Overview

Dataset statistics

Number of variables5
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 KiB
Average record size in memory48.0 B

Variable types

Numeric2
Text2
Categorical1

Dataset

Description대전광역시 동구 민방위 비상급수시설 현황(전쟁 및 상수도 체계 마비 등과 같은 비상사태 발생으로 상수도 공급중단시 최소의 음용 및 생활용수를 주민에게 공급하기 위한 시설)
Author공공데이터포털
URLhttps://www.data.go.kr/data/15102816/fileData.do

Alerts

수질검사결과 has constant value ""Constant
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2024-04-17 11:39:43.133285
Analysis finished2024-04-17 11:39:43.685371
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-17T20:39:43.737409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.05
Q16.25
median11.5
Q316.75
95-th percentile20.95
Maximum22
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.5646597
Kurtosis-1.2
Mean11.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum253
Variance42.166667
MonotonicityStrictly increasing
2024-04-17T20:39:43.830182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 1
 
4.5%
13 1
 
4.5%
22 1
 
4.5%
21 1
 
4.5%
20 1
 
4.5%
19 1
 
4.5%
18 1
 
4.5%
17 1
 
4.5%
16 1
 
4.5%
15 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1 1
4.5%
2 1
4.5%
3 1
4.5%
4 1
4.5%
5 1
4.5%
6 1
4.5%
7 1
4.5%
8 1
4.5%
9 1
4.5%
10 1
4.5%
ValueCountFrequency (%)
22 1
4.5%
21 1
4.5%
20 1
4.5%
19 1
4.5%
18 1
4.5%
17 1
4.5%
16 1
4.5%
15 1
4.5%
14 1
4.5%
13 1
4.5%

시설명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-17T20:39:43.989452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length7.1818182
Min length4

Characters and Unicode

Total characters158
Distinct characters80
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

Unique22 ?
Unique (%)100.0%

Sample

1st row안전목욕탕
2nd row도리공원
3rd row돌샘약수터
4th row매봉공원
5th row계룡공고옆
ValueCountFrequency (%)
안전목욕탕 1
 
4.2%
도리공원 1
 
4.2%
동구청소년자연수련관 1
 
4.2%
동신고등학교 1
 
4.2%
남간정사 1
 
4.2%
동아아파트 1
 
4.2%
대전대학교(6양수장 1
 
4.2%
대전대학교(5양수장 1
 
4.2%
대전대학교(4양수장 1
 
4.2%
한숲아파트 1
 
4.2%
Other values (14) 14
58.3%
2024-04-17T20:39:44.263483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 10
 
6.3%
동 9
 
5.7%
대 7
 
4.4%
파 7
 
4.4%
트 7
 
4.4%
공 6
 
3.8%
( 5
 
3.2%
전 5
 
3.2%
) 5
 
3.2%
수 5
 
3.2%
Other values (70) 92
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 137
86.7%
Decimal Number 8
 
5.1%
Open Punctuation 5
 
3.2%
Close Punctuation 5
 
3.2%
Space Separator 2
 
1.3%
Uppercase Letter 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 10
 
7.3%
동 9
 
6.6%
대 7
 
5.1%
파 7
 
5.1%
트 7
 
5.1%
공 6
 
4.4%
전 5
 
3.6%
수 5
 
3.6%
교 4
 
2.9%
학 4
 
2.9%
Other values (59) 73
53.3%
Decimal Number
ValueCountFrequency (%)
1 2
25.0%
4 1
12.5%
7 1
12.5%
6 1
12.5%
5 1
12.5%
0 1
12.5%
2 1
12.5%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137
86.7%
Common 20
 
12.7%
Latin 1
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 10
 
7.3%
동 9
 
6.6%
대 7
 
5.1%
파 7
 
5.1%
트 7
 
5.1%
공 6
 
4.4%
전 5
 
3.6%
수 5
 
3.6%
교 4
 
2.9%
학 4
 
2.9%
Other values (59) 73
53.3%
Common
ValueCountFrequency (%)
( 5
25.0%
) 5
25.0%
2
 
10.0%
1 2
 
10.0%
4 1
 
5.0%
7 1
 
5.0%
6 1
 
5.0%
5 1
 
5.0%
0 1
 
5.0%
2 1
 
5.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 137
86.7%
ASCII 21
 
13.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 10
 
7.3%
동 9
 
6.6%
대 7
 
5.1%
파 7
 
5.1%
트 7
 
5.1%
공 6
 
4.4%
전 5
 
3.6%
수 5
 
3.6%
교 4
 
2.9%
학 4
 
2.9%
Other values (59) 73
53.3%
ASCII
ValueCountFrequency (%)
( 5
23.8%
) 5
23.8%
2
 
9.5%
1 2
 
9.5%
4 1
 
4.8%
7 1
 
4.8%
6 1
 
4.8%
5 1
 
4.8%
0 1
 
4.8%
B 1
 
4.8%

시설주소
Text

Distinct19
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-04-17T20:39:44.456903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length22.727273
Min length17

Characters and Unicode

Total characters500
Distinct characters72
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

Unique17 ?
Unique (%)77.3%

Sample

1st row대전 동구 계족로 426(용전동)
2nd row대전 동구 새울로109번길 26-24(용운동)
3rd row대전 동구 동부로 55-58(판암동)
4th row대전 동구 가양로132번길 26(가양동, 매봉어린이공원)
5th row대전 동구 솔랑6길 4(삼성동)
ValueCountFrequency (%)
대전 22
22.9%
동구 22
22.9%
대학로 3
 
3.1%
62(용운동 3
 
3.1%
대전천동로 2
 
2.1%
618(삼성동 2
 
2.1%
주공아파트 2
 
2.1%
대전로 2
 
2.1%
53(가양2동 1
 
1.0%
73(용전동 1
 
1.0%
Other values (36) 36
37.5%
2024-04-17T20:39:44.768543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
74
 
14.8%
동 51
 
10.2%
대 32
 
6.4%
전 30
 
6.0%
( 22
 
4.4%
) 22
 
4.4%
구 22
 
4.4%
로 20
 
4.0%
2 15
 
3.0%
4 15
 
3.0%
Other values (62) 197
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 284
56.8%
Decimal Number 85
 
17.0%
Space Separator 74
 
14.8%
Open Punctuation 22
 
4.4%
Close Punctuation 22
 
4.4%
Other Punctuation 8
 
1.6%
Dash Punctuation 5
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 51
18.0%
대 32
 
11.3%
전 30
 
10.6%
구 22
 
7.7%
로 20
 
7.0%
아 10
 
3.5%
길 9
 
3.2%
번 8
 
2.8%
파 7
 
2.5%
트 7
 
2.5%
Other values (47) 88
31.0%
Decimal Number
ValueCountFrequency (%)
2 15
17.6%
4 15
17.6%
6 12
14.1%
1 11
12.9%
8 7
8.2%
5 6
 
7.1%
3 6
 
7.1%
7 6
 
7.1%
9 4
 
4.7%
0 3
 
3.5%
Space Separator
ValueCountFrequency (%)
74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 284
56.8%
Common 216
43.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 51
18.0%
대 32
 
11.3%
전 30
 
10.6%
구 22
 
7.7%
로 20
 
7.0%
아 10
 
3.5%
길 9
 
3.2%
번 8
 
2.8%
파 7
 
2.5%
트 7
 
2.5%
Other values (47) 88
31.0%
Common
ValueCountFrequency (%)
74
34.3%
( 22
 
10.2%
) 22
 
10.2%
2 15
 
6.9%
4 15
 
6.9%
6 12
 
5.6%
1 11
 
5.1%
, 8
 
3.7%
8 7
 
3.2%
5 6
 
2.8%
Other values (5) 24
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 284
56.8%
ASCII 216
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
74
34.3%
( 22
 
10.2%
) 22
 
10.2%
2 15
 
6.9%
4 15
 
6.9%
6 12
 
5.6%
1 11
 
5.1%
, 8
 
3.7%
8 7
 
3.2%
5 6
 
2.8%
Other values (5) 24
 
11.1%
Hangul
ValueCountFrequency (%)
동 51
18.0%
대 32
 
11.3%
전 30
 
10.6%
구 22
 
7.7%
로 20
 
7.0%
아 10
 
3.5%
길 9
 
3.2%
번 8
 
2.8%
파 7
 
2.5%
트 7
 
2.5%
Other values (47) 88
31.0%

규모(톤)
Real number (ℝ)

Distinct15
Distinct (%)68.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean233.45455
Minimum60
Maximum500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-17T20:39:44.873822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile101
Q1162.5
median215.5
Q3297.5
95-th percentile395.1
Maximum500
Range440
Interquartile range (IQR)135

Descriptive statistics

Standard deviation101.52538
Coefficient of variation (CV)0.43488285
Kurtosis1.0389466
Mean233.45455
Median Absolute Deviation (MAD)74.5
Skewness0.66762923
Sum5136
Variance10307.403
MonotonicityNot monotonic
2024-04-17T20:39:44.962695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
200 3
13.6%
300 3
13.6%
120 2
 
9.1%
150 2
 
9.1%
290 2
 
9.1%
60 1
 
4.5%
219 1
 
4.5%
263 1
 
4.5%
302 1
 
4.5%
100 1
 
4.5%
Other values (5) 5
22.7%
ValueCountFrequency (%)
60 1
 
4.5%
100 1
 
4.5%
120 2
9.1%
150 2
9.1%
200 3
13.6%
210 1
 
4.5%
212 1
 
4.5%
219 1
 
4.5%
250 1
 
4.5%
263 1
 
4.5%
ValueCountFrequency (%)
500 1
 
4.5%
400 1
 
4.5%
302 1
 
4.5%
300 3
13.6%
290 2
9.1%
263 1
 
4.5%
250 1
 
4.5%
219 1
 
4.5%
212 1
 
4.5%
210 1
 
4.5%

수질검사결과
Categorical

CONSTANT 

Distinct1
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size308.0 B
적합
22 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
적합 22
100.0%

Length

2024-04-17T20:39:45.059890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:39:45.141196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적합 22
100.0%

Interactions

2024-04-17T20:39:43.436086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:39:43.287074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:39:43.492800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T20:39:43.361809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T20:39:45.456651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설명시설주소규모(톤)
연번1.0001.0000.8540.695
시설명1.0001.0001.0001.000
시설주소0.8541.0001.0000.932
규모(톤)0.6951.0000.9321.000
2024-04-17T20:39:45.533590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번규모(톤)
연번1.0000.446
규모(톤)0.4461.000

Missing values

2024-04-17T20:39:43.575331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T20:39:43.653762image/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

연번시설명시설주소규모(톤)수질검사결과
01안전목욕탕대전 동구 계족로 426(용전동)60적합
12도리공원대전 동구 새울로109번길 26-24(용운동)219적합
23돌샘약수터대전 동구 동부로 55-58(판암동)120적합
34매봉공원대전 동구 가양로132번길 26(가양동, 매봉어린이공원)120적합
45계룡공고옆대전 동구 솔랑6길 4(삼성동)263적합
56빌라맨션(B동 옆)대전 동구 대전천동로 618(삼성동)302적합
67휴먼시아2단지아파트대전 동구 대전로542번길 78-1(천동, 휴먼시아아파트)100적합
78신동아아파트대전 동구 한밭대로1237번길 52(자양동, 신동아아파트)150적합
89구삼성1동주민센터대전 동구 대전천동로 618(삼성동)150적합
910천동주공아파트대전 동구 대전로 449(가오동, 주공아파트)210적합
연번시설명시설주소규모(톤)수질검사결과
1213쌈지마당대전 동구 홍도동 10-18(홍도동)500적합
1314한숲아파트대전 동구 계족로489번길 73(용전동, 한숲아파트)300적합
1415대전대학교(4양수장)대전 동구 대학로 62(용운동)290적합
1516대전대학교(5양수장)대전 동구 대학로 62(용운동)290적합
1617대전대학교(6양수장)대전 동구 대학로 62(용운동)200적합
1718동아아파트대전 동구 성동로 74(자양동, 동아아파트)300적합
1819남간정사대전 동구 충정로 53(가양2동)400적합
1920동신고등학교대전 동구 옥천로 423(비룡동)200적합
2021동구청소년자연수련관대전 동구 산내로474번길 123(상소동)250적합
2122용전공원대전 동구 계족로446번길 19(용전동)212적합