Overview

Dataset statistics

Number of variables5
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory43.5 B

Variable types

Numeric1
Text2
Categorical2

Dataset

Description인천광역시 중구 관내에 위치한 예방접종 위탁의료기관 현황에 대한 데이터 입니다.파일명 인천광역시_중구_예방접종 위탁의료기관 현황파일내용 의료기관명, 전화번호, 행정동 등
Author인천광역시 중구
URLhttps://www.data.go.kr/data/15086300/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
의료기관명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:19:16.381441
Analysis finished2023-12-12 21:19:16.889765
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.5
Minimum1
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-13T06:19:16.975592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.55
Q113.75
median26.5
Q339.25
95-th percentile49.45
Maximum52
Range51
Interquartile range (IQR)25.5

Descriptive statistics

Standard deviation15.154757
Coefficient of variation (CV)0.57187763
Kurtosis-1.2
Mean26.5
Median Absolute Deviation (MAD)13
Skewness0
Sum1378
Variance229.66667
MonotonicityStrictly increasing
2023-12-13T06:19:17.147784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
28 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (42) 42
80.8%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%
43 1
1.9%

의료기관명
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-13T06:19:17.405160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length8.3461538
Min length4

Characters and Unicode

Total characters434
Distinct characters119
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row아이본산부인과의원
2nd row예지요양병원
3rd row인천삼성요양병원
4th row성모연합의원
5th row신포김내과의원
ValueCountFrequency (%)
아이본산부인과의원 1
 
1.7%
성세의료재단 1
 
1.7%
영종바른이비인후과의원 1
 
1.7%
열린이비인후과의원 1
 
1.7%
인천웰빙내과의원 1
 
1.7%
로하스의원 1
 
1.7%
맑은하늘이비인후과의원 1
 
1.7%
비앤씨의원 1
 
1.7%
서울연합의원 1
 
1.7%
성모엘의원 1
 
1.7%
Other values (48) 48
82.8%
2023-12-13T06:19:17.783424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 52
 
12.0%
의 47
 
10.8%
과 31
 
7.1%
인 17
 
3.9%
소 12
 
2.8%
이 11
 
2.5%
내 9
 
2.1%
병 9
 
2.1%
아 8
 
1.8%
비 8
 
1.8%
Other values (109) 230
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 423
97.5%
Space Separator 6
 
1.4%
Decimal Number 3
 
0.7%
Uppercase Letter 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 52
 
12.3%
의 47
 
11.1%
과 31
 
7.3%
인 17
 
4.0%
소 12
 
2.8%
이 11
 
2.6%
내 9
 
2.1%
병 9
 
2.1%
아 8
 
1.9%
비 8
 
1.9%
Other values (103) 219
51.8%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
6 1
33.3%
5 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
E 1
50.0%
M 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 423
97.5%
Common 9
 
2.1%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 52
 
12.3%
의 47
 
11.1%
과 31
 
7.3%
인 17
 
4.0%
소 12
 
2.8%
이 11
 
2.6%
내 9
 
2.1%
병 9
 
2.1%
아 8
 
1.9%
비 8
 
1.9%
Other values (103) 219
51.8%
Common
ValueCountFrequency (%)
6
66.7%
3 1
 
11.1%
6 1
 
11.1%
5 1
 
11.1%
Latin
ValueCountFrequency (%)
E 1
50.0%
M 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 423
97.5%
ASCII 11
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 52
 
12.3%
의 47
 
11.1%
과 31
 
7.3%
인 17
 
4.0%
소 12
 
2.8%
이 11
 
2.6%
내 9
 
2.1%
병 9
 
2.1%
아 8
 
1.9%
비 8
 
1.9%
Other values (103) 219
51.8%
ASCII
ValueCountFrequency (%)
6
54.5%
E 1
 
9.1%
3 1
 
9.1%
6 1
 
9.1%
5 1
 
9.1%
M 1
 
9.1%

전화번호
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-13T06:19:18.036386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters624
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

Unique52 ?
Unique (%)100.0%

Sample

1st row032-772-7474
2nd row032-773-6035
3rd row032-721-7575
4th row032-710-4474
5th row032-777-0902
ValueCountFrequency (%)
032-772-7474 1
 
1.9%
032-773-6035 1
 
1.9%
032-751-5075 1
 
1.9%
032-765-7510 1
 
1.9%
032-764-3800 1
 
1.9%
032-715-6977 1
 
1.9%
032-746-1017 1
 
1.9%
032-752-8800 1
 
1.9%
032-746-7740 1
 
1.9%
032-721-5075 1
 
1.9%
Other values (42) 42
80.8%
2023-12-13T06:19:18.417332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 104
16.7%
0 94
15.1%
7 91
14.6%
2 84
13.5%
3 76
12.2%
5 44
7.1%
1 36
 
5.8%
8 33
 
5.3%
4 26
 
4.2%
6 22
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 520
83.3%
Dash Punctuation 104
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 94
18.1%
7 91
17.5%
2 84
16.2%
3 76
14.6%
5 44
8.5%
1 36
 
6.9%
8 33
 
6.3%
4 26
 
5.0%
6 22
 
4.2%
9 14
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 624
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 104
16.7%
0 94
15.1%
7 91
14.6%
2 84
13.5%
3 76
12.2%
5 44
7.1%
1 36
 
5.8%
8 33
 
5.3%
4 26
 
4.2%
6 22
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 624
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 104
16.7%
0 94
15.1%
7 91
14.6%
2 84
13.5%
3 76
12.2%
5 44
7.1%
1 36
 
5.8%
8 33
 
5.3%
4 26
 
4.2%
6 22
 
3.5%

행정동
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size548.0 B
중산동
18 
운서동
13 
경동
3 
신포동
3 
신흥동
3 
Other values (7)
12 

Length

Max length4
Median length3
Mean length2.8846154
Min length2

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row경동
2nd row경동
3rd row경동
4th row신포동
5th row신포동

Common Values

ValueCountFrequency (%)
중산동 18
34.6%
운서동 13
25.0%
경동 3
 
5.8%
신포동 3
 
5.8%
신흥동 3
 
5.8%
운남동 2
 
3.8%
유동 2
 
3.8%
인현동 2
 
3.8%
항동 2
 
3.8%
항동7가 2
 
3.8%
Other values (2) 2
 
3.8%

Length

2023-12-13T06:19:18.582660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
중산동 18
34.6%
운서동 13
25.0%
경동 3
 
5.8%
신포동 3
 
5.8%
신흥동 3
 
5.8%
운남동 2
 
3.8%
유동 2
 
3.8%
인현동 2
 
3.8%
항동 2
 
3.8%
항동7가 2
 
3.8%
Other values (2) 2
 
3.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-10-23
52 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-23
2nd row2023-10-23
3rd row2023-10-23
4th row2023-10-23
5th row2023-10-23

Common Values

ValueCountFrequency (%)
2023-10-23 52
100.0%

Length

2023-12-13T06:19:18.715381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:19:18.814722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-23 52
100.0%

Interactions

2023-12-13T06:19:16.590571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:19:18.879715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번의료기관명전화번호행정동
연번1.0001.0001.0000.848
의료기관명1.0001.0001.0001.000
전화번호1.0001.0001.0001.000
행정동0.8481.0001.0001.000
2023-12-13T06:19:18.982727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동
연번1.0000.555
행정동0.5551.000

Missing values

2023-12-13T06:19:16.718007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:19:16.855514image/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

연번의료기관명전화번호행정동데이터기준일자
01아이본산부인과의원032-772-7474경동2023-10-23
12예지요양병원032-773-6035경동2023-10-23
23인천삼성요양병원032-721-7575경동2023-10-23
34성모연합의원032-710-4474신포동2023-10-23
45신포김내과의원032-777-0902신포동2023-10-23
56연세참가정의학과의원032-766-0075신포동2023-10-23
67김훈수내과의원032-889-3378신흥동2023-10-23
78신흥메디칼의원032-885-7582신흥동2023-10-23
89인하대학교의과대학부속병원032-890-2000신흥동2023-10-23
910가천대부속 동인천길병원032-770-1300용동2023-10-23
연번의료기관명전화번호행정동데이터기준일자
4243키클소아청소년과의원032-713-7950중산동2023-10-23
4344편안내과의원032-747-2236중산동2023-10-23
4445피터팬소아청소년과의원032-751-0306중산동2023-10-23
4546하늘도시산부인과의원032-746-1236중산동2023-10-23
4647하늘메디컬의원032-752-6008중산동2023-10-23
4748하늘정형외과의원032-747-1321중산동2023-10-23
4849송재현가정의원032-887-5775항동2023-10-23
4950이재준내과의원032-883-6347항동2023-10-23
5051고은요양병원032-715-5933항동7가2023-10-23
5152연안의원032-888-0033항동7가2023-10-23