Overview

Dataset statistics

Number of variables6
Number of observations373
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.3 KiB
Average record size in memory50.4 B

Variable types

Categorical1
Text3
Numeric2

Dataset

Description명칭,좌표주소,위도,경도,상세주소,상세내용
Author금천구
URLhttps://data.seoul.go.kr/dataList/OA-12253/S/1/datasetView.do

Alerts

상세내용 has unique valuesUnique

Reproduction

Analysis started2023-12-11 04:13:22.155053
Analysis finished2023-12-11 04:13:23.176652
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

명칭
Categorical

Distinct9
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
방범 CCTV
174 
어린이보호 CCTV
41 
그린파킹 CCTV
40 
쓰레기무단투기 CCTV
33 
주정차단속 CCTV
31 
Other values (4)
54 

Length

Max length12
Median length11
Mean length8.4932976
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row어린이보호 CCTV
2nd row어린이보호 CCTV
3rd row어린이보호 CCTV
4th row어린이보호 CCTV
5th row어린이보호 CCTV

Common Values

ValueCountFrequency (%)
방범 CCTV 174
46.6%
어린이보호 CCTV 41
 
11.0%
그린파킹 CCTV 40
 
10.7%
쓰레기무단투기 CCTV 33
 
8.8%
주정차단속 CCTV 31
 
8.3%
공원방범 CCTV 28
 
7.5%
스쿨존 CCTV 20
 
5.4%
자전거관리 CCTV 4
 
1.1%
자전거도서관 CCTV 2
 
0.5%

Length

2023-12-11T13:13:23.246645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:13:23.389198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
cctv 373
50.0%
방범 174
23.3%
어린이보호 41
 
5.5%
그린파킹 40
 
5.4%
쓰레기무단투기 33
 
4.4%
주정차단속 31
 
4.2%
공원방범 28
 
3.8%
스쿨존 20
 
2.7%
자전거관리 4
 
0.5%
자전거도서관 2
 
0.3%

좌표주소
Text

Distinct358
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-11T13:13:23.733453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length34
Mean length24.378016
Min length18

Characters and Unicode

Total characters9093
Distinct characters98
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

Unique346 ?
Unique (%)92.8%

Sample

1st row대한민국 서울특별시 금천구 독산로102길
2nd row대한민국 서울특별시 금천구 독산로78다길 53
3rd row대한민국 서울특별시 금천구 벚꽃로18길 33
4th row대한민국 서울특별시 금천구 시흥대로104길 48
5th row대한민국 서울특별시 금천구 독산로64길 107
ValueCountFrequency (%)
대한민국 373
20.1%
서울특별시 370
20.0%
금천구 366
19.7%
독산로 11
 
0.6%
20 10
 
0.5%
시흥동 9
 
0.5%
5 9
 
0.5%
독산동 9
 
0.5%
범안로 9
 
0.5%
35 8
 
0.4%
Other values (394) 680
36.7%
2023-12-11T13:13:24.200136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1481
 
16.3%
시 483
 
5.3%
대 474
 
5.2%
금 393
 
4.3%
한 375
 
4.1%
민 373
 
4.1%
국 373
 
4.1%
구 373
 
4.1%
서 370
 
4.1%
울 370
 
4.1%
Other values (88) 4028
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6140
67.5%
Space Separator 1481
 
16.3%
Decimal Number 1412
 
15.5%
Dash Punctuation 60
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 483
 
7.9%
대 474
 
7.7%
금 393
 
6.4%
한 375
 
6.1%
민 373
 
6.1%
국 373
 
6.1%
구 373
 
6.1%
서 370
 
6.0%
울 370
 
6.0%
특 370
 
6.0%
Other values (76) 2186
35.6%
Decimal Number
ValueCountFrequency (%)
1 271
19.2%
2 187
13.2%
3 165
11.7%
4 156
11.0%
0 122
8.6%
8 112
7.9%
5 112
7.9%
6 109
7.7%
7 92
 
6.5%
9 86
 
6.1%
Space Separator
ValueCountFrequency (%)
1481
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6140
67.5%
Common 2953
32.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 483
 
7.9%
대 474
 
7.7%
금 393
 
6.4%
한 375
 
6.1%
민 373
 
6.1%
국 373
 
6.1%
구 373
 
6.1%
서 370
 
6.0%
울 370
 
6.0%
특 370
 
6.0%
Other values (76) 2186
35.6%
Common
ValueCountFrequency (%)
1481
50.2%
1 271
 
9.2%
2 187
 
6.3%
3 165
 
5.6%
4 156
 
5.3%
0 122
 
4.1%
8 112
 
3.8%
5 112
 
3.8%
6 109
 
3.7%
7 92
 
3.1%
Other values (2) 146
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6140
67.5%
ASCII 2953
32.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1481
50.2%
1 271
 
9.2%
2 187
 
6.3%
3 165
 
5.6%
4 156
 
5.3%
0 122
 
4.1%
8 112
 
3.8%
5 112
 
3.8%
6 109
 
3.7%
7 92
 
3.1%
Other values (2) 146
 
4.9%
Hangul
ValueCountFrequency (%)
시 483
 
7.9%
대 474
 
7.7%
금 393
 
6.4%
한 375
 
6.1%
민 373
 
6.1%
국 373
 
6.1%
구 373
 
6.1%
서 370
 
6.0%
울 370
 
6.0%
특 370
 
6.0%
Other values (76) 2186
35.6%

위도
Real number (ℝ)

Distinct352
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.40928
Minimum35.201013
Maximum37.911063
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-11T13:13:24.327126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.201013
5-th percentile37.434716
Q137.451141
median37.461223
Q337.471457
95-th percentile37.479347
Maximum37.911063
Range2.7100496
Interquartile range (IQR)0.0203161

Descriptive statistics

Standard deviation0.29191291
Coefficient of variation (CV)0.0078032217
Kurtosis27.312561
Mean37.40928
Median Absolute Deviation (MAD)0.0102278
Skewness-5.1902632
Sum13953.662
Variance0.085213147
MonotonicityNot monotonic
2023-12-11T13:13:24.472543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.8284724 7
 
1.9%
36.4269583 5
 
1.3%
37.4235786 3
 
0.8%
37.4759766 2
 
0.5%
37.4585946 2
 
0.5%
37.4473174 2
 
0.5%
37.4492857 2
 
0.5%
37.4717252 2
 
0.5%
37.4482719 2
 
0.5%
37.4506854 2
 
0.5%
Other values (342) 344
92.2%
ValueCountFrequency (%)
35.2010134 1
 
0.3%
35.7083656 1
 
0.3%
35.8284724 7
1.9%
36.4269583 5
1.3%
37.3550352 1
 
0.3%
37.4235786 3
0.8%
37.4345646 1
 
0.3%
37.4348163 1
 
0.3%
37.4350043 1
 
0.3%
37.4359959 1
 
0.3%
ValueCountFrequency (%)
37.911063 1
0.3%
37.8384424 1
0.3%
37.7510418 1
0.3%
37.6031991 1
0.3%
37.5136206 1
0.3%
37.4845446 1
0.3%
37.4839525 1
0.3%
37.4838349 1
0.3%
37.482905 1
0.3%
37.4828444 1
0.3%

경도
Real number (ℝ)

Distinct352
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.95016
Minimum126.75197
Maximum128.65524
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2023-12-11T13:13:24.603727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.75197
5-th percentile126.88856
Q1126.90049
median126.9043
Q3126.90735
95-th percentile126.93791
Maximum128.65524
Range1.9032705
Interquartile range (IQR)0.00686

Descriptive statistics

Standard deviation0.25748735
Coefficient of variation (CV)0.0020282554
Kurtosis35.964316
Mean126.95016
Median Absolute Deviation (MAD)0.0033177
Skewness5.99833
Sum47352.41
Variance0.066299733
MonotonicityNot monotonic
2023-12-11T13:13:24.738919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6552358 7
 
1.9%
127.3885725 5
 
1.3%
126.89834240000005 3
 
0.8%
126.90681789999996 2
 
0.5%
126.8883555 2
 
0.5%
126.90907629999992 2
 
0.5%
126.91046619999996 2
 
0.5%
126.908326 2
 
0.5%
126.9164515 2
 
0.5%
126.9012586 2
 
0.5%
Other values (342) 344
92.2%
ValueCountFrequency (%)
126.75196529999994 1
0.3%
126.8785471 1
0.3%
126.8811402 1
0.3%
126.8811806 1
0.3%
126.88242839999998 1
0.3%
126.8824571 1
0.3%
126.88274 1
0.3%
126.88316609999993 1
0.3%
126.88327279999999 1
0.3%
126.88329909999992 1
0.3%
ValueCountFrequency (%)
128.6552358 7
1.9%
128.25492629999997 1
 
0.3%
127.78140810000002 1
 
0.3%
127.3885725 5
1.3%
127.16704479999999 1
 
0.3%
127.10640739999997 1
 
0.3%
127.09795680000002 1
 
0.3%
127.0773712 1
 
0.3%
126.95952929999999 1
 
0.3%
126.92350540000008 1
 
0.3%

상세주소
Text

Distinct368
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-11T13:13:25.105120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length10.396783
Min length5

Characters and Unicode

Total characters3878
Distinct characters177
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

Unique363 ?
Unique (%)97.3%

Sample

1st row독산로102길 125 영남초교
2nd row독산로78다길 53
3rd row벚꽃로18길 33
4th row시흥대로104길 48
5th row독산로64길 107
ValueCountFrequency (%)
어린이공원 12
 
1.5%
시흥대로 10
 
1.3%
5 9
 
1.1%
13 8
 
1.0%
14 8
 
1.0%
20 8
 
1.0%
35 7
 
0.9%
22 7
 
0.9%
18 7
 
0.9%
10 6
 
0.8%
Other values (470) 701
89.5%
2023-12-11T13:13:25.529307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
411
 
10.6%
로 349
 
9.0%
길 296
 
7.6%
1 279
 
7.2%
2 189
 
4.9%
3 169
 
4.4%
산 169
 
4.4%
4 155
 
4.0%
독 144
 
3.7%
0 121
 
3.1%
Other values (167) 1596
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1982
51.1%
Decimal Number 1423
36.7%
Space Separator 411
 
10.6%
Dash Punctuation 56
 
1.4%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 349
17.6%
길 296
14.9%
산 169
 
8.5%
독 144
 
7.3%
흥 108
 
5.4%
시 108
 
5.4%
대 102
 
5.1%
가 33
 
1.7%
금 32
 
1.6%
하 28
 
1.4%
Other values (151) 613
30.9%
Decimal Number
ValueCountFrequency (%)
1 279
19.6%
2 189
13.3%
3 169
11.9%
4 155
10.9%
0 121
8.5%
5 114
8.0%
6 112
7.9%
8 109
 
7.7%
7 95
 
6.7%
9 80
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
P 1
50.0%
Space Separator
ValueCountFrequency (%)
411
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1982
51.1%
Common 1894
48.8%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 349
17.6%
길 296
14.9%
산 169
 
8.5%
독 144
 
7.3%
흥 108
 
5.4%
시 108
 
5.4%
대 102
 
5.1%
가 33
 
1.7%
금 32
 
1.6%
하 28
 
1.4%
Other values (151) 613
30.9%
Common
ValueCountFrequency (%)
411
21.7%
1 279
14.7%
2 189
10.0%
3 169
8.9%
4 155
 
8.2%
0 121
 
6.4%
5 114
 
6.0%
6 112
 
5.9%
8 109
 
5.8%
7 95
 
5.0%
Other values (4) 140
 
7.4%
Latin
ValueCountFrequency (%)
C 1
50.0%
P 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1982
51.1%
ASCII 1896
48.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
411
21.7%
1 279
14.7%
2 189
10.0%
3 169
8.9%
4 155
 
8.2%
0 121
 
6.4%
5 114
 
6.0%
6 112
 
5.9%
8 109
 
5.7%
7 95
 
5.0%
Other values (6) 142
 
7.5%
Hangul
ValueCountFrequency (%)
로 349
17.6%
길 296
14.9%
산 169
 
8.5%
독 144
 
7.3%
흥 108
 
5.4%
시 108
 
5.4%
대 102
 
5.1%
가 33
 
1.7%
금 32
 
1.6%
하 28
 
1.4%
Other values (151) 613
30.9%

상세내용
Text

UNIQUE 

Distinct373
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2023-12-11T13:13:25.948600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length10.067024
Min length10

Characters and Unicode

Total characters3755
Distinct characters25
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

Unique373 ?
Unique (%)100.0%

Sample

1st row관리번호: SN103
2nd row관리번호: SN104
3rd row관리번호: SN105
4th row관리번호: SN106
5th row관리번호: SN107
ValueCountFrequency (%)
관리번호 373
50.0%
p105 1
 
0.1%
p114 1
 
0.1%
p113 1
 
0.1%
p112 1
 
0.1%
p111 1
 
0.1%
p110 1
 
0.1%
p109 1
 
0.1%
p108 1
 
0.1%
p107 1
 
0.1%
Other values (364) 364
48.8%
2023-12-11T13:13:26.541304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 421
11.2%
관 373
9.9%
번 373
9.9%
호 373
9.9%
: 373
9.9%
373
9.9%
리 373
9.9%
2 184
 
4.9%
P 170
 
4.5%
0 118
 
3.1%
Other values (15) 624
16.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1492
39.7%
Decimal Number 1120
29.8%
Uppercase Letter 396
 
10.5%
Other Punctuation 373
 
9.9%
Space Separator 373
 
9.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 421
37.6%
2 184
16.4%
0 118
 
10.5%
3 76
 
6.8%
4 63
 
5.6%
6 59
 
5.3%
5 56
 
5.0%
7 55
 
4.9%
8 50
 
4.5%
9 38
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
P 170
42.9%
N 48
 
12.1%
G 40
 
10.1%
T 37
 
9.3%
S 37
 
9.3%
C 30
 
7.6%
A 28
 
7.1%
B 6
 
1.5%
Other Letter
ValueCountFrequency (%)
관 373
25.0%
번 373
25.0%
호 373
25.0%
리 373
25.0%
Other Punctuation
ValueCountFrequency (%)
: 373
100.0%
Space Separator
ValueCountFrequency (%)
373
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1867
49.7%
Hangul 1492
39.7%
Latin 396
 
10.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 421
22.5%
: 373
20.0%
373
20.0%
2 184
9.9%
0 118
 
6.3%
3 76
 
4.1%
4 63
 
3.4%
6 59
 
3.2%
5 56
 
3.0%
7 55
 
2.9%
Other values (3) 89
 
4.8%
Latin
ValueCountFrequency (%)
P 170
42.9%
N 48
 
12.1%
G 40
 
10.1%
T 37
 
9.3%
S 37
 
9.3%
C 30
 
7.6%
A 28
 
7.1%
B 6
 
1.5%
Hangul
ValueCountFrequency (%)
관 373
25.0%
번 373
25.0%
호 373
25.0%
리 373
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2263
60.3%
Hangul 1492
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 421
18.6%
: 373
16.5%
373
16.5%
2 184
8.1%
P 170
7.5%
0 118
 
5.2%
3 76
 
3.4%
4 63
 
2.8%
6 59
 
2.6%
5 56
 
2.5%
Other values (11) 370
16.3%
Hangul
ValueCountFrequency (%)
관 373
25.0%
번 373
25.0%
호 373
25.0%
리 373
25.0%

Interactions

2023-12-11T13:13:22.743859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:13:22.484974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:13:22.850070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:13:22.608272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T13:13:26.646023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
명칭위도경도
명칭1.0000.4200.433
위도0.4201.0000.986
경도0.4330.9861.000
2023-12-11T13:13:26.728967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도명칭
위도1.000-0.4400.236
경도-0.4401.0000.245
명칭0.2360.2451.000

Missing values

2023-12-11T13:13:23.004354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T13:13:23.134727image/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

명칭좌표주소위도경도상세주소상세내용
0어린이보호 CCTV대한민국 서울특별시 금천구 독산로102길37.475977126.906818독산로102길 125 영남초교관리번호: SN103
1어린이보호 CCTV대한민국 서울특별시 금천구 독산로78다길 5337.470488126.906568독산로78다길 53관리번호: SN104
2어린이보호 CCTV대한민국 서울특별시 금천구 벚꽃로18길 3337.468207126.890789벚꽃로18길 33관리번호: SN105
3어린이보호 CCTV대한민국 서울특별시 금천구 시흥대로104길 4837.46444126.900331시흥대로104길 48관리번호: SN106
4어린이보호 CCTV대한민국 서울특별시 금천구 독산로64길 10737.466631126.908008독산로64길 107관리번호: SN107
5어린이보호 CCTV대한민국 서울특별시 금천구 독산로50길 6037.462335126.9074독산로50길 60 흥일초교관리번호: SN108
6어린이보호 CCTV대한민국 서울특별시 금천구 독산로36나길 737.459921126.90767독산로36나길 7관리번호: SN109
7어린이보호 CCTV대한민국 서울특별시 금천구 금하로11길 4037.455431126.904157금하로11길 40관리번호: SN110
8어린이보호 CCTV대한민국 서울특별시 금천구 탑골로5길 5237.453722126.912529탑골로5길 52관리번호: SN111
9어린이보호 CCTV대한민국 서울특별시 금천구 탑골로 3537.452033126.913221탑골로35관리번호: SN112
명칭좌표주소위도경도상세주소상세내용
363방범 CCTV대한민국 서울특별시 금천구 독산로58가길 6837.464922126.906977독산로58가길 68관리번호: P101
364방범 CCTV대한민국 서울특별시 금천구 남부순환로128길 1437.479578126.906999남부순환로128길 14관리번호: P180
365방범 CCTV대한민국 서울특별시 금천구 독산로80길 1337.471139126.903933독산로80길 13관리번호: P181
366방범 CCTV대한민국 서울특별시 금천구 독산로70다길 6437.468778126.906178독산로70다길 64관리번호: P182
367방범 CCTV대한민국 서울특별시 금천구 독산로70라길 1437.467633126.904898독산로70라길 14관리번호: P183
368방범 CCTV대한민국 서울특별시 금천구 독산로75길 12-737.469427126.901555독산로75길 12-7관리번호: P184
369방범 CCTV대한민국 서울특별시 금천구 시흥대로128길 3437.470096126.900133시흥대로128길 34관리번호: P185
370방범 CCTV대한민국 서울특별시 금천구 벚꽃로38길 3537.482621126.884455벚꽃로38길 35관리번호: P186
371방범 CCTV대한민국 서울특별시 금천구 가산로5길 4337.47345126.892127가산로5길 43관리번호: P188
372방범 CCTV대한민국 서울특별시 금천구 남부순환로110길 3137.477559126.893453남부순환로110길 31관리번호: P190