Overview

Dataset statistics

Number of variables6
Number of observations411
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.2 KiB
Average record size in memory50.3 B

Variable types

Text2
Numeric2
Categorical2

Dataset

Description고정형CCTV지번주소,위도,경도,자치구,단속지점명,현장구분
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-20493/S/1/datasetView.do

Alerts

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

Reproduction

Analysis started2024-04-06 12:30:59.298213
Analysis finished2024-04-06 12:31:03.941270
Duration4.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고정형CCTV지번주소
Text

Distinct384
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-06T21:31:04.403640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length11.158151
Min length6

Characters and Unicode

Total characters4586
Distinct characters38
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

Unique361 ?
Unique (%)87.8%

Sample

1st row방배본동 19-3
2nd row방배1동 906-13
3rd row방배1동 906-16
4th row반포4동 51-5
5th row서초2동 1325-1
ValueCountFrequency (%)
서울 78
 
7.9%
서초구 77
 
7.8%
반포4동 39
 
4.0%
서초3동 38
 
3.9%
잠원동 33
 
3.4%
서초동 32
 
3.3%
서초2동 28
 
2.9%
양재1동 27
 
2.7%
양재2동 27
 
2.7%
서초4동 24
 
2.4%
Other values (393) 579
59.0%
2024-04-06T21:31:05.121988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
572
12.5%
1 469
 
10.2%
동 416
 
9.1%
- 342
 
7.5%
서 299
 
6.5%
2 264
 
5.8%
4 234
 
5.1%
3 232
 
5.1%
초 221
 
4.8%
6 168
 
3.7%
Other values (28) 1369
29.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2012
43.9%
Other Letter 1649
36.0%
Space Separator 572
 
12.5%
Dash Punctuation 342
 
7.5%
Open Punctuation 5
 
0.1%
Close Punctuation 5
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 416
25.2%
서 299
18.1%
초 221
13.4%
배 84
 
5.1%
방 84
 
5.1%
울 78
 
4.7%
구 77
 
4.7%
포 73
 
4.4%
반 73
 
4.4%
양 60
 
3.6%
Other values (13) 184
11.2%
Decimal Number
ValueCountFrequency (%)
1 469
23.3%
2 264
13.1%
4 234
11.6%
3 232
11.5%
6 168
 
8.3%
5 160
 
8.0%
7 137
 
6.8%
8 125
 
6.2%
9 112
 
5.6%
0 111
 
5.5%
Space Separator
ValueCountFrequency (%)
572
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 342
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2937
64.0%
Hangul 1649
36.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 416
25.2%
서 299
18.1%
초 221
13.4%
배 84
 
5.1%
방 84
 
5.1%
울 78
 
4.7%
구 77
 
4.7%
포 73
 
4.4%
반 73
 
4.4%
양 60
 
3.6%
Other values (13) 184
11.2%
Common
ValueCountFrequency (%)
572
19.5%
1 469
16.0%
- 342
11.6%
2 264
9.0%
4 234
8.0%
3 232
7.9%
6 168
 
5.7%
5 160
 
5.4%
7 137
 
4.7%
8 125
 
4.3%
Other values (5) 234
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2937
64.0%
Hangul 1649
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
572
19.5%
1 469
16.0%
- 342
11.6%
2 264
9.0%
4 234
8.0%
3 232
7.9%
6 168
 
5.7%
5 160
 
5.4%
7 137
 
4.7%
8 125
 
4.3%
Other values (5) 234
8.0%
Hangul
ValueCountFrequency (%)
동 416
25.2%
서 299
18.1%
초 221
13.4%
배 84
 
5.1%
방 84
 
5.1%
울 78
 
4.7%
구 77
 
4.7%
포 73
 
4.4%
반 73
 
4.4%
양 60
 
3.6%
Other values (13) 184
11.2%

위도
Real number (ℝ)

Distinct410
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.489415
Minimum37.443672
Maximum37.520767
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-06T21:31:05.484822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.443672
5-th percentile37.461648
Q137.482225
median37.490531
Q337.499454
95-th percentile37.513253
Maximum37.520767
Range0.077095
Interquartile range (IQR)0.017228985

Descriptive statistics

Standard deviation0.014705818
Coefficient of variation (CV)0.00039226587
Kurtosis0.40456392
Mean37.489415
Median Absolute Deviation (MAD)0.0086010854
Skewness-0.55912925
Sum15408.15
Variance0.00021626109
MonotonicityNot monotonic
2024-04-06T21:31:05.904670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.49600819 2
 
0.5%
37.49549785 1
 
0.2%
37.47713325 1
 
0.2%
37.49476047 1
 
0.2%
37.4940386 1
 
0.2%
37.49390236 1
 
0.2%
37.4864187 1
 
0.2%
37.49340281 1
 
0.2%
37.49319481 1
 
0.2%
37.47851634 1
 
0.2%
Other values (400) 400
97.3%
ValueCountFrequency (%)
37.44367183 1
0.2%
37.44493071 1
0.2%
37.4473249504426 1
0.2%
37.44741089 1
0.2%
37.44782281 1
0.2%
37.44878126 1
0.2%
37.4502115 1
0.2%
37.45446969 1
0.2%
37.45457041 1
0.2%
37.45473781 1
0.2%
ValueCountFrequency (%)
37.52076683 1
0.2%
37.51974342 1
0.2%
37.51910184 1
0.2%
37.51873742 1
0.2%
37.51845346 1
0.2%
37.51839077 1
0.2%
37.51805983 1
0.2%
37.51770551 1
0.2%
37.51627419 1
0.2%
37.51619096 1
0.2%

경도
Real number (ℝ)

Distinct410
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.01374
Minimum126.98182
Maximum127.06364
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-04-06T21:31:06.210874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.98182
5-th percentile126.98521
Q1127.00058
median127.01295
Q3127.02468
95-th percentile127.04512
Maximum127.06364
Range0.081828
Interquartile range (IQR)0.02410165

Descriptive statistics

Standard deviation0.017638206
Coefficient of variation (CV)0.00013886849
Kurtosis-0.17957963
Mean127.01374
Median Absolute Deviation (MAD)0.012137796
Skewness0.34113864
Sum52202.646
Variance0.00031110633
MonotonicityNot monotonic
2024-04-06T21:31:06.581943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0197353 2
 
0.5%
126.9888396 1
 
0.2%
126.9828215 1
 
0.2%
127.002155 1
 
0.2%
127.0106497 1
 
0.2%
127.0105014 1
 
0.2%
126.9830817 1
 
0.2%
127.0091322 1
 
0.2%
127.008491 1
 
0.2%
127.0350485 1
 
0.2%
Other values (400) 400
97.3%
ValueCountFrequency (%)
126.9818165 1
0.2%
126.9818975 1
0.2%
126.9823927 1
0.2%
126.9824706 1
0.2%
126.9826898 1
0.2%
126.9828215 1
0.2%
126.9829792 1
0.2%
126.9830817 1
0.2%
126.983156 1
0.2%
126.9831825 1
0.2%
ValueCountFrequency (%)
127.0636445 1
0.2%
127.06178 1
0.2%
127.0602946 1
0.2%
127.0591375 1
0.2%
127.0590629 1
0.2%
127.0575417 1
0.2%
127.0574218 1
0.2%
127.056764 1
0.2%
127.056296409418 1
0.2%
127.0554108 1
0.2%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
서초구
411 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서초구 411
100.0%

Length

2024-04-06T21:31:06.855072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:31:07.072186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서초구 411
100.0%

단속지점명
Text

UNIQUE 

Distinct411
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-04-06T21:31:07.348953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length9.6009732
Min length4

Characters and Unicode

Total characters3946
Distinct characters369
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

Unique411 ?
Unique (%)100.0%

Sample

1st row서래초병설유치원주변
2nd row서리풀e편한세상APT 주변
3rd row서리풀e편한세상APT2번출구주변
4th row서석빌딩사거리 주변
5th row서운중학교뒷길 주변
ValueCountFrequency (%)
주변 119
 
17.0%
앞 20
 
2.9%
삼거리 11
 
1.6%
입구 9
 
1.3%
부근 9
 
1.3%
사거리 5
 
0.7%
주차장 5
 
0.7%
건너편 4
 
0.6%
아이파크 4
 
0.6%
리오센트아파트 4
 
0.6%
Other values (479) 511
72.9%
2024-04-06T21:31:07.960698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 330
 
8.4%
변 305
 
7.7%
290
 
7.3%
서 83
 
2.1%
초 74
 
1.9%
동 74
 
1.9%
1 64
 
1.6%
원 61
 
1.5%
빌 61
 
1.5%
아 58
 
1.5%
Other values (359) 2546
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3357
85.1%
Space Separator 290
 
7.3%
Decimal Number 196
 
5.0%
Uppercase Letter 65
 
1.6%
Dash Punctuation 11
 
0.3%
Open Punctuation 9
 
0.2%
Close Punctuation 9
 
0.2%
Lowercase Letter 8
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 330
 
9.8%
변 305
 
9.1%
서 83
 
2.5%
초 74
 
2.2%
동 74
 
2.2%
원 61
 
1.8%
빌 61
 
1.8%
아 58
 
1.7%
구 58
 
1.7%
트 58
 
1.7%
Other values (321) 2195
65.4%
Uppercase Letter
ValueCountFrequency (%)
A 10
15.4%
T 9
13.8%
P 8
12.3%
G 6
9.2%
L 4
 
6.2%
S 4
 
6.2%
B 3
 
4.6%
M 3
 
4.6%
C 3
 
4.6%
E 2
 
3.1%
Other values (9) 13
20.0%
Decimal Number
ValueCountFrequency (%)
1 64
32.7%
2 31
15.8%
0 29
14.8%
3 18
 
9.2%
4 18
 
9.2%
5 13
 
6.6%
6 9
 
4.6%
8 7
 
3.6%
7 6
 
3.1%
9 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
e 5
62.5%
v 1
 
12.5%
f 1
 
12.5%
i 1
 
12.5%
Space Separator
ValueCountFrequency (%)
290
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3357
85.1%
Common 516
 
13.1%
Latin 73
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 330
 
9.8%
변 305
 
9.1%
서 83
 
2.5%
초 74
 
2.2%
동 74
 
2.2%
원 61
 
1.8%
빌 61
 
1.8%
아 58
 
1.7%
구 58
 
1.7%
트 58
 
1.7%
Other values (321) 2195
65.4%
Latin
ValueCountFrequency (%)
A 10
13.7%
T 9
12.3%
P 8
11.0%
G 6
 
8.2%
e 5
 
6.8%
L 4
 
5.5%
S 4
 
5.5%
B 3
 
4.1%
M 3
 
4.1%
C 3
 
4.1%
Other values (13) 18
24.7%
Common
ValueCountFrequency (%)
290
56.2%
1 64
 
12.4%
2 31
 
6.0%
0 29
 
5.6%
3 18
 
3.5%
4 18
 
3.5%
5 13
 
2.5%
- 11
 
2.1%
( 9
 
1.7%
) 9
 
1.7%
Other values (5) 24
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3357
85.1%
ASCII 589
 
14.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 330
 
9.8%
변 305
 
9.1%
서 83
 
2.5%
초 74
 
2.2%
동 74
 
2.2%
원 61
 
1.8%
빌 61
 
1.8%
아 58
 
1.7%
구 58
 
1.7%
트 58
 
1.7%
Other values (321) 2195
65.4%
ASCII
ValueCountFrequency (%)
290
49.2%
1 64
 
10.9%
2 31
 
5.3%
0 29
 
4.9%
3 18
 
3.1%
4 18
 
3.1%
5 13
 
2.2%
- 11
 
1.9%
A 10
 
1.7%
( 9
 
1.5%
Other values (28) 96
 
16.3%

현장구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
불법주정차구역
411 

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 411
100.0%

Length

2024-04-06T21:31:08.220261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:31:08.413263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불법주정차구역 411
100.0%

Interactions

2024-04-06T21:31:02.717952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:31:02.138874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:31:03.072934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:31:02.432172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T21:31:08.533879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.835
경도0.8351.000
2024-04-06T21:31:08.708550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.290
경도-0.2901.000

Missing values

2024-04-06T21:31:03.512691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T21:31:03.748192image/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
0방배본동 19-337.495498126.98884서초구서래초병설유치원주변불법주정차구역
1방배1동 906-1337.483566126.99707서초구서리풀e편한세상APT 주변불법주정차구역
2방배1동 906-1637.484531126.997412서초구서리풀e편한세상APT2번출구주변불법주정차구역
3반포4동 51-537.501277127.011311서초구서석빌딩사거리 주변불법주정차구역
4서초2동 1325-137.493085127.024155서초구서운중학교뒷길 주변불법주정차구역
5양재1동 25-337.481504127.037051서초구서울가정행정법원 주변불법주정차구역
6서초1동 1627-137.489027127.016715서초구서울교대정문주변불법주정차구역
7방배2동 447-737.476828126.984773서초구서울메트로뒷길 주변불법주정차구역
8서초3동 170437.494719127.010298서초구서울중앙법원주변불법주정차구역
9내곡동 (신원동) 24737.447823127.057422서초구서울청계숲유치원주변불법주정차구역
고정형CCTV지번주소위도경도자치구단속지점명현장구분
401서울 서초구 서초동 1593-737.486528127.012932서초구BMW 서비스불법주정차구역
402서울 서초구 방배동 876-137.48917126.993822서초구방배4동 876-1 세븐일레븐 앞불법주정차구역
403서울 서초구 방배동 762-237.496291126.98475서초구롯데캐슬헤론불법주정차구역
404서울 서초구 반포동 111-137.498167126.994536서초구장원빌라트와 이수화학 사이불법주정차구역
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406서울 서초구 서초동 1689-637.495493127.018711서초구정관장 앞불법주정차구역
407서울 서초구 서초동 133737.492317127.02865서초구래미안리더스원 아파트불법주정차구역
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409서울 서초구 양재동 306-537.473598127.044846서초구양재2동 306-5불법주정차구역
410서울 서초구 서초동 1340-637.489195127.03136서초구뱅뱅사거리불법주정차구역