Overview

Dataset statistics

Number of variables13
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory109.8 B

Variable types

Categorical5
Boolean1
Text5
Numeric2

Dataset

Description전라남도 응급의료기관에 대한 데이터로 종별, 응급의료 취약지여부, 병원명, 대표전화, 주소 등 항목을 제공합니다.
Author전라남도
URLhttps://www.data.go.kr/data/15069190/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
우편번호 is highly overall correlated with 응급의료 취약지여부 and 1 other fieldsHigh correlation
허가병상수 is highly overall correlated with 종별구분 and 2 other fieldsHigh correlation
종별구분 is highly overall correlated with 허가병상수High correlation
응급의료 취약지여부 is highly overall correlated with 우편번호 and 1 other fieldsHigh correlation
응급의료권역 is highly overall correlated with 우편번호High correlation
의료법상 병원분류 is highly overall correlated with 허가병상수High correlation
종별구분 is highly imbalanced (53.9%)Imbalance
지정일자 is highly imbalanced (81.3%)Imbalance
병원명 has unique valuesUnique
응급실 대표전화 has unique valuesUnique
응급실 팩스번호 has unique valuesUnique
세부주소 has unique valuesUnique
도로명 주소 has unique valuesUnique
우편번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:02:32.865466
Analysis finished2023-12-12 09:02:34.790582
Duration1.93 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종별구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
지역응급의료기관
30 
지역응급의료센터
 
3
권역응급의료센터
 
2

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row권역응급의료센터
2nd row권역응급의료센터
3rd row지역응급의료센터
4th row지역응급의료센터
5th row지역응급의료센터

Common Values

ValueCountFrequency (%)
지역응급의료기관 30
85.7%
지역응급의료센터 3
 
8.6%
권역응급의료센터 2
 
5.7%

Length

2023-12-12T18:02:34.860613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:02:34.994817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지역응급의료기관 30
85.7%
지역응급의료센터 3
 
8.6%
권역응급의료센터 2
 
5.7%

응급의료 취약지여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size167.0 B
True
21 
False
14 
ValueCountFrequency (%)
True 21
60.0%
False 14
40.0%
2023-12-12T18:02:35.120578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

병원명
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-12T18:02:35.348960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length10.171429
Min length4

Characters and Unicode

Total characters356
Distinct characters84
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

Unique35 ?
Unique (%)100.0%

Sample

1st row목포한국병원
2nd row성가롤로병원
3rd row화순전남대학교병원
4th row여천전남병원
5th row의료법인목포구암의료재단 목포중앙병원
ValueCountFrequency (%)
의료법인 2
 
4.4%
목포한국병원 1
 
2.2%
세안종합병원 1
 
2.2%
의료법인장호의료재단녹동현대병원 1
 
2.2%
곡성사랑병원 1
 
2.2%
구례병원 1
 
2.2%
담양사랑병원 1
 
2.2%
아산사회복지재단보성아산병원 1
 
2.2%
완도대성병원 1
 
2.2%
의료법인삼호의료재단 1
 
2.2%
Other values (34) 34
75.6%
2023-12-12T18:02:35.771760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 35
 
9.8%
병 32
 
9.0%
의 27
 
7.6%
료 27
 
7.6%
단 13
 
3.7%
재 13
 
3.7%
법 12
 
3.4%
인 12
 
3.4%
10
 
2.8%
합 7
 
2.0%
Other values (74) 168
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 346
97.2%
Space Separator 10
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 35
 
10.1%
병 32
 
9.2%
의 27
 
7.8%
료 27
 
7.8%
단 13
 
3.8%
재 13
 
3.8%
법 12
 
3.5%
인 12
 
3.5%
합 7
 
2.0%
종 7
 
2.0%
Other values (73) 161
46.5%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 346
97.2%
Common 10
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 35
 
10.1%
병 32
 
9.2%
의 27
 
7.8%
료 27
 
7.8%
단 13
 
3.8%
재 13
 
3.8%
법 12
 
3.5%
인 12
 
3.5%
합 7
 
2.0%
종 7
 
2.0%
Other values (73) 161
46.5%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 346
97.2%
ASCII 10
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 35
 
10.1%
병 32
 
9.2%
의 27
 
7.8%
료 27
 
7.8%
단 13
 
3.8%
재 13
 
3.8%
법 12
 
3.5%
인 12
 
3.5%
합 7
 
2.0%
종 7
 
2.0%
Other values (73) 161
46.5%
ASCII
ValueCountFrequency (%)
10
100.0%

지정일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
2019-01-01
34 
2021-03-30
 
1

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row2019-01-01
2nd row2019-01-01
3rd row2019-01-01
4th row2019-01-01
5th row2019-01-01

Common Values

ValueCountFrequency (%)
2019-01-01 34
97.1%
2021-03-30 1
 
2.9%

Length

2023-12-12T18:02:35.933647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:02:36.074749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-01-01 34
97.1%
2021-03-30 1
 
2.9%

응급의료권역
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
전남목포
12 
광주
12 
전남순천
11 

Length

Max length4
Median length4
Mean length3.3142857
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전남목포
2nd row전남순천
3rd row광주
4th row전남순천
5th row전남목포

Common Values

ValueCountFrequency (%)
전남목포 12
34.3%
광주 12
34.3%
전남순천 11
31.4%

Length

2023-12-12T18:02:36.255979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:02:36.415858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전남목포 12
34.3%
광주 12
34.3%
전남순천 11
31.4%

응급실 대표전화
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-12T18:02:36.667471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters420
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

Unique35 ?
Unique (%)100.0%

Sample

1st row061-270-5666
2nd row061-720-6119
3rd row061-379-8882
4th row061-690-6118
5th row061-280-3119
ValueCountFrequency (%)
061-270-5666 1
 
2.9%
061-530-0119 1
 
2.9%
061-360-6008 1
 
2.9%
061-783-9119 1
 
2.9%
061-380-9119 1
 
2.9%
061-850-3118 1
 
2.9%
061-554-9500 1
 
2.9%
061-859-5119 1
 
2.9%
061-530-7119 1
 
2.9%
061-262-3301 1
 
2.9%
Other values (25) 25
71.4%
2023-12-12T18:02:37.041512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 87
20.7%
0 75
17.9%
- 70
16.7%
6 56
13.3%
9 31
 
7.4%
8 24
 
5.7%
3 21
 
5.0%
7 17
 
4.0%
5 17
 
4.0%
2 13
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 350
83.3%
Dash Punctuation 70
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 87
24.9%
0 75
21.4%
6 56
16.0%
9 31
 
8.9%
8 24
 
6.9%
3 21
 
6.0%
7 17
 
4.9%
5 17
 
4.9%
2 13
 
3.7%
4 9
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 420
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 87
20.7%
0 75
17.9%
- 70
16.7%
6 56
13.3%
9 31
 
7.4%
8 24
 
5.7%
3 21
 
5.0%
7 17
 
4.0%
5 17
 
4.0%
2 13
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 87
20.7%
0 75
17.9%
- 70
16.7%
6 56
13.3%
9 31
 
7.4%
8 24
 
5.7%
3 21
 
5.0%
7 17
 
4.0%
5 17
 
4.0%
2 13
 
3.1%

응급실 팩스번호
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-12T18:02:37.258955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters420
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

Unique35 ?
Unique (%)100.0%

Sample

1st row061-277-0199
2nd row061-720-6000
3rd row061-379-7420
4th row061-690-6000
5th row061-280-3000
ValueCountFrequency (%)
061-277-0199 1
 
2.9%
061-536-4116 1
 
2.9%
061-360-6000 1
 
2.9%
061-780-3300 1
 
2.9%
061-380-9212 1
 
2.9%
061-850-3401 1
 
2.9%
061-553-1234 1
 
2.9%
061-859-5000 1
 
2.9%
061-530-7010 1
 
2.9%
061-262-3301 1
 
2.9%
Other values (25) 25
71.4%
2023-12-12T18:02:37.613695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 98
23.3%
- 70
16.7%
1 59
14.0%
6 54
12.9%
3 29
 
6.9%
2 25
 
6.0%
7 21
 
5.0%
5 19
 
4.5%
9 16
 
3.8%
8 15
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 350
83.3%
Dash Punctuation 70
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 98
28.0%
1 59
16.9%
6 54
15.4%
3 29
 
8.3%
2 25
 
7.1%
7 21
 
6.0%
5 19
 
5.4%
9 16
 
4.6%
8 15
 
4.3%
4 14
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 420
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 98
23.3%
- 70
16.7%
1 59
14.0%
6 54
12.9%
3 29
 
6.9%
2 25
 
6.0%
7 21
 
5.0%
5 19
 
4.5%
9 16
 
3.8%
8 15
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 420
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 98
23.3%
- 70
16.7%
1 59
14.0%
6 54
12.9%
3 29
 
6.9%
2 25
 
6.0%
7 21
 
5.0%
5 19
 
4.5%
9 16
 
3.8%
8 15
 
3.6%

세부주소
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-12T18:02:37.965160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length20.885714
Min length15

Characters and Unicode

Total characters731
Distinct characters114
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row전라남도 목포시 영산로 483 (상동)
2nd row전라남도 순천시 순광로 221 (조례동)
3rd row전라남도 화순군 화순읍 서양로 322
4th row전라남도 여수시 무선로 95, (선원동)
5th row전라남도 목포시 영산로 627 (석현동)
ValueCountFrequency (%)
전라남도 35
 
20.0%
목포시 5
 
2.9%
순천시 4
 
2.3%
영산로 3
 
1.7%
여수시 3
 
1.7%
보성군 2
 
1.1%
조례동 2
 
1.1%
해남군 2
 
1.1%
해남로 2
 
1.1%
영광군 2
 
1.1%
Other values (108) 115
65.7%
2023-12-12T18:02:38.440650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
140
19.2%
남 44
 
6.0%
도 41
 
5.6%
전 37
 
5.1%
라 35
 
4.8%
로 26
 
3.6%
군 21
 
2.9%
읍 18
 
2.5%
1 16
 
2.2%
동 15
 
2.1%
Other values (104) 338
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 468
64.0%
Space Separator 140
 
19.2%
Decimal Number 87
 
11.9%
Open Punctuation 13
 
1.8%
Close Punctuation 13
 
1.8%
Other Punctuation 7
 
1.0%
Dash Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 44
 
9.4%
도 41
 
8.8%
전 37
 
7.9%
라 35
 
7.5%
로 26
 
5.6%
군 21
 
4.5%
읍 18
 
3.8%
동 15
 
3.2%
시 14
 
3.0%
영 11
 
2.4%
Other values (89) 206
44.0%
Decimal Number
ValueCountFrequency (%)
1 16
18.4%
5 12
13.8%
2 11
12.6%
3 10
11.5%
7 10
11.5%
4 8
9.2%
9 7
8.0%
6 6
 
6.9%
8 5
 
5.7%
0 2
 
2.3%
Space Separator
ValueCountFrequency (%)
140
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 468
64.0%
Common 263
36.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 44
 
9.4%
도 41
 
8.8%
전 37
 
7.9%
라 35
 
7.5%
로 26
 
5.6%
군 21
 
4.5%
읍 18
 
3.8%
동 15
 
3.2%
시 14
 
3.0%
영 11
 
2.4%
Other values (89) 206
44.0%
Common
ValueCountFrequency (%)
140
53.2%
1 16
 
6.1%
( 13
 
4.9%
) 13
 
4.9%
5 12
 
4.6%
2 11
 
4.2%
3 10
 
3.8%
7 10
 
3.8%
4 8
 
3.0%
, 7
 
2.7%
Other values (5) 23
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 468
64.0%
ASCII 263
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
140
53.2%
1 16
 
6.1%
( 13
 
4.9%
) 13
 
4.9%
5 12
 
4.6%
2 11
 
4.2%
3 10
 
3.8%
7 10
 
3.8%
4 8
 
3.0%
, 7
 
2.7%
Other values (5) 23
 
8.7%
Hangul
ValueCountFrequency (%)
남 44
 
9.4%
도 41
 
8.8%
전 37
 
7.9%
라 35
 
7.5%
로 26
 
5.6%
군 21
 
4.5%
읍 18
 
3.8%
동 15
 
3.2%
시 14
 
3.0%
영 11
 
2.4%
Other values (89) 206
44.0%

도로명 주소
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-12-12T18:02:38.745134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length20.885714
Min length15

Characters and Unicode

Total characters731
Distinct characters114
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)100.0%

Sample

1st row전라남도 목포시 영산로 483 (상동)
2nd row전라남도 순천시 순광로 221 (조례동)
3rd row전라남도 화순군 화순읍 서양로 322
4th row전라남도 여수시 무선로 96, (선원동)
5th row전라남도 목포시 영산로 628 (석현동)
ValueCountFrequency (%)
전라남도 35
 
20.0%
목포시 5
 
2.9%
순천시 4
 
2.3%
영산로 3
 
1.7%
여수시 3
 
1.7%
보성군 2
 
1.1%
조례동 2
 
1.1%
해남군 2
 
1.1%
해남로 2
 
1.1%
영광군 2
 
1.1%
Other values (108) 115
65.7%
2023-12-12T18:02:39.285345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
140
19.2%
남 44
 
6.0%
도 41
 
5.6%
전 37
 
5.1%
라 35
 
4.8%
로 26
 
3.6%
군 21
 
2.9%
읍 18
 
2.5%
1 16
 
2.2%
동 15
 
2.1%
Other values (104) 338
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 468
64.0%
Space Separator 140
 
19.2%
Decimal Number 87
 
11.9%
Open Punctuation 13
 
1.8%
Close Punctuation 13
 
1.8%
Other Punctuation 7
 
1.0%
Dash Punctuation 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 44
 
9.4%
도 41
 
8.8%
전 37
 
7.9%
라 35
 
7.5%
로 26
 
5.6%
군 21
 
4.5%
읍 18
 
3.8%
동 15
 
3.2%
시 14
 
3.0%
영 11
 
2.4%
Other values (89) 206
44.0%
Decimal Number
ValueCountFrequency (%)
1 16
18.4%
2 11
12.6%
5 11
12.6%
3 10
11.5%
7 9
10.3%
4 8
9.2%
9 7
8.0%
6 7
8.0%
8 6
 
6.9%
0 2
 
2.3%
Space Separator
ValueCountFrequency (%)
140
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 468
64.0%
Common 263
36.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 44
 
9.4%
도 41
 
8.8%
전 37
 
7.9%
라 35
 
7.5%
로 26
 
5.6%
군 21
 
4.5%
읍 18
 
3.8%
동 15
 
3.2%
시 14
 
3.0%
영 11
 
2.4%
Other values (89) 206
44.0%
Common
ValueCountFrequency (%)
140
53.2%
1 16
 
6.1%
( 13
 
4.9%
) 13
 
4.9%
2 11
 
4.2%
5 11
 
4.2%
3 10
 
3.8%
7 9
 
3.4%
4 8
 
3.0%
, 7
 
2.7%
Other values (5) 25
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 468
64.0%
ASCII 263
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
140
53.2%
1 16
 
6.1%
( 13
 
4.9%
) 13
 
4.9%
2 11
 
4.2%
5 11
 
4.2%
3 10
 
3.8%
7 9
 
3.4%
4 8
 
3.0%
, 7
 
2.7%
Other values (5) 25
 
9.5%
Hangul
ValueCountFrequency (%)
남 44
 
9.4%
도 41
 
8.8%
전 37
 
7.9%
라 35
 
7.5%
로 26
 
5.6%
군 21
 
4.5%
읍 18
 
3.8%
동 15
 
3.2%
시 14
 
3.0%
영 11
 
2.4%
Other values (89) 206
44.0%

우편번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58568.2
Minimum57035
Maximum59718
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:02:39.490977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum57035
5-th percentile57167.2
Q157954
median58655
Q359275.5
95-th percentile59673.5
Maximum59718
Range2683
Interquartile range (IQR)1321.5

Descriptive statistics

Standard deviation805.02349
Coefficient of variation (CV)0.013745061
Kurtosis-0.94158871
Mean58568.2
Median Absolute Deviation (MAD)670
Skewness-0.3501365
Sum2049887
Variance648062.81
MonotonicityNot monotonic
2023-12-12T18:02:39.631580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
58643 1
 
2.9%
57931 1
 
2.9%
57540 1
 
2.9%
57645 1
 
2.9%
57343 1
 
2.9%
59443 1
 
2.9%
59109 1
 
2.9%
59431 1
 
2.9%
58847 1
 
2.9%
59552 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
57035 1
2.9%
57044 1
2.9%
57220 1
2.9%
57343 1
2.9%
57540 1
2.9%
57645 1
2.9%
57788 1
2.9%
57931 1
2.9%
57940 1
2.9%
57968 1
2.9%
ValueCountFrequency (%)
59718 1
2.9%
59677 1
2.9%
59672 1
2.9%
59552 1
2.9%
59535 1
2.9%
59443 1
2.9%
59431 1
2.9%
59325 1
2.9%
59324 1
2.9%
59227 1
2.9%

의료법상 병원분류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size412.0 B
종합병원
19 
병원
15 
상급종합병원
 
1

Length

Max length6
Median length4
Mean length3.2
Min length2

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row종합병원
2nd row종합병원
3rd row상급종합병원
4th row종합병원
5th row종합병원

Common Values

ValueCountFrequency (%)
종합병원 19
54.3%
병원 15
42.9%
상급종합병원 1
 
2.9%

Length

2023-12-12T18:02:39.819696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:02:40.057077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종합병원 19
54.3%
병원 15
42.9%
상급종합병원 1
 
2.9%

허가병상수
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean268.2
Minimum30
Maximum684
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2023-12-12T18:02:40.230268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile70.7
Q1147.5
median282
Q3354.5
95-th percentile568.5
Maximum684
Range654
Interquartile range (IQR)207

Descriptive statistics

Standard deviation159.40548
Coefficient of variation (CV)0.59435301
Kurtosis0.15930608
Mean268.2
Median Absolute Deviation (MAD)106
Skewness0.73221462
Sum9387
Variance25410.106
MonotonicityNot monotonic
2023-12-12T18:02:40.423354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
299 2
 
5.7%
163 2
 
5.7%
298 2
 
5.7%
572 1
 
2.9%
30 1
 
2.9%
97 1
 
2.9%
86 1
 
2.9%
103 1
 
2.9%
120 1
 
2.9%
352 1
 
2.9%
Other values (22) 22
62.9%
ValueCountFrequency (%)
30 1
2.9%
35 1
2.9%
86 1
2.9%
97 1
2.9%
100 1
2.9%
103 1
2.9%
118 1
2.9%
120 1
2.9%
132 1
2.9%
163 2
5.7%
ValueCountFrequency (%)
684 1
2.9%
572 1
2.9%
567 1
2.9%
496 1
2.9%
458 1
2.9%
452 1
2.9%
382 1
2.9%
370 1
2.9%
357 1
2.9%
352 1
2.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
2023-08-10
35 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-10
2nd row2023-08-10
3rd row2023-08-10
4th row2023-08-10
5th row2023-08-10

Common Values

ValueCountFrequency (%)
2023-08-10 35
100.0%

Length

2023-12-12T18:02:40.664266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:02:40.853643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-10 35
100.0%

Interactions

2023-12-12T18:02:33.891098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:33.669068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:34.021451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:02:33.774768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:02:40.958714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종별구분응급의료 취약지여부병원명지정일자응급의료권역응급실 대표전화응급실 팩스번호세부주소도로명 주소우편번호의료법상 병원분류허가병상수
종별구분1.0000.2791.0000.0000.0001.0001.0001.0001.0000.0000.7350.877
응급의료 취약지여부0.2791.0001.0000.0000.3041.0001.0001.0001.0000.7500.2730.790
병원명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
지정일자0.0000.0001.0001.0000.0001.0001.0001.0001.0000.0000.0000.000
응급의료권역0.0000.3041.0000.0001.0001.0001.0001.0001.0001.0000.2510.529
응급실 대표전화1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
응급실 팩스번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
세부주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명 주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
우편번호0.0000.7501.0000.0001.0001.0001.0001.0001.0001.0000.5020.508
의료법상 병원분류0.7350.2731.0000.0000.2511.0001.0001.0001.0000.5021.0000.881
허가병상수0.8770.7901.0000.0000.5291.0001.0001.0001.0000.5080.8811.000
2023-12-12T18:02:41.220213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
응급의료 취약지여부지정일자응급의료권역의료법상 병원분류종별구분
응급의료 취약지여부1.0000.0000.4820.4350.444
지정일자0.0001.0000.0000.0000.000
응급의료권역0.4820.0001.0000.0700.000
의료법상 병원분류0.4350.0000.0701.0000.390
종별구분0.4440.0000.0000.3901.000
2023-12-12T18:02:41.410263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호허가병상수종별구분응급의료 취약지여부지정일자응급의료권역의료법상 병원분류
우편번호1.0000.1170.0000.5230.0000.8840.308
허가병상수0.1171.0000.7170.5390.0000.3200.722
종별구분0.0000.7171.0000.4440.0000.0000.390
응급의료 취약지여부0.5230.5390.4441.0000.0000.4820.435
지정일자0.0000.0000.0000.0001.0000.0000.000
응급의료권역0.8840.3200.0000.4820.0001.0000.070
의료법상 병원분류0.3080.7220.3900.4350.0000.0701.000

Missing values

2023-12-12T18:02:34.501879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:02:34.716575image/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

종별구분응급의료 취약지여부병원명지정일자응급의료권역응급실 대표전화응급실 팩스번호세부주소도로명 주소우편번호의료법상 병원분류허가병상수데이터기준일자
0권역응급의료센터N목포한국병원2019-01-01전남목포061-270-5666061-277-0199전라남도 목포시 영산로 483 (상동)전라남도 목포시 영산로 483 (상동)58643종합병원5722023-08-10
1권역응급의료센터N성가롤로병원2019-01-01전남순천061-720-6119061-720-6000전라남도 순천시 순광로 221 (조례동)전라남도 순천시 순광로 221 (조례동)57931종합병원5672023-08-10
2지역응급의료센터N화순전남대학교병원2019-01-01광주061-379-8882061-379-7420전라남도 화순군 화순읍 서양로 322전라남도 화순군 화순읍 서양로 32258128상급종합병원6842023-08-10
3지역응급의료센터N여천전남병원2019-01-01전남순천061-690-6118061-690-6000전라남도 여수시 무선로 95, (선원동)전라남도 여수시 무선로 96, (선원동)59672종합병원2992023-08-10
4지역응급의료센터N의료법인목포구암의료재단 목포중앙병원2019-01-01전남목포061-280-3119061-280-3000전라남도 목포시 영산로 627 (석현동)전라남도 목포시 영산로 628 (석현동)58655종합병원4582023-08-10
5지역응급의료기관N광양사랑병원2019-01-01전남순천061-797-7119061-797-7000전라남도 광양시 공영로 71 (중동)전라남도 광양시 공영로 71 (중동)57788종합병원1632023-08-10
6지역응급의료기관Y나주종합병원2019-01-01광주061-330-6112061-330-6114전라남도 나주시 영산로 5419 (성북동)전라남도 나주시 영산로 5419 (성북동)58251종합병원1762023-08-10
7지역응급의료기관Y대송의료재단무안병원2019-01-01전남목포061-450-3119061-450-3111전라남도 무안군 무안읍 몽탄로 65전라남도 무안군 무안읍 몽탄로 6558531종합병원2982023-08-10
8지역응급의료기관N목포기독병원2019-01-01전남목포061-280-7119061-280-7500전라남도 목포시 백년대로 303 (상동)전라남도 목포시 백년대로 303 (상동)58666종합병원3572023-08-10
9지역응급의료기관N목포시의료원2019-01-01전남목포061-260-6400061-279-3242전라남도 목포시 이로로 18전라남도 목포시 이로로 1858701종합병원2992023-08-10
종별구분응급의료 취약지여부병원명지정일자응급의료권역응급실 대표전화응급실 팩스번호세부주소도로명 주소우편번호의료법상 병원분류허가병상수데이터기준일자
25지역응급의료기관Y의료법인삼호의료재단 삼호병원2019-01-01광주061-859-5119061-859-5000전라남도 보성군 벌교읍 남하로 12,전라남도 보성군 벌교읍 남하로 12,59431병원3522023-08-10
26지역응급의료기관Y의료법인신안대우병원2019-01-01전남목포061-262-3301061-262-3301전라남도 신안군 비금면 송치길 155-11전라남도 신안군 비금면 송치길 155-1158847병원302023-08-10
27지역응급의료기관Y의료법인장호의료재단녹동현대병원2019-01-01전남순천061-840-1119061-840-1200전라남도 고흥군 도양읍 차경구렁목길 215,전라남도 고흥군 도양읍 차경구렁목길 215,59552병원1182023-08-10
28지역응급의료기관N의료법인한마음의료재단여수제일병원2019-01-01전남순천061-689-8118061-689-8123전라남도 여수시 쌍봉로 70 (학동)전라남도 여수시 쌍봉로 70 (학동)59677병원4522023-08-10
29지역응급의료기관Y의료법인행복나눔의료재단 장성병원2019-01-01광주061-390-9119061-390-9299전라남도 장성군 장성읍 역전로 171전라남도 장성군 장성읍 역전로 17157220병원1632023-08-10
30지역응급의료기관Y장흥우리병원2019-01-01광주061-860-0119061-862-6262전라남도 장흥군 장흥읍 흥성로 83전라남도 장흥군 장흥읍 흥성로 8359324병원1322023-08-10
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