Overview

Dataset statistics

Number of variables10
Number of observations32
Missing cells4
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory86.1 B

Variable types

Numeric2
Text4
Categorical4

Dataset

Description대전광역시 유성구 특수의료장비 현황에 대한 데이터로 의료기관명, 의료기관종별, 의료기관소재지, 의료장비종류, 모델명, 형식명, 제조번호, 관리기관명, 관리기관전화번호 등의 항목을 제공합니다.
Author대전광역시 유성구
URLhttps://www.data.go.kr/data/15036447/fileData.do

Alerts

관리기관전화번호 has constant value ""Constant
관리기관명 has constant value ""Constant
순번 is highly overall correlated with 의료장비종류High correlation
의료장비종류 is highly overall correlated with 순번High correlation
형식명 has 4 (12.5%) missing valuesMissing
순번 has unique valuesUnique
제조번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:53:28.208312
Analysis finished2023-12-12 06:53:29.438006
Duration1.23 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.5
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:53:29.521159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.55
Q18.75
median16.5
Q324.25
95-th percentile30.45
Maximum32
Range31
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation9.3808315
Coefficient of variation (CV)0.56853524
Kurtosis-1.2
Mean16.5
Median Absolute Deviation (MAD)8
Skewness0
Sum528
Variance88
MonotonicityStrictly increasing
2023-12-12T15:53:29.673431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 1
 
3.1%
18 1
 
3.1%
32 1
 
3.1%
31 1
 
3.1%
30 1
 
3.1%
29 1
 
3.1%
28 1
 
3.1%
27 1
 
3.1%
26 1
 
3.1%
25 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
1 1
3.1%
2 1
3.1%
3 1
3.1%
4 1
3.1%
5 1
3.1%
6 1
3.1%
7 1
3.1%
8 1
3.1%
9 1
3.1%
10 1
3.1%
ValueCountFrequency (%)
32 1
3.1%
31 1
3.1%
30 1
3.1%
29 1
3.1%
28 1
3.1%
27 1
3.1%
26 1
3.1%
25 1
3.1%
24 1
3.1%
23 1
3.1%

의료기관명
Text

Distinct17
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-12T15:53:29.921489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length9.28125
Min length5

Characters and Unicode

Total characters297
Distinct characters65
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

Unique13 ?
Unique (%)40.6%

Sample

1st row하나로의원
2nd row하나로의원
3rd row반석내과영상의학과의원
4th row사)성재원성세병원
5th row국군대전병원
ValueCountFrequency (%)
의료법인영훈의료재단유성선병원 10
31.2%
하나로의원 5
15.6%
국군대전병원 2
 
6.2%
반석내과영상의학과의원 2
 
6.2%
강창규내과의원 1
 
3.1%
송강복음내과의원 1
 
3.1%
미즈제일여성병원 1
 
3.1%
연합내과의원 1
 
3.1%
송강내과의원 1
 
3.1%
테크노내과의원 1
 
3.1%
Other values (7) 7
21.9%
2023-12-12T15:53:30.274851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
의 38
 
12.8%
원 33
 
11.1%
료 20
 
6.7%
병 16
 
5.4%
성 13
 
4.4%
영 12
 
4.0%
과 11
 
3.7%
재 11
 
3.7%
법 10
 
3.4%
인 10
 
3.4%
Other values (55) 123
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 296
99.7%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 38
 
12.8%
원 33
 
11.1%
료 20
 
6.8%
병 16
 
5.4%
성 13
 
4.4%
영 12
 
4.1%
과 11
 
3.7%
재 11
 
3.7%
법 10
 
3.4%
인 10
 
3.4%
Other values (54) 122
41.2%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 296
99.7%
Common 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 38
 
12.8%
원 33
 
11.1%
료 20
 
6.8%
병 16
 
5.4%
성 13
 
4.4%
영 12
 
4.1%
과 11
 
3.7%
재 11
 
3.7%
법 10
 
3.4%
인 10
 
3.4%
Other values (54) 122
41.2%
Common
ValueCountFrequency (%)
) 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 296
99.7%
ASCII 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
의 38
 
12.8%
원 33
 
11.1%
료 20
 
6.8%
병 16
 
5.4%
성 13
 
4.4%
영 12
 
4.1%
과 11
 
3.7%
재 11
 
3.7%
법 10
 
3.4%
인 10
 
3.4%
Other values (54) 122
41.2%
ASCII
ValueCountFrequency (%)
) 1
100.0%

의료기관종별
Categorical

Distinct4
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size388.0 B
의원
15 
종합병원
10 
병원
6 
부속의원
 
1

Length

Max length4
Median length2
Mean length2.6875
Min length2

Unique

Unique1 ?
Unique (%)3.1%

Sample

1st row의원
2nd row의원
3rd row의원
4th row병원
5th row병원

Common Values

ValueCountFrequency (%)
의원 15
46.9%
종합병원 10
31.2%
병원 6
 
18.8%
부속의원 1
 
3.1%

Length

2023-12-12T15:53:30.484924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:53:30.653638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의원 15
46.9%
종합병원 10
31.2%
병원 6
 
18.8%
부속의원 1
 
3.1%

의료기관소재지(도로명)
Text

Distinct17
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-12T15:53:30.897521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length41
Mean length29.8125
Min length22

Characters and Unicode

Total characters954
Distinct characters90
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

Unique13 ?
Unique (%)40.6%

Sample

1st row대전광역시 유성구 계룡로 92 (봉명동, CJ나인파크 3층)
2nd row대전광역시 유성구 계룡로 92 (봉명동, CJ나인파크 3층)
3rd row대전광역시 유성구 반석로 16, 6,9층 (반석동, 반석크리닉빌딩)
4th row대전광역시 유성구 온천북로33번길 21-32 (봉명동)
5th row대전광역시 유성구 자운로 27 (자운동)
ValueCountFrequency (%)
대전광역시 32
16.5%
유성구 32
16.5%
지족동 11
 
5.7%
북유성대로 10
 
5.2%
93 10
 
5.2%
계룡로 8
 
4.1%
봉명동 8
 
4.1%
3층 8
 
4.1%
92 5
 
2.6%
cj나인파크 5
 
2.6%
Other values (53) 65
33.5%
2023-12-12T15:53:31.300811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
 
17.0%
대 47
 
4.9%
성 44
 
4.6%
유 43
 
4.5%
구 35
 
3.7%
동 33
 
3.5%
전 33
 
3.5%
로 32
 
3.4%
( 32
 
3.4%
) 32
 
3.4%
Other values (80) 461
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 557
58.4%
Space Separator 162
 
17.0%
Decimal Number 122
 
12.8%
Open Punctuation 32
 
3.4%
Close Punctuation 32
 
3.4%
Other Punctuation 28
 
2.9%
Uppercase Letter 14
 
1.5%
Dash Punctuation 4
 
0.4%
Math Symbol 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 47
 
8.4%
성 44
 
7.9%
유 43
 
7.7%
구 35
 
6.3%
동 33
 
5.9%
전 33
 
5.9%
로 32
 
5.7%
시 32
 
5.7%
역 32
 
5.7%
광 32
 
5.7%
Other values (59) 194
34.8%
Decimal Number
ValueCountFrequency (%)
3 27
22.1%
9 20
16.4%
1 20
16.4%
2 19
15.6%
6 12
9.8%
0 8
 
6.6%
4 7
 
5.7%
7 5
 
4.1%
5 3
 
2.5%
8 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
C 6
42.9%
J 5
35.7%
Y 1
 
7.1%
B 1
 
7.1%
E 1
 
7.1%
Space Separator
ValueCountFrequency (%)
162
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 557
58.4%
Common 383
40.1%
Latin 14
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 47
 
8.4%
성 44
 
7.9%
유 43
 
7.7%
구 35
 
6.3%
동 33
 
5.9%
전 33
 
5.9%
로 32
 
5.7%
시 32
 
5.7%
역 32
 
5.7%
광 32
 
5.7%
Other values (59) 194
34.8%
Common
ValueCountFrequency (%)
162
42.3%
( 32
 
8.4%
) 32
 
8.4%
, 28
 
7.3%
3 27
 
7.0%
9 20
 
5.2%
1 20
 
5.2%
2 19
 
5.0%
6 12
 
3.1%
0 8
 
2.1%
Other values (6) 23
 
6.0%
Latin
ValueCountFrequency (%)
C 6
42.9%
J 5
35.7%
Y 1
 
7.1%
B 1
 
7.1%
E 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 557
58.4%
ASCII 397
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
162
40.8%
( 32
 
8.1%
) 32
 
8.1%
, 28
 
7.1%
3 27
 
6.8%
9 20
 
5.0%
1 20
 
5.0%
2 19
 
4.8%
6 12
 
3.0%
0 8
 
2.0%
Other values (11) 37
 
9.3%
Hangul
ValueCountFrequency (%)
대 47
 
8.4%
성 44
 
7.9%
유 43
 
7.7%
구 35
 
6.3%
동 33
 
5.9%
전 33
 
5.9%
로 32
 
5.7%
시 32
 
5.7%
역 32
 
5.7%
광 32
 
5.7%
Other values (59) 194
34.8%

의료장비종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
유방촬영
17 
CT
8 
MRI
7 

Length

Max length4
Median length4
Mean length3.28125
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유방촬영 17
53.1%
CT 8
25.0%
MRI 7
21.9%

Length

2023-12-12T15:53:31.478140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:53:31.610335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유방촬영 17
53.1%
ct 8
25.0%
mri 7
21.9%

모델명
Text

Distinct27
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-12-12T15:53:31.815242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length25
Mean length17.90625
Min length6

Characters and Unicode

Total characters573
Distinct characters56
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)68.8%

Sample

1st rowTOSHIBA SCANNER Aquilion PRIME MODEL TSX-303A
2nd rowTOSHIBA SCANNER Alexion MODEL TSX-032A
3rd rowBrivo CT 385
4th rowSOMATOM Spirit
5th rowSomatom Sensation 64
ValueCountFrequency (%)
magnetom 5
 
6.4%
senographe 4
 
5.1%
selenia 4
 
5.1%
somatom 4
 
5.1%
dimensions 3
 
3.8%
mammomat 3
 
3.8%
64 2
 
2.6%
ds 2
 
2.6%
model 2
 
2.6%
scanner 2
 
2.6%
Other values (41) 47
60.3%
2023-12-12T15:53:32.222161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
8.0%
e 38
 
6.6%
i 36
 
6.3%
n 31
 
5.4%
a 30
 
5.2%
S 29
 
5.1%
o 28
 
4.9%
M 28
 
4.9%
A 21
 
3.7%
s 20
 
3.5%
Other values (46) 266
46.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 296
51.7%
Uppercase Letter 179
31.2%
Space Separator 46
 
8.0%
Decimal Number 41
 
7.2%
Dash Punctuation 8
 
1.4%
Other Punctuation 3
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 38
12.8%
i 36
12.2%
n 31
10.5%
a 30
10.1%
o 28
9.5%
s 20
6.8%
m 19
 
6.4%
t 16
 
5.4%
r 15
 
5.1%
l 14
 
4.7%
Other values (14) 49
16.6%
Uppercase Letter
ValueCountFrequency (%)
S 29
16.2%
M 28
15.6%
A 21
11.7%
T 15
8.4%
O 12
 
6.7%
N 11
 
6.1%
E 11
 
6.1%
D 9
 
5.0%
X 7
 
3.9%
G 6
 
3.4%
Other values (9) 30
16.8%
Decimal Number
ValueCountFrequency (%)
0 19
46.3%
3 5
 
12.2%
1 4
 
9.8%
5 4
 
9.8%
6 3
 
7.3%
4 2
 
4.9%
8 2
 
4.9%
2 2
 
4.9%
Other Punctuation
ValueCountFrequency (%)
/ 1
33.3%
. 1
33.3%
& 1
33.3%
Space Separator
ValueCountFrequency (%)
46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 475
82.9%
Common 98
 
17.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 38
 
8.0%
i 36
 
7.6%
n 31
 
6.5%
a 30
 
6.3%
S 29
 
6.1%
o 28
 
5.9%
M 28
 
5.9%
A 21
 
4.4%
s 20
 
4.2%
m 19
 
4.0%
Other values (33) 195
41.1%
Common
ValueCountFrequency (%)
46
46.9%
0 19
19.4%
- 8
 
8.2%
3 5
 
5.1%
1 4
 
4.1%
5 4
 
4.1%
6 3
 
3.1%
4 2
 
2.0%
8 2
 
2.0%
2 2
 
2.0%
Other values (3) 3
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 573
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
 
8.0%
e 38
 
6.6%
i 36
 
6.3%
n 31
 
5.4%
a 30
 
5.2%
S 29
 
5.1%
o 28
 
4.9%
M 28
 
4.9%
A 21
 
3.7%
s 20
 
3.5%
Other values (46) 266
46.4%

형식명
Text

MISSING 

Distinct24
Distinct (%)85.7%
Missing4
Missing (%)12.5%
Memory size388.0 B
2023-12-12T15:53:32.474921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length9.75
Min length3

Characters and Unicode

Total characters273
Distinct characters40
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

Unique20 ?
Unique (%)71.4%

Sample

1st rowWCT-600-135
2nd rowWCT-300-135
3rd rowWCT-200-140
4th rowWCT-180-130
5th rowWCT-500-140
ValueCountFrequency (%)
mhr-49-p 2
 
6.9%
mr-100-39 2
 
6.9%
wct-500-140 2
 
6.9%
mhr-35-p 2
 
6.9%
r-150-35 1
 
3.4%
wct-600-135 1
 
3.4%
mr-100-35 1
 
3.4%
mr-200-49 1
 
3.4%
mr-85-39 1
 
3.4%
mr-100-49(mr-100-35 1
 
3.4%
Other values (15) 15
51.7%
2023-12-12T15:53:32.881870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 52
19.0%
0 41
15.0%
3 19
 
7.0%
M 17
 
6.2%
R 17
 
6.2%
5 17
 
6.2%
1 17
 
6.2%
4 10
 
3.7%
9 9
 
3.3%
T 9
 
3.3%
Other values (30) 65
23.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 122
44.7%
Uppercase Letter 69
25.3%
Dash Punctuation 52
19.0%
Other Letter 14
 
5.1%
Lowercase Letter 6
 
2.2%
Open Punctuation 3
 
1.1%
Close Punctuation 3
 
1.1%
Other Punctuation 3
 
1.1%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 2
14.3%
장 2
14.3%
식 2
14.3%
구 1
7.1%
도 1
7.1%
형 1
7.1%
초 1
7.1%
방 1
7.1%
전 1
7.1%
기 1
7.1%
Decimal Number
ValueCountFrequency (%)
0 41
33.6%
3 19
15.6%
5 17
13.9%
1 17
13.9%
4 10
 
8.2%
9 9
 
7.4%
8 5
 
4.1%
2 3
 
2.5%
6 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
M 17
24.6%
R 17
24.6%
T 9
13.0%
C 8
11.6%
W 8
11.6%
P 4
 
5.8%
H 4
 
5.8%
S 1
 
1.4%
E 1
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
s 2
33.3%
z 1
16.7%
a 1
16.7%
n 1
16.7%
e 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
, 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 184
67.4%
Latin 75
27.5%
Hangul 14
 
5.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 52
28.3%
0 41
22.3%
3 19
 
10.3%
5 17
 
9.2%
1 17
 
9.2%
4 10
 
5.4%
9 9
 
4.9%
8 5
 
2.7%
( 3
 
1.6%
2 3
 
1.6%
Other values (5) 8
 
4.3%
Latin
ValueCountFrequency (%)
M 17
22.7%
R 17
22.7%
T 9
12.0%
C 8
10.7%
W 8
10.7%
P 4
 
5.3%
H 4
 
5.3%
s 2
 
2.7%
z 1
 
1.3%
S 1
 
1.3%
Other values (4) 4
 
5.3%
Hangul
ValueCountFrequency (%)
자 2
14.3%
장 2
14.3%
식 2
14.3%
구 1
7.1%
도 1
7.1%
형 1
7.1%
초 1
7.1%
방 1
7.1%
전 1
7.1%
기 1
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 259
94.9%
Hangul 14
 
5.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 52
20.1%
0 41
15.8%
3 19
 
7.3%
M 17
 
6.6%
R 17
 
6.6%
5 17
 
6.6%
1 17
 
6.6%
4 10
 
3.9%
9 9
 
3.5%
T 9
 
3.5%
Other values (19) 51
19.7%
Hangul
ValueCountFrequency (%)
자 2
14.3%
장 2
14.3%
식 2
14.3%
구 1
7.1%
도 1
7.1%
형 1
7.1%
초 1
7.1%
방 1
7.1%
전 1
7.1%
기 1
7.1%

제조번호
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4584855 × 109
Minimum57
Maximum8.1001166 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2023-12-12T15:53:33.045578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum57
5-th percentile460.45
Q118827.25
median68256.5
Q3604000.75
95-th percentile1.3302992 × 1010
Maximum8.1001166 × 1010
Range8.1001166 × 1010
Interquartile range (IQR)585173.5

Descriptive statistics

Standard deviation1.5072827 × 1010
Coefficient of variation (CV)4.358216
Kurtosis24.459347
Mean3.4584855 × 109
Median Absolute Deviation (MAD)65915.5
Skewness4.8480162
Sum1.1067154 × 1011
Variance2.2719011 × 1020
MonotonicityNot monotonic
2023-12-12T15:53:33.214966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1392046 1
 
3.1%
50317 1
 
3.1%
600418 1
 
3.1%
131800157 1
 
3.1%
57 1
 
3.1%
3680 1
 
3.1%
614749 1
 
3.1%
12132 1
 
3.1%
131400229 1
 
3.1%
1002 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
57 1
3.1%
109 1
3.1%
748 1
3.1%
1002 1
3.1%
3680 1
3.1%
12132 1
3.1%
12288 1
3.1%
15018 1
3.1%
20097 1
3.1%
25730 1
3.1%
ValueCountFrequency (%)
81001166092 1
3.1%
29401116445 1
3.1%
131800157 1
3.1%
131400229 1
3.1%
1392046 1
3.1%
1342163 1
3.1%
638708 1
3.1%
614749 1
3.1%
600418 1
3.1%
431047 1
3.1%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
042-611-5044
32 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row042-611-5044
2nd row042-611-5044
3rd row042-611-5044
4th row042-611-5044
5th row042-611-5044

Common Values

ValueCountFrequency (%)
042-611-5044 32
100.0%

Length

2023-12-12T15:53:33.391774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:53:33.500107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
042-611-5044 32
100.0%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
대전광역시 유성구보건소
32 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대전광역시 유성구보건소
2nd row대전광역시 유성구보건소
3rd row대전광역시 유성구보건소
4th row대전광역시 유성구보건소
5th row대전광역시 유성구보건소

Common Values

ValueCountFrequency (%)
대전광역시 유성구보건소 32
100.0%

Length

2023-12-12T15:53:33.598123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:53:33.712131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 32
50.0%
유성구보건소 32
50.0%

Interactions

2023-12-12T15:53:28.889139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:53:28.654652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:53:29.010019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:53:28.773767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:53:33.808496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번의료기관명의료기관종별의료기관소재지(도로명)의료장비종류모델명형식명제조번호
순번1.0000.5690.7250.5690.9180.5760.6530.322
의료기관명0.5691.0001.0001.0000.0000.8910.8880.000
의료기관종별0.7251.0001.0001.0000.0210.0000.8470.000
의료기관소재지(도로명)0.5691.0001.0001.0000.0000.8910.8880.000
의료장비종류0.9180.0000.0210.0001.0001.0001.0000.000
모델명0.5760.8910.0000.8911.0001.0000.9731.000
형식명0.6530.8880.8470.8881.0000.9731.0000.000
제조번호0.3220.0000.0000.0000.0001.0000.0001.000
2023-12-12T15:53:34.011448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의료기관종별의료장비종류
의료기관종별1.0000.000
의료장비종류0.0001.000
2023-12-12T15:53:34.106418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번제조번호의료기관종별의료장비종류
순번1.000-0.1940.4620.769
제조번호-0.1941.0000.0000.000
의료기관종별0.4620.0001.0000.000
의료장비종류0.7690.0000.0001.000

Missing values

2023-12-12T15:53:29.164431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:53:29.364009image/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

순번의료기관명의료기관종별의료기관소재지(도로명)의료장비종류모델명형식명제조번호관리기관전화번호관리기관명
01하나로의원의원대전광역시 유성구 계룡로 92 (봉명동, CJ나인파크 3층)CTTOSHIBA SCANNER Aquilion PRIME MODEL TSX-303AWCT-600-1351392046042-611-5044대전광역시 유성구보건소
12하나로의원의원대전광역시 유성구 계룡로 92 (봉명동, CJ나인파크 3층)CTTOSHIBA SCANNER Alexion MODEL TSX-032AWCT-300-1351342163042-611-5044대전광역시 유성구보건소
23반석내과영상의학과의원의원대전광역시 유성구 반석로 16, 6,9층 (반석동, 반석크리닉빌딩)CTBrivo CT 385WCT-200-140431047042-611-5044대전광역시 유성구보건소
34사)성재원성세병원병원대전광역시 유성구 온천북로33번길 21-32 (봉명동)CTSOMATOM SpiritWCT-180-13084732042-611-5044대전광역시 유성구보건소
45국군대전병원병원대전광역시 유성구 자운로 27 (자운동)CTSomatom Sensation 64WCT-500-14055504042-611-5044대전광역시 유성구보건소
56의료법인영훈의료재단유성선병원종합병원대전광역시 유성구 북유성대로 93 (지족동)CTHiSpeed NX/iWCT-350-140107940042-611-5044대전광역시 유성구보건소
67의료법인영훈의료재단유성선병원종합병원대전광역시 유성구 북유성대로 93 (지족동)CTSomatom Definition FlashWCT-800-14073507042-611-5044대전광역시 유성구보건소
78의료법인영훈의료재단유성선병원종합병원대전광역시 유성구 북유성대로 93 (지족동)CTSomatom Sensation 64WCT-500-14055109042-611-5044대전광역시 유성구보건소
89하나로의원의원대전광역시 유성구 계룡로 92 (봉명동, CJ나인파크 3층)MRIMAGNETOM Verio<NA>40129042-611-5044대전광역시 유성구보건소
910리젠정형외과의원의원대전광역시 유성구 계백로 927, 코젤랜드 2,3층 (원내동)MRIMAGNETOM EssenzaEssenza139309042-611-5044대전광역시 유성구보건소
순번의료기관명의료기관종별의료기관소재지(도로명)의료장비종류모델명형식명제조번호관리기관전화번호관리기관명
2223송강내과의원의원대전광역시 유성구 구즉로 72 (송강동)유방촬영MF-150SR-150-3525730042-611-5044대전광역시 유성구보건소
2324연합내과의원의원대전광역시 유성구 노은로 166 (지족동)유방촬영Mammomat 1000MR-150-3512288042-611-5044대전광역시 유성구보건소
2425반석내과영상의학과의원의원대전광역시 유성구 반석로 16, 6,9층 (반석동, 반석크리닉빌딩)유방촬영MXR-200MMHR-49-P1002042-611-5044대전광역시 유성구보건소
2526의료법인영훈의료재단유성선병원종합병원대전광역시 유성구 북유성대로 93 (지족동)유방촬영Selenia Dimensions universalMHR-49-P131400229042-611-5044대전광역시 유성구보건소
2627의료법인영훈의료재단유성선병원종합병원대전광역시 유성구 북유성대로 93 (지족동)유방촬영Mammomat 1000구형식12132042-611-5044대전광역시 유성구보건소
2728의료법인영훈의료재단유성선병원종합병원대전광역시 유성구 북유성대로 93 (지족동)유방촬영Senographe DSMR-100-49(MR-100-35)614749042-611-5044대전광역시 유성구보건소
2829의료법인영훈의료재단유성선병원종합병원대전광역시 유성구 북유성대로 93 (지족동)유방촬영MAMMOMAT InspirationMHR-35-P3680042-611-5044대전광역시 유성구보건소
2930의료법인영훈의료재단유성선병원종합병원대전광역시 유성구 북유성대로 93 (지족동)유방촬영MX-500MR-85-3957042-611-5044대전광역시 유성구보건소
3031미즈제일여성병원병원대전광역시 유성구 계룡로 126, 2~6층 (봉명동)유방촬영Selenia Dimensions universalMR-200-49131800157042-611-5044대전광역시 유성구보건소
3132카이스트부속의원부속의원대전광역시 유성구 대학로 291 (구성동, 한국과학기술원 E-21)유방촬영Senographe DSMR-100-49600418042-611-5044대전광역시 유성구보건소