Overview

Dataset statistics

Number of variables8
Number of observations478
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.9 KiB
Average record size in memory66.3 B

Variable types

Numeric2
Text5
Categorical1

Dataset

Description울산광역시 중구 아파트 현황으로 공동주택명, 세대수, 동수, 준공연도, 도로명주소, 지번주소 항목을 제공하고 있습니다.
URLhttps://www.data.go.kr/data/15106459/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:07:18.848674
Analysis finished2023-12-12 21:07:19.974254
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct478
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean239.5
Minimum1
Maximum478
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-13T06:07:20.034305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile24.85
Q1120.25
median239.5
Q3358.75
95-th percentile454.15
Maximum478
Range477
Interquartile range (IQR)238.5

Descriptive statistics

Standard deviation138.13098
Coefficient of variation (CV)0.57674729
Kurtosis-1.2
Mean239.5
Median Absolute Deviation (MAD)119.5
Skewness0
Sum114481
Variance19080.167
MonotonicityStrictly increasing
2023-12-13T06:07:20.146783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
316 1
 
0.2%
328 1
 
0.2%
327 1
 
0.2%
326 1
 
0.2%
325 1
 
0.2%
324 1
 
0.2%
323 1
 
0.2%
322 1
 
0.2%
321 1
 
0.2%
Other values (468) 468
97.9%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
478 1
0.2%
477 1
0.2%
476 1
0.2%
475 1
0.2%
474 1
0.2%
473 1
0.2%
472 1
0.2%
471 1
0.2%
470 1
0.2%
469 1
0.2%

공동주택명
Text

Distinct458
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-13T06:07:20.366259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length5.9748954
Min length3

Characters and Unicode

Total characters2856
Distinct characters294
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique443 ?
Unique (%)92.7%

Sample

1st row진흥아파트
2nd row우정아파트
3rd row동양아파트
4th row복산맨션
5th row우정맨션
ValueCountFrequency (%)
공동주택 9
 
1.7%
2차 8
 
1.5%
3차 5
 
0.9%
나이스빌 4
 
0.8%
대호하이빌 3
 
0.6%
1차 3
 
0.6%
에일린의 3
 
0.6%
우정lh 3
 
0.6%
아드리아 3
 
0.6%
뜰 3
 
0.6%
Other values (460) 489
91.7%
2023-12-13T06:07:20.705174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 165
 
5.8%
트 155
 
5.4%
빌 153
 
5.4%
파 141
 
4.9%
동 72
 
2.5%
차 70
 
2.5%
62
 
2.2%
리 61
 
2.1%
이 53
 
1.9%
성 50
 
1.8%
Other values (284) 1874
65.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2585
90.5%
Decimal Number 140
 
4.9%
Space Separator 62
 
2.2%
Uppercase Letter 30
 
1.1%
Close Punctuation 16
 
0.6%
Open Punctuation 15
 
0.5%
Other Symbol 4
 
0.1%
Lowercase Letter 3
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 165
 
6.4%
트 155
 
6.0%
빌 153
 
5.9%
파 141
 
5.5%
동 72
 
2.8%
차 70
 
2.7%
리 61
 
2.4%
이 53
 
2.1%
성 50
 
1.9%
라 47
 
1.8%
Other values (256) 1618
62.6%
Uppercase Letter
ValueCountFrequency (%)
A 6
20.0%
B 4
13.3%
K 3
10.0%
L 3
10.0%
H 3
10.0%
P 3
10.0%
I 2
 
6.7%
C 2
 
6.7%
R 1
 
3.3%
O 1
 
3.3%
Other values (2) 2
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 40
28.6%
2 36
25.7%
0 18
12.9%
3 16
 
11.4%
4 13
 
9.3%
5 8
 
5.7%
6 4
 
2.9%
8 2
 
1.4%
9 2
 
1.4%
7 1
 
0.7%
Space Separator
ValueCountFrequency (%)
62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2589
90.7%
Common 234
 
8.2%
Latin 33
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 165
 
6.4%
트 155
 
6.0%
빌 153
 
5.9%
파 141
 
5.4%
동 72
 
2.8%
차 70
 
2.7%
리 61
 
2.4%
이 53
 
2.0%
성 50
 
1.9%
라 47
 
1.8%
Other values (257) 1622
62.6%
Common
ValueCountFrequency (%)
62
26.5%
1 40
17.1%
2 36
15.4%
0 18
 
7.7%
) 16
 
6.8%
3 16
 
6.8%
( 15
 
6.4%
4 13
 
5.6%
5 8
 
3.4%
6 4
 
1.7%
Other values (4) 6
 
2.6%
Latin
ValueCountFrequency (%)
A 6
18.2%
B 4
12.1%
K 3
9.1%
L 3
9.1%
H 3
9.1%
e 3
9.1%
P 3
9.1%
I 2
 
6.1%
C 2
 
6.1%
R 1
 
3.0%
Other values (3) 3
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2585
90.5%
ASCII 267
 
9.3%
None 4
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 165
 
6.4%
트 155
 
6.0%
빌 153
 
5.9%
파 141
 
5.5%
동 72
 
2.8%
차 70
 
2.7%
리 61
 
2.4%
이 53
 
2.1%
성 50
 
1.9%
라 47
 
1.8%
Other values (256) 1618
62.6%
ASCII
ValueCountFrequency (%)
62
23.2%
1 40
15.0%
2 36
13.5%
0 18
 
6.7%
) 16
 
6.0%
3 16
 
6.0%
( 15
 
5.6%
4 13
 
4.9%
5 8
 
3.0%
A 6
 
2.2%
Other values (17) 37
13.9%
None
ValueCountFrequency (%)
㈜ 4
100.0%

세대수
Text

Distinct154
Distinct (%)32.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-13T06:07:20.985076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.1903766
Min length1

Characters and Unicode

Total characters1047
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

Unique100 ?
Unique (%)20.9%

Sample

1st row28
2nd row18
3rd row121
4th row36
5th row29
ValueCountFrequency (%)
16 42
 
8.8%
18 40
 
8.4%
19 39
 
8.2%
14 32
 
6.7%
12 19
 
4.0%
10 14
 
2.9%
8 14
 
2.9%
30 13
 
2.7%
17 11
 
2.3%
40 10
 
2.1%
Other values (144) 244
51.0%
2023-12-13T06:07:21.382591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 288
27.5%
4 114
 
10.9%
2 114
 
10.9%
8 107
 
10.2%
0 98
 
9.4%
6 92
 
8.8%
9 75
 
7.2%
3 69
 
6.6%
5 52
 
5.0%
7 35
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1044
99.7%
Other Punctuation 3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 288
27.6%
4 114
 
10.9%
2 114
 
10.9%
8 107
 
10.2%
0 98
 
9.4%
6 92
 
8.8%
9 75
 
7.2%
3 69
 
6.6%
5 52
 
5.0%
7 35
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1047
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 288
27.5%
4 114
 
10.9%
2 114
 
10.9%
8 107
 
10.2%
0 98
 
9.4%
6 92
 
8.8%
9 75
 
7.2%
3 69
 
6.6%
5 52
 
5.0%
7 35
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1047
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 288
27.5%
4 114
 
10.9%
2 114
 
10.9%
8 107
 
10.2%
0 98
 
9.4%
6 92
 
8.8%
9 75
 
7.2%
3 69
 
6.6%
5 52
 
5.0%
7 35
 
3.3%

동수
Real number (ℝ)

Distinct17
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8200837
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.3 KiB
2023-12-13T06:07:21.484289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile7
Maximum20
Range19
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.4556985
Coefficient of variation (CV)1.3492229
Kurtosis17.038074
Mean1.8200837
Median Absolute Deviation (MAD)0
Skewness3.9465586
Sum870
Variance6.0304553
MonotonicityNot monotonic
2023-12-13T06:07:21.586705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1 384
80.3%
2 38
 
7.9%
3 11
 
2.3%
4 9
 
1.9%
6 7
 
1.5%
11 5
 
1.0%
10 4
 
0.8%
8 4
 
0.8%
5 3
 
0.6%
7 3
 
0.6%
Other values (7) 10
 
2.1%
ValueCountFrequency (%)
1 384
80.3%
2 38
 
7.9%
3 11
 
2.3%
4 9
 
1.9%
5 3
 
0.6%
6 7
 
1.5%
7 3
 
0.6%
8 4
 
0.8%
9 2
 
0.4%
10 4
 
0.8%
ValueCountFrequency (%)
20 1
 
0.2%
16 1
 
0.2%
15 2
 
0.4%
14 1
 
0.2%
13 2
 
0.4%
12 1
 
0.2%
11 5
1.0%
10 4
0.8%
9 2
 
0.4%
8 4
0.8%

준공연도
Text

Distinct432
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-13T06:07:21.866113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9790795
Min length5

Characters and Unicode

Total characters4770
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

Unique392 ?
Unique (%)82.0%

Sample

1st row1975-11-21
2nd row1978-03-14
3rd row1978-04-27
4th row1978-05-20
5th row1978-07-04
ValueCountFrequency (%)
2010-03-30 4
 
0.8%
1991-09-19 3
 
0.6%
2004-06-01 3
 
0.6%
2002-10-10 3
 
0.6%
2013-10-28 3
 
0.6%
2002-11-02 2
 
0.4%
2005-05-12 2
 
0.4%
2003-09-04 2
 
0.4%
1987-03-10 2
 
0.4%
2015-11-04 2
 
0.4%
Other values (422) 452
94.6%
2023-12-13T06:07:22.317113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1138
23.9%
- 952
20.0%
1 721
15.1%
2 690
14.5%
9 327
 
6.9%
3 198
 
4.2%
8 180
 
3.8%
4 158
 
3.3%
7 143
 
3.0%
6 132
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3818
80.0%
Dash Punctuation 952
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1138
29.8%
1 721
18.9%
2 690
18.1%
9 327
 
8.6%
3 198
 
5.2%
8 180
 
4.7%
4 158
 
4.1%
7 143
 
3.7%
6 132
 
3.5%
5 131
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 952
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4770
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1138
23.9%
- 952
20.0%
1 721
15.1%
2 690
14.5%
9 327
 
6.9%
3 198
 
4.2%
8 180
 
3.8%
4 158
 
3.3%
7 143
 
3.0%
6 132
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4770
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1138
23.9%
- 952
20.0%
1 721
15.1%
2 690
14.5%
9 327
 
6.9%
3 198
 
4.2%
8 180
 
3.8%
4 158
 
3.3%
7 143
 
3.0%
6 132
 
2.8%

도로명주소
Text

Distinct474
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-13T06:07:22.702606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length8.3933054
Min length5

Characters and Unicode

Total characters4012
Distinct characters95
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique470 ?
Unique (%)98.3%

Sample

1st row중앙시장길 8
2nd row명륜로 107
3rd row북부순환도로 562
4th row옥교동길 15
5th row당산5길 10
ValueCountFrequency (%)
10 14
 
1.6%
함월16길 10
 
1.1%
25 10
 
1.1%
21 9
 
1.0%
14 9
 
1.0%
성안로 9
 
1.0%
30 9
 
1.0%
50 9
 
1.0%
유곡로 8
 
0.9%
옥교3길 8
 
0.9%
Other values (411) 801
89.4%
2023-12-13T06:07:23.238607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
939
23.4%
길 366
 
9.1%
1 361
 
9.0%
2 205
 
5.1%
3 179
 
4.5%
5 139
 
3.5%
4 137
 
3.4%
6 133
 
3.3%
로 111
 
2.8%
0 104
 
2.6%
Other values (85) 1338
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1519
37.9%
Decimal Number 1502
37.4%
Space Separator 939
23.4%
Dash Punctuation 50
 
1.2%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 366
24.1%
로 111
 
7.3%
함 99
 
6.5%
월 99
 
6.5%
성 78
 
5.1%
교 44
 
2.9%
안 44
 
2.9%
구 32
 
2.1%
신 31
 
2.0%
기 31
 
2.0%
Other values (71) 584
38.4%
Decimal Number
ValueCountFrequency (%)
1 361
24.0%
2 205
13.6%
3 179
11.9%
5 139
 
9.3%
4 137
 
9.1%
6 133
 
8.9%
0 104
 
6.9%
8 99
 
6.6%
7 79
 
5.3%
9 66
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
939
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2491
62.1%
Hangul 1519
37.9%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 366
24.1%
로 111
 
7.3%
함 99
 
6.5%
월 99
 
6.5%
성 78
 
5.1%
교 44
 
2.9%
안 44
 
2.9%
구 32
 
2.1%
신 31
 
2.0%
기 31
 
2.0%
Other values (71) 584
38.4%
Common
ValueCountFrequency (%)
939
37.7%
1 361
 
14.5%
2 205
 
8.2%
3 179
 
7.2%
5 139
 
5.6%
4 137
 
5.5%
6 133
 
5.3%
0 104
 
4.2%
8 99
 
4.0%
7 79
 
3.2%
Other values (2) 116
 
4.7%
Latin
ValueCountFrequency (%)
B 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2493
62.1%
Hangul 1519
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
939
37.7%
1 361
 
14.5%
2 205
 
8.2%
3 179
 
7.2%
5 139
 
5.6%
4 137
 
5.5%
6 133
 
5.3%
0 104
 
4.2%
8 99
 
4.0%
7 79
 
3.2%
Other values (4) 118
 
4.7%
Hangul
ValueCountFrequency (%)
길 366
24.1%
로 111
 
7.3%
함 99
 
6.5%
월 99
 
6.5%
성 78
 
5.1%
교 44
 
2.9%
안 44
 
2.9%
구 32
 
2.1%
신 31
 
2.0%
기 31
 
2.0%
Other values (71) 584
38.4%

지번주소
Text

Distinct473
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-13T06:07:23.649546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length9.1861925
Min length6

Characters and Unicode

Total characters4391
Distinct characters48
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique468 ?
Unique (%)97.9%

Sample

1st row중앙동 97-5
2nd row우정동 425-1
3rd row북정동 128-2
4th row복산1동 611
5th row우정동 285-1
ValueCountFrequency (%)
북정동 123
 
12.9%
태화동 52
 
5.5%
학성동 40
 
4.2%
성안동 33
 
3.5%
우정동 33
 
3.5%
반구2동 25
 
2.6%
중앙동 22
 
2.3%
반구동 22
 
2.3%
병영1동 17
 
1.8%
반구1동 17
 
1.8%
Other values (478) 570
59.7%
2023-12-13T06:07:24.267232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
574
13.1%
동 482
 
11.0%
- 420
 
9.6%
1 358
 
8.2%
2 245
 
5.6%
3 193
 
4.4%
4 188
 
4.3%
5 183
 
4.2%
7 171
 
3.9%
8 168
 
3.8%
Other values (38) 1409
32.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1972
44.9%
Other Letter 1423
32.4%
Space Separator 574
 
13.1%
Dash Punctuation 420
 
9.6%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 482
33.9%
정 156
 
11.0%
북 123
 
8.6%
성 74
 
5.2%
반 64
 
4.5%
구 64
 
4.5%
화 52
 
3.7%
태 52
 
3.7%
학 42
 
3.0%
안 33
 
2.3%
Other values (24) 281
19.7%
Decimal Number
ValueCountFrequency (%)
1 358
18.2%
2 245
12.4%
3 193
9.8%
4 188
9.5%
5 183
9.3%
7 171
8.7%
8 168
8.5%
6 165
8.4%
0 154
7.8%
9 147
7.5%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
574
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 420
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2966
67.5%
Hangul 1423
32.4%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 482
33.9%
정 156
 
11.0%
북 123
 
8.6%
성 74
 
5.2%
반 64
 
4.5%
구 64
 
4.5%
화 52
 
3.7%
태 52
 
3.7%
학 42
 
3.0%
안 33
 
2.3%
Other values (24) 281
19.7%
Common
ValueCountFrequency (%)
574
19.4%
- 420
14.2%
1 358
12.1%
2 245
8.3%
3 193
 
6.5%
4 188
 
6.3%
5 183
 
6.2%
7 171
 
5.8%
8 168
 
5.7%
6 165
 
5.6%
Other values (2) 301
10.1%
Latin
ValueCountFrequency (%)
B 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2968
67.6%
Hangul 1423
32.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
574
19.3%
- 420
14.2%
1 358
12.1%
2 245
8.3%
3 193
 
6.5%
4 188
 
6.3%
5 183
 
6.2%
7 171
 
5.8%
8 168
 
5.7%
6 165
 
5.6%
Other values (4) 303
10.2%
Hangul
ValueCountFrequency (%)
동 482
33.9%
정 156
 
11.0%
북 123
 
8.6%
성 74
 
5.2%
반 64
 
4.5%
구 64
 
4.5%
화 52
 
3.7%
태 52
 
3.7%
학 42
 
3.0%
안 33
 
2.3%
Other values (24) 281
19.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-08-29
478 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-29
2nd row2023-08-29
3rd row2023-08-29
4th row2023-08-29
5th row2023-08-29

Common Values

ValueCountFrequency (%)
2023-08-29 478
100.0%

Length

2023-12-13T06:07:24.433181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:07:24.531140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-29 478
100.0%

Interactions

2023-12-13T06:07:19.352429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:07:19.162746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:07:19.445805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:07:19.257043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:07:24.592843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호동수
번호1.0000.188
동수0.1881.000
2023-12-13T06:07:24.697897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호동수
번호1.000-0.004
동수-0.0041.000

Missing values

2023-12-13T06:07:19.833841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:07:19.935338image/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

번호공동주택명세대수동수준공연도도로명주소지번주소데이터기준일자
01진흥아파트2811975-11-21중앙시장길 8중앙동 97-52023-08-29
12우정아파트1811978-03-14명륜로 107우정동 425-12023-08-29
23동양아파트12131978-04-27북부순환도로 562북정동 128-22023-08-29
34복산맨션3611978-05-20옥교동길 15복산1동 6112023-08-29
45우정맨션2911978-07-04당산5길 10우정동 285-12023-08-29
56명석아파트4021978-08-02옥교10길 14학성동 464-92023-08-29
67중앙아파트3011979-01-26학산로 25-1학성동 429-22023-08-29
78성림아파트3911979-01-27옥교12길 111학성동 154-102023-08-29
89청강아파트4111979-04-16옥교3길 19중앙동 310-62023-08-29
910삼우아파트1811979-06-28명륜로 40우정동 284-32023-08-29
번호공동주택명세대수동수준공연도도로명주소지번주소데이터기준일자
468469참좋은가1312020-02-13내황7길 75반구동 796-42023-08-29
469470세한프리빌 5차912020-09-21구교8길 11반구동 54-102023-08-29
470471성안 에델하임 3차1612020-09-28함월13길 32성안동 393-12023-08-29
471472영우 트리지움3212020-11-04옥교15길 10학성동 470-42023-08-29
472473우정베르지움2412020-12-03강정길 5우정동 266-62023-08-29
473474성지아파트39032021-01-12도화골길 30복산동 186-12023-08-29
474475빌리브 울산40562021-05-10구교로 59학성동 349-152023-08-29
475476경남빌3412022-02-09학성공원8길 17학성동 203-122023-08-29
476477팰리스가든20145000남외2길 9남외동 510-42023-08-29
477478영우 트리지움2차32145097옥교15길 12학성동 470-192023-08-29