Overview

Dataset statistics

Number of variables22
Number of observations10000
Missing cells42528
Missing cells (%)19.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 MiB
Average record size in memory200.0 B

Variable types

Text6
Numeric15
Categorical1

Dataset

Description관리_동별_개요_PK,관리_주택대장_PK,건물_명,주_용도_코드,기타_용도,구조_코드,기타_구조,지붕_코드,건축_면적,연면적,지상_층_수,지하_층_수,높이,세대_수,가구_수,호_수,새주소_도로_코드,새주소_법정동_코드,새주소_지상지하_코드,새주소_본_번,새주소_부_번,작업_일자
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-15405/S/1/datasetView.do

Alerts

기타_용도 has 962 (9.6%) missing valuesMissing
기타_구조 has 4972 (49.7%) missing valuesMissing
지붕_코드 has 264 (2.6%) missing valuesMissing
새주소_도로_코드 has 8785 (87.8%) missing valuesMissing
새주소_법정동_코드 has 8785 (87.8%) missing valuesMissing
새주소_본_번 has 8786 (87.9%) missing valuesMissing
새주소_부_번 has 9769 (97.7%) missing valuesMissing
건축_면적 is highly skewed (γ1 = 76.38994428)Skewed
연면적 is highly skewed (γ1 = 69.30380003)Skewed
높이 is highly skewed (γ1 = 49.650635)Skewed
세대_수 is highly skewed (γ1 = 97.43962979)Skewed
가구_수 is highly skewed (γ1 = 57.12095493)Skewed
호_수 is highly skewed (γ1 = 60.15068933)Skewed
새주소_도로_코드 is highly skewed (γ1 = 33.01065644)Skewed
관리_동별_개요_PK has unique valuesUnique
건축_면적 has 3986 (39.9%) zerosZeros
연면적 has 1412 (14.1%) zerosZeros
지상_층_수 has 3306 (33.1%) zerosZeros
지하_층_수 has 6195 (62.0%) zerosZeros
높이 has 3483 (34.8%) zerosZeros
세대_수 has 9946 (99.5%) zerosZeros
가구_수 has 9554 (95.5%) zerosZeros
호_수 has 9518 (95.2%) zerosZeros
새주소_부_번 has 158 (1.6%) zerosZeros

Reproduction

Analysis started2024-05-18 01:52:08.570250
Analysis finished2024-05-18 01:52:10.956974
Duration2.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리_동별_개요_PK
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T10:52:11.506688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length15
Mean length14.3617
Min length7

Characters and Unicode

Total characters143617
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row11290-1000000000000000110871
2nd row11260-1000000000000000132205
3rd row11350-715
4th row11200-100005421
5th row11320-100008548
ValueCountFrequency (%)
11290-1000000000000000110871 1
 
< 0.1%
11530-100009107 1
 
< 0.1%
11260-100009970 1
 
< 0.1%
11380-100008473 1
 
< 0.1%
11290-1212 1
 
< 0.1%
11350-100006089 1
 
< 0.1%
11590-100004985 1
 
< 0.1%
11560-587 1
 
< 0.1%
11000-100003281 1
 
< 0.1%
11200-100006640 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-18T10:52:12.960361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 52548
36.6%
1 34602
24.1%
- 10000
 
7.0%
5 7653
 
5.3%
6 6361
 
4.4%
4 6313
 
4.4%
3 6151
 
4.3%
2 5799
 
4.0%
7 5564
 
3.9%
8 4510
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 133617
93.0%
Dash Punctuation 10000
 
7.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 52548
39.3%
1 34602
25.9%
5 7653
 
5.7%
6 6361
 
4.8%
4 6313
 
4.7%
3 6151
 
4.6%
2 5799
 
4.3%
7 5564
 
4.2%
8 4510
 
3.4%
9 4116
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 143617
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 52548
36.6%
1 34602
24.1%
- 10000
 
7.0%
5 7653
 
5.3%
6 6361
 
4.4%
4 6313
 
4.4%
3 6151
 
4.3%
2 5799
 
4.0%
7 5564
 
3.9%
8 4510
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 143617
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 52548
36.6%
1 34602
24.1%
- 10000
 
7.0%
5 7653
 
5.3%
6 6361
 
4.4%
4 6313
 
4.4%
3 6151
 
4.3%
2 5799
 
4.0%
7 5564
 
3.9%
8 4510
 
3.1%

관리_주택대장_PK
Text

Distinct3818
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-18T10:52:13.641090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length15
Mean length13.6131
Min length7

Characters and Unicode

Total characters136131
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

Unique2196 ?
Unique (%)22.0%

Sample

1st row11290-1000000000000000137508
2nd row11260-100018854
3rd row11350-510
4th row11200-100015413
5th row11320-100010983
ValueCountFrequency (%)
11710-3648 110
 
1.1%
11680-100048705 56
 
0.6%
11710-2633 51
 
0.5%
11170-100012223 45
 
0.4%
11710-100032624 32
 
0.3%
11680-100024062 31
 
0.3%
11740-100013061 31
 
0.3%
11440-100007621 26
 
0.3%
11380-100009263 24
 
0.2%
11350-100049230 23
 
0.2%
Other values (3808) 9571
95.7%
2024-05-18T10:52:14.692270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 45855
33.7%
1 34553
25.4%
- 10000
 
7.3%
2 7279
 
5.3%
5 7229
 
5.3%
4 6826
 
5.0%
3 6340
 
4.7%
6 6035
 
4.4%
7 4525
 
3.3%
8 4216
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 126131
92.7%
Dash Punctuation 10000
 
7.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45855
36.4%
1 34553
27.4%
2 7279
 
5.8%
5 7229
 
5.7%
4 6826
 
5.4%
3 6340
 
5.0%
6 6035
 
4.8%
7 4525
 
3.6%
8 4216
 
3.3%
9 3273
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 136131
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 45855
33.7%
1 34553
25.4%
- 10000
 
7.3%
2 7279
 
5.3%
5 7229
 
5.3%
4 6826
 
5.0%
3 6340
 
4.7%
6 6035
 
4.4%
7 4525
 
3.3%
8 4216
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 136131
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 45855
33.7%
1 34553
25.4%
- 10000
 
7.3%
2 7279
 
5.3%
5 7229
 
5.3%
4 6826
 
5.0%
3 6340
 
4.7%
6 6035
 
4.4%
7 4525
 
3.3%
8 4216
 
3.1%

건물_명
Text

Distinct2850
Distinct (%)28.7%
Missing83
Missing (%)0.8%
Memory size156.2 KiB
2024-05-18T10:52:15.599797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length32
Mean length5.2198245
Min length1

Characters and Unicode

Total characters51765
Distinct characters457
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2124 ?
Unique (%)21.4%

Sample

1st row101
2nd row지하주차장(공동주택)
3rd row101동
4th row덕현해밀
5th row205동
ValueCountFrequency (%)
101동 364
 
3.4%
상가동 339
 
3.1%
102동 314
 
2.9%
지하주차장 274
 
2.5%
103동 238
 
2.2%
104동 202
 
1.9%
상가 200
 
1.8%
105동 156
 
1.4%
106동 151
 
1.4%
경비실 137
 
1.3%
Other values (2674) 8448
78.1%
2024-05-18T10:52:17.135453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6124
 
11.8%
동 5736
 
11.1%
0 3817
 
7.4%
2 2426
 
4.7%
실 1600
 
3.1%
3 1401
 
2.7%
주 1093
 
2.1%
상 1027
 
2.0%
4 1026
 
2.0%
가 1023
 
2.0%
Other values (447) 26492
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30412
58.8%
Decimal Number 17457
33.7%
Space Separator 910
 
1.8%
Open Punctuation 619
 
1.2%
Dash Punctuation 618
 
1.2%
Close Punctuation 616
 
1.2%
Uppercase Letter 564
 
1.1%
Other Punctuation 520
 
1.0%
Math Symbol 26
 
0.1%
Connector Punctuation 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 5736
 
18.9%
실 1600
 
5.3%
주 1093
 
3.6%
상 1027
 
3.4%
가 1023
 
3.4%
지 931
 
3.1%
경 891
 
2.9%
시 831
 
2.7%
설 792
 
2.6%
비 780
 
2.6%
Other values (396) 15708
51.7%
Uppercase Letter
ValueCountFrequency (%)
B 114
20.2%
A 92
16.3%
D 74
13.1%
M 66
11.7%
F 65
11.5%
L 46
8.2%
P 22
 
3.9%
E 15
 
2.7%
C 15
 
2.7%
T 11
 
2.0%
Other values (12) 44
 
7.8%
Decimal Number
ValueCountFrequency (%)
1 6124
35.1%
0 3817
21.9%
2 2426
 
13.9%
3 1401
 
8.0%
4 1026
 
5.9%
5 754
 
4.3%
6 613
 
3.5%
7 497
 
2.8%
8 406
 
2.3%
9 393
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 358
68.8%
/ 121
 
23.3%
# 22
 
4.2%
. 16
 
3.1%
: 3
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
e 6
60.0%
k 1
 
10.0%
d 1
 
10.0%
h 1
 
10.0%
s 1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 609
98.4%
[ 10
 
1.6%
Close Punctuation
ValueCountFrequency (%)
) 606
98.4%
] 10
 
1.6%
Math Symbol
ValueCountFrequency (%)
~ 20
76.9%
+ 6
 
23.1%
Space Separator
ValueCountFrequency (%)
910
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 618
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 30412
58.8%
Common 20779
40.1%
Latin 574
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 5736
 
18.9%
실 1600
 
5.3%
주 1093
 
3.6%
상 1027
 
3.4%
가 1023
 
3.4%
지 931
 
3.1%
경 891
 
2.9%
시 831
 
2.7%
설 792
 
2.6%
비 780
 
2.6%
Other values (396) 15708
51.7%
Latin
ValueCountFrequency (%)
B 114
19.9%
A 92
16.0%
D 74
12.9%
M 66
11.5%
F 65
11.3%
L 46
8.0%
P 22
 
3.8%
E 15
 
2.6%
C 15
 
2.6%
T 11
 
1.9%
Other values (17) 54
9.4%
Common
ValueCountFrequency (%)
1 6124
29.5%
0 3817
18.4%
2 2426
 
11.7%
3 1401
 
6.7%
4 1026
 
4.9%
910
 
4.4%
5 754
 
3.6%
- 618
 
3.0%
6 613
 
3.0%
( 609
 
2.9%
Other values (14) 2481
11.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 30412
58.8%
ASCII 21353
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6124
28.7%
0 3817
17.9%
2 2426
 
11.4%
3 1401
 
6.6%
4 1026
 
4.8%
910
 
4.3%
5 754
 
3.5%
- 618
 
2.9%
6 613
 
2.9%
( 609
 
2.9%
Other values (41) 3055
14.3%
Hangul
ValueCountFrequency (%)
동 5736
 
18.9%
실 1600
 
5.3%
주 1093
 
3.6%
상 1027
 
3.4%
가 1023
 
3.4%
지 931
 
3.1%
경 891
 
2.9%
시 831
 
2.7%
설 792
 
2.6%
비 780
 
2.6%
Other values (396) 15708
51.7%

주_용도_코드
Text

Distinct55
Distinct (%)0.6%
Missing22
Missing (%)0.2%
Memory size156.2 KiB
2024-05-18T10:52:17.561369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters49890
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)0.2%

Sample

1st row02000
2nd row02000
3rd row02000
4th row02000
5th row02000
ValueCountFrequency (%)
02000 8744
87.6%
03000 338
 
3.4%
04000 331
 
3.3%
07000 167
 
1.7%
14000 67
 
0.7%
z3000 58
 
0.6%
z6000 36
 
0.4%
11000 26
 
0.3%
04010 19
 
0.2%
20000 19
 
0.2%
Other values (45) 173
 
1.7%
2024-05-18T10:52:18.460995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 39526
79.2%
2 8798
 
17.6%
4 482
 
1.0%
3 441
 
0.9%
1 219
 
0.4%
7 172
 
0.3%
Z 110
 
0.2%
9 64
 
0.1%
6 44
 
0.1%
5 18
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49780
99.8%
Uppercase Letter 110
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 39526
79.4%
2 8798
 
17.7%
4 482
 
1.0%
3 441
 
0.9%
1 219
 
0.4%
7 172
 
0.3%
9 64
 
0.1%
6 44
 
0.1%
5 18
 
< 0.1%
8 16
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
Z 110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49780
99.8%
Latin 110
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 39526
79.4%
2 8798
 
17.7%
4 482
 
1.0%
3 441
 
0.9%
1 219
 
0.4%
7 172
 
0.3%
9 64
 
0.1%
6 44
 
0.1%
5 18
 
< 0.1%
8 16
 
< 0.1%
Latin
ValueCountFrequency (%)
Z 110
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49890
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 39526
79.2%
2 8798
 
17.6%
4 482
 
1.0%
3 441
 
0.9%
1 219
 
0.4%
7 172
 
0.3%
Z 110
 
0.2%
9 64
 
0.1%
6 44
 
0.1%
5 18
 
< 0.1%

기타_용도
Text

MISSING 

Distinct1481
Distinct (%)16.4%
Missing962
Missing (%)9.6%
Memory size156.2 KiB
2024-05-18T10:52:19.194709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length66
Mean length6.6194955
Min length1

Characters and Unicode

Total characters59827
Distinct characters330
Distinct categories13 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1062 ?
Unique (%)11.8%

Sample

1st row지하주차장,기전실(공동주택)
2nd row아파트
3rd row공동주택(아파트)
4th row도시형생활주택(단지형다세대주택),오피스텔,1종근린생활시설(소매점)
5th row주민공동시설
ValueCountFrequency (%)
아파트 2384
24.3%
공동주택(아파트 962
 
9.8%
경비실 641
 
6.5%
근린생활시설 444
 
4.5%
지하주차장 369
 
3.8%
부대시설 332
 
3.4%
생활편익시설 166
 
1.7%
주민공동시설 139
 
1.4%
부대복리시설 131
 
1.3%
복리시설 123
 
1.3%
Other values (1376) 4119
42.0%
2024-05-18T10:52:20.498115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
트 3581
 
6.0%
아 3525
 
5.9%
파 3510
 
5.9%
시 3098
 
5.2%
설 2898
 
4.8%
주 2557
 
4.3%
실 2303
 
3.8%
, 2271
 
3.8%
동 1514
 
2.5%
( 1494
 
2.5%
Other values (320) 33076
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51786
86.6%
Other Punctuation 2521
 
4.2%
Open Punctuation 1495
 
2.5%
Close Punctuation 1490
 
2.5%
Decimal Number 1007
 
1.7%
Space Separator 773
 
1.3%
Uppercase Letter 583
 
1.0%
Dash Punctuation 150
 
0.3%
Lowercase Letter 7
 
< 0.1%
Math Symbol 6
 
< 0.1%
Other values (3) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 3581
 
6.9%
아 3525
 
6.8%
파 3510
 
6.8%
시 3098
 
6.0%
설 2898
 
5.6%
주 2557
 
4.9%
실 2303
 
4.4%
동 1514
 
2.9%
택 1482
 
2.9%
공 1471
 
2.8%
Other values (272) 25847
49.9%
Uppercase Letter
ValueCountFrequency (%)
D 166
28.5%
F 161
27.6%
M 161
27.6%
E 23
 
3.9%
A 16
 
2.7%
P 12
 
2.1%
V 12
 
2.1%
L 11
 
1.9%
G 6
 
1.0%
X 6
 
1.0%
Other values (4) 9
 
1.5%
Decimal Number
ValueCountFrequency (%)
2 413
41.0%
1 384
38.1%
3 36
 
3.6%
4 36
 
3.6%
5 35
 
3.5%
6 30
 
3.0%
0 25
 
2.5%
9 19
 
1.9%
7 15
 
1.5%
8 14
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 2271
90.1%
/ 168
 
6.7%
. 68
 
2.7%
# 6
 
0.2%
: 5
 
0.2%
? 2
 
0.1%
& 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
c 2
28.6%
f 1
14.3%
d 1
14.3%
m 1
14.3%
v 1
14.3%
t 1
14.3%
Open Punctuation
ValueCountFrequency (%)
( 1494
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1489
99.9%
] 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
+ 3
50.0%
~ 3
50.0%
Space Separator
ValueCountFrequency (%)
773
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 150
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 5
100.0%
Control
ValueCountFrequency (%)
3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51786
86.6%
Common 7451
 
12.5%
Latin 590
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 3581
 
6.9%
아 3525
 
6.8%
파 3510
 
6.8%
시 3098
 
6.0%
설 2898
 
5.6%
주 2557
 
4.9%
실 2303
 
4.4%
동 1514
 
2.9%
택 1482
 
2.9%
공 1471
 
2.8%
Other values (272) 25847
49.9%
Common
ValueCountFrequency (%)
, 2271
30.5%
( 1494
20.1%
) 1489
20.0%
773
 
10.4%
2 413
 
5.5%
1 384
 
5.2%
/ 168
 
2.3%
- 150
 
2.0%
. 68
 
0.9%
3 36
 
0.5%
Other values (18) 205
 
2.8%
Latin
ValueCountFrequency (%)
D 166
28.1%
F 161
27.3%
M 161
27.3%
E 23
 
3.9%
A 16
 
2.7%
P 12
 
2.0%
V 12
 
2.0%
L 11
 
1.9%
G 6
 
1.0%
X 6
 
1.0%
Other values (10) 16
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51786
86.6%
ASCII 8036
 
13.4%
CJK Compat 5
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
트 3581
 
6.9%
아 3525
 
6.8%
파 3510
 
6.8%
시 3098
 
6.0%
설 2898
 
5.6%
주 2557
 
4.9%
실 2303
 
4.4%
동 1514
 
2.9%
택 1482
 
2.9%
공 1471
 
2.8%
Other values (272) 25847
49.9%
ASCII
ValueCountFrequency (%)
, 2271
28.3%
( 1494
18.6%
) 1489
18.5%
773
 
9.6%
2 413
 
5.1%
1 384
 
4.8%
/ 168
 
2.1%
D 166
 
2.1%
F 161
 
2.0%
M 161
 
2.0%
Other values (37) 556
 
6.9%
CJK Compat
ValueCountFrequency (%)
㎡ 5
100.0%

구조_코드
Real number (ℝ)

Distinct22
Distinct (%)0.2%
Missing59
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean21.294538
Minimum10
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:52:20.990138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile21
Q121
median21
Q321
95-th percentile21
Maximum99
Range89
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.0874691
Coefficient of variation (CV)0.19194918
Kurtosis156.85351
Mean21.294538
Median Absolute Deviation (MAD)0
Skewness9.7392681
Sum211689
Variance16.707404
MonotonicityNot monotonic
2024-05-18T10:52:21.420930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
21 9428
94.3%
11 190
 
1.9%
42 123
 
1.2%
19 52
 
0.5%
26 42
 
0.4%
41 27
 
0.3%
31 19
 
0.2%
32 14
 
0.1%
99 11
 
0.1%
33 9
 
0.1%
Other values (12) 26
 
0.3%
(Missing) 59
 
0.6%
ValueCountFrequency (%)
10 3
 
< 0.1%
11 190
 
1.9%
12 2
 
< 0.1%
13 1
 
< 0.1%
19 52
 
0.5%
21 9428
94.3%
22 2
 
< 0.1%
26 42
 
0.4%
29 6
 
0.1%
31 19
 
0.2%
ValueCountFrequency (%)
99 11
 
0.1%
74 1
 
< 0.1%
63 1
 
< 0.1%
51 1
 
< 0.1%
43 3
 
< 0.1%
42 123
1.2%
41 27
 
0.3%
40 2
 
< 0.1%
39 3
 
< 0.1%
36 1
 
< 0.1%

기타_구조
Text

MISSING 

Distinct119
Distinct (%)2.4%
Missing4972
Missing (%)49.7%
Memory size156.2 KiB
2024-05-18T10:52:21.874477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length8
Mean length7.5346062
Min length2

Characters and Unicode

Total characters37884
Distinct characters88
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

Unique54 ?
Unique (%)1.1%

Sample

1st row철근콘크리트구조
2nd row철근콘크리트구조
3rd row철근콘크리트구조
4th row철근콘크리트구조
5th row철근콘크리트구조
ValueCountFrequency (%)
철근콘크리트구조 3265
63.4%
철근콘크리트조 642
 
12.5%
벽식구조 276
 
5.4%
철근콘크리트 138
 
2.7%
벽식 89
 
1.7%
철근콘크리트라멘조 74
 
1.4%
라멘조 70
 
1.4%
철근콘크리트벽식구조 69
 
1.3%
라멘구조 69
 
1.3%
철골철근콘크리트구조 62
 
1.2%
Other values (95) 394
 
7.7%
2024-05-18T10:52:22.886391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
조 4871
12.9%
철 4499
11.9%
트 4422
11.7%
리 4412
11.6%
근 4409
11.6%
콘 4408
11.6%
크 4407
11.6%
구 3935
10.4%
벽 517
 
1.4%
식 513
 
1.4%
Other values (78) 1491
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37627
99.3%
Space Separator 122
 
0.3%
Other Punctuation 46
 
0.1%
Close Punctuation 28
 
0.1%
Open Punctuation 28
 
0.1%
Math Symbol 21
 
0.1%
Uppercase Letter 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 4871
12.9%
철 4499
12.0%
트 4422
11.8%
리 4412
11.7%
근 4409
11.7%
콘 4408
11.7%
크 4407
11.7%
구 3935
10.5%
벽 517
 
1.4%
식 513
 
1.4%
Other values (69) 1234
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
C 6
50.0%
P 3
25.0%
R 3
25.0%
Other Punctuation
ValueCountFrequency (%)
, 45
97.8%
/ 1
 
2.2%
Space Separator
ValueCountFrequency (%)
122
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 28
100.0%
Math Symbol
ValueCountFrequency (%)
+ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37627
99.3%
Common 245
 
0.6%
Latin 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 4871
12.9%
철 4499
12.0%
트 4422
11.8%
리 4412
11.7%
근 4409
11.7%
콘 4408
11.7%
크 4407
11.7%
구 3935
10.5%
벽 517
 
1.4%
식 513
 
1.4%
Other values (69) 1234
 
3.3%
Common
ValueCountFrequency (%)
122
49.8%
, 45
 
18.4%
) 28
 
11.4%
( 28
 
11.4%
+ 21
 
8.6%
/ 1
 
0.4%
Latin
ValueCountFrequency (%)
C 6
50.0%
P 3
25.0%
R 3
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37627
99.3%
ASCII 257
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
조 4871
12.9%
철 4499
12.0%
트 4422
11.8%
리 4412
11.7%
근 4409
11.7%
콘 4408
11.7%
크 4407
11.7%
구 3935
10.5%
벽 517
 
1.4%
식 513
 
1.4%
Other values (69) 1234
 
3.3%
ASCII
ValueCountFrequency (%)
122
47.5%
, 45
 
17.5%
) 28
 
10.9%
( 28
 
10.9%
+ 21
 
8.2%
C 6
 
2.3%
P 3
 
1.2%
R 3
 
1.2%
/ 1
 
0.4%

지붕_코드
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)0.1%
Missing264
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean18.127671
Minimum10
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:52:23.315416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10
Q110
median10
Q310
95-th percentile90
Maximum90
Range80
Interquartile range (IQR)0

Descriptive statistics

Standard deviation24.079073
Coefficient of variation (CV)1.3283049
Kurtosis5.0144241
Mean18.127671
Median Absolute Deviation (MAD)0
Skewness2.6461292
Sum176491
Variance579.80178
MonotonicityNot monotonic
2024-05-18T10:52:23.761887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
10 8693
86.9%
90 981
 
9.8%
20 34
 
0.3%
30 14
 
0.1%
12 9
 
0.1%
11 4
 
< 0.1%
19 1
 
< 0.1%
(Missing) 264
 
2.6%
ValueCountFrequency (%)
10 8693
86.9%
11 4
 
< 0.1%
12 9
 
0.1%
19 1
 
< 0.1%
20 34
 
0.3%
30 14
 
0.1%
90 981
 
9.8%
ValueCountFrequency (%)
90 981
 
9.8%
30 14
 
0.1%
20 34
 
0.3%
19 1
 
< 0.1%
12 9
 
0.1%
11 4
 
< 0.1%
10 8693
86.9%

건축_면적
Real number (ℝ)

SKEWED  ZEROS 

Distinct4884
Distinct (%)48.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean377.74495
Minimum0
Maximum382032
Zeros3986
Zeros (%)39.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:52:24.314806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median36.558
Q3511.13
95-th percentile929.99596
Maximum382032
Range382032
Interquartile range (IQR)511.13

Descriptive statistics

Standard deviation4339.0349
Coefficient of variation (CV)11.486679
Kurtosis6344.1739
Mean377.74495
Median Absolute Deviation (MAD)36.558
Skewness76.389944
Sum3777449.5
Variance18827223
MonotonicityNot monotonic
2024-05-18T10:52:25.130484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3986
39.9%
595.2 50
 
0.5%
12.96 33
 
0.3%
8.64 16
 
0.2%
9.0 16
 
0.2%
13.5 15
 
0.1%
8.88 15
 
0.1%
60.48 15
 
0.1%
442.15 13
 
0.1%
16.48 12
 
0.1%
Other values (4874) 5829
58.3%
ValueCountFrequency (%)
0.0 3986
39.9%
0.0001 3
 
< 0.1%
0.001 4
 
< 0.1%
0.01 3
 
< 0.1%
0.03 1
 
< 0.1%
0.0973 1
 
< 0.1%
0.1 2
 
< 0.1%
0.28 2
 
< 0.1%
0.48 1
 
< 0.1%
0.74 1
 
< 0.1%
ValueCountFrequency (%)
382032.0 1
 
< 0.1%
188935.0 1
 
< 0.1%
31283.62 1
 
< 0.1%
21167.0 1
 
< 0.1%
19455.58 1
 
< 0.1%
18427.82 1
 
< 0.1%
16160.59 5
0.1%
15011.3 1
 
< 0.1%
10414.01 6
0.1%
9790.49 1
 
< 0.1%

연면적
Real number (ℝ)

SKEWED  ZEROS 

Distinct7562
Distinct (%)75.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5509.0837
Minimum-42.29
Maximum3025075
Zeros1412
Zeros (%)14.1%
Negative6
Negative (%)0.1%
Memory size166.0 KiB
2024-05-18T10:52:26.055552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-42.29
5-th percentile0
Q141.51
median994.755
Q36942.24
95-th percentile16428.626
Maximum3025075
Range3025117.3
Interquartile range (IQR)6900.73

Descriptive statistics

Standard deviation34694.427
Coefficient of variation (CV)6.2976765
Kurtosis5813.4076
Mean5509.0837
Median Absolute Deviation (MAD)994.755
Skewness69.3038
Sum55090837
Variance1.2037032 × 109
MonotonicityNot monotonic
2024-05-18T10:52:26.896850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1412
 
14.1%
12.96 38
 
0.4%
15700.7 36
 
0.4%
8.88 19
 
0.2%
8.64 18
 
0.2%
9.0 16
 
0.2%
13.5 15
 
0.1%
56.7 15
 
0.1%
11141.34 13
 
0.1%
12.0 12
 
0.1%
Other values (7552) 8406
84.1%
ValueCountFrequency (%)
-42.29 1
 
< 0.1%
-10.08 3
 
< 0.1%
-4.62 2
 
< 0.1%
0.0 1412
14.1%
1.74 3
 
< 0.1%
2.21 1
 
< 0.1%
3.37 1
 
< 0.1%
3.58 1
 
< 0.1%
3.63 1
 
< 0.1%
3.6887 1
 
< 0.1%
ValueCountFrequency (%)
3025075.0 1
 
< 0.1%
976073.0 1
 
< 0.1%
579313.272 1
 
< 0.1%
349406.2 5
0.1%
250393.851 1
 
< 0.1%
241931.5878 1
 
< 0.1%
186958.34 1
 
< 0.1%
184457.2 1
 
< 0.1%
170678.79 1
 
< 0.1%
168631.99 1
 
< 0.1%

지상_층_수
Real number (ℝ)

ZEROS 

Distinct51
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4685
Minimum0
Maximum65
Zeros3306
Zeros (%)33.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:52:27.834451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q315
95-th percentile27
Maximum65
Range65
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.6746663
Coefficient of variation (CV)1.2953962
Kurtosis0.58805351
Mean7.4685
Median Absolute Deviation (MAD)1
Skewness1.1909292
Sum74685
Variance93.599168
MonotonicityNot monotonic
2024-05-18T10:52:28.528658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3306
33.1%
1 2009
20.1%
15 534
 
5.3%
2 373
 
3.7%
12 254
 
2.5%
20 243
 
2.4%
18 234
 
2.3%
19 177
 
1.8%
14 174
 
1.7%
13 164
 
1.6%
Other values (41) 2532
25.3%
ValueCountFrequency (%)
0 3306
33.1%
1 2009
20.1%
2 373
 
3.7%
3 154
 
1.5%
4 117
 
1.2%
5 135
 
1.4%
6 162
 
1.6%
7 123
 
1.2%
8 59
 
0.6%
9 78
 
0.8%
ValueCountFrequency (%)
65 1
 
< 0.1%
56 1
 
< 0.1%
55 1
 
< 0.1%
50 1
 
< 0.1%
49 4
< 0.1%
48 2
< 0.1%
47 2
< 0.1%
46 3
< 0.1%
45 3
< 0.1%
43 1
 
< 0.1%

지하_층_수
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7112
Minimum0
Maximum21
Zeros6195
Zeros (%)62.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:52:29.195283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum21
Range21
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.1811579
Coefficient of variation (CV)1.6607958
Kurtosis15.571236
Mean0.7112
Median Absolute Deviation (MAD)0
Skewness2.651187
Sum7112
Variance1.3951341
MonotonicityNot monotonic
2024-05-18T10:52:29.686997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 6195
62.0%
1 1920
 
19.2%
2 1072
 
10.7%
3 481
 
4.8%
4 177
 
1.8%
5 93
 
0.9%
6 32
 
0.3%
7 22
 
0.2%
8 4
 
< 0.1%
9 2
 
< 0.1%
Other values (2) 2
 
< 0.1%
ValueCountFrequency (%)
0 6195
62.0%
1 1920
 
19.2%
2 1072
 
10.7%
3 481
 
4.8%
4 177
 
1.8%
5 93
 
0.9%
6 32
 
0.3%
7 22
 
0.2%
8 4
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
21 1
 
< 0.1%
15 1
 
< 0.1%
9 2
 
< 0.1%
8 4
 
< 0.1%
7 22
 
0.2%
6 32
 
0.3%
5 93
 
0.9%
4 177
 
1.8%
3 481
4.8%
2 1072
10.7%

높이
Real number (ℝ)

SKEWED  ZEROS 

Distinct1857
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.230143
Minimum-13.6
Maximum71000
Zeros3483
Zeros (%)34.8%
Negative1
Negative (%)< 0.1%
Memory size166.0 KiB
2024-05-18T10:52:30.320683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-13.6
5-th percentile0
Q10
median6.5
Q340.955
95-th percentile76.662
Maximum71000
Range71013.6
Interquartile range (IQR)40.955

Descriptive statistics

Standard deviation1146.431
Coefficient of variation (CV)24.798344
Kurtosis2584.2249
Mean46.230143
Median Absolute Deviation (MAD)6.5
Skewness49.650635
Sum462301.43
Variance1314304
MonotonicityNot monotonic
2024-05-18T10:52:31.004052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3483
34.8%
3.6 79
 
0.8%
3.5 70
 
0.7%
3.4 64
 
0.6%
5.0 57
 
0.6%
3.8 55
 
0.5%
3.0 48
 
0.5%
3.9 48
 
0.5%
4.0 48
 
0.5%
3.3 43
 
0.4%
Other values (1847) 6005
60.1%
ValueCountFrequency (%)
-13.6 1
 
< 0.1%
0.0 3483
34.8%
2.1 1
 
< 0.1%
2.25 3
 
< 0.1%
2.3 8
 
0.1%
2.315 2
 
< 0.1%
2.32 1
 
< 0.1%
2.375 1
 
< 0.1%
2.4 2
 
< 0.1%
2.45 1
 
< 0.1%
ValueCountFrequency (%)
71000.0 1
< 0.1%
53500.0 1
< 0.1%
50950.0 1
< 0.1%
44850.0 1
< 0.1%
25300.0 1
< 0.1%
199.54 1
< 0.1%
199.0 2
< 0.1%
184.0 1
< 0.1%
179.5 1
< 0.1%
168.8 2
< 0.1%

세대_수
Real number (ℝ)

SKEWED  ZEROS 

Distinct13
Distinct (%)0.1%
Missing41
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean0.63650969
Minimum0
Maximum4515
Zeros9946
Zeros (%)99.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:52:31.701360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum4515
Range4515
Interquartile range (IQR)0

Descriptive statistics

Standard deviation45.614289
Coefficient of variation (CV)71.66315
Kurtosis9637.2611
Mean0.63650969
Median Absolute Deviation (MAD)0
Skewness97.43963
Sum6339
Variance2080.6634
MonotonicityNot monotonic
2024-05-18T10:52:32.074451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 9946
99.5%
75 2
 
< 0.1%
138 1
 
< 0.1%
54 1
 
< 0.1%
96 1
 
< 0.1%
4515 1
 
< 0.1%
270 1
 
< 0.1%
144 1
 
< 0.1%
232 1
 
< 0.1%
122 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
(Missing) 41
 
0.4%
ValueCountFrequency (%)
0 9946
99.5%
54 1
 
< 0.1%
75 2
 
< 0.1%
96 1
 
< 0.1%
122 1
 
< 0.1%
138 1
 
< 0.1%
144 1
 
< 0.1%
149 1
 
< 0.1%
211 1
 
< 0.1%
232 1
 
< 0.1%
ValueCountFrequency (%)
4515 1
< 0.1%
270 1
< 0.1%
258 1
< 0.1%
232 1
< 0.1%
211 1
< 0.1%
149 1
< 0.1%
144 1
< 0.1%
138 1
< 0.1%
122 1
< 0.1%
96 1
< 0.1%

가구_수
Real number (ℝ)

SKEWED  ZEROS 

Distinct156
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6737
Minimum0
Maximum3226
Zeros9554
Zeros (%)95.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:52:32.711331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum3226
Range3226
Interquartile range (IQR)0

Descriptive statistics

Standard deviation40.167342
Coefficient of variation (CV)10.933757
Kurtosis4305.4708
Mean3.6737
Median Absolute Deviation (MAD)0
Skewness57.120955
Sum36737
Variance1613.4154
MonotonicityNot monotonic
2024-05-18T10:52:33.367869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9554
95.5%
36 13
 
0.1%
60 11
 
0.1%
24 10
 
0.1%
40 10
 
0.1%
48 10
 
0.1%
30 9
 
0.1%
84 9
 
0.1%
52 8
 
0.1%
20 8
 
0.1%
Other values (146) 358
 
3.6%
ValueCountFrequency (%)
0 9554
95.5%
1 8
 
0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 3
 
< 0.1%
5 5
 
0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
3226 1
< 0.1%
1425 1
< 0.1%
440 1
< 0.1%
430 1
< 0.1%
355 1
< 0.1%
340 1
< 0.1%
338 1
< 0.1%
304 1
< 0.1%
294 1
< 0.1%
268 1
< 0.1%

호_수
Real number (ℝ)

SKEWED  ZEROS 

Distinct131
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6883
Minimum0
Maximum3226
Zeros9518
Zeros (%)95.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:52:34.011591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum3226
Range3226
Interquartile range (IQR)0

Descriptive statistics

Standard deviation39.544425
Coefficient of variation (CV)14.709826
Kurtosis4593.5536
Mean2.6883
Median Absolute Deviation (MAD)0
Skewness60.150689
Sum26883
Variance1563.7615
MonotonicityNot monotonic
2024-05-18T10:52:34.447335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9518
95.2%
1 40
 
0.4%
8 27
 
0.3%
10 18
 
0.2%
2 18
 
0.2%
4 17
 
0.2%
5 16
 
0.2%
6 16
 
0.2%
7 16
 
0.2%
3 14
 
0.1%
Other values (121) 300
 
3.0%
ValueCountFrequency (%)
0 9518
95.2%
1 40
 
0.4%
2 18
 
0.2%
3 14
 
0.1%
4 17
 
0.2%
5 16
 
0.2%
6 16
 
0.2%
7 16
 
0.2%
8 27
 
0.3%
9 5
 
0.1%
ValueCountFrequency (%)
3226 1
< 0.1%
1425 1
< 0.1%
559 1
< 0.1%
413 2
< 0.1%
397 1
< 0.1%
355 1
< 0.1%
340 1
< 0.1%
338 1
< 0.1%
324 1
< 0.1%
294 1
< 0.1%

새주소_도로_코드
Real number (ℝ)

MISSING  SKEWED 

Distinct272
Distinct (%)22.4%
Missing8785
Missing (%)87.8%
Infinite0
Infinite (%)0.0%
Mean1.154439 × 1011
Minimum1.111041 × 1011
Maximum4.1285438 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:52:35.002813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111041 × 1011
5-th percentile1.121531 × 1011
Q11.14103 × 1011
median1.1530415 × 1011
Q31.1680306 × 1011
95-th percentile1.1740417 × 1011
Maximum4.1285438 × 1011
Range3.0175028 × 1011
Interquartile range (IQR)2.700063 × 109

Descriptive statistics

Standard deviation8.6951337 × 109
Coefficient of variation (CV)0.075319127
Kurtosis1130.0425
Mean1.154439 × 1011
Median Absolute Deviation (MAD)1.4988566 × 109
Skewness33.010656
Sum1.4026434 × 1014
Variance7.5605351 × 1019
MonotonicityNot monotonic
2024-05-18T10:52:35.666018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
116803122001 38
 
0.4%
113803005054 38
 
0.4%
115303352227 27
 
0.3%
116504163749 26
 
0.3%
115002005007 24
 
0.2%
117103000238 24
 
0.2%
117404858050 22
 
0.2%
117103352706 22
 
0.2%
116803122014 20
 
0.2%
113803111008 19
 
0.2%
Other values (262) 955
 
9.6%
(Missing) 8785
87.8%
ValueCountFrequency (%)
111104100122 2
 
< 0.1%
111104100174 1
 
< 0.1%
111403005011 5
0.1%
111403101002 1
 
< 0.1%
111404103144 1
 
< 0.1%
111404103147 1
 
< 0.1%
111404103236 1
 
< 0.1%
111703005022 8
0.1%
111703102004 1
 
< 0.1%
111704106107 9
0.1%
ValueCountFrequency (%)
412854379017 1
 
< 0.1%
117404858050 22
0.2%
117404858048 3
 
< 0.1%
117404858046 4
 
< 0.1%
117404172446 2
 
< 0.1%
117404172328 1
 
< 0.1%
117404172320 1
 
< 0.1%
117404172292 12
0.1%
117404172274 1
 
< 0.1%
117404172222 3
 
< 0.1%

새주소_법정동_코드
Real number (ℝ)

MISSING 

Distinct76
Distinct (%)6.3%
Missing8785
Missing (%)87.8%
Infinite0
Infinite (%)0.0%
Mean10954.478
Minimum10101
Maximum18201
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:52:36.373235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile10101
Q110301
median10702
Q311201
95-th percentile13201
Maximum18201
Range8100
Interquartile range (IQR)900

Descriptive statistics

Standard deviation1005.9866
Coefficient of variation (CV)0.091833365
Kurtosis11.300181
Mean10954.478
Median Absolute Deviation (MAD)401
Skewness2.778921
Sum13309691
Variance1012009
MonotonicityNot monotonic
2024-05-18T10:52:37.281974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10101 135
 
1.4%
10301 113
 
1.1%
10901 72
 
0.7%
10201 70
 
0.7%
10501 62
 
0.6%
10601 53
 
0.5%
11301 50
 
0.5%
11101 49
 
0.5%
10302 46
 
0.5%
10702 42
 
0.4%
Other values (66) 523
 
5.2%
(Missing) 8785
87.8%
ValueCountFrequency (%)
10101 135
1.4%
10201 70
0.7%
10202 25
 
0.2%
10301 113
1.1%
10302 46
 
0.5%
10303 6
 
0.1%
10401 14
 
0.1%
10403 1
 
< 0.1%
10501 62
0.6%
10502 11
 
0.1%
ValueCountFrequency (%)
18201 2
 
< 0.1%
17401 1
 
< 0.1%
17301 1
 
< 0.1%
17101 1
 
< 0.1%
16201 5
 
0.1%
15602 1
 
< 0.1%
13802 4
 
< 0.1%
13801 13
0.1%
13601 1
 
< 0.1%
13401 9
0.1%

새주소_지상지하_코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6036 
0
3964 

Length

Max length4
Median length4
Mean length2.8108
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row0
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
<NA> 6036
60.4%
0 3964
39.6%

Length

2024-05-18T10:52:38.444780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-18T10:52:38.905579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6036
60.4%
0 3964
39.6%

새주소_본_번
Real number (ℝ)

MISSING 

Distinct181
Distinct (%)14.9%
Missing8786
Missing (%)87.9%
Infinite0
Infinite (%)0.0%
Mean143.91598
Minimum1
Maximum2567
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:52:39.462681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q130
median72
Q3200
95-th percentile520.25
Maximum2567
Range2566
Interquartile range (IQR)170

Descriptive statistics

Standard deviation194.4283
Coefficient of variation (CV)1.3509848
Kurtosis33.788439
Mean143.91598
Median Absolute Deviation (MAD)53
Skewness4.1858224
Sum174714
Variance37802.366
MonotonicityNot monotonic
2024-05-18T10:52:39.953639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 46
 
0.5%
30 39
 
0.4%
17 32
 
0.3%
14 29
 
0.3%
50 28
 
0.3%
220 27
 
0.3%
40 25
 
0.2%
15 25
 
0.2%
160 22
 
0.2%
19 21
 
0.2%
Other values (171) 920
 
9.2%
(Missing) 8786
87.9%
ValueCountFrequency (%)
1 8
0.1%
3 2
 
< 0.1%
5 3
 
< 0.1%
6 17
0.2%
7 7
0.1%
8 7
0.1%
9 9
0.1%
10 12
0.1%
11 8
0.1%
12 11
0.1%
ValueCountFrequency (%)
2567 1
 
< 0.1%
2217 1
 
< 0.1%
1212 1
 
< 0.1%
1176 1
 
< 0.1%
1102 4
< 0.1%
882 1
 
< 0.1%
858 3
< 0.1%
767 3
< 0.1%
753 5
0.1%
720 1
 
< 0.1%

새주소_부_번
Real number (ℝ)

MISSING  ZEROS 

Distinct24
Distinct (%)10.4%
Missing9769
Missing (%)97.7%
Infinite0
Infinite (%)0.0%
Mean5.3852814
Minimum0
Maximum40
Zeros158
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:52:40.500032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile31
Maximum40
Range40
Interquartile range (IQR)6

Descriptive statistics

Standard deviation10.278874
Coefficient of variation (CV)1.9086978
Kurtosis3.4219505
Mean5.3852814
Median Absolute Deviation (MAD)0
Skewness2.0761539
Sum1244
Variance105.65526
MonotonicityNot monotonic
2024-05-18T10:52:41.047268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 158
 
1.6%
12 11
 
0.1%
16 6
 
0.1%
10 5
 
0.1%
38 5
 
0.1%
6 5
 
0.1%
31 4
 
< 0.1%
4 4
 
< 0.1%
13 4
 
< 0.1%
40 4
 
< 0.1%
Other values (14) 25
 
0.2%
(Missing) 9769
97.7%
ValueCountFrequency (%)
0 158
1.6%
2 1
 
< 0.1%
3 4
 
< 0.1%
4 4
 
< 0.1%
5 3
 
< 0.1%
6 5
 
0.1%
7 1
 
< 0.1%
10 5
 
0.1%
11 2
 
< 0.1%
12 11
 
0.1%
ValueCountFrequency (%)
40 4
< 0.1%
38 5
0.1%
36 1
 
< 0.1%
31 4
< 0.1%
29 1
 
< 0.1%
28 3
< 0.1%
27 2
 
< 0.1%
26 1
 
< 0.1%
23 1
 
< 0.1%
19 2
 
< 0.1%

작업_일자
Real number (ℝ)

Distinct670
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20168751
Minimum20111227
Maximum20240517
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-18T10:52:41.550670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20111227
5-th percentile20111227
Q120111227
median20170110
Q320221005
95-th percentile20240517
Maximum20240517
Range129290
Interquartile range (IQR)109778

Descriptive statistics

Standard deviation52665.144
Coefficient of variation (CV)0.0026112248
Kurtosis-1.7112574
Mean20168751
Median Absolute Deviation (MAD)58883
Skewness0.14038808
Sum2.0168751 × 1011
Variance2.7736173 × 109
MonotonicityNot monotonic
2024-05-18T10:52:41.967750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20111227 2870
28.7%
20240517 883
 
8.8%
20120207 736
 
7.4%
20211029 432
 
4.3%
20180927 291
 
2.9%
20120222 242
 
2.4%
20240102 202
 
2.0%
20240208 173
 
1.7%
20191203 106
 
1.1%
20230808 63
 
0.6%
Other values (660) 4002
40.0%
ValueCountFrequency (%)
20111227 2870
28.7%
20120102 1
 
< 0.1%
20120104 2
 
< 0.1%
20120105 1
 
< 0.1%
20120106 1
 
< 0.1%
20120110 1
 
< 0.1%
20120112 1
 
< 0.1%
20120113 2
 
< 0.1%
20120120 4
 
< 0.1%
20120125 1
 
< 0.1%
ValueCountFrequency (%)
20240517 883
8.8%
20240514 18
 
0.2%
20240511 10
 
0.1%
20240507 25
 
0.2%
20240425 22
 
0.2%
20240420 38
 
0.4%
20240417 10
 
0.1%
20240416 2
 
< 0.1%
20240411 12
 
0.1%
20240406 1
 
< 0.1%

Sample

관리_동별_개요_PK관리_주택대장_PK건물_명주_용도_코드기타_용도구조_코드기타_구조지붕_코드건축_면적연면적지상_층_수지하_층_수높이세대_수가구_수호_수새주소_도로_코드새주소_법정동_코드새주소_지상지하_코드새주소_본_번새주소_부_번작업_일자
4606711290-100000000000000011087111290-100000000000000013750810102000<NA>21<NA>10645.318883.6722065.3000<NA><NA><NA><NA><NA>20240327
4429911260-100000000000000013220511260-100018854지하주차장(공동주택)02000지하주차장,기전실(공동주택)21철근콘크리트구조100.028235.0877040.0000112603005028105020670<NA>20240102
1607011350-71511350-510101동02000아파트21<NA>101014.0115029.7915139.6000<NA><NA>0<NA><NA>20111227
3095911200-10000542111200-100015413덕현해밀02000공동주택(아파트)21철근콘크리트구조10991.589359.7810127.6000<NA><NA><NA><NA><NA>20140124
1514611320-10000854811320-100010983205동02000도시형생활주택(단지형다세대주택),오피스텔,1종근린생활시설(소매점)21<NA>10147.57740.267022.200411320412710110701038<NA>20180927
3383811650-10001289011650-100031619주민공동시설02000주민공동시설21철근콘크리트구조100.00.0000.0000<NA><NA><NA><NA><NA>20161013
3960911590-10000577311590-100008521201동 관리사무소02000관리사무소21<NA>100.0275.52200.0000<NA><NA><NA><NA><NA>20240411
1900711680-49911680-212관리동02000관리사무실,노인정21<NA>100.0246.32103.55000<NA><NA>0<NA><NA>20111227
2691111410-10000785011410-100006278404동02000MDF실21철근콘크리트구조100.022.504103.35000<NA><NA><NA><NA><NA>20190529
3581511620-10000792011620-100012423문고02000작은도서관21철근콘크리트구조100.077.61020.000011620416082410101<NA>19<NA>20200508
관리_동별_개요_PK관리_주택대장_PK건물_명주_용도_코드기타_용도구조_코드기타_구조지붕_코드건축_면적연면적지상_층_수지하_층_수높이세대_수가구_수호_수새주소_도로_코드새주소_법정동_코드새주소_지상지하_코드새주소_본_번새주소_부_번작업_일자
4128311740-10000695311740-100013061112동02000아파트21철근콘크리트구조10474.24228.7713040.5000<NA><NA><NA><NA><NA>20221123
1563311590-10000829011590-100019765커뮤니티시설02000복리시설(커뮤니티시설)21<NA>100.06245.0975030.0000<NA><NA><NA><NA><NA>20240102
4282611230-10000835411230-100011045관리사무소(2단지)02000<NA>21<NA>100.043.8100.0000<NA><NA><NA><NA><NA>20220812
4676011170-10000504211170-100012223경비실12-102000<NA>21<NA>1021.3218.0013.84000<NA><NA><NA><NA><NA>20240309
3149111200-10000703511200-100017931115동02000공동주택(아파트)21철근콘크리트구조10326.5813103.58914040.25000<NA><NA><NA><NA><NA>20190511
4078311740-10001078911740-100024984주민공동시설202000작은도서관,공유주방,농기구보관소,경비실21철근콘크리트구조100.0314.22010.0000117404858050103020101<NA>20211029
3320411000-10000951611000-100005830810동02000아파트21<NA>10394.376304.0620059.15000<NA><NA><NA><NA><NA>20240517
42711380-10000479311380-100004201독서실02000독서실21철근콘크리트구조100.058.56100.0000<NA><NA><NA><NA><NA>20120207
3508511710-100000000000000001390611710-1000000000000000025803방재실(관리사무소)02000부대시설21<NA>100.020.2955010.0000<NA><NA><NA><NA><NA>20230221
210011710-10002024911710-100032624부속동6102000펌프실,전기실-1(P1)21철근콘크리트구조100.0832.96030.0000<NA><NA><NA><NA><NA>20190104