Overview

Dataset statistics

Number of variables8
Number of observations65
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory71.0 B

Variable types

Categorical4
Numeric4

Dataset

Description게시글번호,제목,주거용 구분,용도명,건축물 총계,내진성능 확보수량(동(棟)),내진성능 미확보수량(동(棟)),내진성능 확보 비율
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-2389/S/1/datasetView.do

Alerts

용도명 is highly overall correlated with 건축물 총계 and 4 other fieldsHigh correlation
주거용 구분 is highly overall correlated with 건축물 총계 and 3 other fieldsHigh correlation
게시글번호 is highly overall correlated with 제목High correlation
제목 is highly overall correlated with 게시글번호High correlation
건축물 총계 is highly overall correlated with 내진성능 확보수량(동(棟)) and 4 other fieldsHigh correlation
내진성능 확보수량(동(棟)) is highly overall correlated with 건축물 총계 and 3 other fieldsHigh correlation
내진성능 미확보수량(동(棟)) is highly overall correlated with 건축물 총계 and 4 other fieldsHigh correlation
내진성능 확보 비율 is highly overall correlated with 건축물 총계 and 2 other fieldsHigh correlation

Reproduction

Analysis started2023-12-11 09:35:31.799691
Analysis finished2023-12-11 09:35:33.717564
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

게시글번호
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size652.0 B
160
13 
162
13 
181
13 
201
13 
242
13 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row160
2nd row160
3rd row160
4th row160
5th row160

Common Values

ValueCountFrequency (%)
160 13
20.0%
162 13
20.0%
181 13
20.0%
201 13
20.0%
242 13
20.0%

Length

2023-12-11T18:35:33.788765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:35:33.891740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
160 13
20.0%
162 13
20.0%
181 13
20.0%
201 13
20.0%
242 13
20.0%

제목
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size652.0 B
2012년도 2월 건축물 통계현황
13 
2012년도 12월 건축물 통계현황
13 
2013년도 3월 건축물 통계현황
13 
2013년도 6월 건축물 통계현황
13 
2013년도 9월 건축물 통계현황
13 

Length

Max length19
Median length18
Mean length18.2
Min length18

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2012년도 2월 건축물 통계현황
2nd row2012년도 2월 건축물 통계현황
3rd row2012년도 2월 건축물 통계현황
4th row2012년도 2월 건축물 통계현황
5th row2012년도 2월 건축물 통계현황

Common Values

ValueCountFrequency (%)
2012년도 2월 건축물 통계현황 13
20.0%
2012년도 12월 건축물 통계현황 13
20.0%
2013년도 3월 건축물 통계현황 13
20.0%
2013년도 6월 건축물 통계현황 13
20.0%
2013년도 9월 건축물 통계현황 13
20.0%

Length

2023-12-11T18:35:34.006526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:35:34.128061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건축물 65
25.0%
통계현황 65
25.0%
2013년도 39
15.0%
2012년도 26
 
10.0%
2월 13
 
5.0%
12월 13
 
5.0%
3월 13
 
5.0%
6월 13
 
5.0%
9월 13
 
5.0%

주거용 구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size652.0 B
비주거용
42 
주거용
12 
합 계
5 
주거용
 
3
비주거용
 
3

Length

Max length5
Median length4
Mean length3.7846154
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row합 계
2nd row주거용
3rd row주거용
4th row주거용
5th row비주거용

Common Values

ValueCountFrequency (%)
비주거용 42
64.6%
주거용 12
 
18.5%
합 계 5
 
7.7%
주거용 3
 
4.6%
비주거용 3
 
4.6%

Length

2023-12-11T18:35:34.267594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:35:34.390538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
비주거용 45
64.3%
주거용 15
 
21.4%
합 5
 
7.1%
계 5
 
7.1%

용도명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)24.6%
Missing0
Missing (%)0.0%
Memory size652.0 B
합 계
5 
단독주택
5 
공동주택
5 
제1종근린생활시설
5 
의료시설
5 
Other values (11)
40 

Length

Max length10
Median length9
Mean length5.4461538
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row합 계
2nd row주거 소계
3rd row단독주택
4th row공동주택
5th row비주거 소계

Common Values

ValueCountFrequency (%)
합 계 5
 
7.7%
단독주택 5
 
7.7%
공동주택 5
 
7.7%
제1종근린생활시설 5
 
7.7%
의료시설 5
 
7.7%
교육연구시설 5
 
7.7%
업무시설 5
 
7.7%
문화및집회시설 5
 
7.7%
종교시설 5
 
7.7%
기타용도 5
 
7.7%
Other values (6) 15
23.1%

Length

2023-12-11T18:35:34.527289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
소계 10
 
12.5%
합 5
 
6.2%
계 5
 
6.2%
단독주택 5
 
6.2%
공동주택 5
 
6.2%
제1종근린생활시설 5
 
6.2%
의료시설 5
 
6.2%
교육연구시설 5
 
6.2%
업무시설 5
 
6.2%
문화및집회시설 5
 
6.2%
Other values (5) 25
31.2%

건축물 총계
Real number (ℝ)

HIGH CORRELATION 

Distinct63
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean151126.29
Minimum751
Maximum659030
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-11T18:35:34.664449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum751
5-th percentile783.8
Q16979
median55392
Q3161202
95-th percentile651776.6
Maximum659030
Range658279
Interquartile range (IQR)154223

Descriptive statistics

Standard deviation210471.81
Coefficient of variation (CV)1.3926883
Kurtosis0.51552569
Mean151126.29
Median Absolute Deviation (MAD)54422
Skewness1.3841858
Sum9823209
Variance4.4298385 × 1010
MonotonicityNot monotonic
2023-12-11T18:35:34.822023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
907 2
 
3.1%
752 2
 
3.1%
497828 1
 
1.5%
2804 1
 
1.5%
8105 1
 
1.5%
7842 1
 
1.5%
16529 1
 
1.5%
651951 1
 
1.5%
491526 1
 
1.5%
375475 1
 
1.5%
Other values (53) 53
81.5%
ValueCountFrequency (%)
751 1
1.5%
752 2
3.1%
753 1
1.5%
907 2
3.1%
917 1
1.5%
970 1
1.5%
1031 1
1.5%
1331 1
1.5%
2475 1
1.5%
2799 1
1.5%
ValueCountFrequency (%)
659030 1
1.5%
658509 1
1.5%
653834 1
1.5%
651951 1
1.5%
651079 1
1.5%
497828 1
1.5%
496000 1
1.5%
493218 1
1.5%
491526 1
1.5%
490712 1
1.5%

내진성능 확보수량(동(棟))
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12996.785
Minimum123
Maximum60685
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-11T18:35:34.961904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum123
5-th percentile129.4
Q11807
median4420
Q321419
95-th percentile54695.8
Maximum60685
Range60562
Interquartile range (IQR)19612

Descriptive statistics

Standard deviation17160.79
Coefficient of variation (CV)1.3203873
Kurtosis1.1290378
Mean12996.785
Median Absolute Deviation (MAD)4150
Skewness1.4625693
Sum844791
Variance2.944927 × 108
MonotonicityNot monotonic
2023-12-11T18:35:35.096254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128 2
 
3.1%
46367 1
 
1.5%
268 1
 
1.5%
1857 1
 
1.5%
4420 1
 
1.5%
2100 1
 
1.5%
59224 1
 
1.5%
37805 1
 
1.5%
6021 1
 
1.5%
31784 1
 
1.5%
Other values (54) 54
83.1%
ValueCountFrequency (%)
123 1
1.5%
125 1
1.5%
128 2
3.1%
135 1
1.5%
227 1
1.5%
265 1
1.5%
268 1
1.5%
270 1
1.5%
274 1
1.5%
318 1
1.5%
ValueCountFrequency (%)
60685 1
1.5%
59224 1
1.5%
58543 1
1.5%
56778 1
1.5%
46367 1
1.5%
39015 1
1.5%
37805 1
1.5%
37234 1
1.5%
35657 1
1.5%
32690 1
1.5%

내진성능 미확보수량(동(棟))
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean138129.51
Minimum477
Maximum612663
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-11T18:35:35.247218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum477
5-th percentile546.2
Q13398
median45988
Q3141388
95-th percentile592260.4
Maximum612663
Range612186
Interquartile range (IQR)137990

Descriptive statistics

Standard deviation196402.96
Coefficient of variation (CV)1.4218755
Kurtosis0.35328428
Mean138129.51
Median Absolute Deviation (MAD)43573
Skewness1.3618502
Sum8978418
Variance3.8574122 × 1010
MonotonicityNot monotonic
2023-12-11T18:35:35.378384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
779 2
 
3.1%
612663 1
 
1.5%
484 1
 
1.5%
6248 1
 
1.5%
3422 1
 
1.5%
14429 1
 
1.5%
592727 1
 
1.5%
453721 1
 
1.5%
369454 1
 
1.5%
84267 1
 
1.5%
Other values (54) 54
83.1%
ValueCountFrequency (%)
477 1
1.5%
482 1
1.5%
484 1
1.5%
488 1
1.5%
779 2
3.1%
782 1
1.5%
804 1
1.5%
845 1
1.5%
1208 1
1.5%
2157 1
1.5%
ValueCountFrequency (%)
612663 1
1.5%
601731 1
1.5%
595291 1
1.5%
592727 1
1.5%
590394 1
1.5%
470012 1
1.5%
460343 1
1.5%
455984 1
1.5%
453721 1
1.5%
451697 1
1.5%

내진성능 확보 비율
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.516308
Minimum0.96
Maximum56.97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-11T18:35:35.500150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.96
5-th percentile1.62
Q18.62
median13.4
Q322.33
95-th percentile55.802
Maximum56.97
Range56.01
Interquartile range (IQR)13.71

Descriptive statistics

Standard deviation14.183483
Coefficient of variation (CV)0.80973015
Kurtosis2.0155351
Mean17.516308
Median Absolute Deviation (MAD)6.21
Skewness1.5336183
Sum1138.56
Variance201.17118
MonotonicityNot monotonic
2023-12-11T18:35:35.620054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.1 3
 
4.6%
1.6 2
 
3.1%
4.1 2
 
3.1%
56.9 1
 
1.5%
23.1 1
 
1.5%
13.7 1
 
1.5%
13.1 1
 
1.5%
35.6 1
 
1.5%
22.9 1
 
1.5%
56.4 1
 
1.5%
Other values (51) 51
78.5%
ValueCountFrequency (%)
0.96 1
1.5%
1.47 1
1.5%
1.6 2
3.1%
1.7 1
1.5%
4.01 1
1.5%
4.1 2
3.1%
4.15 1
1.5%
4.2 1
1.5%
5.59 1
1.5%
7.04 1
1.5%
ValueCountFrequency (%)
56.97 1
1.5%
56.9 1
1.5%
56.5 1
1.5%
56.4 1
1.5%
53.41 1
1.5%
36.5 1
1.5%
35.9 1
1.5%
35.6 1
1.5%
35.19 1
1.5%
28.0 1
1.5%

Interactions

2023-12-11T18:35:33.169097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:32.126122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:32.459650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:32.803101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:33.250030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:32.206243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:32.544992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:32.886113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:33.342893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:32.289553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:32.629131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:32.979856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:33.447427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:32.374448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:32.716731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:35:33.074035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:35:35.712056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
게시글번호제목주거용 구분용도명건축물 총계내진성능 확보수량(동(棟))내진성능 미확보수량(동(棟))내진성능 확보 비율
게시글번호1.0001.0000.0000.0000.0000.0000.0000.000
제목1.0001.0000.0000.0000.0000.0000.0000.000
주거용 구분0.0000.0001.0001.0000.8880.9040.8840.629
용도명0.0000.0001.0001.0001.0000.9740.9660.965
건축물 총계0.0000.0000.8881.0001.0000.8681.0000.713
내진성능 확보수량(동(棟))0.0000.0000.9040.9740.8681.0000.8450.624
내진성능 미확보수량(동(棟))0.0000.0000.8840.9661.0000.8451.0000.854
내진성능 확보 비율0.0000.0000.6290.9650.7130.6240.8541.000
2023-12-11T18:35:35.821567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도명주거용 구분게시글번호제목
용도명1.0000.9040.0000.000
주거용 구분0.9041.0000.0000.000
게시글번호0.0000.0001.0001.000
제목0.0000.0001.0001.000
2023-12-11T18:35:35.907032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건축물 총계내진성능 확보수량(동(棟))내진성능 미확보수량(동(棟))내진성능 확보 비율게시글번호제목주거용 구분용도명
건축물 총계1.0000.8970.997-0.6090.0000.0000.8150.911
내진성능 확보수량(동(棟))0.8971.0000.888-0.2490.0000.0000.8140.693
내진성능 미확보수량(동(棟))0.9970.8881.000-0.6190.0000.0000.8050.813
내진성능 확보 비율-0.609-0.249-0.6191.0000.0000.0000.4600.810
게시글번호0.0000.0000.0000.0001.0001.0000.0000.000
제목0.0000.0000.0000.0001.0001.0000.0000.000
주거용 구분0.8150.8140.8050.4600.0000.0001.0000.904
용도명0.9110.6930.8130.8100.0000.0000.9041.000

Missing values

2023-12-11T18:35:33.552223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:35:33.667953image/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

게시글번호제목주거용 구분용도명건축물 총계내진성능 확보수량(동(棟))내진성능 미확보수량(동(棟))내진성능 확보 비율
01602012년도 2월 건축물 통계현황합 계합 계659030463676126637.04
11602012년도 2월 건축물 통계현황주거용주거 소계497828278164700125.59
21602012년도 2월 건축물 통계현황주거용단독주택38786737343841330.96
31602012년도 2월 건축물 통계현황주거용공동주택109961240828587921.9
41602012년도 2월 건축물 통계현황비주거용비주거 소계1612021855114265111.51
51602012년도 2월 건축물 통계현황비주거용제1종근린생활시설809473363775844.15
61602012년도 2월 건축물 통계현황비주거용제2종근린생활시설4509672873780916.16
71602012년도 2월 건축물 통계현황비주거용의료시설103122780422.02
81602012년도 2월 건축물 통계현황비주거용교육연구시설63121349496321.37
91602012년도 2월 건축물 통계현황비주거용업무시설69793976300356.97
게시글번호제목주거용 구분용도명건축물 총계내진성능 확보수량(동(棟))내진성능 미확보수량(동(棟))내진성능 확보 비율
552422013년도 9월 건축물 통계현황주거용공동주택116924326908423428.0
562422013년도 9월 건축물 통계현황비주거용비주거 소계1603672167013869713.5
572422013년도 9월 건축물 통계현황비주거용제1종근린생활시설679022837650654.2
582422013년도 9월 건축물 통계현황비주거용제2종근린생활시설5545294964595617.1
592422013년도 9월 건축물 통계현황비주거용종교시설91713578214.7
602422013년도 9월 건축물 통계현황비주거용문화및집회시설2809397241214.1
612422013년도 9월 건축물 통계현황비주거용의료시설75127447736.5
622422013년도 9월 건축물 통계현황비주거용교육연구시설81411884625723.1
632422013년도 9월 건축물 통계현황비주거용업무시설78874489339856.9
642422013년도 9월 건축물 통계현황비주거용기타용도1650821581435013.1