Overview

Dataset statistics

Number of variables12
Number of observations101
Missing cells103
Missing cells (%)8.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.1 KiB
Average record size in memory102.3 B

Variable types

Categorical3
Text2
Unsupported1
Numeric4
Boolean1
DateTime1

Dataset

Description파일 다운로드
Author강남구
URLhttps://data.seoul.go.kr/dataList/OA-15013/S/1/datasetView.do

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
CCTV설치대수 is highly overall correlated with CCTV설치여부High correlation
관할경찰서명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
CCTV설치여부 is highly overall correlated with CCTV설치대수High correlation
CCTV설치여부 is highly imbalanced (86.0%)Imbalance
소재지지번주소 has 101 (100.0%) missing valuesMissing
대상시설명 has unique valuesUnique
소재지지번주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-11 09:05:55.108301
Analysis finished2023-12-11 09:05:57.563611
Duration2.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설종류
Categorical

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
어린이집
44 
초등학교
33 
유치원
21 
특수학교
 
3

Length

Max length4
Median length4
Mean length3.7920792
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
어린이집 44
43.6%
초등학교 33
32.7%
유치원 21
20.8%
특수학교 3
 
3.0%

Length

2023-12-11T18:05:57.622102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:05:57.734874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이집 44
43.6%
초등학교 33
32.7%
유치원 21
20.8%
특수학교 3
 
3.0%

대상시설명
Text

UNIQUE 

Distinct101
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
2023-12-11T18:05:57.961368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length6.3960396
Min length4

Characters and Unicode

Total characters646
Distinct characters131
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)100.0%

Sample

1st row돌샘유치원
2nd row신양유치원
3rd row이화유치원
4th row영동제일유치원
5th row소망유치원
ValueCountFrequency (%)
돌샘유치원 1
 
1.0%
율현초등학교 1
 
1.0%
구민회관어린이집 1
 
1.0%
강남구청어린이집 1
 
1.0%
튼튼영재어린이집 1
 
1.0%
청수어린이집 1
 
1.0%
성아어린이집 1
 
1.0%
선재어린이집 1
 
1.0%
킹스키즈어린이집 1
 
1.0%
한티어린이집 1
 
1.0%
Other values (91) 91
90.1%
2023-12-11T18:05:58.372261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 48
 
7.4%
어 44
 
6.8%
린 44
 
6.8%
집 44
 
6.8%
학 40
 
6.2%
교 39
 
6.0%
초 38
 
5.9%
등 37
 
5.7%
원 25
 
3.9%
치 23
 
3.6%
Other values (121) 264
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 641
99.2%
Uppercase Letter 3
 
0.5%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 48
 
7.5%
어 44
 
6.9%
린 44
 
6.9%
집 44
 
6.9%
학 40
 
6.2%
교 39
 
6.1%
초 38
 
5.9%
등 37
 
5.8%
원 25
 
3.9%
치 23
 
3.6%
Other values (116) 259
40.4%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
K 1
33.3%
G 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 641
99.2%
Latin 3
 
0.5%
Common 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 48
 
7.5%
어 44
 
6.9%
린 44
 
6.9%
집 44
 
6.9%
학 40
 
6.2%
교 39
 
6.1%
초 38
 
5.9%
등 37
 
5.8%
원 25
 
3.9%
치 23
 
3.6%
Other values (116) 259
40.4%
Latin
ValueCountFrequency (%)
L 1
33.3%
K 1
33.3%
G 1
33.3%
Common
ValueCountFrequency (%)
) 1
50.0%
( 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 641
99.2%
ASCII 5
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 48
 
7.5%
어 44
 
6.9%
린 44
 
6.9%
집 44
 
6.9%
학 40
 
6.2%
교 39
 
6.1%
초 38
 
5.9%
등 37
 
5.8%
원 25
 
3.9%
치 23
 
3.6%
Other values (116) 259
40.4%
ASCII
ValueCountFrequency (%)
L 1
20.0%
K 1
20.0%
G 1
20.0%
) 1
20.0%
( 1
20.0%

소재지도로명주소
Text

Distinct95
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Memory size940.0 B
2023-12-11T18:05:58.734428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length19.207921
Min length16

Characters and Unicode

Total characters1940
Distinct characters74
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

Unique89 ?
Unique (%)88.1%

Sample

1st row서울특별시 강남구 개포로 516
2nd row서울특별시 강남구 선릉로10길 18-6
3rd row서울특별시 강남구 개포로109길 9
4th row서울특별시 강남구 삼성로120길 28
5th row서울특별시 강남구 광평로56길 11
ValueCountFrequency (%)
서울특별시 101
24.7%
강남구 101
24.7%
개포로 6
 
1.5%
16 5
 
1.2%
9 5
 
1.2%
17 4
 
1.0%
자곡로 3
 
0.7%
선릉로 3
 
0.7%
학동로 3
 
0.7%
27 3
 
0.7%
Other values (135) 175
42.8%
2023-12-11T18:05:59.218274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
308
15.9%
남 107
 
5.5%
구 107
 
5.5%
강 105
 
5.4%
서 101
 
5.2%
특 101
 
5.2%
별 101
 
5.2%
시 101
 
5.2%
울 101
 
5.2%
로 101
 
5.2%
Other values (64) 707
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1238
63.8%
Decimal Number 384
 
19.8%
Space Separator 308
 
15.9%
Dash Punctuation 8
 
0.4%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 107
8.6%
구 107
8.6%
강 105
8.5%
서 101
8.2%
특 101
8.2%
별 101
8.2%
시 101
8.2%
울 101
8.2%
로 101
8.2%
길 77
 
6.2%
Other values (51) 236
19.1%
Decimal Number
ValueCountFrequency (%)
1 79
20.6%
2 56
14.6%
3 41
10.7%
6 40
10.4%
5 35
9.1%
4 34
8.9%
7 30
 
7.8%
8 25
 
6.5%
9 22
 
5.7%
0 22
 
5.7%
Space Separator
ValueCountFrequency (%)
308
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1238
63.8%
Common 702
36.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 107
8.6%
구 107
8.6%
강 105
8.5%
서 101
8.2%
특 101
8.2%
별 101
8.2%
시 101
8.2%
울 101
8.2%
로 101
8.2%
길 77
 
6.2%
Other values (51) 236
19.1%
Common
ValueCountFrequency (%)
308
43.9%
1 79
 
11.3%
2 56
 
8.0%
3 41
 
5.8%
6 40
 
5.7%
5 35
 
5.0%
4 34
 
4.8%
7 30
 
4.3%
8 25
 
3.6%
9 22
 
3.1%
Other values (3) 32
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1238
63.8%
ASCII 702
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
308
43.9%
1 79
 
11.3%
2 56
 
8.0%
3 41
 
5.8%
6 40
 
5.7%
5 35
 
5.0%
4 34
 
4.8%
7 30
 
4.3%
8 25
 
3.6%
9 22
 
3.1%
Other values (3) 32
 
4.6%
Hangul
ValueCountFrequency (%)
남 107
8.6%
구 107
8.6%
강 105
8.5%
서 101
8.2%
특 101
8.2%
별 101
8.2%
시 101
8.2%
울 101
8.2%
로 101
8.2%
길 77
 
6.2%
Other values (51) 236
19.1%

소재지지번주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing101
Missing (%)100.0%
Memory size1.0 KiB

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.497837
Minimum37.464621
Maximum37.531739
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-11T18:05:59.398682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.464621
5-th percentile37.473522
Q137.486214
median37.494712
Q337.511503
95-th percentile37.525305
Maximum37.531739
Range0.06711766
Interquartile range (IQR)0.0252893

Descriptive statistics

Standard deviation0.016762898
Coefficient of variation (CV)0.00044703639
Kurtosis-0.81811436
Mean37.497837
Median Absolute Deviation (MAD)0.01149091
Skewness0.24324101
Sum3787.2815
Variance0.00028099474
MonotonicityNot monotonic
2023-12-11T18:05:59.575367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.49316115 2
 
2.0%
37.48680544 2
 
2.0%
37.495751 2
 
2.0%
37.52212074 2
 
2.0%
37.49115058 2
 
2.0%
37.50372276 2
 
2.0%
37.493887 1
 
1.0%
37.51796636 1
 
1.0%
37.52244507 1
 
1.0%
37.525052 1
 
1.0%
Other values (85) 85
84.2%
ValueCountFrequency (%)
37.46462136 1
1.0%
37.46682003 1
1.0%
37.468857 1
1.0%
37.4699202 1
1.0%
37.472191 1
1.0%
37.47352236 1
1.0%
37.47356078 1
1.0%
37.474559 1
1.0%
37.47529287 1
1.0%
37.475915 1
1.0%
ValueCountFrequency (%)
37.53173902 1
1.0%
37.53153399 1
1.0%
37.52934822 1
1.0%
37.52828178 1
1.0%
37.52627314 1
1.0%
37.525305 1
1.0%
37.525052 1
1.0%
37.523923 1
1.0%
37.5233613 1
1.0%
37.52262415 1
1.0%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.06137
Minimum127.02399
Maximum127.11161
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-11T18:05:59.752439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.02399
5-th percentile127.03084
Q1127.04515
median127.05636
Q3127.07773
95-th percentile127.10155
Maximum127.11161
Range0.0876195
Interquartile range (IQR)0.0325806

Descriptive statistics

Standard deviation0.022272898
Coefficient of variation (CV)0.00017529244
Kurtosis-0.63320553
Mean127.06137
Median Absolute Deviation (MAD)0.0162425
Skewness0.50528805
Sum12833.199
Variance0.00049608198
MonotonicityNot monotonic
2023-12-11T18:05:59.933844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.032603 2
 
2.0%
127.0699766 2
 
2.0%
127.075096 2
 
2.0%
127.0401134 2
 
2.0%
127.101549 2
 
2.0%
127.063564 2
 
2.0%
127.0642704 1
 
1.0%
127.0470611 1
 
1.0%
127.0576206 1
 
1.0%
127.049284 1
 
1.0%
Other values (85) 85
84.2%
ValueCountFrequency (%)
127.0239915 1
1.0%
127.0262217 1
1.0%
127.026898 1
1.0%
127.0285346 1
1.0%
127.0292754 1
1.0%
127.0308413 1
1.0%
127.0322635 1
1.0%
127.032603 2
2.0%
127.035354 1
1.0%
127.0356146 1
1.0%
ValueCountFrequency (%)
127.111611 1
1.0%
127.108267 1
1.0%
127.1056314 1
1.0%
127.1055895 1
1.0%
127.104503 1
1.0%
127.101549 2
2.0%
127.0998275 1
1.0%
127.0995995 1
1.0%
127.099054 1
1.0%
127.0981867 1
1.0%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
서울특별시 강남구청
101 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 강남구청 101
100.0%

Length

2023-12-11T18:06:00.075086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:06:00.205193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 101
50.0%
강남구청 101
50.0%

관할경찰서명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
수서경찰서
69 
강남경찰서
32 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수서경찰서
2nd row수서경찰서
3rd row수서경찰서
4th row강남경찰서
5th row수서경찰서

Common Values

ValueCountFrequency (%)
수서경찰서 69
68.3%
강남경찰서 32
31.7%

Length

2023-12-11T18:06:00.340976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:06:00.471709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수서경찰서 69
68.3%
강남경찰서 32
31.7%

CCTV설치여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size233.0 B
True
99 
False
 
2
ValueCountFrequency (%)
True 99
98.0%
False 2
 
2.0%
2023-12-11T18:06:00.581700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

CCTV설치대수
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)9.0%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean2.22
Minimum0
Maximum8
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-11T18:06:00.694306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile6.05
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.7441388
Coefficient of variation (CV)0.78564811
Kurtosis2.9584732
Mean2.22
Median Absolute Deviation (MAD)1
Skewness1.8108836
Sum222
Variance3.0420202
MonotonicityNot monotonic
2023-12-11T18:06:00.818569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 45
44.6%
2 27
26.7%
3 11
 
10.9%
4 5
 
5.0%
5 4
 
4.0%
8 3
 
3.0%
6 2
 
2.0%
7 2
 
2.0%
0 1
 
1.0%
(Missing) 1
 
1.0%
ValueCountFrequency (%)
0 1
 
1.0%
1 45
44.6%
2 27
26.7%
3 11
 
10.9%
4 5
 
5.0%
5 4
 
4.0%
6 2
 
2.0%
7 2
 
2.0%
8 3
 
3.0%
ValueCountFrequency (%)
8 3
 
3.0%
7 2
 
2.0%
6 2
 
2.0%
5 4
 
4.0%
4 5
 
5.0%
3 11
 
10.9%
2 27
26.7%
1 45
44.6%
0 1
 
1.0%

보호구역도로폭
Real number (ℝ)

Distinct39
Distinct (%)39.0%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean10.776
Minimum4
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-11T18:06:00.947045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5.5
Q16
median8
Q312
95-th percentile25.185
Maximum40
Range36
Interquartile range (IQR)6

Descriptive statistics

Standard deviation7.2136952
Coefficient of variation (CV)0.66942234
Kurtosis4.9783555
Mean10.776
Median Absolute Deviation (MAD)2
Skewness2.167498
Sum1077.6
Variance52.037398
MonotonicityNot monotonic
2023-12-11T18:06:01.076817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
6.0 25
24.8%
8.0 15
14.9%
12.0 7
 
6.9%
15.0 4
 
4.0%
5.5 4
 
4.0%
20.0 3
 
3.0%
25.0 3
 
3.0%
14.5 2
 
2.0%
40.0 2
 
2.0%
6.5 2
 
2.0%
Other values (29) 33
32.7%
ValueCountFrequency (%)
4.0 1
 
1.0%
5.3 1
 
1.0%
5.4 1
 
1.0%
5.5 4
 
4.0%
5.7 1
 
1.0%
5.8 1
 
1.0%
5.9 2
 
2.0%
6.0 25
24.8%
6.1 1
 
1.0%
6.5 2
 
2.0%
ValueCountFrequency (%)
40.0 2
2.0%
30.0 2
2.0%
28.7 1
 
1.0%
25.0 3
3.0%
23.1 1
 
1.0%
20.0 3
3.0%
19.7 1
 
1.0%
15.2 1
 
1.0%
15.0 4
4.0%
14.7 1
 
1.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size940.0 B
Minimum2020-06-24 00:00:00
Maximum2020-06-24 00:00:00
2023-12-11T18:06:01.180130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:06:01.274917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T18:05:56.785058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:55.566141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:56.001698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:56.374418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:56.875684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:55.668538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:56.096519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:56.468945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:56.985299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:55.771502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:56.194849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:56.558918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:57.089316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:55.901130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:56.283510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:05:56.666986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:06:01.596459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류소재지도로명주소위도경도관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭
시설종류1.0000.5280.0000.0000.0000.0000.5160.149
소재지도로명주소0.5281.0001.0001.0001.0001.0000.5010.950
위도0.0001.0001.0000.7140.9990.1010.0000.281
경도0.0001.0000.7141.0000.7350.3250.1310.417
관할경찰서명0.0001.0000.9990.7351.0000.0000.1490.364
CCTV설치여부0.0001.0000.1010.3250.0001.0001.0000.000
CCTV설치대수0.5160.5010.0000.1310.1491.0001.0000.000
보호구역도로폭0.1490.9500.2810.4170.3640.0000.0001.000
2023-12-11T18:06:01.740528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관할경찰서명CCTV설치여부시설종류
관할경찰서명1.0000.0000.000
CCTV설치여부0.0001.0000.000
시설종류0.0000.0001.000
2023-12-11T18:06:01.870267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도CCTV설치대수보호구역도로폭시설종류관할경찰서명CCTV설치여부
위도1.000-0.6380.131-0.4420.0000.9370.068
경도-0.6381.000-0.1200.3580.0000.5520.237
CCTV설치대수0.131-0.1201.000-0.0840.3460.1410.964
보호구역도로폭-0.4420.358-0.0841.0000.0950.3340.000
시설종류0.0000.0000.3460.0951.0000.0000.000
관할경찰서명0.9370.5520.1410.3340.0001.0000.000
CCTV설치여부0.0680.2370.9640.0000.0000.0001.000

Missing values

2023-12-11T18:05:57.225300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:05:57.386263image/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.
2023-12-11T18:05:57.517931image/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

시설종류대상시설명소재지도로명주소소재지지번주소위도경도관리기관명관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭데이터기준일자
0유치원돌샘유치원서울특별시 강남구 개포로 516<NA>37.48914127.07087서울특별시 강남구청수서경찰서Y112.62020-06-24
1유치원신양유치원서울특별시 강남구 선릉로10길 18-6<NA>37.483431127.061678서울특별시 강남구청수서경찰서Y26.02020-06-24
2유치원이화유치원서울특별시 강남구 개포로109길 9<NA>37.495751127.075096서울특별시 강남구청수서경찰서Y215.02020-06-24
3유치원영동제일유치원서울특별시 강남구 삼성로120길 28<NA>37.517579127.053437서울특별시 강남구청강남경찰서Y25.82020-06-24
4유치원소망유치원서울특별시 강남구 광평로56길 11<NA>37.487979127.105631서울특별시 강남구청수서경찰서Y111.02020-06-24
5유치원묘동유치원서울특별시 강남구 도곡로78길 8<NA>37.497407127.058723서울특별시 강남구청수서경찰서Y55.52020-06-24
6유치원푸른유치원서울특별시 강남구 일원로14길 25<NA>37.484798127.081101서울특별시 강남구청수서경찰서Y115.22020-06-24
7유치원성요셉유치원서울특별시 강남구 도산대로83길 27<NA>37.526273127.048211서울특별시 강남구청강남경찰서Y25.92020-06-24
8유치원강남유치원서울특별시 강남구 선릉로129길 31<NA>37.515448127.039009서울특별시 강남구청강남경찰서Y28.62020-06-24
9유치원반디유치원서울특별시 강남구 광평로47길 17<NA>37.48791127.098187서울특별시 강남구청수서경찰서Y29.62020-06-24
시설종류대상시설명소재지도로명주소소재지지번주소위도경도관리기관명관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭데이터기준일자
91어린이집바롬어린이집서울특별시 강남구 언주로164길 36<NA>37.525305127.036309서울특별시 강남구청강남경찰서Y16.02020-06-24
92어린이집역삼가애어린이집서울특별시 강남구 도곡로37길 15<NA>37.494809127.044725서울특별시 강남구청수서경찰서Y212.02020-06-24
93어린이집아이뜰어린이집서울특별시 강남구 개포로22길 39-11<NA>37.477164127.050117서울특별시 강남구청수서경찰서Y18.02020-06-24
94어린이집해맑은어린이집서울특별시 강남구 개포로36길 14<NA>37.478521127.051305서울특별시 강남구청수서경찰서Y16.02020-06-24
95어린이집대청어린이집서울특별시 강남구 양재대로37길 19<NA>37.490853127.083513서울특별시 강남구청수서경찰서Y16.02020-06-24
96어린이집충현어린이집서울특별시 강남구 테헤란로27길 40<NA>37.505327127.037616서울특별시 강남구청수서경찰서Y212.02020-06-24
97어린이집세곡햇빛어린이집서울특별시 강남구 자곡로 260<NA>37.476549127.111611서울특별시 강남구청수서경찰서N08.02020-06-24
98어린이집한울어린이집서울특별시 강남구 삼성로51길 25<NA>37.495907127.061002서울특별시 강남구청수서경찰서Y18.02020-06-24
99어린이집미담어린이집서울특별시 강남구 일원로 115<NA>37.484021127.08446서울특별시 강남구청수서경찰서Y18.02020-06-24
100어린이집아이앤어린이집서울특별시 강남구 봉은사로68길 35-2<NA>37.510028127.051843서울특별시 강남구청강남경찰서Y18.02020-06-24