Overview

Dataset statistics

Number of variables8
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory76.3 B

Variable types

Numeric7
Categorical1

Dataset

Description경기도 수원시 연도별 인구현황에 대한 데이터로 인구밀도, 증감률 등의 항목을 제공합니다. 잠정자료이므로 추후 변동될 수 있습니다.
Author경기도 수원시
URLhttps://www.data.go.kr/data/15051542/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연도별 is highly overall correlated with 세대1)(가구) and 4 other fieldsHigh correlation
세대1)(가구) is highly overall correlated with 연도별 and 4 other fieldsHigh correlation
인구2)_계 is highly overall correlated with 연도별 and 4 other fieldsHigh correlation
인구2)_남 is highly overall correlated with 연도별 and 4 other fieldsHigh correlation
인구2)_여 is highly overall correlated with 연도별 and 4 other fieldsHigh correlation
인구밀도_(명-제곱키로미터) is highly overall correlated with 연도별 and 4 other fieldsHigh correlation
연도별 has unique valuesUnique
세대1)(가구) has unique valuesUnique
인구2)_계 has unique valuesUnique
인구2)_남 has unique valuesUnique
인구2)_여 has unique valuesUnique
인구밀도_(명-제곱키로미터) has unique valuesUnique

Reproduction

Analysis started2024-03-14 08:34:32.513689
Analysis finished2024-03-14 08:34:46.485036
Duration13.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도별
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2011.5
Minimum2000
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-03-14T17:34:46.660016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2001.15
Q12005.75
median2011.5
Q32017.25
95-th percentile2021.85
Maximum2023
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.0035153208
Kurtosis-1.2
Mean2011.5
Median Absolute Deviation (MAD)6
Skewness0
Sum48276
Variance50
MonotonicityStrictly increasing
2024-03-14T17:34:47.039636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2000 1
 
4.2%
2013 1
 
4.2%
2023 1
 
4.2%
2022 1
 
4.2%
2021 1
 
4.2%
2020 1
 
4.2%
2019 1
 
4.2%
2018 1
 
4.2%
2017 1
 
4.2%
2016 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
2000 1
4.2%
2001 1
4.2%
2002 1
4.2%
2003 1
4.2%
2004 1
4.2%
2005 1
4.2%
2006 1
4.2%
2007 1
4.2%
2008 1
4.2%
2009 1
4.2%
ValueCountFrequency (%)
2023 1
4.2%
2022 1
4.2%
2021 1
4.2%
2020 1
4.2%
2019 1
4.2%
2018 1
4.2%
2017 1
4.2%
2016 1
4.2%
2015 1
4.2%
2014 1
4.2%

세대1)(가구)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean428349.33
Minimum285511
Maximum537078
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-03-14T17:34:47.399511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum285511
5-th percentile326039.5
Q1388128
median421913
Q3485903.25
95-th percentile526883
Maximum537078
Range251567
Interquartile range (IQR)97775.25

Descriptive statistics

Standard deviation68996.683
Coefficient of variation (CV)0.16107573
Kurtosis-0.75851334
Mean428349.33
Median Absolute Deviation (MAD)58945.5
Skewness-0.21134404
Sum10280384
Variance4.7605423 × 109
MonotonicityNot monotonic
2024-03-14T17:34:47.772549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
285511 1
 
4.2%
439996 1
 
4.2%
537078 1
 
4.2%
528482 1
 
4.2%
517822 1
 
4.2%
506950 1
 
4.2%
498836 1
 
4.2%
492939 1
 
4.2%
483558 1
 
4.2%
472194 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
285511 1
4.2%
322621 1
4.2%
345411 1
4.2%
346371 1
4.2%
359103 1
4.2%
365667 1
4.2%
395615 1
4.2%
399898 1
4.2%
402462 1
4.2%
406565 1
4.2%
ValueCountFrequency (%)
537078 1
4.2%
528482 1
4.2%
517822 1
4.2%
506950 1
4.2%
498836 1
4.2%
492939 1
4.2%
483558 1
4.2%
472194 1
4.2%
463154 1
4.2%
454072 1
4.2%

인구2)_계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1135859.5
Minimum946704
Maximum1242212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-03-14T17:34:48.116707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum946704
5-th percentile985474.55
Q11072731.5
median1133087.5
Q31222745.8
95-th percentile1239661.3
Maximum1242212
Range295508
Interquartile range (IQR)150014.25

Descriptive statistics

Standard deviation92496.521
Coefficient of variation (CV)0.081433069
Kurtosis-1.0693165
Mean1135859.5
Median Absolute Deviation (MAD)88931
Skewness-0.41151096
Sum27260627
Variance8.5556065 × 109
MonotonicityNot monotonic
2024-03-14T17:34:48.504712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
946704 1
 
4.2%
1178509 1
 
4.2%
1233424 1
 
4.2%
1225058 1
 
4.2%
1216965 1
 
4.2%
1221913 1
 
4.2%
1235022 1
 
4.2%
1242212 1
 
4.2%
1240480 1
 
4.2%
1231224 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
946704 1
4.2%
978698 1
4.2%
1023875 1
4.2%
1040223 1
4.2%
1042132 1
4.2%
1044113 1
4.2%
1082271 1
4.2%
1086773 1
4.2%
1090678 1
4.2%
1098364 1
4.2%
ValueCountFrequency (%)
1242212 1
4.2%
1240480 1
4.2%
1235022 1
4.2%
1233424 1
4.2%
1231224 1
4.2%
1225058 1
4.2%
1221975 1
4.2%
1221913 1
4.2%
1216965 1
4.2%
1209169 1
4.2%

인구2)_남
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean571790.83
Minimum476639
Maximum627004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-03-14T17:34:48.865609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum476639
5-th percentile495772.2
Q1539190.25
median570536.5
Q3615947.75
95-th percentile625469.2
Maximum627004
Range150365
Interquartile range (IQR)76757.5

Descriptive statistics

Standard deviation47061.253
Coefficient of variation (CV)0.082305014
Kurtosis-1.1114914
Mean571790.83
Median Absolute Deviation (MAD)45147
Skewness-0.39161178
Sum13722980
Variance2.2147615 × 109
MonotonicityNot monotonic
2024-03-14T17:34:49.249234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
476639 1
 
4.2%
593469 1
 
4.2%
620183 1
 
4.2%
616628 1
 
4.2%
612695 1
 
4.2%
615721 1
 
4.2%
622909 1
 
4.2%
627004 1
 
4.2%
625921 1
 
4.2%
620498 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
476639 1
4.2%
492366 1
4.2%
515074 1
4.2%
522912 1
4.2%
523215 1
4.2%
525544 1
4.2%
543739 1
4.2%
545777 1
4.2%
547640 1
4.2%
552244 1
4.2%
ValueCountFrequency (%)
627004 1
4.2%
625921 1
4.2%
622909 1
4.2%
620498 1
4.2%
620183 1
4.2%
616628 1
4.2%
615721 1
4.2%
615646 1
4.2%
612695 1
4.2%
609213 1
4.2%

인구2)_여
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean564068.62
Minimum470065
Maximum615208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-03-14T17:34:49.609304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum470065
5-th percentile489702.35
Q1533628.25
median562551
Q3606854.25
95-th percentile614361.3
Maximum615208
Range145143
Interquartile range (IQR)73226

Descriptive statistics

Standard deviation45446.079
Coefficient of variation (CV)0.08056835
Kurtosis-1.0236562
Mean564068.62
Median Absolute Deviation (MAD)43709.5
Skewness-0.4319697
Sum13537647
Variance2.0653461 × 109
MonotonicityNot monotonic
2024-03-14T17:34:49.999216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
470065 1
 
4.2%
585040 1
 
4.2%
613241 1
 
4.2%
608430 1
 
4.2%
604270 1
 
4.2%
606192 1
 
4.2%
612113 1
 
4.2%
615208 1
 
4.2%
614559 1
 
4.2%
610726 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
470065 1
4.2%
486332 1
4.2%
508801 1
4.2%
517311 1
4.2%
518569 1
4.2%
518917 1
4.2%
538532 1
4.2%
540996 1
4.2%
543038 1
4.2%
546120 1
4.2%
ValueCountFrequency (%)
615208 1
4.2%
614559 1
4.2%
613241 1
4.2%
612113 1
4.2%
610726 1
4.2%
608430 1
4.2%
606329 1
4.2%
606192 1
4.2%
604270 1
4.2%
599956 1
4.2%

인구밀도_(명-제곱키로미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9364.7083
Minimum7816
Maximum10262
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-03-14T17:34:50.373543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7816
5-th percentile8137.95
Q18862
median9271
Q310100.25
95-th percentile10239.8
Maximum10262
Range2446
Interquartile range (IQR)1238.25

Descriptive statistics

Standard deviation760.41336
Coefficient of variation (CV)0.081199898
Kurtosis-1.0577654
Mean9364.7083
Median Absolute Deviation (MAD)748.5
Skewness-0.35160984
Sum224753
Variance578228.48
MonotonicityNot monotonic
2024-03-14T17:34:50.908662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
7816 1
 
4.2%
9301 1
 
4.2%
10186 1
 
4.2%
10116 1
 
4.2%
10050 1
 
4.2%
10091 1
 
4.2%
10199 1
 
4.2%
10262 1
 
4.2%
10247 1
 
4.2%
10171 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
7816 1
4.2%
8082 1
4.2%
8455 1
4.2%
8592 1
4.2%
8609 1
4.2%
8625 1
4.2%
8941 1
4.2%
8980 1
4.2%
9013 1
4.2%
9077 1
4.2%
ValueCountFrequency (%)
10262 1
4.2%
10247 1
4.2%
10199 1
4.2%
10186 1
4.2%
10171 1
4.2%
10116 1
4.2%
10095 1
4.2%
10091 1
4.2%
10050 1
4.2%
9989 1
4.2%

인구밀도_증감률(퍼센트)
Real number (ℝ)

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2845833
Minimum-1.95
Maximum7.4
Zeros0
Zeros (%)0.0%
Negative4
Negative (%)16.7%
Memory size344.0 B
2024-03-14T17:34:51.267304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-1.95
5-th percentile-0.988
Q10.1975
median0.7
Q31.87
95-th percentile4.4865
Maximum7.4
Range9.35
Interquartile range (IQR)1.6725

Descriptive statistics

Standard deviation2.0463817
Coefficient of variation (CV)1.5930315
Kurtosis2.295456
Mean1.2845833
Median Absolute Deviation (MAD)0.545
Skewness1.33426
Sum30.83
Variance4.1876781
MonotonicityNot monotonic
2024-03-14T17:34:51.645128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.75 2
 
8.3%
3.73 1
 
4.2%
3.41 1
 
4.2%
0.69 1
 
4.2%
0.65 1
 
4.2%
-0.4 1
 
4.2%
-1.06 1
 
4.2%
-0.58 1
 
4.2%
0.14 1
 
4.2%
1.06 1
 
4.2%
Other values (13) 13
54.2%
ValueCountFrequency (%)
-1.95 1
4.2%
-1.06 1
4.2%
-0.58 1
4.2%
-0.4 1
4.2%
0.14 1
4.2%
0.19 1
4.2%
0.2 1
4.2%
0.37 1
4.2%
0.44 1
4.2%
0.57 1
4.2%
ValueCountFrequency (%)
7.4 1
4.2%
4.62 1
4.2%
3.73 1
4.2%
3.65 1
4.2%
3.41 1
4.2%
2.65 1
4.2%
1.61 1
4.2%
1.23 1
4.2%
1.06 1
4.2%
0.75 2
8.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size320.0 B
2023-12-31
24 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12-31
2nd row2023-12-31
3rd row2023-12-31
4th row2023-12-31
5th row2023-12-31

Common Values

ValueCountFrequency (%)
2023-12-31 24
100.0%

Length

2024-03-14T17:34:52.026190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:34:52.312093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-31 24
100.0%

Interactions

2024-03-14T17:34:44.113011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:32.755050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:34.452548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:36.128537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:38.074954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:40.157568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:42.396022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:44.344192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:32.986962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:34.681129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:36.370766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:38.315408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:40.493870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:42.652535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:44.572758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:33.220388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:34.912470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:36.610453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:38.558671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:40.812286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:42.890856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:44.819320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:33.475791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:35.160733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:37.052197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:38.816871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:41.115484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:43.139762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:45.067879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:33.727063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:35.411043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:37.334031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:39.153709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:41.419582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:43.394072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:45.324237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:33.988132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:35.665003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:37.592314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:39.537917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:41.751522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:43.646863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:45.565938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:34.219888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:35.897083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:37.834412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:39.833356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:42.116600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:34:43.878416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T17:34:52.490529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도별세대1)(가구)인구2)_계인구2)_남인구2)_여인구밀도_(명-제곱키로미터)인구밀도_증감률(퍼센트)
연도별1.0000.8650.7980.7980.7770.8570.420
세대1)(가구)0.8651.0000.9420.9420.9300.8530.246
인구2)_계0.7980.9421.0001.0000.9991.0000.855
인구2)_남0.7980.9421.0001.0000.9991.0000.855
인구2)_여0.7770.9300.9990.9991.0000.9810.861
인구밀도_(명-제곱키로미터)0.8570.8531.0001.0000.9811.0000.910
인구밀도_증감률(퍼센트)0.4200.2460.8550.8550.8610.9101.000
2024-03-14T17:34:52.748116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도별세대1)(가구)인구2)_계인구2)_남인구2)_여인구밀도_(명-제곱키로미터)인구밀도_증감률(퍼센트)
연도별1.0000.9970.9370.9360.9400.937-0.461
세대1)(가구)0.9971.0000.9350.9330.9400.934-0.450
인구2)_계0.9370.9351.0000.9980.9980.999-0.403
인구2)_남0.9360.9330.9981.0000.9960.997-0.413
인구2)_여0.9400.9400.9980.9961.0000.997-0.394
인구밀도_(명-제곱키로미터)0.9370.9340.9990.9970.9971.000-0.387
인구밀도_증감률(퍼센트)-0.461-0.450-0.403-0.413-0.394-0.3871.000

Missing values

2024-03-14T17:34:45.893451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T17:34:46.313115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연도별세대1)(가구)인구2)_계인구2)_남인구2)_여인구밀도_(명-제곱키로미터)인구밀도_증감률(퍼센트)데이터기준일자
0200028551194670447663947006578163.732023-12-31
1200132262197869849236648633280823.412023-12-31
22002345411102387551507450880184554.622023-12-31
32003359103104022352291251731185921.612023-12-31
42004365667104213252321551891786090.22023-12-31
52005346371104411352554451856986250.192023-12-31
62006395615108227154373953853289413.652023-12-31
72007399898108677354577754099689800.442023-12-31
82008402462109067854764054303890130.372023-12-31
92009406565109836455224454612090770.712023-12-31
연도별세대1)(가구)인구2)_계인구2)_남인구2)_여인구밀도_(명-제곱키로미터)인구밀도_증감률(퍼센트)데이터기준일자
142014454072120916960921359995699897.42023-12-31
1520154631541221975615646606329100951.062023-12-31
1620164721941231224620498610726101710.752023-12-31
1720174835581240480625921614559102470.752023-12-31
1820184929391242212627004615208102620.142023-12-31
192019498836123502262290961211310199-0.582023-12-31
202020506950122191361572160619210091-1.062023-12-31
212021517822121696561269560427010050-0.42023-12-31
2220225284821225058616628608430101160.652023-12-31
2320235370781233424620183613241101860.692023-12-31