Overview

Dataset statistics

Number of variables6
Number of observations90
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory51.5 B

Variable types

Text2
Numeric2
Categorical2

Dataset

Description서울특별시 중랑구의 불법주정차 위반 단속 cctv의 지번주소, 위도, 경도, 단속지점명, 현장구분에 대한 데이터를 제공합니다.
Author서울특별시 중랑구
URLhttps://www.data.go.kr/data/15080653/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 08:36:04.330444
Analysis finished2023-12-12 08:36:05.200336
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고정형CCTV지번주소
Text

UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-12T17:36:05.412902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length15.811111
Min length12

Characters and Unicode

Total characters1423
Distinct characters28
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

Unique90 ?
Unique (%)100.0%

Sample

1st row서울 중랑구 신내동 667
2nd row서울 중랑구 중화동 303-1
3rd row서울 중랑구 상봉동 102-73
4th row서울 중랑구 면목동 102-19
5th row서울 중랑구 면목동 496-26
ValueCountFrequency (%)
서울 90
25.0%
중랑구 90
25.0%
면목동 30
 
8.3%
상봉동 17
 
4.7%
신내동 13
 
3.6%
묵동 11
 
3.1%
망우동 11
 
3.1%
중화동 8
 
2.2%
200-3 1
 
0.3%
236-7 1
 
0.3%
Other values (88) 88
24.4%
2023-12-12T17:36:05.927367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
270
19.0%
중 98
 
6.9%
서 90
 
6.3%
랑 90
 
6.3%
구 90
 
6.3%
동 90
 
6.3%
울 90
 
6.3%
1 81
 
5.7%
- 69
 
4.8%
2 53
 
3.7%
Other values (18) 402
28.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 709
49.8%
Decimal Number 375
26.4%
Space Separator 270
 
19.0%
Dash Punctuation 69
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 98
13.8%
서 90
12.7%
랑 90
12.7%
구 90
12.7%
동 90
12.7%
울 90
12.7%
목 30
 
4.2%
면 30
 
4.2%
상 17
 
2.4%
봉 17
 
2.4%
Other values (6) 67
9.4%
Decimal Number
ValueCountFrequency (%)
1 81
21.6%
2 53
14.1%
3 40
10.7%
4 36
9.6%
6 34
9.1%
5 32
 
8.5%
0 29
 
7.7%
8 26
 
6.9%
7 24
 
6.4%
9 20
 
5.3%
Space Separator
ValueCountFrequency (%)
270
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 714
50.2%
Hangul 709
49.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 98
13.8%
서 90
12.7%
랑 90
12.7%
구 90
12.7%
동 90
12.7%
울 90
12.7%
목 30
 
4.2%
면 30
 
4.2%
상 17
 
2.4%
봉 17
 
2.4%
Other values (6) 67
9.4%
Common
ValueCountFrequency (%)
270
37.8%
1 81
 
11.3%
- 69
 
9.7%
2 53
 
7.4%
3 40
 
5.6%
4 36
 
5.0%
6 34
 
4.8%
5 32
 
4.5%
0 29
 
4.1%
8 26
 
3.6%
Other values (2) 44
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 714
50.2%
Hangul 709
49.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
270
37.8%
1 81
 
11.3%
- 69
 
9.7%
2 53
 
7.4%
3 40
 
5.6%
4 36
 
5.0%
6 34
 
4.8%
5 32
 
4.5%
0 29
 
4.1%
8 26
 
3.6%
Other values (2) 44
 
6.2%
Hangul
ValueCountFrequency (%)
중 98
13.8%
서 90
12.7%
랑 90
12.7%
구 90
12.7%
동 90
12.7%
울 90
12.7%
목 30
 
4.2%
면 30
 
4.2%
상 17
 
2.4%
봉 17
 
2.4%
Other values (6) 67
9.4%

위도
Real number (ℝ)

Distinct89
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.596283
Minimum37.571658
Maximum37.617946
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-12T17:36:06.106918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.571658
5-th percentile37.576546
Q137.58849
median37.595492
Q337.604963
95-th percentile37.616218
Maximum37.617946
Range0.04628764
Interquartile range (IQR)0.01647325

Descriptive statistics

Standard deviation0.011952161
Coefficient of variation (CV)0.00031790805
Kurtosis-0.76165432
Mean37.596283
Median Absolute Deviation (MAD)0.00855
Skewness0.0028548055
Sum3383.6655
Variance0.00014285416
MonotonicityNot monotonic
2023-12-12T17:36:06.266379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.59721 2
 
2.2%
37.60683 1
 
1.1%
37.57822491 1
 
1.1%
37.60279324 1
 
1.1%
37.59407847 1
 
1.1%
37.58124642 1
 
1.1%
37.61645325 1
 
1.1%
37.58334769 1
 
1.1%
37.59874862 1
 
1.1%
37.60440396 1
 
1.1%
Other values (79) 79
87.8%
ValueCountFrequency (%)
37.571658 1
1.1%
37.574091 1
1.1%
37.57473 1
1.1%
37.57526 1
1.1%
37.5753322 1
1.1%
37.57803 1
1.1%
37.57822491 1
1.1%
37.578696 1
1.1%
37.58006 1
1.1%
37.58035207 1
1.1%
ValueCountFrequency (%)
37.61794564 1
1.1%
37.61734852 1
1.1%
37.616566 1
1.1%
37.61649 1
1.1%
37.61645325 1
1.1%
37.61593 1
1.1%
37.61504 1
1.1%
37.6150072 1
1.1%
37.61468 1
1.1%
37.61364 1
1.1%

경도
Real number (ℝ)

Distinct89
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.09354
Minimum37.57526
Maximum127.10895
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-12T17:36:06.418611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.57526
5-th percentile127.07497
Q1127.08044
median127.08734
Q3127.09379
95-th percentile127.10232
Maximum127.10895
Range89.533686
Interquartile range (IQR)0.01334855

Descriptive statistics

Standard deviation9.4354887
Coefficient of variation (CV)0.074829278
Kurtosis89.99985
Mean126.09354
Median Absolute Deviation (MAD)0.0065072
Skewness-9.4868213
Sum11348.419
Variance89.028448
MonotonicityNot monotonic
2023-12-12T17:36:06.838457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.09034 2
 
2.2%
127.0953 1
 
1.1%
127.086467 1
 
1.1%
127.0870118 1
 
1.1%
127.0772015 1
 
1.1%
127.0833356 1
 
1.1%
127.0824546 1
 
1.1%
127.0837625 1
 
1.1%
127.0827323 1
 
1.1%
127.1060449 1
 
1.1%
Other values (79) 79
87.8%
ValueCountFrequency (%)
37.57526 1
1.1%
127.073412 1
1.1%
127.0742 1
1.1%
127.0743784 1
1.1%
127.0745186 1
1.1%
127.075521 1
1.1%
127.076524 1
1.1%
127.07672 1
1.1%
127.076998 1
1.1%
127.077146 1
1.1%
ValueCountFrequency (%)
127.108946 1
1.1%
127.1081735 1
1.1%
127.1060449 1
1.1%
127.104375 1
1.1%
127.102745 1
1.1%
127.10181 1
1.1%
127.10095 1
1.1%
127.100944 1
1.1%
127.10012 1
1.1%
127.09939 1
1.1%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
중랑구
90 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중랑구 90
100.0%

Length

2023-12-12T17:36:06.964460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:36:07.076251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중랑구 90
100.0%

단속지점명
Text

UNIQUE 

Distinct90
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-12T17:36:07.318119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length11.588889
Min length5

Characters and Unicode

Total characters1043
Distinct characters208
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

Unique90 ?
Unique (%)100.0%

Sample

1st row중랑구청 사거리 1001안경
2nd row중화역 파리바게뜨
3rd row상봉역 3번출구 파리바게뜨
4th row면목역 파리바게뜨
5th row사가정역 2번출구
ValueCountFrequency (%)
사거리 6
 
3.6%
앞 6
 
3.6%
정문 5
 
3.0%
파리바게뜨 3
 
1.8%
상봉코스트코 2
 
1.2%
맞은편 2
 
1.2%
중랑역 2
 
1.2%
교통섬 2
 
1.2%
중랑초등학교 2
 
1.2%
국민은행 2
 
1.2%
Other values (129) 137
81.1%
2023-12-12T17:36:07.852822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
80
 
7.7%
( 30
 
2.9%
) 30
 
2.9%
초 29
 
2.8%
교 24
 
2.3%
트 20
 
1.9%
리 20
 
1.9%
학 20
 
1.9%
면 19
 
1.8%
동 19
 
1.8%
Other values (198) 752
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 858
82.3%
Space Separator 80
 
7.7%
Decimal Number 38
 
3.6%
Open Punctuation 30
 
2.9%
Close Punctuation 30
 
2.9%
Uppercase Letter 6
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 29
 
3.4%
교 24
 
2.8%
트 20
 
2.3%
리 20
 
2.3%
학 20
 
2.3%
면 19
 
2.2%
동 19
 
2.2%
등 19
 
2.2%
파 19
 
2.2%
봉 18
 
2.1%
Other values (182) 651
75.9%
Decimal Number
ValueCountFrequency (%)
1 15
39.5%
2 6
 
15.8%
5 5
 
13.2%
0 5
 
13.2%
4 3
 
7.9%
3 2
 
5.3%
7 1
 
2.6%
6 1
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
C 2
33.3%
U 2
33.3%
G 1
16.7%
S 1
16.7%
Space Separator
ValueCountFrequency (%)
80
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 858
82.3%
Common 179
 
17.2%
Latin 6
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 29
 
3.4%
교 24
 
2.8%
트 20
 
2.3%
리 20
 
2.3%
학 20
 
2.3%
면 19
 
2.2%
동 19
 
2.2%
등 19
 
2.2%
파 19
 
2.2%
봉 18
 
2.1%
Other values (182) 651
75.9%
Common
ValueCountFrequency (%)
80
44.7%
( 30
 
16.8%
) 30
 
16.8%
1 15
 
8.4%
2 6
 
3.4%
5 5
 
2.8%
0 5
 
2.8%
4 3
 
1.7%
3 2
 
1.1%
, 1
 
0.6%
Other values (2) 2
 
1.1%
Latin
ValueCountFrequency (%)
C 2
33.3%
U 2
33.3%
G 1
16.7%
S 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 858
82.3%
ASCII 185
 
17.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
80
43.2%
( 30
 
16.2%
) 30
 
16.2%
1 15
 
8.1%
2 6
 
3.2%
5 5
 
2.7%
0 5
 
2.7%
4 3
 
1.6%
C 2
 
1.1%
U 2
 
1.1%
Other values (6) 7
 
3.8%
Hangul
ValueCountFrequency (%)
초 29
 
3.4%
교 24
 
2.8%
트 20
 
2.3%
리 20
 
2.3%
학 20
 
2.3%
면 19
 
2.2%
동 19
 
2.2%
등 19
 
2.2%
파 19
 
2.2%
봉 18
 
2.1%
Other values (182) 651
75.9%

현장구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
불법주정차구역
90 

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 90
100.0%

Length

2023-12-12T17:36:08.046062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:36:08.203743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불법주정차구역 90
100.0%

Interactions

2023-12-12T17:36:04.822949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:04.635190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:04.922649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:36:04.721626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:36:08.303065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고정형CCTV지번주소위도경도단속지점명
고정형CCTV지번주소1.0001.0001.0001.000
위도1.0001.0000.4141.000
경도1.0000.4141.0001.000
단속지점명1.0001.0001.0001.000
2023-12-12T17:36:08.409848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.094
경도0.0941.000

Missing values

2023-12-12T17:36:05.041812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:36:05.155420image/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 중랑구 신내동 66737.60683127.0953중랑구중랑구청 사거리 1001안경불법주정차구역
1서울 중랑구 중화동 303-137.60152127.07941중랑구중화역 파리바게뜨불법주정차구역
2서울 중랑구 상봉동 102-7337.59463127.08602중랑구상봉역 3번출구 파리바게뜨불법주정차구역
3서울 중랑구 면목동 102-1937.58839127.08762중랑구면목역 파리바게뜨불법주정차구역
4서울 중랑구 면목동 496-2637.58071127.0884중랑구사가정역 2번출구불법주정차구역
5서울 중랑구 면목동 88-6037.5924127.0933중랑구상봉로 기사식당 동방빌딩불법주정차구역
6서울 중랑구 면목동 68-1137.58699127.09443중랑구상봉로1길 서일타운불법주정차구역
7서울 중랑구 상봉동 8337.59638127.09292중랑구상봉터미널불법주정차구역
8서울 중랑구 망우동 403-6037.59546127.10012중랑구우림시장 오거리 베스킨라빈스불법주정차구역
9서울 중랑구 망우동 490-1337.59809127.09514중랑구망우로60길 구맛솜씨길 1번지통닭불법주정차구역
고정형CCTV지번주소위도경도자치구단속지점명현장구분
80서울 중랑구 면목동 596-437.581776127.087941중랑구왕십리곱창(사가정로51길)불법주정차구역
81서울 중랑구 망우동 244-537.605353127.104375중랑구동원초등학교 정문 맞은편불법주정차구역
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