Overview

Dataset statistics

Number of variables7
Number of observations246
Missing cells273
Missing cells (%)15.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.3 KiB
Average record size in memory59.5 B

Variable types

Numeric3
Text2
Categorical2

Dataset

Description서울특별시 양천구 아파트 단지내 조경면적 데이터로 아파트명, 주택유형, 지번주소, 건폐율, 조경면적 등의 정보를 제공합니다.(미보유 데이터 제외 구청에서 보유하고 있는 데이터 제공)
Author서울특별시 양천구
URLhttps://www.data.go.kr/data/15102559/fileData.do

Alerts

주택유형 has constant value ""Constant
데이터기준일 has constant value ""Constant
연번 is highly overall correlated with 조경면적(제곱미터)High correlation
건폐율 is highly overall correlated with 조경면적(제곱미터)High correlation
조경면적(제곱미터) is highly overall correlated with 연번 and 1 other fieldsHigh correlation
건폐율 has 37 (15.0%) missing valuesMissing
조경면적(제곱미터) has 236 (95.9%) missing valuesMissing
연번 has unique valuesUnique
지번주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:56:30.801355
Analysis finished2023-12-12 21:56:32.168146
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct246
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123.5
Minimum1
Maximum246
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-13T06:56:32.257077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.25
Q162.25
median123.5
Q3184.75
95-th percentile233.75
Maximum246
Range245
Interquartile range (IQR)122.5

Descriptive statistics

Standard deviation71.158274
Coefficient of variation (CV)0.57618036
Kurtosis-1.2
Mean123.5
Median Absolute Deviation (MAD)61.5
Skewness0
Sum30381
Variance5063.5
MonotonicityStrictly increasing
2023-12-13T06:56:32.436642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
156 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
165 1
 
0.4%
Other values (236) 236
95.9%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
246 1
0.4%
245 1
0.4%
244 1
0.4%
243 1
0.4%
242 1
0.4%
241 1
0.4%
240 1
0.4%
239 1
0.4%
238 1
0.4%
237 1
0.4%

아파트명
Text

Distinct237
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-13T06:56:32.740694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length5.9308943
Min length2

Characters and Unicode

Total characters1459
Distinct characters221
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique228 ?
Unique (%)92.7%

Sample

1st row목동1단지
2nd row목동2단지
3rd row목동3단지
4th row목동4단지
5th row목동5단지
ValueCountFrequency (%)
정은스카이빌 3
 
1.2%
신정대성유니드 2
 
0.8%
목동삼성 2
 
0.8%
2단지 2
 
0.8%
신정뉴타운 2
 
0.8%
현대 2
 
0.8%
신월동코아루 2
 
0.8%
목동성원 2
 
0.8%
탑건위너빌 2
 
0.8%
명지해드는터 2
 
0.8%
Other values (234) 236
91.8%
2023-12-13T06:56:33.162728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 89
 
6.1%
목 58
 
4.0%
신 53
 
3.6%
지 48
 
3.3%
단 42
 
2.9%
아 37
 
2.5%
이 32
 
2.2%
1 31
 
2.1%
트 31
 
2.1%
스 30
 
2.1%
Other values (211) 1008
69.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1307
89.6%
Decimal Number 96
 
6.6%
Open Punctuation 15
 
1.0%
Close Punctuation 15
 
1.0%
Uppercase Letter 12
 
0.8%
Space Separator 11
 
0.8%
Lowercase Letter 2
 
0.1%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 89
 
6.8%
목 58
 
4.4%
신 53
 
4.1%
지 48
 
3.7%
단 42
 
3.2%
아 37
 
2.8%
이 32
 
2.4%
트 31
 
2.4%
스 30
 
2.3%
빌 28
 
2.1%
Other values (185) 859
65.7%
Uppercase Letter
ValueCountFrequency (%)
S 2
16.7%
A 1
8.3%
B 1
8.3%
M 1
8.3%
C 1
8.3%
G 1
8.3%
W 1
8.3%
E 1
8.3%
I 1
8.3%
K 1
8.3%
Decimal Number
ValueCountFrequency (%)
1 31
32.3%
2 28
29.2%
3 13
13.5%
0 8
 
8.3%
4 7
 
7.3%
6 3
 
3.1%
5 3
 
3.1%
9 1
 
1.0%
8 1
 
1.0%
7 1
 
1.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1307
89.6%
Common 138
 
9.5%
Latin 14
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 89
 
6.8%
목 58
 
4.4%
신 53
 
4.1%
지 48
 
3.7%
단 42
 
3.2%
아 37
 
2.8%
이 32
 
2.4%
트 31
 
2.4%
스 30
 
2.3%
빌 28
 
2.1%
Other values (185) 859
65.7%
Common
ValueCountFrequency (%)
1 31
22.5%
2 28
20.3%
( 15
10.9%
) 15
10.9%
3 13
9.4%
11
 
8.0%
0 8
 
5.8%
4 7
 
5.1%
6 3
 
2.2%
5 3
 
2.2%
Other values (4) 4
 
2.9%
Latin
ValueCountFrequency (%)
e 2
14.3%
S 2
14.3%
A 1
7.1%
B 1
7.1%
M 1
7.1%
C 1
7.1%
G 1
7.1%
W 1
7.1%
E 1
7.1%
I 1
7.1%
Other values (2) 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1307
89.6%
ASCII 152
 
10.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 89
 
6.8%
목 58
 
4.4%
신 53
 
4.1%
지 48
 
3.7%
단 42
 
3.2%
아 37
 
2.8%
이 32
 
2.4%
트 31
 
2.4%
스 30
 
2.3%
빌 28
 
2.1%
Other values (185) 859
65.7%
ASCII
ValueCountFrequency (%)
1 31
20.4%
2 28
18.4%
( 15
9.9%
) 15
9.9%
3 13
8.6%
11
 
7.2%
0 8
 
5.3%
4 7
 
4.6%
6 3
 
2.0%
5 3
 
2.0%
Other values (16) 18
11.8%

주택유형
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
아파트
246 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
아파트 246
100.0%

Length

2023-12-13T06:56:33.319179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:56:33.419635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아파트 246
100.0%

지번주소
Text

UNIQUE 

Distinct246
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-13T06:56:33.834043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length19.211382
Min length16

Characters and Unicode

Total characters4726
Distinct characters30
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

Unique246 ?
Unique (%)100.0%

Sample

1st row서울특별시 양천구 목5동 901
2nd row서울특별시 양천구 목5동 902
3rd row서울특별시 양천구 목5동 903
4th row서울특별시 양천구 목5동 904
5th row서울특별시 양천구 목5동 912
ValueCountFrequency (%)
서울특별시 246
25.0%
양천구 246
25.0%
신정3동 32
 
3.3%
신월4동 26
 
2.6%
신월2동 24
 
2.4%
목4동 23
 
2.3%
신정2동 16
 
1.6%
신정4동 16
 
1.6%
목1동 15
 
1.5%
목2동 15
 
1.5%
Other values (259) 324
33.0%
2023-12-13T06:56:34.366292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
740
15.7%
1 250
 
5.3%
서 246
 
5.2%
동 246
 
5.2%
특 246
 
5.2%
별 246
 
5.2%
시 246
 
5.2%
양 246
 
5.2%
천 246
 
5.2%
구 246
 
5.2%
Other values (20) 1768
37.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2652
56.1%
Decimal Number 1222
25.9%
Space Separator 740
 
15.7%
Dash Punctuation 104
 
2.2%
Other Punctuation 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 246
9.3%
동 246
9.3%
특 246
9.3%
별 246
9.3%
시 246
9.3%
양 246
9.3%
천 246
9.3%
구 246
9.3%
울 246
9.3%
신 180
6.8%
Other values (6) 258
9.7%
Decimal Number
ValueCountFrequency (%)
1 250
20.5%
2 164
13.4%
3 158
12.9%
4 145
11.9%
5 104
8.5%
0 103
8.4%
7 98
 
8.0%
9 94
 
7.7%
6 55
 
4.5%
8 51
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 7
87.5%
. 1
 
12.5%
Space Separator
ValueCountFrequency (%)
740
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2652
56.1%
Common 2074
43.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 246
9.3%
동 246
9.3%
특 246
9.3%
별 246
9.3%
시 246
9.3%
양 246
9.3%
천 246
9.3%
구 246
9.3%
울 246
9.3%
신 180
6.8%
Other values (6) 258
9.7%
Common
ValueCountFrequency (%)
740
35.7%
1 250
 
12.1%
2 164
 
7.9%
3 158
 
7.6%
4 145
 
7.0%
5 104
 
5.0%
- 104
 
5.0%
0 103
 
5.0%
7 98
 
4.7%
9 94
 
4.5%
Other values (4) 114
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2652
56.1%
ASCII 2074
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
740
35.7%
1 250
 
12.1%
2 164
 
7.9%
3 158
 
7.6%
4 145
 
7.0%
5 104
 
5.0%
- 104
 
5.0%
0 103
 
5.0%
7 98
 
4.7%
9 94
 
4.5%
Other values (4) 114
 
5.5%
Hangul
ValueCountFrequency (%)
서 246
9.3%
동 246
9.3%
특 246
9.3%
별 246
9.3%
시 246
9.3%
양 246
9.3%
천 246
9.3%
구 246
9.3%
울 246
9.3%
신 180
6.8%
Other values (6) 258
9.7%

건폐율
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct203
Distinct (%)97.1%
Missing37
Missing (%)15.0%
Infinite0
Infinite (%)0.0%
Mean30.082336
Minimum7.11
Maximum59.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-13T06:56:34.536977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.11
5-th percentile19.658
Q124.03
median27.63
Q334.38
95-th percentile49.32
Maximum59.66
Range52.55
Interquartile range (IQR)10.35

Descriptive statistics

Standard deviation9.035965
Coefficient of variation (CV)0.30037444
Kurtosis1.013521
Mean30.082336
Median Absolute Deviation (MAD)4.49
Skewness1.0713049
Sum6287.2083
Variance81.648663
MonotonicityNot monotonic
2023-12-13T06:56:34.733751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22.6 3
 
1.2%
26.15 2
 
0.8%
28.17 2
 
0.8%
27.63 2
 
0.8%
23.14 2
 
0.8%
31.38 1
 
0.4%
21.66 1
 
0.4%
30.74 1
 
0.4%
49.5 1
 
0.4%
37.22 1
 
0.4%
Other values (193) 193
78.5%
(Missing) 37
 
15.0%
ValueCountFrequency (%)
7.11 1
0.4%
14.78 1
0.4%
17.0 1
0.4%
18.18 1
0.4%
18.59 1
0.4%
18.63 1
0.4%
18.84 1
0.4%
18.95 1
0.4%
19.02 1
0.4%
19.1 1
0.4%
ValueCountFrequency (%)
59.66 1
0.4%
58.26 1
0.4%
55.58 1
0.4%
55.5 1
0.4%
55.44 1
0.4%
54.86 1
0.4%
49.89 1
0.4%
49.68 1
0.4%
49.63 1
0.4%
49.54 1
0.4%

조경면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing236
Missing (%)95.9%
Infinite0
Infinite (%)0.0%
Mean9702.086
Minimum288.41
Maximum20791.58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-13T06:56:34.878718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum288.41
5-th percentile320.6795
Q16557.73
median10013.11
Q313768.72
95-th percentile18266.481
Maximum20791.58
Range20503.17
Interquartile range (IQR)7210.99

Descriptive statistics

Standard deviation6478.7282
Coefficient of variation (CV)0.66776652
Kurtosis-0.35879365
Mean9702.086
Median Absolute Deviation (MAD)3932.56
Skewness-0.029731843
Sum97020.86
Variance41973919
MonotonicityNot monotonic
2023-12-13T06:56:34.996847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
6300.32 1
 
0.4%
7329.96 1
 
0.4%
360.12 1
 
0.4%
288.41 1
 
0.4%
15180.25 1
 
0.4%
8728.51 1
 
0.4%
14165.44 1
 
0.4%
11297.71 1
 
0.4%
12578.56 1
 
0.4%
20791.58 1
 
0.4%
(Missing) 236
95.9%
ValueCountFrequency (%)
288.41 1
0.4%
360.12 1
0.4%
6300.32 1
0.4%
7329.96 1
0.4%
8728.51 1
0.4%
11297.71 1
0.4%
12578.56 1
0.4%
14165.44 1
0.4%
15180.25 1
0.4%
20791.58 1
0.4%
ValueCountFrequency (%)
20791.58 1
0.4%
15180.25 1
0.4%
14165.44 1
0.4%
12578.56 1
0.4%
11297.71 1
0.4%
8728.51 1
0.4%
7329.96 1
0.4%
6300.32 1
0.4%
360.12 1
0.4%
288.41 1
0.4%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-11-10
246 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-10
2nd row2023-11-10
3rd row2023-11-10
4th row2023-11-10
5th row2023-11-10

Common Values

ValueCountFrequency (%)
2023-11-10 246
100.0%

Length

2023-12-13T06:56:35.122486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:56:35.215747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-10 246
100.0%

Interactions

2023-12-13T06:56:31.500470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:56:31.021041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:56:31.254322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:56:31.605708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:56:31.096634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:56:31.343582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:56:31.703966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:56:31.169042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:56:31.422198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:56:35.266933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번건폐율조경면적(제곱미터)
연번1.0000.4941.000
건폐율0.4941.0000.735
조경면적(제곱미터)1.0000.7351.000
2023-12-13T06:56:35.350280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번건폐율조경면적(제곱미터)
연번1.0000.0730.733
건폐율0.0731.000-0.624
조경면적(제곱미터)0.733-0.6241.000

Missing values

2023-12-13T06:56:31.840613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:56:31.988839image/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.
2023-12-13T06:56:32.109556image/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

연번아파트명주택유형지번주소건폐율조경면적(제곱미터)데이터기준일
01목동1단지아파트서울특별시 양천구 목5동 901<NA><NA>2023-11-10
12목동2단지아파트서울특별시 양천구 목5동 902<NA><NA>2023-11-10
23목동3단지아파트서울특별시 양천구 목5동 903<NA><NA>2023-11-10
34목동4단지아파트서울특별시 양천구 목5동 904<NA><NA>2023-11-10
45목동5단지아파트서울특별시 양천구 목5동 912<NA><NA>2023-11-10
56목동6단지아파트서울특별시 양천구 목5동 911<NA><NA>2023-11-10
67목동7단지아파트서울특별시 양천구 목1동 925<NA><NA>2023-11-10
78목동8단지아파트서울특별시 양천구 신정6동 314<NA><NA>2023-11-10
89목동9단지아파트서울특별시 양천구 신정1동 312<NA><NA>2023-11-10
910목동10단지아파트서울특별시 양천구 신정1동 311<NA><NA>2023-11-10
연번아파트명주택유형지번주소건폐율조경면적(제곱미터)데이터기준일
236237신정이펜하우스1단지아파트서울특별시 양천구 신정3동 132120.52<NA>2023-11-10
237238신정뉴타운 두산위브아파트서울특별시 양천구 신월2동 105518.59<NA>2023-11-10
238239신정뉴타운 롯데캐슬아파트아파트서울특별시 양천구 신월2동 106320.34<NA>2023-11-10
239240목동힐스테이트아파트서울특별시 양천구 신정1동 132322.9915180.252023-11-10
240241신정숲속마을아파트서울특별시 양천구 신정3동 132420.76<NA>2023-11-10
241242목동센트럴아이파크위브1단지아파트서울특별시 양천구 신월동 107525.338728.512023-11-10
242243목동센트럴아이파크위브2단지아파트서울특별시 양천구 신월동 107626.5814165.442023-11-10
243244목동센트럴아이파크위브3단지아파트서울특별시 양천구 신월동 107722.611297.712023-11-10
244245목동센트럴아이파크위브4단지아파트서울특별시 양천구 신월동 107824.7912578.562023-11-10
245246래미안 목동아델리체아파트서울특별시 양천구 신정동 132622.3720791.582023-11-10