Overview

Dataset statistics

Number of variables9
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory839.8 KiB
Average record size in memory86.0 B

Variable types

Categorical3
Text1
Numeric5

Dataset

Description4단상병별 성별/연령별 건강보험 진료비 통계/진료일자 기준(심사분은 각 진료년+4개월) (예) 진료년월: 2022.1월~12월, 심사년월: 2022.1월~2023.4월 / 보험자: 건강보험 / 요양기관 종별: 약국 제외 / 한방상병 제외
URLhttps://www.data.go.kr/data/15072889/fileData.do

Alerts

진료년도 has constant value ""Constant
환자수 is highly overall correlated with 명세서건수 and 3 other fieldsHigh correlation
명세서건수 is highly overall correlated with 환자수 and 3 other fieldsHigh correlation
입내원일수 is highly overall correlated with 환자수 and 3 other fieldsHigh correlation
요양급여비용총액 is highly overall correlated with 환자수 and 3 other fieldsHigh correlation
보험자부담금 is highly overall correlated with 환자수 and 3 other fieldsHigh correlation
환자수 is highly skewed (γ1 = 25.78634609)Skewed
명세서건수 is highly skewed (γ1 = 24.23928448)Skewed
입내원일수 is highly skewed (γ1 = 22.11145792)Skewed

Reproduction

Analysis started2023-12-12 11:03:30.409080
Analysis finished2023-12-12 11:03:36.564825
Duration6.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

진료년도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 10000
100.0%

Length

2023-12-12T20:03:36.667677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:03:36.824341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 10000
100.0%

주상병코드
Text

Distinct3237
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T20:03:37.418558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters40000
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique688 ?
Unique (%)6.9%

Sample

1st rowC839
2nd rowA840
3rd rowI428
4th rowE611
5th rowI959
ValueCountFrequency (%)
c381 10
 
0.1%
e351 10
 
0.1%
i675 9
 
0.1%
g819 9
 
0.1%
f603 9
 
0.1%
b358 9
 
0.1%
e55 9
 
0.1%
g960 9
 
0.1%
b972 9
 
0.1%
d121 9
 
0.1%
Other values (3227) 9908
99.1%
2023-12-12T20:03:38.284141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4166
 
10.4%
1 3985
 
10.0%
2 3047
 
7.6%
3 2962
 
7.4%
4 2877
 
7.2%
8 2829
 
7.1%
9 2686
 
6.7%
5 2417
 
6.0%
6 2255
 
5.6%
7 2005
 
5.0%
Other values (11) 10771
26.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 29229
73.1%
Uppercase Letter 10000
 
25.0%
Space Separator 771
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4166
14.3%
1 3985
13.6%
2 3047
10.4%
3 2962
10.1%
4 2877
9.8%
8 2829
9.7%
9 2686
9.2%
5 2417
8.3%
6 2255
7.7%
7 2005
6.9%
Uppercase Letter
ValueCountFrequency (%)
H 1390
13.9%
D 1276
12.8%
I 1224
12.2%
C 1201
12.0%
G 1124
11.2%
E 1036
10.4%
F 983
9.8%
B 739
7.4%
A 640
6.4%
J 387
 
3.9%
Space Separator
ValueCountFrequency (%)
771
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30000
75.0%
Latin 10000
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4166
13.9%
1 3985
13.3%
2 3047
10.2%
3 2962
9.9%
4 2877
9.6%
8 2829
9.4%
9 2686
9.0%
5 2417
8.1%
6 2255
7.5%
7 2005
6.7%
Latin
ValueCountFrequency (%)
H 1390
13.9%
D 1276
12.8%
I 1224
12.2%
C 1201
12.0%
G 1124
11.2%
E 1036
10.4%
F 983
9.8%
B 739
7.4%
A 640
6.4%
J 387
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4166
 
10.4%
1 3985
 
10.0%
2 3047
 
7.6%
3 2962
 
7.4%
4 2877
 
7.2%
8 2829
 
7.1%
9 2686
 
6.7%
5 2417
 
6.0%
6 2255
 
5.6%
7 2005
 
5.0%
Other values (11) 10771
26.9%

성별
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
여
5076 
남
4924 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남
2nd row여
3rd row남
4th row여
5th row여

Common Values

ValueCountFrequency (%)
여 5076
50.8%
남 4924
49.2%

Length

2023-12-12T20:03:38.533296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:03:38.720739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여 5076
50.8%
남 4924
49.2%

연령군
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
14_65~69세
 
683
10_45~49세
 
641
13_60~64세
 
620
12_55~59세
 
614
15_70~74세
 
604
Other values (13)
6838 

Length

Max length9
Median length9
Mean length8.8446
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11_50~54세
2nd row03_10~14세
3rd row07_30~34세
4th row02_5~9세
5th row05_20~24세

Common Values

ValueCountFrequency (%)
14_65~69세 683
 
6.8%
10_45~49세 641
 
6.4%
13_60~64세 620
 
6.2%
12_55~59세 614
 
6.1%
15_70~74세 604
 
6.0%
11_50~54세 600
 
6.0%
16_75~79세 591
 
5.9%
08_35~39세 589
 
5.9%
09_40~44세 585
 
5.9%
07_30~34세 568
 
5.7%
Other values (8) 3905
39.1%

Length

2023-12-12T20:03:38.935755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
14_65~69세 683
 
6.5%
10_45~49세 641
 
6.1%
13_60~64세 620
 
5.9%
12_55~59세 614
 
5.8%
15_70~74세 604
 
5.7%
11_50~54세 600
 
5.7%
16_75~79세 591
 
5.6%
08_35~39세 589
 
5.6%
09_40~44세 585
 
5.6%
07_30~34세 568
 
5.4%
Other values (9) 4436
42.1%

환자수
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1690
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1319.4446
Minimum1
Maximum565499
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:03:39.169360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median21
Q3147
95-th percentile3487
Maximum565499
Range565498
Interquartile range (IQR)143

Descriptive statistics

Standard deviation11837.302
Coefficient of variation (CV)8.9714278
Kurtosis926.43568
Mean1319.4446
Median Absolute Deviation (MAD)20
Skewness25.786346
Sum13194446
Variance1.4012172 × 108
MonotonicityNot monotonic
2023-12-12T20:03:39.559866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1265
 
12.7%
2 646
 
6.5%
3 445
 
4.5%
4 387
 
3.9%
5 292
 
2.9%
6 262
 
2.6%
7 204
 
2.0%
8 185
 
1.8%
9 163
 
1.6%
10 145
 
1.5%
Other values (1680) 6006
60.1%
ValueCountFrequency (%)
1 1265
12.7%
2 646
6.5%
3 445
 
4.5%
4 387
 
3.9%
5 292
 
2.9%
6 262
 
2.6%
7 204
 
2.0%
8 185
 
1.8%
9 163
 
1.6%
10 145
 
1.5%
ValueCountFrequency (%)
565499 1
< 0.1%
481873 1
< 0.1%
287444 1
< 0.1%
275812 1
< 0.1%
218629 1
< 0.1%
207215 1
< 0.1%
195381 1
< 0.1%
194158 1
< 0.1%
193696 1
< 0.1%
189513 1
< 0.1%

명세서건수
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2413
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3218.7717
Minimum1
Maximum1174673
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:03:39.865285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q19
median64
Q3436
95-th percentile8818.25
Maximum1174673
Range1174672
Interquartile range (IQR)427

Descriptive statistics

Standard deviation28021.536
Coefficient of variation (CV)8.7056611
Kurtosis756.54795
Mean3218.7717
Median Absolute Deviation (MAD)62
Skewness24.239284
Sum32187717
Variance7.8520645 × 108
MonotonicityNot monotonic
2023-12-12T20:03:40.175367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 744
 
7.4%
2 384
 
3.8%
3 305
 
3.0%
4 275
 
2.8%
6 189
 
1.9%
5 183
 
1.8%
9 155
 
1.6%
7 144
 
1.4%
8 138
 
1.4%
10 134
 
1.3%
Other values (2403) 7349
73.5%
ValueCountFrequency (%)
1 744
7.4%
2 384
3.8%
3 305
3.0%
4 275
 
2.8%
5 183
 
1.8%
6 189
 
1.9%
7 144
 
1.4%
8 138
 
1.4%
9 155
 
1.6%
10 134
 
1.3%
ValueCountFrequency (%)
1174673 1
< 0.1%
962478 1
< 0.1%
940298 1
< 0.1%
851216 1
< 0.1%
704446 1
< 0.1%
537488 1
< 0.1%
492652 1
< 0.1%
472688 1
< 0.1%
452730 1
< 0.1%
438638 1
< 0.1%

입내원일수
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2662
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3747.994
Minimum0
Maximum1178301
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:03:40.483827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q112
median89
Q3629
95-th percentile10467.1
Maximum1178301
Range1178301
Interquartile range (IQR)617

Descriptive statistics

Standard deviation29300.075
Coefficient of variation (CV)7.8175351
Kurtosis648.58638
Mean3747.994
Median Absolute Deviation (MAD)87
Skewness22.111458
Sum37479940
Variance8.5849438 × 108
MonotonicityNot monotonic
2023-12-12T20:03:41.304373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 680
 
6.8%
2 349
 
3.5%
3 265
 
2.6%
4 241
 
2.4%
6 173
 
1.7%
5 162
 
1.6%
9 146
 
1.5%
7 126
 
1.3%
8 122
 
1.2%
10 113
 
1.1%
Other values (2652) 7623
76.2%
ValueCountFrequency (%)
0 4
 
< 0.1%
1 680
6.8%
2 349
3.5%
3 265
 
2.6%
4 241
 
2.4%
5 162
 
1.6%
6 173
 
1.7%
7 126
 
1.3%
8 122
 
1.2%
9 146
 
1.5%
ValueCountFrequency (%)
1178301 1
< 0.1%
964958 1
< 0.1%
949866 1
< 0.1%
851681 1
< 0.1%
704690 1
< 0.1%
537864 1
< 0.1%
494998 1
< 0.1%
476301 1
< 0.1%
453889 1
< 0.1%
453217 1
< 0.1%

요양급여비용총액
Real number (ℝ)

HIGH CORRELATION 

Distinct9657
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2282774 × 108
Minimum0
Maximum4.6314297 × 1010
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:03:41.583473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile31881
Q1954160
median11231705
Q389705470
95-th percentile1.1215953 × 109
Maximum4.6314297 × 1010
Range4.6314297 × 1010
Interquartile range (IQR)88751310

Descriptive statistics

Standard deviation1.7465545 × 109
Coefficient of variation (CV)5.4101748
Kurtosis206.73806
Mean3.2282774 × 108
Median Absolute Deviation (MAD)11157600
Skewness12.546675
Sum3.2282774 × 1012
Variance3.0504525 × 1018
MonotonicityNot monotonic
2023-12-12T20:03:41.846258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16970 101
 
1.0%
12130 36
 
0.4%
21180 16
 
0.2%
29100 15
 
0.1%
14780 10
 
0.1%
33940 10
 
0.1%
17950 7
 
0.1%
16370 7
 
0.1%
11870 7
 
0.1%
38150 6
 
0.1%
Other values (9647) 9785
97.9%
ValueCountFrequency (%)
0 4
< 0.1%
1890 1
 
< 0.1%
3850 1
 
< 0.1%
4930 1
 
< 0.1%
5100 4
< 0.1%
5610 4
< 0.1%
6070 1
 
< 0.1%
6630 3
< 0.1%
6680 1
 
< 0.1%
6850 1
 
< 0.1%
ValueCountFrequency (%)
46314297380 1
< 0.1%
38257032150 1
< 0.1%
36607499730 1
< 0.1%
35239609590 1
< 0.1%
34403766400 1
< 0.1%
33061529130 1
< 0.1%
31541709020 1
< 0.1%
30751772670 1
< 0.1%
28782319150 1
< 0.1%
26706219620 1
< 0.1%

보험자부담금
Real number (ℝ)

HIGH CORRELATION 

Distinct9672
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5805507 × 108
Minimum0
Maximum4.3104938 × 1010
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T20:03:42.101928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20500
Q1615510
median8073945
Q366405162
95-th percentile8.5393812 × 108
Maximum4.3104938 × 1010
Range4.3104938 × 1010
Interquartile range (IQR)65789652

Descriptive statistics

Standard deviation1.4441052 × 109
Coefficient of variation (CV)5.5961125
Kurtosis238.61403
Mean2.5805507 × 108
Median Absolute Deviation (MAD)8028540
Skewness13.253134
Sum2.5805507 × 1012
Variance2.0854398 × 1018
MonotonicityNot monotonic
2023-12-12T20:03:42.354917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11970 79
 
0.8%
8530 22
 
0.2%
15370 17
 
0.2%
10630 14
 
0.1%
14880 13
 
0.1%
20500 12
 
0.1%
23940 8
 
0.1%
3210 7
 
0.1%
14250 7
 
0.1%
9870 7
 
0.1%
Other values (9662) 9814
98.1%
ValueCountFrequency (%)
0 4
< 0.1%
50 1
 
< 0.1%
390 1
 
< 0.1%
2860 4
< 0.1%
2900 1
 
< 0.1%
2920 3
< 0.1%
2960 1
 
< 0.1%
3050 1
 
< 0.1%
3070 4
< 0.1%
3210 7
0.1%
ValueCountFrequency (%)
43104938430 1
< 0.1%
35330963580 1
< 0.1%
28210573660 1
< 0.1%
28178127360 1
< 0.1%
27651933400 1
< 0.1%
27180665310 1
< 0.1%
26882127360 1
< 0.1%
26186042180 1
< 0.1%
24348112490 1
< 0.1%
22047489830 1
< 0.1%

Interactions

2023-12-12T20:03:35.356314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:32.027658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:32.792893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:33.626256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:34.524541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:35.519047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:32.169393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:32.968017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:33.804256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:34.668222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:35.709287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:32.325055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:33.123990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:33.980838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:34.843193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:35.873766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:32.485757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:33.311019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:34.193232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:35.024636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:36.020659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:32.651520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:33.471109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:34.367830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:03:35.187507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:03:42.521928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별연령군환자수명세서건수입내원일수요양급여비용총액보험자부담금
성별1.0000.0050.0000.0000.0000.0000.000
연령군0.0051.0000.0330.0190.0140.0570.076
환자수0.0000.0331.0000.9020.8910.5810.523
명세서건수0.0000.0190.9021.0000.9980.6580.753
입내원일수0.0000.0140.8910.9981.0000.7180.803
요양급여비용총액0.0000.0570.5810.6580.7181.0000.955
보험자부담금0.0000.0760.5230.7530.8030.9551.000
2023-12-12T20:03:42.689690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별연령군
성별1.0000.004
연령군0.0041.000
2023-12-12T20:03:42.848884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환자수명세서건수입내원일수요양급여비용총액보험자부담금성별연령군
환자수1.0000.9630.9330.8320.8150.0000.014
명세서건수0.9631.0000.9790.8960.8840.0000.006
입내원일수0.9330.9791.0000.9450.9370.0000.004
요양급여비용총액0.8320.8960.9451.0000.9980.0000.022
보험자부담금0.8150.8840.9370.9981.0000.0000.025
성별0.0000.0000.0000.0000.0001.0000.004
연령군0.0140.0060.0040.0220.0250.0041.000

Missing values

2023-12-12T20:03:36.220232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:03:36.456648image/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

진료년도주상병코드성별연령군환자수명세서건수입내원일수요양급여비용총액보험자부담금
225852022C839남11_50~54세5161623331602078460
58612022A840여03_10~14세1111697011970
840032022I428남07_30~34세2973781566091010286470
431552022E611여02_5~9세35626234951601662060
910972022I959여05_20~24세3664424532839266018900780
464332022E888여16_75~79세513150015109746215037795600
87792022B303남09_40~44세253434761130526230
906872022I881여05_20~24세30575795814417846092481270
592262022G402여15_70~74세44417242728276444070188318280
81732022B209남16_75~79세412121926581017339710
진료년도주상병코드성별연령군환자수명세서건수입내원일수요양급여비용총액보험자부담금
937752022J203남07_30~34세54686826158201854520
333552022D518남08_35~39세81414487390311990
600322022G442남18_85세 이상219250395278242546510165308040
187102022C52여10_45~49세23242347130459390118767480
663742022G990여07_30~34세6322053754735028134970
219212022C800남14_65~69세20415842396898097110830839600
690222022H164여08_35~39세61898933911102080810
102282022B441여06_25~29세366853370360770
332572022D510남07_30~34세272779165705911220
870492022I651여10_45~49세33751111957896012600220