Overview

Dataset statistics

Number of variables5
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory43.2 B

Variable types

Text1
Numeric1
Categorical3

Dataset

Description경기도 의왕시 불법 주정차 문자에 대한 데이터 정보를 포함하고 있습니다. 불법주정차 문자 알림에 대한 정보를 확인할 수 있습니다.
URLhttps://www.data.go.kr/data/15089329/fileData.do

Alerts

관리부서 has constant value ""Constant
담당자 has constant value ""Constant
담당전화번호 has constant value ""Constant
위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:58:19.511877
Analysis finished2023-12-12 05:58:19.896273
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

위치
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-12T14:58:20.058590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length20.066667
Min length16

Characters and Unicode

Total characters1204
Distinct characters141
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

Unique60 ?
Unique (%)100.0%

Sample

1st row ICD제1터널 출구 주변
2nd row LF아울렛매장 주변
3rd row LG(아)삼거리
4th row 갈뫼초교사거리 주변
5th row 계원대입구사거리 주변
ValueCountFrequency (%)
주변 36
31.3%
앞 5
 
4.3%
롯데아울렛 3
 
2.6%
백운헤링턴 3
 
2.6%
인덕원센트럴자이 2
 
1.7%
입구 1
 
0.9%
에이스청계타워 1
 
0.9%
양지편2로 1
 
0.9%
숲속마을사거리 1
 
0.9%
성원이화아파트 1
 
0.9%
Other values (61) 61
53.0%
2023-12-12T14:58:20.480373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
705
58.6%
주 43
 
3.6%
변 41
 
3.4%
리 21
 
1.7%
거 20
 
1.7%
사 13
 
1.1%
초 13
 
1.1%
교 12
 
1.0%
로 8
 
0.7%
장 8
 
0.7%
Other values (131) 320
26.6%

Most occurring categories

ValueCountFrequency (%)
Space Separator 705
58.6%
Other Letter 476
39.5%
Uppercase Letter 10
 
0.8%
Decimal Number 9
 
0.7%
Math Symbol 2
 
0.2%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 43
 
9.0%
변 41
 
8.6%
리 21
 
4.4%
거 20
 
4.2%
사 13
 
2.7%
초 13
 
2.7%
교 12
 
2.5%
로 8
 
1.7%
장 8
 
1.7%
백 8
 
1.7%
Other values (113) 289
60.7%
Uppercase Letter
ValueCountFrequency (%)
L 2
20.0%
F 1
10.0%
T 1
10.0%
P 1
10.0%
I 1
10.0%
A 1
10.0%
D 1
10.0%
C 1
10.0%
G 1
10.0%
Decimal Number
ValueCountFrequency (%)
1 4
44.4%
2 2
22.2%
4 1
 
11.1%
3 1
 
11.1%
5 1
 
11.1%
Space Separator
ValueCountFrequency (%)
705
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 718
59.6%
Hangul 476
39.5%
Latin 10
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 43
 
9.0%
변 41
 
8.6%
리 21
 
4.4%
거 20
 
4.2%
사 13
 
2.7%
초 13
 
2.7%
교 12
 
2.5%
로 8
 
1.7%
장 8
 
1.7%
백 8
 
1.7%
Other values (113) 289
60.7%
Common
ValueCountFrequency (%)
705
98.2%
1 4
 
0.6%
~ 2
 
0.3%
2 2
 
0.3%
4 1
 
0.1%
3 1
 
0.1%
5 1
 
0.1%
) 1
 
0.1%
( 1
 
0.1%
Latin
ValueCountFrequency (%)
L 2
20.0%
F 1
10.0%
T 1
10.0%
P 1
10.0%
I 1
10.0%
A 1
10.0%
D 1
10.0%
C 1
10.0%
G 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 728
60.5%
Hangul 476
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
705
96.8%
1 4
 
0.5%
~ 2
 
0.3%
2 2
 
0.3%
L 2
 
0.3%
F 1
 
0.1%
T 1
 
0.1%
P 1
 
0.1%
I 1
 
0.1%
A 1
 
0.1%
Other values (8) 8
 
1.1%
Hangul
ValueCountFrequency (%)
주 43
 
9.0%
변 41
 
8.6%
리 21
 
4.4%
거 20
 
4.2%
사 13
 
2.7%
초 13
 
2.7%
교 12
 
2.5%
로 8
 
1.7%
장 8
 
1.7%
백 8
 
1.7%
Other values (113) 289
60.7%

건 수
Real number (ℝ)

Distinct59
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean377.45
Minimum15
Maximum1904
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T14:58:20.636445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile26.9
Q1111
median227.5
Q3488.5
95-th percentile1073
Maximum1904
Range1889
Interquartile range (IQR)377.5

Descriptive statistics

Standard deviation386.24364
Coefficient of variation (CV)1.0232975
Kurtosis3.5361978
Mean377.45
Median Absolute Deviation (MAD)171
Skewness1.7379649
Sum22647
Variance149184.15
MonotonicityNot monotonic
2023-12-12T14:58:20.819565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
76 2
 
3.3%
37 1
 
1.7%
98 1
 
1.7%
731 1
 
1.7%
499 1
 
1.7%
27 1
 
1.7%
144 1
 
1.7%
228 1
 
1.7%
275 1
 
1.7%
821 1
 
1.7%
Other values (49) 49
81.7%
ValueCountFrequency (%)
15 1
1.7%
24 1
1.7%
25 1
1.7%
27 1
1.7%
32 1
1.7%
37 1
1.7%
42 1
1.7%
49 1
1.7%
74 1
1.7%
76 2
3.3%
ValueCountFrequency (%)
1904 1
1.7%
1442 1
1.7%
1130 1
1.7%
1070 1
1.7%
1059 1
1.7%
864 1
1.7%
860 1
1.7%
846 1
1.7%
821 1
1.7%
740 1
1.7%

관리부서
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
교통행정과
60 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
교통행정과 60
100.0%

Length

2023-12-12T14:58:20.980746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:58:21.086161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교통행정과 60
100.0%

담당자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
박지영
60 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
박지영 60
100.0%

Length

2023-12-12T14:58:21.175242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:58:21.313024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
박지영 60
100.0%

담당전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
031-345-3327
60 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row031-345-3327
2nd row031-345-3327
3rd row031-345-3327
4th row031-345-3327
5th row031-345-3327

Common Values

ValueCountFrequency (%)
031-345-3327 60
100.0%

Length

2023-12-12T14:58:21.409964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:58:21.494481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-345-3327 60
100.0%

Interactions

2023-12-12T14:58:19.659868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:58:21.552385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위치건 수
위치1.0001.000
건 수1.0001.000

Missing values

2023-12-12T14:58:19.774267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:58:19.860496image/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

위치건 수관리부서담당자담당전화번호
0ICD제1터널 출구 주변37교통행정과박지영031-345-3327
1LF아울렛매장 주변82교통행정과박지영031-345-3327
2LG(아)삼거리178교통행정과박지영031-345-3327
3갈뫼초교사거리 주변128교통행정과박지영031-345-3327
4계원대입구사거리 주변846교통행정과박지영031-345-3327
5고천사거리24교통행정과박지영031-345-3327
6고천초등학교 주변482교통행정과박지영031-345-3327
7내동 내손초 주변146교통행정과박지영031-345-3327
8내손동국민은행사거리주변1904교통행정과박지영031-345-3327
9내손어린이공원 주변76교통행정과박지영031-345-3327
위치건 수관리부서담당자담당전화번호
50의왕우체국 주변860교통행정과박지영031-345-3327
51의왕초교정문 주변105교통행정과박지영031-345-3327
52인덕원센트럴자이 정문 주변49교통행정과박지영031-345-3327
53인덕원센트럴자이 후문 주변467교통행정과박지영031-345-3327
54인덕원푸르지오378교통행정과박지영031-345-3327
55창말버스정류장 주변172교통행정과박지영031-345-3327
56포일로사거리 주변562교통행정과박지영031-345-3327
57포일초교앞151교통행정과박지영031-345-3327
58현대APT사거리 주변1130교통행정과박지영031-345-3327
59호계예비군훈련장256교통행정과박지영031-345-3327