Overview

Dataset statistics

Number of variables12
Number of observations61
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory101.2 B

Variable types

Categorical4
Text4
Numeric3
Boolean1

Dataset

Description파일 다운로드
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-13279/F/1/datasetView.do

Alerts

관리기관명 has constant value ""Constant
관할경찰서명 has constant value ""Constant
CCTV설치여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
대상시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 04:13:37.285293
Analysis finished2023-12-11 04:13:39.167347
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설종류
Categorical

Distinct4
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size620.0 B
유치원
22 
초등학교
21 
어린이집
17 
특수학교
 
1

Length

Max length4
Median length4
Mean length3.6393443
Min length3

Unique

Unique1 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
유치원 22
36.1%
초등학교 21
34.4%
어린이집 17
27.9%
특수학교 1
 
1.6%

Length

2023-12-11T13:13:39.243558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:13:39.366166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유치원 22
36.1%
초등학교 21
34.4%
어린이집 17
27.9%
특수학교 1
 
1.6%

대상시설명
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2023-12-11T13:13:39.667067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length6.1967213
Min length5

Characters and Unicode

Total characters378
Distinct characters89
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)100.0%

Sample

1st row신상도초등학교
2nd row강남초등학교
3rd row남사초등학교
4th row남성초등학교
5th row노량진초등학교
ValueCountFrequency (%)
은로초등학교 2
 
3.2%
병설유치원 2
 
3.2%
신상도초등학교 1
 
1.6%
강남유치원 1
 
1.6%
상도유치원 1
 
1.6%
성모유치원 1
 
1.6%
행복유치원 1
 
1.6%
신남성초교 1
 
1.6%
샛별유치원 1
 
1.6%
하랑숲유치원 1
 
1.6%
Other values (51) 51
81.0%
2023-12-11T13:13:40.189251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 24
 
6.3%
초 23
 
6.1%
학 23
 
6.1%
원 22
 
5.8%
등 22
 
5.8%
유 22
 
5.8%
치 22
 
5.8%
린 17
 
4.5%
어 17
 
4.5%
집 17
 
4.5%
Other values (79) 169
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 375
99.2%
Space Separator 2
 
0.5%
Decimal Number 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 24
 
6.4%
초 23
 
6.1%
학 23
 
6.1%
원 22
 
5.9%
등 22
 
5.9%
유 22
 
5.9%
치 22
 
5.9%
린 17
 
4.5%
어 17
 
4.5%
집 17
 
4.5%
Other values (77) 166
44.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 375
99.2%
Common 3
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 24
 
6.4%
초 23
 
6.1%
학 23
 
6.1%
원 22
 
5.9%
등 22
 
5.9%
유 22
 
5.9%
치 22
 
5.9%
린 17
 
4.5%
어 17
 
4.5%
집 17
 
4.5%
Other values (77) 166
44.3%
Common
ValueCountFrequency (%)
2
66.7%
4 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 375
99.2%
ASCII 3
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 24
 
6.4%
초 23
 
6.1%
학 23
 
6.1%
원 22
 
5.9%
등 22
 
5.9%
유 22
 
5.9%
치 22
 
5.9%
린 17
 
4.5%
어 17
 
4.5%
집 17
 
4.5%
Other values (77) 166
44.3%
ASCII
ValueCountFrequency (%)
2
66.7%
4 1
33.3%

소재지도로명주소
Text

Distinct58
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size620.0 B
2023-12-11T13:13:40.595607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length19.081967
Min length15

Characters and Unicode

Total characters1164
Distinct characters64
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

Unique55 ?
Unique (%)90.2%

Sample

1st row서울특별시 동작구 장승배기로 14
2nd row서울특별시 동작구 강남초등길 15
3rd row서울특별시 동작구 동작대로13길 22
4th row서울특별시 동작구 사당로23길 57-14
5th row서울특별시 동작구 장승배기로 160
ValueCountFrequency (%)
서울특별시 61
25.1%
동작구 61
25.1%
15 4
 
1.6%
서달로 3
 
1.2%
28 3
 
1.2%
27 3
 
1.2%
22 2
 
0.8%
동작대로17길 2
 
0.8%
여의대방로36길 2
 
0.8%
16 2
 
0.8%
Other values (90) 100
41.2%
2023-12-11T13:13:41.237163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
182
15.6%
동 67
 
5.8%
작 66
 
5.7%
서 64
 
5.5%
시 62
 
5.3%
구 61
 
5.2%
울 61
 
5.2%
별 61
 
5.2%
특 61
 
5.2%
로 56
 
4.8%
Other values (54) 423
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 755
64.9%
Decimal Number 218
 
18.7%
Space Separator 182
 
15.6%
Dash Punctuation 9
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 67
8.9%
작 66
8.7%
서 64
8.5%
시 62
8.2%
구 61
8.1%
울 61
8.1%
별 61
8.1%
특 61
8.1%
로 56
 
7.4%
길 45
 
6.0%
Other values (42) 151
20.0%
Decimal Number
ValueCountFrequency (%)
1 48
22.0%
2 37
17.0%
3 26
11.9%
4 25
11.5%
6 24
11.0%
5 16
 
7.3%
7 14
 
6.4%
0 12
 
5.5%
8 9
 
4.1%
9 7
 
3.2%
Space Separator
ValueCountFrequency (%)
182
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 755
64.9%
Common 409
35.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 67
8.9%
작 66
8.7%
서 64
8.5%
시 62
8.2%
구 61
8.1%
울 61
8.1%
별 61
8.1%
특 61
8.1%
로 56
 
7.4%
길 45
 
6.0%
Other values (42) 151
20.0%
Common
ValueCountFrequency (%)
182
44.5%
1 48
 
11.7%
2 37
 
9.0%
3 26
 
6.4%
4 25
 
6.1%
6 24
 
5.9%
5 16
 
3.9%
7 14
 
3.4%
0 12
 
2.9%
8 9
 
2.2%
Other values (2) 16
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 755
64.9%
ASCII 409
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
182
44.5%
1 48
 
11.7%
2 37
 
9.0%
3 26
 
6.4%
4 25
 
6.1%
6 24
 
5.9%
5 16
 
3.9%
7 14
 
3.4%
0 12
 
2.9%
8 9
 
2.2%
Other values (2) 16
 
3.9%
Hangul
ValueCountFrequency (%)
동 67
8.9%
작 66
8.7%
서 64
8.5%
시 62
8.2%
구 61
8.1%
울 61
8.1%
별 61
8.1%
특 61
8.1%
로 56
 
7.4%
길 45
 
6.0%
Other values (42) 151
20.0%

소재지지번주소
Text

Distinct54
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size620.0 B
2023-12-11T13:13:41.595786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length19.590164
Min length16

Characters and Unicode

Total characters1195
Distinct characters34
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

Unique47 ?
Unique (%)77.0%

Sample

1st row서울특별시 동작구 상도2동 산65
2nd row서울특별시 동작구 상도1동 501
3rd row서울특별시 동작구 사당1동 1011-1
4th row서울특별시 동작구 사당3동 산24
5th row서울특별시 동작구 노량진1동 238
ValueCountFrequency (%)
서울특별시 61
25.2%
동작구 61
25.2%
대방동 7
 
2.9%
상도4동 6
 
2.5%
상도동 5
 
2.1%
흑석1동 4
 
1.7%
상도1동 4
 
1.7%
사당5동 4
 
1.7%
사당1동 4
 
1.7%
신대방1동 4
 
1.7%
Other values (64) 82
33.9%
2023-12-11T13:13:42.144487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
181
15.1%
동 124
 
10.4%
1 79
 
6.6%
작 63
 
5.3%
울 61
 
5.1%
구 61
 
5.1%
서 61
 
5.1%
시 61
 
5.1%
별 61
 
5.1%
특 61
 
5.1%
Other values (24) 382
32.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 684
57.2%
Decimal Number 286
23.9%
Space Separator 181
 
15.1%
Dash Punctuation 44
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 124
18.1%
작 63
9.2%
울 61
8.9%
구 61
8.9%
서 61
8.9%
시 61
8.9%
별 61
8.9%
특 61
8.9%
도 21
 
3.1%
상 21
 
3.1%
Other values (12) 89
13.0%
Decimal Number
ValueCountFrequency (%)
1 79
27.6%
2 41
14.3%
4 36
12.6%
3 35
12.2%
5 24
 
8.4%
0 21
 
7.3%
6 20
 
7.0%
8 13
 
4.5%
7 12
 
4.2%
9 5
 
1.7%
Space Separator
ValueCountFrequency (%)
181
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 684
57.2%
Common 511
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 124
18.1%
작 63
9.2%
울 61
8.9%
구 61
8.9%
서 61
8.9%
시 61
8.9%
별 61
8.9%
특 61
8.9%
도 21
 
3.1%
상 21
 
3.1%
Other values (12) 89
13.0%
Common
ValueCountFrequency (%)
181
35.4%
1 79
15.5%
- 44
 
8.6%
2 41
 
8.0%
4 36
 
7.0%
3 35
 
6.8%
5 24
 
4.7%
0 21
 
4.1%
6 20
 
3.9%
8 13
 
2.5%
Other values (2) 17
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 684
57.2%
ASCII 511
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
181
35.4%
1 79
15.5%
- 44
 
8.6%
2 41
 
8.0%
4 36
 
7.0%
3 35
 
6.8%
5 24
 
4.7%
0 21
 
4.1%
6 20
 
3.9%
8 13
 
2.5%
Other values (2) 17
 
3.3%
Hangul
ValueCountFrequency (%)
동 124
18.1%
작 63
9.2%
울 61
8.9%
구 61
8.9%
서 61
8.9%
시 61
8.9%
별 61
8.9%
특 61
8.9%
도 21
 
3.1%
상 21
 
3.1%
Other values (12) 89
13.0%

위도
Real number (ℝ)

Distinct58
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.497979
Minimum37.480666
Maximum37.511751
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2023-12-11T13:13:42.338363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.480666
5-th percentile37.481944
Q137.489154
median37.498639
Q337.50616
95-th percentile37.510078
Maximum37.511751
Range0.031085192
Interquartile range (IQR)0.017005466

Descriptive statistics

Standard deviation0.0093471723
Coefficient of variation (CV)0.00024927137
Kurtosis-0.97430316
Mean37.497979
Median Absolute Deviation (MAD)0.0078511
Skewness-0.3971351
Sum2287.3767
Variance8.7369631 × 10-5
MonotonicityNot monotonic
2023-12-11T13:13:42.514539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5031946 2
 
3.3%
37.4977312 2
 
3.3%
37.4881508283 2
 
3.3%
37.5003463076 1
 
1.6%
37.5034948815 1
 
1.6%
37.5014486247 1
 
1.6%
37.5015874213 1
 
1.6%
37.4956159 1
 
1.6%
37.49804586 1
 
1.6%
37.4960102 1
 
1.6%
Other values (48) 48
78.7%
ValueCountFrequency (%)
37.480666 1
1.6%
37.4808094523 1
1.6%
37.4816149 1
1.6%
37.4819442959 1
1.6%
37.4822117285 1
1.6%
37.4828055257 1
1.6%
37.4830193742 1
1.6%
37.4830324 1
1.6%
37.4845963277 1
1.6%
37.4851433 1
1.6%
ValueCountFrequency (%)
37.5117511917 1
1.6%
37.5112971535 1
1.6%
37.5103052507 1
1.6%
37.5100779624 1
1.6%
37.5099261605 1
1.6%
37.5093769155 1
1.6%
37.5093408058 1
1.6%
37.5089258 1
1.6%
37.50890703 1
1.6%
37.5088523446 1
1.6%

경도
Real number (ℝ)

Distinct58
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.94965
Minimum126.90737
Maximum126.98179
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2023-12-11T13:13:42.708921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.90737
5-th percentile126.91615
Q1126.93602
median126.94954
Q3126.96511
95-th percentile126.97875
Maximum126.98179
Range0.074414
Interquartile range (IQR)0.0290924

Descriptive statistics

Standard deviation0.019342144
Coefficient of variation (CV)0.00015236075
Kurtosis-0.76142886
Mean126.94965
Median Absolute Deviation (MAD)0.015327544
Skewness-0.13352863
Sum7743.9286
Variance0.00037411853
MonotonicityNot monotonic
2023-12-11T13:13:43.230027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9600007836 2
 
3.3%
126.9332022025 2
 
3.3%
126.9648708672 2
 
3.3%
126.944617497 1
 
1.6%
126.9496786 1
 
1.6%
126.9516555161 1
 
1.6%
126.9399433 1
 
1.6%
126.941139 1
 
1.6%
126.9502826 1
 
1.6%
126.9817887 1
 
1.6%
Other values (48) 48
78.7%
ValueCountFrequency (%)
126.9073747 1
1.6%
126.9116916 1
1.6%
126.9148425 1
1.6%
126.9161464285 1
1.6%
126.9211621 1
1.6%
126.9229536 1
1.6%
126.9248852651 1
1.6%
126.9262918534 1
1.6%
126.9263253 1
1.6%
126.929207 1
1.6%
ValueCountFrequency (%)
126.9817887 1
1.6%
126.9806795 1
1.6%
126.9793688 1
1.6%
126.9787548 1
1.6%
126.9782332263 1
1.6%
126.9775138913 1
1.6%
126.9765108674 1
1.6%
126.9754872048 1
1.6%
126.975172 1
1.6%
126.973077 1
1.6%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size620.0 B
서울특별시 동작구청
61 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 동작구청 61
100.0%

Length

2023-12-11T13:13:43.384625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:13:43.477184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 61
50.0%
동작구청 61
50.0%

관할경찰서명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size620.0 B
동작경찰서
61 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동작경찰서 61
100.0%

Length

2023-12-11T13:13:43.580853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:13:43.681840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동작경찰서 61
100.0%

CCTV설치여부
Boolean

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size193.0 B
True
61 
ValueCountFrequency (%)
True 61
100.0%
2023-12-11T13:13:43.769269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

CCTV설치대수
Real number (ℝ)

Distinct6
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6885246
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2023-12-11T13:13:43.874687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum6
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1767325
Coefficient of variation (CV)0.69689985
Kurtosis3.3085722
Mean1.6885246
Median Absolute Deviation (MAD)0
Skewness1.9086041
Sum103
Variance1.3846995
MonotonicityNot monotonic
2023-12-11T13:13:43.990741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 40
65.6%
2 9
 
14.8%
3 7
 
11.5%
4 2
 
3.3%
5 2
 
3.3%
6 1
 
1.6%
ValueCountFrequency (%)
1 40
65.6%
2 9
 
14.8%
3 7
 
11.5%
4 2
 
3.3%
5 2
 
3.3%
6 1
 
1.6%
ValueCountFrequency (%)
6 1
 
1.6%
5 2
 
3.3%
4 2
 
3.3%
3 7
 
11.5%
2 9
 
14.8%
1 40
65.6%

보호구역도로폭
Text

Distinct39
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Memory size620.0 B
2023-12-11T13:13:44.179517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3
Min length1

Characters and Unicode

Total characters183
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

Unique24 ?
Unique (%)39.3%

Sample

1st row4~17
2nd row4~10
3rd row3~6
4th row4~15
5th row4~24
ValueCountFrequency (%)
6~7 4
 
6.6%
7~9 3
 
4.9%
4~24 3
 
4.9%
6 3
 
4.9%
5~8 3
 
4.9%
3~6 3
 
4.9%
4~5 2
 
3.3%
4~7 2
 
3.3%
13 2
 
3.3%
5~11 2
 
3.3%
Other values (29) 34
55.7%
2023-12-11T13:13:44.540303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
~ 45
24.6%
1 29
15.8%
4 18
 
9.8%
7 17
 
9.3%
5 17
 
9.3%
6 13
 
7.1%
2 13
 
7.1%
3 12
 
6.6%
8 10
 
5.5%
9 6
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 138
75.4%
Math Symbol 45
 
24.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 29
21.0%
4 18
13.0%
7 17
12.3%
5 17
12.3%
6 13
9.4%
2 13
9.4%
3 12
8.7%
8 10
 
7.2%
9 6
 
4.3%
0 3
 
2.2%
Math Symbol
ValueCountFrequency (%)
~ 45
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 183
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
~ 45
24.6%
1 29
15.8%
4 18
 
9.8%
7 17
 
9.3%
5 17
 
9.3%
6 13
 
7.1%
2 13
 
7.1%
3 12
 
6.6%
8 10
 
5.5%
9 6
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 183
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
~ 45
24.6%
1 29
15.8%
4 18
 
9.8%
7 17
 
9.3%
5 17
 
9.3%
6 13
 
7.1%
2 13
 
7.1%
3 12
 
6.6%
8 10
 
5.5%
9 6
 
3.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size620.0 B
2020-02-06
61 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-02-06
2nd row2020-02-06
3rd row2020-02-06
4th row2020-02-06
5th row2020-02-06

Common Values

ValueCountFrequency (%)
2020-02-06 61
100.0%

Length

2023-12-11T13:13:44.685474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:13:44.781943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-02-06 61
100.0%

Interactions

2023-12-11T13:13:38.560092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:13:37.839500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:13:38.241088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:13:38.655537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:13:37.979687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:13:38.346230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:13:38.767158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:13:38.143600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:13:38.451927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T13:13:44.862552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류대상시설명소재지도로명주소소재지지번주소위도경도CCTV설치대수보호구역도로폭
시설종류1.0001.0000.7800.0000.0000.3340.6470.725
대상시설명1.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소0.7801.0001.0001.0001.0001.0000.9371.000
소재지지번주소0.0001.0001.0001.0000.9990.9900.9560.999
위도0.0001.0001.0000.9991.0000.5230.0000.813
경도0.3341.0001.0000.9900.5231.0000.1810.842
CCTV설치대수0.6471.0000.9370.9560.0000.1811.0000.914
보호구역도로폭0.7251.0001.0000.9990.8130.8420.9141.000
2023-12-11T13:13:44.975698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도CCTV설치대수시설종류
위도1.000-0.4000.1840.000
경도-0.4001.0000.0770.188
CCTV설치대수0.1840.0771.0000.467
시설종류0.0000.1880.4671.000

Missing values

2023-12-11T13:13:38.894382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T13:13:39.086206image/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

시설종류대상시설명소재지도로명주소소재지지번주소위도경도관리기관명관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭데이터기준일자
0초등학교신상도초등학교서울특별시 동작구 장승배기로 14서울특별시 동작구 상도2동 산6537.500346126.944617서울특별시 동작구청동작경찰서Y44~172020-02-06
1초등학교강남초등학교서울특별시 동작구 강남초등길 15서울특별시 동작구 상도1동 50137.50616126.953358서울특별시 동작구청동작경찰서Y54~102020-02-06
2초등학교남사초등학교서울특별시 동작구 동작대로13길 22서울특별시 동작구 사당1동 1011-137.481944126.978233서울특별시 동작구청동작경찰서Y23~62020-02-06
3초등학교남성초등학교서울특별시 동작구 사당로23길 57-14서울특별시 동작구 사당3동 산2437.484596126.975487서울특별시 동작구청동작경찰서Y34~152020-02-06
4초등학교노량진초등학교서울특별시 동작구 장승배기로 160서울특별시 동작구 노량진1동 23837.511751126.940822서울특별시 동작구청동작경찰서Y44~242020-02-06
5초등학교대림초등학교서울특별시 동작구 대방동1길 22서울특별시 동작구 대방동391-6237.500613126.924885서울특별시 동작구청동작경찰서Y14~242020-02-06
6초등학교동작초등학교서울특별시 동작구 동작대로29길 214서울특별시 동작구 동작동 산9-137.494115126.976511서울특별시 동작구청동작경찰서Y33~112020-02-06
7초등학교문창초등학교서울특별시 동작구 신대방2길 14서울특별시 동작구 신대방1동 64037.488983126.914843서울특별시 동작구청동작경찰서Y24~52020-02-06
8초등학교보라매초등학교서울특별시 동작구 여의대방로16길 30서울특별시 동작구 신대방1동 485-137.495853126.916146서울특별시 동작구청동작경찰서Y25~122020-02-06
9초등학교본동초등학교서울특별시 동작구 노량진로26길 16-40서울특별시 동작구 본동 13337.509926126.953853서울특별시 동작구청동작경찰서Y24~92020-02-06
시설종류대상시설명소재지도로명주소소재지지번주소위도경도관리기관명관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭데이터기준일자
51어린이집다문화어린이집서울특별시 동작구 동작대로17길 28서울특별시 동작구 사당1동 1011-137.483032126.978755서울특별시 동작구청동작경찰서Y13~62020-02-06
52어린이집노벨어린이집서울특별시 동작구 양녕로 26길 27서울특별시 동작구 상도4동 211-137.497391126.944258서울특별시 동작구청동작경찰서Y17~92020-02-06
53어린이집무지개어린이집서울특별시 동작구 성대로6가길 29서울특별시 동작구 상도3동 256-17537.497731126.933202서울특별시 동작구청동작경찰서Y15~82020-02-06
54어린이집영재어린이집서울특별시 동작구 여의대방로36길 105서울특별시 동작구 대방동 44-337.508852126.931851서울특별시 동작구청동작경찰서Y112~182020-02-06
55어린이집문화어린이집서울특별시 동작구 사당로13길 24서울특별시 동작구 사당동 1131-437.485143126.972412서울특별시 동작구청동작경찰서Y15~82020-02-06
56어린이집큰별어린이집서울특별시 동작구 흑석한강로 28서울특별시 동작구 흑석동 336-137.504636126.965112서울특별시 동작구청동작경찰서Y121~232020-02-06
57어린이집성대어린이집서울특별시 동작구 성대로10길 27서울특별시 동작구 상도동 27137.49682126.935311서울특별시 동작구청동작경찰서Y14~72020-02-06
58특수학교삼성특수학교서울특별시 동작구 양녕로30길 19-4서울특별시 동작구 상도4동 212-12837.498956126.946161서울특별시 동작구청동작경찰서Y17~202020-02-06
59유치원행복한숲유치원서울특별시 동작구 만양로26서울특별시 동작구 상도동41437.507632126.949543서울특별시 동작구청동작경찰서Y16~72020-02-06
60어린이집사당4동어린이집서울특별시 동작구 사당로22나길 70서울특별시 동작구 사당동316-5637.480666126.973077서울특별시 동작구청동작경찰서Y16~72020-02-06