Overview

Dataset statistics

Number of variables11
Number of observations31
Missing cells60
Missing cells (%)17.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory96.3 B

Variable types

Categorical2
Text5
Numeric4

Dataset

Description광주광역시 북구 비상급수시설 현황(시설명, 시설구분, 주소, 설치년도, 심도, 음용수, 생활용수, 관리기관명, 데이터기준일자)를 제공합니다.
Author광주광역시 북구
URLhttps://www.data.go.kr/data/15023810/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
설치년도 is highly overall correlated with 심도 and 2 other fieldsHigh correlation
심도 is highly overall correlated with 설치년도 and 1 other fieldsHigh correlation
음용수 is highly overall correlated with 설치년도 and 2 other fieldsHigh correlation
생활용수 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 설치년도 and 2 other fieldsHigh correlation
음용수 has 20 (64.5%) missing valuesMissing
생활용수 has 11 (35.5%) missing valuesMissing
비고 has 29 (93.5%) missing valuesMissing
시설명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
소재지지번주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:59:24.754136
Analysis finished2023-12-12 01:59:27.297866
Duration2.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
공공용시설
16 
정부지원시설
15 

Length

Max length6
Median length5
Mean length5.483871
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공공용시설 16
51.6%
정부지원시설 15
48.4%

Length

2023-12-12T10:59:27.374459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:59:27.471837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용시설 16
51.6%
정부지원시설 15
48.4%

시설명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T10:59:27.688249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length7.2258065
Min length4

Characters and Unicode

Total characters224
Distinct characters106
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row수창초등학교
2nd row기아챔피언스필드
3rd row한화꿈에그린아파트
4th row용봉동 용주공원
5th row벽산블루밍메가씨티아파트
ValueCountFrequency (%)
수창초등학교 1
 
2.9%
국제고등학교 1
 
2.9%
광주애육원 1
 
2.9%
중소기업진흥공단 1
 
2.9%
호남연수원 1
 
2.9%
각화초등학교 1
 
2.9%
경신여자고등학교 1
 
2.9%
풍향초등학교 1
 
2.9%
고려고등학교 1
 
2.9%
기아챔피언스필드 1
 
2.9%
Other values (24) 24
70.6%
2023-12-12T10:59:28.081234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
등 10
 
4.5%
학 9
 
4.0%
교 9
 
4.0%
원 9
 
4.0%
공 8
 
3.6%
고 6
 
2.7%
아 6
 
2.7%
트 5
 
2.2%
린 5
 
2.2%
파 5
 
2.2%
Other values (96) 152
67.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 216
96.4%
Space Separator 3
 
1.3%
Open Punctuation 2
 
0.9%
Close Punctuation 2
 
0.9%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
등 10
 
4.6%
학 9
 
4.2%
교 9
 
4.2%
원 9
 
4.2%
공 8
 
3.7%
고 6
 
2.8%
아 6
 
2.8%
트 5
 
2.3%
린 5
 
2.3%
파 5
 
2.3%
Other values (92) 144
66.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 216
96.4%
Common 8
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
등 10
 
4.6%
학 9
 
4.2%
교 9
 
4.2%
원 9
 
4.2%
공 8
 
3.7%
고 6
 
2.8%
아 6
 
2.8%
트 5
 
2.3%
린 5
 
2.3%
파 5
 
2.3%
Other values (92) 144
66.7%
Common
ValueCountFrequency (%)
3
37.5%
( 2
25.0%
) 2
25.0%
3 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 216
96.4%
ASCII 8
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
등 10
 
4.6%
학 9
 
4.2%
교 9
 
4.2%
원 9
 
4.2%
공 8
 
3.7%
고 6
 
2.8%
아 6
 
2.8%
트 5
 
2.3%
린 5
 
2.3%
파 5
 
2.3%
Other values (92) 144
66.7%
ASCII
ValueCountFrequency (%)
3
37.5%
( 2
25.0%
) 2
25.0%
3 1
 
12.5%

소재지도로명주소
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T10:59:28.351067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length22.322581
Min length17

Characters and Unicode

Total characters692
Distinct characters76
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row광주광역시 북구 금남로 99(중앙동)
2nd row광주광역시 북구 서림로 10(임동)
3rd row광주광역시 북구 용주로30번길 60(용봉동)
4th row광주광역시 북구 용봉동 1214
5th row광주광역시 북구 서강로54번길 50(운암동)
ValueCountFrequency (%)
광주광역시 31
24.6%
북구 31
24.6%
29(오치동 2
 
1.6%
설죽로 2
 
1.6%
하서로 2
 
1.6%
면앙로 2
 
1.6%
10 1
 
0.8%
각화동 1
 
0.8%
433(삼각동 1
 
0.8%
각화대로39번길 1
 
0.8%
Other values (52) 52
41.3%
2023-12-12T10:59:28.765971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
95
 
13.7%
광 62
 
9.0%
동 34
 
4.9%
북 33
 
4.8%
주 32
 
4.6%
역 31
 
4.5%
시 31
 
4.5%
구 31
 
4.5%
) 29
 
4.2%
( 29
 
4.2%
Other values (66) 285
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 432
62.4%
Decimal Number 105
 
15.2%
Space Separator 95
 
13.7%
Close Punctuation 29
 
4.2%
Open Punctuation 29
 
4.2%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 62
14.4%
동 34
 
7.9%
북 33
 
7.6%
주 32
 
7.4%
역 31
 
7.2%
시 31
 
7.2%
구 31
 
7.2%
로 28
 
6.5%
길 16
 
3.7%
번 14
 
3.2%
Other values (52) 120
27.8%
Decimal Number
ValueCountFrequency (%)
0 17
16.2%
1 14
13.3%
2 14
13.3%
4 12
11.4%
5 10
9.5%
7 10
9.5%
3 10
9.5%
6 7
6.7%
9 7
6.7%
8 4
 
3.8%
Space Separator
ValueCountFrequency (%)
95
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 432
62.4%
Common 260
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 62
14.4%
동 34
 
7.9%
북 33
 
7.6%
주 32
 
7.4%
역 31
 
7.2%
시 31
 
7.2%
구 31
 
7.2%
로 28
 
6.5%
길 16
 
3.7%
번 14
 
3.2%
Other values (52) 120
27.8%
Common
ValueCountFrequency (%)
95
36.5%
) 29
 
11.2%
( 29
 
11.2%
0 17
 
6.5%
1 14
 
5.4%
2 14
 
5.4%
4 12
 
4.6%
5 10
 
3.8%
7 10
 
3.8%
3 10
 
3.8%
Other values (4) 20
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 432
62.4%
ASCII 260
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
95
36.5%
) 29
 
11.2%
( 29
 
11.2%
0 17
 
6.5%
1 14
 
5.4%
2 14
 
5.4%
4 12
 
4.6%
5 10
 
3.8%
7 10
 
3.8%
3 10
 
3.8%
Other values (4) 20
 
7.7%
Hangul
ValueCountFrequency (%)
광 62
14.4%
동 34
 
7.9%
북 33
 
7.6%
주 32
 
7.4%
역 31
 
7.2%
시 31
 
7.2%
구 31
 
7.2%
로 28
 
6.5%
길 16
 
3.7%
번 14
 
3.2%
Other values (52) 120
27.8%

소재지지번주소
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T10:59:29.041640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length17.451613
Min length15

Characters and Unicode

Total characters541
Distinct characters51
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

Unique31 ?
Unique (%)100.0%

Sample

1st row광주광역시 북구 북동 102
2nd row광주광역시 북구 임동 316
3rd row광주광역시 북구 용봉동 1468
4th row광주광역시 북구 용봉동 1214
5th row광주광역시 북구 운암동 68
ValueCountFrequency (%)
광주광역시 31
24.8%
북구 31
24.8%
운암동 4
 
3.2%
두암동 4
 
3.2%
용봉동 3
 
2.4%
오치동 2
 
1.6%
문흥동 2
 
1.6%
삼각동 2
 
1.6%
479-1 1
 
0.8%
장등동 1
 
0.8%
Other values (44) 44
35.2%
2023-12-12T10:59:29.595659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
94
17.4%
광 62
11.5%
동 32
 
5.9%
북 32
 
5.9%
구 31
 
5.7%
1 31
 
5.7%
주 31
 
5.7%
시 31
 
5.7%
역 31
 
5.7%
- 19
 
3.5%
Other values (41) 147
27.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 311
57.5%
Decimal Number 117
 
21.6%
Space Separator 94
 
17.4%
Dash Punctuation 19
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 62
19.9%
동 32
10.3%
북 32
10.3%
구 31
10.0%
주 31
10.0%
시 31
10.0%
역 31
10.0%
암 8
 
2.6%
용 5
 
1.6%
두 4
 
1.3%
Other values (29) 44
14.1%
Decimal Number
ValueCountFrequency (%)
1 31
26.5%
2 16
13.7%
4 15
12.8%
6 11
 
9.4%
8 11
 
9.4%
7 10
 
8.5%
9 7
 
6.0%
3 7
 
6.0%
5 6
 
5.1%
0 3
 
2.6%
Space Separator
ValueCountFrequency (%)
94
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 311
57.5%
Common 230
42.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 62
19.9%
동 32
10.3%
북 32
10.3%
구 31
10.0%
주 31
10.0%
시 31
10.0%
역 31
10.0%
암 8
 
2.6%
용 5
 
1.6%
두 4
 
1.3%
Other values (29) 44
14.1%
Common
ValueCountFrequency (%)
94
40.9%
1 31
 
13.5%
- 19
 
8.3%
2 16
 
7.0%
4 15
 
6.5%
6 11
 
4.8%
8 11
 
4.8%
7 10
 
4.3%
9 7
 
3.0%
3 7
 
3.0%
Other values (2) 9
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 311
57.5%
ASCII 230
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
94
40.9%
1 31
 
13.5%
- 19
 
8.3%
2 16
 
7.0%
4 15
 
6.5%
6 11
 
4.8%
8 11
 
4.8%
7 10
 
4.3%
9 7
 
3.0%
3 7
 
3.0%
Other values (2) 9
 
3.9%
Hangul
ValueCountFrequency (%)
광 62
19.9%
동 32
10.3%
북 32
10.3%
구 31
10.0%
주 31
10.0%
시 31
10.0%
역 31
10.0%
암 8
 
2.6%
용 5
 
1.6%
두 4
 
1.3%
Other values (29) 44
14.1%

설치년도
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)58.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1990.6452
Minimum1977
Maximum2006
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T10:59:29.773273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1977
5-th percentile1982
Q11984
median1993
Q31995.5
95-th percentile2001.5
Maximum2006
Range29
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.3509563
Coefficient of variation (CV)0.0036927507
Kurtosis-0.90857762
Mean1990.6452
Median Absolute Deviation (MAD)6
Skewness0.13671477
Sum61710
Variance54.036559
MonotonicityNot monotonic
2023-12-12T10:59:29.930456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1994 6
19.4%
1982 4
12.9%
1983 3
 
9.7%
1985 2
 
6.5%
1986 2
 
6.5%
1999 2
 
6.5%
1988 1
 
3.2%
2006 1
 
3.2%
1993 1
 
3.2%
1996 1
 
3.2%
Other values (8) 8
25.8%
ValueCountFrequency (%)
1977 1
 
3.2%
1982 4
12.9%
1983 3
9.7%
1985 2
 
6.5%
1986 2
 
6.5%
1987 1
 
3.2%
1988 1
 
3.2%
1989 1
 
3.2%
1993 1
 
3.2%
1994 6
19.4%
ValueCountFrequency (%)
2006 1
 
3.2%
2003 1
 
3.2%
2000 1
 
3.2%
1999 2
 
6.5%
1998 1
 
3.2%
1997 1
 
3.2%
1996 1
 
3.2%
1995 1
 
3.2%
1994 6
19.4%
1993 1
 
3.2%

심도
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)51.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.3871
Minimum17
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T10:59:30.104189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile56
Q180
median82
Q3118
95-th percentile185
Maximum200
Range183
Interquartile range (IQR)38

Descriptive statistics

Standard deviation39.892086
Coefficient of variation (CV)0.3973826
Kurtosis1.3356719
Mean100.3871
Median Absolute Deviation (MAD)18
Skewness0.9239941
Sum3112
Variance1591.3785
MonotonicityNot monotonic
2023-12-12T10:59:30.276416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
80 9
29.0%
100 5
16.1%
82 2
 
6.5%
120 2
 
6.5%
200 2
 
6.5%
150 1
 
3.2%
170 1
 
3.2%
130 1
 
3.2%
110 1
 
3.2%
140 1
 
3.2%
Other values (6) 6
19.4%
ValueCountFrequency (%)
17 1
 
3.2%
52 1
 
3.2%
60 1
 
3.2%
68 1
 
3.2%
75 1
 
3.2%
80 9
29.0%
82 2
 
6.5%
100 5
16.1%
110 1
 
3.2%
116 1
 
3.2%
ValueCountFrequency (%)
200 2
 
6.5%
170 1
 
3.2%
150 1
 
3.2%
140 1
 
3.2%
130 1
 
3.2%
120 2
 
6.5%
116 1
 
3.2%
110 1
 
3.2%
100 5
16.1%
82 2
 
6.5%

음용수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6
Distinct (%)54.5%
Missing20
Missing (%)64.5%
Infinite0
Infinite (%)0.0%
Mean342
Minimum100
Maximum600
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T10:59:30.442384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile100
Q1150
median400
Q3550
95-th percentile600
Maximum600
Range500
Interquartile range (IQR)400

Descriptive statistics

Standard deviation212.04716
Coefficient of variation (CV)0.62002095
Kurtosis-2.0579152
Mean342
Median Absolute Deviation (MAD)200
Skewness0.056433161
Sum3762
Variance44964
MonotonicityNot monotonic
2023-12-12T10:59:30.607033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
600 2
 
6.5%
550 2
 
6.5%
400 2
 
6.5%
100 2
 
6.5%
150 2
 
6.5%
162 1
 
3.2%
(Missing) 20
64.5%
ValueCountFrequency (%)
100 2
6.5%
150 2
6.5%
162 1
3.2%
400 2
6.5%
550 2
6.5%
600 2
6.5%
ValueCountFrequency (%)
600 2
6.5%
550 2
6.5%
400 2
6.5%
162 1
3.2%
150 2
6.5%
100 2
6.5%

생활용수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)65.0%
Missing11
Missing (%)35.5%
Infinite0
Infinite (%)0.0%
Mean383.75
Minimum100
Maximum650
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T10:59:30.755482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile114.25
Q1237.5
median350
Q3600
95-th percentile650
Maximum650
Range550
Interquartile range (IQR)362.5

Descriptive statistics

Standard deviation198.48687
Coefficient of variation (CV)0.51722964
Kurtosis-1.6380235
Mean383.75
Median Absolute Deviation (MAD)195
Skewness0.064854177
Sum7675
Variance39397.039
MonotonicityNot monotonic
2023-12-12T10:59:30.906042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
600 5
16.1%
650 2
 
6.5%
400 2
 
6.5%
250 2
 
6.5%
500 1
 
3.2%
300 1
 
3.2%
270 1
 
3.2%
115 1
 
3.2%
280 1
 
3.2%
130 1
 
3.2%
Other values (3) 3
 
9.7%
(Missing) 11
35.5%
ValueCountFrequency (%)
100 1
3.2%
115 1
3.2%
130 1
3.2%
180 1
3.2%
200 1
3.2%
250 2
6.5%
270 1
3.2%
280 1
3.2%
300 1
3.2%
400 2
6.5%
ValueCountFrequency (%)
650 2
 
6.5%
600 5
16.1%
500 1
 
3.2%
400 2
 
6.5%
300 1
 
3.2%
280 1
 
3.2%
270 1
 
3.2%
250 2
 
6.5%
200 1
 
3.2%
180 1
 
3.2%

관리기관명
Text

Distinct26
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T10:59:31.168070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length18.322581
Min length16

Characters and Unicode

Total characters568
Distinct characters47
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

Unique21 ?
Unique (%)67.7%

Sample

1st row광주광역시 북구 중앙동행정복지센터
2nd row광주광역시 북구 임동행정복지센터
3rd row광주광역시 북구 용봉동행정복지센터
4th row광주광역시 북구 용봉동행정복지센터
5th row광주광역시 북구 운암1동행정복지센터
ValueCountFrequency (%)
광주광역시 31
33.3%
북구 31
33.3%
용봉동행정복지센터 2
 
2.2%
두암2동행정복지센터 2
 
2.2%
건국동행정복지센터 2
 
2.2%
삼각동행정복지센터 2
 
2.2%
운암2동행정복지센터 2
 
2.2%
두암3동행정복지센터 1
 
1.1%
일곡동행정복지센터 1
 
1.1%
문흥1동행정복지센터 1
 
1.1%
Other values (18) 18
19.4%
2023-12-12T10:59:31.632438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
광 62
 
10.9%
62
 
10.9%
동 32
 
5.6%
주 32
 
5.6%
시 31
 
5.5%
북 31
 
5.5%
구 31
 
5.5%
역 31
 
5.5%
센 31
 
5.5%
터 31
 
5.5%
Other values (37) 194
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 493
86.8%
Space Separator 62
 
10.9%
Decimal Number 13
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 62
12.6%
동 32
 
6.5%
주 32
 
6.5%
시 31
 
6.3%
북 31
 
6.3%
구 31
 
6.3%
역 31
 
6.3%
센 31
 
6.3%
터 31
 
6.3%
행 30
 
6.1%
Other values (33) 151
30.6%
Decimal Number
ValueCountFrequency (%)
2 7
53.8%
1 4
30.8%
3 2
 
15.4%
Space Separator
ValueCountFrequency (%)
62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 493
86.8%
Common 75
 
13.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 62
12.6%
동 32
 
6.5%
주 32
 
6.5%
시 31
 
6.3%
북 31
 
6.3%
구 31
 
6.3%
역 31
 
6.3%
센 31
 
6.3%
터 31
 
6.3%
행 30
 
6.1%
Other values (33) 151
30.6%
Common
ValueCountFrequency (%)
62
82.7%
2 7
 
9.3%
1 4
 
5.3%
3 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 493
86.8%
ASCII 75
 
13.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
광 62
12.6%
동 32
 
6.5%
주 32
 
6.5%
시 31
 
6.3%
북 31
 
6.3%
구 31
 
6.3%
역 31
 
6.3%
센 31
 
6.3%
터 31
 
6.3%
행 30
 
6.1%
Other values (33) 151
30.6%
ASCII
ValueCountFrequency (%)
62
82.7%
2 7
 
9.3%
1 4
 
5.3%
3 2
 
2.7%

비고
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing29
Missing (%)93.5%
Memory size380.0 B
2023-12-12T10:59:31.817508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters22
Distinct characters9
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

Unique2 ?
Unique (%)100.0%

Sample

1st row2023년 2월 폐공
2nd row2023년 7월 폐공
ValueCountFrequency (%)
2023년 2
33.3%
폐공 2
33.3%
2월 1
16.7%
7월 1
16.7%
2023-12-12T10:59:32.078897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 5
22.7%
4
18.2%
0 2
 
9.1%
3 2
 
9.1%
년 2
 
9.1%
월 2
 
9.1%
폐 2
 
9.1%
공 2
 
9.1%
7 1
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
45.5%
Other Letter 8
36.4%
Space Separator 4
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5
50.0%
0 2
 
20.0%
3 2
 
20.0%
7 1
 
10.0%
Other Letter
ValueCountFrequency (%)
년 2
25.0%
월 2
25.0%
폐 2
25.0%
공 2
25.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14
63.6%
Hangul 8
36.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2 5
35.7%
4
28.6%
0 2
 
14.3%
3 2
 
14.3%
7 1
 
7.1%
Hangul
ValueCountFrequency (%)
년 2
25.0%
월 2
25.0%
폐 2
25.0%
공 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
63.6%
Hangul 8
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 5
35.7%
4
28.6%
0 2
 
14.3%
3 2
 
14.3%
7 1
 
7.1%
Hangul
ValueCountFrequency (%)
년 2
25.0%
월 2
25.0%
폐 2
25.0%
공 2
25.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-09-04
31 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-04
2nd row2023-09-04
3rd row2023-09-04
4th row2023-09-04
5th row2023-09-04

Common Values

ValueCountFrequency (%)
2023-09-04 31
100.0%

Length

2023-12-12T10:59:32.230951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:59:32.339461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-04 31
100.0%

Interactions

2023-12-12T10:59:26.425380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:25.207920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:25.639669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:26.020654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:26.518888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:25.319611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:25.741157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:26.120919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:26.640894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:25.442337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:25.839788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:26.237202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:26.749304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:25.555406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:25.929913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:59:26.338405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:59:32.425327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시설명소재지도로명주소소재지지번주소설치년도심도음용수생활용수관리기관명비고
구분1.0001.0001.0001.0000.6360.6340.7090.6950.936NaN
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0000.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0000.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0000.000
설치년도0.6361.0001.0001.0001.0000.7480.8850.2860.7780.000
심도0.6341.0001.0001.0000.7481.0000.8460.0000.5040.000
음용수0.7091.0001.0001.0000.8850.8461.000NaN1.000NaN
생활용수0.6951.0001.0001.0000.2860.000NaN1.0000.8010.000
관리기관명0.9361.0001.0001.0000.7780.5041.0000.8011.0000.000
비고NaN0.0000.0000.0000.0000.000NaN0.0000.0001.000
2023-12-12T10:59:32.586809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도심도음용수생활용수구분
설치년도1.0000.746-0.633-0.2970.543
심도0.7461.000-0.696-0.4140.409
음용수-0.633-0.6961.000NaN0.680
생활용수-0.297-0.414NaN1.0000.633
구분0.5430.4090.6800.6331.000

Missing values

2023-12-12T10:59:26.900495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:59:27.093895image/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.
2023-12-12T10:59:27.220095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

구분시설명소재지도로명주소소재지지번주소설치년도심도음용수생활용수관리기관명비고데이터기준일자
0정부지원시설수창초등학교광주광역시 북구 금남로 99(중앙동)광주광역시 북구 북동 102198582<NA>500광주광역시 북구 중앙동행정복지센터2023년 2월 폐공2023-09-04
1정부지원시설기아챔피언스필드광주광역시 북구 서림로 10(임동)광주광역시 북구 임동 316198380600<NA>광주광역시 북구 임동행정복지센터<NA>2023-09-04
2정부지원시설한화꿈에그린아파트광주광역시 북구 용주로30번길 60(용봉동)광주광역시 북구 용봉동 1468198380550<NA>광주광역시 북구 용봉동행정복지센터<NA>2023-09-04
3정부지원시설용봉동 용주공원광주광역시 북구 용봉동 1214광주광역시 북구 용봉동 1214198682<NA>650광주광역시 북구 용봉동행정복지센터<NA>2023-09-04
4정부지원시설벽산블루밍메가씨티아파트광주광역시 북구 서강로54번길 50(운암동)광주광역시 북구 운암동 68198252<NA>600광주광역시 북구 운암1동행정복지센터<NA>2023-09-04
5정부지원시설동운초등학교광주광역시 북구 북문대로8번길 21(운암동)광주광역시 북구 운암동 484197717400<NA>광주광역시 북구 운암2동행정복지센터<NA>2023-09-04
6정부지원시설중외공원광주광역시 북구 하서로 72(운암동)광주광역시 북구 운암동 172198968<NA>600광주광역시 북구 운암3동행정복지센터<NA>2023-09-04
7정부지원시설풍향동고지대광주광역시 북구 두방길 50-1(풍향동)광주광역시 북구 풍향동 474-1198280<NA>400광주광역시 북구 풍향동행정복지센터<NA>2023-09-04
8정부지원시설무등도서관광주광역시 북구 면앙로 130(우산동)광주광역시 북구 우산동 213-4198360<NA>600광주광역시 북구 우산동행정복지센터<NA>2023-09-04
9정부지원시설미라보아파트앞광주광역시 북구 면앙로 208-3(두암동)광주광역시 북구 두암동 812-1198280400<NA>광주광역시 북구 두암2동행정복지센터<NA>2023-09-04
구분시설명소재지도로명주소소재지지번주소설치년도심도음용수생활용수관리기관명비고데이터기준일자
21공공용시설풍향초등학교광주광역시 북구 군왕로51번길 77(두암동)광주광역시 북구 두암동 8001994100150<NA>광주광역시 북구 두암1동행정복지센터<NA>2023-09-04
22공공용시설국제고등학교광주광역시 북구 설죽로 433(삼각동)광주광역시 북구 삼각동 479-11995200<NA>250광주광역시 북구 삼각동행정복지센터<NA>2023-09-04
23공공용시설고려고등학교광주광역시 북구 설죽로 369(삼각동)광주광역시 북구 삼각동 666199480<NA>280광주광역시 북구 삼각동행정복지센터<NA>2023-09-04
24공공용시설일곡중학교광주광역시 북구 설죽로570(일곡동)광주광역시 북구 일곡동 818-11996130<NA>130광주광역시 북구 일곡동행정복지센터<NA>2023-09-04
25공공용시설문흥동현대아파트광주광역시 북구 대천로 160(문흥동)광주광역시 북구 문흥동 971-11994100<NA>650광주광역시 북구 문흥1동행정복지센터<NA>2023-09-04
26공공용시설국제온천광주광역시 북구 호동로75번길 3(문흥동)광주광역시 북구 문흥동 734-41999100<NA>200광주광역시 북구 문흥2동행정복지센터<NA>2023-09-04
27공공용시설남흥대중사우나광주광역시 북구 밤실로 172(두암동)광주광역시 북구 두암동 277-22199380<NA>180광주광역시 북구 두암3동행정복지센터<NA>2023-09-04
28공공용시설부영사우나광주광역시 북구 하백로6번길 20(매곡동)광주광역시 북구 매곡동 45-221994170<NA>100광주광역시 북구 매곡동행정복지센터<NA>2023-09-04
29공공용시설씨너스사우나광주광역시 북구 우치로 60 (중흥동)광주광역시 북구 중흥동 362-122006120162<NA>광주광역시 북구 중흥2동행정복지센터<NA>2023-09-04
30공공용시설용두주공아파트광주광역시 북구 임방울대로1041번길 15(신용동)광주광역시 북구 신용동 643-11999100100<NA>광주광역시 북구 신용동행정복지센터<NA>2023-09-04