Overview

Dataset statistics

Number of variables6
Number of observations177
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.8 KiB
Average record size in memory50.7 B

Variable types

Text2
Numeric2
Categorical2

Dataset

Description고정형CCTV지번주소,위도,경도,자치구,단속지점명,현장구분
Author성동구
URLhttps://data.seoul.go.kr/dataList/OA-20475/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
현장구분 has constant value ""Constant
단속지점명 has unique valuesUnique

Reproduction

Analysis started2024-04-06 12:17:15.480357
Analysis finished2024-04-06 12:17:16.946297
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고정형CCTV지번주소
Text

Distinct175
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-06T21:17:17.525453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length20
Mean length12.960452
Min length7

Characters and Unicode

Total characters2294
Distinct characters62
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

Unique173 ?
Unique (%)97.7%

Sample

1st row행당동 6-2
2nd row행당동 19-98
3rd row마장동 520-10
4th row마장동 818
5th row마장동 767-41
ValueCountFrequency (%)
서울 63
 
13.0%
성동구 62
 
12.8%
성수동2가 38
 
7.9%
성수동1가 31
 
6.4%
행당동 21
 
4.3%
마장동 18
 
3.7%
옥수동 13
 
2.7%
하왕십리동 12
 
2.5%
용답동 9
 
1.9%
금호동4가 7
 
1.4%
Other values (188) 209
43.3%
2024-04-06T21:17:18.795305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
308
 
13.4%
동 239
 
10.4%
1 156
 
6.8%
2 154
 
6.7%
- 143
 
6.2%
성 132
 
5.8%
3 102
 
4.4%
가 94
 
4.1%
수 83
 
3.6%
6 83
 
3.6%
Other values (52) 800
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 987
43.0%
Decimal Number 853
37.2%
Space Separator 308
 
13.4%
Dash Punctuation 143
 
6.2%
Open Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 239
24.2%
성 132
13.4%
가 94
 
9.5%
수 83
 
8.4%
울 63
 
6.4%
서 63
 
6.4%
구 62
 
6.3%
금 26
 
2.6%
호 25
 
2.5%
행 22
 
2.2%
Other values (37) 178
18.0%
Decimal Number
ValueCountFrequency (%)
1 156
18.3%
2 154
18.1%
3 102
12.0%
6 83
9.7%
7 82
9.6%
5 63
7.4%
8 58
 
6.8%
4 56
 
6.6%
0 53
 
6.2%
9 46
 
5.4%
Space Separator
ValueCountFrequency (%)
308
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 143
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1307
57.0%
Hangul 987
43.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 239
24.2%
성 132
13.4%
가 94
 
9.5%
수 83
 
8.4%
울 63
 
6.4%
서 63
 
6.4%
구 62
 
6.3%
금 26
 
2.6%
호 25
 
2.5%
행 22
 
2.2%
Other values (37) 178
18.0%
Common
ValueCountFrequency (%)
308
23.6%
1 156
11.9%
2 154
11.8%
- 143
10.9%
3 102
 
7.8%
6 83
 
6.4%
7 82
 
6.3%
5 63
 
4.8%
8 58
 
4.4%
4 56
 
4.3%
Other values (5) 102
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1307
57.0%
Hangul 987
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
308
23.6%
1 156
11.9%
2 154
11.8%
- 143
10.9%
3 102
 
7.8%
6 83
 
6.4%
7 82
 
6.3%
5 63
 
4.8%
8 58
 
4.4%
4 56
 
4.3%
Other values (5) 102
 
7.8%
Hangul
ValueCountFrequency (%)
동 239
24.2%
성 132
13.4%
가 94
 
9.5%
수 83
 
8.4%
울 63
 
6.4%
서 63
 
6.4%
구 62
 
6.3%
금 26
 
2.6%
호 25
 
2.5%
행 22
 
2.2%
Other values (37) 178
18.0%

위도
Real number (ℝ)

Distinct174
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.585611
Minimum37.53722
Maximum127.061
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-06T21:17:19.068286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.53722
5-th percentile37.540004
Q137.544498
median37.551177
Q337.56039
95-th percentile37.570346
Maximum127.061
Range89.523777
Interquartile range (IQR)0.01589203

Descriptive statistics

Standard deviation16.240516
Coefficient of variation (CV)0.40015453
Kurtosis25.277203
Mean40.585611
Median Absolute Deviation (MAD)0.0078005697
Skewness5.1953522
Sum7183.6532
Variance263.75437
MonotonicityNot monotonic
2024-04-06T21:17:19.714742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.54816055 2
 
1.1%
37.56847 2
 
1.1%
37.5480320424066 2
 
1.1%
37.5634966783305 1
 
0.6%
37.55823517 1
 
0.6%
37.55796051 1
 
0.6%
37.547335542479 1
 
0.6%
37.5599777503539 1
 
0.6%
37.5525306136723 1
 
0.6%
37.5656127929688 1
 
0.6%
Other values (164) 164
92.7%
ValueCountFrequency (%)
37.53722 1
0.6%
37.53774643 1
0.6%
37.53806305 1
0.6%
37.53871972 1
0.6%
37.53900959503152 1
0.6%
37.53942233447043 1
0.6%
37.53955841 1
0.6%
37.5397071838379 1
0.6%
37.5399704 1
0.6%
37.54001188795923 1
0.6%
ValueCountFrequency (%)
127.06099720132076 1
0.6%
127.05498497206293 1
0.6%
127.05403869196364 1
0.6%
127.0438277284258 1
0.6%
127.016616821289 1
0.6%
127.015312194824 1
0.6%
37.57103729 1
0.6%
37.57092035972494 1
0.6%
37.57060242 1
0.6%
37.57028198 1
0.6%

경도
Real number (ℝ)

Distinct174
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.0071
Minimum37.538419
Maximum127.07004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-04-06T21:17:19.970755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.538419
5-th percentile127.01342
Q1127.02592
median127.04161
Q3127.05276
95-th percentile127.06534
Maximum127.07004
Range89.531619
Interquartile range (IQR)0.026840193

Descriptive statistics

Standard deviation16.242196
Coefficient of variation (CV)0.13097795
Kurtosis25.277168
Mean124.0071
Median Absolute Deviation (MAD)0.0131149
Skewness-5.1953473
Sum21949.256
Variance263.80892
MonotonicityNot monotonic
2024-04-06T21:17:20.233519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.044754 2
 
1.1%
127.0425186 2
 
1.1%
127.015349539879 2
 
1.1%
37.5434837341309 1
 
0.6%
127.0318985 1
 
0.6%
127.0351715 1
 
0.6%
127.065784500807 1
 
0.6%
127.029529282616 1
 
0.6%
127.036710195473 1
 
0.6%
127.046508789063 1
 
0.6%
Other values (164) 164
92.7%
ValueCountFrequency (%)
37.53841854034201 1
0.6%
37.54149572893306 1
0.6%
37.541690826416 1
0.6%
37.5434837341309 1
0.6%
37.54453321261708 1
0.6%
37.54733376708909 1
0.6%
127.01135177623 1
0.6%
127.0120316 1
0.6%
127.0128632 1
0.6%
127.0135574 1
0.6%
ValueCountFrequency (%)
127.0700378 1
0.6%
127.0695648 1
0.6%
127.0686951 1
0.6%
127.0681229 1
0.6%
127.06788687251652 1
0.6%
127.0664967475244 1
0.6%
127.0662079 1
0.6%
127.065784500807 1
0.6%
127.06564994218458 1
0.6%
127.0652653 1
0.6%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
성동구
177 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성동구 177
100.0%

Length

2024-04-06T21:17:20.489507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:17:20.689211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성동구 177
100.0%

단속지점명
Text

UNIQUE 

Distinct177
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-06T21:17:20.959533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length26
Mean length18.615819
Min length11

Characters and Unicode

Total characters3295
Distinct characters283
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique177 ?
Unique (%)100.0%

Sample

1st rowP013_한양대 병원 후문 입구 주변
2nd rowP014_한양대 동문회관 주변
3rd rowP015_마장치안센터 주변
4th rowP016_축산물시장 북문 주변
5th rowP017_마장동 시대약국 주변
ValueCountFrequency (%)
주변 108
 
19.7%
앞 18
 
3.3%
정문 8
 
1.5%
통학로 7
 
1.3%
삼거리 6
 
1.1%
입구 6
 
1.1%
후문 5
 
0.9%
사거리 5
 
0.9%
주민센터 5
 
0.9%
인근 4
 
0.7%
Other values (365) 377
68.7%
2024-04-06T21:17:21.706542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
380
 
11.5%
0 156
 
4.7%
_ 138
 
4.2%
1 129
 
3.9%
주 129
 
3.9%
변 120
 
3.6%
P 111
 
3.4%
2 75
 
2.3%
3 69
 
2.1%
C 67
 
2.0%
Other values (273) 1921
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1778
54.0%
Decimal Number 723
21.9%
Space Separator 380
 
11.5%
Uppercase Letter 213
 
6.5%
Connector Punctuation 138
 
4.2%
Close Punctuation 18
 
0.5%
Open Punctuation 18
 
0.5%
Other Punctuation 16
 
0.5%
Dash Punctuation 11
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 129
 
7.3%
변 120
 
6.7%
동 65
 
3.7%
수 48
 
2.7%
성 46
 
2.6%
로 45
 
2.5%
리 35
 
2.0%
길 34
 
1.9%
초 32
 
1.8%
학 30
 
1.7%
Other values (240) 1194
67.2%
Uppercase Letter
ValueCountFrequency (%)
P 111
52.1%
C 67
31.5%
S 12
 
5.6%
G 5
 
2.3%
K 3
 
1.4%
H 3
 
1.4%
T 2
 
0.9%
W 2
 
0.9%
I 2
 
0.9%
O 1
 
0.5%
Other values (5) 5
 
2.3%
Decimal Number
ValueCountFrequency (%)
0 156
21.6%
1 129
17.8%
2 75
10.4%
3 69
9.5%
6 54
 
7.5%
8 51
 
7.1%
5 49
 
6.8%
7 48
 
6.6%
9 46
 
6.4%
4 46
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 9
56.2%
/ 6
37.5%
, 1
 
6.2%
Space Separator
ValueCountFrequency (%)
380
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 138
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1778
54.0%
Common 1304
39.6%
Latin 213
 
6.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 129
 
7.3%
변 120
 
6.7%
동 65
 
3.7%
수 48
 
2.7%
성 46
 
2.6%
로 45
 
2.5%
리 35
 
2.0%
길 34
 
1.9%
초 32
 
1.8%
학 30
 
1.7%
Other values (240) 1194
67.2%
Common
ValueCountFrequency (%)
380
29.1%
0 156
12.0%
_ 138
 
10.6%
1 129
 
9.9%
2 75
 
5.8%
3 69
 
5.3%
6 54
 
4.1%
8 51
 
3.9%
5 49
 
3.8%
7 48
 
3.7%
Other values (8) 155
11.9%
Latin
ValueCountFrequency (%)
P 111
52.1%
C 67
31.5%
S 12
 
5.6%
G 5
 
2.3%
K 3
 
1.4%
H 3
 
1.4%
T 2
 
0.9%
W 2
 
0.9%
I 2
 
0.9%
O 1
 
0.5%
Other values (5) 5
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1778
54.0%
ASCII 1517
46.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
380
25.0%
0 156
10.3%
_ 138
 
9.1%
1 129
 
8.5%
P 111
 
7.3%
2 75
 
4.9%
3 69
 
4.5%
C 67
 
4.4%
6 54
 
3.6%
8 51
 
3.4%
Other values (23) 287
18.9%
Hangul
ValueCountFrequency (%)
주 129
 
7.3%
변 120
 
6.7%
동 65
 
3.7%
수 48
 
2.7%
성 46
 
2.6%
로 45
 
2.5%
리 35
 
2.0%
길 34
 
1.9%
초 32
 
1.8%
학 30
 
1.7%
Other values (240) 1194
67.2%

현장구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
불법주정차구역
177 

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 177
100.0%

Length

2024-04-06T21:17:21.981837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:17:22.189138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불법주정차구역 177
100.0%

Interactions

2024-04-06T21:17:16.295632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:17:15.938670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:17:16.441014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:17:16.105608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T21:17:22.309860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.991
경도0.9911.000
2024-04-06T21:17:22.452382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.327
경도-0.3271.000

Missing values

2024-04-06T21:17:16.658279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T21:17:16.870905image/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
0행당동 6-237.5602127.041107성동구P013_한양대 병원 후문 입구 주변불법주정차구역
1행당동 19-9837.55896127.040794성동구P014_한양대 동문회관 주변불법주정차구역
2마장동 520-1037.569138127.037521성동구P015_마장치안센터 주변불법주정차구역
3마장동 81837.570602127.042519성동구P016_축산물시장 북문 주변불법주정차구역
4마장동 767-4137.567585127.044815성동구P017_마장동 시대약국 주변불법주정차구역
5마장동 781-137.566624127.043945성동구P018_마장동 주민센터 삼거리 주변불법주정차구역
6마장동 772-237.566051127.042519성동구P019_마장역 2번출구 주변불법주정차구역
7용답동 234-237.56039127.066208성동구P020_용답동 매매센터 정문 주변불법주정차구역
8행당동 319-937.558346127.033371성동구P021_무학여고 사거리 주변불법주정차구역
9성수동2가 300-6 건너37.545502127.055428성동구P022_성수동2가 롯데캐슬 정문 주변불법주정차구역
고정형CCTV지번주소위도경도자치구단속지점명현장구분
167서울 성동구 금호동1가 167-3537.555759127.023837성동구C818_GH01 라이크어시네마 앞불법주정차구역
168서울 성동구 행당동 37-437.557086127.040896성동구C897 살곶이길 356 한양대병원 교차로 남쪽불법주정차구역
169서울 성동구 금호동2가 52237.55336127.02063성동구C057 무수막길 84 금호파출소 (금호2-3가동주민센터 앞)불법주정차구역
170서울 성동구 금호동2가 222-237.554878127.019272성동구C405 금호로 155 금호파출소(해물명가 앞 골목)불법주정차구역
171서울 성동구 금호동2가 446 (금호새마을금고)37.554141127.019644성동구P118_GH23 / 금호산길 68불법주정차구역
172서울 성동구 옥수동 460-1037.540012127.011352성동구P119 독서당로39길 46-50 한남교회불법주정차구역
173서울 성동구 성수동2가 321-1737.542019127.053596성동구C069 성수이로7길 34 무지개어린이공원 주변불법주정차구역
174서울 성동구 금호동2가 530-137.553629127.021186성동구P117_GH23 금호동2가530-1불법주정차구역
175서울 성동구 성수동1가 656-121237.543266127.046791성동구C065 왕십리로2길 20 글로벌 직업개발센터불법주정차구역
176서울 성동구 성수동2가 289-20127.05498537.547334성동구신한은행 성수동지점 부근불법주정차구역