Overview

Dataset statistics

Number of variables4
Number of observations151
Missing cells131
Missing cells (%)21.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory32.9 B

Variable types

Categorical1
Text3

Dataset

Description한국보훈복지의료공단 광주보훈병원에서 개방하는 진료과정보로 진료과별로 보유하고 있는 장비와 진료내용의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15066442/fileData.do

Alerts

소속부서 has 60 (39.7%) missing valuesMissing
보유장비 has 60 (39.7%) missing valuesMissing
내용 has 11 (7.3%) missing valuesMissing

Reproduction

Analysis started2023-12-12 19:37:45.823125
Analysis finished2023-12-12 19:37:46.740953
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

진료과별
Categorical

Distinct23
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
내과
21 
재활의학과(재활센터)
11 
신경과
 
9
산부인과
 
9
영상의학과
 
9
Other values (18)
92 

Length

Max length11
Median length6
Mean length4.5231788
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
내과 21
 
13.9%
재활의학과(재활센터) 11
 
7.3%
신경과 9
 
6.0%
산부인과 9
 
6.0%
영상의학과 9
 
6.0%
소아청소년과 8
 
5.3%
비뇨의학과 8
 
5.3%
안과 7
 
4.6%
가정의학과 7
 
4.6%
한의과 6
 
4.0%
Other values (13) 56
37.1%

Length

2023-12-13T04:37:46.822057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
내과 21
 
13.9%
재활의학과(재활센터 11
 
7.3%
신경과 9
 
6.0%
산부인과 9
 
6.0%
영상의학과 9
 
6.0%
소아청소년과 8
 
5.3%
비뇨의학과 8
 
5.3%
안과 7
 
4.6%
가정의학과 7
 
4.6%
한의과 6
 
4.0%
Other values (13) 56
37.1%

소속부서
Text

MISSING 

Distinct58
Distinct (%)63.7%
Missing60
Missing (%)39.7%
Memory size1.3 KiB
2023-12-13T04:37:47.075781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length13
Mean length8.5384615
Min length3

Characters and Unicode

Total characters777
Distinct characters144
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)51.6%

Sample

1st row소화기(내시경실)
2nd row소화기(내시경실)
3rd row소화기(내시경실)
4th row순환기(심혈관조영실)
5th row순환기(심혈관조영실)
ValueCountFrequency (%)
뇌신경센터 8
 
5.5%
치료실 7
 
4.8%
순환기(심혈관조영실 6
 
4.1%
미숙아영유아 5
 
3.4%
소아당뇨 5
 
3.4%
저신장 5
 
3.4%
소아발달장애비만 5
 
3.4%
치 5
 
3.4%
및 5
 
3.4%
소아알레르기신생아 5
 
3.4%
Other values (63) 89
61.4%
2023-12-13T04:37:47.508828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
 
6.9%
실 47
 
6.0%
아 33
 
4.2%
신 25
 
3.2%
기 22
 
2.8%
치 22
 
2.8%
소 21
 
2.7%
료 19
 
2.4%
리 18
 
2.3%
) 18
 
2.3%
Other values (134) 498
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 660
84.9%
Space Separator 54
 
6.9%
Close Punctuation 18
 
2.3%
Open Punctuation 18
 
2.3%
Other Punctuation 16
 
2.1%
Uppercase Letter 10
 
1.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
실 47
 
7.1%
아 33
 
5.0%
신 25
 
3.8%
기 22
 
3.3%
치 22
 
3.3%
소 21
 
3.2%
료 19
 
2.9%
리 18
 
2.7%
장 17
 
2.6%
영 15
 
2.3%
Other values (122) 421
63.8%
Uppercase Letter
ValueCountFrequency (%)
T 3
30.0%
C 2
20.0%
P 1
 
10.0%
E 1
 
10.0%
M 1
 
10.0%
R 1
 
10.0%
I 1
 
10.0%
Space Separator
ValueCountFrequency (%)
54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 660
84.9%
Common 107
 
13.8%
Latin 10
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
실 47
 
7.1%
아 33
 
5.0%
신 25
 
3.8%
기 22
 
3.3%
치 22
 
3.3%
소 21
 
3.2%
료 19
 
2.9%
리 18
 
2.7%
장 17
 
2.6%
영 15
 
2.3%
Other values (122) 421
63.8%
Latin
ValueCountFrequency (%)
T 3
30.0%
C 2
20.0%
P 1
 
10.0%
E 1
 
10.0%
M 1
 
10.0%
R 1
 
10.0%
I 1
 
10.0%
Common
ValueCountFrequency (%)
54
50.5%
) 18
 
16.8%
( 18
 
16.8%
, 16
 
15.0%
- 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 660
84.9%
ASCII 117
 
15.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54
46.2%
) 18
 
15.4%
( 18
 
15.4%
, 16
 
13.7%
T 3
 
2.6%
C 2
 
1.7%
- 1
 
0.9%
P 1
 
0.9%
E 1
 
0.9%
M 1
 
0.9%
Other values (2) 2
 
1.7%
Hangul
ValueCountFrequency (%)
실 47
 
7.1%
아 33
 
5.0%
신 25
 
3.8%
기 22
 
3.3%
치 22
 
3.3%
소 21
 
3.2%
료 19
 
2.9%
리 18
 
2.7%
장 17
 
2.6%
영 15
 
2.3%
Other values (122) 421
63.8%

보유장비
Text

MISSING 

Distinct82
Distinct (%)90.1%
Missing60
Missing (%)39.7%
Memory size1.3 KiB
2023-12-13T04:37:47.767008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length7.6483516
Min length3

Characters and Unicode

Total characters696
Distinct characters184
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)82.4%

Sample

1st row위내시경
2nd rowS상 결장경
3rd row초음파 내시경
4th row심혈관조영기
5th row(Angio)
ValueCountFrequency (%)
초음파 6
 
4.7%
컴퓨터당층촬영기(ct 3
 
2.4%
검사 3
 
2.4%
뇌 3
 
2.4%
ct 2
 
1.6%
골밀도 2
 
1.6%
치료기 2
 
1.6%
내시경 2
 
1.6%
수술기 2
 
1.6%
및 2
 
1.6%
Other values (91) 100
78.7%
2023-12-13T04:37:48.171058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 48
 
6.9%
38
 
5.5%
사 24
 
3.4%
검 24
 
3.4%
파 18
 
2.6%
영 15
 
2.2%
자 14
 
2.0%
초 13
 
1.9%
경 13
 
1.9%
( 12
 
1.7%
Other values (174) 477
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 510
73.3%
Lowercase Letter 67
 
9.6%
Uppercase Letter 45
 
6.5%
Space Separator 38
 
5.5%
Open Punctuation 12
 
1.7%
Close Punctuation 12
 
1.7%
Decimal Number 7
 
1.0%
Other Punctuation 3
 
0.4%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 48
 
9.4%
사 24
 
4.7%
검 24
 
4.7%
파 18
 
3.5%
영 15
 
2.9%
자 14
 
2.7%
초 13
 
2.5%
경 13
 
2.5%
동 11
 
2.2%
음 11
 
2.2%
Other values (132) 319
62.5%
Lowercase Letter
ValueCountFrequency (%)
a 10
14.9%
o 8
11.9%
e 6
9.0%
t 6
9.0%
r 6
9.0%
n 5
7.5%
l 5
7.5%
m 4
 
6.0%
c 4
 
6.0%
s 4
 
6.0%
Other values (6) 9
13.4%
Uppercase Letter
ValueCountFrequency (%)
T 8
17.8%
C 7
15.6%
I 5
11.1%
M 4
8.9%
R 4
8.9%
A 4
8.9%
P 3
 
6.7%
S 2
 
4.4%
B 2
 
4.4%
E 1
 
2.2%
Other values (5) 5
11.1%
Decimal Number
ValueCountFrequency (%)
2 2
28.6%
3 2
28.6%
0 1
14.3%
9 1
14.3%
1 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 510
73.3%
Latin 112
 
16.1%
Common 74
 
10.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 48
 
9.4%
사 24
 
4.7%
검 24
 
4.7%
파 18
 
3.5%
영 15
 
2.9%
자 14
 
2.7%
초 13
 
2.5%
경 13
 
2.5%
동 11
 
2.2%
음 11
 
2.2%
Other values (132) 319
62.5%
Latin
ValueCountFrequency (%)
a 10
 
8.9%
o 8
 
7.1%
T 8
 
7.1%
C 7
 
6.2%
e 6
 
5.4%
t 6
 
5.4%
r 6
 
5.4%
n 5
 
4.5%
I 5
 
4.5%
l 5
 
4.5%
Other values (21) 46
41.1%
Common
ValueCountFrequency (%)
38
51.4%
( 12
 
16.2%
) 12
 
16.2%
2 2
 
2.7%
- 2
 
2.7%
3 2
 
2.7%
, 2
 
2.7%
0 1
 
1.4%
. 1
 
1.4%
9 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 510
73.3%
ASCII 186
 
26.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 48
 
9.4%
사 24
 
4.7%
검 24
 
4.7%
파 18
 
3.5%
영 15
 
2.9%
자 14
 
2.7%
초 13
 
2.5%
경 13
 
2.5%
동 11
 
2.2%
음 11
 
2.2%
Other values (132) 319
62.5%
ASCII
ValueCountFrequency (%)
38
20.4%
( 12
 
6.5%
) 12
 
6.5%
a 10
 
5.4%
o 8
 
4.3%
T 8
 
4.3%
C 7
 
3.8%
e 6
 
3.2%
t 6
 
3.2%
r 6
 
3.2%
Other values (32) 73
39.2%

내용
Text

MISSING 

Distinct137
Distinct (%)97.9%
Missing11
Missing (%)7.3%
Memory size1.3 KiB
2023-12-13T04:37:48.457799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length41
Mean length33.278571
Min length7

Characters and Unicode

Total characters4659
Distinct characters370
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)95.7%

Sample

1st row상하부 위장 질환, 간질환 위암, 간암진단 및 치료, 내시경
2nd row역행성 담췌관조영술(ERCP)
3rd row치료내시경(용종절제술/EVL/헤모클립 지혈술/내시경적 점막절제술)
4th row심장질환과 혈관질환에 대해 전박적인 검사 및 치료 시행
5th row고혈압, 심부전증, 심장판막질환, 동맥경화증, 고지혈증, 부정맥, 협심증
ValueCountFrequency (%)
및 46
 
4.2%
치료 37
 
3.3%
등 22
 
2.0%
진단 17
 
1.5%
질환 15
 
1.4%
시행 15
 
1.4%
진료 13
 
1.2%
수술 9
 
0.8%
등의 7
 
0.6%
등을 7
 
0.6%
Other values (742) 920
83.0%
2023-12-13T04:37:48.892071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
987
 
21.2%
, 229
 
4.9%
환 83
 
1.8%
료 78
 
1.7%
질 76
 
1.6%
치 73
 
1.6%
의 61
 
1.3%
진 61
 
1.3%
증 56
 
1.2%
기 53
 
1.1%
Other values (360) 2902
62.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3325
71.4%
Space Separator 987
 
21.2%
Other Punctuation 234
 
5.0%
Uppercase Letter 39
 
0.8%
Close Punctuation 32
 
0.7%
Open Punctuation 32
 
0.7%
Decimal Number 7
 
0.2%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
환 83
 
2.5%
료 78
 
2.3%
질 76
 
2.3%
치 73
 
2.2%
의 61
 
1.8%
진 61
 
1.8%
증 56
 
1.7%
기 53
 
1.6%
경 50
 
1.5%
및 48
 
1.4%
Other values (336) 2686
80.8%
Uppercase Letter
ValueCountFrequency (%)
C 8
20.5%
T 6
15.4%
P 6
15.4%
E 5
12.8%
F 3
 
7.7%
R 3
 
7.7%
I 2
 
5.1%
A 2
 
5.1%
O 1
 
2.6%
V 1
 
2.6%
Other values (2) 2
 
5.1%
Decimal Number
ValueCountFrequency (%)
4 2
28.6%
2 2
28.6%
5 1
14.3%
1 1
14.3%
8 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 229
97.9%
/ 4
 
1.7%
; 1
 
0.4%
Space Separator
ValueCountFrequency (%)
987
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3325
71.4%
Common 1295
 
27.8%
Latin 39
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
환 83
 
2.5%
료 78
 
2.3%
질 76
 
2.3%
치 73
 
2.2%
의 61
 
1.8%
진 61
 
1.8%
증 56
 
1.7%
기 53
 
1.6%
경 50
 
1.5%
및 48
 
1.4%
Other values (336) 2686
80.8%
Common
ValueCountFrequency (%)
987
76.2%
, 229
 
17.7%
) 32
 
2.5%
( 32
 
2.5%
/ 4
 
0.3%
- 3
 
0.2%
4 2
 
0.2%
2 2
 
0.2%
5 1
 
0.1%
; 1
 
0.1%
Other values (2) 2
 
0.2%
Latin
ValueCountFrequency (%)
C 8
20.5%
T 6
15.4%
P 6
15.4%
E 5
12.8%
F 3
 
7.7%
R 3
 
7.7%
I 2
 
5.1%
A 2
 
5.1%
O 1
 
2.6%
V 1
 
2.6%
Other values (2) 2
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3325
71.4%
ASCII 1334
28.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
987
74.0%
, 229
 
17.2%
) 32
 
2.4%
( 32
 
2.4%
C 8
 
0.6%
T 6
 
0.4%
P 6
 
0.4%
E 5
 
0.4%
/ 4
 
0.3%
F 3
 
0.2%
Other values (14) 22
 
1.6%
Hangul
ValueCountFrequency (%)
환 83
 
2.5%
료 78
 
2.3%
질 76
 
2.3%
치 73
 
2.2%
의 61
 
1.8%
진 61
 
1.8%
증 56
 
1.7%
기 53
 
1.6%
경 50
 
1.5%
및 48
 
1.4%
Other values (336) 2686
80.8%

Correlations

2023-12-13T04:37:48.977252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
진료과별소속부서보유장비
진료과별1.0001.0000.000
소속부서1.0001.0000.838
보유장비0.0000.8381.000

Missing values

2023-12-13T04:37:46.439768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:37:46.545677image/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.
2023-12-13T04:37:46.668666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

진료과별소속부서보유장비내용
0내과소화기(내시경실)위내시경상하부 위장 질환, 간질환 위암, 간암진단 및 치료, 내시경
1내과소화기(내시경실)S상 결장경역행성 담췌관조영술(ERCP)
2내과소화기(내시경실)초음파 내시경치료내시경(용종절제술/EVL/헤모클립 지혈술/내시경적 점막절제술)
3내과순환기(심혈관조영실)심혈관조영기심장질환과 혈관질환에 대해 전박적인 검사 및 치료 시행
4내과순환기(심혈관조영실)(Angio)고혈압, 심부전증, 심장판막질환, 동맥경화증, 고지혈증, 부정맥, 협심증
5내과순환기(심혈관조영실)심장초음파심방세동, 허혈성 심질환 진단 및 치료
6내과순환기(심혈관조영실)심운동부하검사관상동맥 조영술, 경피적 혈관내 금속스텐트 삽입술, 풍선혈관성형술
7내과순환기(심혈관조영실)동맥경화검사말초혈관성형술(상, 하지), 경동맥혈관 성형술
8내과순환기(심혈관조영실)<NA>영구적 심장박동기 삽입술
9내과호흡기흉부 CT호흡기질환(만성 폐쇄성 폐질환, 폐렴 , 호흡부전, 폐암, 결액) 간질성 폐질환
진료과별소속부서보유장비내용
141마취통증의학과수술실<NA>수술에 대한 전신마취, 부위마취, 진정 시행, 수술 외 처치에 필요한 진정이나 마취
142마취통증의학과회복실<NA>요통, 오십견에 의한 어깨통증, 수술 후 통증치료, 대상;포진 후 신경통 진료
143마취통증의학과통증클리닉<NA><NA>
144마취통증의학과외래환자 마취실<NA><NA>
145응급의학과<NA>초음파진단기(이동)광주,전남/북권역에서 발생되는 응급환자 발생시 신속 정확한 초기단계의 진료를
146응급의학과<NA>Automatic Blood통해 응급환자의 생명을 보존하고 진료를 위한 타진료영역과 연계를 통하여 효율
147응급의학과<NA>Gas Analyzer적인 진료 응급환자들에게 양질의 진료를 제공하기 위해 24시간 진료체제로 운영
148혈액종양내과<NA>Blood Warmer각종 혈액 질환과 종양의 진단과 치료를 담당
149혈액종양내과<NA><NA>급만성백혈병, 악성림프종, 골수형성이상증후군, 다발성골수증 등과 같은 혈액 질환을 치료
150혈액종양내과<NA><NA>두경부암, 폐암, 식도암, 위암, 간암, 췌담도암 등과 같은 종양을 치료