Overview

Dataset statistics

Number of variables4
Number of observations192
Missing cells3
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory33.7 B

Variable types

Text3
Numeric1

Dataset

Description서울특별시 영등포구 관내 공동주택 단지 정보(1) 제공 데이터- 공동주택(아파트) 단지명- 단지 주소(도로명 주소)- 단지 세대수- 전화번호
Author서울특별시 영등포구
URLhttps://www.data.go.kr/data/15046137/fileData.do

Alerts

전화 has 3 (1.6%) missing valuesMissing
아파트명 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:25:55.345791
Analysis finished2023-12-12 13:25:55.772296
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

UNIQUE 

Distinct192
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T22:25:55.967957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.59375
Min length2

Characters and Unicode

Total characters1074
Distinct characters205
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique192 ?
Unique (%)100.0%

Sample

1st row영등포푸르지오
2nd row순영웰라이빌
3rd row영등포두산위브
4th row신길우성4차
5th row현대프라자
ValueCountFrequency (%)
영등포 2
 
1.0%
영등포푸르지오 1
 
0.5%
선유도삼성홈타운 1
 
0.5%
양평성원 1
 
0.5%
양평경남2차아너스빌 1
 
0.5%
삼호한숲 1
 
0.5%
에이스리버티움 1
 
0.5%
동보 1
 
0.5%
양평한신 1
 
0.5%
양평한솔 1
 
0.5%
Other values (185) 185
94.4%
2023-12-12T22:25:56.364179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 44
 
4.1%
차 33
 
3.1%
신 32
 
3.0%
산 29
 
2.7%
성 28
 
2.6%
래 28
 
2.6%
림 25
 
2.3%
당 24
 
2.2%
삼 22
 
2.0%
스 21
 
2.0%
Other values (195) 788
73.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1016
94.6%
Decimal Number 36
 
3.4%
Close Punctuation 6
 
0.6%
Open Punctuation 6
 
0.6%
Space Separator 5
 
0.5%
Uppercase Letter 4
 
0.4%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 44
 
4.3%
차 33
 
3.2%
신 32
 
3.1%
산 29
 
2.9%
성 28
 
2.8%
래 28
 
2.8%
림 25
 
2.5%
당 24
 
2.4%
삼 22
 
2.2%
스 21
 
2.1%
Other values (182) 730
71.9%
Decimal Number
ValueCountFrequency (%)
2 15
41.7%
1 7
19.4%
3 5
 
13.9%
5 3
 
8.3%
7 2
 
5.6%
4 2
 
5.6%
6 2
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
S 3
75.0%
K 1
 
25.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1016
94.6%
Common 53
 
4.9%
Latin 5
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 44
 
4.3%
차 33
 
3.2%
신 32
 
3.1%
산 29
 
2.9%
성 28
 
2.8%
래 28
 
2.8%
림 25
 
2.5%
당 24
 
2.4%
삼 22
 
2.2%
스 21
 
2.1%
Other values (182) 730
71.9%
Common
ValueCountFrequency (%)
2 15
28.3%
1 7
13.2%
) 6
 
11.3%
( 6
 
11.3%
3 5
 
9.4%
5
 
9.4%
5 3
 
5.7%
7 2
 
3.8%
4 2
 
3.8%
6 2
 
3.8%
Latin
ValueCountFrequency (%)
S 3
60.0%
K 1
 
20.0%
e 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1016
94.6%
ASCII 58
 
5.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 44
 
4.3%
차 33
 
3.2%
신 32
 
3.1%
산 29
 
2.9%
성 28
 
2.8%
래 28
 
2.8%
림 25
 
2.5%
당 24
 
2.4%
삼 22
 
2.2%
스 21
 
2.1%
Other values (182) 730
71.9%
ASCII
ValueCountFrequency (%)
2 15
25.9%
1 7
12.1%
) 6
 
10.3%
( 6
 
10.3%
3 5
 
8.6%
5
 
8.6%
5 3
 
5.2%
S 3
 
5.2%
7 2
 
3.4%
4 2
 
3.4%
Other values (3) 4
 
6.9%

주소
Text

UNIQUE 

Distinct192
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T22:25:56.713346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22.5
Mean length19.416667
Min length16

Characters and Unicode

Total characters3728
Distinct characters63
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

Unique192 ?
Unique (%)100.0%

Sample

1st row서울특별시 영등포구 도신로29길 28
2nd row서울특별시 영등포구 영등포로62길 42
3rd row서울특별시 영등포구 신길로60나길 9
4th row서울특별시 영등포구 영등포로64길 11
5th row서울특별시 영등포구 양산로 214
ValueCountFrequency (%)
서울특별시 192
25.0%
영등포구 192
25.0%
7 8
 
1.0%
6 7
 
0.9%
5 7
 
0.9%
선유서로 7
 
0.9%
가마산로 6
 
0.8%
13 6
 
0.8%
9 6
 
0.8%
당산로 5
 
0.7%
Other values (214) 331
43.2%
2023-12-12T22:25:57.209788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
579
15.5%
영 216
 
5.8%
서 205
 
5.5%
등 203
 
5.4%
포 203
 
5.4%
시 196
 
5.3%
로 192
 
5.2%
특 192
 
5.2%
별 192
 
5.2%
구 192
 
5.2%
Other values (53) 1358
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2540
68.1%
Decimal Number 601
 
16.1%
Space Separator 579
 
15.5%
Dash Punctuation 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 216
 
8.5%
서 205
 
8.1%
등 203
 
8.0%
포 203
 
8.0%
시 196
 
7.7%
로 192
 
7.6%
특 192
 
7.6%
별 192
 
7.6%
구 192
 
7.6%
울 192
 
7.6%
Other values (41) 557
21.9%
Decimal Number
ValueCountFrequency (%)
1 105
17.5%
2 99
16.5%
3 71
11.8%
4 67
11.1%
7 57
9.5%
5 53
8.8%
9 48
8.0%
6 43
7.2%
0 35
 
5.8%
8 23
 
3.8%
Space Separator
ValueCountFrequency (%)
579
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2540
68.1%
Common 1188
31.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 216
 
8.5%
서 205
 
8.1%
등 203
 
8.0%
포 203
 
8.0%
시 196
 
7.7%
로 192
 
7.6%
특 192
 
7.6%
별 192
 
7.6%
구 192
 
7.6%
울 192
 
7.6%
Other values (41) 557
21.9%
Common
ValueCountFrequency (%)
579
48.7%
1 105
 
8.8%
2 99
 
8.3%
3 71
 
6.0%
4 67
 
5.6%
7 57
 
4.8%
5 53
 
4.5%
9 48
 
4.0%
6 43
 
3.6%
0 35
 
2.9%
Other values (2) 31
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2540
68.1%
ASCII 1188
31.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
579
48.7%
1 105
 
8.8%
2 99
 
8.3%
3 71
 
6.0%
4 67
 
5.6%
7 57
 
4.8%
5 53
 
4.5%
9 48
 
4.0%
6 43
 
3.6%
0 35
 
2.9%
Other values (2) 31
 
2.6%
Hangul
ValueCountFrequency (%)
영 216
 
8.5%
서 205
 
8.1%
등 203
 
8.0%
포 203
 
8.0%
시 196
 
7.7%
로 192
 
7.6%
특 192
 
7.6%
별 192
 
7.6%
구 192
 
7.6%
울 192
 
7.6%
Other values (41) 557
21.9%

세대수
Real number (ℝ)

Distinct160
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean375.94271
Minimum34
Maximum2462
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T22:25:57.377337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile50.1
Q1161.5
median270
Q3470
95-th percentile1167.4
Maximum2462
Range2428
Interquartile range (IQR)308.5

Descriptive statistics

Standard deviation354.62031
Coefficient of variation (CV)0.94328284
Kurtosis8.0433489
Mean375.94271
Median Absolute Deviation (MAD)132
Skewness2.4389582
Sum72181
Variance125755.56
MonotonicityNot monotonic
2023-12-12T22:25:57.544479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198 3
 
1.6%
134 3
 
1.6%
212 3
 
1.6%
284 3
 
1.6%
360 3
 
1.6%
160 3
 
1.6%
299 2
 
1.0%
54 2
 
1.0%
164 2
 
1.0%
410 2
 
1.0%
Other values (150) 166
86.5%
ValueCountFrequency (%)
34 1
0.5%
36 1
0.5%
37 1
0.5%
38 2
1.0%
42 1
0.5%
43 1
0.5%
48 1
0.5%
49 2
1.0%
51 1
0.5%
54 2
1.0%
ValueCountFrequency (%)
2462 1
0.5%
1722 1
0.5%
1584 1
0.5%
1546 1
0.5%
1476 1
0.5%
1391 1
0.5%
1302 1
0.5%
1221 1
0.5%
1215 1
0.5%
1174 1
0.5%

전화
Text

MISSING 

Distinct188
Distinct (%)99.5%
Missing3
Missing (%)1.6%
Memory size1.6 KiB
2023-12-12T22:25:57.795547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.571429
Min length11

Characters and Unicode

Total characters2187
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)98.9%

Sample

1st row02-6745-2247
2nd row02-849-7740
3rd row02-841-8244
4th row02-849-1156
5th row02-2633-1760
ValueCountFrequency (%)
02-832-3982 2
 
1.1%
02-2672-0736 1
 
0.5%
02-833-6584 1
 
0.5%
02-6745-2247 1
 
0.5%
02-2632-0207 1
 
0.5%
02-2676-2465 1
 
0.5%
02-2672-9833 1
 
0.5%
02-2675-2467 1
 
0.5%
02-2068-9010 1
 
0.5%
02-2672-7151 1
 
0.5%
Other values (178) 178
94.2%
2023-12-12T22:25:58.147637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 399
18.2%
- 378
17.3%
0 288
13.2%
6 214
9.8%
8 173
7.9%
3 162
7.4%
7 159
 
7.3%
4 122
 
5.6%
1 103
 
4.7%
9 102
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1809
82.7%
Dash Punctuation 378
 
17.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 399
22.1%
0 288
15.9%
6 214
11.8%
8 173
9.6%
3 162
9.0%
7 159
 
8.8%
4 122
 
6.7%
1 103
 
5.7%
9 102
 
5.6%
5 87
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 378
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2187
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 399
18.2%
- 378
17.3%
0 288
13.2%
6 214
9.8%
8 173
7.9%
3 162
7.4%
7 159
 
7.3%
4 122
 
5.6%
1 103
 
4.7%
9 102
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2187
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 399
18.2%
- 378
17.3%
0 288
13.2%
6 214
9.8%
8 173
7.9%
3 162
7.4%
7 159
 
7.3%
4 122
 
5.6%
1 103
 
4.7%
9 102
 
4.7%

Interactions

2023-12-12T22:25:55.539175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T22:25:55.643347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:25:55.733137image/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

아파트명주소세대수전화
0영등포푸르지오서울특별시 영등포구 도신로29길 28246202-6745-2247
1순영웰라이빌서울특별시 영등포구 영등포로62길 4213602-849-7740
2영등포두산위브서울특별시 영등포구 신길로60나길 927102-841-8244
3신길우성4차서울특별시 영등포구 영등포로64길 1147602-849-1156
4현대프라자서울특별시 영등포구 양산로 21411502-2633-1760
5영등포경남아너스빌서울특별시 영등포구 양산로 17760002-2633-4779
6아크로타워스퀘어서울특별시 영등포구 국회대로54길 10122102-2068-5941
7브라운스톤영등포서울특별시 영등포구 버드나루로12가길 1311802-2677-6592
8영등포삼환서울특별시 영등포구 영중로 14552002-2677-1635
9당산푸르지오서울특별시 영등포구 영중로 15453802-2678-1489
아파트명주소세대수전화
182대림성원상떼빌서울특별시 영등포구 도신로 3222002-835-2850
183성락서울특별시 영등포구 대림로34다길 148002-849-3116
184대림우성2차서울특별시 영등포구 도림로47길 112002-834-0664
185대림우성서울특별시 영등포구 도림로 18743502-833-7186
186대림신동아서울특별시 영등포구 가마산로 31259102-832-3430
187대림현대2차서울특별시 영등포구 도신로4길 628002-834-8687
188대림현대1차서울특별시 영등포구 도신로4길 1447602-844-1417
189대림쌍용플래티넘S서울특별시 영등포구 대림로29길 1329102-831-5512
190문래 롯데캐슬서울특별시 영등포구 선유로9길 3049902-6949-1129
191영등포 자이르네서울특별시 영등포구 시흥대로 62521202-862-9174