Overview

Dataset statistics

Number of variables11
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.4 KiB
Average record size in memory96.3 B

Variable types

Categorical5
Text2
Numeric4

Dataset

Description샘플 데이터
Author지디에스컨설팅그룹
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=153a4740-2e00-11ea-9713-eb3e5186fb38

Alerts

화력발전소 고유id has constant value ""Constant
화력발전소 명 has constant value ""Constant
화력발전소 주소 has constant value ""Constant
화력발전소 x 위치 has constant value ""Constant
화력발전소 y 위치 has constant value ""Constant
진료비 is highly overall correlated with 본인부담금 and 1 other fieldsHigh correlation
본인부담금 is highly overall correlated with 진료비 and 1 other fieldsHigh correlation
전국화력발전소 진료비 총액 is highly overall correlated with 진료비 and 1 other fieldsHigh correlation
질병코드 has unique valuesUnique
질병명칭 has unique valuesUnique
진료비 has unique valuesUnique
본인부담금 has unique valuesUnique
전국화력발전소 진료비 총액 has unique valuesUnique

Reproduction

Analysis started2023-12-10 11:54:56.509971
Analysis finished2023-12-10 11:55:00.099011
Duration3.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

화력발전소 고유id
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 100
100.0%

Length

2023-12-10T20:55:00.207165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:55:00.339484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 100
100.0%

화력발전소 명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
광양복합화력발전소
100 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광양복합화력발전소 100
100.0%

Length

2023-12-10T20:55:00.499975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:55:00.637642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광양복합화력발전소 100
100.0%

화력발전소 주소
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
전라남도 광양시 제철로 2148-567
100 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전라남도 광양시 제철로 2148-567
2nd row전라남도 광양시 제철로 2148-567
3rd row전라남도 광양시 제철로 2148-567
4th row전라남도 광양시 제철로 2148-567
5th row전라남도 광양시 제철로 2148-567

Common Values

ValueCountFrequency (%)
전라남도 광양시 제철로 2148-567 100
100.0%

Length

2023-12-10T20:55:00.787202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:55:00.929610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라남도 100
25.0%
광양시 100
25.0%
제철로 100
25.0%
2148-567 100
25.0%

화력발전소 x 위치
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
34.88715092
100 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row34.88715092
2nd row34.88715092
3rd row34.88715092
4th row34.88715092
5th row34.88715092

Common Values

ValueCountFrequency (%)
34.88715092 100
100.0%

Length

2023-12-10T20:55:01.109218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:55:01.267972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
34.88715092 100
100.0%

화력발전소 y 위치
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
127.7760381
100 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row127.7760381
2nd row127.7760381
3rd row127.7760381
4th row127.7760381
5th row127.7760381

Common Values

ValueCountFrequency (%)
127.7760381 100
100.0%

Length

2023-12-10T20:55:01.390696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:55:01.523798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
127.7760381 100
100.0%

질병코드
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T20:55:01.907801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters300
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st rowI00
2nd rowI01
3rd rowI05
4th rowI06
5th rowI07
ValueCountFrequency (%)
i00 1
 
1.0%
i82 1
 
1.0%
i99 1
 
1.0%
i98 1
 
1.0%
i97 1
 
1.0%
i95 1
 
1.0%
i89 1
 
1.0%
i88 1
 
1.0%
i87 1
 
1.0%
i86 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T20:55:02.487960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
I 74
24.7%
0 27
 
9.0%
1 27
 
9.0%
J 26
 
8.7%
3 25
 
8.3%
2 23
 
7.7%
6 19
 
6.3%
8 19
 
6.3%
4 18
 
6.0%
7 17
 
5.7%
Other values (2) 25
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 200
66.7%
Uppercase Letter 100
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 27
13.5%
1 27
13.5%
3 25
12.5%
2 23
11.5%
6 19
9.5%
8 19
9.5%
4 18
9.0%
7 17
8.5%
5 14
7.0%
9 11
5.5%
Uppercase Letter
ValueCountFrequency (%)
I 74
74.0%
J 26
 
26.0%

Most occurring scripts

ValueCountFrequency (%)
Common 200
66.7%
Latin 100
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 27
13.5%
1 27
13.5%
3 25
12.5%
2 23
11.5%
6 19
9.5%
8 19
9.5%
4 18
9.0%
7 17
8.5%
5 14
7.0%
9 11
5.5%
Latin
ValueCountFrequency (%)
I 74
74.0%
J 26
 
26.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
I 74
24.7%
0 27
 
9.0%
1 27
 
9.0%
J 26
 
8.7%
3 25
 
8.3%
2 23
 
7.7%
6 19
 
6.3%
8 19
 
6.3%
4 18
 
6.0%
7 17
 
5.7%
Other values (2) 25
 
8.3%

질병명칭
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T20:55:02.971211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length20
Mean length12.5
Min length2

Characters and Unicode

Total characters1250
Distinct characters163
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row심장 침습이 없는 류마티스열
2nd row심장 침습이 있는 류마티스 열
3rd row류마티스성 승모판 질환
4th row류마티스성 대동맥판 질환
5th row류마티스성 삼첨판 질환
ValueCountFrequency (%)
및 23
 
6.7%
기타 21
 
6.1%
질환 17
 
4.9%
장애 16
 
4.6%
급성 16
 
4.6%
심장 12
 
3.5%
달리 11
 
3.2%
않은 8
 
2.3%
질환에서의 7
 
2.0%
분류된 7
 
2.0%
Other values (144) 207
60.0%
2023-12-10T20:55:03.686911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
245
 
19.6%
성 50
 
4.0%
의 35
 
2.8%
기 32
 
2.6%
장 31
 
2.5%
환 29
 
2.3%
심 28
 
2.2%
염 28
 
2.2%
질 26
 
2.1%
류 25
 
2.0%
Other values (153) 721
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 991
79.3%
Space Separator 245
 
19.6%
Close Punctuation 6
 
0.5%
Open Punctuation 6
 
0.5%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 50
 
5.0%
의 35
 
3.5%
기 32
 
3.2%
장 31
 
3.1%
환 29
 
2.9%
심 28
 
2.8%
염 28
 
2.8%
질 26
 
2.6%
류 25
 
2.5%
혈 24
 
2.4%
Other values (147) 683
68.9%
Close Punctuation
ValueCountFrequency (%)
) 4
66.7%
] 2
33.3%
Open Punctuation
ValueCountFrequency (%)
( 4
66.7%
[ 2
33.3%
Space Separator
ValueCountFrequency (%)
245
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 991
79.3%
Common 259
 
20.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 50
 
5.0%
의 35
 
3.5%
기 32
 
3.2%
장 31
 
3.1%
환 29
 
2.9%
심 28
 
2.8%
염 28
 
2.8%
질 26
 
2.6%
류 25
 
2.5%
혈 24
 
2.4%
Other values (147) 683
68.9%
Common
ValueCountFrequency (%)
245
94.6%
) 4
 
1.5%
( 4
 
1.5%
[ 2
 
0.8%
] 2
 
0.8%
, 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 991
79.3%
ASCII 259
 
20.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
245
94.6%
) 4
 
1.5%
( 4
 
1.5%
[ 2
 
0.8%
] 2
 
0.8%
, 2
 
0.8%
Hangul
ValueCountFrequency (%)
성 50
 
5.0%
의 35
 
3.5%
기 32
 
3.2%
장 31
 
3.1%
환 29
 
2.9%
심 28
 
2.8%
염 28
 
2.8%
질 26
 
2.6%
류 25
 
2.5%
혈 24
 
2.4%
Other values (147) 683
68.9%

진료비
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7620392 × 108
Minimum10600
Maximum6.9102895 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:55:03.938678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10600
5-th percentile218230
Q15580970
median55376010
Q32.9796094 × 108
95-th percentile1.7528709 × 109
Maximum6.9102895 × 109
Range6.9102789 × 109
Interquartile range (IQR)2.9237997 × 108

Descriptive statistics

Standard deviation9.1921357 × 108
Coefficient of variation (CV)2.4433918
Kurtosis28.928282
Mean3.7620392 × 108
Median Absolute Deviation (MAD)54677985
Skewness4.8839123
Sum3.7620392 × 1010
Variance8.4495359 × 1017
MonotonicityNot monotonic
2023-12-10T20:55:04.175076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
497480 1
 
1.0%
717814440 1
 
1.0%
587771160 1
 
1.0%
559250 1
 
1.0%
158950 1
 
1.0%
221350 1
 
1.0%
23959180 1
 
1.0%
19013620 1
 
1.0%
38480980 1
 
1.0%
20239570 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
10600 1
1.0%
39760 1
1.0%
76930 1
1.0%
127360 1
1.0%
158950 1
1.0%
221350 1
1.0%
228320 1
1.0%
429150 1
1.0%
497480 1
1.0%
559250 1
1.0%
ValueCountFrequency (%)
6910289520 1
1.0%
4313225920 1
1.0%
3046465630 1
1.0%
1858161490 1
1.0%
1814681340 1
1.0%
1749617770 1
1.0%
1383637170 1
1.0%
1366091730 1
1.0%
1169616100 1
1.0%
909777030 1
1.0%

본인부담금
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93578064
Minimum3700
Maximum1.9521378 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:55:04.417736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3700
5-th percentile69058.7
Q11059003.8
median10134841
Q371933634
95-th percentile3.6758492 × 108
Maximum1.9521378 × 109
Range1.9521341 × 109
Interquartile range (IQR)70874630

Descriptive statistics

Standard deviation2.4926079 × 108
Coefficient of variation (CV)2.6636669
Kurtosis34.365238
Mean93578064
Median Absolute Deviation (MAD)9896861
Skewness5.3632095
Sum9.3578064 × 109
Variance6.2130943 × 1016
MonotonicityNot monotonic
2023-12-10T20:55:04.667490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
49030 1
 
1.0%
168870249 1
 
1.0%
162956148 1
 
1.0%
286300 1
 
1.0%
51003 1
 
1.0%
70009 1
 
1.0%
8617221 1
 
1.0%
5266110 1
 
1.0%
10792732 1
 
1.0%
5341644 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
3700 1
1.0%
12008 1
1.0%
18400 1
1.0%
49030 1
1.0%
51003 1
1.0%
70009 1
1.0%
85500 1
1.0%
86960 1
1.0%
173840 1
1.0%
197981 1
1.0%
ValueCountFrequency (%)
1952137825 1
1.0%
1149072496 1
1.0%
798995775 1
1.0%
496448866 1
1.0%
384137591 1
1.0%
366713729 1
1.0%
339221557 1
1.0%
332864310 1
1.0%
280526388 1
1.0%
254716538 1
1.0%

본인부담금 비율
Real number (ℝ)

Distinct35
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.97
Minimum8
Maximum67
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:55:04.891572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile11
Q120
median26.5
Q330
95-th percentile41.05
Maximum67
Range59
Interquartile range (IQR)10

Descriptive statistics

Standard deviation9.4135675
Coefficient of variation (CV)0.36247853
Kurtosis3.3356411
Mean25.97
Median Absolute Deviation (MAD)5
Skewness0.98015477
Sum2597
Variance88.615253
MonotonicityNot monotonic
2023-12-10T20:55:05.111805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
30 8
 
8.0%
28 8
 
8.0%
27 7
 
7.0%
26 7
 
7.0%
32 7
 
7.0%
20 6
 
6.0%
24 5
 
5.0%
14 5
 
5.0%
29 4
 
4.0%
25 4
 
4.0%
Other values (25) 39
39.0%
ValueCountFrequency (%)
8 1
 
1.0%
9 1
 
1.0%
10 1
 
1.0%
11 3
3.0%
12 2
 
2.0%
14 5
5.0%
15 2
 
2.0%
16 3
3.0%
17 1
 
1.0%
19 2
 
2.0%
ValueCountFrequency (%)
67 1
1.0%
52 1
1.0%
51 1
1.0%
46 1
1.0%
42 1
1.0%
41 1
1.0%
38 1
1.0%
37 1
1.0%
36 1
1.0%
35 1
1.0%

전국화력발전소 진료비 총액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2499077 × 108
Minimum127420
Maximum1.3301036 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:55:05.332353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127420
5-th percentile2749277.9
Q118692694
median82892182
Q35.1264738 × 108
95-th percentile2.2429669 × 109
Maximum1.3301036 × 1010
Range1.3300909 × 1010
Interquartile range (IQR)4.9395469 × 108

Descriptive statistics

Standard deviation1.6387864 × 109
Coefficient of variation (CV)2.622097
Kurtosis38.720386
Mean6.2499077 × 108
Median Absolute Deviation (MAD)79244122
Skewness5.67735
Sum6.2499077 × 1010
Variance2.685621 × 1018
MonotonicityNot monotonic
2023-12-10T20:55:05.573138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5308830 1
 
1.0%
1145125293 1
 
1.0%
1095585940 1
 
1.0%
6112204 1
 
1.0%
19455481 1
 
1.0%
2298482 1
 
1.0%
22977200 1
 
1.0%
21985814 1
 
1.0%
65953812 1
 
1.0%
33787479 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
127420 1
1.0%
201316 1
1.0%
283152 1
1.0%
1126160 1
1.0%
2298482 1
1.0%
2773004 1
1.0%
3540037 1
1.0%
3756084 1
1.0%
3913507 1
1.0%
4063330 1
1.0%
ValueCountFrequency (%)
13301036376 1
1.0%
7180681515 1
1.0%
4974559794 1
1.0%
2929218036 1
1.0%
2885045378 1
1.0%
2209173258 1
1.0%
2013268585 1
1.0%
1868808142 1
1.0%
1671938068 1
1.0%
1483711556 1
1.0%

Interactions

2023-12-10T20:54:58.675063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:56.942766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:57.559983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:58.150776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:58.810441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:57.108833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:57.717390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:58.273244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:58.955846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:57.273875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:57.868487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:58.426753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:59.524986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:57.412625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:58.017630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:58.550268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T20:55:05.723788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
질병코드질병명칭진료비본인부담금본인부담금 비율전국화력발전소 진료비 총액
질병코드1.0001.0001.0001.0001.0001.000
질병명칭1.0001.0001.0001.0001.0001.000
진료비1.0001.0001.0000.9920.0000.994
본인부담금1.0001.0000.9921.0000.0000.988
본인부담금 비율1.0001.0000.0000.0001.0000.000
전국화력발전소 진료비 총액1.0001.0000.9940.9880.0001.000
2023-12-10T20:55:05.895572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
진료비본인부담금본인부담금 비율전국화력발전소 진료비 총액
진료비1.0000.992-0.4190.939
본인부담금0.9921.000-0.3250.943
본인부담금 비율-0.419-0.3251.000-0.300
전국화력발전소 진료비 총액0.9390.943-0.3001.000

Missing values

2023-12-10T20:54:59.723375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T20:54:59.999107image/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

화력발전소 고유id화력발전소 명화력발전소 주소화력발전소 x 위치화력발전소 y 위치질병코드질병명칭진료비본인부담금본인부담금 비율전국화력발전소 진료비 총액
01광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038I00심장 침습이 없는 류마티스열4974804903095308830
11광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038I01심장 침습이 있는 류마티스 열80161025670032283152
21광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038I05류마티스성 승모판 질환1729446060419983482704388
31광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038I06류마티스성 대동맥판 질환595986017900813014438474
41광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038I07류마티스성 삼첨판 질환444430011753632624888469
51광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038I08다발성 판막 질환6455049074046801130874421
61광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038I09기타 류마티스성 심장 질환710680268300375973399
71광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038I10본태성(원발성) 고혈압691028952019521378252813301036376
81광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038I11고혈압성 심장 질환1804246505235050329726123800
91광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038I12고혈압성 신장 질환1422659040802102872106700
화력발전소 고유id화력발전소 명화력발전소 주소화력발전소 x 위치화력발전소 y 위치질병코드질병명칭진료비본인부담금본인부담금 비율전국화력발전소 진료비 총액
901광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038J20급성 기관지염43132259201149072496267180681515
911광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038J21급성 세기관지염116961610025471653821787304641
921광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038J22상세불명의 급성 하기도 감염2927787308416449228229010373
931광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038J30혈관운동성 및 알레르기성 비염1814681340496448866272209173258
941광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038J31만성 비염,비인두염 및 인두염531452101710018132317158249
951광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038J32만성 부비동염483462990140728845291181221254
961광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038J33비용종1732579056708203247444932
971광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038J34코 및 비동의 기타 장애2343626506740397528482614565
981광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038J35편도 및 아데노이드의 만성 질환1837671804609128925331869470
991광양복합화력발전소전라남도 광양시 제철로 2148-56734.887151127.776038J36편도주위 농양2611140507188625127296829543