Overview

Dataset statistics

Number of variables6
Number of observations114
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory51.2 B

Variable types

Text2
Numeric2
Categorical2

Dataset

Description고정형CCTV지번주소,위도,경도,자치구,단속지점명,현장구분
Author강서구
URLhttps://data.seoul.go.kr/dataList/OA-20487/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
현장구분 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
위도 has unique valuesUnique
경도 has unique valuesUnique
단속지점명 has unique valuesUnique

Reproduction

Analysis started2024-04-06 11:56:04.520997
Analysis finished2024-04-06 11:56:05.829299
Duration1.31 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고정형CCTV지번주소
Text

Distinct106
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-04-06T20:56:06.211376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length13.982456
Min length7

Characters and Unicode

Total characters1594
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)89.5%

Sample

1st row서울 강서구 염창동 53-1
2nd row가양동 1497
3rd row가양동 1500
4th row서울 강서구 염창동 254-2
5th row서울 강서구 화곡동 1075-25
ValueCountFrequency (%)
서울 83
21.0%
강서구 83
21.0%
마곡동 38
 
9.6%
화곡동 16
 
4.1%
방화동 14
 
3.5%
등촌동 12
 
3.0%
염창동 9
 
2.3%
공항동 8
 
2.0%
가양동 7
 
1.8%
886 4
 
1.0%
Other values (113) 121
30.6%
2024-04-06T20:56:06.935005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
281
17.6%
서 166
 
10.4%
동 114
 
7.2%
강 83
 
5.2%
구 83
 
5.2%
울 83
 
5.2%
- 76
 
4.8%
1 72
 
4.5%
7 71
 
4.5%
곡 57
 
3.6%
Other values (25) 508
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 763
47.9%
Decimal Number 474
29.7%
Space Separator 281
 
17.6%
Dash Punctuation 76
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 166
21.8%
동 114
14.9%
강 83
10.9%
구 83
10.9%
울 83
10.9%
곡 57
 
7.5%
마 38
 
5.0%
화 33
 
4.3%
촌 15
 
2.0%
등 15
 
2.0%
Other values (13) 76
10.0%
Decimal Number
ValueCountFrequency (%)
1 72
15.2%
7 71
15.0%
8 53
11.2%
6 52
11.0%
2 44
9.3%
3 44
9.3%
9 37
7.8%
0 34
7.2%
5 34
7.2%
4 33
7.0%
Space Separator
ValueCountFrequency (%)
281
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 831
52.1%
Hangul 763
47.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 166
21.8%
동 114
14.9%
강 83
10.9%
구 83
10.9%
울 83
10.9%
곡 57
 
7.5%
마 38
 
5.0%
화 33
 
4.3%
촌 15
 
2.0%
등 15
 
2.0%
Other values (13) 76
10.0%
Common
ValueCountFrequency (%)
281
33.8%
- 76
 
9.1%
1 72
 
8.7%
7 71
 
8.5%
8 53
 
6.4%
6 52
 
6.3%
2 44
 
5.3%
3 44
 
5.3%
9 37
 
4.5%
0 34
 
4.1%
Other values (2) 67
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 831
52.1%
Hangul 763
47.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
281
33.8%
- 76
 
9.1%
1 72
 
8.7%
7 71
 
8.5%
8 53
 
6.4%
6 52
 
6.3%
2 44
 
5.3%
3 44
 
5.3%
9 37
 
4.5%
0 34
 
4.1%
Other values (2) 67
 
8.1%
Hangul
ValueCountFrequency (%)
서 166
21.8%
동 114
14.9%
강 83
10.9%
구 83
10.9%
울 83
10.9%
곡 57
 
7.5%
마 38
 
5.0%
화 33
 
4.3%
촌 15
 
2.0%
등 15
 
2.0%
Other values (13) 76
10.0%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.557848
Minimum37.5297
Maximum37.577632
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T20:56:07.278089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.5297
5-th percentile37.534025
Q137.552877
median37.559127
Q337.56567
95-th percentile37.572598
Maximum37.577632
Range0.047932471
Interquartile range (IQR)0.012793691

Descriptive statistics

Standard deviation0.010746536
Coefficient of variation (CV)0.0002861329
Kurtosis0.16129191
Mean37.557848
Median Absolute Deviation (MAD)0.0065460389
Skewness-0.75851372
Sum4281.5947
Variance0.00011548804
MonotonicityNot monotonic
2024-04-06T20:56:07.538961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.55350886688954 1
 
0.9%
37.55922044594632 1
 
0.9%
37.56603247886235 1
 
0.9%
37.56511038905501 1
 
0.9%
37.559263567123935 1
 
0.9%
37.54997638232231 1
 
0.9%
37.55675973897552 1
 
0.9%
37.55521291677319 1
 
0.9%
37.55835165207217 1
 
0.9%
37.56367393778018 1
 
0.9%
Other values (104) 104
91.2%
ValueCountFrequency (%)
37.5297 1
0.9%
37.5308431281297 1
0.9%
37.53242467687191 1
0.9%
37.53272244842884 1
0.9%
37.533391855027816 1
0.9%
37.53347423608091 1
0.9%
37.53432124 1
0.9%
37.5402642763893 1
0.9%
37.54085056418874 1
0.9%
37.54093446809216 1
0.9%
ValueCountFrequency (%)
37.57763247067855 1
0.9%
37.576522853519066 1
0.9%
37.57471642357493 1
0.9%
37.57448793 1
0.9%
37.57346346010483 1
0.9%
37.57262440644588 1
0.9%
37.57258332835809 1
0.9%
37.57203875948671 1
0.9%
37.57152426808186 1
0.9%
37.56995022 1
0.9%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.83595
Minimum126.80075
Maximum126.87671
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-04-06T20:56:07.797336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.80075
5-th percentile126.80347
Q1126.82077
median126.83718
Q3126.84833
95-th percentile126.86898
Maximum126.87671
Range0.075957733
Interquartile range (IQR)0.027558654

Descriptive statistics

Standard deviation0.019028287
Coefficient of variation (CV)0.00015002282
Kurtosis-0.6042629
Mean126.83595
Median Absolute Deviation (MAD)0.013504362
Skewness0.06516729
Sum14459.299
Variance0.00036207572
MonotonicityNot monotonic
2024-04-06T20:56:08.031366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.87110032590876 1
 
0.9%
126.83762912479332 1
 
0.9%
126.8429993190465 1
 
0.9%
126.81163690317906 1
 
0.9%
126.8237193318225 1
 
0.9%
126.82361106684876 1
 
0.9%
126.83691297215492 1
 
0.9%
126.83254221124687 1
 
0.9%
126.83325952407074 1
 
0.9%
126.8362301053564 1
 
0.9%
Other values (104) 104
91.2%
ValueCountFrequency (%)
126.80075409398076 1
0.9%
126.80158802897782 1
0.9%
126.80181606541956 1
0.9%
126.8020011589573 1
0.9%
126.80261119707228 1
0.9%
126.80281395412042 1
0.9%
126.80381648644924 1
0.9%
126.80399566653853 1
0.9%
126.80727962121924 1
0.9%
126.80921329871703 1
0.9%
ValueCountFrequency (%)
126.87671182725336 1
0.9%
126.876423538204 1
0.9%
126.8738642 1
0.9%
126.8726852544358 1
0.9%
126.87110032590876 1
0.9%
126.8705354865566 1
0.9%
126.86814910497286 1
0.9%
126.8677853 1
0.9%
126.86596396719696 1
0.9%
126.863684550372 1
0.9%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
강서구
114 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강서구 114
100.0%

Length

2024-04-06T20:56:08.271514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:56:08.420732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강서구 114
100.0%

단속지점명
Text

UNIQUE 

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2024-04-06T20:56:08.726864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length10.578947
Min length5

Characters and Unicode

Total characters1206
Distinct characters220
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)100.0%

Sample

1st row염창주민센터 사거리 주변
2nd row가양보람아파트 정문 주변
3rd row한강자이아파트 출입구 주변
4th row무학아파트 105동주변
5th row화곡역 인품빌딩 주변
ValueCountFrequency (%)
주변 98
36.4%
정문 7
 
2.6%
사거리 6
 
2.2%
출구 4
 
1.5%
화곡역 3
 
1.1%
후문 3
 
1.1%
건와빌딩 2
 
0.7%
신방화역 2
 
0.7%
화일초교 2
 
0.7%
국제선1층 2
 
0.7%
Other values (135) 140
52.0%
2024-04-06T20:56:09.343827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
158
 
13.1%
주 114
 
9.5%
변 106
 
8.8%
화 22
 
1.8%
1 21
 
1.7%
곡 20
 
1.7%
교 19
 
1.6%
리 17
 
1.4%
트 17
 
1.4%
초 16
 
1.3%
Other values (210) 696
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 984
81.6%
Space Separator 158
 
13.1%
Decimal Number 54
 
4.5%
Uppercase Letter 4
 
0.3%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%
Other Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 114
 
11.6%
변 106
 
10.8%
화 22
 
2.2%
곡 20
 
2.0%
교 19
 
1.9%
리 17
 
1.7%
트 17
 
1.7%
초 16
 
1.6%
문 15
 
1.5%
정 15
 
1.5%
Other values (195) 623
63.3%
Decimal Number
ValueCountFrequency (%)
1 21
38.9%
3 9
16.7%
4 7
 
13.0%
0 6
 
11.1%
2 6
 
11.1%
5 3
 
5.6%
7 2
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
K 2
50.0%
S 1
25.0%
T 1
25.0%
Space Separator
ValueCountFrequency (%)
158
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 984
81.6%
Common 218
 
18.1%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 114
 
11.6%
변 106
 
10.8%
화 22
 
2.2%
곡 20
 
2.0%
교 19
 
1.9%
리 17
 
1.7%
트 17
 
1.7%
초 16
 
1.6%
문 15
 
1.5%
정 15
 
1.5%
Other values (195) 623
63.3%
Common
ValueCountFrequency (%)
158
72.5%
1 21
 
9.6%
3 9
 
4.1%
4 7
 
3.2%
0 6
 
2.8%
2 6
 
2.8%
5 3
 
1.4%
7 2
 
0.9%
) 2
 
0.9%
( 2
 
0.9%
Other values (2) 2
 
0.9%
Latin
ValueCountFrequency (%)
K 2
50.0%
S 1
25.0%
T 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 984
81.6%
ASCII 222
 
18.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
158
71.2%
1 21
 
9.5%
3 9
 
4.1%
4 7
 
3.2%
0 6
 
2.7%
2 6
 
2.7%
5 3
 
1.4%
7 2
 
0.9%
) 2
 
0.9%
K 2
 
0.9%
Other values (5) 6
 
2.7%
Hangul
ValueCountFrequency (%)
주 114
 
11.6%
변 106
 
10.8%
화 22
 
2.2%
곡 20
 
2.0%
교 19
 
1.9%
리 17
 
1.7%
트 17
 
1.7%
초 16
 
1.6%
문 15
 
1.5%
정 15
 
1.5%
Other values (195) 623
63.3%

현장구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
불법주정차구역
114 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
불법주정차구역 114
100.0%

Length

2024-04-06T20:56:09.572329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T20:56:09.725868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불법주정차구역 114
100.0%

Interactions

2024-04-06T20:56:05.180757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:56:04.853307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:56:05.344181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T20:56:05.008865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T20:56:09.816617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.569
경도0.5691.000
2024-04-06T20:56:09.939197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.501
경도-0.5011.000

Missing values

2024-04-06T20:56:05.593506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T20:56:05.762238image/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

고정형CCTV지번주소위도경도자치구단속지점명현장구분
0서울 강서구 염창동 53-137.553509126.8711강서구염창주민센터 사거리 주변불법주정차구역
1가양동 149737.567514126.848718강서구가양보람아파트 정문 주변불법주정차구역
2가양동 150037.567363126.84981강서구한강자이아파트 출입구 주변불법주정차구역
3서울 강서구 염창동 254-237.550722126.876424강서구무학아파트 105동주변불법주정차구역
4서울 강서구 화곡동 1075-2537.540934126.840766강서구화곡역 인품빌딩 주변불법주정차구역
5서울 강서구 화곡동 340-5337.532722126.846313강서구까치산역 1번 출구 주변불법주정차구역
6등촌3동 14-1837.56419126.84892강서구홈플러스 가양점 주변불법주정차구역
7우장산동 677-1137.552696126.83655강서구미즈메디병원 주변불법주정차구역
8서울 강서구 화곡동 1065-2437.541609126.83982강서구화곡역 7번 출구 주변불법주정차구역
9서울 강서구 방화동 88637.562411126.802814강서구김포공항 롯데몰 주변불법주정차구역
고정형CCTV지번주소위도경도자치구단속지점명현장구분
104서울 강서구 내발산동 74237.553419126.83028강서구수명산파크1단지 주변불법주정차구역
105서울 강서구 공항동 22-3037.563649126.81069강서구공항시장역 주변불법주정차구역
106서울 강서구 화곡동 102-16037.540264126.84639강서구화일초교 후문 통학로 주변불법주정차구역
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108서울 강서구 마곡동 797-637.559978126.833803강서구건와빌딩 사거리 주변불법주정차구역
109서울 강서구 염창동 95-1037.551526126.872685강서구염동초등학교 주변불법주정차구역
110서울 강서구 마곡동 749-837.555923126.820695강서구강서농산물 도매시장 주변불법주정차구역
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112서울 강서구 화곡동 91-1437.547379126.844877강서구우장초교 통학로 주변불법주정차구역
113서울 강서구 등촌동 519-2537.547157126.859699강서구등촌초등학교 주변불법주정차구역