Overview

Dataset statistics

Number of variables5
Number of observations199
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.3 KiB
Average record size in memory42.7 B

Variable types

Numeric2
Text2
Categorical1

Dataset

Description서울특별시 강서구 공유재산(건물)현황에 대한 자료입니다. 제공데이터: 연번, 재산명, 소재지, 면적, 재산용도
URLhttps://www.data.go.kr/data/15112834/fileData.do

Alerts

재산용도 is highly imbalanced (88.7%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:14:19.685899
Analysis finished2023-12-12 03:14:21.068666
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct199
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100
Minimum1
Maximum199
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T12:14:21.158347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.9
Q150.5
median100
Q3149.5
95-th percentile189.1
Maximum199
Range198
Interquartile range (IQR)99

Descriptive statistics

Standard deviation57.590508
Coefficient of variation (CV)0.57590508
Kurtosis-1.2
Mean100
Median Absolute Deviation (MAD)50
Skewness0
Sum19900
Variance3316.6667
MonotonicityStrictly increasing
2023-12-12T12:14:21.346768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
138 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
Other values (189) 189
95.0%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
199 1
0.5%
198 1
0.5%
197 1
0.5%
196 1
0.5%
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%

재산명
Text

Distinct194
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T12:14:21.662748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length8.5829146
Min length2

Characters and Unicode

Total characters1708
Distinct characters236
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique190 ?
Unique (%)95.5%

Sample

1st row성재정경노당
2nd row가양1동 주민센터
3rd row구암근린공원관리사무실
4th row직업재활센터
5th row가양2동청사
ValueCountFrequency (%)
구립 6
 
2.2%
공중화장실 5
 
1.9%
빗물펌프장 4
 
1.5%
고객만족센터 4
 
1.5%
강서구 4
 
1.5%
어린이집 3
 
1.1%
궁산근린공원 3
 
1.1%
강서50플러스센터 3
 
1.1%
경로당 2
 
0.7%
화장실 2
 
0.7%
Other values (223) 234
86.7%
2023-12-12T12:14:22.131474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
4.4%
화 64
 
3.7%
장 52
 
3.0%
당 49
 
2.9%
공 45
 
2.6%
동 45
 
2.6%
경 44
 
2.6%
노 43
 
2.5%
구 38
 
2.2%
센 36
 
2.1%
Other values (226) 1217
71.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1537
90.0%
Space Separator 75
 
4.4%
Decimal Number 63
 
3.7%
Dash Punctuation 11
 
0.6%
Close Punctuation 9
 
0.5%
Open Punctuation 9
 
0.5%
Other Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 64
 
4.2%
장 52
 
3.4%
당 49
 
3.2%
공 45
 
2.9%
동 45
 
2.9%
경 44
 
2.9%
노 43
 
2.8%
구 38
 
2.5%
센 36
 
2.3%
터 35
 
2.3%
Other values (210) 1086
70.7%
Decimal Number
ValueCountFrequency (%)
1 19
30.2%
2 13
20.6%
3 10
15.9%
0 4
 
6.3%
5 4
 
6.3%
8 4
 
6.3%
4 3
 
4.8%
6 3
 
4.8%
7 2
 
3.2%
9 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
/ 2
50.0%
. 2
50.0%
Space Separator
ValueCountFrequency (%)
75
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1537
90.0%
Common 171
 
10.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
화 64
 
4.2%
장 52
 
3.4%
당 49
 
3.2%
공 45
 
2.9%
동 45
 
2.9%
경 44
 
2.9%
노 43
 
2.8%
구 38
 
2.5%
센 36
 
2.3%
터 35
 
2.3%
Other values (210) 1086
70.7%
Common
ValueCountFrequency (%)
75
43.9%
1 19
 
11.1%
2 13
 
7.6%
- 11
 
6.4%
3 10
 
5.8%
) 9
 
5.3%
( 9
 
5.3%
0 4
 
2.3%
5 4
 
2.3%
8 4
 
2.3%
Other values (6) 13
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1537
90.0%
ASCII 171
 
10.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75
43.9%
1 19
 
11.1%
2 13
 
7.6%
- 11
 
6.4%
3 10
 
5.8%
) 9
 
5.3%
( 9
 
5.3%
0 4
 
2.3%
5 4
 
2.3%
8 4
 
2.3%
Other values (6) 13
 
7.6%
Hangul
ValueCountFrequency (%)
화 64
 
4.2%
장 52
 
3.4%
당 49
 
3.2%
공 45
 
2.9%
동 45
 
2.9%
경 44
 
2.9%
노 43
 
2.8%
구 38
 
2.5%
센 36
 
2.3%
터 35
 
2.3%
Other values (210) 1086
70.7%

소재지
Text

Distinct187
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T12:14:22.532878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length31
Mean length20.81407
Min length17

Characters and Unicode

Total characters4142
Distinct characters52
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

Unique177 ?
Unique (%)88.9%

Sample

1st row서울특별시 강서구 가양동 131-1
2nd row서울특별시 강서구 가양동 1462-3
3rd row서울특별시 강서구 가양동 1471
4th row서울특별시 강서구 가양동 1472 1472-1
5th row서울특별시 강서구 가양동 1472-4
ValueCountFrequency (%)
강서구 200
24.1%
서울특별시 199
23.9%
화곡동 82
 
9.9%
방화동 23
 
2.8%
등촌동 21
 
2.5%
가양동 17
 
2.0%
마곡동 17
 
2.0%
산 17
 
2.0%
내발산동 14
 
1.7%
염창동 10
 
1.2%
Other values (198) 231
27.8%
2023-12-12T12:14:23.104270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
830
20.0%
서 399
 
9.6%
동 205
 
4.9%
강 200
 
4.8%
구 200
 
4.8%
별 199
 
4.8%
시 199
 
4.8%
특 199
 
4.8%
울 199
 
4.8%
- 173
 
4.2%
Other values (42) 1339
32.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2257
54.5%
Decimal Number 882
 
21.3%
Space Separator 830
 
20.0%
Dash Punctuation 173
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 399
17.7%
동 205
9.1%
강 200
8.9%
구 200
8.9%
별 199
8.8%
시 199
8.8%
특 199
8.8%
울 199
8.8%
화 109
 
4.8%
곡 99
 
4.4%
Other values (30) 249
11.0%
Decimal Number
ValueCountFrequency (%)
1 171
19.4%
2 102
11.6%
6 101
11.5%
4 86
9.8%
0 79
9.0%
8 78
8.8%
3 70
7.9%
5 70
7.9%
7 66
 
7.5%
9 59
 
6.7%
Space Separator
ValueCountFrequency (%)
830
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 173
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2257
54.5%
Common 1885
45.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 399
17.7%
동 205
9.1%
강 200
8.9%
구 200
8.9%
별 199
8.8%
시 199
8.8%
특 199
8.8%
울 199
8.8%
화 109
 
4.8%
곡 99
 
4.4%
Other values (30) 249
11.0%
Common
ValueCountFrequency (%)
830
44.0%
- 173
 
9.2%
1 171
 
9.1%
2 102
 
5.4%
6 101
 
5.4%
4 86
 
4.6%
0 79
 
4.2%
8 78
 
4.1%
3 70
 
3.7%
5 70
 
3.7%
Other values (2) 125
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2257
54.5%
ASCII 1885
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
830
44.0%
- 173
 
9.2%
1 171
 
9.1%
2 102
 
5.4%
6 101
 
5.4%
4 86
 
4.6%
0 79
 
4.2%
8 78
 
4.1%
3 70
 
3.7%
5 70
 
3.7%
Other values (2) 125
 
6.6%
Hangul
ValueCountFrequency (%)
서 399
17.7%
동 205
9.1%
강 200
8.9%
구 200
8.9%
별 199
8.8%
시 199
8.8%
특 199
8.8%
울 199
8.8%
화 109
 
4.8%
곡 99
 
4.4%
Other values (30) 249
11.0%

면적(제곱미터)
Real number (ℝ)

Distinct188
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1177.2554
Minimum12.79
Maximum23879.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T12:14:23.315152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12.79
5-th percentile34.703
Q1148.24
median410.8
Q31210.29
95-th percentile4170.176
Maximum23879.8
Range23867.01
Interquartile range (IQR)1062.05

Descriptive statistics

Standard deviation2438.0447
Coefficient of variation (CV)2.0709565
Kurtosis42.117448
Mean1177.2554
Median Absolute Deviation (MAD)314.7
Skewness5.595986
Sum234273.82
Variance5944062.1
MonotonicityNot monotonic
2023-12-12T12:14:23.535397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90.27 4
 
2.0%
96.1 3
 
1.5%
200.0 3
 
1.5%
36.0 2
 
1.0%
144.0 2
 
1.0%
22.0 2
 
1.0%
91.28 2
 
1.0%
2046.45 1
 
0.5%
796.0 1
 
0.5%
417.15 1
 
0.5%
Other values (178) 178
89.4%
ValueCountFrequency (%)
12.79 1
0.5%
14.0 1
0.5%
14.78 1
0.5%
19.8 1
0.5%
21.0 1
0.5%
22.0 2
1.0%
23.29 1
0.5%
27.0 1
0.5%
32.03 1
0.5%
35.0 1
0.5%
ValueCountFrequency (%)
23879.8 1
0.5%
13128.78 1
0.5%
11357.35 1
0.5%
9402.69 1
0.5%
7884.79 1
0.5%
6928.62 1
0.5%
6569.39 1
0.5%
5448.19 1
0.5%
4752.3 1
0.5%
4203.08 1
0.5%

재산용도
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
행정재산
196 
일반재산
 
3

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
행정재산 196
98.5%
일반재산 3
 
1.5%

Length

2023-12-12T12:14:23.702992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:14:23.840306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
행정재산 196
98.5%
일반재산 3
 
1.5%

Interactions

2023-12-12T12:14:20.632636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:14:19.999631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:14:20.760993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:14:20.163314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:14:23.940465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적(제곱미터)재산용도
연번1.0000.0000.207
면적(제곱미터)0.0001.0000.000
재산용도0.2070.0001.000
2023-12-12T12:14:24.081998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적(제곱미터)재산용도
연번1.000-0.0650.155
면적(제곱미터)-0.0651.0000.000
재산용도0.1550.0001.000

Missing values

2023-12-12T12:14:20.901807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:14:21.024734image/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

연번재산명소재지면적(제곱미터)재산용도
01성재정경노당서울특별시 강서구 가양동 131-1257.37행정재산
12가양1동 주민센터서울특별시 강서구 가양동 1462-323879.8행정재산
23구암근린공원관리사무실서울특별시 강서구 가양동 147174.34행정재산
34직업재활센터서울특별시 강서구 가양동 1472 1472-12209.66행정재산
45가양2동청사서울특별시 강서구 가양동 1472-41952.73행정재산
56가양3동사무소서울특별시 강서구 가양동 1488-11689.46행정재산
67강서구청가양동별관서울특별시 강서구 가양동 1488-93773.45행정재산
78가양레포츠센터서울특별시 강서구 가양동 14936569.39행정재산
89가양 빗물펌프장서울특별시 강서구 가양동 14932354.49행정재산
910강서등촌지역자활센터(구.가양1동청사)서울특별시 강서구 가양동 179-1563.55행정재산
연번재산명소재지면적(제곱미터)재산용도
189190까치산근린공원화장실서울특별시 강서구 화곡동 산 162-143.2행정재산
190191강서 다목적체육관서울특별시 강서구 화곡동 산 22-32872.25행정재산
191192봉제산 배드민턴장서울특별시 강서구 화곡동 산 22-80200.0행정재산
192193봉제산노인복지센터서울특별시 강서구 화곡동 산 41-161288.78행정재산
193194무궁화공원 공중화장실서울특별시 강서구 화곡동 산 47-1635.6행정재산
194195무궁화공원초소서울특별시 강서구 화곡동 산 47-1635.0행정재산
195196봉제경노당서울특별시 강서구 화곡동 산 47-1690.27행정재산
196197궁도장서울특별시 강서구 화곡동 산 60-192.88행정재산
197198우장공원3화장실서울특별시 강서구 화곡동 산 60-136.0행정재산
198199우장근린공원관리사무실서울특별시 강서구 화곡동 산 60-1211.0행정재산