Overview

Dataset statistics

Number of variables6
Number of observations65
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory51.0 B

Variable types

Numeric1
Text4
Categorical1

Dataset

Description전북특별자치도 김제시 병의원(병원/한의원/치과) 현황입니다.의료기관명, 도로명주소, 전화번호와 팩스번호, 층수를 포함하고 있습니다.
Author전북특별자치도 김제시
URLhttps://www.data.go.kr/data/3068570/fileData.do

Alerts

순번 is highly overall correlated with 층수High correlation
층수 is highly overall correlated with 순번High correlation
층수 is highly imbalanced (68.2%)Imbalance
순번 has unique valuesUnique
의료기관명 has unique valuesUnique

Reproduction

Analysis started2024-03-23 05:42:24.607685
Analysis finished2024-03-23 05:42:27.984185
Duration3.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33
Minimum1
Maximum65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2024-03-23T05:42:28.263584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.2
Q117
median33
Q349
95-th percentile61.8
Maximum65
Range64
Interquartile range (IQR)32

Descriptive statistics

Standard deviation18.90767
Coefficient of variation (CV)0.57295971
Kurtosis-1.2
Mean33
Median Absolute Deviation (MAD)16
Skewness0
Sum2145
Variance357.5
MonotonicityStrictly increasing
2024-03-23T05:42:28.813976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
50 1
 
1.5%
36 1
 
1.5%
37 1
 
1.5%
38 1
 
1.5%
39 1
 
1.5%
40 1
 
1.5%
41 1
 
1.5%
42 1
 
1.5%
43 1
 
1.5%
Other values (55) 55
84.6%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%
58 1
1.5%
57 1
1.5%
56 1
1.5%

의료기관명
Text

UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size652.0 B
2024-03-23T05:42:29.432360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length7.9384615
Min length3

Characters and Unicode

Total characters516
Distinct characters128
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)100.0%

Sample

1st row(의)백상의료재단 가족사랑요양병원
2nd row믿음병원
3rd row김제병원
4th row의료법인 명지원의료재단김제중앙병원
5th row효드림요양병원
ValueCountFrequency (%)
의)백상의료재단 1
 
1.4%
참좋은내과의원 1
 
1.4%
금산제일의원 1
 
1.4%
나방주내과의원 1
 
1.4%
한양의원 1
 
1.4%
우리정형외과의원 1
 
1.4%
원평연합의원 1
 
1.4%
튼튼가정의학과의원 1
 
1.4%
우리들마취통증의학과의원 1
 
1.4%
한사랑산부인과의원 1
 
1.4%
Other values (60) 60
85.7%
2024-03-23T05:42:30.520657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
의 69
 
13.4%
원 67
 
13.0%
과 40
 
7.8%
김 13
 
2.5%
병 12
 
2.3%
제 12
 
2.3%
한 11
 
2.1%
정 9
 
1.7%
학 8
 
1.6%
내 8
 
1.6%
Other values (118) 267
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 507
98.3%
Space Separator 5
 
1.0%
Open Punctuation 2
 
0.4%
Close Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 69
 
13.6%
원 67
 
13.2%
과 40
 
7.9%
김 13
 
2.6%
병 12
 
2.4%
제 12
 
2.4%
한 11
 
2.2%
정 9
 
1.8%
학 8
 
1.6%
내 8
 
1.6%
Other values (115) 258
50.9%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 507
98.3%
Common 9
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 69
 
13.6%
원 67
 
13.2%
과 40
 
7.9%
김 13
 
2.6%
병 12
 
2.4%
제 12
 
2.4%
한 11
 
2.2%
정 9
 
1.8%
학 8
 
1.6%
내 8
 
1.6%
Other values (115) 258
50.9%
Common
ValueCountFrequency (%)
5
55.6%
( 2
 
22.2%
) 2
 
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 507
98.3%
ASCII 9
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
의 69
 
13.6%
원 67
 
13.2%
과 40
 
7.9%
김 13
 
2.6%
병 12
 
2.4%
제 12
 
2.4%
한 11
 
2.2%
정 9
 
1.8%
학 8
 
1.6%
내 8
 
1.6%
Other values (115) 258
50.9%
ASCII
ValueCountFrequency (%)
5
55.6%
( 2
 
22.2%
) 2
 
22.2%

의료기관주소(도로명)
Text

Distinct59
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size652.0 B
2024-03-23T05:42:31.215985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length17.415385
Min length14

Characters and Unicode

Total characters1132
Distinct characters68
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

Unique53 ?
Unique (%)81.5%

Sample

1st row김제시 하동1길 13 (하동)
2nd row김제시 금성로 90-0 (신풍동)
3rd row김제시 중앙로 55 (서암동)
4th row김제시 동서로 77 (교동)
5th row김제시 화동길 135 (신풍동)
ValueCountFrequency (%)
김제시 65
24.2%
요촌동 35
 
13.0%
동서로 13
 
4.8%
남북로 12
 
4.5%
중앙로 9
 
3.3%
검산동 5
 
1.9%
금산면 5
 
1.9%
금구면 4
 
1.5%
신풍동 4
 
1.5%
225 4
 
1.5%
Other values (85) 113
42.0%
2024-03-23T05:42:32.395664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
204
18.0%
동 71
 
6.3%
김 65
 
5.7%
시 65
 
5.7%
제 65
 
5.7%
( 53
 
4.7%
) 53
 
4.7%
로 46
 
4.1%
1 43
 
3.8%
2 41
 
3.6%
Other values (58) 426
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 612
54.1%
Space Separator 204
 
18.0%
Decimal Number 195
 
17.2%
Open Punctuation 53
 
4.7%
Close Punctuation 53
 
4.7%
Other Punctuation 9
 
0.8%
Dash Punctuation 6
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 71
11.6%
김 65
 
10.6%
시 65
 
10.6%
제 65
 
10.6%
로 46
 
7.5%
요 36
 
5.9%
촌 36
 
5.9%
서 21
 
3.4%
길 19
 
3.1%
산 16
 
2.6%
Other values (43) 172
28.1%
Decimal Number
ValueCountFrequency (%)
1 43
22.1%
2 41
21.0%
5 24
12.3%
6 16
 
8.2%
3 16
 
8.2%
0 14
 
7.2%
4 12
 
6.2%
7 11
 
5.6%
9 11
 
5.6%
8 7
 
3.6%
Space Separator
ValueCountFrequency (%)
204
100.0%
Open Punctuation
ValueCountFrequency (%)
( 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 612
54.1%
Common 520
45.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 71
11.6%
김 65
 
10.6%
시 65
 
10.6%
제 65
 
10.6%
로 46
 
7.5%
요 36
 
5.9%
촌 36
 
5.9%
서 21
 
3.4%
길 19
 
3.1%
산 16
 
2.6%
Other values (43) 172
28.1%
Common
ValueCountFrequency (%)
204
39.2%
( 53
 
10.2%
) 53
 
10.2%
1 43
 
8.3%
2 41
 
7.9%
5 24
 
4.6%
6 16
 
3.1%
3 16
 
3.1%
0 14
 
2.7%
4 12
 
2.3%
Other values (5) 44
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 612
54.1%
ASCII 520
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
204
39.2%
( 53
 
10.2%
) 53
 
10.2%
1 43
 
8.3%
2 41
 
7.9%
5 24
 
4.6%
6 16
 
3.1%
3 16
 
3.1%
0 14
 
2.7%
4 12
 
2.3%
Other values (5) 44
 
8.5%
Hangul
ValueCountFrequency (%)
동 71
11.6%
김 65
 
10.6%
시 65
 
10.6%
제 65
 
10.6%
로 46
 
7.5%
요 36
 
5.9%
촌 36
 
5.9%
서 21
 
3.4%
길 19
 
3.1%
산 16
 
2.6%
Other values (43) 172
28.1%

의료기관전화번호
Text

Distinct64
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
2024-03-23T05:42:33.275923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.015385
Min length11

Characters and Unicode

Total characters781
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)96.9%

Sample

1st row063-540-1500
2nd row063543-5119
3rd row063-770-8275
4th row063-547-9999
5th row063-547-5000
ValueCountFrequency (%)
063-545-8275 2
 
3.0%
063-545-3769 1
 
1.5%
063-542-4117 1
 
1.5%
063-542-7575 1
 
1.5%
063-546-3322 1
 
1.5%
063-545-0026 1
 
1.5%
063-544-7515 1
 
1.5%
063-544-1675 1
 
1.5%
063-544-5900 1
 
1.5%
063-544-9336 1
 
1.5%
Other values (55) 55
83.3%
2024-03-23T05:42:34.736347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 129
16.5%
0 123
15.7%
5 114
14.6%
3 89
11.4%
4 86
11.0%
6 78
10.0%
7 47
 
6.0%
8 39
 
5.0%
1 28
 
3.6%
2 25
 
3.2%
Other values (2) 23
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 651
83.4%
Dash Punctuation 129
 
16.5%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 123
18.9%
5 114
17.5%
3 89
13.7%
4 86
13.2%
6 78
12.0%
7 47
 
7.2%
8 39
 
6.0%
1 28
 
4.3%
2 25
 
3.8%
9 22
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 129
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 781
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 129
16.5%
0 123
15.7%
5 114
14.6%
3 89
11.4%
4 86
11.0%
6 78
10.0%
7 47
 
6.0%
8 39
 
5.0%
1 28
 
3.6%
2 25
 
3.2%
Other values (2) 23
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 781
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 129
16.5%
0 123
15.7%
5 114
14.6%
3 89
11.4%
4 86
11.0%
6 78
10.0%
7 47
 
6.0%
8 39
 
5.0%
1 28
 
3.6%
2 25
 
3.2%
Other values (2) 23
 
2.9%

의료기관팩스번호
Text

Distinct54
Distinct (%)83.1%
Missing0
Missing (%)0.0%
Memory size652.0 B
2024-03-23T05:42:35.392741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.292308
Min length2

Characters and Unicode

Total characters669
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)80.0%

Sample

1st row063-540-1510
2nd row063543-5122
3rd row063-770-8276
4th row없음
5th row없음
ValueCountFrequency (%)
없음 11
 
16.9%
063-545-7337 2
 
3.1%
063-548-0071 1
 
1.5%
063-546-1113 1
 
1.5%
063-540-1510 1
 
1.5%
063-542-4118 1
 
1.5%
063-546-7515 1
 
1.5%
063-545-1675 1
 
1.5%
063-542-3003 1
 
1.5%
063-544-1355 1
 
1.5%
Other values (44) 44
67.7%
2024-03-23T05:42:36.422345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 107
16.0%
5 93
13.9%
0 91
13.6%
3 82
12.3%
6 77
11.5%
4 67
10.0%
7 36
 
5.4%
2 34
 
5.1%
1 26
 
3.9%
8 19
 
2.8%
Other values (3) 37
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 540
80.7%
Dash Punctuation 107
 
16.0%
Other Letter 22
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 93
17.2%
0 91
16.9%
3 82
15.2%
6 77
14.3%
4 67
12.4%
7 36
 
6.7%
2 34
 
6.3%
1 26
 
4.8%
8 19
 
3.5%
9 15
 
2.8%
Other Letter
ValueCountFrequency (%)
없 11
50.0%
음 11
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 107
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 647
96.7%
Hangul 22
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 107
16.5%
5 93
14.4%
0 91
14.1%
3 82
12.7%
6 77
11.9%
4 67
10.4%
7 36
 
5.6%
2 34
 
5.3%
1 26
 
4.0%
8 19
 
2.9%
Hangul
ValueCountFrequency (%)
없 11
50.0%
음 11
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 647
96.7%
Hangul 22
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 107
16.5%
5 93
14.4%
0 91
14.1%
3 82
12.7%
6 77
11.9%
4 67
10.4%
7 36
 
5.6%
2 34
 
5.3%
1 26
 
4.0%
8 19
 
2.9%
Hangul
ValueCountFrequency (%)
없 11
50.0%
음 11
50.0%

층수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size652.0 B
5층이하
59 
5
 
5
6
 
1

Length

Max length4
Median length4
Mean length3.7230769
Min length1

Unique

Unique1 ?
Unique (%)1.5%

Sample

1st row6
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5층이하 59
90.8%
5 5
 
7.7%
6 1
 
1.5%

Length

2024-03-23T05:42:37.067827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T05:42:37.528974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5층이하 59
90.8%
5 5
 
7.7%
6 1
 
1.5%

Interactions

2024-03-23T05:42:26.461553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T05:42:37.872068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번의료기관명의료기관주소(도로명)의료기관전화번호의료기관팩스번호층수
순번1.0001.0000.8361.0000.7990.713
의료기관명1.0001.0001.0001.0001.0001.000
의료기관주소(도로명)0.8361.0001.0001.0000.9230.892
의료기관전화번호1.0001.0001.0001.0001.0001.000
의료기관팩스번호0.7991.0000.9231.0001.0000.388
층수0.7131.0000.8921.0000.3881.000
2024-03-23T05:42:38.258507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번층수
순번1.0000.538
층수0.5381.000

Missing values

2024-03-23T05:42:27.046570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T05:42:27.736910image/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

순번의료기관명의료기관주소(도로명)의료기관전화번호의료기관팩스번호층수
01(의)백상의료재단 가족사랑요양병원김제시 하동1길 13 (하동)063-540-1500063-540-15106
12믿음병원김제시 금성로 90-0 (신풍동)063543-5119063543-51225
23김제병원김제시 중앙로 55 (서암동)063-770-8275063-770-82765
34의료법인 명지원의료재단김제중앙병원김제시 동서로 77 (교동)063-547-9999없음5
45효드림요양병원김제시 화동길 135 (신풍동)063-547-5000없음5
56의료법인지석의료재단효병원김제시 금산면 구성5길 84-15070-4035-8712063-545-87025
67김제우석병원김제시 서암4길 45 (서암동)063-540-5114063-540-51045층이하
78미래요양병원김제시 금구면 낙산1길 72063-540-8899063-545-15725층이하
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910(의)혜민의료재단 우리한방병원김제시 중앙로 209 (신풍동)063-545-5511063-545-55225층이하
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5556한마음안과의원김제시 동서로 151-1 (요촌동)063-543-4488063-547-13305층이하
5657차영범비뇨기과의원김제시 동서로 151 (요촌동)063-547-0781없음5층이하
5758서지석이비인후과의원김제시 동서로 134-1 (요촌동)063-542-8888없음5층이하
5859조용거소아청소년과의원김제시 도작로 62 (검산동)063-542-9933063-542-99325층이하
5960이명철정형외과의원김제시 동서로 125 (옥산동)063-544-8083063-540-20545층이하
6061김종범소아청소년과의원김제시 동서로 149 (요촌동)063-542-0667063-542-06635층이하
6162비타민금구의원김제시 금구면 봉두로 91(금구면)063-548-7525063-548-75265층이하
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