Overview

Dataset statistics

Number of variables7
Number of observations39
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory61.4 B

Variable types

Numeric2
Categorical3
Text2

Dataset

Description연수구 비상급수시설 현황에 대한 데이터로 비상급수시설 지정구분, 권역별, 시설명, 소재지 도로명주소, 수질구분, 양수량(톤) 등을 제공합니다
Author인천광역시 연수구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3068237&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 권역별High correlation
지정구분 is highly overall correlated with 수질구분High correlation
권역별 is highly overall correlated with 연번High correlation
수질구분 is highly overall correlated with 지정구분High correlation
지정구분 is highly imbalanced (59.3%)Imbalance
수질구분 is highly imbalanced (52.3%)Imbalance
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2024-04-06 09:38:40.448944
Analysis finished2024-04-06 09:38:41.368728
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2024-04-06T18:38:41.435260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.9
Q110.5
median20
Q329.5
95-th percentile37.1
Maximum39
Range38
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.401754
Coefficient of variation (CV)0.57008771
Kurtosis-1.2
Mean20
Median Absolute Deviation (MAD)10
Skewness0
Sum780
Variance130
MonotonicityStrictly increasing
2024-04-06T18:38:41.584157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 1
 
2.6%
2 1
 
2.6%
23 1
 
2.6%
24 1
 
2.6%
25 1
 
2.6%
26 1
 
2.6%
27 1
 
2.6%
28 1
 
2.6%
29 1
 
2.6%
30 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
1 1
2.6%
2 1
2.6%
3 1
2.6%
4 1
2.6%
5 1
2.6%
6 1
2.6%
7 1
2.6%
8 1
2.6%
9 1
2.6%
10 1
2.6%
ValueCountFrequency (%)
39 1
2.6%
38 1
2.6%
37 1
2.6%
36 1
2.6%
35 1
2.6%
34 1
2.6%
33 1
2.6%
32 1
2.6%
31 1
2.6%
30 1
2.6%

지정구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size444.0 B
공공용
34 
정부지원
4 
자치단체
 
1

Length

Max length4
Median length3
Mean length3.1282051
Min length3

Unique

Unique1 ?
Unique (%)2.6%

Sample

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

Common Values

ValueCountFrequency (%)
공공용 34
87.2%
정부지원 4
 
10.3%
자치단체 1
 
2.6%

Length

2024-04-06T18:38:41.728241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:38:41.831026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 34
87.2%
정부지원 4
 
10.3%
자치단체 1
 
2.6%

권역별
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
청학동
10 
옥련1동
7 
선학동
5 
동춘1동
5 
옥련2동
4 
Other values (4)
8 

Length

Max length4
Median length4
Mean length3.6153846
Min length3

Unique

Unique1 ?
Unique (%)2.6%

Sample

1st row옥련1동
2nd row옥련1동
3rd row옥련1동
4th row옥련1동
5th row옥련1동

Common Values

ValueCountFrequency (%)
청학동 10
25.6%
옥련1동 7
17.9%
선학동 5
12.8%
동춘1동 5
12.8%
옥련2동 4
 
10.3%
연수2동 3
 
7.7%
연수1동 2
 
5.1%
동춘2동 2
 
5.1%
연수3동 1
 
2.6%

Length

2024-04-06T18:38:41.960145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:38:42.093972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청학동 10
25.6%
옥련1동 7
17.9%
선학동 5
12.8%
동춘1동 5
12.8%
옥련2동 4
 
10.3%
연수2동 3
 
7.7%
연수1동 2
 
5.1%
동춘2동 2
 
5.1%
연수3동 1
 
2.6%

시설명
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-04-06T18:38:42.428731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length5.6923077
Min length3

Characters and Unicode

Total characters222
Distinct characters116
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st row벽산빌리지
2nd row블루모텔
3rd row산아래
4th row가빈호텔
5th rowSK엔크린 아시아self주유소
ValueCountFrequency (%)
벽산빌리지 1
 
2.5%
태평양사우나 1
 
2.5%
일송정 1
 
2.5%
성호공원 1
 
2.5%
용담공원 1
 
2.5%
용담연못 1
 
2.5%
큐브모텔 1
 
2.5%
청학탕 1
 
2.5%
청학그린대중탕 1
 
2.5%
신창빌딩 1
 
2.5%
Other values (30) 30
75.0%
2024-04-06T18:38:43.240831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 9
 
4.1%
아 8
 
3.6%
주 7
 
3.2%
유 6
 
2.7%
원 5
 
2.3%
소 5
 
2.3%
탕 5
 
2.3%
텔 4
 
1.8%
대 4
 
1.8%
송 4
 
1.8%
Other values (106) 165
74.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 198
89.2%
Uppercase Letter 6
 
2.7%
Lowercase Letter 6
 
2.7%
Open Punctuation 4
 
1.8%
Close Punctuation 4
 
1.8%
Decimal Number 2
 
0.9%
Dash Punctuation 1
 
0.5%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
학 9
 
4.5%
아 8
 
4.0%
주 7
 
3.5%
유 6
 
3.0%
원 5
 
2.5%
소 5
 
2.5%
탕 5
 
2.5%
텔 4
 
2.0%
대 4
 
2.0%
송 4
 
2.0%
Other values (91) 141
71.2%
Lowercase Letter
ValueCountFrequency (%)
s 2
33.3%
e 1
16.7%
f 1
16.7%
l 1
16.7%
g 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
K 2
33.3%
S 2
33.3%
G 1
16.7%
L 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 198
89.2%
Common 12
 
5.4%
Latin 12
 
5.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 9
 
4.5%
아 8
 
4.0%
주 7
 
3.5%
유 6
 
3.0%
원 5
 
2.5%
소 5
 
2.5%
탕 5
 
2.5%
텔 4
 
2.0%
대 4
 
2.0%
송 4
 
2.0%
Other values (91) 141
71.2%
Latin
ValueCountFrequency (%)
K 2
16.7%
S 2
16.7%
s 2
16.7%
e 1
8.3%
G 1
8.3%
L 1
8.3%
f 1
8.3%
l 1
8.3%
g 1
8.3%
Common
ValueCountFrequency (%)
( 4
33.3%
) 4
33.3%
- 1
 
8.3%
1
 
8.3%
2 1
 
8.3%
1 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 198
89.2%
ASCII 24
 
10.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 9
 
4.5%
아 8
 
4.0%
주 7
 
3.5%
유 6
 
3.0%
원 5
 
2.5%
소 5
 
2.5%
탕 5
 
2.5%
텔 4
 
2.0%
대 4
 
2.0%
송 4
 
2.0%
Other values (91) 141
71.2%
ASCII
ValueCountFrequency (%)
( 4
16.7%
) 4
16.7%
K 2
 
8.3%
S 2
 
8.3%
s 2
 
8.3%
e 1
 
4.2%
- 1
 
4.2%
G 1
 
4.2%
L 1
 
4.2%
f 1
 
4.2%
Other values (5) 5
20.8%

소재지 도로명 주소
Text

Distinct38
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-04-06T18:38:43.641567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length20.358974
Min length15

Characters and Unicode

Total characters794
Distinct characters76
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

Unique37 ?
Unique (%)94.9%

Sample

1st row인천광역시 연수구 한나루로 158번길31
2nd row인천광역시 연수구 능허대로 179번길14
3rd row인천광역시 연수구 청룡로 46
4th row인천광역시 연수구 인권로 17
5th row인천광역시 연수구 한나루로 131
ValueCountFrequency (%)
인천광역시 39
23.8%
연수구 39
23.8%
용담로 5
 
3.0%
비류대로 5
 
3.0%
경원대로 3
 
1.8%
능허대로 3
 
1.8%
연수동 2
 
1.2%
한나루로 2
 
1.2%
인권로 2
 
1.2%
앵고개로 2
 
1.2%
Other values (61) 62
37.8%
2024-04-06T18:38:44.179608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
126
15.9%
인 42
 
5.3%
연 41
 
5.2%
수 41
 
5.2%
광 39
 
4.9%
역 39
 
4.9%
시 39
 
4.9%
구 39
 
4.9%
로 39
 
4.9%
천 39
 
4.9%
Other values (66) 310
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 516
65.0%
Decimal Number 133
 
16.8%
Space Separator 126
 
15.9%
Open Punctuation 7
 
0.9%
Close Punctuation 7
 
0.9%
Dash Punctuation 3
 
0.4%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 42
 
8.1%
연 41
 
7.9%
수 41
 
7.9%
광 39
 
7.6%
역 39
 
7.6%
시 39
 
7.6%
구 39
 
7.6%
로 39
 
7.6%
천 39
 
7.6%
길 17
 
3.3%
Other values (51) 141
27.3%
Decimal Number
ValueCountFrequency (%)
1 30
22.6%
5 17
12.8%
2 15
11.3%
3 15
11.3%
6 13
9.8%
8 12
 
9.0%
7 11
 
8.3%
4 11
 
8.3%
9 5
 
3.8%
0 4
 
3.0%
Space Separator
ValueCountFrequency (%)
126
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 516
65.0%
Common 278
35.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 42
 
8.1%
연 41
 
7.9%
수 41
 
7.9%
광 39
 
7.6%
역 39
 
7.6%
시 39
 
7.6%
구 39
 
7.6%
로 39
 
7.6%
천 39
 
7.6%
길 17
 
3.3%
Other values (51) 141
27.3%
Common
ValueCountFrequency (%)
126
45.3%
1 30
 
10.8%
5 17
 
6.1%
2 15
 
5.4%
3 15
 
5.4%
6 13
 
4.7%
8 12
 
4.3%
7 11
 
4.0%
4 11
 
4.0%
( 7
 
2.5%
Other values (5) 21
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 516
65.0%
ASCII 278
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
126
45.3%
1 30
 
10.8%
5 17
 
6.1%
2 15
 
5.4%
3 15
 
5.4%
6 13
 
4.7%
8 12
 
4.3%
7 11
 
4.0%
4 11
 
4.0%
( 7
 
2.5%
Other values (5) 21
 
7.6%
Hangul
ValueCountFrequency (%)
인 42
 
8.1%
연 41
 
7.9%
수 41
 
7.9%
광 39
 
7.6%
역 39
 
7.6%
시 39
 
7.6%
구 39
 
7.6%
로 39
 
7.6%
천 39
 
7.6%
길 17
 
3.3%
Other values (51) 141
27.3%

수질구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
생활용수
35 
음용수
4 

Length

Max length4
Median length4
Mean length3.8974359
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row음용수
2nd row생활용수
3rd row생활용수
4th row생활용수
5th row생활용수

Common Values

ValueCountFrequency (%)
생활용수 35
89.7%
음용수 4
 
10.3%

Length

2024-04-06T18:38:44.375442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:38:44.534146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활용수 35
89.7%
음용수 4
 
10.3%

양수량(톤)
Real number (ℝ)

Distinct23
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.761538
Minimum33
Maximum288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2024-04-06T18:38:44.649448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile44.5
Q165.5
median74.5
Q3104
95-th percentile129.2
Maximum288
Range255
Interquartile range (IQR)38.5

Descriptive statistics

Standard deviation45.293799
Coefficient of variation (CV)0.50460141
Kurtosis9.9350165
Mean89.761538
Median Absolute Deviation (MAD)16.5
Skewness2.703861
Sum3500.7
Variance2051.5282
MonotonicityNot monotonic
2024-04-06T18:38:44.779532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
72.0 6
15.4%
115.0 5
 
12.8%
100.0 4
 
10.3%
65.0 2
 
5.1%
90.0 2
 
5.1%
60.0 2
 
5.1%
50.0 2
 
5.1%
33.0 1
 
2.6%
212.0 1
 
2.6%
45.0 1
 
2.6%
Other values (13) 13
33.3%
ValueCountFrequency (%)
33.0 1
2.6%
40.0 1
2.6%
45.0 1
2.6%
50.0 2
5.1%
60.0 2
5.1%
63.0 1
2.6%
65.0 2
5.1%
66.0 1
2.6%
67.0 1
2.6%
70.0 1
2.6%
ValueCountFrequency (%)
288.0 1
 
2.6%
212.0 1
 
2.6%
120.0 1
 
2.6%
115.2 1
 
2.6%
115.0 5
12.8%
108.0 1
 
2.6%
100.0 4
10.3%
91.0 1
 
2.6%
90.0 2
 
5.1%
87.0 1
 
2.6%

Interactions

2024-04-06T18:38:40.971754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:38:40.777634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:38:41.071787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:38:40.881398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T18:38:44.866095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지정구분권역별시설명소재지 도로명 주소수질구분양수량(톤)
연번1.0000.4000.8931.0001.0000.4010.304
지정구분0.4001.0000.3451.0000.0000.4540.596
권역별0.8930.3451.0001.0001.0000.3730.593
시설명1.0001.0001.0001.0001.0001.0001.000
소재지 도로명 주소1.0000.0001.0001.0001.0000.0000.960
수질구분0.4010.4540.3731.0000.0001.0000.450
양수량(톤)0.3040.5960.5931.0000.9600.4501.000
2024-04-06T18:38:44.982018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정구분권역별수질구분
지정구분1.0000.1280.693
권역별0.1281.0000.328
수질구분0.6930.3281.000
2024-04-06T18:38:45.073987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번양수량(톤)지정구분권역별수질구분
연번1.0000.4140.2940.6610.405
양수량(톤)0.4141.0000.2820.3190.301
지정구분0.2940.2821.0000.1280.693
권역별0.6610.3190.1281.0000.328
수질구분0.4050.3010.6930.3281.000

Missing values

2024-04-06T18:38:41.213492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T18:38:41.324785image/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

연번지정구분권역별시설명소재지 도로명 주소수질구분양수량(톤)
01공공용옥련1동벽산빌리지인천광역시 연수구 한나루로 158번길31음용수33.0
12공공용옥련1동블루모텔인천광역시 연수구 능허대로 179번길14생활용수115.0
23공공용옥련1동산아래인천광역시 연수구 청룡로 46생활용수66.0
34공공용옥련1동가빈호텔인천광역시 연수구 인권로 17생활용수65.0
45공공용옥련1동SK엔크린 아시아self주유소인천광역시 연수구 한나루로 131생활용수84.0
56공공용옥련1동태영프라자인천광역시 연수구 비류대로 184생활용수40.0
67공공용옥련1동(주)새힘인천광역시 연수구 인권로 16 (옥련동)생활용수72.0
78공공용옥련2동LG-칼텍스정유(gs셀프금강주유소)인천광역시 연수구 비류대로 223생활용수72.0
89공공용옥련2동해양과학고등학교인천광역시 연수구 능허대로 71생활용수91.0
910공공용옥련2동인송중학교인천광역시 연수구 능허대로79번길 55생활용수87.0
연번지정구분권역별시설명소재지 도로명 주소수질구분양수량(톤)
2930공공용청학동티파니빌딩인천광역시 연수구 용담로 87생활용수90.0
3031공공용청학동일송정인천광역시 연수구 비류대로 331번길8생활용수72.0
3132공공용청학동청학숲요양원인천광역시 연수구 청솔로 158생활용수115.0
3233공공용동춘1동궁중삼계탕인천광역시 연수구 청량로 84생활용수115.0
3334공공용동춘1동라마다송도호텔인천광역시 연수구 능허대로267번길 29생활용수288.0
3435공공용동춘1동아리아리랑인천광역시 연수구 솔밭로 5생활용수72.0
3536공공용동춘1동기아오토큐인천광역시 연수구 앵고개로 125(동춘동)생활용수74.5
3637공공용동춘1동송도골프인천광역시 연수구 능허대로 236생활용수45.0
3738공공용동춘2동아주탕인천광역시 연수구 먼우금로63번길 13생활용수115.0
3839공공용동춘2동백두산랜드인천광역시 연수구 앵고개로 250생활용수212.0