Overview

Dataset statistics

Number of variables5
Number of observations108
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory43.2 B

Variable types

Numeric2
Text2
Categorical1

Dataset

Description대전광역시 유성구 개방화장실 현황에 대한 데이터로 시설물 이름, 주소, 설치년도, 화장실 유형 등의 항목을 제공합니다.
Author대전광역시 유성구
URLhttps://www.data.go.kr/data/15108943/fileData.do

Alerts

번호 has unique valuesUnique
시설물이름 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:00:29.974965
Analysis finished2023-12-12 06:00:31.050938
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1074.8611
Minimum854
Maximum1351
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T15:00:31.133113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum854
5-th percentile866.4
Q1933
median1045.5
Q31216.25
95-th percentile1310.9
Maximum1351
Range497
Interquartile range (IQR)283.25

Descriptive statistics

Standard deviation153.94825
Coefficient of variation (CV)0.14322618
Kurtosis-1.422661
Mean1074.8611
Median Absolute Deviation (MAD)144
Skewness0.14456259
Sum116085
Variance23700.065
MonotonicityNot monotonic
2023-12-12T15:00:31.287616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
854 1
 
0.9%
1178 1
 
0.9%
1215 1
 
0.9%
1214 1
 
0.9%
1212 1
 
0.9%
1210 1
 
0.9%
1209 1
 
0.9%
1208 1
 
0.9%
1187 1
 
0.9%
1185 1
 
0.9%
Other values (98) 98
90.7%
ValueCountFrequency (%)
854 1
0.9%
856 1
0.9%
862 1
0.9%
863 1
0.9%
864 1
0.9%
865 1
0.9%
869 1
0.9%
870 1
0.9%
871 1
0.9%
874 1
0.9%
ValueCountFrequency (%)
1351 1
0.9%
1329 1
0.9%
1325 1
0.9%
1318 1
0.9%
1317 1
0.9%
1313 1
0.9%
1307 1
0.9%
1294 1
0.9%
1293 1
0.9%
1289 1
0.9%

시설물이름
Text

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-12T15:00:31.617796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length6.3796296
Min length2

Characters and Unicode

Total characters689
Distinct characters184
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)100.0%

Sample

1st row투유1차
2nd row위드리버
3rd row투유2차
4th row노블레스3
5th row봉명씨티빌
ValueCountFrequency (%)
투유1차 1
 
0.9%
대성주유소 1
 
0.9%
강변오일뱅크 1
 
0.9%
주)공항하이웨이주슈소 1
 
0.9%
유성ic주유소 1
 
0.9%
유성ic충전소 1
 
0.9%
위성주유소 1
 
0.9%
mlb 1
 
0.9%
밀레대전점 1
 
0.9%
하이마트유성점 1
 
0.9%
Other values (99) 99
90.8%
2023-12-12T15:00:32.131719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 62
 
9.0%
소 58
 
8.4%
주 57
 
8.3%
S 18
 
2.6%
성 17
 
2.5%
스 15
 
2.2%
대 14
 
2.0%
전 12
 
1.7%
K 10
 
1.5%
교 9
 
1.3%
Other values (174) 417
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 620
90.0%
Uppercase Letter 47
 
6.8%
Decimal Number 8
 
1.2%
Open Punctuation 6
 
0.9%
Close Punctuation 6
 
0.9%
Space Separator 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 62
 
10.0%
소 58
 
9.4%
주 57
 
9.2%
성 17
 
2.7%
스 15
 
2.4%
대 14
 
2.3%
전 12
 
1.9%
교 9
 
1.5%
회 9
 
1.5%
동 9
 
1.5%
Other values (159) 358
57.7%
Uppercase Letter
ValueCountFrequency (%)
S 18
38.3%
K 10
21.3%
G 9
19.1%
C 3
 
6.4%
I 3
 
6.4%
B 2
 
4.3%
L 1
 
2.1%
M 1
 
2.1%
Decimal Number
ValueCountFrequency (%)
1 4
50.0%
2 3
37.5%
3 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 620
90.0%
Latin 47
 
6.8%
Common 22
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 62
 
10.0%
소 58
 
9.4%
주 57
 
9.2%
성 17
 
2.7%
스 15
 
2.4%
대 14
 
2.3%
전 12
 
1.9%
교 9
 
1.5%
회 9
 
1.5%
동 9
 
1.5%
Other values (159) 358
57.7%
Latin
ValueCountFrequency (%)
S 18
38.3%
K 10
21.3%
G 9
19.1%
C 3
 
6.4%
I 3
 
6.4%
B 2
 
4.3%
L 1
 
2.1%
M 1
 
2.1%
Common
ValueCountFrequency (%)
( 6
27.3%
) 6
27.3%
1 4
18.2%
2 3
13.6%
3 1
 
4.5%
1
 
4.5%
& 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 620
90.0%
ASCII 69
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 62
 
10.0%
소 58
 
9.4%
주 57
 
9.2%
성 17
 
2.7%
스 15
 
2.4%
대 14
 
2.3%
전 12
 
1.9%
교 9
 
1.5%
회 9
 
1.5%
동 9
 
1.5%
Other values (159) 358
57.7%
ASCII
ValueCountFrequency (%)
S 18
26.1%
K 10
14.5%
G 9
13.0%
( 6
 
8.7%
) 6
 
8.7%
1 4
 
5.8%
C 3
 
4.3%
I 3
 
4.3%
2 3
 
4.3%
B 2
 
2.9%
Other values (5) 5
 
7.2%

주소
Text

Distinct107
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size996.0 B
2023-12-12T15:00:32.507798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length19
Mean length18.703704
Min length16

Characters and Unicode

Total characters2020
Distinct characters78
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)98.1%

Sample

1st row대전광역시 유성구 봉명동 692-6
2nd row대전광역시 유성구 봉명동 678-4
3rd row대전광역시 유성구 봉명동 662-1
4th row대전광역시 유성구 봉명동 640-8
5th row대전광역시 유성구 봉명동 640-7
ValueCountFrequency (%)
대전광역시 108
24.7%
유성구 108
24.7%
봉명동 15
 
3.4%
지족동 14
 
3.2%
장대동 11
 
2.5%
원내동 6
 
1.4%
원촌동 5
 
1.1%
방동 5
 
1.1%
반석동 5
 
1.1%
화암동 5
 
1.1%
Other values (133) 155
35.5%
2023-12-12T15:00:33.073647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
329
16.3%
대 120
 
5.9%
구 112
 
5.5%
전 112
 
5.5%
유 110
 
5.4%
성 110
 
5.4%
시 108
 
5.3%
역 108
 
5.3%
광 108
 
5.3%
동 108
 
5.3%
Other values (68) 695
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1195
59.2%
Decimal Number 408
 
20.2%
Space Separator 329
 
16.3%
Dash Punctuation 84
 
4.2%
Uppercase Letter 2
 
0.1%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 120
10.0%
구 112
9.4%
전 112
9.4%
유 110
9.2%
성 110
9.2%
시 108
9.0%
역 108
9.0%
광 108
9.0%
동 108
9.0%
봉 16
 
1.3%
Other values (52) 183
15.3%
Decimal Number
ValueCountFrequency (%)
1 66
16.2%
3 59
14.5%
4 50
12.3%
6 38
9.3%
2 38
9.3%
5 37
9.1%
9 33
8.1%
8 30
7.4%
7 29
7.1%
0 28
6.9%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
L 1
50.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
329
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1195
59.2%
Common 821
40.6%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 120
10.0%
구 112
9.4%
전 112
9.4%
유 110
9.2%
성 110
9.2%
시 108
9.0%
역 108
9.0%
광 108
9.0%
동 108
9.0%
봉 16
 
1.3%
Other values (52) 183
15.3%
Common
ValueCountFrequency (%)
329
40.1%
- 84
 
10.2%
1 66
 
8.0%
3 59
 
7.2%
4 50
 
6.1%
6 38
 
4.6%
2 38
 
4.6%
5 37
 
4.5%
9 33
 
4.0%
8 30
 
3.7%
Other values (2) 57
 
6.9%
Latin
ValueCountFrequency (%)
G 1
25.0%
L 1
25.0%
k 1
25.0%
s 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1195
59.2%
ASCII 825
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
329
39.9%
- 84
 
10.2%
1 66
 
8.0%
3 59
 
7.2%
4 50
 
6.1%
6 38
 
4.6%
2 38
 
4.6%
5 37
 
4.5%
9 33
 
4.0%
8 30
 
3.6%
Other values (6) 61
 
7.4%
Hangul
ValueCountFrequency (%)
대 120
10.0%
구 112
9.4%
전 112
9.4%
유 110
9.2%
성 110
9.2%
시 108
9.0%
역 108
9.0%
광 108
9.0%
동 108
9.0%
봉 16
 
1.3%
Other values (52) 183
15.3%

설치년도
Real number (ℝ)

Distinct26
Distinct (%)24.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2000.537
Minimum1979
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T15:00:33.292610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1979
5-th percentile1992
Q11995
median2001
Q32006
95-th percentile2011
Maximum2021
Range42
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.1151095
Coefficient of variation (CV)0.0035565998
Kurtosis0.35400977
Mean2000.537
Median Absolute Deviation (MAD)6
Skewness0.015758851
Sum216058
Variance50.624784
MonotonicityNot monotonic
2023-12-12T15:00:33.447094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1995 16
14.8%
2004 9
 
8.3%
1994 9
 
8.3%
2001 9
 
8.3%
2007 8
 
7.4%
1993 6
 
5.6%
2002 6
 
5.6%
2006 6
 
5.6%
1996 5
 
4.6%
2003 5
 
4.6%
Other values (16) 29
26.9%
ValueCountFrequency (%)
1979 1
 
0.9%
1982 1
 
0.9%
1987 1
 
0.9%
1989 1
 
0.9%
1992 3
 
2.8%
1993 6
 
5.6%
1994 9
8.3%
1995 16
14.8%
1996 5
 
4.6%
1997 3
 
2.8%
ValueCountFrequency (%)
2021 1
 
0.9%
2017 1
 
0.9%
2015 1
 
0.9%
2014 2
 
1.9%
2011 2
 
1.9%
2010 1
 
0.9%
2009 2
 
1.9%
2008 5
4.6%
2007 8
7.4%
2006 6
5.6%

유형
Categorical

Distinct5
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size996.0 B
주유소·충전소
57 
상업시설
33 
기타
11 
공공용시설
 
5
교통시설
 
2

Length

Max length7
Median length7
Mean length5.4259259
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주유소·충전소 57
52.8%
상업시설 33
30.6%
기타 11
 
10.2%
공공용시설 5
 
4.6%
교통시설 2
 
1.9%

Length

2023-12-12T15:00:33.588174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:00:33.705667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주유소·충전소 57
52.8%
상업시설 33
30.6%
기타 11
 
10.2%
공공용시설 5
 
4.6%
교통시설 2
 
1.9%

Interactions

2023-12-12T15:00:30.404833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:00:30.235851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:00:30.496108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:00:30.321661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:00:33.776598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호설치년도유형
번호1.0000.5980.638
설치년도0.5981.0000.587
유형0.6380.5871.000
2023-12-12T15:00:33.861018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호설치년도유형
번호1.000-0.1590.311
설치년도-0.1591.0000.254
유형0.3110.2541.000

Missing values

2023-12-12T15:00:30.869031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:00:30.991634image/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

번호시설물이름주소설치년도유형
0854투유1차대전광역시 유성구 봉명동 692-62004상업시설
1856위드리버대전광역시 유성구 봉명동 678-42004상업시설
2862투유2차대전광역시 유성구 봉명동 662-12004상업시설
3863노블레스3대전광역시 유성구 봉명동 640-82006상업시설
4864봉명씨티빌대전광역시 유성구 봉명동 640-72004상업시설
5865상그릴라플러스빌대전광역시 유성구 봉명동 604-22004상업시설
6869유성시외버스정류소대전광역시 유성구 봉명동 561-131995교통시설
7870진터벌주유소대전광역시 유성구 봉명동 559-11994주유소·충전소
8871유성온천주유소대전광역시 유성구 봉명동 554-62007주유소·충전소
9874청주해장국대전광역시 유성구 봉명동 538-162001상업시설
번호시설물이름주소설치년도유형
981289테크노밸리주유소대전광역시 유성구 용산동 5782010주유소·충전소
991293북유성IC주유소대전광역시 유성구 외삼동 323-12003주유소·충전소
1001294한빛프라자대전광역시 유성구 어은동 991993상업시설
1011307신성주유소대전광역시 유성구 신성동 4792017주유소·충전소
1021313SK첨단주유소대전광역시 유성구 신성동 160-21993주유소·충전소
1031317햇빛주유소대전광역시 유성구 송정동 344-31997주유소·충전소
1041318송정가스충전소대전광역시 유성구 송정동 300-72008주유소·충전소
1051325송강재래시장대전광역시 유성구 송강동 49-31997상업시설
1061329현대송강주유소대전광역시 유성구 송강동 204-81992주유소·충전소
1071351대광주유소대전광역시 유성구 봉산동 691-11992주유소·충전소