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

Description5단상병별 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/15072876/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
입내원일수 is highly skewed (γ1 = 69.9307136)Skewed
요양급여비용총액 is highly skewed (γ1 = 51.77926953)Skewed
보험자부담금 is highly skewed (γ1 = 46.49536151)Skewed

Reproduction

Analysis started2023-12-12 13:41:21.671647
Analysis finished2023-12-12 13:41:25.541498
Duration3.87 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

2023-12-12T22:41:25.597476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:41:25.713888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 10000
100.0%

주상병코드
Text

Distinct3303
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T22:41:26.072274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters50000
Distinct characters19
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

Unique730 ?
Unique (%)7.3%

Sample

1st rowC108
2nd rowF061
3rd rowC548
4th rowF810
5th rowG547
ValueCountFrequency (%)
h430 10
 
0.1%
f431 10
 
0.1%
h600 10
 
0.1%
h0241 10
 
0.1%
e876 10
 
0.1%
c444 10
 
0.1%
c716 10
 
0.1%
d127 9
 
0.1%
d383 9
 
0.1%
h184 9
 
0.1%
Other values (3293) 9903
99.0%
2023-12-12T22:41:26.522436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8328
16.7%
1 5070
10.1%
0 5051
10.1%
2 3220
 
6.4%
3 3087
 
6.2%
4 3040
 
6.1%
8 2912
 
5.8%
9 2649
 
5.3%
5 2525
 
5.1%
6 2361
 
4.7%
Other values (9) 11757
23.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31672
63.3%
Uppercase Letter 10000
 
20.0%
Space Separator 8328
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5070
16.0%
0 5051
15.9%
2 3220
10.2%
3 3087
9.7%
4 3040
9.6%
8 2912
9.2%
9 2649
8.4%
5 2525
8.0%
6 2361
7.5%
7 1757
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
H 1897
19.0%
E 1435
14.3%
D 1429
14.3%
C 1384
13.8%
G 1216
12.2%
F 1094
10.9%
A 817
8.2%
B 728
 
7.3%
Space Separator
ValueCountFrequency (%)
8328
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40000
80.0%
Latin 10000
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8328
20.8%
1 5070
12.7%
0 5051
12.6%
2 3220
 
8.1%
3 3087
 
7.7%
4 3040
 
7.6%
8 2912
 
7.3%
9 2649
 
6.6%
5 2525
 
6.3%
6 2361
 
5.9%
Latin
ValueCountFrequency (%)
H 1897
19.0%
E 1435
14.3%
D 1429
14.3%
C 1384
13.8%
G 1216
12.2%
F 1094
10.9%
A 817
8.2%
B 728
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8328
16.7%
1 5070
10.1%
0 5051
10.1%
2 3220
 
6.4%
3 3087
 
6.2%
4 3040
 
6.1%
8 2912
 
5.8%
9 2649
 
5.3%
5 2525
 
5.1%
6 2361
 
4.7%
Other values (9) 11757
23.5%

성별
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
여
5022 
남
4978 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여 5022
50.2%
남 4978
49.8%

Length

2023-12-12T22:41:26.640850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:41:26.724738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여 5022
50.2%
남 4978
49.8%

연령군
Categorical

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
13_60~64세
 
662
14_65~69세
 
640
12_55~59세
 
634
10_45~49세
 
615
16_75~79세
 
611
Other values (13)
6838 

Length

Max length9
Median length9
Mean length8.86
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row18_85세 이상
2nd row15_70~74세
3rd row15_70~74세
4th row05_20~24세
5th row13_60~64세

Common Values

ValueCountFrequency (%)
13_60~64세 662
 
6.6%
14_65~69세 640
 
6.4%
12_55~59세 634
 
6.3%
10_45~49세 615
 
6.2%
16_75~79세 611
 
6.1%
11_50~54세 606
 
6.1%
06_25~29세 600
 
6.0%
09_40~44세 597
 
6.0%
15_70~74세 597
 
6.0%
17_80~84세 593
 
5.9%
Other values (8) 3845
38.5%

Length

2023-12-12T22:41:26.822383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
13_60~64세 662
 
6.3%
14_65~69세 640
 
6.1%
12_55~59세 634
 
6.0%
10_45~49세 615
 
5.8%
16_75~79세 611
 
5.8%
11_50~54세 606
 
5.7%
06_25~29세 600
 
5.7%
09_40~44세 597
 
5.7%
15_70~74세 597
 
5.7%
17_80~84세 593
 
5.6%
Other values (9) 4389
41.6%

환자수
Real number (ℝ)

HIGH CORRELATION 

Distinct1507
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean684.6554
Minimum1
Maximum152812
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:41:26.937881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median17
Q3119.25
95-th percentile2344.05
Maximum152812
Range152811
Interquartile range (IQR)116.25

Descriptive statistics

Standard deviation4185.2533
Coefficient of variation (CV)6.112934
Kurtosis372.75056
Mean684.6554
Median Absolute Deviation (MAD)16
Skewness16.094784
Sum6846554
Variance17516345
MonotonicityNot monotonic
2023-12-12T22:41:27.055167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1354
 
13.5%
2 746
 
7.5%
3 549
 
5.5%
4 419
 
4.2%
5 265
 
2.6%
6 254
 
2.5%
7 227
 
2.3%
8 201
 
2.0%
9 168
 
1.7%
10 153
 
1.5%
Other values (1497) 5664
56.6%
ValueCountFrequency (%)
1 1354
13.5%
2 746
7.5%
3 549
5.5%
4 419
 
4.2%
5 265
 
2.6%
6 254
 
2.5%
7 227
 
2.3%
8 201
 
2.0%
9 168
 
1.7%
10 153
 
1.5%
ValueCountFrequency (%)
152812 1
< 0.1%
112047 1
< 0.1%
95878 1
< 0.1%
92539 1
< 0.1%
88405 1
< 0.1%
81751 1
< 0.1%
81402 1
< 0.1%
68157 1
< 0.1%
66475 1
< 0.1%
66302 1
< 0.1%

명세서건수
Real number (ℝ)

HIGH CORRELATION 

Distinct2209
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1884.9588
Minimum1
Maximum454086
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:41:27.181581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q18
median53
Q3355
95-th percentile6623
Maximum454086
Range454085
Interquartile range (IQR)347

Descriptive statistics

Standard deviation11665.888
Coefficient of variation (CV)6.1889351
Kurtosis392.11683
Mean1884.9588
Median Absolute Deviation (MAD)51
Skewness16.326581
Sum18849588
Variance1.3609293 × 108
MonotonicityNot monotonic
2023-12-12T22:41:27.515661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 738
 
7.4%
2 464
 
4.6%
3 306
 
3.1%
4 297
 
3.0%
5 227
 
2.3%
8 183
 
1.8%
6 181
 
1.8%
7 174
 
1.7%
9 138
 
1.4%
10 125
 
1.2%
Other values (2199) 7167
71.7%
ValueCountFrequency (%)
1 738
7.4%
2 464
4.6%
3 306
3.1%
4 297
3.0%
5 227
 
2.3%
6 181
 
1.8%
7 174
 
1.7%
8 183
 
1.8%
9 138
 
1.4%
10 125
 
1.2%
ValueCountFrequency (%)
454086 1
< 0.1%
282156 1
< 0.1%
249011 1
< 0.1%
238449 1
< 0.1%
230875 1
< 0.1%
214721 1
< 0.1%
201520 1
< 0.1%
194181 1
< 0.1%
182910 1
< 0.1%
179128 1
< 0.1%

입내원일수
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct2401
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2593.951
Minimum0
Maximum2983759
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:41:27.621783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q110
median70
Q3491
95-th percentile7792.8
Maximum2983759
Range2983759
Interquartile range (IQR)481

Descriptive statistics

Standard deviation34466.033
Coefficient of variation (CV)13.287079
Kurtosis5769.4124
Mean2593.951
Median Absolute Deviation (MAD)68
Skewness69.930714
Sum25939510
Variance1.1879074 × 109
MonotonicityNot monotonic
2023-12-12T22:41:27.738457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 686
 
6.9%
2 402
 
4.0%
3 261
 
2.6%
4 260
 
2.6%
5 204
 
2.0%
8 164
 
1.6%
6 163
 
1.6%
7 159
 
1.6%
9 136
 
1.4%
10 116
 
1.2%
Other values (2391) 7449
74.5%
ValueCountFrequency (%)
0 5
 
0.1%
1 686
6.9%
2 402
4.0%
3 261
 
2.6%
4 260
 
2.6%
5 204
 
2.0%
6 163
 
1.6%
7 159
 
1.6%
8 164
 
1.6%
9 136
 
1.4%
ValueCountFrequency (%)
2983759 1
< 0.1%
1243579 1
< 0.1%
279965 1
< 0.1%
275265 1
< 0.1%
248867 1
< 0.1%
238426 1
< 0.1%
230599 1
< 0.1%
226153 1
< 0.1%
222176 1
< 0.1%
201934 1
< 0.1%

요양급여비용총액
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct9668
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8088868 × 108
Minimum0
Maximum2.3582 × 1011
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:41:27.867374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile33940
Q1783325
median8417420
Q362386415
95-th percentile8.0167348 × 108
Maximum2.3582 × 1011
Range2.3582 × 1011
Interquartile range (IQR)61603090

Descriptive statistics

Standard deviation3.0899179 × 109
Coefficient of variation (CV)11.000507
Kurtosis3561.4546
Mean2.8088868 × 108
Median Absolute Deviation (MAD)8342370
Skewness51.77927
Sum2.8088868 × 1012
Variance9.5475925 × 1018
MonotonicityNot monotonic
2023-12-12T22:41:27.986469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16970 103
 
1.0%
12130 39
 
0.4%
21180 13
 
0.1%
29100 12
 
0.1%
14780 10
 
0.1%
33940 7
 
0.1%
24260 6
 
0.1%
20110 6
 
0.1%
11870 6
 
0.1%
17950 6
 
0.1%
Other values (9658) 9792
97.9%
ValueCountFrequency (%)
0 2
< 0.1%
2240 1
 
< 0.1%
3850 1
 
< 0.1%
4930 1
 
< 0.1%
5100 2
< 0.1%
5610 4
< 0.1%
5930 1
 
< 0.1%
6070 2
< 0.1%
6630 1
 
< 0.1%
8160 1
 
< 0.1%
ValueCountFrequency (%)
235820000000 1
< 0.1%
100629000000 1
< 0.1%
71987700400 1
< 0.1%
69607967620 1
< 0.1%
56942114570 1
< 0.1%
37271687190 1
< 0.1%
34664264260 1
< 0.1%
31136766910 1
< 0.1%
29182070240 1
< 0.1%
26560564630 1
< 0.1%

보험자부담금
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct9660
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.248684 × 108
Minimum0
Maximum1.76072 × 1011
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T22:41:28.099249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile22366
Q1513152.5
median6058835
Q346265408
95-th percentile6.0557597 × 108
Maximum1.76072 × 1011
Range1.76072 × 1011
Interquartile range (IQR)45752255

Descriptive statistics

Standard deviation2.4391541 × 109
Coefficient of variation (CV)10.847029
Kurtosis2925.5917
Mean2.248684 × 108
Median Absolute Deviation (MAD)6013165
Skewness46.495362
Sum2.248684 × 1012
Variance5.9494728 × 1018
MonotonicityNot monotonic
2023-12-12T22:41:28.249353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11970 75
 
0.8%
8530 21
 
0.2%
15370 21
 
0.2%
10630 15
 
0.1%
20500 10
 
0.1%
14880 8
 
0.1%
10380 7
 
0.1%
17060 6
 
0.1%
16170 6
 
0.1%
14250 6
 
0.1%
Other values (9650) 9825
98.2%
ValueCountFrequency (%)
0 2
 
< 0.1%
50 1
 
< 0.1%
1340 1
 
< 0.1%
2710 1
 
< 0.1%
2910 2
 
< 0.1%
2920 1
 
< 0.1%
3060 1
 
< 0.1%
3070 3
< 0.1%
3210 5
0.1%
3610 1
 
< 0.1%
ValueCountFrequency (%)
176072000000 1
< 0.1%
75534895280 1
< 0.1%
66960543610 1
< 0.1%
63875885710 1
< 0.1%
52070254350 1
< 0.1%
34308133310 1
< 0.1%
28837767100 1
< 0.1%
24504634880 1
< 0.1%
23052710960 1
< 0.1%
21779005100 1
< 0.1%

Interactions

2023-12-12T22:41:24.779145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:22.590276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:23.173104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:23.699558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:24.245104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:24.899924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:22.710470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:23.270037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:23.808505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:24.366665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:24.986652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:22.809000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:23.379136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:23.938242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:24.464802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:25.089566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:22.949897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:23.480452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:24.056623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:24.557390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:25.184847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:23.061286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:23.596005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:24.143719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:41:24.662888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:41:28.339088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별연령군환자수명세서건수입내원일수요양급여비용총액보험자부담금
성별1.0000.0440.0220.0280.0000.0150.000
연령군0.0441.0000.0540.0290.0000.0000.000
환자수0.0220.0541.0000.7770.7820.6190.601
명세서건수0.0280.0290.7771.0001.0000.8720.855
입내원일수0.0000.0000.7821.0001.0001.0001.000
요양급여비용총액0.0150.0000.6190.8721.0001.0000.994
보험자부담금0.0000.0000.6010.8551.0000.9941.000
2023-12-12T22:41:28.432635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별연령군
성별1.0000.035
연령군0.0351.000
2023-12-12T22:41:28.514544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
환자수명세서건수입내원일수요양급여비용총액보험자부담금성별연령군
환자수1.0000.9580.9290.8270.8100.0220.018
명세서건수0.9581.0000.9790.8950.8830.0210.012
입내원일수0.9290.9791.0000.9430.9350.0000.000
요양급여비용총액0.8270.8950.9431.0000.9980.0110.000
보험자부담금0.8100.8830.9350.9981.0000.0000.000
성별0.0220.0210.0000.0110.0001.0000.035
연령군0.0180.0120.0000.0000.0000.0351.000

Missing values

2023-12-12T22:41:25.316170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:41:25.481923image/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
156622022C108남18_85세 이상4112278745706963100
553282022F061여15_70~74세204545754710647810
217202022C548여15_70~74세401301432453633021931350
638172022F810남05_20~24세618181254840995440
713532022G547남13_60~64세2216818795011405749690
751612022G932남01_0~4세6111319517901656290
883792022H472여11_50~54세2504144144696466028331960
418842022E040남08_35~39세59121121108971707243470
816332022H170여16_75~79세18494918350901265190
25772022A1651남12_55~59세16210341885529237080512615280
진료년도주상병코드성별연령군환자수명세서건수입내원일수요양급여비용총액보험자부담금
738232022G803남05_20~24세294804801919827011762070
373122022D484여16_75~79세1465851458572012942930
34612022A198남14_65~69세114361086366010666490
498842022E344남10_45~49세1223335023450
452462022E118남02_5~9세15445248669803336770
81812022B021남12_55~59세15371163519167024458350
372052022D481여03_10~14세251221224481241040636210
328212022D235남06_25~29세161940854112292189780201041520
213792022C5069여10_45~49세1011311282730007406800
255522022C829여04_15~19세111152100144500