Overview

Dataset statistics

Number of variables4
Number of observations813
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.3 KiB
Average record size in memory33.2 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description대전광역시 중구 소재 감염병예방법 시행령 제24조 의거 소독의무대상시설 (상호명, 소재지) 현황을 제공합니다.
Author대전광역시 중구
URLhttps://www.data.go.kr/data/15119317/fileData.do

Alerts

연번 is highly overall correlated with 시설구분High correlation
시설구분 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:17:50.897968
Analysis finished2023-12-12 11:17:51.845885
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct813
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean407
Minimum1
Maximum813
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-12T20:17:51.966318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile41.6
Q1204
median407
Q3610
95-th percentile772.4
Maximum813
Range812
Interquartile range (IQR)406

Descriptive statistics

Standard deviation234.83718
Coefficient of variation (CV)0.57699552
Kurtosis-1.2
Mean407
Median Absolute Deviation (MAD)203
Skewness0
Sum330891
Variance55148.5
MonotonicityStrictly increasing
2023-12-12T20:17:52.243176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
547 1
 
0.1%
537 1
 
0.1%
538 1
 
0.1%
539 1
 
0.1%
540 1
 
0.1%
541 1
 
0.1%
542 1
 
0.1%
543 1
 
0.1%
544 1
 
0.1%
Other values (803) 803
98.8%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
813 1
0.1%
812 1
0.1%
811 1
0.1%
810 1
0.1%
809 1
0.1%
808 1
0.1%
807 1
0.1%
806 1
0.1%
805 1
0.1%
804 1
0.1%

시설구분
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
연면적2천제곱미터이상 건물
309 
집단급식소
87 
숙박업(일반)
81 
일반음식점
58 
300세대 공동주택
45 
Other values (28)
233 

Length

Max length14
Median length12
Mean length8.8892989
Min length2

Unique

Unique4 ?
Unique (%)0.5%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(일반)

Common Values

ValueCountFrequency (%)
연면적2천제곱미터이상 건물 309
38.0%
집단급식소 87
 
10.7%
숙박업(일반) 81
 
10.0%
일반음식점 58
 
7.1%
300세대 공동주택 45
 
5.5%
어린이집 30
 
3.7%
초등학교 27
 
3.3%
유치원 21
 
2.6%
기숙사 및 합숙소 20
 
2.5%
휴게음식점 17
 
2.1%
Other values (23) 118
 
14.5%

Length

2023-12-12T20:17:52.500169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연면적2천제곱미터이상 309
25.4%
건물 309
25.4%
집단급식소 87
 
7.2%
숙박업(일반 81
 
6.7%
일반음식점 58
 
4.8%
300세대 45
 
3.7%
공동주택 45
 
3.7%
어린이집 30
 
2.5%
초등학교 27
 
2.2%
및 24
 
2.0%
Other values (28) 200
16.5%

상호명
Text

Distinct666
Distinct (%)81.9%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-12-12T20:17:52.965488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length29
Mean length9.2570726
Min length2

Characters and Unicode

Total characters7526
Distinct characters418
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique566 ?
Unique (%)69.6%

Sample

1st row럭키호텔
2nd row허브모텔
3rd row만월호텔대흥점
4th row월드파크
5th row로즈모텔
ValueCountFrequency (%)
근린생활시설 62
 
5.0%
외 59
 
4.8%
업무시설 52
 
4.2%
외1 26
 
2.1%
사무실 22
 
1.8%
공동주택 20
 
1.6%
외2 20
 
1.6%
제1,2종근린생활시설 17
 
1.4%
1 17
 
1.4%
2 17
 
1.4%
Other values (649) 917
74.6%
2023-12-12T20:17:53.625030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
423
 
5.6%
시 380
 
5.0%
설 349
 
4.6%
, 218
 
2.9%
린 174
 
2.3%
대 171
 
2.3%
교 155
 
2.1%
외 155
 
2.1%
생 151
 
2.0%
활 147
 
2.0%
Other values (408) 5203
69.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6419
85.3%
Space Separator 423
 
5.6%
Decimal Number 263
 
3.5%
Other Punctuation 223
 
3.0%
Close Punctuation 82
 
1.1%
Open Punctuation 81
 
1.1%
Uppercase Letter 14
 
0.2%
Lowercase Letter 10
 
0.1%
Other Symbol 9
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 380
 
5.9%
설 349
 
5.4%
린 174
 
2.7%
대 171
 
2.7%
교 155
 
2.4%
외 155
 
2.4%
생 151
 
2.4%
활 147
 
2.3%
근 142
 
2.2%
전 142
 
2.2%
Other values (373) 4453
69.4%
Decimal Number
ValueCountFrequency (%)
1 111
42.2%
2 100
38.0%
3 27
 
10.3%
4 11
 
4.2%
5 6
 
2.3%
6 3
 
1.1%
7 2
 
0.8%
9 2
 
0.8%
0 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
C 4
28.6%
N 3
21.4%
H 1
 
7.1%
R 1
 
7.1%
S 1
 
7.1%
K 1
 
7.1%
D 1
 
7.1%
F 1
 
7.1%
A 1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
o 3
30.0%
n 2
20.0%
l 1
 
10.0%
e 1
 
10.0%
t 1
 
10.0%
k 1
 
10.0%
c 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 218
97.8%
· 2
 
0.9%
/ 2
 
0.9%
. 1
 
0.4%
Space Separator
ValueCountFrequency (%)
423
100.0%
Close Punctuation
ValueCountFrequency (%)
) 82
100.0%
Open Punctuation
ValueCountFrequency (%)
( 81
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6428
85.4%
Common 1073
 
14.3%
Latin 25
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 380
 
5.9%
설 349
 
5.4%
린 174
 
2.7%
대 171
 
2.7%
교 155
 
2.4%
외 155
 
2.4%
생 151
 
2.3%
활 147
 
2.3%
근 142
 
2.2%
전 142
 
2.2%
Other values (374) 4462
69.4%
Common
ValueCountFrequency (%)
423
39.4%
, 218
20.3%
1 111
 
10.3%
2 100
 
9.3%
) 82
 
7.6%
( 81
 
7.5%
3 27
 
2.5%
4 11
 
1.0%
5 6
 
0.6%
6 3
 
0.3%
Other values (7) 11
 
1.0%
Latin
ValueCountFrequency (%)
C 4
16.0%
N 3
12.0%
o 3
12.0%
n 2
 
8.0%
l 1
 
4.0%
e 1
 
4.0%
t 1
 
4.0%
H 1
 
4.0%
Ⅱ 1
 
4.0%
k 1
 
4.0%
Other values (7) 7
28.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6419
85.3%
ASCII 1095
 
14.5%
None 11
 
0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
423
38.6%
, 218
19.9%
1 111
 
10.1%
2 100
 
9.1%
) 82
 
7.5%
( 81
 
7.4%
3 27
 
2.5%
4 11
 
1.0%
5 6
 
0.5%
C 4
 
0.4%
Other values (22) 32
 
2.9%
Hangul
ValueCountFrequency (%)
시 380
 
5.9%
설 349
 
5.4%
린 174
 
2.7%
대 171
 
2.7%
교 155
 
2.4%
외 155
 
2.4%
생 151
 
2.4%
활 147
 
2.3%
근 142
 
2.2%
전 142
 
2.2%
Other values (373) 4453
69.4%
None
ValueCountFrequency (%)
㈜ 9
81.8%
· 2
 
18.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지(도로명)
Text

Distinct783
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-12-12T20:17:54.144016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length47
Mean length23.072571
Min length14

Characters and Unicode

Total characters18758
Distinct characters220
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique756 ?
Unique (%)93.0%

Sample

1st row대전광역시 중구 당디로 112 (유천동)
2nd row대전광역시 중구 목척1길 29 (은행동)
3rd row대전광역시 중구 대흥로165번길 35, 1-6층 (대흥동)
4th row대전광역시 중구 오류로 64 (오류동)
5th row대전광역시 중구 태평로 183 (태평동)
ValueCountFrequency (%)
중구 814
21.1%
대전광역시 813
21.0%
대흥동 62
 
1.6%
대종로 61
 
1.6%
계룡로 52
 
1.3%
문화동 43
 
1.1%
중앙로 41
 
1.1%
계백로 41
 
1.1%
유천동 28
 
0.7%
선화동 26
 
0.7%
Other values (767) 1883
48.7%
2023-12-12T20:17:54.902785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3082
 
16.4%
대 1142
 
6.1%
중 966
 
5.1%
전 839
 
4.5%
역 816
 
4.4%
시 816
 
4.4%
광 814
 
4.3%
구 814
 
4.3%
로 802
 
4.3%
1 777
 
4.1%
Other values (210) 7890
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10932
58.3%
Decimal Number 3392
 
18.1%
Space Separator 3082
 
16.4%
Close Punctuation 444
 
2.4%
Open Punctuation 444
 
2.4%
Other Punctuation 329
 
1.8%
Dash Punctuation 111
 
0.6%
Math Symbol 19
 
0.1%
Uppercase Letter 4
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 1142
 
10.4%
중 966
 
8.8%
전 839
 
7.7%
역 816
 
7.5%
시 816
 
7.5%
광 814
 
7.4%
구 814
 
7.4%
로 802
 
7.3%
동 468
 
4.3%
길 293
 
2.7%
Other values (188) 3162
28.9%
Decimal Number
ValueCountFrequency (%)
1 777
22.9%
2 456
13.4%
3 364
10.7%
4 314
9.3%
5 310
 
9.1%
6 270
 
8.0%
0 238
 
7.0%
8 234
 
6.9%
9 223
 
6.6%
7 206
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
N 1
25.0%
C 1
25.0%
A 1
25.0%
B 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 325
98.8%
. 4
 
1.2%
Space Separator
ValueCountFrequency (%)
3082
100.0%
Close Punctuation
ValueCountFrequency (%)
) 444
100.0%
Open Punctuation
ValueCountFrequency (%)
( 444
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%
Math Symbol
ValueCountFrequency (%)
~ 19
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10933
58.3%
Common 7821
41.7%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 1142
 
10.4%
중 966
 
8.8%
전 839
 
7.7%
역 816
 
7.5%
시 816
 
7.5%
광 814
 
7.4%
구 814
 
7.4%
로 802
 
7.3%
동 468
 
4.3%
길 293
 
2.7%
Other values (189) 3163
28.9%
Common
ValueCountFrequency (%)
3082
39.4%
1 777
 
9.9%
2 456
 
5.8%
) 444
 
5.7%
( 444
 
5.7%
3 364
 
4.7%
, 325
 
4.2%
4 314
 
4.0%
5 310
 
4.0%
6 270
 
3.5%
Other values (7) 1035
 
13.2%
Latin
ValueCountFrequency (%)
N 1
25.0%
C 1
25.0%
A 1
25.0%
B 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10932
58.3%
ASCII 7825
41.7%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3082
39.4%
1 777
 
9.9%
2 456
 
5.8%
) 444
 
5.7%
( 444
 
5.7%
3 364
 
4.7%
, 325
 
4.2%
4 314
 
4.0%
5 310
 
4.0%
6 270
 
3.5%
Other values (11) 1039
 
13.3%
Hangul
ValueCountFrequency (%)
대 1142
 
10.4%
중 966
 
8.8%
전 839
 
7.7%
역 816
 
7.5%
시 816
 
7.5%
광 814
 
7.4%
구 814
 
7.4%
로 802
 
7.3%
동 468
 
4.3%
길 293
 
2.7%
Other values (188) 3162
28.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

Interactions

2023-12-12T20:17:51.426722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:17:55.055126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설구분
연번1.0000.962
시설구분0.9621.000
2023-12-12T20:17:55.201033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시설구분
연번1.0000.774
시설구분0.7741.000

Missing values

2023-12-12T20:17:51.645924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:17:51.782557image/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

연번시설구분상호명소재지(도로명)
01숙박업(일반)럭키호텔대전광역시 중구 당디로 112 (유천동)
12숙박업(일반)허브모텔대전광역시 중구 목척1길 29 (은행동)
23숙박업(일반)만월호텔대흥점대전광역시 중구 대흥로165번길 35, 1-6층 (대흥동)
34숙박업(일반)월드파크대전광역시 중구 오류로 64 (오류동)
45숙박업(일반)로즈모텔대전광역시 중구 태평로 183 (태평동)
56숙박업(일반)뉴히딩크모텔대전광역시 중구 유등천동로 324-1 (산성동)
67숙박업(일반)오렌지파크대전광역시 중구 목척3길 36 (은행동)
78숙박업(일반)황토방모텔대전광역시 중구 목척7길 32 (은행동)
89숙박업(일반)큐모텔대전광역시 중구 계룡로874번길 103 (오류동)
910숙박업(일반)호텔노크온(Knock on Hotel)대전광역시 중구 인창로 7 (대흥동)
연번시설구분상호명소재지(도로명)
803804300세대 공동주택센트럴파크 2단지대전광역시 중구 서문로 96 (문화동, 센트럴파크2단지아파트)
804805300세대 공동주택센트럴파크 3단지대전광역시 중구 계백로1716번길 87 (문화동, 센트럴파크3단지아파트)
805806300세대 공동주택선화동 참좋은아파트대전광역시 중구 대종로 544 (선화동, 참좋은아파트)
806807300세대 공동주택쌍용예가대전광역시 중구 평촌로 93 (태평동, 쌍용예가아파트)
807808300세대 공동주택목동 더샵대전광역시 중구 목동로22번길 16 (목동, 더샵아파트)
808809300세대 공동주택목동 올리브힐대전광역시 중구 목동로 70 (목동, 올리브힐아파트)
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