Overview

Dataset statistics

Number of variables13
Number of observations84
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.7 KiB
Average record size in memory105.6 B

Variable types

Categorical6
Text5
DateTime2

Dataset

Description충청남도 부여군에 소재한 의료기관에 설치된 의료기기 현황 정보(사업장명, 주소, 의료장비종류, 장치모델명, 장치용도 등)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=436&beforeMenuCd=DOM_000000201001001000&publicdatapk=15031339

Alerts

시군명 has constant value ""Constant
사용구분명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
장비용도 is highly overall correlated with 장치명칭High correlation
장치명칭 is highly overall correlated with 장비용도High correlation
제조국가명 is highly imbalanced (67.6%)Imbalance
제조번호 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:16:38.251381
Analysis finished2024-01-09 21:16:39.185342
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
충청남도 부여군
84 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청남도 부여군
2nd row충청남도 부여군
3rd row충청남도 부여군
4th row충청남도 부여군
5th row충청남도 부여군

Common Values

ValueCountFrequency (%)
충청남도 부여군 84
100.0%

Length

2024-01-10T06:16:39.232894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:16:39.544796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 84
50.0%
부여군 84
50.0%

사업장명
Text

Distinct42
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-01-10T06:16:39.713204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length10
Mean length8.202381
Min length4

Characters and Unicode

Total characters689
Distinct characters94
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)14.3%

Sample

1st row서울아산튼튼의원
2nd row서울아산튼튼의원
3rd row서울아산튼튼의원
4th row서울연합내과의원
5th row부여치과의원
ValueCountFrequency (%)
학교법인 6
 
6.1%
건양대학교부여병원 6
 
6.1%
건양교육재단 6
 
6.1%
성모의원 4
 
4.0%
서울아산튼튼의원 3
 
3.0%
박경석신경외과의원 3
 
3.0%
부여군보건소 3
 
3.0%
신통신경외과의원 3
 
3.0%
박태서치과의원 3
 
3.0%
성요셉연합의원 3
 
3.0%
Other values (36) 59
59.6%
2024-01-10T06:16:40.087391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 77
 
11.2%
의 68
 
9.9%
과 51
 
7.4%
치 37
 
5.4%
부 28
 
4.1%
여 24
 
3.5%
건 19
 
2.8%
교 18
 
2.6%
15
 
2.2%
외 14
 
2.0%
Other values (84) 338
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 674
97.8%
Space Separator 15
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 77
 
11.4%
의 68
 
10.1%
과 51
 
7.6%
치 37
 
5.5%
부 28
 
4.2%
여 24
 
3.6%
건 19
 
2.8%
교 18
 
2.7%
외 14
 
2.1%
양 14
 
2.1%
Other values (83) 324
48.1%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 674
97.8%
Common 15
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 77
 
11.4%
의 68
 
10.1%
과 51
 
7.6%
치 37
 
5.5%
부 28
 
4.2%
여 24
 
3.6%
건 19
 
2.8%
교 18
 
2.7%
외 14
 
2.1%
양 14
 
2.1%
Other values (83) 324
48.1%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 674
97.8%
ASCII 15
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 77
 
11.4%
의 68
 
10.1%
과 51
 
7.6%
치 37
 
5.5%
부 28
 
4.2%
여 24
 
3.6%
건 19
 
2.8%
교 18
 
2.7%
외 14
 
2.1%
양 14
 
2.1%
Other values (83) 324
48.1%
ASCII
ValueCountFrequency (%)
15
100.0%

소재지도로명주소
Text

Distinct42
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-01-10T06:16:40.294471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length23.119048
Min length18

Characters and Unicode

Total characters1942
Distinct characters75
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)14.3%

Sample

1st row충청남도 부여군 부여읍 성왕로193번길 3, 2층
2nd row충청남도 부여군 부여읍 성왕로193번길 3, 2층
3rd row충청남도 부여군 부여읍 성왕로193번길 3, 2층
4th row충청남도 부여군 부여읍 중앙로 9, 2층 (정진빌딩)
5th row충청남도 부여군 부여읍 석탑로 52
ValueCountFrequency (%)
충청남도 84
17.8%
부여군 84
17.8%
부여읍 69
14.6%
2층 25
 
5.3%
사비로 20
 
4.2%
성왕로 14
 
3.0%
중앙로 7
 
1.5%
계백로 6
 
1.3%
200 6
 
1.3%
192 5
 
1.1%
Other values (71) 152
32.2%
2024-01-10T06:16:40.655425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
388
20.0%
여 157
 
8.1%
부 157
 
8.1%
도 86
 
4.4%
충 85
 
4.4%
군 84
 
4.3%
청 84
 
4.3%
남 84
 
4.3%
로 80
 
4.1%
읍 69
 
3.6%
Other values (65) 668
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1201
61.8%
Space Separator 388
 
20.0%
Decimal Number 275
 
14.2%
Other Punctuation 58
 
3.0%
Dash Punctuation 9
 
0.5%
Math Symbol 7
 
0.4%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
여 157
13.1%
부 157
13.1%
도 86
 
7.2%
충 85
 
7.1%
군 84
 
7.0%
청 84
 
7.0%
남 84
 
7.0%
로 80
 
6.7%
읍 69
 
5.7%
층 51
 
4.2%
Other values (49) 264
22.0%
Decimal Number
ValueCountFrequency (%)
2 62
22.5%
1 48
17.5%
3 36
13.1%
9 28
10.2%
0 25
9.1%
6 22
 
8.0%
4 15
 
5.5%
7 14
 
5.1%
8 13
 
4.7%
5 12
 
4.4%
Space Separator
ValueCountFrequency (%)
388
100.0%
Other Punctuation
ValueCountFrequency (%)
, 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1201
61.8%
Common 741
38.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
여 157
13.1%
부 157
13.1%
도 86
 
7.2%
충 85
 
7.1%
군 84
 
7.0%
청 84
 
7.0%
남 84
 
7.0%
로 80
 
6.7%
읍 69
 
5.7%
층 51
 
4.2%
Other values (49) 264
22.0%
Common
ValueCountFrequency (%)
388
52.4%
2 62
 
8.4%
, 58
 
7.8%
1 48
 
6.5%
3 36
 
4.9%
9 28
 
3.8%
0 25
 
3.4%
6 22
 
3.0%
4 15
 
2.0%
7 14
 
1.9%
Other values (6) 45
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1201
61.8%
ASCII 741
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
388
52.4%
2 62
 
8.4%
, 58
 
7.8%
1 48
 
6.5%
3 36
 
4.9%
9 28
 
3.8%
0 25
 
3.4%
6 22
 
3.0%
4 15
 
2.0%
7 14
 
1.9%
Other values (6) 45
 
6.1%
Hangul
ValueCountFrequency (%)
여 157
13.1%
부 157
13.1%
도 86
 
7.2%
충 85
 
7.1%
군 84
 
7.0%
청 84
 
7.0%
남 84
 
7.0%
로 80
 
6.7%
읍 69
 
5.7%
층 51
 
4.2%
Other values (49) 264
22.0%

사용구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
사용중
84 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용중 84
100.0%

Length

2024-01-10T06:16:40.776418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:16:40.873817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중 84
100.0%

신고일자
Date

Distinct76
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size804.0 B
Minimum1994-12-24 00:00:00
Maximum2022-08-26 00:00:00
2024-01-10T06:16:41.001270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:16:41.113035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

장비용도
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Memory size804.0 B
치과(구내촬영)
24 
일반촬영
18 
치과
12 
골밀도
12 
투시(C-ARM)
5 
Other values (6)
13 

Length

Max length12
Median length9
Mean length5.5833333
Min length2

Unique

Unique2 ?
Unique (%)2.4%

Sample

1st row투시(C-ARM)
2nd row일반촬영
3rd row투시(C-ARM)
4th row일반촬영
5th row치과

Common Values

ValueCountFrequency (%)
치과(구내촬영) 24
28.6%
일반촬영 18
21.4%
치과 12
14.3%
골밀도 12
14.3%
투시(C-ARM) 5
 
6.0%
유방촬영 3
 
3.6%
치과용CT 및 파노라마 3
 
3.6%
치과(파노라마·세팔로) 3
 
3.6%
전신 2
 
2.4%
이비인후과 1
 
1.2%

Length

2024-01-10T06:16:41.216144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
치과(구내촬영 24
26.1%
일반촬영 18
19.6%
치과 12
13.0%
골밀도 12
13.0%
투시(c-arm 5
 
5.4%
및 4
 
4.3%
유방촬영 3
 
3.3%
치과용ct 3
 
3.3%
파노라마 3
 
3.3%
치과(파노라마·세팔로 3
 
3.3%
Other values (4) 5
 
5.4%

장치명칭
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size804.0 B
진단용 엑스선 발생기
30 
치과진단용 엑스선 발생장치
17 
진단용 엑스선 장치
14 
전산화 단층 촬영장치
13 
치과용 전산화 단층 촬영장치
4 
Other values (5)
6 

Length

Max length15
Median length11
Mean length11.535714
Min length7

Unique

Unique4 ?
Unique (%)4.8%

Sample

1st row진단용 엑스선 발생기
2nd row진단용 엑스선 장치
3rd row진단용 엑스선 발생기
4th row진단용 엑스선 장치
5th row전산화 단층 촬영장치

Common Values

ValueCountFrequency (%)
진단용 엑스선 발생기 30
35.7%
치과진단용 엑스선 발생장치 17
20.2%
진단용 엑스선 장치 14
16.7%
전산화 단층 촬영장치 13
15.5%
치과용 전산화 단층 촬영장치 4
 
4.8%
유방촬영용장치 2
 
2.4%
포터블엑스선촬영장치 1
 
1.2%
치과용전산화단층촬영엑스선장치 1
 
1.2%
치과진단용X선발생장치 1
 
1.2%
유방촬영용 장치 1
 
1.2%

Length

2024-01-10T06:16:41.341258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:16:41.448380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
엑스선 61
24.9%
진단용 44
18.0%
발생기 30
12.2%
치과진단용 17
 
6.9%
발생장치 17
 
6.9%
전산화 17
 
6.9%
단층 17
 
6.9%
촬영장치 17
 
6.9%
장치 15
 
6.1%
치과용 4
 
1.6%
Other values (5) 6
 
2.4%

장치모델명
Text

Distinct62
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-01-10T06:16:41.698126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length18
Mean length10.214286
Min length3

Characters and Unicode

Total characters858
Distinct characters62
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)60.7%

Sample

1st rowZEN-2090 Turbo
2nd rowSIG-40-525
3rd rowZEN-2090 Turbo
4th rowJUMONG GENERAL
5th rowPHT-35LHS
ValueCountFrequency (%)
max-gls 7
 
5.1%
t 6
 
4.4%
dexxum 6
 
4.4%
point 5
 
3.7%
3d 5
 
3.7%
combi 5
 
3.7%
sig-40-525 3
 
2.2%
easy-ray 3
 
2.2%
500 3
 
2.2%
pht-35lhs 3
 
2.2%
Other values (77) 90
66.2%
2024-01-10T06:16:42.034728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 59
 
6.9%
52
 
6.1%
0 48
 
5.6%
S 40
 
4.7%
X 39
 
4.5%
E 35
 
4.1%
5 31
 
3.6%
o 29
 
3.4%
T 28
 
3.3%
M 28
 
3.3%
Other values (52) 469
54.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 404
47.1%
Lowercase Letter 192
22.4%
Decimal Number 141
 
16.4%
Dash Punctuation 59
 
6.9%
Space Separator 52
 
6.1%
Other Letter 3
 
0.3%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Letter Number 2
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 40
 
9.9%
X 39
 
9.7%
E 35
 
8.7%
T 28
 
6.9%
M 28
 
6.9%
D 27
 
6.7%
P 27
 
6.7%
R 23
 
5.7%
A 23
 
5.7%
G 17
 
4.2%
Other values (15) 117
29.0%
Lowercase Letter
ValueCountFrequency (%)
o 29
15.1%
i 22
11.5%
a 18
9.4%
m 18
9.4%
n 13
 
6.8%
t 13
 
6.8%
r 12
 
6.2%
u 11
 
5.7%
c 10
 
5.2%
y 10
 
5.2%
Other values (10) 36
18.8%
Decimal Number
ValueCountFrequency (%)
0 48
34.0%
5 31
22.0%
2 17
 
12.1%
3 16
 
11.3%
1 12
 
8.5%
6 9
 
6.4%
4 5
 
3.5%
9 3
 
2.1%
Other Letter
ValueCountFrequency (%)
제 1
33.3%
스 1
33.3%
우 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%
Space Separator
ValueCountFrequency (%)
52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 598
69.7%
Common 257
30.0%
Hangul 3
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 40
 
6.7%
X 39
 
6.5%
E 35
 
5.9%
o 29
 
4.8%
T 28
 
4.7%
M 28
 
4.7%
D 27
 
4.5%
P 27
 
4.5%
R 23
 
3.8%
A 23
 
3.8%
Other values (36) 299
50.0%
Common
ValueCountFrequency (%)
- 59
23.0%
52
20.2%
0 48
18.7%
5 31
12.1%
2 17
 
6.6%
3 16
 
6.2%
1 12
 
4.7%
6 9
 
3.5%
4 5
 
1.9%
9 3
 
1.2%
Other values (3) 5
 
1.9%
Hangul
ValueCountFrequency (%)
제 1
33.3%
스 1
33.3%
우 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 853
99.4%
Hangul 3
 
0.3%
Number Forms 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 59
 
6.9%
52
 
6.1%
0 48
 
5.6%
S 40
 
4.7%
X 39
 
4.6%
E 35
 
4.1%
5 31
 
3.6%
o 29
 
3.4%
T 28
 
3.3%
M 28
 
3.3%
Other values (48) 464
54.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
Hangul
ValueCountFrequency (%)
제 1
33.3%
스 1
33.3%
우 1
33.3%

장치형식명
Text

Distinct53
Distinct (%)63.1%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-01-10T06:16:42.243776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length10.166667
Min length6

Characters and Unicode

Total characters854
Distinct characters26
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)47.6%

Sample

1st rowHRF-20-110
2nd rowR-500-125
3rd rowHRF-20-110
4th rowR-500-125
5th rowCBCT(P)-16-99
ValueCountFrequency (%)
r-500-125 9
 
10.7%
d-10-60 5
 
6.0%
cbct(p)-16-99 4
 
4.8%
hr-60-p 4
 
4.8%
hrf-20-110 3
 
3.6%
hr-2-70 3
 
3.6%
d-60-p 3
 
3.6%
cbct(p)-10-90 3
 
3.6%
d-60-s 2
 
2.4%
mhr-150-35 2
 
2.4%
Other values (43) 46
54.8%
2024-01-10T06:16:42.563524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 186
21.8%
0 105
12.3%
1 69
 
8.1%
R 53
 
6.2%
5 47
 
5.5%
P 45
 
5.3%
H 38
 
4.4%
C 36
 
4.2%
6 33
 
3.9%
9 28
 
3.3%
Other values (16) 214
25.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 357
41.8%
Uppercase Letter 259
30.3%
Dash Punctuation 186
21.8%
Close Punctuation 22
 
2.6%
Open Punctuation 22
 
2.6%
Other Punctuation 4
 
0.5%
Lowercase Letter 4
 
0.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 53
20.5%
P 45
17.4%
H 38
14.7%
C 36
13.9%
D 25
9.7%
B 25
9.7%
T 21
 
8.1%
F 8
 
3.1%
S 3
 
1.2%
M 3
 
1.2%
Decimal Number
ValueCountFrequency (%)
0 105
29.4%
1 69
19.3%
5 47
13.2%
6 33
 
9.2%
9 28
 
7.8%
2 27
 
7.6%
3 25
 
7.0%
8 11
 
3.1%
7 8
 
2.2%
4 4
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 186
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
p 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 591
69.2%
Latin 263
30.8%

Most frequent character per script

Common
ValueCountFrequency (%)
- 186
31.5%
0 105
17.8%
1 69
 
11.7%
5 47
 
8.0%
6 33
 
5.6%
9 28
 
4.7%
2 27
 
4.6%
3 25
 
4.2%
) 22
 
3.7%
( 22
 
3.7%
Other values (4) 27
 
4.6%
Latin
ValueCountFrequency (%)
R 53
20.2%
P 45
17.1%
H 38
14.4%
C 36
13.7%
D 25
9.5%
B 25
9.5%
T 21
 
8.0%
F 8
 
3.0%
p 4
 
1.5%
S 3
 
1.1%
Other values (2) 5
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 854
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 186
21.8%
0 105
12.3%
1 69
 
8.1%
R 53
 
6.2%
5 47
 
5.5%
P 45
 
5.3%
H 38
 
4.4%
C 36
 
4.2%
6 33
 
3.9%
9 28
 
3.3%
Other values (16) 214
25.1%

제조국가명
Categorical

IMBALANCE 

Distinct5
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
대한민국
74 
독일
 
3
일본
 
3
미국
 
3
멕시코
 
1

Length

Max length4
Median length4
Mean length3.7738095
Min length2

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
대한민국 74
88.1%
독일 3
 
3.6%
일본 3
 
3.6%
미국 3
 
3.6%
멕시코 1
 
1.2%

Length

2024-01-10T06:16:42.710413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:16:42.897826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대한민국 74
88.1%
독일 3
 
3.6%
일본 3
 
3.6%
미국 3
 
3.6%
멕시코 1
 
1.2%

제조년월일
Date

Distinct76
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size804.0 B
Minimum1989-07-01 00:00:00
Maximum2022-08-23 00:00:00
2024-01-10T06:16:43.107798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:16:43.299567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제조번호
Text

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-01-10T06:16:43.683514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length10.214286
Min length2

Characters and Unicode

Total characters858
Distinct characters40
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)100.0%

Sample

1st rowZEN-720009-11122
2nd rowF7-91D522156
3rd rowZEN-518008-11122
4th rowSGJG2205275
5th row069-003914
ValueCountFrequency (%)
zen-720009-11122 1
 
1.1%
076-001472 1
 
1.1%
ah1ff 1
 
1.1%
052-1773 1
 
1.1%
bmt-dexa-14-065 1
 
1.1%
ah1fe1408012 1
 
1.1%
gd-080611-20414 1
 
1.1%
stx114049 1
 
1.1%
pnzs-kbl0790b 1
 
1.1%
061-0779 1
 
1.1%
Other values (78) 78
88.6%
2024-01-10T06:16:44.125826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 161
18.8%
1 118
13.8%
2 64
 
7.5%
- 56
 
6.5%
4 41
 
4.8%
3 40
 
4.7%
7 37
 
4.3%
6 35
 
4.1%
9 34
 
4.0%
5 34
 
4.0%
Other values (30) 238
27.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 586
68.3%
Uppercase Letter 207
 
24.1%
Dash Punctuation 56
 
6.5%
Space Separator 4
 
0.5%
Lowercase Letter 3
 
0.3%
Other Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 24
 
11.6%
E 15
 
7.2%
C 15
 
7.2%
N 14
 
6.8%
D 14
 
6.8%
G 13
 
6.3%
P 13
 
6.3%
M 10
 
4.8%
F 9
 
4.3%
B 9
 
4.3%
Other values (13) 71
34.3%
Decimal Number
ValueCountFrequency (%)
0 161
27.5%
1 118
20.1%
2 64
 
10.9%
4 41
 
7.0%
3 40
 
6.8%
7 37
 
6.3%
6 35
 
6.0%
9 34
 
5.8%
5 34
 
5.8%
8 22
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
s 1
33.3%
t 1
33.3%
x 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 648
75.5%
Latin 210
 
24.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 24
 
11.4%
E 15
 
7.1%
C 15
 
7.1%
N 14
 
6.7%
D 14
 
6.7%
G 13
 
6.2%
P 13
 
6.2%
M 10
 
4.8%
F 9
 
4.3%
B 9
 
4.3%
Other values (16) 74
35.2%
Common
ValueCountFrequency (%)
0 161
24.8%
1 118
18.2%
2 64
 
9.9%
- 56
 
8.6%
4 41
 
6.3%
3 40
 
6.2%
7 37
 
5.7%
6 35
 
5.4%
9 34
 
5.2%
5 34
 
5.2%
Other values (4) 28
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 858
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 161
18.8%
1 118
13.8%
2 64
 
7.5%
- 56
 
6.5%
4 41
 
4.8%
3 40
 
4.7%
7 37
 
4.3%
6 35
 
4.1%
9 34
 
4.0%
5 34
 
4.0%
Other values (30) 238
27.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
2022-08-31
84 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-31
2nd row2022-08-31
3rd row2022-08-31
4th row2022-08-31
5th row2022-08-31

Common Values

ValueCountFrequency (%)
2022-08-31 84
100.0%

Length

2024-01-10T06:16:44.249645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:16:44.334985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-31 84
100.0%

Correlations

2024-01-10T06:16:44.399038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명소재지도로명주소신고일자장비용도장치명칭장치모델명장치형식명제조국가명제조년월일제조번호
사업장명1.0001.0000.9990.0000.0000.3090.6430.0000.6601.000
소재지도로명주소1.0001.0000.9990.0000.0000.3090.6430.0000.6601.000
신고일자0.9990.9991.0000.8710.0000.8590.9840.0000.8641.000
장비용도0.0000.0000.8711.0000.8610.9961.0000.6580.8141.000
장치명칭0.0000.0000.0000.8611.0000.9750.9620.4580.9591.000
장치모델명0.3090.3090.8590.9960.9751.0000.9881.0000.9701.000
장치형식명0.6430.6430.9841.0000.9620.9881.0000.8500.9601.000
제조국가명0.0000.0000.0000.6580.4581.0000.8501.0000.0001.000
제조년월일0.6600.6600.8640.8140.9590.9700.9600.0001.0001.000
제조번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-01-10T06:16:44.528003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제조국가명장비용도장치명칭
제조국가명1.0000.4190.197
장비용도0.4191.0000.593
장치명칭0.1970.5931.000
2024-01-10T06:16:44.630390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
장비용도장치명칭제조국가명
장비용도1.0000.5930.419
장치명칭0.5931.0000.197
제조국가명0.4190.1971.000

Missing values

2024-01-10T06:16:38.997368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:16:39.133917image/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

시군명사업장명소재지도로명주소사용구분명신고일자장비용도장치명칭장치모델명장치형식명제조국가명제조년월일제조번호데이터기준일자
0충청남도 부여군서울아산튼튼의원충청남도 부여군 부여읍 성왕로193번길 3, 2층사용중2022-08-26투시(C-ARM)진단용 엑스선 발생기ZEN-2090 TurboHRF-20-110대한민국2022-08-23ZEN-720009-111222022-08-31
1충청남도 부여군서울아산튼튼의원충청남도 부여군 부여읍 성왕로193번길 3, 2층사용중2022-06-15일반촬영진단용 엑스선 장치SIG-40-525R-500-125대한민국2022-05-01F7-91D5221562022-08-31
2충청남도 부여군서울아산튼튼의원충청남도 부여군 부여읍 성왕로193번길 3, 2층사용중2022-06-15투시(C-ARM)진단용 엑스선 발생기ZEN-2090 TurboHRF-20-110대한민국2022-05-26ZEN-518008-111222022-08-31
3충청남도 부여군서울연합내과의원충청남도 부여군 부여읍 중앙로 9, 2층 (정진빌딩)사용중2022-05-13일반촬영진단용 엑스선 장치JUMONG GENERALR-500-125대한민국2022-05-01SGJG22052752022-08-31
4충청남도 부여군부여치과의원충청남도 부여군 부여읍 석탑로 52사용중2022-04-28치과전산화 단층 촬영장치PHT-35LHSCBCT(P)-16-99대한민국2019-07-01069-0039142022-08-31
5충청남도 부여군학교법인 건양교육재단 건양대학교부여병원충청남도 부여군 부여읍 계백로 200사용중2022-01-28유방촬영유방촬영용장치RMF-2000MHR-125-39대한민국2022-01-01MA7A057212022-08-31
6충청남도 부여군외산연세의원충청남도 부여군 외산면 외산로 87, 2층사용중2021-11-08일반촬영진단용 엑스선 장치DXG 100N-R-FSR-100-100대한민국1995-05-019506012022-08-31
7충청남도 부여군성모의원충청남도 부여군 부여읍 신동엽길 6, 2,3층사용중2021-11-04전신전산화 단층 촬영장치Somatom Emotion 6WCT-345-130독일2018-06-26444092022-08-31
8충청남도 부여군부여이비인후과의원충청남도 부여군 부여읍 성왕로 196, 3층사용중2021-09-23이비인후과전산화 단층 촬영장치PAPAYA 3D PremiumCBCT(C)-12-90대한민국2021-08-20GCT-081902-705212022-08-31
9충청남도 부여군부여효요양병원충청남도 부여군 초촌면 소호로 71사용중2021-08-31일반촬영진단용 엑스선 발생기Sirius 130HPHR-250-130일본2014-06-01SX121114152022-08-31
시군명사업장명소재지도로명주소사용구분명신고일자장비용도장치명칭장치모델명장치형식명제조국가명제조년월일제조번호데이터기준일자
74충청남도 부여군서울치과의원충청남도 부여군 홍산면 홍산로 39, 2층사용중2009-09-11치과치과용 전산화 단층 촬영장치Point CT Combi+DCT-90-P대한민국2019-08-01PNCB 09080012022-08-31
75충청남도 부여군노승식치과의원충청남도 부여군 부여읍 사비로 92사용중2009-04-10치과(파노라마·세팔로)치과진단용 엑스선 발생장치PaX-PrimoDP-10-80대한민국2019-03-01PPRIMO-NO903PNX041A2022-08-31
76충청남도 부여군서울치과의원충청남도 부여군 홍산면 홍산로 39, 2층사용중2008-05-30치과(구내촬영)진단용 엑스선 발생기DIOX-602HR-60-P대한민국2017-05-18DO7E04682022-08-31
77충청남도 부여군성모의원충청남도 부여군 부여읍 신동엽길 6, 2,3층사용중2008-04-28유방촬영유방촬영용장치MF-150SMHR-150-35미국1996-12-01BMF-267302022-08-31
78충청남도 부여군부여효요양병원충청남도 부여군 초촌면 소호로 71사용중2007-12-31일반촬영진단용 엑스선 장치SMS-5125-GMR-500-125대한민국2010-09-0153000332022-08-31
79충청남도 부여군굿샘치과의원충청남도 부여군 부여읍 중앙로 5사용중2006-12-12치과(파노라마·세팔로)치과진단용 엑스선 발생장치PaX-300(C)DP-82-P대한민국2013-09-01PX3-0001152022-08-31
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