Overview

Dataset statistics

Number of variables3
Number of observations288
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory25.5 B

Variable types

Numeric1
Categorical1
Text1

Dataset

Description충청남도_아산시_무인단속카메라 현황으로 단속유형(주정차단속 등) 설치위치가 표시됩니다.----------------------
URLhttps://www.data.go.kr/data/15040494/fileData.do

Alerts

연번 is highly overall correlated with 단속유형High correlation
단속유형 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
설치주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:33:23.871552
Analysis finished2023-12-12 17:33:24.417555
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct288
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean144.5
Minimum1
Maximum288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2023-12-13T02:33:24.495960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.35
Q172.75
median144.5
Q3216.25
95-th percentile273.65
Maximum288
Range287
Interquartile range (IQR)143.5

Descriptive statistics

Standard deviation83.282651
Coefficient of variation (CV)0.57635053
Kurtosis-1.2
Mean144.5
Median Absolute Deviation (MAD)72
Skewness0
Sum41616
Variance6936
MonotonicityStrictly increasing
2023-12-13T02:33:24.649420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
146 1
 
0.3%
198 1
 
0.3%
197 1
 
0.3%
196 1
 
0.3%
195 1
 
0.3%
194 1
 
0.3%
193 1
 
0.3%
192 1
 
0.3%
191 1
 
0.3%
Other values (278) 278
96.5%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
288 1
0.3%
287 1
0.3%
286 1
0.3%
285 1
0.3%
284 1
0.3%
283 1
0.3%
282 1
0.3%
281 1
0.3%
280 1
0.3%
279 1
0.3%

단속유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
주정차단속
195 
과속 및 신호
71 
과속
 
14
구간단속
 
8

Length

Max length7
Median length5
Mean length5.3194444
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주정차단속 195
67.7%
과속 및 신호 71
 
24.7%
과속 14
 
4.9%
구간단속 8
 
2.8%

Length

2023-12-13T02:33:24.790914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:33:24.901757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주정차단속 195
45.3%
과속 85
19.8%
및 71
 
16.5%
신호 71
 
16.5%
구간단속 8
 
1.9%

설치주소
Text

UNIQUE 

Distinct288
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-13T02:33:25.160971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length40
Mean length26.638889
Min length12

Characters and Unicode

Total characters7672
Distinct characters315
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

Unique288 ?
Unique (%)100.0%

Sample

1st row천도초등학교주변(실옥동 181-147)
2nd row온양관광호텔 사거리(온천동 222-5)
3rd row동신초등학교주변(모종동 586-4)
4th row아고오거리주변(온천동 1791)
5th row시민로사거리주변(온천동 1706)
ValueCountFrequency (%)
아산 49
 
3.8%
아산시 46
 
3.5%
공수리 23
 
1.8%
배방읍 23
 
1.8%
장재리 23
 
1.8%
북수리 21
 
1.6%
탕정면 20
 
1.5%
앞 20
 
1.5%
온천대로 18
 
1.4%
입구 12
 
0.9%
Other values (727) 1048
80.4%
2023-12-13T02:33:25.605535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1024
 
13.3%
( 314
 
4.1%
) 309
 
4.0%
리 225
 
2.9%
1 207
 
2.7%
아 174
 
2.3%
산 161
 
2.1%
2 151
 
2.0%
동 146
 
1.9%
로 146
 
1.9%
Other values (305) 4815
62.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4803
62.6%
Space Separator 1024
 
13.3%
Decimal Number 1011
 
13.2%
Open Punctuation 314
 
4.1%
Close Punctuation 309
 
4.0%
Dash Punctuation 114
 
1.5%
Math Symbol 49
 
0.6%
Other Punctuation 34
 
0.4%
Uppercase Letter 13
 
0.2%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 225
 
4.7%
아 174
 
3.6%
산 161
 
3.4%
동 146
 
3.0%
로 146
 
3.0%
방 143
 
3.0%
배 116
 
2.4%
면 111
 
2.3%
주 110
 
2.3%
교 105
 
2.2%
Other values (278) 3366
70.1%
Decimal Number
ValueCountFrequency (%)
1 207
20.5%
2 151
14.9%
3 118
11.7%
4 113
11.2%
5 101
10.0%
7 67
 
6.6%
6 66
 
6.5%
9 66
 
6.5%
8 61
 
6.0%
0 61
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
T 4
30.8%
K 3
23.1%
X 2
15.4%
A 1
 
7.7%
P 1
 
7.7%
H 1
 
7.7%
L 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 23
67.6%
@ 9
 
26.5%
. 2
 
5.9%
Math Symbol
ValueCountFrequency (%)
→ 47
95.9%
↔ 2
 
4.1%
Space Separator
ValueCountFrequency (%)
1024
100.0%
Open Punctuation
ValueCountFrequency (%)
( 314
100.0%
Close Punctuation
ValueCountFrequency (%)
) 309
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4803
62.6%
Common 2856
37.2%
Latin 13
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 225
 
4.7%
아 174
 
3.6%
산 161
 
3.4%
동 146
 
3.0%
로 146
 
3.0%
방 143
 
3.0%
배 116
 
2.4%
면 111
 
2.3%
주 110
 
2.3%
교 105
 
2.2%
Other values (278) 3366
70.1%
Common
ValueCountFrequency (%)
1024
35.9%
( 314
 
11.0%
) 309
 
10.8%
1 207
 
7.2%
2 151
 
5.3%
3 118
 
4.1%
- 114
 
4.0%
4 113
 
4.0%
5 101
 
3.5%
7 67
 
2.3%
Other values (10) 338
 
11.8%
Latin
ValueCountFrequency (%)
T 4
30.8%
K 3
23.1%
X 2
15.4%
A 1
 
7.7%
P 1
 
7.7%
H 1
 
7.7%
L 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4803
62.6%
ASCII 2820
36.8%
Arrows 49
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1024
36.3%
( 314
 
11.1%
) 309
 
11.0%
1 207
 
7.3%
2 151
 
5.4%
3 118
 
4.2%
- 114
 
4.0%
4 113
 
4.0%
5 101
 
3.6%
7 67
 
2.4%
Other values (15) 302
 
10.7%
Hangul
ValueCountFrequency (%)
리 225
 
4.7%
아 174
 
3.6%
산 161
 
3.4%
동 146
 
3.0%
로 146
 
3.0%
방 143
 
3.0%
배 116
 
2.4%
면 111
 
2.3%
주 110
 
2.3%
교 105
 
2.2%
Other values (278) 3366
70.1%
Arrows
ValueCountFrequency (%)
→ 47
95.9%
↔ 2
 
4.1%

Interactions

2023-12-13T02:33:24.092030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:33:25.725857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단속유형
연번1.0000.783
단속유형0.7831.000
2023-12-13T02:33:25.816213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번단속유형
연번1.0000.595
단속유형0.5951.000

Missing values

2023-12-13T02:33:24.262030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:33:24.369514image/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

연번단속유형설치주소
01주정차단속천도초등학교주변(실옥동 181-147)
12주정차단속온양관광호텔 사거리(온천동 222-5)
23주정차단속동신초등학교주변(모종동 586-4)
34주정차단속아고오거리주변(온천동 1791)
45주정차단속시민로사거리주변(온천동 1706)
56주정차단속한올고사거리주변(권곡사거리)(권곡동 545-14)
67주정차단속동천교회사거리주변(권곡동 548-26)
78주정차단속온양온천초등학교주변(온천동 82-1)
89주정차단속남산사거리주변(온천동 200-10)
910주정차단속송악사거리(온천동 84-1)
연번단속유형설치주소
278279과속 및 신호아산시 인주면 아산만로 문방2리 입구(노인보호구역, 대음리→밀두리)
279280과속 및 신호아산시 인주면 아산만로 문방2리 입구 건너편(노인보호구역, 밀두리→대음리)
280281과속 및 신호아산시 탕정면 탕정면로 동덕초등학교 앞(천안→탕정)
281282과속 및 신호아산시 탕정면 탕정면로 동덕초등학교 건너편(탕정→천안)
282283과속 및 신호아산시 배방읍 호서로 북수초등학교 앞(월천리→화룡리)
283284과속 및 신호아산시 배방읍 호서로 북수초등학교 건너편(화룡리→월천리)
284285과속 및 신호아산시 송악면 송악로 송남초등학교 앞(송악저수지→외암삼거리)
285286과속 및 신호아산시 인주면 서해로 밀두교차로(당진→아산)
286287과속아산시 신창면 온양순환로 경찰대학교 부근(황산리 20-14, 신창→천안)
287288과속 및 신호아산시 송악면 송악로 송남초등학교 건너편(외암삼거리→송악저수지)