Overview

Dataset statistics

Number of variables10
Number of observations78
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory84.7 B

Variable types

Text4
Categorical3
Numeric3

Dataset

Description중소기업은행의 CCTV 현황을 csv파일로 제공 *제공정보 : 관리기관명, 소재지 도로명(지번) 주소, 카메라 대수 등
URLhttps://www.data.go.kr/data/15077778/fileData.do

Alerts

설치목적구분 has constant value ""Constant
보관일수 has constant value ""Constant
데이터기준일자 has constant value ""Constant
관리기관명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
소재지지번주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:22:30.040208
Analysis finished2023-12-12 00:22:31.744525
Duration1.7 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Text

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-12T09:22:31.949243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length10.320513
Min length7

Characters and Unicode

Total characters805
Distinct characters121
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

Unique78 ?
Unique (%)100.0%

Sample

1st row기업은행 수지IT센터
2nd row기업은행 한티역지점
3rd row기업은행 노원역지점
4th row기업은행 마들역지점
5th row기업은행 장위동지점
ValueCountFrequency (%)
기업은행 78
50.0%
울산중앙지점 1
 
0.6%
남동2단지지점 1
 
0.6%
검단산업단지지점 1
 
0.6%
충주연수원 1
 
0.6%
기흥연수원 1
 
0.6%
불광역지점 1
 
0.6%
북가좌동지점 1
 
0.6%
동대문지점 1
 
0.6%
창원지점 1
 
0.6%
Other values (69) 69
44.2%
2023-12-12T09:22:32.406607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 80
 
9.9%
기 79
 
9.8%
은 78
 
9.7%
행 78
 
9.7%
78
 
9.7%
지 75
 
9.3%
점 71
 
8.8%
동 18
 
2.2%
단 15
 
1.9%
산 13
 
1.6%
Other values (111) 220
27.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 711
88.3%
Space Separator 78
 
9.7%
Uppercase Letter 8
 
1.0%
Decimal Number 6
 
0.7%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 80
11.3%
기 79
11.1%
은 78
 
11.0%
행 78
 
11.0%
지 75
 
10.5%
점 71
 
10.0%
동 18
 
2.5%
단 15
 
2.1%
산 13
 
1.8%
역 8
 
1.1%
Other values (101) 196
27.6%
Uppercase Letter
ValueCountFrequency (%)
T 3
37.5%
V 2
25.0%
M 2
25.0%
I 1
 
12.5%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
3 2
33.3%
4 1
 
16.7%
Space Separator
ValueCountFrequency (%)
78
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 711
88.3%
Common 86
 
10.7%
Latin 8
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 80
11.3%
기 79
11.1%
은 78
 
11.0%
행 78
 
11.0%
지 75
 
10.5%
점 71
 
10.0%
동 18
 
2.5%
단 15
 
2.1%
산 13
 
1.8%
역 8
 
1.1%
Other values (101) 196
27.6%
Common
ValueCountFrequency (%)
78
90.7%
2 3
 
3.5%
3 2
 
2.3%
) 1
 
1.2%
( 1
 
1.2%
4 1
 
1.2%
Latin
ValueCountFrequency (%)
T 3
37.5%
V 2
25.0%
M 2
25.0%
I 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 711
88.3%
ASCII 94
 
11.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 80
11.3%
기 79
11.1%
은 78
 
11.0%
행 78
 
11.0%
지 75
 
10.5%
점 71
 
10.0%
동 18
 
2.5%
단 15
 
2.1%
산 13
 
1.8%
역 8
 
1.1%
Other values (101) 196
27.6%
ASCII
ValueCountFrequency (%)
78
83.0%
2 3
 
3.2%
T 3
 
3.2%
3 2
 
2.1%
V 2
 
2.1%
M 2
 
2.1%
) 1
 
1.1%
( 1
 
1.1%
I 1
 
1.1%
4 1
 
1.1%

소재지도로명주소
Text

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-12T09:22:32.843061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length30.5
Mean length24.935897
Min length17

Characters and Unicode

Total characters1945
Distinct characters178
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)100.0%

Sample

1st row경기도 용인시 수지구 신수로 799 (동천동)
2nd row서울특별시 강남구 선릉로 332 (대치동)
3rd row서울특별시 노원구 노해로 489 (상계동)
4th row서울특별시 노원구 동일로 1527 (상계동)
5th row서울특별시 성북구 화랑로 251 (장위동)
ValueCountFrequency (%)
경기도 17
 
4.1%
서울특별시 17
 
4.1%
부산광역시 8
 
1.9%
경상북도 8
 
1.9%
중앙로 7
 
1.7%
대구광역시 6
 
1.4%
중구 5
 
1.2%
인천광역시 5
 
1.2%
전라남도 4
 
1.0%
시흥시 4
 
1.0%
Other values (295) 338
80.7%
2023-12-12T09:22:33.490289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
342
 
17.6%
로 83
 
4.3%
시 82
 
4.2%
동 79
 
4.1%
) 77
 
4.0%
( 77
 
4.0%
구 68
 
3.5%
2 54
 
2.8%
1 44
 
2.3%
도 41
 
2.1%
Other values (168) 998
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1171
60.2%
Space Separator 342
 
17.6%
Decimal Number 269
 
13.8%
Close Punctuation 77
 
4.0%
Open Punctuation 77
 
4.0%
Dash Punctuation 5
 
0.3%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 83
 
7.1%
시 82
 
7.0%
동 79
 
6.7%
구 68
 
5.8%
도 41
 
3.5%
산 35
 
3.0%
광 32
 
2.7%
서 32
 
2.7%
경 30
 
2.6%
대 25
 
2.1%
Other values (152) 664
56.7%
Decimal Number
ValueCountFrequency (%)
2 54
20.1%
1 44
16.4%
3 29
10.8%
5 27
10.0%
6 22
8.2%
8 22
8.2%
7 18
 
6.7%
9 18
 
6.7%
4 18
 
6.7%
0 16
 
5.9%
Space Separator
ValueCountFrequency (%)
342
100.0%
Close Punctuation
ValueCountFrequency (%)
) 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 77
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1171
60.2%
Common 774
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 83
 
7.1%
시 82
 
7.0%
동 79
 
6.7%
구 68
 
5.8%
도 41
 
3.5%
산 35
 
3.0%
광 32
 
2.7%
서 32
 
2.7%
경 30
 
2.6%
대 25
 
2.1%
Other values (152) 664
56.7%
Common
ValueCountFrequency (%)
342
44.2%
) 77
 
9.9%
( 77
 
9.9%
2 54
 
7.0%
1 44
 
5.7%
3 29
 
3.7%
5 27
 
3.5%
6 22
 
2.8%
8 22
 
2.8%
7 18
 
2.3%
Other values (6) 62
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1171
60.2%
ASCII 773
39.7%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
342
44.2%
) 77
 
10.0%
( 77
 
10.0%
2 54
 
7.0%
1 44
 
5.7%
3 29
 
3.8%
5 27
 
3.5%
6 22
 
2.8%
8 22
 
2.8%
7 18
 
2.3%
Other values (5) 61
 
7.9%
Hangul
ValueCountFrequency (%)
로 83
 
7.1%
시 82
 
7.0%
동 79
 
6.7%
구 68
 
5.8%
도 41
 
3.5%
산 35
 
3.0%
광 32
 
2.7%
서 32
 
2.7%
경 30
 
2.6%
대 25
 
2.1%
Other values (152) 664
56.7%
None
ValueCountFrequency (%)
１ 1
100.0%

소재지지번주소
Text

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-12T09:22:33.907653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length19.269231
Min length15

Characters and Unicode

Total characters1503
Distinct characters141
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

Unique78 ?
Unique (%)100.0%

Sample

1st row경기도 용인시 수지구 동천동 185-3
2nd row서울특별시 강남구 대치동 921-3
3rd row서울특별시 노원구 상계2동 716-1
4th row서울특별시 노원구 상계동 651-8
5th row서울특별시 성북구 장위동 63-91
ValueCountFrequency (%)
경기도 17
 
5.1%
서울특별시 17
 
5.1%
부산광역시 8
 
2.4%
경상북도 8
 
2.4%
대구광역시 6
 
1.8%
중구 6
 
1.8%
인천광역시 5
 
1.5%
전라남도 4
 
1.2%
시흥시 4
 
1.2%
서구 3
 
0.9%
Other values (229) 256
76.6%
2023-12-12T09:22:34.449523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
261
 
17.4%
시 80
 
5.3%
1 79
 
5.3%
동 76
 
5.1%
구 64
 
4.3%
- 59
 
3.9%
2 43
 
2.9%
도 41
 
2.7%
3 30
 
2.0%
광 30
 
2.0%
Other values (131) 740
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 864
57.5%
Decimal Number 319
 
21.2%
Space Separator 261
 
17.4%
Dash Punctuation 59
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 80
 
9.3%
동 76
 
8.8%
구 64
 
7.4%
도 41
 
4.7%
광 30
 
3.5%
경 29
 
3.4%
서 27
 
3.1%
산 26
 
3.0%
역 23
 
2.7%
기 19
 
2.2%
Other values (119) 449
52.0%
Decimal Number
ValueCountFrequency (%)
1 79
24.8%
2 43
13.5%
3 30
 
9.4%
5 30
 
9.4%
0 27
 
8.5%
4 27
 
8.5%
7 26
 
8.2%
8 23
 
7.2%
6 18
 
5.6%
9 16
 
5.0%
Space Separator
ValueCountFrequency (%)
261
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 864
57.5%
Common 639
42.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 80
 
9.3%
동 76
 
8.8%
구 64
 
7.4%
도 41
 
4.7%
광 30
 
3.5%
경 29
 
3.4%
서 27
 
3.1%
산 26
 
3.0%
역 23
 
2.7%
기 19
 
2.2%
Other values (119) 449
52.0%
Common
ValueCountFrequency (%)
261
40.8%
1 79
 
12.4%
- 59
 
9.2%
2 43
 
6.7%
3 30
 
4.7%
5 30
 
4.7%
0 27
 
4.2%
4 27
 
4.2%
7 26
 
4.1%
8 23
 
3.6%
Other values (2) 34
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 864
57.5%
ASCII 639
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
261
40.8%
1 79
 
12.4%
- 59
 
9.2%
2 43
 
6.7%
3 30
 
4.7%
5 30
 
4.7%
0 27
 
4.2%
4 27
 
4.2%
7 26
 
4.1%
8 23
 
3.6%
Other values (2) 34
 
5.3%
Hangul
ValueCountFrequency (%)
시 80
 
9.3%
동 76
 
8.8%
구 64
 
7.4%
도 41
 
4.7%
광 30
 
3.5%
경 29
 
3.4%
서 27
 
3.1%
산 26
 
3.0%
역 23
 
2.7%
기 19
 
2.2%
Other values (119) 449
52.0%

설치목적구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
다목적
78 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
다목적 78
100.0%

Length

2023-12-12T09:22:34.604740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:22:34.720560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다목적 78
100.0%

카메라대수
Real number (ℝ)

Distinct13
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1153846
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-12T09:22:34.845499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile13
Maximum20
Range19
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.9443557
Coefficient of variation (CV)0.95844158
Kurtosis6.6635287
Mean4.1153846
Median Absolute Deviation (MAD)1
Skewness2.4856933
Sum321
Variance15.557942
MonotonicityNot monotonic
2023-12-12T09:22:35.006215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2 17
21.8%
1 15
19.2%
3 15
19.2%
5 8
10.3%
4 8
10.3%
6 5
 
6.4%
8 2
 
2.6%
7 2
 
2.6%
13 2
 
2.6%
12 1
 
1.3%
Other values (3) 3
 
3.8%
ValueCountFrequency (%)
1 15
19.2%
2 17
21.8%
3 15
19.2%
4 8
10.3%
5 8
10.3%
6 5
 
6.4%
7 2
 
2.6%
8 2
 
2.6%
12 1
 
1.3%
13 2
 
2.6%
ValueCountFrequency (%)
20 1
 
1.3%
19 1
 
1.3%
18 1
 
1.3%
13 2
 
2.6%
12 1
 
1.3%
8 2
 
2.6%
7 2
 
2.6%
6 5
6.4%
5 8
10.3%
4 8
10.3%

보관일수
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
2개월
78 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2개월
2nd row2개월
3rd row2개월
4th row2개월
5th row2개월

Common Values

ValueCountFrequency (%)
2개월 78
100.0%

Length

2023-12-12T09:22:35.148057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:22:35.239780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2개월 78
100.0%

관리기관전화번호
Text

Distinct74
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size756.0 B
2023-12-12T09:22:35.501641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.820513
Min length11

Characters and Unicode

Total characters922
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)89.7%

Sample

1st row031-229-2162
2nd row02-508-3983
3rd row02-939-3813
4th row02-934-7873
5th row02-915-4133
ValueCountFrequency (%)
051-727-8343 2
 
2.6%
031-496-8646 2
 
2.6%
031-275-6504 2
 
2.6%
02-729-7866 2
 
2.6%
031-229-2162 1
 
1.3%
032-517-8233 1
 
1.3%
032-529-1451 1
 
1.3%
032-815-6023 1
 
1.3%
032-822-7183 1
 
1.3%
043-840-6108 1
 
1.3%
Other values (64) 64
82.1%
2023-12-12T09:22:35.962654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 156
16.9%
0 121
13.1%
3 115
12.5%
1 91
9.9%
2 85
9.2%
5 70
7.6%
4 70
7.6%
6 63
6.8%
7 59
 
6.4%
8 52
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 766
83.1%
Dash Punctuation 156
 
16.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 121
15.8%
3 115
15.0%
1 91
11.9%
2 85
11.1%
5 70
9.1%
4 70
9.1%
6 63
8.2%
7 59
7.7%
8 52
6.8%
9 40
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 156
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 922
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 156
16.9%
0 121
13.1%
3 115
12.5%
1 91
9.9%
2 85
9.2%
5 70
7.6%
4 70
7.6%
6 63
6.8%
7 59
 
6.4%
8 52
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 922
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 156
16.9%
0 121
13.1%
3 115
12.5%
1 91
9.9%
2 85
9.2%
5 70
7.6%
4 70
7.6%
6 63
6.8%
7 59
 
6.4%
8 52
 
5.6%

위도
Real number (ℝ)

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.602633
Minimum34.740455
Maximum37.754661
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-12T09:22:36.126563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.740455
5-th percentile35.059824
Q135.837565
median37.089342
Q337.49676
95-th percentile37.651893
Maximum37.754661
Range3.014206
Interquartile range (IQR)1.659195

Descriptive statistics

Standard deviation0.99782009
Coefficient of variation (CV)0.027260883
Kurtosis-1.3725205
Mean36.602633
Median Absolute Deviation (MAD)0.5226415
Skewness-0.48880967
Sum2855.0054
Variance0.99564494
MonotonicityNot monotonic
2023-12-12T09:22:36.264505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.341554 1
 
1.3%
37.582427 1
 
1.3%
37.514312 1
 
1.3%
37.408794 1
 
1.3%
37.394261 1
 
1.3%
37.594847 1
 
1.3%
36.999479 1
 
1.3%
37.227485 1
 
1.3%
37.610318 1
 
1.3%
37.651314 1
 
1.3%
Other values (68) 68
87.2%
ValueCountFrequency (%)
34.740455 1
1.3%
34.766117 1
1.3%
34.802006 1
1.3%
34.943306 1
1.3%
35.080386 1
1.3%
35.090247 1
1.3%
35.092432 1
1.3%
35.099425 1
1.3%
35.100025 1
1.3%
35.137002 1
1.3%
ValueCountFrequency (%)
37.754661 1
1.3%
37.664978 1
1.3%
37.659394 1
1.3%
37.655173 1
1.3%
37.651314 1
1.3%
37.611429 1
1.3%
37.610318 1
1.3%
37.594847 1
1.3%
37.582427 1
1.3%
37.571045 1
1.3%

경도
Real number (ℝ)

UNIQUE 

Distinct78
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.58406
Minimum126.43017
Maximum129.36473
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size834.0 B
2023-12-12T09:22:36.409718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.43017
5-th percentile126.69687
Q1126.89663
median127.06905
Q3128.47727
95-th percentile129.0748
Maximum129.36473
Range2.934565
Interquartile range (IQR)1.5806405

Descriptive statistics

Standard deviation0.90154085
Coefficient of variation (CV)0.0070662496
Kurtosis-1.1925511
Mean127.58406
Median Absolute Deviation (MAD)0.3407665
Skewness0.65334385
Sum9951.5571
Variance0.8127759
MonotonicityNot monotonic
2023-12-12T09:22:36.578603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.102024 1
 
1.3%
126.912926 1
 
1.3%
126.704254 1
 
1.3%
126.695386 1
 
1.3%
126.697136 1
 
1.3%
126.613367 1
 
1.3%
128.007014 1
 
1.3%
127.112323 1
 
1.3%
126.929691 1
 
1.3%
126.778567 1
 
1.3%
Other values (68) 68
87.2%
ValueCountFrequency (%)
126.430167 1
1.3%
126.438145 1
1.3%
126.613367 1
1.3%
126.695386 1
1.3%
126.697136 1
1.3%
126.704254 1
1.3%
126.711497 1
1.3%
126.727183 1
1.3%
126.731429 1
1.3%
126.764173 1
1.3%
ValueCountFrequency (%)
129.364732 1
1.3%
129.329603 1
1.3%
129.216772 1
1.3%
129.180264 1
1.3%
129.056189 1
1.3%
129.038395 1
1.3%
129.035081 1
1.3%
129.024721 1
1.3%
128.987195 1
1.3%
128.970032 1
1.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size756.0 B
2022-12-31
78 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-31
2nd row2022-12-31
3rd row2022-12-31
4th row2022-12-31
5th row2022-12-31

Common Values

ValueCountFrequency (%)
2022-12-31 78
100.0%

Length

2023-12-12T09:22:36.753422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:22:36.853683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-31 78
100.0%

Interactions

2023-12-12T09:22:31.142442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:22:30.535795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:22:30.845735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:22:31.249745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:22:30.648261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:22:30.942267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:22:31.335628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:22:30.754101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:22:31.054365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:22:36.928186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관명소재지도로명주소소재지지번주소카메라대수관리기관전화번호위도경도
관리기관명1.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.000
카메라대수1.0001.0001.0001.0000.0000.0640.335
관리기관전화번호1.0001.0001.0000.0001.0000.9960.906
위도1.0001.0001.0000.0640.9961.0000.924
경도1.0001.0001.0000.3350.9060.9241.000
2023-12-12T09:22:37.043095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카메라대수위도경도
카메라대수1.0000.0270.122
위도0.0271.000-0.477
경도0.122-0.4771.000

Missing values

2023-12-12T09:22:31.485606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:22:31.647224image/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

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수보관일수관리기관전화번호위도경도데이터기준일자
0기업은행 수지IT센터경기도 용인시 수지구 신수로 799 (동천동)경기도 용인시 수지구 동천동 185-3다목적122개월031-229-216237.341554127.1020242022-12-31
1기업은행 한티역지점서울특별시 강남구 선릉로 332 (대치동)서울특별시 강남구 대치동 921-3다목적22개월02-508-398337.499655127.0516772022-12-31
2기업은행 노원역지점서울특별시 노원구 노해로 489 (상계동)서울특별시 노원구 상계2동 716-1다목적62개월02-939-381337.655173127.0621762022-12-31
3기업은행 마들역지점서울특별시 노원구 동일로 1527 (상계동)서울특별시 노원구 상계동 651-8다목적12개월02-934-787337.664978127.0574452022-12-31
4기업은행 장위동지점서울특별시 성북구 화랑로 251 (장위동)서울특별시 성북구 장위동 63-91다목적22개월02-915-413337.611429127.0570112022-12-31
5기업은행 상계역지점서울특별시 노원구 덕릉로 690(중계동)서울특별시 노원구 중계동 160-3다목적32개월02-936-008837.659394127.0756442022-12-31
6기업은행 문래동지점서울특별시 영등포구 도림로128길 2 (문래동3가)서울특별시 영등포구 문래동3가 54-14다목적52개월02-2675-876137.515075126.8960992022-12-31
7기업은행 강릉지점강원도 강릉시 경강로 2087 (임당동)강원도 강릉시 임당동 82-1다목적12개월033-641-179337.754661128.8952722022-12-31
8기업은행 원주지점강원도 원주시 원일로 107 (일산동)강원도 원주시 일산동 52-3다목적32개월033-742-310337.349477127.9487382022-12-31
9기업은행 발안산단지점경기도 화성시 향남읍 발안공단로2길 38 (하길리)경기도 화성시 향남읍 하길리 1410-3다목적22개월031-366-096237.087348126.9118592022-12-31
관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수보관일수관리기관전화번호위도경도데이터기준일자
68기업은행 대불공단지점전라남도 영암군 삼호읍 나불로 206 (나불리)전라남도 영암군 삼호읍 나불리 338-7다목적12개월061-463-113734.766117126.4381452022-12-31
69기업은행 목포지점전라남도 목포시 옥암로 25 (상동)전라남도 목포시 상동 1009-2다목적42개월061-284-783034.802006126.4301672022-12-31
70기업은행 하남공단지점광주광역시 광산구 하남산단8번로 169 (도천동)광주광역시 광산구 도천동 621-17다목적22개월062-958-590235.209127126.8142652022-12-31
71기업은행 광양지점전라남도 광양시 오류로 52 (중동)전라남도 광양시 중동 1324-4다목적12개월061-791-731334.943306127.6954052022-12-31
72기업은행 정읍지점전라북도 정읍시 중앙로 72 (연지동)전라북도 정읍시 연지동 50-4다목적22개월063-531-411435.570042126.8482752022-12-31
73기업은행 전주지점전라북도 전주시 완산구 팔달로 163 (경원동1가)전라북도 전주시 완산구 경원동1가 106다목적12개월063-284-682335.817319127.1470222022-12-31
74기업은행 익산중앙지점전라북도 익산시 익산대로16길 23 (창인동1가)전라북도 익산시 창인동1가 145다목적12개월063-858-993735.940422126.9500192022-12-31
75기업은행 여수지점전라남도 여수시 통제영5길 6 (중앙동)전라남도 여수시 중앙동 710다목적12개월061-662-511334.740455127.7358032022-12-31
76기업은행 용인통합서고경기도 용인시 처인구 남사면 원암로 346 (방아리)경기도 용인시 처인구 남사면 방아리 1121-7다목적132개월02-3425-411337.091336127.1832732022-12-31
77기업은행 시흥매화산단지점경기도 시흥시 매화산단2길 15경기도 시흥시 도창동 508-21다목적52개월031-599-244137.407844126.81912022-12-31