Overview

Dataset statistics

Number of variables15
Number of observations90
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.1 KiB
Average record size in memory126.5 B

Variable types

Categorical9
Text1
Numeric4
DateTime1

Dataset

Description공동주택명,동번호,전용구역위치구분코드,시도명,시군구명,시군구코드,소재지도로명주소,소재지지번주소,위도,경도,전용주차단위구획수,공동주택관리소전화번호,관할소방서명,관할소방서전화번호,데이터기준일자
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21307/S/1/datasetView.do

Alerts

시도명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
시군구명 is highly overall correlated with 시군구코드 and 10 other fieldsHigh correlation
공동주택명 is highly overall correlated with 시군구코드 and 10 other fieldsHigh correlation
공동주택관리소전화번호 is highly overall correlated with 시군구코드 and 10 other fieldsHigh correlation
관할소방서명 is highly overall correlated with 시군구코드 and 10 other fieldsHigh correlation
소재지지번주소 is highly overall correlated with 시군구코드 and 10 other fieldsHigh correlation
소재지도로명주소 is highly overall correlated with 시군구코드 and 10 other fieldsHigh correlation
관할소방서전화번호 is highly overall correlated with 시군구코드 and 10 other fieldsHigh correlation
시군구코드 is highly overall correlated with 위도 and 8 other fieldsHigh correlation
위도 is highly overall correlated with 시군구코드 and 8 other fieldsHigh correlation
경도 is highly overall correlated with 공동주택명 and 7 other fieldsHigh correlation
전용주차단위구획수 is highly overall correlated with 공동주택명 and 6 other fieldsHigh correlation
전용구역위치구분코드 is highly overall correlated with 시군구코드 and 9 other fieldsHigh correlation

Reproduction

Analysis started2023-12-11 09:45:33.393948
Analysis finished2023-12-11 09:45:36.611323
Duration3.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

공동주택명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
e편한세상 광진 그랜드파크
24 
마곡엠벨리9단지
19 
래미안파크스위트
8 
양원역금호어울림포레스트
8 
LH서울양원1단지
7 
Other values (13)
24 

Length

Max length16
Median length14
Mean length11.355556
Min length7

Unique

Unique10 ?
Unique (%)11.1%

Sample

1st row마곡엠벨리9단지
2nd row마곡엠벨리9단지
3rd row마곡엠벨리9단지
4th row마곡엠벨리9단지
5th row마곡엠벨리9단지

Common Values

ValueCountFrequency (%)
e편한세상 광진 그랜드파크 24
26.7%
마곡엠벨리9단지 19
21.1%
래미안파크스위트 8
 
8.9%
양원역금호어울림포레스트 8
 
8.9%
LH서울양원1단지 7
 
7.8%
신내역 금강펜테리움 센트럴파크 6
 
6.7%
신내역 힐데스하임 참좋은아파트 4
 
4.4%
엘에이치 엘스타시온 4
 
4.4%
용산KCC스위첸 1
 
1.1%
시티프라디움 아파트 1
 
1.1%
Other values (8) 8
 
8.9%

Length

2023-12-11T18:45:36.708885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
e편한세상 24
14.5%
그랜드파크 24
14.5%
광진 24
14.5%
마곡엠벨리9단지 19
11.4%
신내역 10
 
6.0%
래미안파크스위트 8
 
4.8%
양원역금호어울림포레스트 8
 
4.8%
lh서울양원1단지 7
 
4.2%
금강펜테리움 6
 
3.6%
센트럴파크 6
 
3.6%
Other values (18) 30
18.1%

동번호
Text

Distinct54
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
2023-12-11T18:45:36.936157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length3
Mean length3.7
Min length3

Characters and Unicode

Total characters333
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)41.1%

Sample

1st row901
2nd row902
3rd row903
4th row904
5th row905
ValueCountFrequency (%)
101 12
 
11.7%
102 9
 
8.7%
103 8
 
7.8%
108 5
 
4.9%
104 5
 
4.9%
110 4
 
3.9%
105 4
 
3.9%
109 3
 
2.9%
107 3
 
2.9%
106 3
 
2.9%
Other values (40) 47
45.6%
2023-12-11T18:45:37.341781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 106
31.8%
0 94
28.2%
3 26
 
7.8%
9 24
 
7.2%
2 22
 
6.6%
4 17
 
5.1%
13
 
3.9%
5 11
 
3.3%
8 7
 
2.1%
6 6
 
1.8%
Other values (2) 7
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 318
95.5%
Space Separator 13
 
3.9%
Math Symbol 2
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 106
33.3%
0 94
29.6%
3 26
 
8.2%
9 24
 
7.5%
2 22
 
6.9%
4 17
 
5.3%
5 11
 
3.5%
8 7
 
2.2%
6 6
 
1.9%
7 5
 
1.6%
Space Separator
ValueCountFrequency (%)
13
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 333
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 106
31.8%
0 94
28.2%
3 26
 
7.8%
9 24
 
7.2%
2 22
 
6.6%
4 17
 
5.1%
13
 
3.9%
5 11
 
3.3%
8 7
 
2.1%
6 6
 
1.8%
Other values (2) 7
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 333
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 106
31.8%
0 94
28.2%
3 26
 
7.8%
9 24
 
7.2%
2 22
 
6.6%
4 17
 
5.1%
13
 
3.9%
5 11
 
3.3%
8 7
 
2.1%
6 6
 
1.8%
Other values (2) 7
 
2.1%

전용구역위치구분코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size852.0 B
1
52 
2
38 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 52
57.8%
2 38
42.2%

Length

2023-12-11T18:45:37.470776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:45:37.585530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 52
57.8%
2 38
42.2%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
서울특별시
90 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 90
100.0%

Length

2023-12-11T18:45:37.696308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:45:37.794966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 90
100.0%

시군구명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size852.0 B
광진구
32 
중랑구
29 
강서구
19 
용산구
6 
중구
 
2
Other values (2)
 
2

Length

Max length3
Median length3
Mean length2.9777778
Min length2

Unique

Unique2 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
광진구 32
35.6%
중랑구 29
32.2%
강서구 19
21.1%
용산구 6
 
6.7%
중구 2
 
2.2%
도봉구 1
 
1.1%
송파구 1
 
1.1%

Length

2023-12-11T18:45:37.895780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:45:38.046008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광진구 32
35.6%
중랑구 29
32.2%
강서구 19
21.1%
용산구 6
 
6.7%
중구 2
 
2.2%
도봉구 1
 
1.1%
송파구 1
 
1.1%

시군구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11291.667
Minimum11140
Maximum11710
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-11T18:45:38.181479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11140
5-th percentile11170
Q111215
median11260
Q311260
95-th percentile11500
Maximum11710
Range570
Interquartile range (IQR)45

Descriptive statistics

Standard deviation123.27233
Coefficient of variation (CV)0.010917107
Kurtosis0.53590978
Mean11291.667
Median Absolute Deviation (MAD)45
Skewness1.2999455
Sum1016250
Variance15196.067
MonotonicityNot monotonic
2023-12-11T18:45:38.312201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
11215 32
35.6%
11260 29
32.2%
11500 19
21.1%
11170 6
 
6.7%
11140 2
 
2.2%
11320 1
 
1.1%
11710 1
 
1.1%
ValueCountFrequency (%)
11140 2
 
2.2%
11170 6
 
6.7%
11215 32
35.6%
11260 29
32.2%
11320 1
 
1.1%
11500 19
21.1%
11710 1
 
1.1%
ValueCountFrequency (%)
11710 1
 
1.1%
11500 19
21.1%
11320 1
 
1.1%
11260 29
32.2%
11215 32
35.6%
11170 6
 
6.7%
11140 2
 
2.2%

소재지도로명주소
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
서울특별시 광진구 광나루로 458
24 
서울특별시 강서구 공항대로 103
19 
서울특별시 광진구 광나루로 545
8 
서울특별시 중랑구 양원역로10길 75
8 
서울특별시 중랑구 양원역로 92
7 
Other values (13)
24 

Length

Max length22
Median length18
Mean length18.366667
Min length15

Unique

Unique10 ?
Unique (%)11.1%

Sample

1st row서울특별시 강서구 공항대로 103
2nd row서울특별시 강서구 공항대로 103
3rd row서울특별시 강서구 공항대로 103
4th row서울특별시 강서구 공항대로 103
5th row서울특별시 강서구 공항대로 103

Common Values

ValueCountFrequency (%)
서울특별시 광진구 광나루로 458 24
26.7%
서울특별시 강서구 공항대로 103 19
21.1%
서울특별시 광진구 광나루로 545 8
 
8.9%
서울특별시 중랑구 양원역로10길 75 8
 
8.9%
서울특별시 중랑구 양원역로 92 7
 
7.8%
서울특별시 중랑구 용마산로136길 160 6
 
6.7%
서울특별시 중랑구 봉화산로 301 4
 
4.4%
서울특별시 중랑구 양원역로10길 47 4
 
4.4%
서울특별시 용산구 백범로 275 1
 
1.1%
서울특별시 도봉구 노해로 144 1
 
1.1%
Other values (8) 8
 
8.9%

Length

2023-12-11T18:45:38.454835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 90
25.1%
광진구 32
 
8.9%
광나루로 32
 
8.9%
중랑구 29
 
8.1%
458 24
 
6.7%
강서구 19
 
5.3%
공항대로 19
 
5.3%
103 19
 
5.3%
양원역로10길 12
 
3.3%
545 8
 
2.2%
Other values (30) 75
20.9%

소재지지번주소
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Memory size852.0 B
서울특별시 광진구 구의동 680
24 
서울특별시 강서구 마곡동 744
19 
서울특별시 중랑구 망우동
18 
서울특별시 광진구 구의동 668
8 
서울특별시 중랑구 망우동 272-1
7 
Other values (11)
14 

Length

Max length19
Median length17
Mean length16.455556
Min length13

Unique

Unique10 ?
Unique (%)11.1%

Sample

1st row서울특별시 강서구 마곡동 744
2nd row서울특별시 강서구 마곡동 744
3rd row서울특별시 강서구 마곡동 744
4th row서울특별시 강서구 마곡동 744
5th row서울특별시 강서구 마곡동 744

Common Values

ValueCountFrequency (%)
서울특별시 광진구 구의동 680 24
26.7%
서울특별시 강서구 마곡동 744 19
21.1%
서울특별시 중랑구 망우동 18
20.0%
서울특별시 광진구 구의동 668 8
 
8.9%
서울특별시 중랑구 망우동 272-1 7
 
7.8%
서울특별시 중랑구 망우동 620 4
 
4.4%
서울특별시 도봉구 쌍문동 734-0 1
 
1.1%
서울특별시 송파구 거여동 654 1
 
1.1%
서울특별시 용산구 동빙고동 1-76 1
 
1.1%
서울특별시 용산구 효창동 152-1 1
 
1.1%
Other values (6) 6
 
6.7%

Length

2023-12-11T18:45:38.624217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 90
26.3%
광진구 32
 
9.4%
구의동 32
 
9.4%
중랑구 29
 
8.5%
망우동 29
 
8.5%
680 24
 
7.0%
강서구 19
 
5.6%
마곡동 19
 
5.6%
744 19
 
5.6%
668 8
 
2.3%
Other values (24) 41
12.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct81
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.569031
Minimum37.484092
Maximum37.646606
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-11T18:45:38.775220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.484092
5-th percentile37.539262
Q137.544066
median37.561636
Q337.607984
95-th percentile37.609703
Maximum37.646606
Range0.162514
Interquartile range (IQR)0.0639175

Descriptive statistics

Standard deviation0.031166551
Coefficient of variation (CV)0.00082958089
Kurtosis-0.79042317
Mean37.569031
Median Absolute Deviation (MAD)0.0180059
Skewness0.34122559
Sum3381.2128
Variance0.00097135388
MonotonicityNot monotonic
2023-12-11T18:45:38.961771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.608024 2
 
2.2%
37.608762 2
 
2.2%
37.609035 2
 
2.2%
37.608405 2
 
2.2%
37.608665 2
 
2.2%
37.607752 2
 
2.2%
37.608005 2
 
2.2%
37.607501 2
 
2.2%
37.609703 2
 
2.2%
37.543606 1
 
1.1%
Other values (71) 71
78.9%
ValueCountFrequency (%)
37.484092 1
1.1%
37.52562 1
1.1%
37.52683 1
1.1%
37.5362 1
1.1%
37.53874 1
1.1%
37.5399 1
1.1%
37.54091 1
1.1%
37.543278 1
1.1%
37.543295 1
1.1%
37.543306 1
1.1%
ValueCountFrequency (%)
37.646606 1
1.1%
37.6101 1
1.1%
37.610018 1
1.1%
37.609718 1
1.1%
37.609703 2
2.2%
37.609616 1
1.1%
37.609547 1
1.1%
37.609297 1
1.1%
37.609035 2
2.2%
37.608777 1
1.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct81
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.02676
Minimum126.81698
Maximum127.14659
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-11T18:45:39.147795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.81698
5-th percentile126.81759
Q1126.96997
median127.08125
Q3127.10705
95-th percentile127.11057
Maximum127.14659
Range0.329608
Interquartile range (IQR)0.13708075

Descriptive statistics

Standard deviation0.11391875
Coefficient of variation (CV)0.00089680904
Kurtosis-0.40998692
Mean127.02676
Median Absolute Deviation (MAD)0.0272115
Skewness-1.1635113
Sum11432.408
Variance0.012977481
MonotonicityNot monotonic
2023-12-11T18:45:39.312986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.109479 2
 
2.2%
127.110572 2
 
2.2%
127.107573 2
 
2.2%
127.107051 2
 
2.2%
127.106304 2
 
2.2%
127.111078 2
 
2.2%
127.110263 2
 
2.2%
127.109569 2
 
2.2%
127.105893 2
 
2.2%
127.081269 1
 
1.1%
Other values (71) 71
78.9%
ValueCountFrequency (%)
126.816984 1
1.1%
126.8169853 1
1.1%
126.816992 1
1.1%
126.8170058 1
1.1%
126.8175898 1
1.1%
126.8175992 1
1.1%
126.817618 1
1.1%
126.8177018 1
1.1%
126.8182664 1
1.1%
126.8183073 1
1.1%
ValueCountFrequency (%)
127.146592 1
1.1%
127.111078 2
2.2%
127.110623 1
1.1%
127.110572 2
2.2%
127.110263 2
2.2%
127.109569 2
2.2%
127.109513 1
1.1%
127.109479 2
2.2%
127.109371 1
1.1%
127.109182 1
1.1%

전용주차단위구획수
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7666667
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size942.0 B
2023-12-11T18:45:39.456268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile3.55
Maximum6
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1616532
Coefficient of variation (CV)0.65753956
Kurtosis4.4567494
Mean1.7666667
Median Absolute Deviation (MAD)0
Skewness2.010152
Sum159
Variance1.3494382
MonotonicityNot monotonic
2023-12-11T18:45:39.624512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 51
56.7%
2 21
23.3%
3 13
 
14.4%
6 3
 
3.3%
4 1
 
1.1%
5 1
 
1.1%
ValueCountFrequency (%)
1 51
56.7%
2 21
23.3%
3 13
 
14.4%
4 1
 
1.1%
5 1
 
1.1%
6 3
 
3.3%
ValueCountFrequency (%)
6 3
 
3.3%
5 1
 
1.1%
4 1
 
1.1%
3 13
 
14.4%
2 21
23.3%
1 51
56.7%

공동주택관리소전화번호
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size852.0 B
02-447-0991
24 
02-2666-2806
19 
02-3394-9484
8 
02-496-8704
8 
주:070-4496-6201 야:070-4496-6202
7 
Other values (13)
24 

Length

Max length31
Median length11
Mean length12.888889
Min length4

Unique

Unique10 ?
Unique (%)11.1%

Sample

1st row02-2666-2806
2nd row02-2666-2806
3rd row02-2666-2806
4th row02-2666-2806
5th row02-2666-2806

Common Values

ValueCountFrequency (%)
02-447-0991 24
26.7%
02-2666-2806 19
21.1%
02-3394-9484 8
 
8.9%
02-496-8704 8
 
8.9%
주:070-4496-6201 야:070-4496-6202 7
 
7.8%
02-435-7343 6
 
6.7%
02-2208-6914 4
 
4.4%
02-433-0965 4
 
4.4%
02-3275-2981 1
 
1.1%
02-2016-2686 1
 
1.1%
Other values (8) 8
 
8.9%

Length

2023-12-11T18:45:39.781138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02-447-0991 24
24.7%
02-2666-2806 19
19.6%
02-3394-9484 8
 
8.2%
02-496-8704 8
 
8.2%
주:070-4496-6201 7
 
7.2%
야:070-4496-6202 7
 
7.2%
02-435-7343 6
 
6.2%
02-2208-6914 4
 
4.1%
02-433-0965 4
 
4.1%
02-2256-7502 1
 
1.0%
Other values (9) 9
 
9.3%

관할소방서명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size852.0 B
광진소방서
32 
중랑소방서
29 
강서소방서
19 
용산소방서
6 
중부소방서
 
2
Other values (2)
 
2

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique2 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
광진소방서 32
35.6%
중랑소방서 29
32.2%
강서소방서 19
21.1%
용산소방서 6
 
6.7%
중부소방서 2
 
2.2%
도봉소방서 1
 
1.1%
송파소방서 1
 
1.1%

Length

2023-12-11T18:45:39.928219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:45:40.044019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광진소방서 32
35.6%
중랑소방서 29
32.2%
강서소방서 19
21.1%
용산소방서 6
 
6.7%
중부소방서 2
 
2.2%
도봉소방서 1
 
1.1%
송파소방서 1
 
1.1%

관할소방서전화번호
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size852.0 B
02-6981-6643
32 
02-6981-8843
29 
02-6981-5043
19 
02-6943-1443
6 
02-2253-0119
 
2
Other values (2)
 
2

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique2 ?
Unique (%)2.2%

Sample

1st row02-6981-5043
2nd row02-6981-5043
3rd row02-6981-5043
4th row02-6981-5043
5th row02-6981-5043

Common Values

ValueCountFrequency (%)
02-6981-6643 32
35.6%
02-6981-8843 29
32.2%
02-6981-5043 19
21.1%
02-6943-1443 6
 
6.7%
02-2253-0119 2
 
2.2%
02-6981-8043 1
 
1.1%
02-6981-5243 1
 
1.1%

Length

2023-12-11T18:45:40.190552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:45:40.342027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
02-6981-6643 32
35.6%
02-6981-8843 29
32.2%
02-6981-5043 19
21.1%
02-6943-1443 6
 
6.7%
02-2253-0119 2
 
2.2%
02-6981-8043 1
 
1.1%
02-6981-5243 1
 
1.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size852.0 B
Minimum2022-08-19 00:00:00
Maximum2022-08-19 00:00:00
2023-12-11T18:45:40.472506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:40.584829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T18:45:35.787799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:34.361085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:34.798432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:35.318206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:35.907100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:34.472569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:34.933371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:35.441842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:36.031541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:34.595690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:35.084821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:35.558496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:36.148318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:34.695363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:35.202419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:45:35.701542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:45:40.702152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공동주택명동번호전용구역위치구분코드시군구명시군구코드소재지도로명주소소재지지번주소위도경도전용주차단위구획수공동주택관리소전화번호관할소방서명관할소방서전화번호
공동주택명1.0000.9660.9161.0001.0001.0001.0001.0000.9810.9931.0001.0001.000
동번호0.9661.0000.0000.9060.8490.9660.9280.7980.4500.9990.9450.9060.906
전용구역위치구분코드0.9160.0001.0000.5530.7860.9160.9180.6990.5830.5290.8310.5530.553
시군구명1.0000.9060.5531.0001.0001.0001.0000.9580.9880.7341.0001.0001.000
시군구코드1.0000.8490.7861.0001.0001.0001.0000.9970.9540.8251.0001.0001.000
소재지도로명주소1.0000.9660.9161.0001.0001.0001.0001.0000.9810.9931.0001.0001.000
소재지지번주소1.0000.9280.9181.0001.0001.0001.0001.0000.9790.9571.0001.0001.000
위도1.0000.7980.6990.9580.9971.0001.0001.0000.8870.8181.0000.9580.958
경도0.9810.4500.5830.9880.9540.9810.9790.8871.0000.6860.9810.9880.988
전용주차단위구획수0.9930.9990.5290.7340.8250.9930.9570.8180.6861.0000.9670.7340.734
공동주택관리소전화번호1.0000.9450.8311.0001.0001.0001.0001.0000.9810.9671.0001.0001.000
관할소방서명1.0000.9060.5531.0001.0001.0001.0000.9580.9880.7341.0001.0001.000
관할소방서전화번호1.0000.9060.5531.0001.0001.0001.0000.9580.9880.7341.0001.0001.000
2023-12-11T18:45:40.868338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전용구역위치구분코드시군구명공동주택명공동주택관리소전화번호관할소방서명소재지지번주소소재지도로명주소관할소방서전화번호
전용구역위치구분코드1.0000.5770.7050.7100.5770.7150.7050.577
시군구명0.5771.0000.9310.9371.0000.9440.9311.000
공동주택명0.7050.9311.0001.0000.9310.9861.0000.931
공동주택관리소전화번호0.7100.9371.0001.0000.9370.9861.0000.937
관할소방서명0.5771.0000.9310.9371.0000.9440.9311.000
소재지지번주소0.7150.9440.9860.9860.9441.0000.9860.944
소재지도로명주소0.7050.9311.0001.0000.9310.9861.0000.931
관할소방서전화번호0.5771.0000.9310.9371.0000.9440.9311.000
2023-12-11T18:45:41.307762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구코드위도경도전용주차단위구획수공동주택명전용구역위치구분코드시군구명소재지도로명주소소재지지번주소공동주택관리소전화번호관할소방서명관할소방서전화번호
시군구코드1.0000.568-0.0990.3730.9260.5870.9940.9260.9390.9310.9940.994
위도0.5681.0000.4410.1600.9260.5020.9160.9260.9390.9310.9160.916
경도-0.0990.4411.000-0.3840.8660.6090.8240.8660.8790.8720.8240.824
전용주차단위구획수0.3730.160-0.3841.0000.8140.3730.5460.8140.8040.8180.5460.546
공동주택명0.9260.9260.8660.8141.0000.7050.9311.0000.9861.0000.9310.931
전용구역위치구분코드0.5870.5020.6090.3730.7051.0000.5770.7050.7150.7100.5770.577
시군구명0.9940.9160.8240.5460.9310.5771.0000.9310.9440.9371.0001.000
소재지도로명주소0.9260.9260.8660.8141.0000.7050.9311.0000.9861.0000.9310.931
소재지지번주소0.9390.9390.8790.8040.9860.7150.9440.9861.0000.9860.9440.944
공동주택관리소전화번호0.9310.9310.8720.8181.0000.7100.9371.0000.9861.0000.9370.937
관할소방서명0.9940.9160.8240.5460.9310.5771.0000.9310.9440.9371.0001.000
관할소방서전화번호0.9940.9160.8240.5460.9310.5771.0000.9310.9440.9371.0001.000

Missing values

2023-12-11T18:45:36.309098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:45:36.520345image/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

공동주택명동번호전용구역위치구분코드시도명시군구명시군구코드소재지도로명주소소재지지번주소위도경도전용주차단위구획수공동주택관리소전화번호관할소방서명관할소방서전화번호데이터기준일자
0마곡엠벨리9단지9011서울특별시강서구11500서울특별시 강서구 공항대로 103서울특별시 강서구 마곡동 74437.562316126.819132202-2666-2806강서소방서02-6981-50432022-08-19
1마곡엠벨리9단지9021서울특별시강서구11500서울특별시 강서구 공항대로 103서울특별시 강서구 마곡동 74437.562379126.819546202-2666-2806강서소방서02-6981-50432022-08-19
2마곡엠벨리9단지9031서울특별시강서구11500서울특별시 강서구 공항대로 103서울특별시 강서구 마곡동 74437.562336126.820297202-2666-2806강서소방서02-6981-50432022-08-19
3마곡엠벨리9단지9041서울특별시강서구11500서울특별시 강서구 공항대로 103서울특별시 강서구 마곡동 74437.561842126.819927302-2666-2806강서소방서02-6981-50432022-08-19
4마곡엠벨리9단지9051서울특별시강서구11500서울특별시 강서구 공항대로 103서울특별시 강서구 마곡동 74437.561575126.819113302-2666-2806강서소방서02-6981-50432022-08-19
5마곡엠벨리9단지9061서울특별시강서구11500서울특별시 강서구 공항대로 103서울특별시 강서구 마곡동 74437.56091126.819928302-2666-2806강서소방서02-6981-50432022-08-19
6마곡엠벨리9단지9071서울특별시강서구11500서울특별시 강서구 공항대로 103서울특별시 강서구 마곡동 74437.560897126.81932202-2666-2806강서소방서02-6981-50432022-08-19
7마곡엠벨리9단지9081서울특별시강서구11500서울특별시 강서구 공항대로 103서울특별시 강서구 마곡동 74437.561315126.818386202-2666-2806강서소방서02-6981-50432022-08-19
8마곡엠벨리9단지9091서울특별시강서구11500서울특별시 강서구 공항대로 103서울특별시 강서구 마곡동 74437.56122126.817702302-2666-2806강서소방서02-6981-50432022-08-19
9마곡엠벨리9단지9101서울특별시강서구11500서울특별시 강서구 공항대로 103서울특별시 강서구 마곡동 74437.561283126.816985202-2666-2806강서소방서02-6981-50432022-08-19
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