Overview

Dataset statistics

Number of variables13
Number of observations26
Missing cells33
Missing cells (%)9.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory110.1 B

Variable types

Numeric1
Text3
Categorical2
Boolean6
DateTime1

Dataset

Description전라남도 광양시에 위치한 코로나19 비대면진료 의료기관 현황입니다. 의료기관명, 주소, 연락처를 제공합니다.
URLhttps://www.data.go.kr/data/15102746/fileData.do

Alerts

호흡기환자진료 has constant value ""Constant
신속항원검사여부 has constant value ""Constant
PCR검사여부 has constant value ""Constant
코로나19치료제처방여부 has constant value ""Constant
확진자대면진료여부 has constant value ""Constant
확진자비대면진료 has constant value ""Constant
데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 의료기관구분High correlation
의료기관구분 is highly overall correlated with 연번High correlation
PCR검사여부 has 19 (73.1%) missing valuesMissing
코로나19치료제처방여부 has 7 (26.9%) missing valuesMissing
확진자대면진료여부 has 7 (26.9%) missing valuesMissing
연번 has unique valuesUnique
의료기관명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:09:12.896294
Analysis finished2023-12-12 18:09:13.620430
Duration0.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T03:09:13.679714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2023-12-13T03:09:13.793182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

의료기관명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T03:09:13.966903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length6.1538462
Min length4

Characters and Unicode

Total characters160
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row광양병원
2nd row정학민내과의원
3rd row차소아청소년과의원
4th row광양내과의원
5th row연합의원
ValueCountFrequency (%)
광양병원 1
 
3.8%
정학민내과의원 1
 
3.8%
진상의원 1
 
3.8%
연세의원 1
 
3.8%
조은의원 1
 
3.8%
장진형내과의원 1
 
3.8%
정외과의원 1
 
3.8%
미래여성의원 1
 
3.8%
나성규신경과의원 1
 
3.8%
박이비인후과의원 1
 
3.8%
Other values (16) 16
61.5%
2023-12-13T03:09:14.287100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 26
 
16.2%
의 22
 
13.8%
과 12
 
7.5%
광 6
 
3.8%
양 6
 
3.8%
소 5
 
3.1%
내 5
 
3.1%
병 4
 
2.5%
연 3
 
1.9%
아 3
 
1.9%
Other values (48) 68
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 160
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 26
 
16.2%
의 22
 
13.8%
과 12
 
7.5%
광 6
 
3.8%
양 6
 
3.8%
소 5
 
3.1%
내 5
 
3.1%
병 4
 
2.5%
연 3
 
1.9%
아 3
 
1.9%
Other values (48) 68
42.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 160
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 26
 
16.2%
의 22
 
13.8%
과 12
 
7.5%
광 6
 
3.8%
양 6
 
3.8%
소 5
 
3.1%
내 5
 
3.1%
병 4
 
2.5%
연 3
 
1.9%
아 3
 
1.9%
Other values (48) 68
42.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 160
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 26
 
16.2%
의 22
 
13.8%
과 12
 
7.5%
광 6
 
3.8%
양 6
 
3.8%
소 5
 
3.1%
내 5
 
3.1%
병 4
 
2.5%
연 3
 
1.9%
아 3
 
1.9%
Other values (48) 68
42.5%

의료기관구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
의원
22 
병원
4 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
의원 22
84.6%
병원 4
 
15.4%

Length

2023-12-13T03:09:14.411527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:09:14.509237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의원 22
84.6%
병원 4
 
15.4%

행정동
Categorical

Distinct7
Distinct (%)26.9%
Missing0
Missing (%)0.0%
Memory size340.0 B
중마동
12 
광양읍
8 
광영동
2 
태인동
 
1
금호동
 
1
Other values (2)
2 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique4 ?
Unique (%)15.4%

Sample

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

Common Values

ValueCountFrequency (%)
중마동 12
46.2%
광양읍 8
30.8%
광영동 2
 
7.7%
태인동 1
 
3.8%
금호동 1
 
3.8%
진상면 1
 
3.8%
옥곡면 1
 
3.8%

Length

2023-12-13T03:09:14.626820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:09:14.747680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중마동 12
46.2%
광양읍 8
30.8%
광영동 2
 
7.7%
태인동 1
 
3.8%
금호동 1
 
3.8%
진상면 1
 
3.8%
옥곡면 1
 
3.8%

소재지도로명주소
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T03:09:14.984651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length30
Mean length24.653846
Min length16

Characters and Unicode

Total characters641
Distinct characters69
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

Unique26 ?
Unique (%)100.0%

Sample

1st row전라남도 광양시 광양읍 인덕로 992
2nd row전라남도 광양시 광양읍 신재로 43-1, 1층
3rd row전라남도 광양시 광양읍 칠성로 55, 1층
4th row전라남도 광양시 광양읍 읍내중앙길 11, 1~2층
5th row전라남도 광양시 광양읍 읍성길 158
ValueCountFrequency (%)
전라남도 27
18.2%
광양시 26
17.6%
중동 10
 
6.8%
광양읍 8
 
5.4%
1층 5
 
3.4%
중마중앙로 5
 
3.4%
2층 4
 
2.7%
광장로 3
 
2.0%
공영로 3
 
2.0%
신재로 2
 
1.4%
Other values (54) 55
37.2%
2023-12-13T03:09:15.400710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
122
19.0%
광 40
 
6.2%
양 35
 
5.5%
1 33
 
5.1%
라 28
 
4.4%
전 27
 
4.2%
남 27
 
4.2%
도 27
 
4.2%
시 27
 
4.2%
중 22
 
3.4%
Other values (59) 253
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 376
58.7%
Space Separator 122
 
19.0%
Decimal Number 90
 
14.0%
Other Punctuation 16
 
2.5%
Open Punctuation 15
 
2.3%
Close Punctuation 15
 
2.3%
Dash Punctuation 4
 
0.6%
Math Symbol 2
 
0.3%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 40
 
10.6%
양 35
 
9.3%
라 28
 
7.4%
전 27
 
7.2%
남 27
 
7.2%
도 27
 
7.2%
시 27
 
7.2%
중 22
 
5.9%
로 22
 
5.9%
동 17
 
4.5%
Other values (42) 104
27.7%
Decimal Number
ValueCountFrequency (%)
1 33
36.7%
2 14
15.6%
7 8
 
8.9%
5 7
 
7.8%
3 6
 
6.7%
4 5
 
5.6%
8 5
 
5.6%
6 4
 
4.4%
0 4
 
4.4%
9 4
 
4.4%
Space Separator
ValueCountFrequency (%)
122
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 376
58.7%
Common 264
41.2%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 40
 
10.6%
양 35
 
9.3%
라 28
 
7.4%
전 27
 
7.2%
남 27
 
7.2%
도 27
 
7.2%
시 27
 
7.2%
중 22
 
5.9%
로 22
 
5.9%
동 17
 
4.5%
Other values (42) 104
27.7%
Common
ValueCountFrequency (%)
122
46.2%
1 33
 
12.5%
, 16
 
6.1%
( 15
 
5.7%
) 15
 
5.7%
2 14
 
5.3%
7 8
 
3.0%
5 7
 
2.7%
3 6
 
2.3%
4 5
 
1.9%
Other values (6) 23
 
8.7%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 376
58.7%
ASCII 265
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122
46.0%
1 33
 
12.5%
, 16
 
6.0%
( 15
 
5.7%
) 15
 
5.7%
2 14
 
5.3%
7 8
 
3.0%
5 7
 
2.6%
3 6
 
2.3%
4 5
 
1.9%
Other values (7) 24
 
9.1%
Hangul
ValueCountFrequency (%)
광 40
 
10.6%
양 35
 
9.3%
라 28
 
7.4%
전 27
 
7.2%
남 27
 
7.2%
도 27
 
7.2%
시 27
 
7.2%
중 22
 
5.9%
로 22
 
5.9%
동 17
 
4.5%
Other values (42) 104
27.7%

호흡기환자진료
Boolean

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size158.0 B
True
26 
ValueCountFrequency (%)
True 26
100.0%
2023-12-13T03:09:15.548561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

신속항원검사여부
Boolean

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size158.0 B
True
26 
ValueCountFrequency (%)
True 26
100.0%
2023-12-13T03:09:15.638603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

PCR검사여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)14.3%
Missing19
Missing (%)73.1%
Memory size184.0 B
True
7 
(Missing)
19 
ValueCountFrequency (%)
True 7
 
26.9%
(Missing) 19
73.1%
2023-12-13T03:09:15.722282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

코로나19치료제처방여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)5.3%
Missing7
Missing (%)26.9%
Memory size184.0 B
True
19 
(Missing)
7 
ValueCountFrequency (%)
True 19
73.1%
(Missing) 7
 
26.9%
2023-12-13T03:09:15.802767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

확진자대면진료여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)5.3%
Missing7
Missing (%)26.9%
Memory size184.0 B
True
19 
(Missing)
7 
ValueCountFrequency (%)
True 19
73.1%
(Missing) 7
 
26.9%
2023-12-13T03:09:15.888348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

확진자비대면진료
Boolean

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size158.0 B
True
26 
ValueCountFrequency (%)
True 26
100.0%
2023-12-13T03:09:15.981537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

전화번호
Text

Distinct24
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T03:09:16.152808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters312
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)84.6%

Sample

1st row061-761-7575
2nd row061-762-8338
3rd row061-763-8295
4th row061-763-4555
5th row061-762-2266
ValueCountFrequency (%)
061-762-2266 2
 
7.7%
061-793-7501 2
 
7.7%
061-761-7575 1
 
3.8%
061-793-7975 1
 
3.8%
061-772-1140 1
 
3.8%
061-799-3800 1
 
3.8%
061-793-9016 1
 
3.8%
061-794-6575 1
 
3.8%
061-791-7070 1
 
3.8%
061-791-8575 1
 
3.8%
Other values (14) 14
53.8%
2023-12-13T03:09:16.484510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 52
16.7%
7 45
14.4%
6 44
14.1%
0 43
13.8%
1 38
12.2%
9 20
 
6.4%
5 19
 
6.1%
8 17
 
5.4%
3 16
 
5.1%
2 14
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 260
83.3%
Dash Punctuation 52
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 45
17.3%
6 44
16.9%
0 43
16.5%
1 38
14.6%
9 20
7.7%
5 19
7.3%
8 17
 
6.5%
3 16
 
6.2%
2 14
 
5.4%
4 4
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 52
16.7%
7 45
14.4%
6 44
14.1%
0 43
13.8%
1 38
12.2%
9 20
 
6.4%
5 19
 
6.1%
8 17
 
5.4%
3 16
 
5.1%
2 14
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 52
16.7%
7 45
14.4%
6 44
14.1%
0 43
13.8%
1 38
12.2%
9 20
 
6.4%
5 19
 
6.1%
8 17
 
5.4%
3 16
 
5.1%
2 14
 
4.5%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum2023-07-10 00:00:00
Maximum2023-07-10 00:00:00
2023-12-13T03:09:16.617329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:09:16.710106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T03:09:13.182605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:09:16.803400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번의료기관명의료기관구분행정동소재지도로명주소전화번호
연번1.0001.0000.7960.7301.0000.955
의료기관명1.0001.0001.0001.0001.0001.000
의료기관구분0.7961.0001.0000.0001.0001.000
행정동0.7301.0000.0001.0001.0000.929
소재지도로명주소1.0001.0001.0001.0001.0001.000
전화번호0.9551.0001.0000.9291.0001.000
2023-12-13T03:09:16.930930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의료기관구분행정동
의료기관구분1.0000.000
행정동0.0001.000
2023-12-13T03:09:17.034916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번의료기관구분행정동
연번1.0000.6790.392
의료기관구분0.6791.0000.000
행정동0.3920.0001.000

Missing values

2023-12-13T03:09:13.292650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:09:13.444350image/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.
2023-12-13T03:09:13.559516image/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

연번의료기관명의료기관구분행정동소재지도로명주소호흡기환자진료신속항원검사여부PCR검사여부코로나19치료제처방여부확진자대면진료여부확진자비대면진료전화번호데이터기준일
01광양병원병원광양읍전라남도 광양시 광양읍 인덕로 992YY<NA>YYY061-761-75752023-07-10
12정학민내과의원의원광양읍전라남도 광양시 광양읍 신재로 43-1, 1층YY<NA>YYY061-762-83382023-07-10
23차소아청소년과의원의원광양읍전라남도 광양시 광양읍 칠성로 55, 1층YY<NA><NA><NA>Y061-763-82952023-07-10
34광양내과의원의원광양읍전라남도 광양시 광양읍 읍내중앙길 11, 1~2층YY<NA>YYY061-763-45552023-07-10
45연합의원의원광양읍전라남도 광양시 광양읍 읍성길 158YY<NA><NA><NA>Y061-762-22662023-07-10
56광양이비인후과의원의원광양읍전라남도 광양시 광양읍 칠성로 51, 1층YY<NA><NA><NA>Y061-763-38832023-07-10
67한솔의원의원광양읍전라남도 광양시 광양읍 숲샘길 129YY<NA>YYY061-763-66132023-07-10
78광양조은내과의원의원광양읍전라남도 광양시 광양읍 신재로 18YY<NA>YYY061-761-95882023-07-10
89광양사랑병원병원중마동전라남도 광양시 공영로 71 (중동)YYYYYY061-797-70002023-07-10
910광양서울병원병원중마동전라남도 광양시 진등길 93 (마동)YYYYYY061-798-98002023-07-10
연번의료기관명의료기관구분행정동소재지도로명주소호흡기환자진료신속항원검사여부PCR검사여부코로나19치료제처방여부확진자대면진료여부확진자비대면진료전화번호데이터기준일
1617코앤기의원의원중마동전라남도 광양시 중마중앙로 73 (중동)YY<NA>YYY061-793-75012023-07-10
1718박이비인후과의원의원중마동전라남도 광양시 중마중앙로 87-1, 2층 (중동)YY<NA>YYY061-794-68002023-07-10
1819나성규신경과의원의원중마동전라남도 광양시 중마중앙로 71-1, 1층(중동)YY<NA>YYY061-791-85752023-07-10
1920미래여성의원의원중마동전라남도 광양시 중마중앙로 142, 1~4층 (중동)YY<NA>YYY061-791-70702023-07-10
2021정외과의원의원광영동전라남도 광양시 광영로 74(광영동)YY<NA><NA><NA>Y061-762-22662023-07-10
2122장진형내과의원의원광영동전라남도 광양시 금영로 151YY<NA>YYY061-794-65752023-07-10
2223조은의원의원태인동전라남도 광양시 용지길 20 (태인동)YY<NA><NA><NA>Y061-793-90162023-07-10
2324연세의원의원금호동전라남도 광양시 백운로 1638-11, 1층 (금호동)YY<NA>YYY061-799-38002023-07-10
2425진상의원의원진상면전라남도 광양시 진상면 학연로 10, 2층YY<NA><NA><NA>Y061-772-11402023-07-10
2526늘푸른의원의원옥곡면전라남도 광양시 옥곡면 옥진로 683YY<NA>YYY061-772-82752023-07-10