Overview

Dataset statistics

Number of variables12
Number of observations53
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory101.5 B

Variable types

Numeric3
Text3
Categorical4
DateTime2

Dataset

Description서울특별시 종로구에 설치되어 있는 햇빛 그늘막(가림막)에 대한 위치(위,경도), 주소, 그늘막 재질 등에 대한 데이터를 등록합니다.
Author서울특별시 종로구
URLhttps://www.data.go.kr/data/15103072/fileData.do

Alerts

담당부서 has constant value ""Constant
데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 원단High correlation
위도 is highly overall correlated with 행정동High correlation
경도 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
규모(높이_지름) is highly overall correlated with 원단High correlation
원단 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
관리번호 has unique valuesUnique
설치장소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:33:17.635627
Analysis finished2023-12-12 00:33:19.240669
Duration1.61 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T09:33:19.316419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.6
Q114
median27
Q340
95-th percentile50.4
Maximum53
Range52
Interquartile range (IQR)26

Descriptive statistics

Standard deviation15.443445
Coefficient of variation (CV)0.57197945
Kurtosis-1.2
Mean27
Median Absolute Deviation (MAD)13
Skewness0
Sum1431
Variance238.5
MonotonicityStrictly increasing
2023-12-12T09:33:19.450623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
41 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
53 1
1.9%
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%

관리번호
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T09:33:19.690606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10.377358
Min length8

Characters and Unicode

Total characters550
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)100.0%

Sample

1st row1(사직동-1)
2nd row2(사직동-2)
3rd row3(삼청동-1)
4th row4(삼청동-2)
5th row5(부암동-1)
ValueCountFrequency (%)
1(사직동-1 1
 
1.9%
28(교남동-3 1
 
1.9%
30(교남동-5 1
 
1.9%
31(가회동-1 1
 
1.9%
32(종로14가동-4 1
 
1.9%
33(종로14가동-5 1
 
1.9%
34(종로14가동-6 1
 
1.9%
35(종로14가동-7 1
 
1.9%
36(종로14가동-8 1
 
1.9%
37(종로14가동-9 1
 
1.9%
Other values (43) 43
81.1%
2023-12-12T09:33:20.076873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 61
11.1%
( 54
 
9.8%
- 53
 
9.6%
) 53
 
9.6%
동 53
 
9.6%
4 39
 
7.1%
2 31
 
5.6%
3 24
 
4.4%
가 22
 
4.0%
로 21
 
3.8%
Other values (29) 139
25.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 208
37.8%
Other Letter 182
33.1%
Open Punctuation 54
 
9.8%
Dash Punctuation 53
 
9.6%
Close Punctuation 53
 
9.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 53
29.1%
가 22
12.1%
로 21
 
11.5%
종 21
 
11.5%
화 6
 
3.3%
사 5
 
2.7%
직 5
 
2.7%
창 5
 
2.7%
이 4
 
2.2%
신 4
 
2.2%
Other values (16) 36
19.8%
Decimal Number
ValueCountFrequency (%)
1 61
29.3%
4 39
18.8%
2 31
14.9%
3 24
 
11.5%
5 17
 
8.2%
6 11
 
5.3%
7 7
 
3.4%
8 6
 
2.9%
9 6
 
2.9%
0 6
 
2.9%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%
Close Punctuation
ValueCountFrequency (%)
) 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 368
66.9%
Hangul 182
33.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 53
29.1%
가 22
12.1%
로 21
 
11.5%
종 21
 
11.5%
화 6
 
3.3%
사 5
 
2.7%
직 5
 
2.7%
창 5
 
2.7%
이 4
 
2.2%
신 4
 
2.2%
Other values (16) 36
19.8%
Common
ValueCountFrequency (%)
1 61
16.6%
( 54
14.7%
- 53
14.4%
) 53
14.4%
4 39
10.6%
2 31
8.4%
3 24
 
6.5%
5 17
 
4.6%
6 11
 
3.0%
7 7
 
1.9%
Other values (3) 18
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 368
66.9%
Hangul 182
33.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 61
16.6%
( 54
14.7%
- 53
14.4%
) 53
14.4%
4 39
10.6%
2 31
8.4%
3 24
 
6.5%
5 17
 
4.6%
6 11
 
3.0%
7 7
 
1.9%
Other values (3) 18
 
4.9%
Hangul
ValueCountFrequency (%)
동 53
29.1%
가 22
12.1%
로 21
 
11.5%
종 21
 
11.5%
화 6
 
3.3%
사 5
 
2.7%
직 5
 
2.7%
창 5
 
2.7%
이 4
 
2.2%
신 4
 
2.2%
Other values (16) 36
19.8%

행정동
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Memory size556.0 B
종로14가동
17 
사직동
5 
교남동
4 
종로56가동
4 
이화동
4 
Other values (12)
19 

Length

Max length6
Median length5
Mean length4.3962264
Min length3

Unique

Unique7 ?
Unique (%)13.2%

Sample

1st row사직동
2nd row사직동
3rd row삼청동
4th row삼청동
5th row부암동

Common Values

ValueCountFrequency (%)
종로14가동 17
32.1%
사직동 5
 
9.4%
교남동 4
 
7.5%
종로56가동 4
 
7.5%
이화동 4
 
7.5%
부암동 3
 
5.7%
숭인2동 3
 
5.7%
삼청동 2
 
3.8%
혜화동 2
 
3.8%
창신1동 2
 
3.8%
Other values (7) 7
13.2%

Length

2023-12-12T09:33:20.223943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
종로14가동 17
32.1%
사직동 5
 
9.4%
교남동 4
 
7.5%
종로56가동 4
 
7.5%
이화동 4
 
7.5%
부암동 3
 
5.7%
숭인2동 3
 
5.7%
삼청동 2
 
3.8%
혜화동 2
 
3.8%
창신1동 2
 
3.8%
Other values (6) 7
13.2%

설치장소
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T09:33:20.568538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length14.358491
Min length8

Characters and Unicode

Total characters761
Distinct characters176
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

Unique53 ?
Unique (%)100.0%

Sample

1st row사직동주민센터 앞 교통섬
2nd row경복궁역 1번출구 교통섬
3rd row안국빌딩 앞 교통섬
4th row동십자각 사거리 교통섬
5th row상명대 입구 교차로 분수대 방면 교통섬
ValueCountFrequency (%)
앞 31
 
17.4%
교통섬 18
 
10.1%
횡단보도 11
 
6.2%
사거리 9
 
5.1%
방면 5
 
2.8%
입구 4
 
2.2%
출구 4
 
2.2%
교차로 3
 
1.7%
종로3가역 2
 
1.1%
흥인지문 2
 
1.1%
Other values (82) 89
50.0%
2023-12-12T09:33:21.126237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
127
 
16.7%
앞 33
 
4.3%
교 25
 
3.3%
리 22
 
2.9%
동 19
 
2.5%
섬 18
 
2.4%
통 18
 
2.4%
사 16
 
2.1%
거 16
 
2.1%
로 14
 
1.8%
Other values (166) 453
59.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 597
78.4%
Space Separator 127
 
16.7%
Decimal Number 24
 
3.2%
Uppercase Letter 9
 
1.2%
Lowercase Letter 2
 
0.3%
Dash Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 33
 
5.5%
교 25
 
4.2%
리 22
 
3.7%
동 19
 
3.2%
섬 18
 
3.0%
통 18
 
3.0%
사 16
 
2.7%
거 16
 
2.7%
로 14
 
2.3%
구 14
 
2.3%
Other values (146) 402
67.3%
Decimal Number
ValueCountFrequency (%)
3 6
25.0%
2 5
20.8%
1 4
16.7%
6 2
 
8.3%
5 2
 
8.3%
0 2
 
8.3%
7 1
 
4.2%
9 1
 
4.2%
4 1
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
E 2
22.2%
W 2
22.2%
T 2
22.2%
K 1
11.1%
J 1
11.1%
S 1
11.1%
Lowercase Letter
ValueCountFrequency (%)
s 1
50.0%
c 1
50.0%
Space Separator
ValueCountFrequency (%)
127
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 597
78.4%
Common 153
 
20.1%
Latin 11
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 33
 
5.5%
교 25
 
4.2%
리 22
 
3.7%
동 19
 
3.2%
섬 18
 
3.0%
통 18
 
3.0%
사 16
 
2.7%
거 16
 
2.7%
로 14
 
2.3%
구 14
 
2.3%
Other values (146) 402
67.3%
Common
ValueCountFrequency (%)
127
83.0%
3 6
 
3.9%
2 5
 
3.3%
1 4
 
2.6%
6 2
 
1.3%
5 2
 
1.3%
0 2
 
1.3%
7 1
 
0.7%
9 1
 
0.7%
- 1
 
0.7%
Other values (2) 2
 
1.3%
Latin
ValueCountFrequency (%)
E 2
18.2%
W 2
18.2%
T 2
18.2%
K 1
9.1%
s 1
9.1%
c 1
9.1%
J 1
9.1%
S 1
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 597
78.4%
ASCII 164
 
21.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
127
77.4%
3 6
 
3.7%
2 5
 
3.0%
1 4
 
2.4%
6 2
 
1.2%
E 2
 
1.2%
W 2
 
1.2%
5 2
 
1.2%
T 2
 
1.2%
0 2
 
1.2%
Other values (10) 10
 
6.1%
Hangul
ValueCountFrequency (%)
앞 33
 
5.5%
교 25
 
4.2%
리 22
 
3.7%
동 19
 
3.2%
섬 18
 
3.0%
통 18
 
3.0%
사 16
 
2.7%
거 16
 
2.7%
로 14
 
2.3%
구 14
 
2.3%
Other values (146) 402
67.3%

도로명주소
Text

Distinct52
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T09:33:21.370336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length6.9811321
Min length3

Characters and Unicode

Total characters370
Distinct characters56
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)96.2%

Sample

1st row사직로9길 5
2nd row자하문로 1
3rd row율곡로 33
4th row율곡로 1
5th row세검정로 220
ValueCountFrequency (%)
종로 12
 
11.7%
율곡로 4
 
3.9%
창경궁로 3
 
2.9%
99 3
 
2.9%
청계천로 3
 
2.9%
세종대로 3
 
2.9%
1 3
 
2.9%
대학로 3
 
2.9%
통일로 2
 
1.9%
우정국로 2
 
1.9%
Other values (59) 65
63.1%
2023-12-12T09:33:21.688660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
 
14.1%
로 48
 
13.0%
1 27
 
7.3%
9 20
 
5.4%
종 19
 
5.1%
2 17
 
4.6%
3 13
 
3.5%
4 13
 
3.5%
7 11
 
3.0%
길 10
 
2.7%
Other values (46) 140
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 177
47.8%
Decimal Number 133
35.9%
Space Separator 52
 
14.1%
Open Punctuation 3
 
0.8%
Close Punctuation 3
 
0.8%
Dash Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 48
27.1%
종 19
 
10.7%
길 10
 
5.6%
대 8
 
4.5%
세 6
 
3.4%
창 5
 
2.8%
문 5
 
2.8%
율 5
 
2.8%
곡 5
 
2.8%
정 4
 
2.3%
Other values (32) 62
35.0%
Decimal Number
ValueCountFrequency (%)
1 27
20.3%
9 20
15.0%
2 17
12.8%
3 13
9.8%
4 13
9.8%
7 11
8.3%
5 10
 
7.5%
8 8
 
6.0%
6 7
 
5.3%
0 7
 
5.3%
Space Separator
ValueCountFrequency (%)
52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 193
52.2%
Hangul 177
47.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 48
27.1%
종 19
 
10.7%
길 10
 
5.6%
대 8
 
4.5%
세 6
 
3.4%
창 5
 
2.8%
문 5
 
2.8%
율 5
 
2.8%
곡 5
 
2.8%
정 4
 
2.3%
Other values (32) 62
35.0%
Common
ValueCountFrequency (%)
52
26.9%
1 27
14.0%
9 20
 
10.4%
2 17
 
8.8%
3 13
 
6.7%
4 13
 
6.7%
7 11
 
5.7%
5 10
 
5.2%
8 8
 
4.1%
6 7
 
3.6%
Other values (4) 15
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193
52.2%
Hangul 177
47.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
26.9%
1 27
14.0%
9 20
 
10.4%
2 17
 
8.8%
3 13
 
6.7%
4 13
 
6.7%
7 11
 
5.7%
5 10
 
5.2%
8 8
 
4.1%
6 7
 
3.6%
Other values (4) 15
 
7.8%
Hangul
ValueCountFrequency (%)
로 48
27.1%
종 19
 
10.7%
길 10
 
5.6%
대 8
 
4.5%
세 6
 
3.4%
창 5
 
2.8%
문 5
 
2.8%
율 5
 
2.8%
곡 5
 
2.8%
정 4
 
2.3%
Other values (32) 62
35.0%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.575105
Minimum37.5264
Maximum37.605688
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T09:33:21.804549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.5264
5-th percentile37.569866
Q137.570425
median37.57417
Q337.57613
95-th percentile37.599861
Maximum37.605688
Range0.079288
Interquartile range (IQR)0.005705

Descriptive statistics

Standard deviation0.010709804
Coefficient of variation (CV)0.00028502392
Kurtosis9.4277811
Mean37.575105
Median Absolute Deviation (MAD)0.002912
Skewness-0.66230234
Sum1991.4806
Variance0.00011469989
MonotonicityNot monotonic
2023-12-12T09:33:21.923613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5759 1
 
1.9%
37.575359 1
 
1.9%
37.569841 1
 
1.9%
37.579079 1
 
1.9%
37.57061 1
 
1.9%
37.570327 1
 
1.9%
37.570404 1
 
1.9%
37.570149 1
 
1.9%
37.576584 1
 
1.9%
37.573411 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
37.5264 1
1.9%
37.566109 1
1.9%
37.569841 1
1.9%
37.569882 1
1.9%
37.57 1
1.9%
37.570115 1
1.9%
37.570149 1
1.9%
37.570327 1
1.9%
37.57033 1
1.9%
37.570334 1
1.9%
ValueCountFrequency (%)
37.605688 1
1.9%
37.60007 1
1.9%
37.600036 1
1.9%
37.599745 1
1.9%
37.585957 1
1.9%
37.583932 1
1.9%
37.582822 1
1.9%
37.581321 1
1.9%
37.579079 1
1.9%
37.576804 1
1.9%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.98814
Minimum126.95785
Maximum127.02315
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T09:33:22.076566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.95785
5-th percentile126.95814
Q1126.97365
median126.98536
Q3127.00239
95-th percentile127.01728
Maximum127.02315
Range0.0653
Interquartile range (IQR)0.02874

Descriptive statistics

Standard deviation0.018841162
Coefficient of variation (CV)0.00014836947
Kurtosis-1.0006037
Mean126.98814
Median Absolute Deviation (MAD)0.015949
Skewness0.1105636
Sum6730.3712
Variance0.00035498938
MonotonicityNot monotonic
2023-12-12T09:33:22.204551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.969115 1
 
1.9%
126.982801 1
 
1.9%
126.962984 1
 
1.9%
126.985364 1
 
1.9%
126.991897 1
 
1.9%
126.992175 1
 
1.9%
126.989494 1
 
1.9%
126.989572 1
 
1.9%
126.986126 1
 
1.9%
126.997711 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
126.957854 1
1.9%
126.95799 1
1.9%
126.958118 1
1.9%
126.95815 1
1.9%
126.960285 1
1.9%
126.961704 1
1.9%
126.962984 1
1.9%
126.966626 1
1.9%
126.967069 1
1.9%
126.969115 1
1.9%
ValueCountFrequency (%)
127.023154 1
1.9%
127.023139 1
1.9%
127.019204 1
1.9%
127.016003 1
1.9%
127.015732 1
1.9%
127.01546 1
1.9%
127.012075 1
1.9%
127.009037 1
1.9%
127.008959 1
1.9%
127.007767 1
1.9%

규모(높이_지름)
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Memory size556.0 B
3.5M*5M
20 
3.3M*4M
13 
3M*3M
11 
3M*4.6M
3 
3.5M*3M
 
2
Other values (3)
4 

Length

Max length9
Median length7
Mean length6.6226415
Min length5

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row3.5M*5M
2nd row3.5M*5M
3rd row3.3M*4M
4th row3M*3M
5th row3.3M*4M

Common Values

ValueCountFrequency (%)
3.5M*5M 20
37.7%
3.3M*4M 13
24.5%
3M*3M 11
20.8%
3M*4.6M 3
 
5.7%
3.5M*3M 2
 
3.8%
3M*4.8M 2
 
3.8%
3M*3.5M 1
 
1.9%
2.3M*3.4M 1
 
1.9%

Length

2023-12-12T09:33:22.321832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:33:22.423390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3.5m*5m 20
37.7%
3.3m*4m 13
24.5%
3m*3m 11
20.8%
3m*4.6m 3
 
5.7%
3.5m*3m 2
 
3.8%
3m*4.8m 2
 
3.8%
3m*3.5m 1
 
1.9%
2.3m*3.4m 1
 
1.9%

원단
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
메쉬
47 
아크릴
6 

Length

Max length3
Median length2
Mean length2.1132075
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
메쉬 47
88.7%
아크릴 6
 
11.3%

Length

2023-12-12T09:33:22.526880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:33:22.602845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
메쉬 47
88.7%
아크릴 6
 
11.3%

설치년월
Date

Distinct7
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2018-06-01 00:00:00
Maximum2023-07-01 00:00:00
2023-12-12T09:33:22.672465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:22.754739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

담당부서
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
서울특별시 종로구 안전도시과
53 

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 종로구 안전도시과
2nd row서울특별시 종로구 안전도시과
3rd row서울특별시 종로구 안전도시과
4th row서울특별시 종로구 안전도시과
5th row서울특별시 종로구 안전도시과

Common Values

ValueCountFrequency (%)
서울특별시 종로구 안전도시과 53
100.0%

Length

2023-12-12T09:33:22.859052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:33:22.931236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 53
33.3%
종로구 53
33.3%
안전도시과 53
33.3%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
Minimum2023-09-21 00:00:00
Maximum2023-09-21 00:00:00
2023-12-12T09:33:22.992089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:23.066815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T09:33:18.660795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:18.107146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:18.381846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:18.733058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:18.179918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:18.466793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:18.853024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:18.274289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:33:18.549855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:33:23.131912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관리번호행정동설치장소도로명주소위도경도규모(높이_지름)원단설치년월
연번1.0001.0000.7501.0001.0000.6240.7650.4410.7390.795
관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
행정동0.7501.0001.0001.0001.0000.8950.9120.0000.0000.000
설치장소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도0.6241.0000.8951.0001.0001.0000.5980.0000.0000.000
경도0.7651.0000.9121.0001.0000.5981.0000.1040.2300.240
규모(높이_지름)0.4411.0000.0001.0001.0000.0000.1041.0000.9960.796
원단0.7391.0000.0001.0001.0000.0000.2300.9961.0000.818
설치년월0.7951.0000.0001.0001.0000.0000.2400.7960.8181.000
2023-12-12T09:33:23.238431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동규모(높이_지름)원단
행정동1.0000.0000.000
규모(높이_지름)0.0001.0000.887
원단0.0000.8871.000
2023-12-12T09:33:23.314008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도행정동규모(높이_지름)원단
연번1.000-0.3360.2380.3930.2050.524
위도-0.3361.000-0.0420.6300.0000.000
경도0.238-0.0421.0000.6140.0000.152
행정동0.3930.6300.6141.0000.0000.000
규모(높이_지름)0.2050.0000.0000.0001.0000.887
원단0.5240.0000.1520.0000.8871.000

Missing values

2023-12-12T09:33:18.993196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:33:19.183073image/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

연번관리번호행정동설치장소도로명주소위도경도규모(높이_지름)원단설치년월담당부서데이터기준일
011(사직동-1)사직동사직동주민센터 앞 교통섬사직로9길 537.5759126.9691153.5M*5M메쉬2018-06-01서울특별시 종로구 안전도시과2023-09-21
122(사직동-2)사직동경복궁역 1번출구 교통섬자하문로 137.576067126.972523.5M*5M메쉬2018-06-01서울특별시 종로구 안전도시과2023-09-21
233(삼청동-1)삼청동안국빌딩 앞 교통섬율곡로 3337.575717126.9830963.3M*4M메쉬2018-06-01서울특별시 종로구 안전도시과2023-09-21
344(삼청동-2)삼청동동십자각 사거리 교통섬율곡로 137.575975126.9795593M*3M메쉬2018-06-01서울특별시 종로구 안전도시과2023-09-21
455(부암동-1)부암동상명대 입구 교차로 분수대 방면 교통섬세검정로 22037.599745126.9581183.3M*4M메쉬2018-06-01서울특별시 종로구 안전도시과2023-09-21
566(평창동-1)평창동세검정새마을금고 본점 앞 횡단보도평창11길 637.605688126.9670693M*3M메쉬2018-06-01서울특별시 종로구 안전도시과2023-09-21
677(무악동-1)무악동독립문역 2번 출구 앞 횡단보도통일로 25037.574542126.957993M*3M메쉬2018-06-01서울특별시 종로구 안전도시과2023-09-21
788(교남동-1)교남동독립문사거리 행촌동 방면 교통섬통일로 22037.5264126.9602853.3M*4M메쉬2018-06-01서울특별시 종로구 안전도시과2023-09-21
899(청운효자동-1)청운효자동청운효자동주민센터 앞자하문로 9237.583932126.9704073.5M*5M메쉬2018-06-01서울특별시 종로구 안전도시과2023-09-21
91010(이화동-1)이화동이화사거리 이화동주민센터대학로 6037.57624127.002393.3M*4M메쉬2018-06-01서울특별시 종로구 안전도시과2023-09-21
연번관리번호행정동설치장소도로명주소위도경도규모(높이_지름)원단설치년월담당부서데이터기준일
434444(숭인2동-4)숭인2동신설동역오거리 더플레이스위 홍보관 앞 교통섬종로 41237.575178127.0231543.5M*5M메쉬2020-06-01서울특별시 종로구 안전도시과2023-09-21
444545(종로14가동-11)종로14가동그랑서울 앞 횡단보도종로 33(청진동)37.570425126.9812073.5M*5M메쉬2020-08-01서울특별시 종로구 안전도시과2023-09-21
454646(종로14가동-17)종로14가동안국동사거리 동덕빌딩 앞 횡단보도우정국로 6837.57528126.983053M*4.6M아크릴2023-07-01서울특별시 종로구 안전도시과2023-09-21
464747(창신2동-2)창신2동둥대문역 3번 출구 앞 횡단보도종로 311(창신동)37.5721127.0120753.5M*3M메쉬2020-08-01서울특별시 종로구 안전도시과2023-09-21
474848(이화동-4)이화동율곡로19길 57율곡로19길 57(이화동)37.576804127.0075423.5M*3M아크릴2020-10-01서울특별시 종로구 안전도시과2023-09-21
484949(종로14가동-12)종로14가동영풍문고 앞 교통섬청계천로 4137.57126.982763.3M*4M메쉬2022-10-01서울특별시 종로구 안전도시과2023-09-21
495050(종로14가동-13)종로14가동종로타워 앞 교통섬종로 5137.57039126.983223.5M*5M메쉬2022-10-01서울특별시 종로구 안전도시과2023-09-21
505151(종로(14가동-14)종로14가동대한민국역사박물관 앞세종대로 19837.57417126.977383M*4.8M아크릴2022-10-01서울특별시 종로구 안전도시과2023-09-21
515252(종로14가동-15)종로14가동KT광화문WEST 앞세종대로 17837.57256126.977433M*4.8M아크릴2022-10-01서울특별시 종로구 안전도시과2023-09-21
525353(사직동-5)사직동새문안교회 앞 횡단보도새문안로 7937.57033126.973653M*4.6M아크릴2023-07-01서울특별시 종로구 안전도시과2023-09-21