Overview

Dataset statistics

Number of variables17
Number of observations66
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.3 KiB
Average record size in memory145.0 B

Variable types

Categorical5
Text5
DateTime1
Numeric6

Dataset

Description경기도 고양시_민방위 비상급수시설 현황에 대한 데이터로 급수시설명, 인허가일자, 면적, 위치, 시설구분명 등의 항목을 제공합니다.
Author경기도 고양시
URLhttps://www.data.go.kr/data/3078893/fileData.do

Alerts

시군명 has constant value ""Constant
영업상태구분코드 has constant value ""Constant
영업상태명 has constant value ""Constant
소재지면적정보 has constant value ""Constant
도로명우편번호 is highly overall correlated with 소재지우편번호 and 4 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with 도로명우편번호 and 4 other fieldsHigh correlation
위도 is highly overall correlated with 도로명우편번호 and 2 other fieldsHigh correlation
경도 is highly overall correlated with 도로명우편번호 and 2 other fieldsHigh correlation
좌표값(X) is highly overall correlated with 도로명우편번호 and 2 other fieldsHigh correlation
좌표값(Y) is highly overall correlated with 도로명우편번호 and 2 other fieldsHigh correlation
급수시설명 has unique valuesUnique
시설명건물명정보 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:23:17.994040
Analysis finished2024-04-06 08:23:28.415220
Duration10.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
고양시
66 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고양시 66
100.0%

Length

2024-04-06T17:23:28.540188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:23:28.708800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고양시 66
100.0%

급수시설명
Text

UNIQUE 

Distinct66
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
2024-04-06T17:23:29.097055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length8.530303
Min length4

Characters and Unicode

Total characters563
Distinct characters158
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)100.0%

Sample

1st row123골프클럽
2nd rowNH인재개발원
3rd row가좌공원
4th row경성스폰지
5th row경일주류 (배상현)
ValueCountFrequency (%)
원흥역 6
 
6.2%
푸르지오 6
 
6.2%
2호공 6
 
6.2%
1호공 5
 
5.2%
3호공 4
 
4.1%
신고려관광 4
 
4.1%
농협대학 3
 
3.1%
중산힐스 3
 
3.1%
올림픽골프클럽 2
 
2.1%
4호공 2
 
2.1%
Other values (56) 56
57.7%
2024-04-06T17:23:30.070793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 43
 
7.6%
31
 
5.5%
) 27
 
4.8%
( 27
 
4.8%
원 24
 
4.3%
호 23
 
4.1%
지 13
 
2.3%
고 10
 
1.8%
역 9
 
1.6%
1 9
 
1.6%
Other values (148) 347
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 445
79.0%
Space Separator 31
 
5.5%
Decimal Number 28
 
5.0%
Close Punctuation 27
 
4.8%
Open Punctuation 27
 
4.8%
Uppercase Letter 4
 
0.7%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 43
 
9.7%
원 24
 
5.4%
호 23
 
5.2%
지 13
 
2.9%
고 10
 
2.2%
역 9
 
2.0%
산 8
 
1.8%
농 7
 
1.6%
한 7
 
1.6%
오 7
 
1.6%
Other values (133) 294
66.1%
Decimal Number
ValueCountFrequency (%)
1 9
32.1%
2 9
32.1%
3 5
17.9%
4 2
 
7.1%
6 1
 
3.6%
5 1
 
3.6%
7 1
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
H 1
25.0%
N 1
25.0%
I 1
25.0%
C 1
25.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 446
79.2%
Common 113
 
20.1%
Latin 4
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 43
 
9.6%
원 24
 
5.4%
호 23
 
5.2%
지 13
 
2.9%
고 10
 
2.2%
역 9
 
2.0%
산 8
 
1.8%
농 7
 
1.6%
한 7
 
1.6%
오 7
 
1.6%
Other values (134) 295
66.1%
Common
ValueCountFrequency (%)
31
27.4%
) 27
23.9%
( 27
23.9%
1 9
 
8.0%
2 9
 
8.0%
3 5
 
4.4%
4 2
 
1.8%
6 1
 
0.9%
5 1
 
0.9%
7 1
 
0.9%
Latin
ValueCountFrequency (%)
H 1
25.0%
N 1
25.0%
I 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 445
79.0%
ASCII 117
 
20.8%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 43
 
9.7%
원 24
 
5.4%
호 23
 
5.2%
지 13
 
2.9%
고 10
 
2.2%
역 9
 
2.0%
산 8
 
1.8%
농 7
 
1.6%
한 7
 
1.6%
오 7
 
1.6%
Other values (133) 294
66.1%
ASCII
ValueCountFrequency (%)
31
26.5%
) 27
23.1%
( 27
23.1%
1 9
 
7.7%
2 9
 
7.7%
3 5
 
4.3%
4 2
 
1.7%
6 1
 
0.9%
5 1
 
0.9%
7 1
 
0.9%
Other values (4) 4
 
3.4%
None
ValueCountFrequency (%)
㈜ 1
100.0%

인허가일자
Date

Distinct44
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size660.0 B
Minimum1995-01-30 00:00:00
Maximum2022-12-01 00:00:00
2024-04-06T17:23:30.331379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:30.558864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)

영업상태구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
1
66 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 66
100.0%

Length

2024-04-06T17:23:30.780518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:23:30.939173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 66
100.0%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
영업/정상
66 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 66
100.0%

Length

2024-04-06T17:23:31.112074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:23:31.301538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 66
100.0%

소재지면적정보
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size660.0 B
사용중
66 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사용중 66
100.0%

Length

2024-04-06T17:23:31.479507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:23:31.655349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용중 66
100.0%

도로명우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)68.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10387.515
Minimum10206
Maximum10596
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-04-06T17:23:31.911853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10206
5-th percentile10226
Q110271
median10375
Q310471.75
95-th percentile10566
Maximum10596
Range390
Interquartile range (IQR)200.75

Descriptive statistics

Standard deviation124.86155
Coefficient of variation (CV)0.012020349
Kurtosis-1.429945
Mean10387.515
Median Absolute Deviation (MAD)104
Skewness0.19674817
Sum685576
Variance15590.407
MonotonicityNot monotonic
2024-04-06T17:23:32.234081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
10563 6
 
9.1%
10246 5
 
7.6%
10292 4
 
6.1%
10566 4
 
6.1%
10443 3
 
4.5%
10226 2
 
3.0%
10442 2
 
3.0%
10271 2
 
3.0%
10314 2
 
3.0%
10283 1
 
1.5%
Other values (35) 35
53.0%
ValueCountFrequency (%)
10206 1
 
1.5%
10210 1
 
1.5%
10219 1
 
1.5%
10226 2
 
3.0%
10246 5
7.6%
10247 1
 
1.5%
10249 1
 
1.5%
10252 1
 
1.5%
10253 1
 
1.5%
10257 1
 
1.5%
ValueCountFrequency (%)
10596 1
 
1.5%
10579 1
 
1.5%
10566 4
6.1%
10563 6
9.1%
10553 1
 
1.5%
10551 1
 
1.5%
10528 1
 
1.5%
10512 1
 
1.5%
10472 1
 
1.5%
10471 1
 
1.5%

소재지도로명주소
Text

Distinct52
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size660.0 B
2024-04-06T17:23:32.931152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length35
Mean length28.181818
Min length24

Characters and Unicode

Total characters1860
Distinct characters124
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

Unique45 ?
Unique (%)68.2%

Sample

1st row경기도 고양시 덕양구 통일로 43-168 (동산동)
2nd row경기도 고양시 일산동구 문원길 71 (설문동)
3rd row경기도 고양시 일산서구 송산로 387-17 비상급수시설
4th row경기도 고양시 일산동구 문원길 9-6 (문봉동)
5th row경기도 고양시 덕양구 호국로 571-33 (화정동)
ValueCountFrequency (%)
고양시 66
 
16.1%
경기도 65
 
15.9%
덕양구 33
 
8.1%
일산동구 22
 
5.4%
비상급수시설 15
 
3.7%
일산서구 11
 
2.7%
671 6
 
1.5%
원흥동 6
 
1.5%
권율대로 6
 
1.5%
백석동 5
 
1.2%
Other values (116) 174
42.5%
2024-04-06T17:23:34.392295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
343
 
18.4%
양 101
 
5.4%
시 82
 
4.4%
동 74
 
4.0%
고 73
 
3.9%
경 70
 
3.8%
도 67
 
3.6%
구 66
 
3.5%
기 65
 
3.5%
로 55
 
3.0%
Other values (114) 864
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1169
62.8%
Space Separator 343
 
18.4%
Decimal Number 222
 
11.9%
Open Punctuation 51
 
2.7%
Close Punctuation 51
 
2.7%
Dash Punctuation 13
 
0.7%
Other Punctuation 11
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 101
 
8.6%
시 82
 
7.0%
동 74
 
6.3%
고 73
 
6.2%
경 70
 
6.0%
도 67
 
5.7%
구 66
 
5.6%
기 65
 
5.6%
로 55
 
4.7%
산 47
 
4.0%
Other values (99) 469
40.1%
Decimal Number
ValueCountFrequency (%)
1 35
15.8%
2 29
13.1%
3 29
13.1%
7 28
12.6%
6 26
11.7%
4 22
9.9%
8 19
8.6%
5 13
 
5.9%
0 12
 
5.4%
9 9
 
4.1%
Space Separator
ValueCountFrequency (%)
343
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1169
62.8%
Common 691
37.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 101
 
8.6%
시 82
 
7.0%
동 74
 
6.3%
고 73
 
6.2%
경 70
 
6.0%
도 67
 
5.7%
구 66
 
5.6%
기 65
 
5.6%
로 55
 
4.7%
산 47
 
4.0%
Other values (99) 469
40.1%
Common
ValueCountFrequency (%)
343
49.6%
( 51
 
7.4%
) 51
 
7.4%
1 35
 
5.1%
2 29
 
4.2%
3 29
 
4.2%
7 28
 
4.1%
6 26
 
3.8%
4 22
 
3.2%
8 19
 
2.7%
Other values (5) 58
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1169
62.8%
ASCII 691
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
343
49.6%
( 51
 
7.4%
) 51
 
7.4%
1 35
 
5.1%
2 29
 
4.2%
3 29
 
4.2%
7 28
 
4.1%
6 26
 
3.8%
4 22
 
3.2%
8 19
 
2.7%
Other values (5) 58
 
8.4%
Hangul
ValueCountFrequency (%)
양 101
 
8.6%
시 82
 
7.0%
동 74
 
6.3%
고 73
 
6.2%
경 70
 
6.0%
도 67
 
5.7%
구 66
 
5.6%
기 65
 
5.6%
로 55
 
4.7%
산 47
 
4.0%
Other values (99) 469
40.1%

소재지지번주소
Text

Distinct57
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size660.0 B
2024-04-06T17:23:34.919228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length20.939394
Min length19

Characters and Unicode

Total characters1382
Distinct characters64
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

Unique52 ?
Unique (%)78.8%

Sample

1st row경기도 고양시 덕양구 동산동 53-124
2nd row경기도 고양시 일산동구 설문동 135-9
3rd row경기도 고양시 일산서구 가좌동 1098
4th row경기도 고양시 일산동구 문봉동 190-22
5th row경기도 고양시 덕양구 화정동 809-1
ValueCountFrequency (%)
경기도 66
20.0%
고양시 66
20.0%
덕양구 33
 
10.0%
일산동구 22
 
6.7%
일산서구 11
 
3.3%
623 6
 
1.8%
대화동 6
 
1.8%
원흥동 6
 
1.8%
백석동 5
 
1.5%
성석동 5
 
1.5%
Other values (83) 104
31.5%
2024-04-06T17:23:35.868923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
264
19.1%
양 99
 
7.2%
동 89
 
6.4%
도 68
 
4.9%
경 66
 
4.8%
고 66
 
4.8%
시 66
 
4.8%
구 66
 
4.8%
기 66
 
4.8%
1 59
 
4.3%
Other values (54) 473
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 825
59.7%
Space Separator 264
 
19.1%
Decimal Number 260
 
18.8%
Dash Punctuation 33
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 99
12.0%
동 89
10.8%
도 68
8.2%
경 66
 
8.0%
고 66
 
8.0%
시 66
 
8.0%
구 66
 
8.0%
기 66
 
8.0%
산 38
 
4.6%
덕 34
 
4.1%
Other values (42) 167
20.2%
Decimal Number
ValueCountFrequency (%)
1 59
22.7%
2 34
13.1%
4 27
10.4%
3 25
9.6%
6 25
9.6%
8 22
 
8.5%
0 19
 
7.3%
7 18
 
6.9%
5 16
 
6.2%
9 15
 
5.8%
Space Separator
ValueCountFrequency (%)
264
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 825
59.7%
Common 557
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 99
12.0%
동 89
10.8%
도 68
8.2%
경 66
 
8.0%
고 66
 
8.0%
시 66
 
8.0%
구 66
 
8.0%
기 66
 
8.0%
산 38
 
4.6%
덕 34
 
4.1%
Other values (42) 167
20.2%
Common
ValueCountFrequency (%)
264
47.4%
1 59
 
10.6%
2 34
 
6.1%
- 33
 
5.9%
4 27
 
4.8%
3 25
 
4.5%
6 25
 
4.5%
8 22
 
3.9%
0 19
 
3.4%
7 18
 
3.2%
Other values (2) 31
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 825
59.7%
ASCII 557
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
264
47.4%
1 59
 
10.6%
2 34
 
6.1%
- 33
 
5.9%
4 27
 
4.8%
3 25
 
4.5%
6 25
 
4.5%
8 22
 
3.9%
0 19
 
3.4%
7 18
 
3.2%
Other values (2) 31
 
5.6%
Hangul
ValueCountFrequency (%)
양 99
12.0%
동 89
10.8%
도 68
8.2%
경 66
 
8.0%
고 66
 
8.0%
시 66
 
8.0%
구 66
 
8.0%
기 66
 
8.0%
산 38
 
4.6%
덕 34
 
4.1%
Other values (42) 167
20.2%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)68.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10387.515
Minimum10206
Maximum10596
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-04-06T17:23:36.313212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10206
5-th percentile10226
Q110271
median10375
Q310471.75
95-th percentile10566
Maximum10596
Range390
Interquartile range (IQR)200.75

Descriptive statistics

Standard deviation124.86155
Coefficient of variation (CV)0.012020349
Kurtosis-1.429945
Mean10387.515
Median Absolute Deviation (MAD)104
Skewness0.19674817
Sum685576
Variance15590.407
MonotonicityNot monotonic
2024-04-06T17:23:36.785614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
10563 6
 
9.1%
10246 5
 
7.6%
10292 4
 
6.1%
10566 4
 
6.1%
10443 3
 
4.5%
10226 2
 
3.0%
10442 2
 
3.0%
10271 2
 
3.0%
10314 2
 
3.0%
10283 1
 
1.5%
Other values (35) 35
53.0%
ValueCountFrequency (%)
10206 1
 
1.5%
10210 1
 
1.5%
10219 1
 
1.5%
10226 2
 
3.0%
10246 5
7.6%
10247 1
 
1.5%
10249 1
 
1.5%
10252 1
 
1.5%
10253 1
 
1.5%
10257 1
 
1.5%
ValueCountFrequency (%)
10596 1
 
1.5%
10579 1
 
1.5%
10566 4
6.1%
10563 6
9.1%
10553 1
 
1.5%
10551 1
 
1.5%
10528 1
 
1.5%
10512 1
 
1.5%
10472 1
 
1.5%
10471 1
 
1.5%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.669999
Minimum37.606138
Maximum37.731699
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-04-06T17:23:37.213171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.606138
5-th percentile37.626699
Q137.649865
median37.664911
Q337.692239
95-th percentile37.717918
Maximum37.731699
Range0.12556096
Interquartile range (IQR)0.042374005

Descriptive statistics

Standard deviation0.028117833
Coefficient of variation (CV)0.00074642512
Kurtosis-0.33920922
Mean37.669999
Median Absolute Deviation (MAD)0.019008905
Skewness0.039038658
Sum2486.2199
Variance0.00079061255
MonotonicityNot monotonic
2024-04-06T17:23:37.521748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.64986523 6
 
9.1%
37.66491141 3
 
4.5%
37.66050357 3
 
4.5%
37.70145956 2
 
3.0%
37.72186104 2
 
3.0%
37.64527203 2
 
3.0%
37.70000631 2
 
3.0%
37.64146789 1
 
1.5%
37.66913094 1
 
1.5%
37.65143531 1
 
1.5%
Other values (43) 43
65.2%
ValueCountFrequency (%)
37.60613842 1
1.5%
37.60741269 1
1.5%
37.61579225 1
1.5%
37.62588774 1
1.5%
37.62913327 1
1.5%
37.63569019 1
1.5%
37.63934685 1
1.5%
37.64146789 1
1.5%
37.64498575 1
1.5%
37.64527203 2
3.0%
ValueCountFrequency (%)
37.73169938 1
1.5%
37.72186104 2
3.0%
37.719022 1
1.5%
37.71460613 1
1.5%
37.70820293 1
1.5%
37.70587784 1
1.5%
37.7022201 1
1.5%
37.70151 1
1.5%
37.70145956 2
3.0%
37.70094522 1
1.5%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.8229
Minimum126.72168
Maximum126.90643
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-04-06T17:23:37.838278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.72168
5-th percentile126.74837
Q1126.77934
median126.82443
Q3126.87274
95-th percentile126.89302
Maximum126.90643
Range0.1847464
Interquartile range (IQR)0.093395725

Descriptive statistics

Standard deviation0.04866912
Coefficient of variation (CV)0.00038375656
Kurtosis-1.0444555
Mean126.8229
Median Absolute Deviation (MAD)0.04587955
Skewness-0.15005482
Sum8370.3115
Variance0.0023686833
MonotonicityNot monotonic
2024-04-06T17:23:38.159297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8727383 6
 
9.1%
126.8767048 3
 
4.5%
126.8732383 3
 
4.5%
126.7786037 2
 
3.0%
126.8930214 2
 
3.0%
126.7996304 2
 
3.0%
126.8254441 2
 
3.0%
126.9064277 1
 
1.5%
126.8872256 1
 
1.5%
126.7978719 1
 
1.5%
Other values (43) 43
65.2%
ValueCountFrequency (%)
126.7216813 1
1.5%
126.730909 1
1.5%
126.7320522 1
1.5%
126.7482755 1
1.5%
126.7486618 1
1.5%
126.7538975 1
1.5%
126.7558819 1
1.5%
126.756232 1
1.5%
126.7699449 1
1.5%
126.7720959 1
1.5%
ValueCountFrequency (%)
126.9064277 1
 
1.5%
126.8983879 1
 
1.5%
126.895847 1
 
1.5%
126.8930214 2
 
3.0%
126.8872256 1
 
1.5%
126.8767048 3
4.5%
126.874985 1
 
1.5%
126.8745582 1
 
1.5%
126.8732383 3
4.5%
126.8727383 6
9.1%

좌표값(X)
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean463391.83
Minimum456304.32
Maximum470234.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-04-06T17:23:38.451972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum456304.32
5-th percentile458582.74
Q1461149.22
median462818.55
Q3465863.71
95-th percentile468711.49
Maximum470234.27
Range13929.955
Interquartile range (IQR)4714.4941

Descriptive statistics

Standard deviation3123.0108
Coefficient of variation (CV)0.0067394603
Kurtosis-0.34624923
Mean463391.83
Median Absolute Deviation (MAD)2113.9053
Skewness0.037458705
Sum30583861
Variance9753196.7
MonotonicityNot monotonic
2024-04-06T17:23:38.823445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
461149.2153 6
 
9.1%
462818.5452 3
 
4.5%
462329.7789 3
 
4.5%
466890.5238 2
 
3.0%
469136.9826 2
 
3.0%
460650.7372 2
 
3.0%
466720.5148 2
 
3.0%
460213.7964 1
 
1.5%
463285.6543 1
 
1.5%
461335.0597 1
 
1.5%
Other values (43) 43
65.2%
ValueCountFrequency (%)
456304.318 1
1.5%
456440.3954 1
1.5%
457372.9022 1
1.5%
458494.2612 1
1.5%
458848.1607 1
1.5%
459578.0247 1
1.5%
459988.8889 1
1.5%
460213.7964 1
1.5%
460613.4968 1
1.5%
460650.7372 2
3.0%
ValueCountFrequency (%)
470234.2728 1
1.5%
469136.9826 2
3.0%
468834.5973 1
1.5%
468342.1531 1
1.5%
467630.8472 1
1.5%
467380.8614 1
1.5%
466985.6475 1
1.5%
466896.7888 1
1.5%
466890.5238 2
3.0%
466833.4625 1
1.5%

좌표값(Y)
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184377.86
Minimum175453.7
Maximum191742.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size726.0 B
2024-04-06T17:23:39.127838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum175453.7
5-th percentile177807.48
Q1180541.6
median184508.36
Q3188770.69
95-th percentile190569.56
Maximum191742.45
Range16288.753
Interquartile range (IQR)8229.0906

Descriptive statistics

Standard deviation4291.309
Coefficient of variation (CV)0.023274535
Kurtosis-1.0440019
Mean184377.86
Median Absolute Deviation (MAD)4034.7359
Skewness-0.14919765
Sum12168939
Variance18415333
MonotonicityNot monotonic
2024-04-06T17:23:39.466459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
188770.6945 6
 
9.1%
189122.8877 3
 
4.5%
188816.414 3
 
4.5%
180477.974 2
 
3.0%
190569.5574 2
 
3.0%
182318.718 2
 
3.0%
184607.9203 2
 
3.0%
191742.4517 1
 
1.5%
190051.5988 1
 
1.5%
182165.0213 1
 
1.5%
Other values (43) 43
65.2%
ValueCountFrequency (%)
175453.6983 1
1.5%
176262.0718 1
1.5%
176373.4519 1
1.5%
177799.2227 1
1.5%
177832.2679 1
1.5%
178291.5211 1
1.5%
178469.1936 1
1.5%
178499.7871 1
1.5%
179713.3083 1
1.5%
179893.0798 1
1.5%
ValueCountFrequency (%)
191742.4517 1
 
1.5%
191037.7411 1
 
1.5%
190811.5715 1
 
1.5%
190569.5574 2
 
3.0%
190051.5988 1
 
1.5%
189122.8877 3
4.5%
188965.8809 1
 
1.5%
188936.9926 1
 
1.5%
188816.414 3
4.5%
188770.6945 6
9.1%

비상시설위치
Text

Distinct57
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size660.0 B
2024-04-06T17:23:39.975040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length20.939394
Min length19

Characters and Unicode

Total characters1382
Distinct characters64
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

Unique52 ?
Unique (%)78.8%

Sample

1st row경기도 고양시 덕양구 동산동 53-124
2nd row경기도 고양시 일산동구 설문동 135-9
3rd row경기도 고양시 일산서구 가좌동 1098
4th row경기도 고양시 일산동구 문봉동 190-22
5th row경기도 고양시 덕양구 화정동 809-1
ValueCountFrequency (%)
경기도 66
20.0%
고양시 66
20.0%
덕양구 33
 
10.0%
일산동구 22
 
6.7%
일산서구 11
 
3.3%
623 6
 
1.8%
대화동 6
 
1.8%
원흥동 6
 
1.8%
백석동 5
 
1.5%
성석동 5
 
1.5%
Other values (83) 104
31.5%
2024-04-06T17:23:40.693712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
264
19.1%
양 99
 
7.2%
동 89
 
6.4%
도 68
 
4.9%
경 66
 
4.8%
고 66
 
4.8%
시 66
 
4.8%
구 66
 
4.8%
기 66
 
4.8%
1 59
 
4.3%
Other values (54) 473
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 825
59.7%
Space Separator 264
 
19.1%
Decimal Number 260
 
18.8%
Dash Punctuation 33
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 99
12.0%
동 89
10.8%
도 68
8.2%
경 66
 
8.0%
고 66
 
8.0%
시 66
 
8.0%
구 66
 
8.0%
기 66
 
8.0%
산 38
 
4.6%
덕 34
 
4.1%
Other values (42) 167
20.2%
Decimal Number
ValueCountFrequency (%)
1 59
22.7%
2 34
13.1%
4 27
10.4%
3 25
9.6%
6 25
9.6%
8 22
 
8.5%
0 19
 
7.3%
7 18
 
6.9%
5 16
 
6.2%
9 15
 
5.8%
Space Separator
ValueCountFrequency (%)
264
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 825
59.7%
Common 557
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 99
12.0%
동 89
10.8%
도 68
8.2%
경 66
 
8.0%
고 66
 
8.0%
시 66
 
8.0%
구 66
 
8.0%
기 66
 
8.0%
산 38
 
4.6%
덕 34
 
4.1%
Other values (42) 167
20.2%
Common
ValueCountFrequency (%)
264
47.4%
1 59
 
10.6%
2 34
 
6.1%
- 33
 
5.9%
4 27
 
4.8%
3 25
 
4.5%
6 25
 
4.5%
8 22
 
3.9%
0 19
 
3.4%
7 18
 
3.2%
Other values (2) 31
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 825
59.7%
ASCII 557
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
264
47.4%
1 59
 
10.6%
2 34
 
6.1%
- 33
 
5.9%
4 27
 
4.8%
3 25
 
4.5%
6 25
 
4.5%
8 22
 
3.9%
0 19
 
3.4%
7 18
 
3.2%
Other values (2) 31
 
5.6%
Hangul
ValueCountFrequency (%)
양 99
12.0%
동 89
10.8%
도 68
8.2%
경 66
 
8.0%
고 66
 
8.0%
시 66
 
8.0%
구 66
 
8.0%
기 66
 
8.0%
산 38
 
4.6%
덕 34
 
4.1%
Other values (42) 167
20.2%

시설구분명
Categorical

Distinct4
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size660.0 B
민간시설
28 
공공시설
22 
정부지원시설
11 
자치단체자체시설
5 

Length

Max length8
Median length4
Mean length4.6363636
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row민간시설
2nd row공공시설
3rd row정부지원시설
4th row민간시설
5th row민간시설

Common Values

ValueCountFrequency (%)
민간시설 28
42.4%
공공시설 22
33.3%
정부지원시설 11
 
16.7%
자치단체자체시설 5
 
7.6%

Length

2024-04-06T17:23:41.054058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:23:41.326708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간시설 28
42.4%
공공시설 22
33.3%
정부지원시설 11
 
16.7%
자치단체자체시설 5
 
7.6%

시설명건물명정보
Text

UNIQUE 

Distinct66
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size660.0 B
2024-04-06T17:23:41.831236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length8.530303
Min length4

Characters and Unicode

Total characters563
Distinct characters158
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)100.0%

Sample

1st row123골프클럽
2nd rowNH인재개발원
3rd row가좌공원
4th row경성스폰지
5th row경일주류 (배상현)
ValueCountFrequency (%)
원흥역 6
 
6.2%
푸르지오 6
 
6.2%
2호공 6
 
6.2%
1호공 5
 
5.2%
3호공 4
 
4.1%
신고려관광 4
 
4.1%
농협대학 3
 
3.1%
중산힐스 3
 
3.1%
올림픽골프클럽 2
 
2.1%
4호공 2
 
2.1%
Other values (56) 56
57.7%
2024-04-06T17:23:42.658869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 43
 
7.6%
31
 
5.5%
) 27
 
4.8%
( 27
 
4.8%
원 24
 
4.3%
호 23
 
4.1%
지 13
 
2.3%
고 10
 
1.8%
역 9
 
1.6%
1 9
 
1.6%
Other values (148) 347
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 445
79.0%
Space Separator 31
 
5.5%
Decimal Number 28
 
5.0%
Close Punctuation 27
 
4.8%
Open Punctuation 27
 
4.8%
Uppercase Letter 4
 
0.7%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 43
 
9.7%
원 24
 
5.4%
호 23
 
5.2%
지 13
 
2.9%
고 10
 
2.2%
역 9
 
2.0%
산 8
 
1.8%
농 7
 
1.6%
한 7
 
1.6%
오 7
 
1.6%
Other values (133) 294
66.1%
Decimal Number
ValueCountFrequency (%)
1 9
32.1%
2 9
32.1%
3 5
17.9%
4 2
 
7.1%
6 1
 
3.6%
5 1
 
3.6%
7 1
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
H 1
25.0%
N 1
25.0%
I 1
25.0%
C 1
25.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 446
79.2%
Common 113
 
20.1%
Latin 4
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 43
 
9.6%
원 24
 
5.4%
호 23
 
5.2%
지 13
 
2.9%
고 10
 
2.2%
역 9
 
2.0%
산 8
 
1.8%
농 7
 
1.6%
한 7
 
1.6%
오 7
 
1.6%
Other values (134) 295
66.1%
Common
ValueCountFrequency (%)
31
27.4%
) 27
23.9%
( 27
23.9%
1 9
 
8.0%
2 9
 
8.0%
3 5
 
4.4%
4 2
 
1.8%
6 1
 
0.9%
5 1
 
0.9%
7 1
 
0.9%
Latin
ValueCountFrequency (%)
H 1
25.0%
N 1
25.0%
I 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 445
79.0%
ASCII 117
 
20.8%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 43
 
9.7%
원 24
 
5.4%
호 23
 
5.2%
지 13
 
2.9%
고 10
 
2.2%
역 9
 
2.0%
산 8
 
1.8%
농 7
 
1.6%
한 7
 
1.6%
오 7
 
1.6%
Other values (133) 294
66.1%
ASCII
ValueCountFrequency (%)
31
26.5%
) 27
23.1%
( 27
23.1%
1 9
 
7.7%
2 9
 
7.7%
3 5
 
4.3%
4 2
 
1.7%
6 1
 
0.9%
5 1
 
0.9%
7 1
 
0.9%
Other values (4) 4
 
3.4%
None
ValueCountFrequency (%)
㈜ 1
100.0%

Interactions

2024-04-06T17:23:26.127334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:19.651178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:20.958076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:22.510060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:23.709524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:24.878324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:26.313335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:19.876779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:21.511782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:22.692433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:23.898918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:25.073215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:26.507321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:20.102893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:21.743637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:22.904234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:24.106848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:25.305463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:26.698362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:20.296399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:21.929968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:23.143135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:24.287440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:25.519065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:26.920552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:20.506540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:22.119087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:23.364300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:24.461901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:25.723253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:27.151650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:20.723646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:22.309942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:23.521222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:24.680742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:23:25.933244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:23:42.885205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급수시설명인허가일자도로명우편번호소재지도로명주소소재지지번주소소재지우편번호위도경도좌표값(X)좌표값(Y)비상시설위치시설구분명시설명건물명정보
급수시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
인허가일자1.0001.0000.9820.9970.9970.9820.9610.9520.9620.9390.9970.9981.000
도로명우편번호1.0000.9821.0001.0001.0001.0000.8530.8440.8470.8291.0000.3771.000
소재지도로명주소1.0000.9971.0001.0000.9991.0000.9961.0000.9971.0000.9991.0001.000
소재지지번주소1.0000.9971.0000.9991.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호1.0000.9821.0001.0001.0001.0000.8530.8440.8470.8291.0000.3771.000
위도1.0000.9610.8530.9961.0000.8531.0000.7451.0000.7561.0000.5441.000
경도1.0000.9520.8441.0001.0000.8440.7451.0000.7621.0001.0000.2061.000
좌표값(X)1.0000.9620.8470.9971.0000.8471.0000.7621.0000.7731.0000.5411.000
좌표값(Y)1.0000.9390.8291.0001.0000.8290.7561.0000.7731.0001.0000.2491.000
비상시설위치1.0000.9971.0000.9991.0001.0001.0001.0001.0001.0001.0001.0001.000
시설구분명1.0000.9980.3771.0001.0000.3770.5440.2060.5410.2491.0001.0001.000
시설명건물명정보1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-04-06T17:23:43.232572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도로명우편번호소재지우편번호위도경도좌표값(X)좌표값(Y)시설구분명
도로명우편번호1.0001.000-0.7260.589-0.7270.5890.225
소재지우편번호1.0001.000-0.7260.589-0.7270.5890.225
위도-0.726-0.7261.000-0.3131.000-0.3130.336
경도0.5890.589-0.3131.000-0.3211.0000.109
좌표값(X)-0.727-0.7271.000-0.3211.000-0.3210.336
좌표값(Y)0.5890.589-0.3131.000-0.3211.0000.109
시설구분명0.2250.2250.3360.1090.3360.1091.000

Missing values

2024-04-06T17:23:27.456504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:23:28.212973image/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

시군명급수시설명인허가일자영업상태구분코드영업상태명소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호위도경도좌표값(X)좌표값(Y)비상시설위치시설구분명시설명건물명정보
0고양시123골프클럽2004-12-011영업/정상사용중10596경기도 고양시 덕양구 통일로 43-168 (동산동)경기도 고양시 덕양구 동산동 53-1241059637.641468126.906428460213.7964191742.4517경기도 고양시 덕양구 동산동 53-124민간시설123골프클럽
1고양시NH인재개발원2008-05-201영업/정상사용중10253경기도 고양시 일산동구 문원길 71 (설문동)경기도 고양시 일산동구 설문동 135-91025337.714606126.817347468342.1531183897.0866경기도 고양시 일산동구 설문동 135-9공공시설NH인재개발원
2고양시가좌공원2007-04-021영업/정상사용중10210경기도 고양시 일산서구 송산로 387-17 비상급수시설경기도 고양시 일산서구 가좌동 10981021037.686199126.721681465210.2842175453.6983경기도 고양시 일산서구 가좌동 1098정부지원시설가좌공원
3고양시경성스폰지2005-07-081영업/정상사용중10257경기도 고양시 일산동구 문원길 9-6 (문봉동)경기도 고양시 일산동구 문봉동 190-221025737.708203126.821365467630.8472184249.9721경기도 고양시 일산동구 문봉동 190-22민간시설경성스폰지
4고양시경일주류 (배상현)2021-10-281영업/정상사용중10455경기도 고양시 덕양구 호국로 571-33 (화정동)경기도 고양시 덕양구 화정동 809-11045537.639347126.823817459988.8889184451.772경기도 고양시 덕양구 화정동 809-1민간시설경일주류 (배상현)
5고양시고양농산물유통센터2005-06-141영업/정상사용중10226경기도 고양시 일산서구 대화로 362 (대화동)경기도 고양시 일산서구 대화동 23241022637.682904126.748662464837.875177832.2679경기도 고양시 일산서구 대화동 2324공공시설고양농산물유통센터
6고양시고양송암고등학교2008-05-161영업/정상사용중10246경기도 고양시 일산동구 고봉로531번길 67-13 (성석동)경기도 고양시 일산동구 성석동 1457-111024637.705878126.778599467380.8614180478.7587경기도 고양시 일산동구 성석동 1457-11공공시설고양송암고등학교
7고양시고양어울림누리2021-10-241영업/정상사용중10471경기도 고양시 덕양구 어울림로 33 (성사동)경기도 고양시 덕양구 성사동 7771047137.649066126.835405461065.6357185476.2948경기도 고양시 덕양구 성사동 777공공시설고양어울림누리
8고양시고양컨트리클럽㈜ (2호공)2019-07-291영업/정상사용중10553경기도 고양시 덕양구 흥도로 304-23 (도내동, 고양컨트리클럽)경기도 고양시 덕양구 도내동 457-11055337.63569126.857561459578.0247187429.0648경기도 고양시 덕양구 도내동 457-1민간시설고양컨트리클럽㈜ (2호공)
9고양시고일주유소2008-05-131영업/정상사용중10308경기도 고양시 일산동구 백마로 455 (풍동)경기도 고양시 일산동구 풍동 8401030837.661472126.79865462448.7324182236.1031경기도 고양시 일산동구 풍동 840민간시설고일주유소
시군명급수시설명인허가일자영업상태구분코드영업상태명소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호위도경도좌표값(X)좌표값(Y)비상시설위치시설구분명시설명건물명정보
56고양시탄현마을7단지2008-01-041영업/정상사용중10249경기도 고양시 일산서구 탄현로 64 (탄현동)경기도 고양시 일산서구 탄현동 14801024937.697179126.769945466417.3201179713.3083경기도 고양시 일산서구 탄현동 1480공공시설탄현마을7단지
57고양시평양막국수초계탕2005-05-161영업/정상사용중10368경기도 고양시 일산서구 성저로38번길 71 (대화동)경기도 고양시 일산서구 대화동 2046-61036837.68331126.755882464881.2833178469.1936경기도 고양시 일산서구 대화동 2046-6민간시설평양막국수초계탕
58고양시필리핀참전비1996-12-101영업/정상사용중10282경기도 고양시 덕양구 통일로 686 비상급수시설경기도 고양시 덕양구 대자동 11701028237.688307126.874558465415.2584188936.9926경기도 고양시 덕양구 대자동 1170정부지원시설필리핀참전비
59고양시한국가스공사 서울지역본부2021-11-201영업/정상사용중10439경기도 고양시 덕양구 호국로 112 (행주외동)경기도 고양시 덕양구 행주외동 282-21043937.606138126.818933456304.318184013.6236경기도 고양시 덕양구 행주외동 282-2공공시설한국가스공사 서울지역본부
60고양시한국지역난방공사(1호공)2007-11-141영업/정상사용중10443경기도 고양시 일산동구 경의로 149 (백석동)경기도 고양시 일산동구 백석동 11431044337.645272126.79963460650.7372182318.718경기도 고양시 일산동구 백석동 1143공공시설한국지역난방공사(1호공)
61고양시한국지역난방공사(2호공)2007-11-141영업/정상사용중10443경기도 고양시 일산동구 경의로 149 (백석동)경기도 고양시 일산동구 백석동 11431044337.645272126.79963460650.7372182318.718경기도 고양시 일산동구 백석동 1143공공시설한국지역난방공사(2호공)
62고양시한뫼공원1996-12-271영업/정상사용중10339경기도 고양시 일산서구 탄중로 284 비상급수시설경기도 고양시 일산서구 일산동 15581033937.69355126.776287466013.193180271.6032경기도 고양시 일산서구 일산동 1558정부지원시설한뫼공원
63고양시한우물숲길공원2019-12-301영업/정상사용중10579경기도 고양시 덕양구 큰골길 4 비상급수시설경기도 고양시 덕양구 오금동 5841057937.664515126.895847462772.5354190811.5715경기도 고양시 덕양구 오금동 584자치단체자체시설한우물숲길공원
64고양시영농조합법인한국농원2022-12-011영업/정상사용중10252고양시 일산동구 은마길151번길 45 (설문동)경기도 고양시 일산동구 설문동 4781025237.719022126.804158468834.5973182735.3809경기도 고양시 일산동구 설문동 478민간시설영농조합법인한국농원
65고양시덕진수산 영어조합법인2022-12-011영업/정상사용중10246경기도 고양시 일산동구 고봉로 467-48 (성석동)경기도 고양시 일산동구 성석동 1306-121024637.70151126.77895466896.7888180508.5277경기도 고양시 일산동구 성석동 1306-12민간시설덕진수산 영어조합법인