
12048
12049
12050
12051
12052
12053
12054
12055
12056
12057
12058
12059
12060
12061
12062
12063
12064
12065
12066
12067
12068
12069
12070
12071
12072
12073
12074
12075
12076
12077
12078
12079
13001
13002
13003
13004
13005
13006
13007
14001
14002
14003
14004
14005
14006
14007
14008
14009
14010
14011
14012
14013
14014
14015
14016
14017
14018
14019
14020
14021
14022
15001
15002
15003
15004
15005
15006
15007
15008
15009
15010
15011
15012
16001
16002
16003
16004
16005
17001
17002
17003
17004
17005
17006
17007
17008
17009
17010
17011
17012
17013
17014
17015
17016
17017
17018
17019
17020
17021
17022
18001
18002
18003
18004
18005
18006
18007
19001
19002
19003
19004
20001
20002
20003
20004
20005
20006
20007
20008
20009
20010
20011
20012
20013
21001
21002
21003
21004
21005
21006
21007
21008
21009
21010
21011
21012
21013
21014
21015
21016
21017
21018
21019
21020
21021
21022
21023
21024
21025
22001
22002
22003
22004
22005
22006
23001
23002
24001
24002
3840
01
02
03
04
05
06
07
08
09
10
3840
1
2
3
4
5
6
7
8
10
3840
1
2
3
4
5
6
7
8
3840
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
15482
15482
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15482
1
2
3
4
5
6
7
8
9
10
20
15482
1
2
5462
10020
1
2
Sysmiss
10088
011
111
112
121
122
133
134
141
143
214
221
222
224
225
226
231
232
233
234
235
241
242
251
261
263
264
265
311
312
313
315
321
323
325
332
333
334
335
341
343
352
411
412
413
421
422
431
432
441
511
512
513
514
516
521
531
532
541
542
543
544
545
546
547
548
549
550
611
612
613
621
622
631
632
633
634
711
712
713
721
722
723
724
725
731
733
734
735
736
737
738
739
741
742
751
752
753
754
755
757
811
813
814
815
816
818
821
831
832
833
834
835
836
837
911
912
913
914
916
921
931
932
933
934
941
951
952
954
955
956
961
962
963
964
998
10088
0111
0112
0113
0114
0115
0119
0120
0130
0141
0145
0146
0150
0160
0170
0220
0230
0240
0310
0320
0720
0810
0890
1010
1020
1030
1040
1060
1070
1080
1100
1200
1310
1390
1410
1430
1510
1520
1610
1620
1700
1810
2020
2100
2210
2220
2310
2390
2420
2510
2590
2610
2640
2730
2920
2930
3100
3210
3310
3510
3600
3810
3830
4100
4210
4220
4320
4330
4390
4510
4520
4530
4540
4620
4640
4650
4660
4690
4710
4720
4730
4740
4750
4760
4770
4780
4790
4920
5010
5020
5110
5220
5510
5610
5620
5810
6010
6020
6120
6190
6200
6310
6320
6410
6490
6610
6620
6810
6910
6920
7110
7420
7500
7720
7730
7910
8010
8110
8120
8130
8210
8220
8230
8290
8410
8420
8510
8520
8530
8540
8550
8610
8620
8690
8790
9000
9200
9490
9510
9520
9600
9900
9980
9990
10088
5394
1
2
3
4
5
6
7
8
Sysmiss
10088
5394
1
2
3
4
5
Sysmiss
10021
5461
1
90
44.04
16.036
10021
5461
1
31
24.888
6.69
10085
5397
1
2
Sysmiss
2032
13450
1
2
Sysmiss
10054
5428
1
2
Sysmiss
4763
10719
1
2
3
4
Sysmiss
10087
5395
1
2
3
4
Sysmiss
2437
011
141
221
222
224
233
234
235
265
312
313
323
332
341
343
411
441
512
513
514
531
541
542
544
545
546
548
550
611
612
613
621
622
631
632
634
711
712
713
721
725
731
734
735
737
739
741
742
751
753
755
813
816
832
833
834
835
836
837
911
912
914
921
931
932
933
934
951
954
955
956
961
963
964
2437
0111
0112
0113
0114
0115
0119
0120
0130
0141
0145
0146
0160
0170
0220
0230
0310
0320
0810
1010
1020
1060
1070
1100
1390
1410
1520
1610
1620
1810
2030
2510
3210
3510
3600
4100
4390
4540
4620
4660
4710
4720
4730
4740
4750
4770
4780
4790
4920
5020
5220
5510
5610
5620
5810
6310
6620
7720
8010
8120
8210
8410
8420
8510
8520
8530
8540
8550
8620
8690
9000
9200
9490
9510
9600
2437
13045
1
3
4
6
Sysmiss
2437
13045
1
3
4
Sysmiss
2437
13045
2
67
17.85
11.756
2437
13045
1
30
22.017
9.454
2432
13050
1
2
Sysmiss
686
14796
1
2
Sysmiss
1525
13957
1
2
3
4
Sysmiss
422
15060
2
25
6.806
4.169
369
15113
1
2
Sysmiss
10060
5422
1
90
48.475
15.926
5145
10337
15000
19320000
871188.426
753199.669
10087
5395
1
2
3
Sysmiss
62
15420
2
56
11.903
8.717
58
15424
1
60
22.379
13.575
57
15425
1
2
Sysmiss
57
15425
1
2
3
Sysmiss
45
15437
1
2
3
4
6
7
12
Sysmiss
5399
10083
1
2
Sysmiss
16
15466
1
2
3
5
Sysmiss
5
15477
3
4
Sysmiss
2
15480
1
Sysmiss
16
15466
1
2
Sysmiss
16
15466
4
56
46.438
16.423
13
15469
1
2
3
4
Sysmiss
5384
10098
1
2
3
4
5
6
7
8
9
Sysmiss
70
15412
1
2
3
4
5
6
8
10
12
14
20
Sysmiss
61
15421
1
2
Sysmiss
15482
16110
16110
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16106
4
1
2
3
4
5
6
7
8
9
10
Sysmiss
16110
1
2
16110
1
2
16110
1
2
13607
2503
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Sysmiss
13608
2502
88
8.836
12.239
13616
2494
1
2
Sysmiss
3752
12358
21
5.807
4.347
3752
12358
1
2
3
4
6
7
8
Sysmiss
3761
12349
1
2
Sysmiss
1391
14719
1
2
3
4
6
7
8
9
10
11
12
Sysmiss
16110
1
2
1008
15102
1
2
Sysmiss
728
15382
1
2
4
5
6
Sysmiss
16108
2
1
2
Sysmiss
3561
12549
22
5.211
4.394
3554
12556
10000000
238917.136
739802.333
3554
12556
5760000
192063.731
434218.708
3555
12555
4000000
40766.47
97096.671
3555
12555
3200000
68100.028
122923.638
3556
12554
9150000
494003.431
657572.707
3555
12555
4800000
52313.783
201217.488
3555
12555
160000
2213.924
6736.318
3552
12558
18200000
1087992.005
1442093.158
16110
540
0100110
0100203
0100208
0100209
0100304
0100306
0100309
0100510
0100608
0100609
0100610
0100703
0101007
0101104
0101105
0101203
0101205
0101207
0101403
0101408
0101605
0200107
0200310
0200401
0200405
0200502
0200603
0200606
0200706
0201003
0201009
0201104
0201204
0201210
0201403
0201409
0201410
0201503
0201506
0201507
0201508
0201604
0201707
0201907
0202005
0202006
0202107
0202201
0202301
0202305
0202403
0202408
0300101
0300104
0300304
0300308
0300403
0300410
0300501
0300506
0300510
0300605
0300607
0300705
0300805
0300806
0301005
0301010
0301101
0301103
0301104
0301107
0301110
0301303
0301304
0301602
0301609
0301703
0301707
0301709
0301805
0301909
0302101
0302103
0302108
0302201
0302202
0302204
0302206
0302305
0302310
0302401
0302402
0302502
0302507
0302602
0302608
0302901
0302902
0302903
0302906
0302907
0302909
0303103
0303106
0303110
0303201
0303206
0303401
0303405
0303504
0400105
0400201
0400307
0400309
0400409
0400410
0400506
0400508
0400604
0400706
0400707
0400806
0401105
0500104
0500105
0500107
0500110
0500207
0500210
0500405
0500408
0500410
0500510
0500702
0500704
0500707
0500805
0501002
0501005
0501010
0501103
0501104
0501201
0501203
0501302
0501304
0501306
0501309
0501401
0501501
0501506
0501507
0501508
0501509
0501510
0501604
0501609
0501610
0501710
0501801
0501802
0501807
0502103
0502304
0502308
0502405
0502407
0502409
0502501
0502509
0502701
0502707
0502804
0502805
0502807
0502810
0503103
0503106
0503203
0503204
0503207
0503208
0503210
0600102
0600105
0600208
0600301
0600401
0600403
0600504
0600705
0600707
0600809
0601003
0601007
0601102
0601103
0601108
0601110
0601203
0601205
0601209
0601210
0601305
0700106
0700208
0700405
0700408
0700410
0700503
0700507
0700606
0700608
0700705
0700803
0700908
0800204
0800405
0800406
0800605
0800610
0800701
0800703
0800704
0800903
0801002
0801005
0801009
0801205
0801206
0801208
0801307
0801403
0801405
0801502
0801808
0801904
0801905
0802108
0802203
0802404
0802408
0802410
0900104
1000106
1000301
1000304
1000307
1000505
1000601
1000709
1000910
1001007
1200110
1200502
1200505
1200601
1200609
1200702
1200703
1200706
1200707
1200708
1200804
1200806
1200908
1201003
1201006
1201106
1201202
1201302
1201304
1201307
1201308
1201509
1201906
1202205
1202207
1202303
1202309
1202401
1202503
1202505
1202904
1202906
1203009
1203101
1203105
1203106
1203203
1203309
1203702
1203902
1204001
1204004
1204201
1204209
1204210
1204501
1204510
1204601
1204604
1204605
1204703
1204710
1204901
1204904
1204909
1204910
1205008
1205010
1205206
1205207
1205208
1205410
1205504
1205906
1206102
1206103
1206202
1206203
1206204
1206302
1206304
1206401
1206403
1206404
1206405
1206406
1206409
1206410
1206710
1207404
1207510
1207804
1207808
1207901
1207902
1207903
1300204
1300207
1300305
1300308
1300409
1300503
1300507
1300509
1300602
1300704
1300706
1400101
1400103
1400209
1400307
1400403
1400408
1400410
1400601
1400604
1400802
1400805
1401003
1401006
1401103
1401204
1401301
1401302
1401305
1401308
1401402
1401404
1401405
1401502
1401601
1401701
1401804
1401810
1401905
1401909
1402203
1402204
1402206
1402209
1500101
1500406
1500704
1500805
1500807
1500904
1500907
1500910
1501002
1501006
1501201
1501202
1600202
1600203
1600206
1600208
1600209
1600504
1700102
1700201
1700209
1700305
1700402
1700410
1700505
1700508
1700606
1700609
1700709
1700804
1700806
1700809
1700903
1700908
1701002
1701005
1701104
1701106
1701201
1701303
1701308
1701309
1701403
1701404
1701508
1701602
1701608
1701609
1701802
1701804
1701806
1702101
1702105
1702204
1800106
1800107
1800201
1800204
1800208
1800308
1800310
1800408
1800503
1800508
1800604
1800606
1900106
1900110
1900202
1900205
1900206
1900208
1900210
1900301
1900302
1900307
1900308
1900409
1900410
2000301
2000304
2000308
2000602
2000608
2000609
2000707
2000710
2000801
2000910
2001101
2001104
2001110
2001208
2001301
2100102
2100108
2100109
2100208
2100307
2100402
2100407
2100507
2100510
2100709
2100808
2100905
2101002
2101108
2101110
2101306
2101404
2101407
2101605
2101610
2101701
2101702
2101707
2101802
2101807
2101901
2101905
2101909
2102006
2102208
2102502
2102507
2102510
2200104
2200201
2200208
2200209
2200301
2200303
2200407
2200501
2200604
2200606
2300102
2300109
2300206
2300207
2400105
2400108
2400206
2400208
540
1
2
540
1
2
3
4
5
6
7
8
539
1
1
2
3
4
5
6
7
8
9
10
11
12
Sysmiss
539
1
1
2
Sysmiss
529
11
1
2
Sysmiss
463
77
23
1.3
2.582
37
503
1
2
3
4
7
Sysmiss
497
43
1
2
Sysmiss
497
43
1
2
Sysmiss
497
43
1
2
Sysmiss
492
48
1
2
4
Sysmiss
488
52
1
2
3
Sysmiss
539
1
1
2
Sysmiss
528
12
1
2
3
4
5
6
Sysmiss
521
19
1
2
Sysmiss
511
29
1
2
Sysmiss
540
010011002
010020305
010020802
010020903
010030407
010030605
010030902
010051002
010060802
010060902
010061002
010070302
010100702
010110403
010110505
010120302
010120505
010120508
010120702
010140302
010140804
010160504
020010702
020031003
020031004
020040103
020040505
020050202
020060302
020060608
020070602
020100304
020100902
020110402
020120402
020121002
020140302
020140902
020141004
020150307
020150601
020150704
020150802
020160402
020170702
020190704
020200504
020200602
020210702
020220102
020230102
020230502
020240302
020240803
030010102
030010402
030030403
030030803
030040303
030041002
030050105
030050603
030051002
030060502
030060702
030070502
030080502
030080602
030100502
030101003
030110102
030110302
030110402
030110702
030111004
030130304
030130403
030160201
030160902
030170303
030170702
030170905
030180502
030190902
030210102
030210303
030210801
030220101
030220202
030220402
030220603
030230502
030231002
030240102
030240206
030250202
030250703
030260202
030260802
030290103
030290202
030290306
030290603
030290703
030290902
030310302
030310602
030311002
030320102
030320602
030340102
030340502
030350404
040010502
040020104
040030702
040030902
040040903
040041002
040050602
040050802
040060403
040070602
040070702
040080602
040110502
050010403
050010502
050010702
050011002
050020702
050021002
050040503
050040804
050041005
050051003
050070202
050070402
050070708
050080503
050100202
050100502
050101002
050110302
050110402
050120103
050120302
050130205
050130402
050130602
050130903
050140103
050150102
050150602
050150702
050150802
050150904
050151005
050160402
050160902
050161002
050171002
050180103
050180202
050180702
050210302
050230402
050230805
050240504
050240703
050240901
050250103
050250902
050270102
050270704
050280402
050280504
050280702
050281002
050310302
050310602
050320303
050320402
050320702
050320802
050321004
060010203
060010502
060020801
060030102
060040102
060040302
060050403
060070502
060070702
060080905
060100301
060100704
060110202
060110303
060110801
060111002
060120302
060120504
060120901
060121002
060130502
070010602
070020803
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070080302
070090802
080020402
080040502
080040602
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080061002
080070102
080070303
080070403
080090306
080100203
080100502
080100902
080120502
080120603
080120801
080130702
080140302
080140504
080150203
080180804
080190402
080190502
080210802
080220302
080240402
080240802
080241003
090010402
100010602
100030103
100030402
100030702
100050502
100060102
100070902
100091003
100100708
120011002
120050207
120050506
120060102
120060905
120070202
120070302
120070602
120070702
120070802
120080402
120080602
120090803
120100302
120100602
120110606
120120202
120130206
120130405
120130705
120130802
120150902
120190605
120220506
120220702
120230304
120230902
120240102
120250306
120250504
120290403
120290602
120300902
120310102
120310502
120310602
120320302
120330902
120370204
120390204
120400103
120400403
120420102
120420902
120421001
120450102
120451002
120460102
120460404
120460502
120470302
120471002
120490104
120490402
120490902
120491002
120500802
120501008
120520602
120520702
120520804
120541002
120550403
120590603
120610202
120610302
120620203
120620302
120620401
120630201
120630402
120640104
120640302
120640408
120640505
120640603
120640903
120641002
120671002
120740402
120751004
120780401
120780802
120790102
120790203
120790302
130020402
130020703
130030505
130030802
130040902
130050302
130050701
130050902
130060202
130070402
130070602
140010103
140010303
140020902
140030702
140040303
140040803
140041003
140060102
140060403
140080202
140080502
140100302
140100606
140110303
140120402
140130102
140130202
140130502
140130803
140140202
140140402
140140504
140150202
140160101
140170102
140180402
140181002
140190502
140190902
140220302
140220403
140220606
140220902
150010103
150040602
150070403
150080502
150080702
150090402
150090702
150091002
150100201
150100602
150120102
150120202
160020202
160020302
160020605
160020802
160020902
160050403
170010204
170020102
170020902
170030503
170040203
170041002
170050502
170050804
170060602
170060903
170070902
170080402
170080606
170080902
170090302
170090802
170100202
170100502
170110402
170110603
170120102
170130304
170130802
170130902
170140303
170140406
170150802
170160203
170160802
170160902
170180202
170180402
170180602
170210102
170210503
170220402
180010602
180010705
180020102
180020402
180020802
180030802
180031001
180040802
180050302
180050802
180060404
180060606
190010602
190011002
190020202
190020503
190020602
190020803
190021002
190030102
190030203
190030703
190030802
190040902
190041002
200030104
200030404
200030803
200060202
200060802
200060902
200070705
200071003
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200091002
200110102
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210010202
210010803
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210030702
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210050702
210051003
210070902
210080802
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210100202
210110803
210111002
210130604
210140402
210140707
210160502
210161002
210170103
210170203
210170702
210180202
210180702
210190103
210190502
210190904
210200601
210220802
210250201
210250204
210250702
210251002
220010403
220020102
220020802
220020902
220030102
220030302
220040703
220050103
220060403
220060601
230010202
230010901
230020603
230020702
240010503
240010805
240020602
240020802
539
010011005
010020307
010020806
010020909
010030406
010030608
010030905
010051005
010060803
010060904
010061005
010070304
010100703
010110406
010110511
010120306
010120507
010120511
010120707
010140303
010140806
010160508
020010705
020031009
020031011
020040104
020040504
020050205
020060303
020060607
020070604
020100306
020100906
020110403
020120404
020121007
020140305
020140905
020141006
020150308
020150604
020150706
020150803
020160407
020170704
020190706
020200507
020200604
020210706
020220104
020230103
020230504
020240304
020240806
030010104
030010406
030030404
030030805
030040306
030041004
030050107
030050610
030051005
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030060704
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030080605
030100505
030101004
030110107
030110305
030110404
030110705
030110706
030111005
030130303
030130405
030160203
030160904
030170304
030170708
030170904
030180505
030190904
030210105
030210309
030210802
030220107
030220205
030220404
030220607
030230503
030231004
030240105
030240205
030250203
030250705
030260207
030260803
030290106
030290204
030290307
030290606
030290707
030290912
030310307
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030311005
030320105
030320605
030340103
030340505
030350406
040010503
040020108
040030703
040030904
040040906
040041005
040050607
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040060406
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040070705
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050010404
050010503
050010704
050011004
050020704
050021004
050040505
050040807
050041007
050051004
050070205
050070404
050070710
050080506
050100205
050100503
050101003
050110306
050110403
050120105
050120305
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050130603
050130906
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050180106
050180203
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050210304
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050230807
050240507
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050240904
050250105
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050270104
050270705
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050281004
050310305
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050320310
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050320706
050320803
050321006
050321007
060010205
060010503
060020802
060030103
060040104
060040303
060050409
060070505
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060080907
060100306
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060110205
060110306
060110803
060111004
060120304
060120506
060120904
060121003
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070040510
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070050304
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070060605
070060803
070070506
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080061005
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080070308
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080090307
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080100905
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080120605
080120803
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080140510
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090010405
100010604
100030108
100030403
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100050505
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100091009
100100709
120011004
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120060107
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120120206
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120150904
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120220507
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120230307
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120240105
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120290405
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120300905
120310104
120310503
120310603
120320304
120330903
120370206
120390207
120400106
120400407
120420104
120420908
120421003
120450107
120451005
120460104
120460406
120460503
120470304
120471005
120490111
120490405
120490904
120491003
120500805
120501011
120520606
120520707
120520809
120541005
120550406
120590605
120610204
120610303
120620205
120620304
120620404
120630203
120630405
120640109
120640307
120640412
120640502
120640610
120640905
120641004
120671001
120740405
120751011
120780404
120780805
120790104
120790207
120790304
130020404
130020705
130030506
130030804
130040904
130050307
130050706
130050905
130060205
130070404
130070604
140010104
140010308
140020903
140030704
140040311
140040805
140041007
140060105
140060404
140080203
140080503
140100304
140100610
140110304
140120405
140130104
140130205
140130505
140130807
140140203
140140405
140140510
140150205
140160102
140170104
140180405
140181006
140190505
140190903
140220303
140220408
140220609
140220903
150010105
150040605
150070404
150080505
150080704
150090404
150090704
150091004
150100203
150100605
150120106
150120205
160020205
160020305
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160020904
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170010208
170020106
170020904
170030505
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170041005
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170100201
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170110405
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170130306
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170130904
170140306
170140409
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170160207
170160803
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170210106
170210505
170220404
180010603
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180030805
180031003
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180060405
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190011003
190020203
190020509
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190021004
190030105
190030208
190030707
190030804
190040904
190041004
200030103
200030408
200030409
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200060205
200060804
200060905
200070709
200071007
200080104
200091005
200110105
200110408
200111006
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200130106
210010203
210010804
210010904
210020807
210030704
210040206
210040705
210050705
210051006
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210090504
210100205
210110807
210111005
210130606
210140403
210140706
210160504
210160505
210161005
210170107
210170204
210170703
210180205
210180703
210190107
210190504
210190903
210200604
210220803
210250205
210250206
210250704
210251006
220010407
220020103
220020803
220020804
220020904
220030103
220030304
220040705
220050109
220060406
220060607
230010204
230010905
230020605
230020705
240010504
240010806
240020604
240020805
16909
16909
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16909
1
2
2415
14494
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
19
Sysmiss
2422
14487
1
2
Sysmiss
2422
14487
1
2
3
Sysmiss
173
16736
1
30
13.48
11.433
2422
14487
1
2
Sysmiss
16909
1
2
3
4
5
6
16909
30
0.24
0.808
2423
14486
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
18
19
Sysmiss
916
15993
1
2
3
4
5
7
8
9
10
11
12
13
14
15
16
18
19
Sysmiss
2402
14507
1
2
Sysmiss
117
16792
1
30
5.658
6.474
2411
14498
4000000
15473.082
113314.97
2422
14487
32000000
152756.358
880215.254
2387
14522
1
2
3
4
5
6
Sysmiss
230
16679
1
2
3
4
5
6
Sysmiss
9
16900
3
4
5
6
Sysmiss
16909
1138
1138
1
2
3
4
1138
1
2
3
4
5
6
7
8
9
1137
1
1
2
3
4
5
6
7
8
9
10
11
12
15
Sysmiss
1136
2
1
2
3
4
5
7
Sysmiss
1138
1
98
6.918
4.183
1138
1
2
3
4
5
7
909
229
1
2
3
4
5
6
7
Sysmiss
245
893
1
2
3
4
5
6
7
Sysmiss
55
1083
2
3
4
5
6
7
Sysmiss
1138
15482
15482
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15482
1
2
3
15482
3840
01001
01002
01003
01004
01005
01006
01007
01008
01009
01010
01011
01012
01013
01014
01015
01016
02001
02002
02003
02004
02005
02006
02007
02008
02009
02010
02011
02012
02013
02014
02015
02016
02017
02018
02019
02020
02021
02022
02023
02024
03001
03002
03003
03004
03005
03006
03007
03008
03009
03010
03011
03012
03013
03014
03015
03016
03017
03018
03019
03020
03021
03022
03023
03024
03025
03026
03027
03028
03029
03030
03031
03032
03033
03034
03035
03036
04001
04002
04003
04004
04005
04006
04007
04008
04009
04010
04011
04012
05001
05002
05003
05004
05005
05006
05007
05008
05009
05010
05011
05012
05013
05014
05015
05016
05017
05018
05019
05020
05021
05022
05023
05024
05025
05026
05027
05028
05029
05030
05031
05032
06001
06002
06003
06004
06005
06006
06007
06008
06009
06010
06011
06012
06013
07001
07002
07003
07004
07005
07006
07007
07008
07009
07010
08001
08002
08003
08004
08005
08006
08007
08008
08009
08010
08011
08012
08013
08014
08015
08016
08017
08018
08019
08020
08021
08022
08023
08024
09001
10001
10002
10003
10004
10005
10006
10007
10008
10009
10010
12001
12002
12003
12004
12005
12006
12007
12008
12009
12010
12011
12012
12013
12014
12015
12016
12017
12018
12019
12020
12021
12022
12023
12024
12025
12026
12027
12028
12029
12030
12031
12032
12033
12034
12035
12036
12037
12038
12039
12040
12041
12042
12043
12044
12045
12046
12047
12048
12049
12050
12051
12052
12053
12054
12055
12056
12057
12058
12059
12060
12061
12062
12063
12064
12065
12066
12067
12068
12069
12070
12071
12072
12073
12074
12075
12076
12077
12078
12079
13001
13002
13003
13004
13005
13006
13007
14001
14002
14003
14004
14005
14006
14007
14008
14009
14010
14011
14012
14013
14014
14015
14016
14017
14018
14019
14020
14021
14022
15001
15002
15003
15004
15005
15006
15007
15008
15009
15010
15011
15012
16001
16002
16003
16004
16005
17001
17002
17003
17004
17005
17006
17007
17008
17009
17010
17011
17012
17013
17014
17015
17016
17017
17018
17019
17020
17021
17022
18001
18002
18003
18004
18005
18006
18007
19001
19002
19003
19004
20001
20002
20003
20004
20005
20006
20007
20008
20009
20010
20011
20012
20013
21001
21002
21003
21004
21005
21006
21007
21008
21009
21010
21011
21012
21013
21014
21015
21016
21017
21018
21019
21020
21021
21022
21023
21024
21025
22001
22002
22003
22004
22005
22006
23001
23002
24001
24002
3840
3840
1
2
3840
1
2
3840
11
242
106.362
62.772
3840
101.74
2408.711
895.273
473.267
3840
170.044
25040.539
4127.212
2779.478
3840
01001
01002
01003
01004
01005
01006
01007
01008
01009
01010
01011
01012
01013
01014
01015
01016
02001
02002
02003
02004
02005
02006
02007
02008
02009
02010
02011
02012
02013
02014
02015
02016
02017
02018
02019
02020
02021
02022
02023
02024
03001
03002
03003
03004
03005
03006
03007
03008
03009
03010
03011
03012
03013
03014
03015
03016
03017
03018
03019
03020
03021
03022
03023
03024
03025
03026
03027
03028
03029
03030
03031
03032
03033
03034
03035
03036
04001
04002
04003
04004
04005
04006
04007
04008
04009
04010
04011
04012
05001
05002
05003
05004
05005
05006
05007
05008
05009
05010
05011
05012
05013
05014
05015
05016
05017
05018
05019
05020
05021
05022
05023
05024
05025
05026
05027
05028
05029
05030
05031
05032
06001
06002
06003
06004
06005
06006
06007
06008
06009
06010
06011
06012
06013
07001
07002
07003
07004
07005
07006
07007
07008
07009
07010
08001
08002
08003
08004
08005
08006
08007
08008
08009
08010
08011
08012
08013
08014
08015
08016
08017
08018
08019
08020
08021
08022
08023
08024
09001
10001
10002
10003
10004
10005
10006
10007
10008
10009
10010
12001
12002
12003
12004
12005
12006
12007
12008
12009
12010
12011
12012
12013
12014
12015
12016
12017
12018
12019
12020
12021
12022
12023
12024
12025
12026
12027
12028
12029
12030
12031
12032
12033
12034
12035
12036
12037
12038
12039
12040
12041
12042
12043
12044
12045
12046
12047
12048
12049
12050
12051
12052
12053
12054
12055
12056
12057
12058
12059
12060
12061
12062
12063
12064
12065
12066
12067
12068
12069
12070
12071
12072
12073
12074
12075
12076
12077
12078
12079
13001
13002
13003
13004
13005
13006
13007
14001
14002
14003
14004
14005
14006
14007
14008
14009
14010
14011
14012
14013
14014
14015
14016
14017
14018
14019
14020
14021
14022
15001
15002
15003
15004
15005
15006
15007
15008
15009
15010
15011
15012
16001
16002
16003
16004
16005
17001
17002
17003
17004
17005
17006
17007
17008
17009
17010
17011
17012
17013
17014
17015
17016
17017
17018
17019
17020
17021
17022
18001
18002
18003
18004
18005
18006
18007
19001
19002
19003
19004
20001
20002
20003
20004
20005
20006
20007
20008
20009
20010
20011
20012
20013
21001
21002
21003
21004
21005
21006
21007
21008
21009
21010
21011
21012
21013
21014
21015
21016
21017
21018
21019
21020
21021
21022
21023
21024
21025
22001
22002
22003
22004
22005
22006
23001
23002
24001
24002
3840
3840
1
2
3840
1
2
3840
11
242
106.362
62.772
3840
101.74
2408.711
895.273
473.267
3840
170.044
25040.539
4127.212
2779.478
3840
01001
01002
01003
01004
01005
01006
01007
01008
01009
01010
01011
01012
01013
01014
01015
01016
02001
02002
02003
02004
02005
02006
02007
02008
02009
02010
02011
02012
02013
02014
02015
02016
02017
02018
02019
02020
02021
02022
02023
02024
03001
03002
03003
03004
03005
03006
03007
03008
03009
03010
03011
03012
03013
03014
03015
03016
03017
03018
03019
03020
03021
03022
03023
03024
03025
03026
03027
03028
03029
03030
03031
03032
03033
03034
03035
03036
04001
04002
04003
04004
04005
04006
04007
04008
04009
04010
04011
04012
05001
05002
05003
05004
05005
05006
05007
05008
05009
05010
05011
05012
05013
05014
05015
05016
05017
05018
05019
05020
05021
05022
05023
05024
05025
05026
05027
05028
05029
05030
05031
05032
06001
06002
06003
06004
06005
06006
06007
06008
06009
06010
06011
06012
06013
07001
07002
07003
07004
07005
07006
07007
07008
07009
07010
08001
08002
08003
08004
08005
08006
08007
08008
08009
08010
08011
08012
08013
08014
08015
08016
08017
08018
08019
08020
08021
08022
08023
08024
09001
10001
10002
10003
10004
10005
10006
10007
10008
10009
10010
12001
12002
12003
12004
12005
12006
12007
12008
12009
12010
12011
12012
12013
12014
12015
12016
12017
12018
12019
12020
12021
12022
12023
12024
12025
12026
12027
12028
12029
12030
12031
12032
12033
12034
12035
12036
12037
12038
12039
12040
12041
12042
12043
12044
12045
12046
12047
12048
12049
12050
12051
12052
12053
12054
12055
12056
12057
12058
12059
12060
12061
12062
12063
12064
12065
12066
12067
12068
12069
12070
12071
12072
12073
12074
12075
12076
12077
12078
12079
13001
13002
13003
13004
13005
13006
13007
14001
14002
14003
14004
14005
14006
14007
14008
14009
14010
14011
14012
14013
14014
14015
14016
14017
14018
14019
14020
14021
14022
15001
15002
15003
15004
15005
15006
15007
15008
15009
15010
15011
15012
16001
16002
16003
16004
16005
17001
17002
17003
17004
17005
17006
17007
17008
17009
17010
17011
17012
17013
17014
17015
17016
17017
17018
17019
17020
17021
17022
18001
18002
18003
18004
18005
18006
18007
19001
19002
19003
19004
20001
20002
20003
20004
20005
20006
20007
20008
20009
20010
20011
20012
20013
21001
21002
21003
21004
21005
21006
21007
21008
21009
21010
21011
21012
21013
21014
21015
21016
21017
21018
21019
21020
21021
21022
21023
21024
21025
22001
22002
22003
22004
22005
22006
23001
23002
24001
24002
3840
3840
3437849.228
1
Urban
2
Rural
3840
3437849.228
1
Urban
2
Rural
11
242
106.362
102.821
62.772
65.702
3840
3437849.228
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
3840
101.74
2408.711
895.273
473.267
16909
15848494.991
1
Urban
2
Rural
16909
15848494.991
11
242
106.817
103.575
63.045
65.666
16909
69.92
3037.031
937.282
484.084