Overview

Dataset statistics

Number of variables22
Number of observations9350
Missing cells216
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 MiB
Average record size in memory192.0 B

Variable types

Categorical4
Numeric16
Text2

Dataset

Description2022년 1월 ~ 2023년 5월 서울특별시 구단위별, 연령별 건강보험 적용인구 수 1. 연월: 2022년 1월 ~ 2023년 5월(월단위) 2. 시도, 시군구: 서울특별시, 구단위 3. 연령: 0~99세(5세 단위), 100세 이상 - (지역가입자) 적용인구수, 세대주수, 세대원수, 세대수, 평균부양자수_남녀 구분 - (직장가입자) 적용인구수, 직장가입자수, 피부양자수, 평균피부양자수_남녀 구분 ※ 민원인의 제공 신청에 따른 제공 건으로서 2023-07-10 발췌
Author공공데이터포털
URLhttps://www.data.go.kr/data/15116517/fileData.do

Alerts

시도 has constant value ""Constant
(지역-남자)평균부양자수 has 111 (1.2%) missing valuesMissing
(지역-여자)평균부양자수 has 105 (1.1%) missing valuesMissing
(직장-남자)적용인구수 is highly skewed (γ1 = 55.79030572)Skewed
(직장-여자)적용인구수 is highly skewed (γ1 = 55.78865486)Skewed
(직장-남자)직장가입자수 is highly skewed (γ1 = 55.7643822)Skewed
(직장-여자)직장가입자수 is highly skewed (γ1 = 55.73321977)Skewed
(직장-남자)피부양자수 is highly skewed (γ1 = 55.78347048)Skewed
(직장-여자)피부양자수 is highly skewed (γ1 = 55.79905189)Skewed
(지역-남자)세대주수 has 111 (1.2%) zerosZeros
(지역-여자)세대주수 has 105 (1.1%) zerosZeros
(지역-남자)세대수 has 98 (1.0%) zerosZeros
(지역-여자)세대수 has 101 (1.1%) zerosZeros
(직장-남자)적용인구수 has 98 (1.0%) zerosZeros
(직장-여자)적용인구수 has 97 (1.0%) zerosZeros
(직장-남자)직장가입자수 has 1467 (15.7%) zerosZeros
(직장-여자)직장가입자수 has 1924 (20.6%) zerosZeros
(직장-남자)피부양자수 has 99 (1.1%) zerosZeros
(직장-여자)피부양자수 has 97 (1.0%) zerosZeros

Reproduction

Analysis started2024-04-17 14:18:21.279808
Analysis finished2024-04-17 14:18:21.730155
Duration0.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연월
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size73.2 KiB
2022년1월
 
550
2022년2월
 
550
2022년3월
 
550
2022년4월
 
550
2022년5월
 
550
Other values (12)
6600 

Length

Max length8
Median length7
Mean length7.1764706
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022년1월
2nd row2022년1월
3rd row2022년1월
4th row2022년1월
5th row2022년1월

Common Values

ValueCountFrequency (%)
2022년1월 550
 
5.9%
2022년2월 550
 
5.9%
2022년3월 550
 
5.9%
2022년4월 550
 
5.9%
2022년5월 550
 
5.9%
2022년6월 550
 
5.9%
2022년7월 550
 
5.9%
2022년8월 550
 
5.9%
2022년9월 550
 
5.9%
2022년10월 550
 
5.9%
Other values (7) 3850
41.2%

Length

2024-04-17T23:18:21.782779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2022년1월 550
 
5.9%
2022년10월 550
 
5.9%
2023년4월 550
 
5.9%
2023년3월 550
 
5.9%
2023년2월 550
 
5.9%
2023년1월 550
 
5.9%
2022년12월 550
 
5.9%
2022년11월 550
 
5.9%
2022년9월 550
 
5.9%
2022년2월 550
 
5.9%
Other values (7) 3850
41.2%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size73.2 KiB
서울특별시
9350 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row서울특별시
3rd row서울특별시
4th row서울특별시
5th row서울특별시

Common Values

ValueCountFrequency (%)
서울특별시 9350
100.0%

Length

2024-04-17T23:18:21.877547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T23:18:21.947044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 9350
100.0%

시군구
Categorical

Distinct25
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size73.2 KiB
종로구
 
374
중구
 
374
용산구
 
374
성동구
 
374
광진구
 
374
Other values (20)
7480 

Length

Max length4
Median length3
Mean length3.08
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row종로구
2nd row종로구
3rd row종로구
4th row종로구
5th row종로구

Common Values

ValueCountFrequency (%)
종로구 374
 
4.0%
중구 374
 
4.0%
용산구 374
 
4.0%
성동구 374
 
4.0%
광진구 374
 
4.0%
동대문구 374
 
4.0%
중랑구 374
 
4.0%
성북구 374
 
4.0%
강북구 374
 
4.0%
도봉구 374
 
4.0%
Other values (15) 5610
60.0%

Length

2024-04-17T23:18:22.029848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
종로구 374
 
4.0%
마포구 374
 
4.0%
송파구 374
 
4.0%
강남구 374
 
4.0%
서초구 374
 
4.0%
관악구 374
 
4.0%
동작구 374
 
4.0%
영등포구 374
 
4.0%
금천구 374
 
4.0%
구로구 374
 
4.0%
Other values (15) 5610
60.0%

연령
Categorical

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size73.2 KiB
0세
 
425
1-4세
 
425
5-9세
 
425
10-14세
 
425
15-19세
 
425
Other values (17)
7225 

Length

Max length6
Median length6
Mean length5.6363636
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0세
2nd row1-4세
3rd row5-9세
4th row10-14세
5th row15-19세

Common Values

ValueCountFrequency (%)
0세 425
 
4.5%
1-4세 425
 
4.5%
5-9세 425
 
4.5%
10-14세 425
 
4.5%
15-19세 425
 
4.5%
20-24세 425
 
4.5%
25-29세 425
 
4.5%
30-34세 425
 
4.5%
35-39세 425
 
4.5%
40-44세 425
 
4.5%
Other values (12) 5100
54.5%

Length

2024-04-17T23:18:22.143884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0세 425
 
4.5%
1-4세 425
 
4.5%
95-99세 425
 
4.5%
90-94세 425
 
4.5%
85-89세 425
 
4.5%
80-84세 425
 
4.5%
75-79세 425
 
4.5%
70-74세 425
 
4.5%
65-69세 425
 
4.5%
60-64세 425
 
4.5%
Other values (12) 5100
54.5%

(지역-남자)적용인구수
Real number (ℝ)

Distinct4476
Distinct (%)47.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2326.1933
Minimum1
Maximum9243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:22.256330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15
Q1623
median1923
Q33793
95-th percentile5854
Maximum9243
Range9242
Interquartile range (IQR)3170

Descriptive statistics

Standard deviation1909.0551
Coefficient of variation (CV)0.82067779
Kurtosis-0.53819574
Mean2326.1933
Median Absolute Deviation (MAD)1506
Skewness0.59486241
Sum21749907
Variance3644491.5
MonotonicityNot monotonic
2024-04-17T23:18:22.377207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 106
 
1.1%
4 85
 
0.9%
3 78
 
0.8%
6 61
 
0.7%
2 43
 
0.5%
20 28
 
0.3%
24 25
 
0.3%
19 25
 
0.3%
26 25
 
0.3%
23 24
 
0.3%
Other values (4466) 8850
94.7%
ValueCountFrequency (%)
1 19
 
0.2%
2 43
0.5%
3 78
0.8%
4 85
0.9%
5 106
1.1%
6 61
0.7%
7 21
 
0.2%
8 9
 
0.1%
9 6
 
0.1%
10 4
 
< 0.1%
ValueCountFrequency (%)
9243 1
< 0.1%
9215 1
< 0.1%
9156 1
< 0.1%
9135 1
< 0.1%
9125 1
< 0.1%
9107 1
< 0.1%
8952 1
< 0.1%
8896 1
< 0.1%
8823 1
< 0.1%
8720 1
< 0.1%

(지역-여자)적용인구수
Real number (ℝ)

Distinct4662
Distinct (%)49.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2503.6612
Minimum3
Maximum9607
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:22.498417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile49
Q1782
median2090
Q33951
95-th percentile6180
Maximum9607
Range9604
Interquartile range (IQR)3169

Descriptive statistics

Standard deviation2006.7633
Coefficient of variation (CV)0.8015315
Kurtosis-0.52783752
Mean2503.6612
Median Absolute Deviation (MAD)1574
Skewness0.60851349
Sum23409232
Variance4027098.9
MonotonicityNot monotonic
2024-04-17T23:18:22.859660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16 31
 
0.3%
14 30
 
0.3%
12 30
 
0.3%
11 28
 
0.3%
19 27
 
0.3%
17 27
 
0.3%
15 26
 
0.3%
5 26
 
0.3%
13 24
 
0.3%
10 19
 
0.2%
Other values (4652) 9082
97.1%
ValueCountFrequency (%)
3 1
 
< 0.1%
4 13
0.1%
5 26
0.3%
6 18
0.2%
7 10
 
0.1%
8 9
 
0.1%
9 11
 
0.1%
10 19
0.2%
11 28
0.3%
12 30
0.3%
ValueCountFrequency (%)
9607 1
< 0.1%
9504 1
< 0.1%
9496 1
< 0.1%
9400 1
< 0.1%
9381 1
< 0.1%
9321 1
< 0.1%
9270 1
< 0.1%
9173 1
< 0.1%
9092 1
< 0.1%
9070 1
< 0.1%

(지역-남자)세대주수
Real number (ℝ)

ZEROS 

Distinct3587
Distinct (%)38.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1504.2329
Minimum0
Maximum6785
Zeros111
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:22.974650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q171
median1098
Q32526
95-th percentile4623.1
Maximum6785
Range6785
Interquartile range (IQR)2455

Descriptive statistics

Standard deviation1568.541
Coefficient of variation (CV)1.0427514
Kurtosis-0.130617
Mean1504.2329
Median Absolute Deviation (MAD)1066
Skewness0.89326925
Sum14064578
Variance2460321
MonotonicityNot monotonic
2024-04-17T23:18:23.094056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 220
 
2.4%
1 161
 
1.7%
4 133
 
1.4%
3 123
 
1.3%
0 111
 
1.2%
5 79
 
0.8%
15 61
 
0.7%
17 56
 
0.6%
18 51
 
0.5%
14 48
 
0.5%
Other values (3577) 8307
88.8%
ValueCountFrequency (%)
0 111
1.2%
1 161
1.7%
2 220
2.4%
3 123
1.3%
4 133
1.4%
5 79
 
0.8%
6 47
 
0.5%
7 27
 
0.3%
8 28
 
0.3%
9 31
 
0.3%
ValueCountFrequency (%)
6785 1
< 0.1%
6728 1
< 0.1%
6720 1
< 0.1%
6693 1
< 0.1%
6667 1
< 0.1%
6642 1
< 0.1%
6542 1
< 0.1%
6525 1
< 0.1%
6394 1
< 0.1%
6374 1
< 0.1%

(지역-여자)세대주수
Real number (ℝ)

ZEROS 

Distinct2839
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1047.9467
Minimum0
Maximum6481
Zeros105
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:23.232971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q179
median917
Q31712
95-th percentile2896.1
Maximum6481
Range6481
Interquartile range (IQR)1633

Descriptive statistics

Standard deviation998.19027
Coefficient of variation (CV)0.95252004
Kurtosis0.55416892
Mean1047.9467
Median Absolute Deviation (MAD)829
Skewness0.85885198
Sum9798302
Variance996383.81
MonotonicityNot monotonic
2024-04-17T23:18:23.356688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 159
 
1.7%
1 149
 
1.6%
3 106
 
1.1%
0 105
 
1.1%
6 94
 
1.0%
5 89
 
1.0%
4 80
 
0.9%
7 54
 
0.6%
27 47
 
0.5%
9 45
 
0.5%
Other values (2829) 8422
90.1%
ValueCountFrequency (%)
0 105
1.1%
1 149
1.6%
2 159
1.7%
3 106
1.1%
4 80
0.9%
5 89
1.0%
6 94
1.0%
7 54
 
0.6%
8 41
 
0.4%
9 45
 
0.5%
ValueCountFrequency (%)
6481 1
< 0.1%
6474 1
< 0.1%
6470 1
< 0.1%
6288 1
< 0.1%
6251 1
< 0.1%
6186 1
< 0.1%
5973 1
< 0.1%
5943 1
< 0.1%
5928 1
< 0.1%
5802 1
< 0.1%

(지역-남자)세대원수
Real number (ℝ)

Distinct2344
Distinct (%)25.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean821.96032
Minimum0
Maximum3046
Zeros72
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:23.475067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q1161
median661
Q31371
95-th percentile2111
Maximum3046
Range3046
Interquartile range (IQR)1210

Descriptive statistics

Standard deviation712.31762
Coefficient of variation (CV)0.86660828
Kurtosis-0.60568475
Mean821.96032
Median Absolute Deviation (MAD)555.5
Skewness0.63189284
Sum7685329
Variance507396.39
MonotonicityNot monotonic
2024-04-17T23:18:23.600328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 176
 
1.9%
2 119
 
1.3%
4 72
 
0.8%
0 72
 
0.8%
3 68
 
0.7%
5 59
 
0.6%
7 55
 
0.6%
6 43
 
0.5%
9 40
 
0.4%
8 37
 
0.4%
Other values (2334) 8609
92.1%
ValueCountFrequency (%)
0 72
0.8%
1 176
1.9%
2 119
1.3%
3 68
 
0.7%
4 72
0.8%
5 59
 
0.6%
6 43
 
0.5%
7 55
 
0.6%
8 37
 
0.4%
9 40
 
0.4%
ValueCountFrequency (%)
3046 1
< 0.1%
3042 1
< 0.1%
3035 1
< 0.1%
3012 1
< 0.1%
2996 1
< 0.1%
2987 1
< 0.1%
2948 1
< 0.1%
2936 1
< 0.1%
2920 1
< 0.1%
2908 1
< 0.1%

(지역-여자)세대원수
Real number (ℝ)

Distinct3349
Distinct (%)35.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1455.7144
Minimum2
Maximum6067
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:23.739311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile28
Q1517.25
median1319.5
Q32191
95-th percentile3460.1
Maximum6067
Range6065
Interquartile range (IQR)1673.75

Descriptive statistics

Standard deviation1104.0941
Coefficient of variation (CV)0.75845516
Kurtosis-0.082106669
Mean1455.7144
Median Absolute Deviation (MAD)837.5
Skewness0.63416794
Sum13610930
Variance1219023.8
MonotonicityNot monotonic
2024-04-17T23:18:23.858906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 45
 
0.5%
7 40
 
0.4%
13 36
 
0.4%
3 33
 
0.4%
6 31
 
0.3%
10 30
 
0.3%
14 29
 
0.3%
11 27
 
0.3%
12 25
 
0.3%
9 23
 
0.2%
Other values (3339) 9031
96.6%
ValueCountFrequency (%)
2 9
 
0.1%
3 33
0.4%
4 19
0.2%
5 19
0.2%
6 31
0.3%
7 40
0.4%
8 45
0.5%
9 23
0.2%
10 30
0.3%
11 27
0.3%
ValueCountFrequency (%)
6067 1
< 0.1%
6034 1
< 0.1%
5996 1
< 0.1%
5893 1
< 0.1%
5870 1
< 0.1%
5823 1
< 0.1%
5741 1
< 0.1%
5708 1
< 0.1%
5707 1
< 0.1%
5699 1
< 0.1%

(지역-남자)세대수
Real number (ℝ)

ZEROS 

Distinct4048
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1918.8256
Minimum0
Maximum9086
Zeros98
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:23.978115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q185
median1321.5
Q33238.75
95-th percentile5948
Maximum9086
Range9086
Interquartile range (IQR)3153.75

Descriptive statistics

Standard deviation2026.3024
Coefficient of variation (CV)1.0560118
Kurtosis-0.18232065
Mean1918.8256
Median Absolute Deviation (MAD)1289.5
Skewness0.90264503
Sum17941019
Variance4105901.3
MonotonicityNot monotonic
2024-04-17T23:18:24.093057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 193
 
2.1%
1 141
 
1.5%
3 125
 
1.3%
4 108
 
1.2%
5 99
 
1.1%
0 98
 
1.0%
21 57
 
0.6%
18 52
 
0.6%
27 52
 
0.6%
6 50
 
0.5%
Other values (4038) 8375
89.6%
ValueCountFrequency (%)
0 98
1.0%
1 141
1.5%
2 193
2.1%
3 125
1.3%
4 108
1.2%
5 99
1.1%
6 50
 
0.5%
7 30
 
0.3%
8 22
 
0.2%
9 23
 
0.2%
ValueCountFrequency (%)
9086 1
< 0.1%
8900 1
< 0.1%
8827 1
< 0.1%
8823 1
< 0.1%
8751 1
< 0.1%
8746 1
< 0.1%
8583 1
< 0.1%
8575 1
< 0.1%
8539 1
< 0.1%
8465 1
< 0.1%

(지역-여자)세대수
Real number (ℝ)

ZEROS 

Distinct3176
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1255.38
Minimum0
Maximum6960
Zeros101
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:24.213586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q193
median1093
Q32075
95-th percentile3433.55
Maximum6960
Range6960
Interquartile range (IQR)1982

Descriptive statistics

Standard deviation1178.5812
Coefficient of variation (CV)0.93882425
Kurtosis-0.062851978
Mean1255.38
Median Absolute Deviation (MAD)997
Skewness0.74278331
Sum11737803
Variance1389053.6
MonotonicityNot monotonic
2024-04-17T23:18:24.350688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 128
 
1.4%
1 123
 
1.3%
3 106
 
1.1%
0 101
 
1.1%
6 89
 
1.0%
5 82
 
0.9%
4 72
 
0.8%
7 71
 
0.8%
8 46
 
0.5%
35 44
 
0.5%
Other values (3166) 8488
90.8%
ValueCountFrequency (%)
0 101
1.1%
1 123
1.3%
2 128
1.4%
3 106
1.1%
4 72
0.8%
5 82
0.9%
6 89
1.0%
7 71
0.8%
8 46
 
0.5%
9 42
 
0.4%
ValueCountFrequency (%)
6960 1
< 0.1%
6947 1
< 0.1%
6944 1
< 0.1%
6777 1
< 0.1%
6740 1
< 0.1%
6667 1
< 0.1%
6428 1
< 0.1%
6394 1
< 0.1%
6387 1
< 0.1%
6265 1
< 0.1%

(지역-남자)평균부양자수
Real number (ℝ)

MISSING 

Distinct3468
Distinct (%)37.5%
Missing111
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean7.1621271
Minimum0
Maximum189
Zeros72
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:24.519579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.13
Q10.1708876
median0.49
Q32.33
95-th percentile37.5
Maximum189
Range189
Interquartile range (IQR)2.1591124

Descriptive statistics

Standard deviation18.053138
Coefficient of variation (CV)2.5206392
Kurtosis29.81545
Mean7.1621271
Median Absolute Deviation (MAD)0.34
Skewness4.7334874
Sum66170.892
Variance325.91581
MonotonicityNot monotonic
2024-04-17T23:18:24.689526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.15 399
 
4.3%
0.14 331
 
3.5%
0.13 275
 
2.9%
0.16 262
 
2.8%
0.17 212
 
2.3%
0.12 176
 
1.9%
0.18 144
 
1.5%
0.2 119
 
1.3%
0.5 117
 
1.3%
0.21 106
 
1.1%
Other values (3458) 7098
75.9%
(Missing) 111
 
1.2%
ValueCountFrequency (%)
0.0 72
0.8%
0.096969697 1
 
< 0.1%
0.1 11
 
0.1%
0.100253165 1
 
< 0.1%
0.102051282 1
 
< 0.1%
0.102164066 1
 
< 0.1%
0.106666667 1
 
< 0.1%
0.10738255 1
 
< 0.1%
0.108739159 1
 
< 0.1%
0.109483794 1
 
< 0.1%
ValueCountFrequency (%)
189.0 1
 
< 0.1%
178.0 1
 
< 0.1%
176.0 1
 
< 0.1%
175.0 1
 
< 0.1%
173.0 1
 
< 0.1%
172.0 4
< 0.1%
171.0 2
< 0.1%
169.0 2
< 0.1%
168.0 1
 
< 0.1%
167.0 1
 
< 0.1%

(지역-여자)평균부양자수
Real number (ℝ)

MISSING 

Distinct3514
Distinct (%)38.0%
Missing105
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean7.8800396
Minimum0.29
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:24.884526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.29
5-th percentile0.78
Q11.08
median1.36
Q32.5
95-th percentile41.902
Maximum200
Range199.71
Interquartile range (IQR)1.42

Descriptive statistics

Standard deviation18.439942
Coefficient of variation (CV)2.3400824
Kurtosis28.286079
Mean7.8800396
Median Absolute Deviation (MAD)0.3617497
Skewness4.6526474
Sum72850.966
Variance340.03145
MonotonicityNot monotonic
2024-04-17T23:18:25.030574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.33 96
 
1.0%
1.04 88
 
0.9%
1.2 78
 
0.8%
1.0 78
 
0.8%
0.89 75
 
0.8%
1.26 74
 
0.8%
1.21 73
 
0.8%
1.32 71
 
0.8%
1.1 71
 
0.8%
1.4 70
 
0.7%
Other values (3504) 8471
90.6%
(Missing) 105
 
1.1%
ValueCountFrequency (%)
0.29 1
 
< 0.1%
0.3 2
 
< 0.1%
0.31 3
 
< 0.1%
0.32 5
0.1%
0.33 2
 
< 0.1%
0.34 8
0.1%
0.35 4
< 0.1%
0.36 5
0.1%
0.37 1
 
< 0.1%
0.373748023 1
 
< 0.1%
ValueCountFrequency (%)
200.0 1
< 0.1%
199.0 1
< 0.1%
194.0 1
< 0.1%
190.0 1
< 0.1%
189.0 1
< 0.1%
187.0 1
< 0.1%
185.0 1
< 0.1%
178.0 1
< 0.1%
177.0 2
< 0.1%
175.0 1
< 0.1%

(직장-남자)적용인구수
Real number (ℝ)

SKEWED  ZEROS 

Distinct6243
Distinct (%)66.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12049.487
Minimum0
Maximum18727138
Zeros98
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:25.192950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17
Q11526.25
median5052
Q39480
95-th percentile15027.2
Maximum18727138
Range18727138
Interquartile range (IQR)7953.75

Descriptive statistics

Standard deviation334379.74
Coefficient of variation (CV)27.750539
Kurtosis3111.9577
Mean12049.487
Median Absolute Deviation (MAD)3995
Skewness55.790306
Sum1.126627 × 108
Variance1.1180981 × 1011
MonotonicityNot monotonic
2024-04-17T23:18:25.327485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 98
 
1.0%
5 79
 
0.8%
6 66
 
0.7%
7 48
 
0.5%
4 47
 
0.5%
8 39
 
0.4%
3 22
 
0.2%
2 20
 
0.2%
37 19
 
0.2%
36 17
 
0.2%
Other values (6233) 8895
95.1%
ValueCountFrequency (%)
0 98
1.0%
1 3
 
< 0.1%
2 20
 
0.2%
3 22
 
0.2%
4 47
0.5%
5 79
0.8%
6 66
0.7%
7 48
0.5%
8 39
 
0.4%
9 17
 
0.2%
ValueCountFrequency (%)
18727138 1
< 0.1%
18667002 1
< 0.1%
18625804 1
< 0.1%
28807 1
< 0.1%
28717 1
< 0.1%
28605 1
< 0.1%
28511 1
< 0.1%
28447 1
< 0.1%
28404 1
< 0.1%
28351 1
< 0.1%

(직장-여자)적용인구수
Real number (ℝ)

SKEWED  ZEROS 

Distinct6547
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12379.85
Minimum0
Maximum18633926
Zeros97
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:25.456185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile64.45
Q11854
median5366
Q39994
95-th percentile15928.4
Maximum18633926
Range18633926
Interquartile range (IQR)8140

Descriptive statistics

Standard deviation332983.01
Coefficient of variation (CV)26.897177
Kurtosis3111.8173
Mean12379.85
Median Absolute Deviation (MAD)3937
Skewness55.788655
Sum1.157516 × 108
Variance1.1087768 × 1011
MonotonicityNot monotonic
2024-04-17T23:18:25.578275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 97
 
1.0%
24 25
 
0.3%
19 25
 
0.3%
25 22
 
0.2%
18 21
 
0.2%
26 21
 
0.2%
14 21
 
0.2%
17 16
 
0.2%
22 15
 
0.2%
23 14
 
0.1%
Other values (6537) 9073
97.0%
ValueCountFrequency (%)
0 97
1.0%
7 2
 
< 0.1%
8 5
 
0.1%
9 9
 
0.1%
10 11
 
0.1%
11 12
 
0.1%
12 12
 
0.1%
13 12
 
0.1%
14 21
 
0.2%
15 10
 
0.1%
ValueCountFrequency (%)
18633926 1
< 0.1%
18580760 1
< 0.1%
18572006 1
< 0.1%
29690 1
< 0.1%
29098 1
< 0.1%
28944 1
< 0.1%
28760 1
< 0.1%
28682 1
< 0.1%
28575 1
< 0.1%
28561 1
< 0.1%

(직장-남자)직장가입자수
Real number (ℝ)

SKEWED  ZEROS 

Distinct4665
Distinct (%)49.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7444.0334
Minimum0
Maximum11337584
Zeros1467
Zeros (%)15.7%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:25.728736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median1179
Q37315.75
95-th percentile13538.5
Maximum11337584
Range11337584
Interquartile range (IQR)7310.75

Descriptive statistics

Standard deviation201276.59
Coefficient of variation (CV)27.038647
Kurtosis3110.2854
Mean7444.0334
Median Absolute Deviation (MAD)1179
Skewness55.764382
Sum69601712
Variance4.0512265 × 1010
MonotonicityNot monotonic
2024-04-17T23:18:25.845731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1467
 
15.7%
1 497
 
5.3%
2 171
 
1.8%
4 101
 
1.1%
3 78
 
0.8%
5 67
 
0.7%
8 52
 
0.6%
6 52
 
0.6%
7 38
 
0.4%
10 34
 
0.4%
Other values (4655) 6793
72.7%
ValueCountFrequency (%)
0 1467
15.7%
1 497
 
5.3%
2 171
 
1.8%
3 78
 
0.8%
4 101
 
1.1%
5 67
 
0.7%
6 52
 
0.6%
7 38
 
0.4%
8 52
 
0.6%
9 23
 
0.2%
ValueCountFrequency (%)
11337584 1
< 0.1%
11224986 1
< 0.1%
11152047 1
< 0.1%
21816 1
< 0.1%
21455 1
< 0.1%
21209 1
< 0.1%
21208 1
< 0.1%
21207 1
< 0.1%
21198 1
< 0.1%
21194 1
< 0.1%

(직장-여자)직장가입자수
Real number (ℝ)

SKEWED  ZEROS 

Distinct4505
Distinct (%)48.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6168.6786
Minimum0
Maximum8286678
Zeros1924
Zeros (%)20.6%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:25.954249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median962.5
Q36257
95-th percentile12583.55
Maximum8286678
Range8286678
Interquartile range (IQR)6255

Descriptive statistics

Standard deviation146280.08
Coefficient of variation (CV)23.713357
Kurtosis3108.428
Mean6168.6786
Median Absolute Deviation (MAD)962.5
Skewness55.73322
Sum57677145
Variance2.1397862 × 1010
MonotonicityNot monotonic
2024-04-17T23:18:26.323509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1924
 
20.6%
1 311
 
3.3%
2 189
 
2.0%
4 81
 
0.9%
3 63
 
0.7%
8 55
 
0.6%
9 55
 
0.6%
6 52
 
0.6%
7 51
 
0.5%
5 45
 
0.5%
Other values (4495) 6524
69.8%
ValueCountFrequency (%)
0 1924
20.6%
1 311
 
3.3%
2 189
 
2.0%
3 63
 
0.7%
4 81
 
0.9%
5 45
 
0.5%
6 52
 
0.6%
7 51
 
0.5%
8 55
 
0.6%
9 55
 
0.6%
ValueCountFrequency (%)
8286678 1
< 0.1%
8138815 1
< 0.1%
8072895 1
< 0.1%
34262 1
< 0.1%
33542 1
< 0.1%
32994 1
< 0.1%
32313 1
< 0.1%
31315 1
< 0.1%
30229 1
< 0.1%
29141 1
< 0.1%

(직장-남자)피부양자수
Real number (ℝ)

SKEWED  ZEROS 

Distinct4527
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4942.8582
Minimum0
Maximum7514955
Zeros99
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:26.423367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20
Q1652
median1403.5
Q33380.75
95-th percentile9063.7
Maximum7514955
Range7514955
Interquartile range (IQR)2728.75

Descriptive statistics

Standard deviation133167.35
Coefficient of variation (CV)26.941367
Kurtosis3112.6207
Mean4942.8582
Median Absolute Deviation (MAD)1080
Skewness55.78347
Sum46215724
Variance1.7733544 × 1010
MonotonicityNot monotonic
2024-04-17T23:18:26.544341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 99
 
1.1%
5 58
 
0.6%
6 55
 
0.6%
4 43
 
0.5%
3 43
 
0.5%
7 41
 
0.4%
8 40
 
0.4%
28 22
 
0.2%
2 20
 
0.2%
31 19
 
0.2%
Other values (4517) 8910
95.3%
ValueCountFrequency (%)
0 99
1.1%
1 10
 
0.1%
2 20
 
0.2%
3 43
0.5%
4 43
0.5%
5 58
0.6%
6 55
0.6%
7 41
0.4%
8 40
0.4%
9 8
 
0.1%
ValueCountFrequency (%)
7514955 1
< 0.1%
7502152 1
< 0.1%
7288220 1
< 0.1%
27578 1
< 0.1%
22630 1
< 0.1%
21878 1
< 0.1%
21570 1
< 0.1%
21021 1
< 0.1%
20567 1
< 0.1%
20132 1
< 0.1%

(직장-여자)피부양자수
Real number (ℝ)

SKEWED  ZEROS 

Distinct5229
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6728.7535
Minimum0
Maximum10507865
Zeros97
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size82.3 KiB
2024-04-17T23:18:26.661810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile62.45
Q11404.25
median3038
Q34615.5
95-th percentile8258.1
Maximum10507865
Range10507865
Interquartile range (IQR)3211.25

Descriptive statistics

Standard deviation186765.23
Coefficient of variation (CV)27.75629
Kurtosis3113.169
Mean6728.7535
Median Absolute Deviation (MAD)1606
Skewness55.799052
Sum62913845
Variance3.4881252 × 1010
MonotonicityNot monotonic
2024-04-17T23:18:26.782338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 97
 
1.0%
24 25
 
0.3%
19 25
 
0.3%
25 22
 
0.2%
26 21
 
0.2%
18 21
 
0.2%
17 16
 
0.2%
14 16
 
0.2%
22 15
 
0.2%
12 15
 
0.2%
Other values (5219) 9077
97.1%
ValueCountFrequency (%)
0 97
1.0%
7 2
 
< 0.1%
8 6
 
0.1%
9 11
 
0.1%
10 9
 
0.1%
11 12
 
0.1%
12 15
 
0.2%
13 13
 
0.1%
14 16
 
0.2%
15 10
 
0.1%
ValueCountFrequency (%)
10507865 1
< 0.1%
10495111 1
< 0.1%
10285328 1
< 0.1%
24039 1
< 0.1%
23445 1
< 0.1%
23119 1
< 0.1%
22788 1
< 0.1%
22599 1
< 0.1%
22426 1
< 0.1%
22286 1
< 0.1%

(직장-남자)평균피부양자수
Text

Distinct2220
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size73.2 KiB
2024-04-17T23:18:27.111979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length3.5119786
Min length1

Characters and Unicode

Total characters32837
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1471 ?
Unique (%)15.7%

Sample

1st row
2nd row
3rd row1700
4th row940.5
5th row21.85
ValueCountFrequency (%)
0.07 404
 
5.1%
0.06 330
 
4.2%
0.08 272
 
3.5%
0.09 206
 
2.6%
0.05 173
 
2.2%
0.1 148
 
1.9%
0.11 114
 
1.4%
0.14 110
 
1.4%
0.13 105
 
1.3%
0.12 94
 
1.2%
Other values (2209) 5927
75.2%
2024-04-17T23:18:27.569965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7157
21.8%
0 5920
18.0%
1 3208
9.8%
2 2335
 
7.1%
3 2231
 
6.8%
5 2058
 
6.3%
4 2021
 
6.2%
6 1785
 
5.4%
7 1748
 
5.3%
8 1520
 
4.6%
Other values (2) 2854
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24213
73.7%
Other Punctuation 7157
 
21.8%
Space Separator 1467
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5920
24.4%
1 3208
13.2%
2 2335
 
9.6%
3 2231
 
9.2%
5 2058
 
8.5%
4 2021
 
8.3%
6 1785
 
7.4%
7 1748
 
7.2%
8 1520
 
6.3%
9 1387
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 7157
100.0%
Space Separator
ValueCountFrequency (%)
1467
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32837
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7157
21.8%
0 5920
18.0%
1 3208
9.8%
2 2335
 
7.1%
3 2231
 
6.8%
5 2058
 
6.3%
4 2021
 
6.2%
6 1785
 
5.4%
7 1748
 
5.3%
8 1520
 
4.6%
Other values (2) 2854
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32837
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7157
21.8%
0 5920
18.0%
1 3208
9.8%
2 2335
 
7.1%
3 2231
 
6.8%
5 2058
 
6.3%
4 2021
 
6.2%
6 1785
 
5.4%
7 1748
 
5.3%
8 1520
 
4.6%
Other values (2) 2854
 
8.7%

(직장-여자)평균피부양자수
Text

Distinct2578
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Memory size73.2 KiB
2024-04-17T23:18:27.927794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length3.484385
Min length1

Characters and Unicode

Total characters32579
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1926 ?
Unique (%)20.6%

Sample

1st row
2nd row
3rd row
4th row
5th row20.41
ValueCountFrequency (%)
0.44 105
 
1.4%
0.47 94
 
1.3%
0.4 92
 
1.2%
0.24 91
 
1.2%
0.36 89
 
1.2%
0.37 89
 
1.2%
0.22 88
 
1.2%
0.39 82
 
1.1%
0.42 82
 
1.1%
0.46 80
 
1.1%
Other values (2567) 6534
88.0%
2024-04-17T23:18:28.383850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 6892
21.2%
0 4161
12.8%
1 3572
11.0%
2 2837
8.7%
3 2476
 
7.6%
4 2457
 
7.5%
5 1930
 
5.9%
1924
 
5.9%
6 1630
 
5.0%
8 1596
 
4.9%
Other values (2) 3104
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23763
72.9%
Other Punctuation 6892
 
21.2%
Space Separator 1924
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4161
17.5%
1 3572
15.0%
2 2837
11.9%
3 2476
10.4%
4 2457
10.3%
5 1930
8.1%
6 1630
 
6.9%
8 1596
 
6.7%
7 1583
 
6.7%
9 1521
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 6892
100.0%
Space Separator
ValueCountFrequency (%)
1924
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32579
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 6892
21.2%
0 4161
12.8%
1 3572
11.0%
2 2837
8.7%
3 2476
 
7.6%
4 2457
 
7.5%
5 1930
 
5.9%
1924
 
5.9%
6 1630
 
5.0%
8 1596
 
4.9%
Other values (2) 3104
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32579
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 6892
21.2%
0 4161
12.8%
1 3572
11.0%
2 2837
8.7%
3 2476
 
7.6%
4 2457
 
7.5%
5 1930
 
5.9%
1924
 
5.9%
6 1630
 
5.0%
8 1596
 
4.9%
Other values (2) 3104
9.5%

Sample

연월시도시군구연령(지역-남자)적용인구수(지역-여자)적용인구수(지역-남자)세대주수(지역-여자)세대주수(지역-남자)세대원수(지역-여자)세대원수(지역-남자)세대수(지역-여자)세대수(지역-남자)평균부양자수(지역-여자)평균부양자수(직장-남자)적용인구수(직장-여자)적용인구수(직장-남자)직장가입자수(직장-여자)직장가입자수(직장-남자)피부양자수(직장-여자)피부양자수(직장-남자)평균피부양자수(직장-여자)평균피부양자수
02022년1월서울특별시종로구0세47442145432122.543.020318600203186
12022년1월서울특별시종로구1-4세231225672252186737.531.1493394000933940
22022년1월서울특별시종로구5-9세4904191413476406141334.031.231701167810170016781700
32022년1월서울특별시종로구10-14세5705722835542537283519.3615.34188319192018811919940.5
42022년1월서울특별시종로구15-19세72372488148635576881487.223.891988201387941901191921.8520.41
52022년1월서울특별시종로구20-24세17062448736157197087774715941.320.56334241427371434260527083.531.89
62022년1월서울특별시종로구25-29세16421824827106781575788311200.990.715161537532713938189014370.580.36
72022년1월서울특별시종로구30-34세161414888787157367739908120.841.0840464147348334235637240.160.21
82022년1월서울특별시종로구35-39세1427148983565459283510237640.711.2835033569322727762767930.090.29
92022년1월서울특별시종로구40-44세1581168497672860595611608260.621.3134753697327427622019350.060.34
연월시도시군구연령(지역-남자)적용인구수(지역-여자)적용인구수(지역-남자)세대주수(지역-여자)세대주수(지역-남자)세대원수(지역-여자)세대원수(지역-남자)세대수(지역-여자)세대수(지역-남자)평균부양자수(지역-여자)평균부양자수(직장-남자)적용인구수(직장-여자)적용인구수(직장-남자)직장가입자수(직장-여자)직장가입자수(직장-남자)피부양자수(직장-여자)피부양자수(직장-남자)평균피부양자수(직장-여자)평균피부양자수
93402023년5월서울특별시강동구55-59세51715425425623639153062546229520.211.3107781174194117641136741000.150.54
93412023년5월서울특별시강동구60-64세62366993528528899514104692535860.181.42111021263686006475250261610.290.95
93422023년5월서울특별시강동구65-69세52446105448024777643628587229780.171.4686881006560413700264763650.441.72
93432023년5월서울특별시강동구70-74세36073930314615894612341399819130.151.475801641430361443276549710.913.44
93442023년5월서울특별시강동구75-79세24462499213210933141406258413540.151.29387943261263398261639282.079.87
93452023년5월서울특별시강동구80-84세13991580118277721780314339340.181.032227286533883188927825.5933.52
93462023년5월서울특별시강동구85-89세5118254093761024494884640.251.1977015745315717155913.53103.93
93472023년5월서울특별시강동구90-94세12636190147362141151760.41.461996877319268427.43228
93482023년5월서울특별시강동구95-99세2095143466116430.431.79371570037157
93492023년5월서울특별시강동구100세이상42244018440.04.5928108288