Overview

Dataset statistics

Number of variables6
Number of observations150
Missing cells5
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory49.9 B

Variable types

Numeric1
Text4
DateTime1

Dataset

Description이 데이터는 서울특별시 동작구 소재에 있는 아파트 관리사무소에 관한 것입니다. 이 데이터에는 관리사무소의 주소, 전화번호, 팩스번호가 포함되어 있습니다.
URLhttps://www.data.go.kr/data/15037272/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
팩스번호 has 5 (3.3%) missing valuesMissing
연번 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:17:19.432774
Analysis finished2023-12-12 20:17:19.935475
Duration0.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct150
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.5
Minimum1
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T05:17:20.008183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.45
Q138.25
median75.5
Q3112.75
95-th percentile142.55
Maximum150
Range149
Interquartile range (IQR)74.5

Descriptive statistics

Standard deviation43.445368
Coefficient of variation (CV)0.57543534
Kurtosis-1.2
Mean75.5
Median Absolute Deviation (MAD)37.5
Skewness0
Sum11325
Variance1887.5
MonotonicityStrictly increasing
2023-12-13T05:17:20.170917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
96 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
105 1
 
0.7%
Other values (140) 140
93.3%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%

아파트명
Text

Distinct149
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T05:17:20.510063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length10
Mean length6.5733333
Min length2

Characters and Unicode

Total characters986
Distinct characters211
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique148 ?
Unique (%)98.7%

Sample

1st row노량진우성
2nd row노량진삼익
3rd row신동아리버파크
4th row노량진쌍용예가
5th row형인한강
ValueCountFrequency (%)
삼성 2
 
1.2%
래미안 2
 
1.2%
e편한세상 2
 
1.2%
상도 2
 
1.2%
이수역 2
 
1.2%
보라매삼성쉐르빌 1
 
0.6%
장은해그린 1
 
0.6%
보라매아카데미타워 1
 
0.6%
보라매코오롱하늘채 1
 
0.6%
대방현대1차 1
 
0.6%
Other values (146) 146
90.7%
2023-12-13T05:17:20.991265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 42
 
4.3%
상 35
 
3.5%
도 30
 
3.0%
동 28
 
2.8%
방 20
 
2.0%
스 20
 
2.0%
이 20
 
2.0%
신 18
 
1.8%
아 17
 
1.7%
차 17
 
1.7%
Other values (201) 739
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 910
92.3%
Decimal Number 29
 
2.9%
Uppercase Letter 18
 
1.8%
Space Separator 11
 
1.1%
Close Punctuation 5
 
0.5%
Open Punctuation 5
 
0.5%
Lowercase Letter 4
 
0.4%
Dash Punctuation 2
 
0.2%
Other Punctuation 1
 
0.1%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 42
 
4.6%
상 35
 
3.8%
도 30
 
3.3%
동 28
 
3.1%
방 20
 
2.2%
스 20
 
2.2%
이 20
 
2.2%
신 18
 
2.0%
아 17
 
1.9%
차 17
 
1.9%
Other values (180) 663
72.9%
Uppercase Letter
ValueCountFrequency (%)
C 6
33.3%
K 4
22.2%
H 2
 
11.1%
S 2
 
11.1%
R 1
 
5.6%
A 1
 
5.6%
P 1
 
5.6%
I 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
2 13
44.8%
1 10
34.5%
3 2
 
6.9%
0 2
 
6.9%
5 1
 
3.4%
4 1
 
3.4%
Space Separator
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 910
92.3%
Common 53
 
5.4%
Latin 23
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 42
 
4.6%
상 35
 
3.8%
도 30
 
3.3%
동 28
 
3.1%
방 20
 
2.2%
스 20
 
2.2%
이 20
 
2.2%
신 18
 
2.0%
아 17
 
1.9%
차 17
 
1.9%
Other values (180) 663
72.9%
Common
ValueCountFrequency (%)
2 13
24.5%
11
20.8%
1 10
18.9%
) 5
 
9.4%
( 5
 
9.4%
- 2
 
3.8%
3 2
 
3.8%
0 2
 
3.8%
' 1
 
1.9%
5 1
 
1.9%
Latin
ValueCountFrequency (%)
C 6
26.1%
e 4
17.4%
K 4
17.4%
H 2
 
8.7%
S 2
 
8.7%
R 1
 
4.3%
A 1
 
4.3%
P 1
 
4.3%
I 1
 
4.3%
Ⅱ 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 910
92.3%
ASCII 75
 
7.6%
Number Forms 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 42
 
4.6%
상 35
 
3.8%
도 30
 
3.3%
동 28
 
3.1%
방 20
 
2.2%
스 20
 
2.2%
이 20
 
2.2%
신 18
 
2.0%
아 17
 
1.9%
차 17
 
1.9%
Other values (180) 663
72.9%
ASCII
ValueCountFrequency (%)
2 13
17.3%
11
14.7%
1 10
13.3%
C 6
8.0%
) 5
 
6.7%
( 5
 
6.7%
e 4
 
5.3%
K 4
 
5.3%
H 2
 
2.7%
- 2
 
2.7%
Other values (10) 13
17.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

Distinct148
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T05:17:21.360258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length9.02
Min length5

Characters and Unicode

Total characters1353
Distinct characters69
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

Unique146 ?
Unique (%)97.3%

Sample

1st row만양로8길 50
2nd row만양로 84
3rd row만양로 19
4th row장승배기로16길 134
5th row만양로 36
ValueCountFrequency (%)
상도로 8
 
2.7%
동작대로29길 7
 
2.3%
40 6
 
2.0%
여의대방로10길 5
 
1.7%
서달로 5
 
1.7%
보라매로5길 5
 
1.7%
만양로 5
 
1.7%
22 5
 
1.7%
여의대방로44길 4
 
1.3%
47 4
 
1.3%
Other values (172) 246
82.0%
2023-12-13T05:17:21.877569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
150
 
11.1%
로 143
 
10.6%
길 107
 
7.9%
1 98
 
7.2%
2 95
 
7.0%
3 59
 
4.4%
5 52
 
3.8%
4 48
 
3.5%
0 47
 
3.5%
대 39
 
2.9%
Other values (59) 515
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 676
50.0%
Decimal Number 521
38.5%
Space Separator 150
 
11.1%
Dash Punctuation 5
 
0.4%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 143
21.2%
길 107
15.8%
대 39
 
5.8%
사 31
 
4.6%
당 29
 
4.3%
방 24
 
3.6%
의 21
 
3.1%
여 21
 
3.1%
상 19
 
2.8%
도 19
 
2.8%
Other values (46) 223
33.0%
Decimal Number
ValueCountFrequency (%)
1 98
18.8%
2 95
18.2%
3 59
11.3%
5 52
10.0%
4 48
9.2%
0 47
9.0%
7 34
 
6.5%
9 34
 
6.5%
6 30
 
5.8%
8 24
 
4.6%
Space Separator
ValueCountFrequency (%)
150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 677
50.0%
Hangul 676
50.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 143
21.2%
길 107
15.8%
대 39
 
5.8%
사 31
 
4.6%
당 29
 
4.3%
방 24
 
3.6%
의 21
 
3.1%
여 21
 
3.1%
상 19
 
2.8%
도 19
 
2.8%
Other values (46) 223
33.0%
Common
ValueCountFrequency (%)
150
22.2%
1 98
14.5%
2 95
14.0%
3 59
 
8.7%
5 52
 
7.7%
4 48
 
7.1%
0 47
 
6.9%
7 34
 
5.0%
9 34
 
5.0%
6 30
 
4.4%
Other values (3) 30
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 677
50.0%
Hangul 676
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
150
22.2%
1 98
14.5%
2 95
14.0%
3 59
 
8.7%
5 52
 
7.7%
4 48
 
7.1%
0 47
 
6.9%
7 34
 
5.0%
9 34
 
5.0%
6 30
 
4.4%
Other values (3) 30
 
4.4%
Hangul
ValueCountFrequency (%)
로 143
21.2%
길 107
15.8%
대 39
 
5.8%
사 31
 
4.6%
당 29
 
4.3%
방 24
 
3.6%
의 21
 
3.1%
여 21
 
3.1%
상 19
 
2.8%
도 19
 
2.8%
Other values (46) 223
33.0%

전화번호
Text

UNIQUE 

Distinct150
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T05:17:22.144462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length11.153333
Min length11

Characters and Unicode

Total characters1673
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)100.0%

Sample

1st row02-823-4532
2nd row02-815-6850
3rd row02-812-0322
4th row02-813-7510
5th row02-814-1925
ValueCountFrequency (%)
02-823-4532 1
 
0.7%
02-3486-1182 1
 
0.7%
02-582-1145 1
 
0.7%
02-584-5012 1
 
0.7%
02-882-0185 1
 
0.7%
02-436-5775 1
 
0.7%
02-824-9974 1
 
0.7%
02-826-2970 1
 
0.7%
02-823-1319 1
 
0.7%
02-825-2190 1
 
0.7%
Other values (140) 140
93.3%
2023-12-13T05:17:22.535832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 300
17.9%
2 292
17.5%
0 226
13.5%
8 172
10.3%
5 122
7.3%
1 120
 
7.2%
3 115
 
6.9%
4 101
 
6.0%
7 80
 
4.8%
9 72
 
4.3%
Other values (2) 73
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1372
82.0%
Dash Punctuation 300
 
17.9%
Other Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 292
21.3%
0 226
16.5%
8 172
12.5%
5 122
8.9%
1 120
8.7%
3 115
 
8.4%
4 101
 
7.4%
7 80
 
5.8%
9 72
 
5.2%
6 72
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 300
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1673
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 300
17.9%
2 292
17.5%
0 226
13.5%
8 172
10.3%
5 122
7.3%
1 120
 
7.2%
3 115
 
6.9%
4 101
 
6.0%
7 80
 
4.8%
9 72
 
4.3%
Other values (2) 73
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1673
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 300
17.9%
2 292
17.5%
0 226
13.5%
8 172
10.3%
5 122
7.3%
1 120
 
7.2%
3 115
 
6.9%
4 101
 
6.0%
7 80
 
4.8%
9 72
 
4.3%
Other values (2) 73
 
4.4%

팩스번호
Text

MISSING 

Distinct144
Distinct (%)99.3%
Missing5
Missing (%)3.3%
Memory size1.3 KiB
2023-12-13T05:17:22.814831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.193103
Min length11

Characters and Unicode

Total characters1623
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

Unique143 ?
Unique (%)98.6%

Sample

1st row02-823-4531
2nd row02-815-6851
3rd row02-812-2133
4th row02-813-7544
5th row02-814-1925
ValueCountFrequency (%)
02-3280-4805 2
 
1.4%
02-817-5142 1
 
0.7%
02-825-2191 1
 
0.7%
02-823-4531 1
 
0.7%
02-813-1406 1
 
0.7%
02-436-8998 1
 
0.7%
02-817-9469 1
 
0.7%
02-826-9999 1
 
0.7%
02-823-1320 1
 
0.7%
02-826-1262 1
 
0.7%
Other values (134) 134
92.4%
2023-12-13T05:17:23.219122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 290
17.9%
2 272
16.8%
0 216
13.3%
8 163
10.0%
5 114
 
7.0%
1 112
 
6.9%
3 108
 
6.7%
4 108
 
6.7%
6 92
 
5.7%
9 77
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1333
82.1%
Dash Punctuation 290
 
17.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 272
20.4%
0 216
16.2%
8 163
12.2%
5 114
8.6%
1 112
8.4%
3 108
 
8.1%
4 108
 
8.1%
6 92
 
6.9%
9 77
 
5.8%
7 71
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 290
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1623
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 290
17.9%
2 272
16.8%
0 216
13.3%
8 163
10.0%
5 114
 
7.0%
1 112
 
6.9%
3 108
 
6.7%
4 108
 
6.7%
6 92
 
5.7%
9 77
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1623
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 290
17.9%
2 272
16.8%
0 216
13.3%
8 163
10.0%
5 114
 
7.0%
1 112
 
6.9%
3 108
 
6.7%
4 108
 
6.7%
6 92
 
5.7%
9 77
 
4.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2023-07-06 00:00:00
Maximum2023-07-06 00:00:00
2023-12-13T05:17:23.379131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:17:23.472726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T05:17:19.667752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T05:17:19.779955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:17:19.888714image/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

연번아파트명도로명주소전화번호팩스번호데이터기준일자
01노량진우성만양로8길 5002-823-453202-823-45312023-07-06
12노량진삼익만양로 8402-815-685002-815-68512023-07-06
23신동아리버파크만양로 1902-812-032202-812-21332023-07-06
34노량진쌍용예가장승배기로16길 13402-813-751002-813-75442023-07-06
45형인한강만양로 3602-814-192502-814-19252023-07-06
56노량진장승배기로18길 2702-813-2844<NA>2023-07-06
67극동강변매봉로 15802-813-044902-813-04492023-07-06
78본동신동아매봉로 13402-825-231802-826-12912023-07-06
89한강쌍용노량진로24길 202-822-674002-822-67412023-07-06
910유원강변노량진로23가길 1602-824-941402-825-94142023-07-06
연번아파트명도로명주소전화번호팩스번호데이터기준일자
140141이수자이사당로 30002-597-5116,512502-597-51172023-07-06
141142동작상떼빌신대방1가길 3802-3289-111302-3289-11142023-07-06
142143삼성보라매옴니타워보라매로5길 2302-836-482802-845-75832023-07-06
143144보라매현대(한국컴퓨터)보라매로5길 3502-835-349402-835-18482023-07-06
144145보라매삼성쉐르빌보라매로5길 4302-848-520302-848-52042023-07-06
145146롯데타워보라매로5길 5102-846-970102-846-97062023-07-06
146147보라매나산스위트보라매로5가길 2402-835-703002-835-70312023-07-06
147148보라매아카데미타워보라매로5가길 1602-831-664902-831-66622023-07-06
148149캐릭터그린빌보라매로5가길 702-833-475102-833-47522023-07-06
149150동작협성휴포레시그니처시흥대로 60602-849-883402-849-88352023-07-06