Overview

Dataset statistics

Number of variables6
Number of observations142
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 KiB
Average record size in memory50.9 B

Variable types

Text2
Numeric2
Categorical2

Dataset

Description고정형CCTV지번주소,위도,경도,자치구,단속지점명,현장구분
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-20485/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
단속지점명 has unique valuesUnique

Reproduction

Analysis started2024-04-17 10:36:14.501339
Analysis finished2024-04-17 10:36:15.154753
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고정형CCTV지번주소
Text

Distinct141
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-17T19:36:15.423906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length11.084507
Min length6

Characters and Unicode

Total characters1574
Distinct characters49
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

Unique140 ?
Unique (%)98.6%

Sample

1st row공덕동 463
2nd row아현동 282-1
3rd row아현동 326-16
4th row아현동 784
5th row공덕동 256-4
ValueCountFrequency (%)
서울 52
 
13.4%
마포구 52
 
13.4%
서교동 24
 
6.2%
도화동 15
 
3.9%
성산동 13
 
3.4%
상암동 11
 
2.8%
신수동 8
 
2.1%
대흥동 8
 
2.1%
합정동 7
 
1.8%
망원동 7
 
1.8%
Other values (152) 190
49.1%
2024-04-17T19:36:15.862983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
246
15.6%
동 148
 
9.4%
- 105
 
6.7%
1 90
 
5.7%
서 76
 
4.8%
3 70
 
4.4%
2 64
 
4.1%
4 61
 
3.9%
5 57
 
3.6%
구 54
 
3.4%
Other values (39) 603
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 685
43.5%
Decimal Number 538
34.2%
Space Separator 246
 
15.6%
Dash Punctuation 105
 
6.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 148
21.6%
서 76
11.1%
구 54
 
7.9%
포 53
 
7.7%
마 53
 
7.7%
울 52
 
7.6%
교 30
 
4.4%
화 15
 
2.2%
상 15
 
2.2%
도 15
 
2.2%
Other values (27) 174
25.4%
Decimal Number
ValueCountFrequency (%)
1 90
16.7%
3 70
13.0%
2 64
11.9%
4 61
11.3%
5 57
10.6%
6 48
8.9%
7 41
7.6%
9 37
6.9%
0 35
 
6.5%
8 35
 
6.5%
Space Separator
ValueCountFrequency (%)
246
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 105
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 889
56.5%
Hangul 685
43.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 148
21.6%
서 76
11.1%
구 54
 
7.9%
포 53
 
7.7%
마 53
 
7.7%
울 52
 
7.6%
교 30
 
4.4%
화 15
 
2.2%
상 15
 
2.2%
도 15
 
2.2%
Other values (27) 174
25.4%
Common
ValueCountFrequency (%)
246
27.7%
- 105
11.8%
1 90
 
10.1%
3 70
 
7.9%
2 64
 
7.2%
4 61
 
6.9%
5 57
 
6.4%
6 48
 
5.4%
7 41
 
4.6%
9 37
 
4.2%
Other values (2) 70
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 889
56.5%
Hangul 685
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
246
27.7%
- 105
11.8%
1 90
 
10.1%
3 70
 
7.9%
2 64
 
7.2%
4 61
 
6.9%
5 57
 
6.4%
6 48
 
5.4%
7 41
 
4.6%
9 37
 
4.2%
Other values (2) 70
 
7.9%
Hangul
ValueCountFrequency (%)
동 148
21.6%
서 76
11.1%
구 54
 
7.9%
포 53
 
7.7%
마 53
 
7.7%
울 52
 
7.6%
교 30
 
4.4%
화 15
 
2.2%
상 15
 
2.2%
도 15
 
2.2%
Other values (27) 174
25.4%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct141
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.554298
Minimum37.537699
Maximum37.585044
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-17T19:36:15.989919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.537699
5-th percentile37.540313
Q137.546682
median37.5522
Q337.558593
95-th percentile37.578726
Maximum37.585044
Range0.047345211
Interquartile range (IQR)0.011911484

Descriptive statistics

Standard deviation0.010799763
Coefficient of variation (CV)0.00028757728
Kurtosis0.58631505
Mean37.554298
Median Absolute Deviation (MAD)0.005826815
Skewness0.97627144
Sum5332.7104
Variance0.00011663488
MonotonicityNot monotonic
2024-04-17T19:36:16.108792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5508021700653 2
 
1.4%
37.58130194 1
 
0.7%
37.5794419093126 1
 
0.7%
37.5805267876515 1
 
0.7%
37.5816223202625 1
 
0.7%
37.581324224744 1
 
0.7%
37.5850443805494 1
 
0.7%
37.5787580201272 1
 
0.7%
37.5758805538364 1
 
0.7%
37.55012053 1
 
0.7%
Other values (131) 131
92.3%
ValueCountFrequency (%)
37.53769917 1
0.7%
37.53782577 1
0.7%
37.53867632 1
0.7%
37.5395026364148 1
0.7%
37.53967881 1
0.7%
37.53980547974158 1
0.7%
37.5400938 1
0.7%
37.54030273 1
0.7%
37.54051281 1
0.7%
37.54128166 1
0.7%
ValueCountFrequency (%)
37.5850443805494 1
0.7%
37.583129757070445 1
0.7%
37.5816223202625 1
0.7%
37.581324224744 1
0.7%
37.58130194 1
0.7%
37.5805267876515 1
0.7%
37.5794419093126 1
0.7%
37.5787580201272 1
0.7%
37.5781215 1
0.7%
37.5770108208633 1
0.7%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct141
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.92564
Minimum126.87987
Maximum126.96027
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-17T19:36:16.261324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.87987
5-th percentile126.89041
Q1126.91229
median126.92377
Q3126.9451
95-th percentile126.95375
Maximum126.96027
Range0.080400657
Interquartile range (IQR)0.032805453

Descriptive statistics

Standard deviation0.019530547
Coefficient of variation (CV)0.00015387392
Kurtosis-0.80841147
Mean126.92564
Median Absolute Deviation (MAD)0.01679175
Skewness-0.24952126
Sum18023.442
Variance0.00038144226
MonotonicityNot monotonic
2024-04-17T19:36:16.401851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.916715922466 2
 
1.4%
126.8921143 1
 
0.7%
126.890322604776 1
 
0.7%
126.88772655104 1
 
0.7%
126.886049581236 1
 
0.7%
126.888548408154 1
 
0.7%
126.879869563728 1
 
0.7%
126.880806276364 1
 
0.7%
126.8949825596 1
 
0.7%
126.9548215 1
 
0.7%
Other values (131) 131
92.3%
ValueCountFrequency (%)
126.879869563728 1
0.7%
126.880806276364 1
0.7%
126.88482755974434 1
0.7%
126.886049581236 1
0.7%
126.88772655104 1
0.7%
126.888548408154 1
0.7%
126.890099645545 1
0.7%
126.890322604776 1
0.7%
126.8921143 1
0.7%
126.8936508 1
0.7%
ValueCountFrequency (%)
126.96027022088732 1
0.7%
126.9558245 1
0.7%
126.9553603 1
0.7%
126.9551748 1
0.7%
126.9551048 1
0.7%
126.9548215 1
0.7%
126.95404971935456 1
0.7%
126.9537761 1
0.7%
126.95325922769524 1
0.7%
126.952968 1
0.7%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
마포구
142 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
마포구 142
100.0%

Length

2024-04-17T19:36:16.523249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:36:16.606807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마포구 142
100.0%

단속지점명
Text

UNIQUE 

Distinct142
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-17T19:36:16.777976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length10.084507
Min length6

Characters and Unicode

Total characters1432
Distinct characters242
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)100.0%

Sample

1st row마포경찰서 주변
2nd row아현초등학교 주변
3rd row행화정교회 주변
4th row공덕지구대 주변
5th row공덕초등학교주변
ValueCountFrequency (%)
주변 120
39.0%
사거리 7
 
2.3%
정문 4
 
1.3%
삼거리 4
 
1.3%
후문 3
 
1.0%
홍대입구역 2
 
0.6%
망원나들목 2
 
0.6%
상가 2
 
0.6%
2번출구 2
 
0.6%
공영주차장 2
 
0.6%
Other values (158) 160
51.9%
2024-04-17T19:36:17.082839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
177
 
12.4%
주 133
 
9.3%
변 127
 
8.9%
교 26
 
1.8%
리 23
 
1.6%
트 19
 
1.3%
아 19
 
1.3%
마 18
 
1.3%
파 17
 
1.2%
스 17
 
1.2%
Other values (232) 856
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1201
83.9%
Space Separator 177
 
12.4%
Uppercase Letter 23
 
1.6%
Decimal Number 19
 
1.3%
Close Punctuation 6
 
0.4%
Open Punctuation 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 133
 
11.1%
변 127
 
10.6%
교 26
 
2.2%
리 23
 
1.9%
트 19
 
1.6%
아 19
 
1.6%
마 18
 
1.5%
파 17
 
1.4%
스 17
 
1.4%
구 16
 
1.3%
Other values (209) 786
65.4%
Uppercase Letter
ValueCountFrequency (%)
B 3
13.0%
A 3
13.0%
C 3
13.0%
T 3
13.0%
M 2
8.7%
G 2
8.7%
L 1
 
4.3%
I 1
 
4.3%
D 1
 
4.3%
J 1
 
4.3%
Other values (3) 3
13.0%
Decimal Number
ValueCountFrequency (%)
2 7
36.8%
1 6
31.6%
3 2
 
10.5%
8 1
 
5.3%
9 1
 
5.3%
5 1
 
5.3%
0 1
 
5.3%
Space Separator
ValueCountFrequency (%)
177
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1201
83.9%
Common 208
 
14.5%
Latin 23
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 133
 
11.1%
변 127
 
10.6%
교 26
 
2.2%
리 23
 
1.9%
트 19
 
1.6%
아 19
 
1.6%
마 18
 
1.5%
파 17
 
1.4%
스 17
 
1.4%
구 16
 
1.3%
Other values (209) 786
65.4%
Latin
ValueCountFrequency (%)
B 3
13.0%
A 3
13.0%
C 3
13.0%
T 3
13.0%
M 2
8.7%
G 2
8.7%
L 1
 
4.3%
I 1
 
4.3%
D 1
 
4.3%
J 1
 
4.3%
Other values (3) 3
13.0%
Common
ValueCountFrequency (%)
177
85.1%
2 7
 
3.4%
) 6
 
2.9%
( 6
 
2.9%
1 6
 
2.9%
3 2
 
1.0%
8 1
 
0.5%
9 1
 
0.5%
5 1
 
0.5%
0 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1201
83.9%
ASCII 231
 
16.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
177
76.6%
2 7
 
3.0%
) 6
 
2.6%
( 6
 
2.6%
1 6
 
2.6%
B 3
 
1.3%
A 3
 
1.3%
C 3
 
1.3%
T 3
 
1.3%
M 2
 
0.9%
Other values (13) 15
 
6.5%
Hangul
ValueCountFrequency (%)
주 133
 
11.1%
변 127
 
10.6%
교 26
 
2.2%
리 23
 
1.9%
트 19
 
1.6%
아 19
 
1.6%
마 18
 
1.5%
파 17
 
1.4%
스 17
 
1.4%
구 16
 
1.3%
Other values (209) 786
65.4%

현장구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
불법주정차구역
142 

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 142
100.0%

Length

2024-04-17T19:36:17.220425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T19:36:17.307464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불법주정차구역 142
100.0%

Interactions

2024-04-17T19:36:14.827053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:36:14.680663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:36:14.901629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T19:36:14.746399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T19:36:17.362582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.871
경도0.8711.000
2024-04-17T19:36:17.432017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.732
경도-0.7321.000

Missing values

2024-04-17T19:36:15.016687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T19:36:15.113004image/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
0공덕동 46337.550121126.954821마포구마포경찰서 주변불법주정차구역
1아현동 282-137.55514126.955825마포구아현초등학교 주변불법주정차구역
2아현동 326-1637.555392126.955175마포구행화정교회 주변불법주정차구역
3아현동 78437.551553126.953776마포구공덕지구대 주변불법주정차구역
4공덕동 256-437.545775126.955105마포구공덕초등학교주변불법주정차구역
5아현동 73837.552538126.95536마포구마포트라팰리스2차 주변불법주정차구역
6도화동 204-1037.538676126.94758마포구근신빌딩 주변불법주정차구역
7도화동 200-1037.540303126.951529마포구도화동 동원베네스트 주변불법주정차구역
8도화동 149-237.537699126.947537마포구우성아파트 주변불법주정차구역
9마포동 226-137.537826126.945864마포구진선미 어린이집 주변불법주정차구역
고정형CCTV지번주소위도경도자치구단속지점명현장구분
132서울 마포구 대흥동 20-437.553272126.945744마포구마포프레스티지자이3단지 주변불법주정차구역
133서울 마포구 창전동 45037.549383126.931373마포구이랜드청년주택 주변불법주정차구역
134서울 마포구 서교동 403-637.549556126.920838마포구호연빌딩 주변불법주정차구역
135서울 마포구 서교동 460-2537.556582126.916903마포구서교대우미래사랑 주변불법주정차구역
136서울 마포구 성산동 128-937.568376126.914152마포구가좌역 2번출구 주변불법주정차구역
137서울 마포구 염리동 53237.552171126.946606마포구마포프레스티지자이1단지 주변불법주정차구역
138서울 마포구 상암동 162337.575464126.898534마포구롯데몰상암DMC점(예정) 주변불법주정차구역
139서울 마포구 서교동 48637.554198126.923621마포구서교초등학교 주변불법주정차구역
140서울 마포구 서교동 408-2137.549303126.920814마포구뉴에라 홍대점 주변불법주정차구역
141서울 마포구 성산동 292-137.55802126.908423마포구(구)망원우체국 사거리불법주정차구역