Overview

Dataset statistics

Number of variables9
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory810.5 KiB
Average record size in memory83.0 B

Variable types

Numeric3
Categorical5
DateTime1

Dataset

Description서울특별시 관악구 법정동 주택현황 데이터로 순번,대장종류, 시군구,법정동명,대지구분, 본번, 부번, 주용도, 데이터기준일자 등을 제공합니다
Author서울특별시 관악구
URLhttps://www.data.go.kr/data/15108260/fileData.do

Alerts

시군구 has constant value ""Constant
데이터기준일자 has constant value ""Constant
주용도 is highly overall correlated with 대장종류High correlation
대장종류 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
순번 is highly overall correlated with 대장종류High correlation
본번 is highly overall correlated with 법정동명High correlation
법정동명 is highly overall correlated with 본번High correlation
대지구분 is highly imbalanced (93.3%)Imbalance
주용도 is highly imbalanced (57.1%)Imbalance
순번 has unique valuesUnique
부번 has 355 (3.5%) zerosZeros

Reproduction

Analysis started2023-12-12 05:41:17.028140
Analysis finished2023-12-12 05:41:19.366550
Duration2.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16135.635
Minimum1
Maximum32041
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T14:41:19.486406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1655.95
Q18021.5
median16259.5
Q324163
95-th percentile30526.2
Maximum32041
Range32040
Interquartile range (IQR)16141.5

Descriptive statistics

Standard deviation9272.721
Coefficient of variation (CV)0.57467345
Kurtosis-1.205018
Mean16135.635
Median Absolute Deviation (MAD)8076
Skewness-0.0079481165
Sum1.6135635 × 108
Variance85983355
MonotonicityNot monotonic
2023-12-12T14:41:19.668433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30966 1
 
< 0.1%
4558 1
 
< 0.1%
9994 1
 
< 0.1%
11288 1
 
< 0.1%
2301 1
 
< 0.1%
30812 1
 
< 0.1%
126 1
 
< 0.1%
31473 1
 
< 0.1%
10776 1
 
< 0.1%
9190 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
13 1
< 0.1%
17 1
< 0.1%
ValueCountFrequency (%)
32041 1
< 0.1%
32039 1
< 0.1%
32037 1
< 0.1%
32036 1
< 0.1%
32035 1
< 0.1%
32034 1
< 0.1%
32033 1
< 0.1%
32031 1
< 0.1%
32027 1
< 0.1%
32020 1
< 0.1%

대장종류
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반건축물
7729 
표제부
2271 

Length

Max length5
Median length5
Mean length4.5458
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row표제부
2nd row일반건축물
3rd row일반건축물
4th row일반건축물
5th row일반건축물

Common Values

ValueCountFrequency (%)
일반건축물 7729
77.3%
표제부 2271
 
22.7%

Length

2023-12-12T14:41:19.869504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:41:20.008525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반건축물 7729
77.3%
표제부 2271
 
22.7%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
서울특별시 관악구
10000 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 관악구 10000
100.0%

Length

2023-12-12T14:41:20.137998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:41:20.261479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 10000
50.0%
관악구 10000
50.0%

법정동명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
신림동
5587 
봉천동
4051 
남현동
 
362

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row신림동
2nd row봉천동
3rd row신림동
4th row신림동
5th row신림동

Common Values

ValueCountFrequency (%)
신림동 5587
55.9%
봉천동 4051
40.5%
남현동 362
 
3.6%

Length

2023-12-12T14:41:20.389418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:41:20.532099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신림동 5587
55.9%
봉천동 4051
40.5%
남현동 362
 
3.6%

대지구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대지
9865 
산
 
131
블록
 
4

Length

Max length2
Median length2
Mean length1.9869
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대지 9865
98.7%
산 131
 
1.3%
블록 4
 
< 0.1%

Length

2023-12-12T14:41:20.663874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:41:20.805853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대지 9865
98.7%
산 131
 
1.3%
블록 4
 
< 0.1%

본번
Real number (ℝ)

HIGH CORRELATION 

Distinct936
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean808.6709
Minimum0
Maximum1741
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T14:41:20.926772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile41
Q1358
median650
Q31480
95-th percentile1680
Maximum1741
Range1741
Interquartile range (IQR)1122

Descriptive statistics

Standard deviation574.0366
Coefficient of variation (CV)0.70985193
Kurtosis-1.3240531
Mean808.6709
Median Absolute Deviation (MAD)435
Skewness0.30932515
Sum8086709
Variance329518.02
MonotonicityNot monotonic
2023-12-12T14:41:21.127733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
635 172
 
1.7%
41 157
 
1.6%
100 141
 
1.4%
610 133
 
1.3%
180 129
 
1.3%
251 120
 
1.2%
10 112
 
1.1%
412 105
 
1.1%
646 95
 
0.9%
98 94
 
0.9%
Other values (926) 8742
87.4%
ValueCountFrequency (%)
0 4
 
< 0.1%
1 56
0.6%
2 2
 
< 0.1%
3 6
 
0.1%
4 21
 
0.2%
5 8
 
0.1%
6 6
 
0.1%
7 15
 
0.1%
8 5
 
0.1%
9 9
 
0.1%
ValueCountFrequency (%)
1741 3
 
< 0.1%
1740 2
 
< 0.1%
1739 1
 
< 0.1%
1737 2
 
< 0.1%
1736 7
 
0.1%
1735 35
0.4%
1734 2
 
< 0.1%
1733 11
 
0.1%
1732 1
 
< 0.1%
1730 28
0.3%

부번
Real number (ℝ)

ZEROS 

Distinct623
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.9205
Minimum0
Maximum1386
Zeros355
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T14:41:21.336233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q110
median25
Q370
95-th percentile339
Maximum1386
Range1386
Interquartile range (IQR)60

Descriptive statistics

Standard deviation122.83604
Coefficient of variation (CV)1.6845201
Kurtosis12.934409
Mean72.9205
Median Absolute Deviation (MAD)20
Skewness3.1579586
Sum729205
Variance15088.694
MonotonicityNot monotonic
2023-12-12T14:41:21.512541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 375
 
3.8%
0 355
 
3.5%
2 257
 
2.6%
4 240
 
2.4%
3 233
 
2.3%
5 227
 
2.3%
7 218
 
2.2%
14 213
 
2.1%
8 208
 
2.1%
10 207
 
2.1%
Other values (613) 7467
74.7%
ValueCountFrequency (%)
0 355
3.5%
1 375
3.8%
2 257
2.6%
3 233
2.3%
4 240
2.4%
5 227
2.3%
6 191
1.9%
7 218
2.2%
8 208
2.1%
9 188
1.9%
ValueCountFrequency (%)
1386 1
< 0.1%
1137 1
< 0.1%
1126 1
< 0.1%
1125 1
< 0.1%
1124 1
< 0.1%
1116 1
< 0.1%
1005 1
< 0.1%
996 1
< 0.1%
977 1
< 0.1%
900 1
< 0.1%

주용도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단독주택
5716 
공동주택
2079 
제2종근린생활시설
922 
제1종근린생활시설
714 
업무시설
 
193
Other values (17)
 
376

Length

Max length10
Median length4
Mean length4.8758
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row공동주택
2nd row단독주택
3rd row단독주택
4th row제2종근린생활시설
5th row단독주택

Common Values

ValueCountFrequency (%)
단독주택 5716
57.2%
공동주택 2079
 
20.8%
제2종근린생활시설 922
 
9.2%
제1종근린생활시설 714
 
7.1%
업무시설 193
 
1.9%
교육연구시설 161
 
1.6%
노유자시설 44
 
0.4%
종교시설 40
 
0.4%
숙박시설 39
 
0.4%
교정및군사시설 34
 
0.3%
Other values (12) 58
 
0.6%

Length

2023-12-12T14:41:21.661841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 5716
57.2%
공동주택 2079
 
20.8%
제2종근린생활시설 922
 
9.2%
제1종근린생활시설 714
 
7.1%
업무시설 193
 
1.9%
교육연구시설 161
 
1.6%
노유자시설 44
 
0.4%
종교시설 40
 
0.4%
숙박시설 39
 
0.4%
교정및군사시설 34
 
0.3%
Other values (12) 58
 
0.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-11-21 00:00:00
Maximum2022-11-21 00:00:00
2023-12-12T14:41:21.795157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:41:21.886329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T14:41:18.388062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:41:17.720997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:41:18.062927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:41:18.507946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:41:17.835633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:41:18.179072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:41:18.942218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:41:17.953078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:41:18.279202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:41:21.977842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번대장종류법정동명대지구분본번부번주용도
순번1.0000.9970.1260.1950.1410.1550.656
대장종류0.9971.0000.0570.0350.1140.1370.998
법정동명0.1260.0571.0000.3230.9150.1260.395
대지구분0.1950.0350.3231.0000.3790.0250.668
본번0.1410.1140.9150.3791.0000.3200.285
부번0.1550.1370.1260.0250.3201.0000.116
주용도0.6560.9980.3950.6680.2850.1161.000
2023-12-12T14:41:22.103434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주용도법정동명대지구분대장종류
주용도1.0000.2250.4560.958
법정동명0.2251.0000.1110.094
대지구분0.4560.1111.0000.059
대장종류0.9580.0940.0591.000
2023-12-12T14:41:22.215504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번본번부번대장종류법정동명대지구분주용도
순번1.0000.0780.0020.9480.0750.1180.310
본번0.0781.000-0.4050.1140.6620.1810.115
부번0.002-0.4051.0000.1050.0750.0150.043
대장종류0.9480.1140.1051.0000.0940.0590.958
법정동명0.0750.6620.0750.0941.0000.1110.225
대지구분0.1180.1810.0150.0590.1111.0000.456
주용도0.3100.1150.0430.9580.2250.4561.000

Missing values

2023-12-12T14:41:19.119483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:41:19.288574image/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

순번대장종류시군구법정동명대지구분본번부번주용도데이터기준일자
3096530966표제부서울특별시 관악구신림동대지685187공동주택2022-11-21
1368613687일반건축물서울특별시 관악구봉천동대지412단독주택2022-11-21
1887318874일반건축물서울특별시 관악구신림동대지5135단독주택2022-11-21
2045620457일반건축물서울특별시 관악구신림동대지166614제2종근린생활시설2022-11-21
24402441일반건축물서울특별시 관악구신림동대지51425단독주택2022-11-21
86448645일반건축물서울특별시 관악구신림동대지254287제2종근린생활시설2022-11-21
3090630907표제부서울특별시 관악구봉천동대지64757공동주택2022-11-21
2795227953표제부서울특별시 관악구봉천동대지6721공동주택2022-11-21
2770027701표제부서울특별시 관악구남현동대지107243공동주택2022-11-21
2915229153표제부서울특별시 관악구봉천동대지9144업무시설2022-11-21
순번대장종류시군구법정동명대지구분본번부번주용도데이터기준일자
1630116302일반건축물서울특별시 관악구신림동대지3774단독주택2022-11-21
1454914550일반건축물서울특별시 관악구신림동대지68538단독주택2022-11-21
2325123252일반건축물서울특별시 관악구봉천동산17536운동시설2022-11-21
73537354일반건축물서울특별시 관악구신림동대지607138제1종근린생활시설2022-11-21
1579915800일반건축물서울특별시 관악구신림동대지56448단독주택2022-11-21
1955019551일반건축물서울특별시 관악구신림동대지67561단독주택2022-11-21
486487일반건축물서울특별시 관악구신림동대지2363단독주택2022-11-21
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