Overview

Dataset statistics

Number of variables9
Number of observations33
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory82.0 B

Variable types

Categorical3
Numeric6

Dataset

Description광주보훈병원에서 개방하는 진료정보 데이터로, 광주보훈병원 만성질환 환자 연령별 현황에 대한 내용이 포함된 공공데이터입니다.
URLhttps://www.data.go.kr/data/15102118/fileData.do

Alerts

상병코드 is highly overall correlated with 상병명칭High correlation
상병명칭 is highly overall correlated with 상병코드High correlation
59세이하 is highly overall correlated with 60세-64세 and 4 other fieldsHigh correlation
60세-64세 is highly overall correlated with 59세이하 and 4 other fieldsHigh correlation
65세-69세 is highly overall correlated with 59세이하 and 4 other fieldsHigh correlation
70세-79세 is highly overall correlated with 59세이하 and 4 other fieldsHigh correlation
80세-89세 is highly overall correlated with 59세이하 and 4 other fieldsHigh correlation
90세이상 is highly overall correlated with 59세이하 and 4 other fieldsHigh correlation
70세-79세 has unique valuesUnique
59세이하 has 6 (18.2%) zerosZeros
60세-64세 has 4 (12.1%) zerosZeros
65세-69세 has 5 (15.2%) zerosZeros
80세-89세 has 4 (12.1%) zerosZeros
90세이상 has 4 (12.1%) zerosZeros

Reproduction

Analysis started2023-12-11 22:51:05.645247
Analysis finished2023-12-11 22:51:09.488093
Duration3.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct3
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
입원 실인원
11 
입원 연인원
11 
외래
11 

Length

Max length6
Median length6
Mean length4.6666667
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row입원 실인원
2nd row입원 실인원
3rd row입원 실인원
4th row입원 실인원
5th row입원 실인원

Common Values

ValueCountFrequency (%)
입원 실인원 11
33.3%
입원 연인원 11
33.3%
외래 11
33.3%

Length

2023-12-12T07:51:09.549269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:51:09.643169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입원 22
40.0%
실인원 11
20.0%
연인원 11
20.0%
외래 11
20.0%

상병코드
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size396.0 B
I10~I13, I15
3 
E10~E14
3 
F00~F99, G40~G41
3 
A15, A16, A19
3 
I05~I09, I20~I27, I30~I52
3 
Other values (6)
18 

Length

Max length25
Median length17
Mean length12.636364
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI10~I13, I15
2nd rowE10~E14
3rd rowF00~F99, G40~G41
4th rowA15, A16, A19
5th rowI05~I09, I20~I27, I30~I52

Common Values

ValueCountFrequency (%)
I10~I13, I15 3
9.1%
E10~E14 3
9.1%
F00~F99, G40~G41 3
9.1%
A15, A16, A19 3
9.1%
I05~I09, I20~I27, I30~I52 3
9.1%
I60~I69 3
9.1%
G00~G37, G43~G83 3
9.1%
C00~C97, D00~D09 3
9.1%
E00~E07 3
9.1%
B18, B19, K70~K77 3
9.1%

Length

2023-12-12T07:51:09.741386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
i10~i13 3
 
4.8%
i60~i69 3
 
4.8%
k70~k77 3
 
4.8%
b19 3
 
4.8%
b18 3
 
4.8%
e00~e07 3
 
4.8%
d00~d09 3
 
4.8%
c00~c97 3
 
4.8%
g43~g83 3
 
4.8%
g00~g37 3
 
4.8%
Other values (11) 33
52.4%

상병명칭
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size396.0 B
고혈압
3 
당뇨병
3 
정신 및 행동장애
3 
호흡기결핵
3 
심장질환
3 
Other values (6)
18 

Length

Max length9
Median length7
Mean length5.2727273
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row고혈압
2nd row당뇨병
3rd row정신 및 행동장애
4th row호흡기결핵
5th row심장질환

Common Values

ValueCountFrequency (%)
고혈압 3
9.1%
당뇨병 3
9.1%
정신 및 행동장애 3
9.1%
호흡기결핵 3
9.1%
심장질환 3
9.1%
대뇌혈관질환 3
9.1%
신경계질환 3
9.1%
악성신생물 3
9.1%
갑상선의 장애 3
9.1%
간의 질환 3
9.1%

Length

2023-12-12T07:51:10.111135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고혈압 3
 
6.7%
당뇨병 3
 
6.7%
정신 3
 
6.7%
및 3
 
6.7%
행동장애 3
 
6.7%
호흡기결핵 3
 
6.7%
심장질환 3
 
6.7%
대뇌혈관질환 3
 
6.7%
신경계질환 3
 
6.7%
악성신생물 3
 
6.7%
Other values (5) 15
33.3%

59세이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean496.42424
Minimum0
Maximum3109
Zeros6
Zeros (%)18.2%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T07:51:10.244148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median57
Q3740
95-th percentile1624.8
Maximum3109
Range3109
Interquartile range (IQR)736

Descriptive statistics

Standard deviation733.96168
Coefficient of variation (CV)1.4784969
Kurtosis3.6629371
Mean496.42424
Median Absolute Deviation (MAD)57
Skewness1.8094109
Sum16382
Variance538699.75
MonotonicityNot monotonic
2023-12-12T07:51:10.383815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 6
 
18.2%
3 2
 
6.1%
7 2
 
6.1%
1552 1
 
3.0%
640 1
 
3.0%
740 1
 
3.0%
407 1
 
3.0%
655 1
 
3.0%
1734 1
 
3.0%
1487 1
 
3.0%
Other values (16) 16
48.5%
ValueCountFrequency (%)
0 6
18.2%
3 2
 
6.1%
4 1
 
3.0%
5 1
 
3.0%
7 2
 
6.1%
10 1
 
3.0%
21 1
 
3.0%
25 1
 
3.0%
56 1
 
3.0%
57 1
 
3.0%
ValueCountFrequency (%)
3109 1
3.0%
1734 1
3.0%
1552 1
3.0%
1487 1
3.0%
1472 1
3.0%
1259 1
3.0%
1134 1
3.0%
954 1
3.0%
740 1
3.0%
732 1
3.0%

60세-64세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean302.81818
Minimum0
Maximum1269
Zeros4
Zeros (%)12.1%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T07:51:10.556409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median62
Q3486
95-th percentile1072.2
Maximum1269
Range1269
Interquartile range (IQR)481

Descriptive statistics

Standard deviation411.73789
Coefficient of variation (CV)1.3596868
Kurtosis-0.11051446
Mean302.81818
Median Absolute Deviation (MAD)62
Skewness1.1616303
Sum9993
Variance169528.09
MonotonicityNot monotonic
2023-12-12T07:51:10.709245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 4
 
12.1%
1 2
 
6.1%
14 2
 
6.1%
5 2
 
6.1%
1065 1
 
3.0%
72 1
 
3.0%
353 1
 
3.0%
201 1
 
3.0%
451 1
 
3.0%
1269 1
 
3.0%
Other values (17) 17
51.5%
ValueCountFrequency (%)
0 4
12.1%
1 2
6.1%
3 1
 
3.0%
5 2
6.1%
13 1
 
3.0%
14 2
6.1%
16 1
 
3.0%
18 1
 
3.0%
25 1
 
3.0%
34 1
 
3.0%
ValueCountFrequency (%)
1269 1
3.0%
1083 1
3.0%
1065 1
3.0%
1060 1
3.0%
1033 1
3.0%
825 1
3.0%
690 1
3.0%
638 1
3.0%
486 1
3.0%
451 1
3.0%

65세-69세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean397.0303
Minimum0
Maximum1906
Zeros5
Zeros (%)15.2%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T07:51:10.886536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median59
Q3574
95-th percentile1530.6
Maximum1906
Range1906
Interquartile range (IQR)570

Descriptive statistics

Standard deviation563.92666
Coefficient of variation (CV)1.4203618
Kurtosis0.81042446
Mean397.0303
Median Absolute Deviation (MAD)59
Skewness1.4081443
Sum13102
Variance318013.28
MonotonicityNot monotonic
2023-12-12T07:51:11.016261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 5
 
15.2%
1 2
 
6.1%
7 1
 
3.0%
239 1
 
3.0%
340 1
 
3.0%
266 1
 
3.0%
574 1
 
3.0%
1505 1
 
3.0%
812 1
 
3.0%
1503 1
 
3.0%
Other values (18) 18
54.5%
ValueCountFrequency (%)
0 5
15.2%
1 2
 
6.1%
2 1
 
3.0%
4 1
 
3.0%
7 1
 
3.0%
15 1
 
3.0%
18 1
 
3.0%
21 1
 
3.0%
22 1
 
3.0%
27 1
 
3.0%
ValueCountFrequency (%)
1906 1
3.0%
1569 1
3.0%
1505 1
3.0%
1503 1
3.0%
1199 1
3.0%
934 1
3.0%
858 1
3.0%
812 1
3.0%
574 1
3.0%
550 1
3.0%

70세-79세
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3368.1818
Minimum4
Maximum14894
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T07:51:11.176570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5.6
Q174
median604
Q37752
95-th percentile12269.8
Maximum14894
Range14890
Interquartile range (IQR)7678

Descriptive statistics

Standard deviation4655.9496
Coefficient of variation (CV)1.3823332
Kurtosis-0.085932567
Mean3368.1818
Median Absolute Deviation (MAD)585
Skewness1.1748051
Sum111150
Variance21677866
MonotonicityNot monotonic
2023-12-12T07:51:11.386786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
28 1
 
3.0%
71 1
 
3.0%
74 1
 
3.0%
291 1
 
3.0%
604 1
 
3.0%
11120 1
 
3.0%
12448 1
 
3.0%
9408 1
 
3.0%
14894 1
 
3.0%
4 1
 
3.0%
Other values (23) 23
69.7%
ValueCountFrequency (%)
4 1
3.0%
5 1
3.0%
6 1
3.0%
19 1
3.0%
23 1
3.0%
28 1
3.0%
30 1
3.0%
71 1
3.0%
74 1
3.0%
100 1
3.0%
ValueCountFrequency (%)
14894 1
3.0%
12448 1
3.0%
12151 1
3.0%
11120 1
3.0%
9408 1
3.0%
9358 1
3.0%
8364 1
3.0%
8115 1
3.0%
7752 1
3.0%
5407 1
3.0%

80세-89세
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean824
Minimum0
Maximum4883
Zeros4
Zeros (%)12.1%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T07:51:11.585334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114
median151
Q31340
95-th percentile3316.6
Maximum4883
Range4883
Interquartile range (IQR)1326

Descriptive statistics

Standard deviation1250.6992
Coefficient of variation (CV)1.5178388
Kurtosis3.8248005
Mean824
Median Absolute Deviation (MAD)151
Skewness1.9657299
Sum27192
Variance1564248.5
MonotonicityNot monotonic
2023-12-12T07:51:11.732987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 4
 
12.1%
7 1
 
3.0%
4426 1
 
3.0%
969 1
 
3.0%
181 1
 
3.0%
210 1
 
3.0%
1773 1
 
3.0%
1340 1
 
3.0%
1927 1
 
3.0%
2577 1
 
3.0%
Other values (20) 20
60.6%
ValueCountFrequency (%)
0 4
12.1%
2 1
 
3.0%
5 1
 
3.0%
7 1
 
3.0%
8 1
 
3.0%
14 1
 
3.0%
18 1
 
3.0%
23 1
 
3.0%
45 1
 
3.0%
49 1
 
3.0%
ValueCountFrequency (%)
4883 1
3.0%
4426 1
3.0%
2577 1
3.0%
2074 1
3.0%
1927 1
3.0%
1795 1
3.0%
1773 1
3.0%
1638 1
3.0%
1340 1
3.0%
1216 1
3.0%

90세이상
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct28
Distinct (%)84.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean224.87879
Minimum0
Maximum1584
Zeros4
Zeros (%)12.1%
Negative0
Negative (%)0.0%
Memory size429.0 B
2023-12-12T07:51:11.893691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median36
Q3303
95-th percentile874.8
Maximum1584
Range1584
Interquartile range (IQR)299

Descriptive statistics

Standard deviation370.66029
Coefficient of variation (CV)1.648267
Kurtosis5.1007186
Mean224.87879
Median Absolute Deviation (MAD)36
Skewness2.1931084
Sum7421
Variance137389.05
MonotonicityNot monotonic
2023-12-12T07:51:12.063057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0 4
 
12.1%
4 3
 
9.1%
1104 1
 
3.0%
169 1
 
3.0%
44 1
 
3.0%
33 1
 
3.0%
411 1
 
3.0%
273 1
 
3.0%
654 1
 
3.0%
694 1
 
3.0%
Other values (18) 18
54.5%
ValueCountFrequency (%)
0 4
12.1%
1 1
 
3.0%
3 1
 
3.0%
4 3
9.1%
6 1
 
3.0%
8 1
 
3.0%
19 1
 
3.0%
21 1
 
3.0%
22 1
 
3.0%
25 1
 
3.0%
ValueCountFrequency (%)
1584 1
3.0%
1104 1
3.0%
722 1
3.0%
694 1
3.0%
654 1
3.0%
523 1
3.0%
495 1
3.0%
411 1
3.0%
303 1
3.0%
273 1
3.0%

Interactions

2023-12-12T07:51:08.793101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:06.001173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:06.586334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:07.186857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:07.753888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:08.321948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:08.875001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:06.093914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:06.668111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:07.279469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:07.840274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:08.403166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:08.955399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:06.195689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:06.751696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:07.370293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:07.946372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:08.476894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:09.052049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:06.290257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:06.865714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:07.459780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:08.068271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:08.559335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:09.134455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:06.386713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:06.979721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:07.555277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:08.150289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:08.640385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:09.212038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:06.482458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:07.056128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:07.648152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:08.227136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:08.714248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:51:12.201483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분상병코드상병명칭59세이하60세-64세65세-69세70세-79세80세-89세90세이상
구분1.0000.0000.0000.5400.5940.7080.5030.3900.621
상병코드0.0001.0001.0000.0000.4130.2800.3370.6470.000
상병명칭0.0001.0001.0000.0000.4130.2800.3370.6470.000
59세이하0.5400.0000.0001.0000.8830.8570.8090.8950.916
60세-64세0.5940.4130.4130.8831.0000.8000.9020.7390.764
65세-69세0.7080.2800.2800.8570.8001.0000.9420.8840.868
70세-79세0.5030.3370.3370.8090.9020.9421.0000.9090.804
80세-89세0.3900.6470.6470.8950.7390.8840.9091.0000.908
90세이상0.6210.0000.0000.9160.7640.8680.8040.9081.000
2023-12-12T07:51:12.343902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분상병코드상병명칭
구분1.0000.0000.000
상병코드0.0001.0001.000
상병명칭0.0001.0001.000
2023-12-12T07:51:12.463165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
59세이하60세-64세65세-69세70세-79세80세-89세90세이상구분상병코드상병명칭
59세이하1.0000.8450.8580.8840.8950.8040.3920.0000.000
60세-64세0.8451.0000.8800.8830.8800.8060.4150.1630.163
65세-69세0.8580.8801.0000.8240.8330.8290.3620.0560.056
70세-79세0.8840.8830.8241.0000.9570.8570.3280.1120.112
80세-89세0.8950.8800.8330.9571.0000.9250.2550.3450.345
90세이상0.8040.8060.8290.8570.9251.0000.4770.0000.000
구분0.3920.4150.3620.3280.2550.4771.0000.0000.000
상병코드0.0000.1630.0560.1120.3450.0000.0001.0001.000
상병명칭0.0000.1630.0560.1120.3450.0000.0001.0001.000

Missing values

2023-12-12T07:51:09.324459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:51:09.440869image/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

구분상병코드상병명칭59세이하60세-64세65세-69세70세-79세80세-89세90세이상
0입원 실인원I10~I13, I15고혈압3112874
1입원 실인원E10~E14당뇨병353594276
2입원 실인원F00~F99, G40~G41정신 및 행동장애40030188
3입원 실인원A15, A16, A19호흡기결핵010600
4입원 실인원I05~I09, I20~I27, I30~I52심장질환2118183084922
5입원 실인원I60~I69대뇌혈관질환2514221894519
6입원 실인원G00~G37, G43~G83신경계질환571615100233
7입원 실인원C00~C97, D00~D09악성신생물65344556815139
8입원 실인원E00~E07갑상선의 장애001500
9입원 실인원B18, B19, K70~K77간의 질환7542351
구분상병코드상병명칭59세이하60세-64세65세-69세70세-79세80세-89세90세이상
23외래E10~E14당뇨병147210601569124481795303
24외래F00~F99, G40~G41정신 및 행동장애310910831199940848831584
25외래A15, A16, A19호흡기결핵525071146
26외래I05~I09, I20~I27, I30~I52심장질환113410331503148942577694
27외래I60~I69대뇌혈관질환148769081281151927654
28외래G00~G37, G43~G83신경계질환17341269150577521340273
29외래C00~C97, D00~D09악성신생물65545157493581773411
30외래E00~E07갑상선의 장애407201266116021033
31외래B18, B19, K70~K77간의 질환740353340194518144
32외래N18만성신부전증640722392386969169