Overview

Dataset statistics

Number of variables6
Number of observations4202
Missing cells3
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory205.3 KiB
Average record size in memory50.0 B

Variable types

Text2
Numeric2
Categorical2

Dataset

Description고정형CCTV지번주소,위도,경도,자치구,단속지점명,현장구분
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-20471/S/1/datasetView.do

Alerts

현장구분 is highly imbalanced (92.5%)Imbalance
위도 is highly skewed (γ1 = 26.40331885)Skewed
경도 is highly skewed (γ1 = 64.82283548)Skewed

Reproduction

Analysis started2024-04-06 12:11:38.743865
Analysis finished2024-04-06 12:11:41.447744
Duration2.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고정형CCTV지번주소
Text

Distinct4040
Distinct (%)96.2%
Missing3
Missing (%)0.1%
Memory size33.0 KiB
2024-04-06T21:11:41.915387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35
Mean length9.5132174
Min length2

Characters and Unicode

Total characters39946
Distinct characters299
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

Unique3911 ?
Unique (%)93.1%

Sample

1st row목4동 762-10
2nd row목4동 797-8
3rd row신월2동 496
4th row신월7동 928-1
5th row목1동 917
ValueCountFrequency (%)
구로구 75
 
0.9%
창동 58
 
0.7%
대치동 54
 
0.6%
역삼동 52
 
0.6%
신사동 48
 
0.6%
삼성동 45
 
0.5%
청담동 45
 
0.5%
논현동 41
 
0.5%
정릉동 41
 
0.5%
반포4동 39
 
0.5%
Other values (4276) 7875
94.1%
2024-04-06T21:11:42.893212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4405
 
11.0%
동 4126
 
10.3%
1 3619
 
9.1%
- 3282
 
8.2%
2 2449
 
6.1%
3 1974
 
4.9%
4 1754
 
4.4%
5 1558
 
3.9%
6 1518
 
3.8%
7 1402
 
3.5%
Other values (289) 13859
34.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17922
44.9%
Other Letter 14253
35.7%
Space Separator 4405
 
11.0%
Dash Punctuation 3282
 
8.2%
Open Punctuation 26
 
0.1%
Close Punctuation 26
 
0.1%
Other Punctuation 19
 
< 0.1%
Uppercase Letter 12
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4126
28.9%
가 466
 
3.3%
신 380
 
2.7%
구 278
 
2.0%
로 265
 
1.9%
서 210
 
1.5%
성 197
 
1.4%
산 180
 
1.3%
초 177
 
1.2%
수 172
 
1.2%
Other values (264) 7802
54.7%
Decimal Number
ValueCountFrequency (%)
1 3619
20.2%
2 2449
13.7%
3 1974
11.0%
4 1754
9.8%
5 1558
8.7%
6 1518
8.5%
7 1402
 
7.8%
8 1282
 
7.2%
9 1189
 
6.6%
0 1177
 
6.6%
Uppercase Letter
ValueCountFrequency (%)
G 3
25.0%
A 2
16.7%
P 2
16.7%
T 2
16.7%
S 2
16.7%
L 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 15
78.9%
/ 2
 
10.5%
. 1
 
5.3%
@ 1
 
5.3%
Space Separator
ValueCountFrequency (%)
4405
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3282
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25681
64.3%
Hangul 14253
35.7%
Latin 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4126
28.9%
가 466
 
3.3%
신 380
 
2.7%
구 278
 
2.0%
로 265
 
1.9%
서 210
 
1.5%
성 197
 
1.4%
산 180
 
1.3%
초 177
 
1.2%
수 172
 
1.2%
Other values (264) 7802
54.7%
Common
ValueCountFrequency (%)
4405
17.2%
1 3619
14.1%
- 3282
12.8%
2 2449
9.5%
3 1974
7.7%
4 1754
 
6.8%
5 1558
 
6.1%
6 1518
 
5.9%
7 1402
 
5.5%
8 1282
 
5.0%
Other values (9) 2438
9.5%
Latin
ValueCountFrequency (%)
G 3
25.0%
A 2
16.7%
P 2
16.7%
T 2
16.7%
S 2
16.7%
L 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25693
64.3%
Hangul 14253
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4405
17.1%
1 3619
14.1%
- 3282
12.8%
2 2449
9.5%
3 1974
7.7%
4 1754
 
6.8%
5 1558
 
6.1%
6 1518
 
5.9%
7 1402
 
5.5%
8 1282
 
5.0%
Other values (15) 2450
9.5%
Hangul
ValueCountFrequency (%)
동 4126
28.9%
가 466
 
3.3%
신 380
 
2.7%
구 278
 
2.0%
로 265
 
1.9%
서 210
 
1.5%
성 197
 
1.4%
산 180
 
1.3%
초 177
 
1.2%
수 172
 
1.2%
Other values (264) 7802
54.7%

위도
Real number (ℝ)

SKEWED 

Distinct4145
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.674591
Minimum35.517833
Maximum127.061
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-04-06T21:11:43.266919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.517833
5-th percentile37.47575
Q137.501174
median37.544208
Q337.583749
95-th percentile37.646518
Maximum127.061
Range91.543164
Interquartile range (IQR)0.082574771

Descriptive statistics

Standard deviation3.3803031
Coefficient of variation (CV)0.089723683
Kurtosis695.70138
Mean37.674591
Median Absolute Deviation (MAD)0.04181544
Skewness26.403319
Sum158308.63
Variance11.426449
MonotonicityNot monotonic
2024-04-06T21:11:43.982285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5251913154781 5
 
0.1%
37.481345 3
 
0.1%
37.62701873 3
 
0.1%
37.6581397 3
 
0.1%
37.63139447 3
 
0.1%
37.62235828 3
 
0.1%
37.62782213 3
 
0.1%
37.64363763 3
 
0.1%
37.62473909 3
 
0.1%
37.49857 3
 
0.1%
Other values (4135) 4170
99.2%
ValueCountFrequency (%)
35.517833 1
< 0.1%
37.36114 1
< 0.1%
37.43544018017112 1
< 0.1%
37.44122280819926 1
< 0.1%
37.44367183 1
< 0.1%
37.44493071 1
< 0.1%
37.4463 1
< 0.1%
37.44666321848974 1
< 0.1%
37.446707 1
< 0.1%
37.447218 1
< 0.1%
ValueCountFrequency (%)
127.06099720132076 1
< 0.1%
127.05498497206293 1
< 0.1%
127.05403869196364 1
< 0.1%
127.0438277284258 1
< 0.1%
127.016616821289 1
< 0.1%
127.015312194824 1
< 0.1%
37.69082309522302 1
< 0.1%
37.69013773708887 2
< 0.1%
37.68931953088563 1
< 0.1%
37.68921764030013 1
< 0.1%

경도
Real number (ℝ)

SKEWED 

Distinct4147
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean300912.12
Minimum37.538419
Maximum1.2638998 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size37.1 KiB
2024-04-06T21:11:44.244707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.538419
5-th percentile126.85716
Q1126.9249
median127.00924
Q3127.0467
95-th percentile127.10924
Maximum1.2638998 × 109
Range1.2638998 × 109
Interquartile range (IQR)0.12179883

Descriptive statistics

Standard deviation19497754
Coefficient of variation (CV)64.795511
Kurtosis4202
Mean300912.12
Median Absolute Deviation (MAD)0.05519014
Skewness64.822835
Sum1.2644327 × 109
Variance3.8016242 × 1014
MonotonicityNot monotonic
2024-04-06T21:11:44.573921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.929112756574 5
 
0.1%
127.072772 3
 
0.1%
127.0729715 3
 
0.1%
127.0499072 3
 
0.1%
127.0868014 3
 
0.1%
127.0610884 3
 
0.1%
127.0889875 3
 
0.1%
127.026877 3
 
0.1%
127.0766611 3
 
0.1%
127.0647458 3
 
0.1%
Other values (4137) 4170
99.2%
ValueCountFrequency (%)
37.53841854034201 1
< 0.1%
37.54149572893306 1
< 0.1%
37.541690826416 1
< 0.1%
37.5434837341309 1
< 0.1%
37.54453321261708 1
< 0.1%
37.54733376708909 1
< 0.1%
37.57526 1
< 0.1%
126.80075409398076 1
< 0.1%
126.80158802897782 1
< 0.1%
126.80181606541956 1
< 0.1%
ValueCountFrequency (%)
1263899849.0 1
< 0.1%
127.17967905122998 1
< 0.1%
127.178237 1
< 0.1%
127.17478362505832 1
< 0.1%
127.1744614 1
< 0.1%
127.17401708848259 1
< 0.1%
127.1738434 1
< 0.1%
127.1734772 1
< 0.1%
127.1734543 1
< 0.1%
127.1733246 1
< 0.1%

자치구
Categorical

Distinct26
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size33.0 KiB
서초구
411 
강남구
357 
서울시
300 
성북구
 
236
관악구
 
216
Other values (21)
2682 

Length

Max length4
Median length3
Mean length3.0578296
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서초구 411
 
9.8%
강남구 357
 
8.5%
서울시 300
 
7.1%
성북구 236
 
5.6%
관악구 216
 
5.1%
은평구 207
 
4.9%
영등포구 181
 
4.3%
성동구 177
 
4.2%
종로구 159
 
3.8%
노원구 156
 
3.7%
Other values (16) 1802
42.9%

Length

2024-04-06T21:11:44.881638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서초구 411
 
9.8%
강남구 357
 
8.5%
서울시 300
 
7.1%
성북구 236
 
5.6%
관악구 216
 
5.1%
은평구 207
 
4.9%
영등포구 181
 
4.3%
성동구 177
 
4.2%
종로구 159
 
3.8%
노원구 156
 
3.7%
Other values (16) 1802
42.9%

단속지점명
Text

Distinct4196
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size33.0 KiB
2024-04-06T21:11:45.415838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length34
Mean length14.024036
Min length3

Characters and Unicode

Total characters58929
Distinct characters718
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4190 ?
Unique (%)99.7%

Sample

1st row목4동 영도초등학교 주변
2nd row목4동 태학관 주변
3rd row신월2동 양강초교 후문 주변
4th row신월7동 우성상가 주변
5th row목1동 파라곤(SBS) 주변
ValueCountFrequency (%)
주변 1418
 
13.5%
앞 511
 
4.9%
부근 206
 
2.0%
인근 170
 
1.6%
정문 153
 
1.5%
사거리 120
 
1.1%
삼거리 82
 
0.8%
후문 76
 
0.7%
입구 60
 
0.6%
건너편 47
 
0.4%
Other values (6205) 7655
72.9%
2024-04-06T21:11:46.436948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6431
 
10.9%
주 2220
 
3.8%
1 2035
 
3.5%
변 1767
 
3.0%
0 1502
 
2.5%
2 1124
 
1.9%
동 1023
 
1.7%
로 934
 
1.6%
( 816
 
1.4%
) 815
 
1.4%
Other values (708) 40262
68.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39273
66.6%
Decimal Number 8191
 
13.9%
Space Separator 6431
 
10.9%
Uppercase Letter 1332
 
2.3%
Open Punctuation 1174
 
2.0%
Close Punctuation 1173
 
2.0%
Dash Punctuation 629
 
1.1%
Other Punctuation 429
 
0.7%
Connector Punctuation 226
 
0.4%
Lowercase Letter 39
 
0.1%
Other values (2) 32
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2220
 
5.7%
변 1767
 
4.5%
동 1023
 
2.6%
로 934
 
2.4%
교 738
 
1.9%
앞 707
 
1.8%
정 672
 
1.7%
리 659
 
1.7%
초 608
 
1.5%
구 587
 
1.5%
Other values (636) 29358
74.8%
Uppercase Letter
ValueCountFrequency (%)
P 236
17.7%
C 156
11.7%
N 151
11.3%
S 117
8.8%
D 101
7.6%
G 92
 
6.9%
A 82
 
6.2%
K 56
 
4.2%
J 48
 
3.6%
B 41
 
3.1%
Other values (14) 252
18.9%
Lowercase Letter
ValueCountFrequency (%)
e 9
23.1%
a 4
 
10.3%
s 3
 
7.7%
p 3
 
7.7%
m 2
 
5.1%
o 2
 
5.1%
l 2
 
5.1%
i 2
 
5.1%
u 1
 
2.6%
g 1
 
2.6%
Other values (10) 10
25.6%
Decimal Number
ValueCountFrequency (%)
1 2035
24.8%
0 1502
18.3%
2 1124
13.7%
3 729
 
8.9%
4 599
 
7.3%
5 571
 
7.0%
6 470
 
5.7%
7 429
 
5.2%
9 379
 
4.6%
8 353
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 241
56.2%
. 150
35.0%
@ 18
 
4.2%
/ 9
 
2.1%
? 4
 
0.9%
& 3
 
0.7%
; 3
 
0.7%
# 1
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 816
69.5%
[ 358
30.5%
Close Punctuation
ValueCountFrequency (%)
) 815
69.5%
] 358
30.5%
Math Symbol
ValueCountFrequency (%)
~ 28
96.6%
+ 1
 
3.4%
Space Separator
ValueCountFrequency (%)
6431
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 629
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 226
100.0%
Control
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39273
66.6%
Common 18285
31.0%
Latin 1371
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 2220
 
5.7%
변 1767
 
4.5%
동 1023
 
2.6%
로 934
 
2.4%
교 738
 
1.9%
앞 707
 
1.8%
정 672
 
1.7%
리 659
 
1.7%
초 608
 
1.5%
구 587
 
1.5%
Other values (636) 29358
74.8%
Latin
ValueCountFrequency (%)
P 236
17.2%
C 156
11.4%
N 151
11.0%
S 117
8.5%
D 101
 
7.4%
G 92
 
6.7%
A 82
 
6.0%
K 56
 
4.1%
J 48
 
3.5%
B 41
 
3.0%
Other values (34) 291
21.2%
Common
ValueCountFrequency (%)
6431
35.2%
1 2035
 
11.1%
0 1502
 
8.2%
2 1124
 
6.1%
( 816
 
4.5%
) 815
 
4.5%
3 729
 
4.0%
- 629
 
3.4%
4 599
 
3.3%
5 571
 
3.1%
Other values (18) 3034
16.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39273
66.6%
ASCII 19656
33.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6431
32.7%
1 2035
 
10.4%
0 1502
 
7.6%
2 1124
 
5.7%
( 816
 
4.2%
) 815
 
4.1%
3 729
 
3.7%
- 629
 
3.2%
4 599
 
3.0%
5 571
 
2.9%
Other values (62) 4405
22.4%
Hangul
ValueCountFrequency (%)
주 2220
 
5.7%
변 1767
 
4.5%
동 1023
 
2.6%
로 934
 
2.4%
교 738
 
1.9%
앞 707
 
1.8%
정 672
 
1.7%
리 659
 
1.7%
초 608
 
1.5%
구 587
 
1.5%
Other values (636) 29358
74.8%

현장구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size33.0 KiB
불법주정차구역
4142 
버스전용차로
 
46
자전거전용차로
 
14

Length

Max length7
Median length7
Mean length6.9890528
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
불법주정차구역 4142
98.6%
버스전용차로 46
 
1.1%
자전거전용차로 14
 
0.3%

Length

2024-04-06T21:11:46.653899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:11:46.812390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불법주정차구역 4142
98.6%
버스전용차로 46
 
1.1%
자전거전용차로 14
 
0.3%

Interactions

2024-04-06T21:11:40.586286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:11:40.056999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:11:40.855660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:11:40.281183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T21:11:46.912144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도자치구현장구분
위도1.0000.0000.2060.000
경도0.0001.0000.0000.000
자치구0.2060.0001.0000.500
현장구분0.0000.0000.5001.000
2024-04-06T21:11:47.065829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자치구현장구분
자치구1.0000.297
현장구분0.2971.000
2024-04-06T21:11:47.219211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도자치구현장구분
위도1.0000.1720.1630.000
경도0.1721.0000.0000.000
자치구0.1630.0001.0000.297
현장구분0.0000.0000.2971.000

Missing values

2024-04-06T21:11:41.102566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T21:11:41.361981image/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
0목4동 762-1037.535891126.870566양천구목4동 영도초등학교 주변불법주정차구역
1목4동 797-837.53274126.867191양천구목4동 태학관 주변불법주정차구역
2신월2동 49637.524535126.848224양천구신월2동 양강초교 후문 주변불법주정차구역
3신월7동 928-137.522349126.833529양천구신월7동 우성상가 주변불법주정차구역
4목1동 91737.528982126.874597양천구목1동 파라곤(SBS) 주변불법주정차구역
5목3동 602-1037.548024126.866839양천구목3동 롯데캐슬프라자 주변불법주정차구역
6신월1동 131-737.531127126.831572양천구신월1동 대흥가스 주변불법주정차구역
7신정7동 325-837.509141126.861695양천구신정7동 봉영여자중학교 주변불법주정차구역
8신정2동 119-137.522205126.877254양천구신정2동 파리바게트 주변불법주정차구역
9목4동 766-1637.536176126.867045양천구목4동 한신빌딩 앞 사거리불법주정차구역
고정형CCTV지번주소위도경도자치구단속지점명현장구분
4192망우동 21637.605234127.104448중랑구동원초등학교 정문불법주정차구역
4193원남동 96-937.575672126.997551종로구원남동사거리 주변불법주정차구역
4194청량리동 520-7937.586788127.040283동대문구제기로65 (국제자원앞,CR0_P001)불법주정차구역
4195양평동4가 7-137.533953126.895835영등포구영등포세무서 청사 앞불법주정차구역
4196신길동 341-137.502654126.906524영등포구대영초등학교 후문불법주정차구역
4197신당동 251-16037.56622127.011929중구동대문 한국산업단지공단불법주정차구역
4198성수동2가 289-20127.05498537.547334성동구신한은행 성수동지점 부근불법주정차구역
4199잠실7동 50-437.509567127.072559송파구정신여자중고등학교 주변불법주정차구역
4200정릉동 109-3137.600881127.014066성북구아리랑고개사거리불법주정차구역
4201오금동 16237.498356127.137593송파구보인중 정문 주변불법주정차구역