Overview

Dataset statistics

Number of variables13
Number of observations804
Missing cells77
Missing cells (%)0.7%
Duplicate rows2
Duplicate rows (%)0.2%
Total size in memory85.7 KiB
Average record size in memory109.2 B

Variable types

Categorical6
Text3
Numeric3
DateTime1

Dataset

Description파일 다운로드
Author종로구
URLhttps://data.seoul.go.kr/dataList/OA-11568/F/1/datasetView.do

Alerts

관리기관명 has constant value ""Constant
보관일수 has constant value ""Constant
관리기관번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 2 (0.2%) duplicate rowsDuplicates
설치목적구분 is highly overall correlated with 카메라화소수High correlation
카메라화소수 is highly overall correlated with 설치목적구분High correlation
카메라화소수 is highly imbalanced (93.2%)Imbalance
촬영방면정보 is highly imbalanced (75.9%)Imbalance
소재지지번주소 has 76 (9.5%) missing valuesMissing

Reproduction

Analysis started2023-12-11 04:54:37.947717
Analysis finished2023-12-11 04:54:41.663181
Duration3.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
서울특별시 종로구청
804 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 종로구청
2nd row서울특별시 종로구청
3rd row서울특별시 종로구청
4th row서울특별시 종로구청
5th row서울특별시 종로구청

Common Values

ValueCountFrequency (%)
서울특별시 종로구청 804
100.0%

Length

2023-12-11T13:54:41.803841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:54:42.041503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 804
50.0%
종로구청 804
50.0%

소재지도로명주소
Text

Distinct740
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
2023-12-11T13:54:42.702664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length31
Mean length19.874378
Min length14

Characters and Unicode

Total characters15979
Distinct characters178
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

Unique703 ?
Unique (%)87.4%

Sample

1st row서울특별시 종로구 옥인6가길 8
2nd row서울특별시 종로구 옥인6길 39
3rd row서울특별시 종로구 옥인6길 23
4th row서울특별시 종로구 옥인6길 32
5th row서울특별시 종로구 옥인3길 32-1
ValueCountFrequency (%)
서울특별시 804
23.8%
종로구 804
23.8%
종로 30
 
0.9%
자하문로 18
 
0.5%
19 17
 
0.5%
1 16
 
0.5%
9 16
 
0.5%
14 14
 
0.4%
6 14
 
0.4%
5 13
 
0.4%
Other values (780) 1634
48.3%
2023-12-11T13:54:43.700318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2590
16.2%
로 1312
 
8.2%
종 905
 
5.7%
서 824
 
5.2%
시 812
 
5.1%
구 809
 
5.1%
울 807
 
5.1%
별 805
 
5.0%
특 804
 
5.0%
1 563
 
3.5%
Other values (168) 5748
36.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10348
64.8%
Space Separator 2590
 
16.2%
Decimal Number 2546
 
15.9%
Dash Punctuation 215
 
1.3%
Close Punctuation 134
 
0.8%
Open Punctuation 134
 
0.8%
Other Punctuation 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 1312
12.7%
종 905
 
8.7%
서 824
 
8.0%
시 812
 
7.8%
구 809
 
7.8%
울 807
 
7.8%
별 805
 
7.8%
특 804
 
7.8%
길 563
 
5.4%
동 143
 
1.4%
Other values (153) 2564
24.8%
Decimal Number
ValueCountFrequency (%)
1 563
22.1%
2 391
15.4%
3 349
13.7%
5 240
9.4%
4 230
9.0%
7 176
 
6.9%
6 172
 
6.8%
9 162
 
6.4%
0 132
 
5.2%
8 131
 
5.1%
Space Separator
ValueCountFrequency (%)
2590
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 215
100.0%
Close Punctuation
ValueCountFrequency (%)
) 134
100.0%
Open Punctuation
ValueCountFrequency (%)
( 134
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10348
64.8%
Common 5631
35.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 1312
12.7%
종 905
 
8.7%
서 824
 
8.0%
시 812
 
7.8%
구 809
 
7.8%
울 807
 
7.8%
별 805
 
7.8%
특 804
 
7.8%
길 563
 
5.4%
동 143
 
1.4%
Other values (153) 2564
24.8%
Common
ValueCountFrequency (%)
2590
46.0%
1 563
 
10.0%
2 391
 
6.9%
3 349
 
6.2%
5 240
 
4.3%
4 230
 
4.1%
- 215
 
3.8%
7 176
 
3.1%
6 172
 
3.1%
9 162
 
2.9%
Other values (5) 543
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10348
64.8%
ASCII 5631
35.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2590
46.0%
1 563
 
10.0%
2 391
 
6.9%
3 349
 
6.2%
5 240
 
4.3%
4 230
 
4.1%
- 215
 
3.8%
7 176
 
3.1%
6 172
 
3.1%
9 162
 
2.9%
Other values (5) 543
 
9.6%
Hangul
ValueCountFrequency (%)
로 1312
12.7%
종 905
 
8.7%
서 824
 
8.0%
시 812
 
7.8%
구 809
 
7.8%
울 807
 
7.8%
별 805
 
7.8%
특 804
 
7.8%
길 563
 
5.4%
동 143
 
1.4%
Other values (153) 2564
24.8%

소재지지번주소
Text

MISSING 

Distinct685
Distinct (%)94.1%
Missing76
Missing (%)9.5%
Memory size6.4 KiB
2023-12-11T13:54:44.188904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length18.684066
Min length15

Characters and Unicode

Total characters13602
Distinct characters117
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

Unique659 ?
Unique (%)90.5%

Sample

1st row서울특별시 종로구 누상동 166-114
2nd row서울특별시 종로구 누상동 166-16
3rd row서울특별시 종로구 누상동 166-125
4th row서울특별시 종로구 누상동 166-214
5th row서울특별시 종로구 누상동 166-3
ValueCountFrequency (%)
서울특별시 728
24.9%
종로구 728
24.9%
창신동 78
 
2.7%
숭인동 70
 
2.4%
부암동 30
 
1.0%
평창동 28
 
1.0%
명륜3가 27
 
0.9%
명륜1가 26
 
0.9%
혜화동 25
 
0.9%
동숭동 23
 
0.8%
Other values (712) 1158
39.6%
2023-12-11T13:54:44.911893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2194
16.1%
로 770
 
5.7%
종 759
 
5.6%
서 747
 
5.5%
구 744
 
5.5%
울 728
 
5.4%
특 728
 
5.4%
별 728
 
5.4%
시 728
 
5.4%
1 678
 
5.0%
Other values (107) 4798
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8055
59.2%
Decimal Number 2776
 
20.4%
Space Separator 2194
 
16.1%
Dash Punctuation 577
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 770
9.6%
종 759
9.4%
서 747
9.3%
구 744
9.2%
울 728
9.0%
특 728
9.0%
별 728
9.0%
시 728
9.0%
동 640
7.9%
신 128
 
1.6%
Other values (95) 1355
16.8%
Decimal Number
ValueCountFrequency (%)
1 678
24.4%
2 400
14.4%
3 314
11.3%
6 241
 
8.7%
4 225
 
8.1%
5 219
 
7.9%
7 185
 
6.7%
8 183
 
6.6%
0 169
 
6.1%
9 162
 
5.8%
Space Separator
ValueCountFrequency (%)
2194
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 577
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8055
59.2%
Common 5547
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 770
9.6%
종 759
9.4%
서 747
9.3%
구 744
9.2%
울 728
9.0%
특 728
9.0%
별 728
9.0%
시 728
9.0%
동 640
7.9%
신 128
 
1.6%
Other values (95) 1355
16.8%
Common
ValueCountFrequency (%)
2194
39.6%
1 678
 
12.2%
- 577
 
10.4%
2 400
 
7.2%
3 314
 
5.7%
6 241
 
4.3%
4 225
 
4.1%
5 219
 
3.9%
7 185
 
3.3%
8 183
 
3.3%
Other values (2) 331
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8055
59.2%
ASCII 5547
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2194
39.6%
1 678
 
12.2%
- 577
 
10.4%
2 400
 
7.2%
3 314
 
5.7%
6 241
 
4.3%
4 225
 
4.1%
5 219
 
3.9%
7 185
 
3.3%
8 183
 
3.3%
Other values (2) 331
 
6.0%
Hangul
ValueCountFrequency (%)
로 770
9.6%
종 759
9.4%
서 747
9.3%
구 744
9.2%
울 728
9.0%
특 728
9.0%
별 728
9.0%
시 728
9.0%
동 640
7.9%
신 128
 
1.6%
Other values (95) 1355
16.8%

설치목적구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
생활방범
554 
공원
106 
교통단속
101 
다목적
 
37
치수
 
3

Length

Max length4
Median length4
Mean length3.6791045
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생활방범 554
68.9%
공원 106
 
13.2%
교통단속 101
 
12.6%
다목적 37
 
4.6%
치수 3
 
0.4%
문화재 3
 
0.4%

Length

2023-12-11T13:54:45.178022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:54:45.437598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활방범 554
68.9%
공원 106
 
13.2%
교통단속 101
 
12.6%
다목적 37
 
4.6%
치수 3
 
0.4%
문화재 3
 
0.4%

카메라대수
Real number (ℝ)

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3097015
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-11T13:54:45.664842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile4
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.97533998
Coefficient of variation (CV)0.42227967
Kurtosis-0.51135207
Mean2.3097015
Median Absolute Deviation (MAD)1
Skewness0.098747909
Sum1857
Variance0.95128808
MonotonicityNot monotonic
2023-12-11T13:54:45.878184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 332
41.3%
1 216
26.9%
2 193
24.0%
4 59
 
7.3%
6 3
 
0.4%
5 1
 
0.1%
ValueCountFrequency (%)
1 216
26.9%
2 193
24.0%
3 332
41.3%
4 59
 
7.3%
5 1
 
0.1%
6 3
 
0.4%
ValueCountFrequency (%)
6 3
 
0.4%
5 1
 
0.1%
4 59
 
7.3%
3 332
41.3%
2 193
24.0%
1 216
26.9%

카메라화소수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
200
794 
130
 
7
41
 
3

Length

Max length3
Median length3
Mean length2.9962687
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row200
2nd row200
3rd row200
4th row200
5th row200

Common Values

ValueCountFrequency (%)
200 794
98.8%
130 7
 
0.9%
41 3
 
0.4%

Length

2023-12-11T13:54:46.057780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:54:46.382555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
200 794
98.8%
130 7
 
0.9%
41 3
 
0.4%

촬영방면정보
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
360도전방면
772 
카메라 전면(고정)
 
32

Length

Max length10
Median length7
Mean length7.119403
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row360도전방면
2nd row360도전방면
3rd row360도전방면
4th row카메라 전면(고정)
5th row360도전방면

Common Values

ValueCountFrequency (%)
360도전방면 772
96.0%
카메라 전면(고정) 32
 
4.0%

Length

2023-12-11T13:54:46.996382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:54:47.543253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
360도전방면 772
92.3%
카메라 32
 
3.8%
전면(고정 32
 
3.8%

보관일수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
30
804 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30
2nd row30
3rd row30
4th row30
5th row30

Common Values

ValueCountFrequency (%)
30 804
100.0%

Length

2023-12-11T13:54:47.974486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:54:48.405387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 804
100.0%

설치년월
Text

Distinct66
Distinct (%)8.2%
Missing1
Missing (%)0.1%
Memory size6.4 KiB
2023-12-11T13:54:49.022516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.98132
Min length1

Characters and Unicode

Total characters4803
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)1.9%

Sample

1st rowDec-13
2nd rowDec-13
3rd rowDec-13
4th rowDec-13
5th rowSep-20
ValueCountFrequency (%)
dec-13 205
25.5%
dec-15 59
 
7.3%
dec-16 42
 
5.2%
feb-20 34
 
4.2%
feb-22 30
 
3.7%
sep-19 27
 
3.4%
dec-20 23
 
2.9%
jun-18 23
 
2.9%
jun-16 22
 
2.7%
oct-14 21
 
2.6%
Other values (56) 317
39.5%
2023-12-11T13:54:50.242920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 803
16.7%
1 659
13.7%
e 507
 
10.6%
c 417
 
8.7%
D 366
 
7.6%
2 226
 
4.7%
3 217
 
4.5%
u 119
 
2.5%
0 107
 
2.2%
F 105
 
2.2%
Other values (23) 1277
26.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1600
33.3%
Lowercase Letter 1600
33.3%
Dash Punctuation 803
16.7%
Uppercase Letter 800
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 507
31.7%
c 417
26.1%
u 119
 
7.4%
b 105
 
6.6%
n 75
 
4.7%
p 62
 
3.9%
t 51
 
3.2%
a 50
 
3.1%
o 47
 
2.9%
v 47
 
2.9%
Other values (4) 120
 
7.5%
Decimal Number
ValueCountFrequency (%)
1 659
41.2%
2 226
 
14.1%
3 217
 
13.6%
0 107
 
6.7%
5 84
 
5.2%
8 76
 
4.8%
6 73
 
4.6%
9 55
 
3.4%
4 52
 
3.2%
7 51
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
D 366
45.8%
F 105
 
13.1%
J 94
 
11.8%
A 66
 
8.2%
O 51
 
6.4%
N 47
 
5.9%
S 36
 
4.5%
M 35
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 803
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2403
50.0%
Latin 2400
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 507
21.1%
c 417
17.4%
D 366
15.2%
u 119
 
5.0%
F 105
 
4.4%
b 105
 
4.4%
J 94
 
3.9%
n 75
 
3.1%
A 66
 
2.8%
p 62
 
2.6%
Other values (12) 484
20.2%
Common
ValueCountFrequency (%)
- 803
33.4%
1 659
27.4%
2 226
 
9.4%
3 217
 
9.0%
0 107
 
4.5%
5 84
 
3.5%
8 76
 
3.2%
6 73
 
3.0%
9 55
 
2.3%
4 52
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4803
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 803
16.7%
1 659
13.7%
e 507
 
10.6%
c 417
 
8.7%
D 366
 
7.6%
2 226
 
4.7%
3 217
 
4.5%
u 119
 
2.5%
0 107
 
2.2%
F 105
 
2.2%
Other values (23) 1277
26.6%

관리기관번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
02-2148-4301
804 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row02-2148-4301
2nd row02-2148-4301
3rd row02-2148-4301
4th row02-2148-4301
5th row02-2148-4301

Common Values

ValueCountFrequency (%)
02-2148-4301 804
100.0%

Length

2023-12-11T13:54:50.726061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:54:51.107729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02-2148-4301 804
100.0%

위도
Real number (ℝ)

Distinct773
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.581451
Minimum37.567387
Maximum37.616553
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-11T13:54:51.582050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.567387
5-th percentile37.570319
Q137.573912
median37.578197
Q337.586668
95-th percentile37.605612
Maximum37.616553
Range0.049166
Interquartile range (IQR)0.01275625

Descriptive statistics

Standard deviation0.010384116
Coefficient of variation (CV)0.00027630961
Kurtosis1.1915977
Mean37.581451
Median Absolute Deviation (MAD)0.005299
Skewness1.2958207
Sum30215.486
Variance0.00010782987
MonotonicityNot monotonic
2023-12-11T13:54:52.159106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.575694 6
 
0.7%
37.572264 3
 
0.4%
37.573 3
 
0.4%
37.579057 2
 
0.2%
37.580421 2
 
0.2%
37.567387 2
 
0.2%
37.577837 2
 
0.2%
37.575179 2
 
0.2%
37.571806 2
 
0.2%
37.576939 2
 
0.2%
Other values (763) 778
96.8%
ValueCountFrequency (%)
37.567387 2
0.2%
37.568559 1
0.1%
37.568702 1
0.1%
37.568713 1
0.1%
37.568744 1
0.1%
37.5689 1
0.1%
37.568989 1
0.1%
37.569073 1
0.1%
37.569092 1
0.1%
37.569093 1
0.1%
ValueCountFrequency (%)
37.616553 1
0.1%
37.61485 1
0.1%
37.614715 1
0.1%
37.614664 1
0.1%
37.61401 1
0.1%
37.613921 1
0.1%
37.613456 1
0.1%
37.613127 1
0.1%
37.612638 1
0.1%
37.612555 1
0.1%

경도
Real number (ℝ)

Distinct785
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98861
Minimum126.9536
Maximum127.02296
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.2 KiB
2023-12-11T13:54:52.747391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.9536
5-th percentile126.96017
Q1126.96833
median126.99053
Q3127.00565
95-th percentile127.01842
Maximum127.02296
Range0.069359
Interquartile range (IQR)0.0373175

Descriptive statistics

Standard deviation0.019784999
Coefficient of variation (CV)0.00015580137
Kurtosis-1.3482956
Mean126.98861
Median Absolute Deviation (MAD)0.0187925
Skewness-0.021950493
Sum102098.84
Variance0.00039144619
MonotonicityNot monotonic
2023-12-11T13:54:53.326407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.012429 6
 
0.7%
126.986323 3
 
0.4%
127.022001 2
 
0.2%
126.986877 2
 
0.2%
126.967675 2
 
0.2%
126.963924 2
 
0.2%
126.965804 2
 
0.2%
126.965679 2
 
0.2%
127.010734 2
 
0.2%
126.96531 2
 
0.2%
Other values (775) 779
96.9%
ValueCountFrequency (%)
126.953597 1
0.1%
126.954983 1
0.1%
126.955233 1
0.1%
126.955875 1
0.1%
126.95616 1
0.1%
126.95634 1
0.1%
126.956509 1
0.1%
126.956631 1
0.1%
126.956637 1
0.1%
126.956638 1
0.1%
ValueCountFrequency (%)
127.022956 1
0.1%
127.02271 1
0.1%
127.022696 1
0.1%
127.02258 1
0.1%
127.02251 1
0.1%
127.022001 2
0.2%
127.021873 1
0.1%
127.021649 1
0.1%
127.021571 1
0.1%
127.021516 1
0.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.4 KiB
Minimum2022-03-01 00:00:00
Maximum2022-03-01 00:00:00
2023-12-11T13:54:53.713494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:54:53.884325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T13:54:40.377631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:54:38.836516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:54:39.351029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:54:40.537583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:54:38.998973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:54:39.509400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:54:40.683995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:54:39.162664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:54:40.212041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T13:54:54.035361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치목적구분카메라대수카메라화소수촬영방면정보설치년월위도경도
설치목적구분1.0000.8460.9410.4270.9900.2870.148
카메라대수0.8461.0000.7910.3460.8030.1570.134
카메라화소수0.9410.7911.0000.1810.9730.1550.000
촬영방면정보0.4270.3460.1811.0000.6140.0000.000
설치년월0.9900.8030.9730.6141.0000.4630.568
위도0.2870.1570.1550.0000.4631.0000.731
경도0.1480.1340.0000.0000.5680.7311.000
2023-12-11T13:54:54.269829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
촬영방면정보설치목적구분카메라화소수
촬영방면정보1.0000.3070.297
설치목적구분0.3071.0000.704
카메라화소수0.2970.7041.000
2023-12-11T13:54:54.462218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카메라대수위도경도설치목적구분카메라화소수촬영방면정보
카메라대수1.0000.032-0.0100.4650.4700.248
위도0.0321.000-0.3300.1540.0930.000
경도-0.010-0.3301.0000.0780.0000.000
설치목적구분0.4650.1540.0781.0000.7040.307
카메라화소수0.4700.0930.0000.7041.0000.297
촬영방면정보0.2480.0000.0000.3070.2971.000

Missing values

2023-12-11T13:54:40.974493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T13:54:41.354765image/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.
2023-12-11T13:54:41.567538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치년월관리기관번호위도경도데이터기준일자
0서울특별시 종로구청서울특별시 종로구 옥인6가길 8서울특별시 종로구 누상동 166-114생활방범3200360도전방면30Dec-1302-2148-430137.581566126.9649332022-03-01
1서울특별시 종로구청서울특별시 종로구 옥인6길 39서울특별시 종로구 누상동 166-16생활방범2200360도전방면30Dec-1302-2148-430137.58045126.9648482022-03-01
2서울특별시 종로구청서울특별시 종로구 옥인6길 23서울특별시 종로구 누상동 166-125생활방범2200360도전방면30Dec-1302-2148-430137.580918126.9647652022-03-01
3서울특별시 종로구청서울특별시 종로구 옥인6길 32서울특별시 종로구 누상동 166-214생활방범1200카메라 전면(고정)30Dec-1302-2148-430137.580905126.9645732022-03-01
4서울특별시 종로구청서울특별시 종로구 옥인3길 32-1서울특별시 종로구 누상동 166-3생활방범3200360도전방면30Sep-2002-2148-430137.579952126.9656942022-03-01
5서울특별시 종로구청서울특별시 종로구 옥인길 40서울특별시 종로구 옥인동 171-1생활방범4200360도전방면30Dec-1302-2148-430137.581068126.9665772022-03-01
6서울특별시 종로구청서울특별시 종로구 필운대로5나길 26서울특별시 종로구 누상동 80생활방범3200360도전방면30Dec-1302-2148-430137.580066126.9669432022-03-01
7서울특별시 종로구청서울특별시 종로구 자하문로23길 19서울특별시 종로구 신교동 17-47생활방범3200360도전방면30Dec-1302-2148-430137.583301126.9691772022-03-01
8서울특별시 종로구청서울특별시 종로구 필운대로 116서울특별시 종로구 신교동 59생활방범4200360도전방면30Mar-2002-2148-430137.583731126.9701922022-03-01
9서울특별시 종로구청서울특별시 종로구 필운대로13길 17-1서울특별시 종로구 신교동 2-20생활방범2200360도전방면30Dec-1302-2148-430137.584969126.9666262022-03-01
관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치년월관리기관번호위도경도데이터기준일자
794서울특별시 종로구청서울특별시 종로구 숭인동길 40서울특별시 종로구 숭인동 750교통단속1200360도전방면30May-2102-2148-430137.576939127.0220012022-03-01
795서울특별시 종로구청서울특별시 종로구 경교장길 5서울특별시 종로구 교남동 7교통단속1200360도전방면30Jun-2102-2148-430137.567387126.9658042022-03-01
796서울특별시 종로구청서울특별시 종로구 창신길 12서울특별시 종로구 창신동 56교통단속1200360도전방면30Sep-2102-2148-430137.572264127.0107342022-03-01
797서울특별시 종로구청서울특별시 종로구 삼일대로30길 23서울특별시 종로구 익선동 34교통단속1200360도전방면30Oct-2102-2148-430137.574145126.9889522022-03-01
798서울특별시 종로구청서울특별시 종로구 세검정로6길 51-4서울특별시 종로구 신영동 140-1치수1200360도전방면30Jul-1402-2148-430137.600281126.9618832022-03-01
799서울특별시 종로구청서울특별시 종로구 세검정로9길 1서울특별시 종로구 신영동 219-4치수1200360도전방면30Jul-1402-2148-430137.603375126.9620142022-03-01
800서울특별시 종로구청서울특별시 종로구 홍지동 72-7<NA>치수1200360도전방면30Nov-1602-2148-430137.600282126.9579492022-03-01
801서울특별시 종로구청서울특별시 종로구 홍지동 136-3<NA>문화재441카메라 전면(고정)30-02-2148-430137.598804126.9566312022-03-01
802서울특별시 종로구청서울특별시 종로구 창경궁로 307서울특별시 종로구 혜화동 28-5문화재641카메라 전면(고정)30-02-2148-430137.587933127.0038212022-03-01
803서울특별시 종로구청서울특별시 종로구 혜화로5길 53서울특별시 종로구 명륜1가 36-1문화재641카메라 전면(고정)30-02-2148-430137.587548126.9997152022-03-01

Duplicate rows

Most frequently occurring

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치년월관리기관번호위도경도데이터기준일자# duplicates
1서울특별시 종로구청서울특별시 종로구 창신6가길 39 (산마루놀이터)서울특별시 종로구 창신동 23-350공원1200360도전방면30Nov-1802-2148-430137.575694127.0124292022-03-015
0서울특별시 종로구청서울특별시 종로구 인사동길 24서울특별시 종로구 인사동 15생활방범1200카메라 전면(고정)30Jan-2202-2148-430137.573126.9863232022-03-012