Overview

Dataset statistics

Number of variables7
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory61.6 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 지정구분 and 2 other fieldsHigh correlation
지정구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
권역별 is highly overall correlated with 연번High correlation
수질구분 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
지정구분 is highly imbalanced (57.8%)Imbalance
수질구분 is highly imbalanced (50.6%)Imbalance
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2024-04-06 09:38:56.332112
Analysis finished2024-04-06 09:38:57.319195
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19
Minimum1
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-04-06T18:38:57.428010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.8
Q110
median19
Q328
95-th percentile35.2
Maximum37
Range36
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.824355
Coefficient of variation (CV)0.56970291
Kurtosis-1.2
Mean19
Median Absolute Deviation (MAD)9
Skewness0
Sum703
Variance117.16667
MonotonicityStrictly increasing
2024-04-06T18:38:57.602178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 1
 
2.7%
29 1
 
2.7%
22 1
 
2.7%
23 1
 
2.7%
24 1
 
2.7%
25 1
 
2.7%
26 1
 
2.7%
27 1
 
2.7%
28 1
 
2.7%
30 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
1 1
2.7%
2 1
2.7%
3 1
2.7%
4 1
2.7%
5 1
2.7%
6 1
2.7%
7 1
2.7%
8 1
2.7%
9 1
2.7%
10 1
2.7%
ValueCountFrequency (%)
37 1
2.7%
36 1
2.7%
35 1
2.7%
34 1
2.7%
33 1
2.7%
32 1
2.7%
31 1
2.7%
30 1
2.7%
29 1
2.7%
28 1
2.7%

지정구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size428.0 B
공공용
32 
정부지원
4 
자치단체
 
1

Length

Max length4
Median length3
Mean length3.1351351
Min length3

Unique

Unique1 ?
Unique (%)2.7%

Sample

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

Common Values

ValueCountFrequency (%)
공공용 32
86.5%
정부지원 4
 
10.8%
자치단체 1
 
2.7%

Length

2024-04-06T18:38:57.759608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:38:57.869269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 32
86.5%
정부지원 4
 
10.8%
자치단체 1
 
2.7%

권역별
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
청학동
10 
옥련1동
6 
선학동
5 
동춘1동
5 
옥련2동
4 
Other values (4)
7 

Length

Max length4
Median length4
Mean length3.5945946
Min length3

Unique

Unique2 ?
Unique (%)5.4%

Sample

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

Common Values

ValueCountFrequency (%)
청학동 10
27.0%
옥련1동 6
16.2%
선학동 5
13.5%
동춘1동 5
13.5%
옥련2동 4
 
10.8%
연수2동 3
 
8.1%
동춘2동 2
 
5.4%
연수1동 1
 
2.7%
연수3동 1
 
2.7%

Length

2024-04-06T18:38:57.985971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:38:58.109952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청학동 10
27.0%
옥련1동 6
16.2%
선학동 5
13.5%
동춘1동 5
13.5%
옥련2동 4
 
10.8%
연수2동 3
 
8.1%
동춘2동 2
 
5.4%
연수1동 1
 
2.7%
연수3동 1
 
2.7%

시설명
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-04-06T18:38:58.334495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length5.7027027
Min length3

Characters and Unicode

Total characters211
Distinct characters114
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

Unique37 ?
Unique (%)100.0%

Sample

1st row벽산빌리지
2nd row블루모텔
3rd row산아래
4th row가빈호텔
5th rowSK엔크린 아시아self주유소
ValueCountFrequency (%)
벽산빌리지 1
 
2.6%
티파니빌딩 1
 
2.6%
성호공원 1
 
2.6%
용담공원 1
 
2.6%
용담연못 1
 
2.6%
큐브모텔 1
 
2.6%
청학탕 1
 
2.6%
청학그린대중탕 1
 
2.6%
신창빌딩 1
 
2.6%
일송정 1
 
2.6%
Other values (28) 28
73.7%
2024-04-06T18:38:58.713896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
학 9
 
4.3%
아 8
 
3.8%
주 7
 
3.3%
유 6
 
2.8%
원 5
 
2.4%
소 5
 
2.4%
탕 5
 
2.4%
송 4
 
1.9%
( 4
 
1.9%
양 4
 
1.9%
Other values (104) 154
73.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 187
88.6%
Uppercase Letter 6
 
2.8%
Lowercase Letter 6
 
2.8%
Open Punctuation 4
 
1.9%
Close Punctuation 4
 
1.9%
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
 
4.8%
아 8
 
4.3%
주 7
 
3.7%
유 6
 
3.2%
원 5
 
2.7%
소 5
 
2.7%
탕 5
 
2.7%
송 4
 
2.1%
양 4
 
2.1%
대 4
 
2.1%
Other values (89) 130
69.5%
Lowercase Letter
ValueCountFrequency (%)
s 2
33.3%
g 1
16.7%
f 1
16.7%
l 1
16.7%
e 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 187
88.6%
Common 12
 
5.7%
Latin 12
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
학 9
 
4.8%
아 8
 
4.3%
주 7
 
3.7%
유 6
 
3.2%
원 5
 
2.7%
소 5
 
2.7%
탕 5
 
2.7%
송 4
 
2.1%
양 4
 
2.1%
대 4
 
2.1%
Other values (89) 130
69.5%
Latin
ValueCountFrequency (%)
K 2
16.7%
S 2
16.7%
s 2
16.7%
g 1
8.3%
G 1
8.3%
L 1
8.3%
f 1
8.3%
l 1
8.3%
e 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 187
88.6%
ASCII 24
 
11.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
학 9
 
4.8%
아 8
 
4.3%
주 7
 
3.7%
유 6
 
3.2%
원 5
 
2.7%
소 5
 
2.7%
탕 5
 
2.7%
송 4
 
2.1%
양 4
 
2.1%
대 4
 
2.1%
Other values (89) 130
69.5%
ASCII
ValueCountFrequency (%)
( 4
16.7%
) 4
16.7%
K 2
 
8.3%
S 2
 
8.3%
s 2
 
8.3%
g 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

Distinct36
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size428.0 B
2024-04-06T18:38:58.968216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length18.243243
Min length14

Characters and Unicode

Total characters675
Distinct characters71
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 (%)94.6%

Sample

1st row인천광역시 연수구 한나루로158번길31
2nd row인천광역시 연수구 능허대로179번길14
3rd row인천광역시 연수구 청룡로46
4th row인천광역시 연수구 인권로17
5th row인천광역시 연수구 한나루로131
ValueCountFrequency (%)
인천광역시 37
33.0%
연수구 37
33.0%
용담로61 2
 
1.8%
능허대로236 1
 
0.9%
함박뫼로162 1
 
0.9%
용담로87 1
 
0.9%
능허대로179번길14 1
 
0.9%
솔샘로43번길15 1
 
0.9%
용담로85번길20 1
 
0.9%
청학로5번길16-8 1
 
0.9%
Other values (29) 29
25.9%
2024-04-06T18:38:59.414488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
11.1%
인 40
 
5.9%
광 37
 
5.5%
역 37
 
5.5%
시 37
 
5.5%
연 37
 
5.5%
수 37
 
5.5%
구 37
 
5.5%
천 37
 
5.5%
로 37
 
5.5%
Other values (61) 264
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 471
69.8%
Decimal Number 122
 
18.1%
Space Separator 75
 
11.1%
Dash Punctuation 3
 
0.4%
Other Punctuation 2
 
0.3%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 40
 
8.5%
광 37
 
7.9%
역 37
 
7.9%
시 37
 
7.9%
연 37
 
7.9%
수 37
 
7.9%
구 37
 
7.9%
천 37
 
7.9%
로 37
 
7.9%
길 15
 
3.2%
Other values (46) 120
25.5%
Decimal Number
ValueCountFrequency (%)
1 26
21.3%
5 17
13.9%
2 15
12.3%
3 13
10.7%
6 12
9.8%
8 11
9.0%
7 11
9.0%
4 8
 
6.6%
9 5
 
4.1%
0 4
 
3.3%
Space Separator
ValueCountFrequency (%)
75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 471
69.8%
Common 204
30.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 40
 
8.5%
광 37
 
7.9%
역 37
 
7.9%
시 37
 
7.9%
연 37
 
7.9%
수 37
 
7.9%
구 37
 
7.9%
천 37
 
7.9%
로 37
 
7.9%
길 15
 
3.2%
Other values (46) 120
25.5%
Common
ValueCountFrequency (%)
75
36.8%
1 26
 
12.7%
5 17
 
8.3%
2 15
 
7.4%
3 13
 
6.4%
6 12
 
5.9%
8 11
 
5.4%
7 11
 
5.4%
4 8
 
3.9%
9 5
 
2.5%
Other values (5) 11
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 471
69.8%
ASCII 204
30.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
36.8%
1 26
 
12.7%
5 17
 
8.3%
2 15
 
7.4%
3 13
 
6.4%
6 12
 
5.9%
8 11
 
5.4%
7 11
 
5.4%
4 8
 
3.9%
9 5
 
2.5%
Other values (5) 11
 
5.4%
Hangul
ValueCountFrequency (%)
인 40
 
8.5%
광 37
 
7.9%
역 37
 
7.9%
시 37
 
7.9%
연 37
 
7.9%
수 37
 
7.9%
구 37
 
7.9%
천 37
 
7.9%
로 37
 
7.9%
길 15
 
3.2%
Other values (46) 120
25.5%

수질구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
생활용수
33 
음용수
4 

Length

Max length4
Median length4
Mean length3.8918919
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생활용수 33
89.2%
음용수 4
 
10.8%

Length

2024-04-06T18:38:59.659274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:38:59.766322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활용수 33
89.2%
음용수 4
 
10.8%

양수량(톤)
Real number (ℝ)

Distinct21
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.586486
Minimum20
Maximum288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2024-04-06T18:38:59.877150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile32.4
Q165
median72
Q3100
95-th percentile134.56
Maximum288
Range268
Interquartile range (IQR)35

Descriptive statistics

Standard deviation47.75713
Coefficient of variation (CV)0.54525683
Kurtosis8.7653892
Mean87.586486
Median Absolute Deviation (MAD)22
Skewness2.4683651
Sum3240.7
Variance2280.7434
MonotonicityNot monotonic
2024-04-06T18:39:00.012102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
72.0 6
16.2%
115.0 5
13.5%
100.0 4
 
10.8%
65.0 2
 
5.4%
60.0 2
 
5.4%
50.0 2
 
5.4%
90.0 2
 
5.4%
33.0 1
 
2.7%
70.0 1
 
2.7%
212.0 1
 
2.7%
Other values (11) 11
29.7%
ValueCountFrequency (%)
20.0 1
2.7%
30.0 1
2.7%
33.0 1
2.7%
45.0 1
2.7%
50.0 2
5.4%
60.0 2
5.4%
65.0 2
5.4%
66.0 1
2.7%
67.0 1
2.7%
70.0 1
2.7%
ValueCountFrequency (%)
288.0 1
 
2.7%
212.0 1
 
2.7%
115.2 1
 
2.7%
115.0 5
13.5%
108.0 1
 
2.7%
100.0 4
10.8%
91.0 1
 
2.7%
90.0 2
 
5.4%
84.0 1
 
2.7%
74.5 1
 
2.7%

Interactions

2024-04-06T18:38:56.875587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:38:56.679119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:38:56.976671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:38:56.789148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T18:39:00.120136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지정구분권역별시설명소재지 도로명 주소수질구분양수량(톤)
연번1.0000.6290.8661.0000.9390.8340.428
지정구분0.6291.0000.2151.0000.0000.4520.576
권역별0.8660.2151.0001.0001.0000.3600.541
시설명1.0001.0001.0001.0001.0001.0001.000
소재지 도로명 주소0.9390.0001.0001.0001.0000.0000.979
수질구분0.8340.4520.3601.0000.0001.0000.457
양수량(톤)0.4280.5760.5411.0000.9790.4571.000
2024-04-06T18:39:00.232109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정구분권역별수질구분
지정구분1.0000.0360.690
권역별0.0361.0000.314
수질구분0.6900.3141.000
2024-04-06T18:39:00.330420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번양수량(톤)지정구분권역별수질구분
연번1.0000.4380.5220.6500.745
양수량(톤)0.4381.0000.2670.2780.305
지정구분0.5220.2671.0000.0360.690
권역별0.6500.2780.0361.0000.314
수질구분0.7450.3050.6900.3141.000

Missing values

2024-04-06T18:38:57.130832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T18:38:57.257825image/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 한나루로158번길31음용수33.0
12공공용옥련1동블루모텔인천광역시 연수구 능허대로179번길14생활용수115.0
23공공용옥련1동산아래인천광역시 연수구 청룡로46생활용수66.0
34공공용옥련1동가빈호텔인천광역시 연수구 인권로17생활용수65.0
45공공용옥련1동SK엔크린 아시아self주유소인천광역시 연수구 한나루로131생활용수84.0
56공공용옥련1동(주)새힘인천광역시 연수구 인권로16 (옥련동)생활용수72.0
67공공용옥련2동LG-칼텍스정유(gs셀프금강주유소)인천광역시 연수구 비류대로223생활용수72.0
78공공용옥련2동해양과학고등학교인천광역시 연수구 능허대로71생활용수91.0
89공공용옥련2동인송중학교인천광역시 연수구 능허대로79번길55생활용수30.0
910공공용옥련2동태평양사우나인천광역시 연수구 비류대로170생활용수20.0
연번지정구분권역별시설명소재지 도로명 주소수질구분양수량(톤)
2728공공용청학동티파니빌딩인천광역시 연수구 용담로87생활용수90.0
2829공공용청학동일송정인천광역시 연수구 비류대로331번길8생활용수72.0
2930공공용청학동청학숲요양원인천광역시 연수구 청솔로158생활용수115.0
3031공공용동춘1동궁중삼계탕인천광역시 연수구 청량로84생활용수115.0
3132공공용동춘1동라마다송도호텔인천광역시 연수구 능허대로267번길29생활용수288.0
3233공공용동춘1동아리아리랑인천광역시 연수구 솔밭로5생활용수72.0
3334공공용동춘1동기아오토큐인천광역시 연수구 앵고개로125생활용수74.5
3435공공용동춘1동송도골프인천광역시 연수구 능허대로236생활용수45.0
3536공공용동춘2동아주탕인천광역시 연수구 먼우금로63번길13생활용수115.0
3637공공용동춘2동백두산랜드인천광역시 연수구 앵고개로250생활용수212.0