Overview

Dataset statistics

Number of variables68
Number of observations10000
Missing cells56837
Missing cells (%)8.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 MiB
Average record size in memory595.0 B

Variable types

Numeric38
Text9
Categorical16
Unsupported1
DateTime4

Dataset

Description경상남도 김해시 건축물 현황(건축물대장 표제부)대한 데이터로 번지주소,도로명주소,위도,경도 등의 항목을 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15033374

Alerts

새주소지상지하코드 has constant value ""Constant
특수지명 is highly imbalanced (97.8%)Imbalance
블록 is highly imbalanced (98.1%)Imbalance
로트 is highly imbalanced (98.3%)Imbalance
새주소도로코드 is highly imbalanced (56.7%)Imbalance
주부속구분코드 is highly imbalanced (52.8%)Imbalance
주부속구분코드명 is highly imbalanced (52.8%)Imbalance
허가번호기관코드명 is highly imbalanced (59.9%)Imbalance
허가번호구분코드명 is highly imbalanced (62.8%)Imbalance
건물명 has 8252 (82.5%) missing valuesMissing
새주소법정동코드 has 891 (8.9%) missing valuesMissing
새주소본번 has 845 (8.5%) missing valuesMissing
새주소부번 has 3559 (35.6%) missing valuesMissing
동명칭 has 7998 (80.0%) missing valuesMissing
허가일 has 2902 (29.0%) missing valuesMissing
착공일 has 3578 (35.8%) missing valuesMissing
사용승인일 has 414 (4.1%) missing valuesMissing
허가번호년 has 6215 (62.2%) missing valuesMissing
허가번호기관코드 has 6243 (62.4%) missing valuesMissing
허가번호구분코드 has 6213 (62.1%) missing valuesMissing
내진능력 has 9682 (96.8%) missing valuesMissing
is highly skewed (γ1 = 25.53503491)Skewed
외필지수 is highly skewed (γ1 = 21.2684125)Skewed
대지면적(제곱미터) is highly skewed (γ1 = 33.09028291)Skewed
가구수(가구) is highly skewed (γ1 = 22.94179829)Skewed
부속건축물수 is highly skewed (γ1 = 82.95945178)Skewed
부속건축물면적(제곱미터) is highly skewed (γ1 = 31.86445799)Skewed
옥내기계식대수(대) is highly skewed (γ1 = 29.29269869)Skewed
옥내기계식면적(제곱미터) is highly skewed (γ1 = 26.12146288)Skewed
옥외기계식대수(대) is highly skewed (γ1 = 46.55489768)Skewed
옥외기계식면적(제곱미터) is highly skewed (γ1 = 36.82845146)Skewed
옥내자주식대수(대) is highly skewed (γ1 = 24.04745033)Skewed
옥외자주식대수(대) is highly skewed (γ1 = 27.37684592)Skewed
옥외자주식면적(제곱미터) is highly skewed (γ1 = 31.74636092)Skewed
호수(호) is highly skewed (γ1 = 29.50859297)Skewed
순번 has unique valuesUnique
관리건축물대장 has unique valuesUnique
주용도코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
has 152 (1.5%) zerosZeros
has 2370 (23.7%) zerosZeros
외필지수 has 9044 (90.4%) zerosZeros
새주소부번 has 2019 (20.2%) zerosZeros
대지면적(제곱미터) has 4054 (40.5%) zerosZeros
건축면적(제곱미터) has 399 (4.0%) zerosZeros
건폐율(퍼센트) has 4071 (40.7%) zerosZeros
용적률산정연면적(제곱미터) has 193 (1.9%) zerosZeros
용적률(퍼센트) has 4072 (40.7%) zerosZeros
세대수(세대) has 9083 (90.8%) zerosZeros
가구수(가구) has 5000 (50.0%) zerosZeros
높이(미터) has 3396 (34.0%) zerosZeros
지상층수 has 127 (1.3%) zerosZeros
지하층수 has 9043 (90.4%) zerosZeros
승용승강기수 has 9472 (94.7%) zerosZeros
비상용승강기수 has 9749 (97.5%) zerosZeros
부속건축물수 has 8601 (86.0%) zerosZeros
부속건축물면적(제곱미터) has 8616 (86.2%) zerosZeros
총동연면적(제곱미터) has 157 (1.6%) zerosZeros
옥내기계식대수(대) has 9951 (99.5%) zerosZeros
옥내기계식면적(제곱미터) has 9956 (99.6%) zerosZeros
옥외기계식대수(대) has 9987 (99.9%) zerosZeros
옥외기계식면적(제곱미터) has 9988 (99.9%) zerosZeros
옥내자주식대수(대) has 9124 (91.2%) zerosZeros
옥내자주식면적(제곱미터) has 9161 (91.6%) zerosZeros
옥외자주식대수(대) has 5909 (59.1%) zerosZeros
옥외자주식면적(제곱미터) has 5989 (59.9%) zerosZeros
호수(호) has 9787 (97.9%) zerosZeros

Reproduction

Analysis started2023-12-10 23:24:09.682790
Analysis finished2023-12-10 23:24:12.105002
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12453.874
Minimum3
Maximum25058
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:12.173700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile1174.95
Q16081.25
median12550.5
Q318730.5
95-th percentile23742.25
Maximum25058
Range25055
Interquartile range (IQR)12649.25

Descriptive statistics

Standard deviation7262.6009
Coefficient of variation (CV)0.58315999
Kurtosis-1.2101211
Mean12453.874
Median Absolute Deviation (MAD)6326.5
Skewness-0.0017462813
Sum1.2453874 × 108
Variance52745372
MonotonicityNot monotonic
2023-12-11T08:24:12.294211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4883 1
 
< 0.1%
960 1
 
< 0.1%
13889 1
 
< 0.1%
19305 1
 
< 0.1%
2363 1
 
< 0.1%
11397 1
 
< 0.1%
11677 1
 
< 0.1%
10926 1
 
< 0.1%
9811 1
 
< 0.1%
4174 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
3 1
< 0.1%
7 1
< 0.1%
9 1
< 0.1%
14 1
< 0.1%
16 1
< 0.1%
18 1
< 0.1%
22 1
< 0.1%
25 1
< 0.1%
27 1
< 0.1%
28 1
< 0.1%
ValueCountFrequency (%)
25058 1
< 0.1%
25057 1
< 0.1%
25054 1
< 0.1%
25051 1
< 0.1%
25042 1
< 0.1%
25039 1
< 0.1%
25036 1
< 0.1%
25033 1
< 0.1%
25032 1
< 0.1%
25031 1
< 0.1%
Distinct8888
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:24:12.520635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length20.9657
Min length11

Characters and Unicode

Total characters209657
Distinct characters118
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

Unique8324 ?
Unique (%)83.2%

Sample

1st row경상남도 김해시 내동 1083-10번지
2nd row경상남도 김해시 내동 530번지
3rd row경상남도 김해시 외동 1199-3번지
4th row경상남도 김해시 무계동 491번지
5th row경상남도 김해시 흥동 322-2번지
ValueCountFrequency (%)
경상남도 10000
23.2%
김해시 10000
23.2%
진영읍 1701
 
4.0%
주촌면 1016
 
2.4%
진영리 552
 
1.3%
삼방동 502
 
1.2%
내동 451
 
1.0%
외동 403
 
0.9%
동상동 395
 
0.9%
어방동 390
 
0.9%
Other values (7105) 17607
40.9%
2023-12-11T08:24:12.879249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33017
 
15.7%
10529
 
5.0%
10466
 
5.0%
10015
 
4.8%
10010
 
4.8%
10008
 
4.8%
10008
 
4.8%
10000
 
4.8%
10000
 
4.8%
9847
 
4.7%
Other values (108) 85757
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 128153
61.1%
Decimal Number 40803
 
19.5%
Space Separator 33017
 
15.7%
Dash Punctuation 7662
 
3.7%
Uppercase Letter 22
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10529
 
8.2%
10466
 
8.2%
10015
 
7.8%
10010
 
7.8%
10008
 
7.8%
10008
 
7.8%
10000
 
7.8%
10000
 
7.8%
9847
 
7.7%
8038
 
6.3%
Other values (93) 29232
22.8%
Decimal Number
ValueCountFrequency (%)
1 9241
22.6%
2 4881
12.0%
3 4116
10.1%
4 3759
9.2%
6 3543
 
8.7%
5 3526
 
8.6%
0 3114
 
7.6%
7 3111
 
7.6%
8 2760
 
6.8%
9 2752
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
L 8
36.4%
B 8
36.4%
A 6
27.3%
Space Separator
ValueCountFrequency (%)
33017
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7662
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 128153
61.1%
Common 81482
38.9%
Latin 22
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10529
 
8.2%
10466
 
8.2%
10015
 
7.8%
10010
 
7.8%
10008
 
7.8%
10008
 
7.8%
10000
 
7.8%
10000
 
7.8%
9847
 
7.7%
8038
 
6.3%
Other values (93) 29232
22.8%
Common
ValueCountFrequency (%)
33017
40.5%
1 9241
 
11.3%
- 7662
 
9.4%
2 4881
 
6.0%
3 4116
 
5.1%
4 3759
 
4.6%
6 3543
 
4.3%
5 3526
 
4.3%
0 3114
 
3.8%
7 3111
 
3.8%
Other values (2) 5512
 
6.8%
Latin
ValueCountFrequency (%)
L 8
36.4%
B 8
36.4%
A 6
27.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 128153
61.1%
ASCII 81504
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33017
40.5%
1 9241
 
11.3%
- 7662
 
9.4%
2 4881
 
6.0%
3 4116
 
5.1%
4 3759
 
4.6%
6 3543
 
4.3%
5 3526
 
4.3%
0 3114
 
3.8%
7 3111
 
3.8%
Other values (5) 5534
 
6.8%
Hangul
ValueCountFrequency (%)
10529
 
8.2%
10466
 
8.2%
10015
 
7.8%
10010
 
7.8%
10008
 
7.8%
10008
 
7.8%
10000
 
7.8%
10000
 
7.8%
9847
 
7.7%
8038
 
6.3%
Other values (93) 29232
22.8%


Real number (ℝ)

ZEROS 

Distinct1507
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean587.3247
Minimum0
Maximum6820
Zeros152
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:13.006563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile33
Q1229.75
median496
Q3890
95-th percentile1428
Maximum6820
Range6820
Interquartile range (IQR)660.25

Descriptive statistics

Standard deviation445.47269
Coefficient of variation (CV)0.7584777
Kurtosis5.7793763
Mean587.3247
Median Absolute Deviation (MAD)304
Skewness1.1420023
Sum5873247
Variance198445.92
MonotonicityNot monotonic
2023-12-11T08:24:13.145699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 152
 
1.5%
1417 52
 
0.5%
319 40
 
0.4%
275 39
 
0.4%
700 36
 
0.4%
312 35
 
0.4%
268 32
 
0.3%
1099 31
 
0.3%
256 29
 
0.3%
162 29
 
0.3%
Other values (1497) 9525
95.2%
ValueCountFrequency (%)
0 152
1.5%
1 2
 
< 0.1%
2 12
 
0.1%
3 5
 
0.1%
4 6
 
0.1%
5 6
 
0.1%
6 8
 
0.1%
7 10
 
0.1%
8 13
 
0.1%
9 17
 
0.2%
ValueCountFrequency (%)
6820 1
< 0.1%
5384 1
< 0.1%
5357 1
< 0.1%
1974 1
< 0.1%
1923 2
< 0.1%
1909 1
< 0.1%
1893 1
< 0.1%
1891 1
< 0.1%
1885 2
< 0.1%
1884 1
< 0.1%


Real number (ℝ)

SKEWED  ZEROS 

Distinct149
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1952
Minimum0
Maximum1772
Zeros2370
Zeros (%)23.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:13.284491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q38
95-th percentile22
Maximum1772
Range1772
Interquartile range (IQR)7

Descriptive statistics

Standard deviation38.345862
Coefficient of variation (CV)4.6790636
Kurtosis839.4614
Mean8.1952
Median Absolute Deviation (MAD)3
Skewness25.535035
Sum81952
Variance1470.4051
MonotonicityNot monotonic
2023-12-11T08:24:13.416722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2370
23.7%
1 1249
12.5%
2 873
 
8.7%
3 730
 
7.3%
4 626
 
6.3%
5 498
 
5.0%
6 443
 
4.4%
7 419
 
4.2%
9 343
 
3.4%
8 339
 
3.4%
Other values (139) 2110
21.1%
ValueCountFrequency (%)
0 2370
23.7%
1 1249
12.5%
2 873
 
8.7%
3 730
 
7.3%
4 626
 
6.3%
5 498
 
5.0%
6 443
 
4.4%
7 419
 
4.2%
8 339
 
3.4%
9 343
 
3.4%
ValueCountFrequency (%)
1772 1
< 0.1%
1121 1
< 0.1%
1106 1
< 0.1%
1105 1
< 0.1%
1083 1
< 0.1%
914 1
< 0.1%
912 1
< 0.1%
862 1
< 0.1%
782 1
< 0.1%
781 1
< 0.1%
Distinct7974
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:24:13.694656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length19.9193
Min length1

Characters and Unicode

Total characters199193
Distinct characters126
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

Unique7437 ?
Unique (%)74.4%

Sample

1st row 경상남도 김해시 경원로11번길 31-10
2nd row 경상남도 김해시 금관대로 1269-1
3rd row 경상남도 김해시 함박로45번길 23-11
4th row
5th row 경상남도 김해시 전하로124번길 38-15
ValueCountFrequency (%)
경상남도 8916
23.4%
김해시 8916
23.4%
진영읍 1478
 
3.9%
주촌면 918
 
2.4%
김해대로 226
 
0.6%
분성로 144
 
0.4%
진영로 131
 
0.3%
서부로 114
 
0.3%
서부로1499번길 113
 
0.3%
9 105
 
0.3%
Other values (3764) 17097
44.8%
2023-12-11T08:24:14.101875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39242
19.7%
1 10245
 
5.1%
9815
 
4.9%
9730
 
4.9%
8953
 
4.5%
8931
 
4.5%
8916
 
4.5%
8916
 
4.5%
8916
 
4.5%
8647
 
4.3%
Other values (116) 76882
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111404
55.9%
Decimal Number 44228
 
22.2%
Space Separator 39242
 
19.7%
Dash Punctuation 4319
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9815
 
8.8%
9730
 
8.7%
8953
 
8.0%
8931
 
8.0%
8916
 
8.0%
8916
 
8.0%
8916
 
8.0%
8647
 
7.8%
6425
 
5.8%
6239
 
5.6%
Other values (104) 25916
23.3%
Decimal Number
ValueCountFrequency (%)
1 10245
23.2%
2 6305
14.3%
3 4820
10.9%
4 4039
 
9.1%
5 3764
 
8.5%
6 3409
 
7.7%
7 3241
 
7.3%
9 3083
 
7.0%
0 2718
 
6.1%
8 2604
 
5.9%
Space Separator
ValueCountFrequency (%)
39242
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4319
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111404
55.9%
Common 87789
44.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9815
 
8.8%
9730
 
8.7%
8953
 
8.0%
8931
 
8.0%
8916
 
8.0%
8916
 
8.0%
8916
 
8.0%
8647
 
7.8%
6425
 
5.8%
6239
 
5.6%
Other values (104) 25916
23.3%
Common
ValueCountFrequency (%)
39242
44.7%
1 10245
 
11.7%
2 6305
 
7.2%
3 4820
 
5.5%
- 4319
 
4.9%
4 4039
 
4.6%
5 3764
 
4.3%
6 3409
 
3.9%
7 3241
 
3.7%
9 3083
 
3.5%
Other values (2) 5322
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111404
55.9%
ASCII 87789
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39242
44.7%
1 10245
 
11.7%
2 6305
 
7.2%
3 4820
 
5.5%
- 4319
 
4.9%
4 4039
 
4.6%
5 3764
 
4.3%
6 3409
 
3.9%
7 3241
 
3.7%
9 3083
 
3.5%
Other values (2) 5322
 
6.1%
Hangul
ValueCountFrequency (%)
9815
 
8.8%
9730
 
8.7%
8953
 
8.0%
8931
 
8.0%
8916
 
8.0%
8916
 
8.0%
8916
 
8.0%
8647
 
7.8%
6425
 
5.8%
6239
 
5.6%
Other values (104) 25916
23.3%
Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:24:14.315235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length12.3057
Min length10

Characters and Unicode

Total characters123057
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 row48250-102011395
2nd row48250-35816
3rd row48250-102047439
4th row48250-32614
5th row48250-40064
ValueCountFrequency (%)
48250-102011395 1
 
< 0.1%
48250-102101999 1
 
< 0.1%
48250-30349 1
 
< 0.1%
48250-102006222 1
 
< 0.1%
48250-102108504 1
 
< 0.1%
48250-41618 1
 
< 0.1%
48250-102058919 1
 
< 0.1%
48250-55425 1
 
< 0.1%
48250-37241 1
 
< 0.1%
48250-19643 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-11T08:24:14.653974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20005
16.3%
2 18999
15.4%
4 15750
12.8%
5 15353
12.5%
8 14377
11.7%
1 10198
8.3%
- 10000
8.1%
3 5678
 
4.6%
6 4275
 
3.5%
9 4240
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 113057
91.9%
Dash Punctuation 10000
 
8.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20005
17.7%
2 18999
16.8%
4 15750
13.9%
5 15353
13.6%
8 14377
12.7%
1 10198
9.0%
3 5678
 
5.0%
6 4275
 
3.8%
9 4240
 
3.8%
7 4182
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 123057
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20005
16.3%
2 18999
15.4%
4 15750
12.8%
5 15353
12.5%
8 14377
11.7%
1 10198
8.3%
- 10000
8.1%
3 5678
 
4.6%
6 4275
 
3.5%
9 4240
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123057
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20005
16.3%
2 18999
15.4%
4 15750
12.8%
5 15353
12.5%
8 14377
11.7%
1 10198
8.3%
- 10000
8.1%
3 5678
 
4.6%
6 4275
 
3.5%
9 4240
 
3.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반
8757 
집합
1243 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반
2nd row집합
3rd row일반
4th row일반
5th row일반

Common Values

ValueCountFrequency (%)
일반 8757
87.6%
집합 1243
 
12.4%

Length

2023-12-11T08:24:14.771237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:24:14.867849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 8757
87.6%
집합 1243
 
12.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반건축물
8757 
표제부
1243 

Length

Max length5
Median length5
Mean length4.7514
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반건축물
2nd row표제부
3rd row일반건축물
4th row일반건축물
5th row일반건축물

Common Values

ValueCountFrequency (%)
일반건축물 8757
87.6%
표제부 1243
 
12.4%

Length

2023-12-11T08:24:14.997043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:24:15.122244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반건축물 8757
87.6%
표제부 1243
 
12.4%

건물명
Text

MISSING 

Distinct1014
Distinct (%)58.0%
Missing8252
Missing (%)82.5%
Memory size156.2 KiB
2023-12-11T08:24:15.340255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length27
Mean length8.0778032
Min length1

Characters and Unicode

Total characters14120
Distinct characters459
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique758 ?
Unique (%)43.4%

Sample

1st row신장유 일동미라주 더파크 아파트
2nd row중앙파크빌
3rd row부산경남경마공원
4th row화정마을아이파크가야
5th row(주)경남은행
ValueCountFrequency (%)
김해 81
 
3.1%
워터파크 51
 
2.0%
롯데 51
 
2.0%
부영아파트 46
 
1.8%
푸르지오 38
 
1.5%
아파트 35
 
1.4%
석봉마을 25
 
1.0%
율현마을 24
 
0.9%
화정마을 21
 
0.8%
진영 21
 
0.8%
Other values (1150) 2193
84.8%
2023-12-11T08:24:15.763409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
838
 
5.9%
478
 
3.4%
464
 
3.3%
428
 
3.0%
352
 
2.5%
323
 
2.3%
316
 
2.2%
301
 
2.1%
274
 
1.9%
238
 
1.7%
Other values (449) 10108
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12351
87.5%
Space Separator 838
 
5.9%
Decimal Number 477
 
3.4%
Uppercase Letter 128
 
0.9%
Close Punctuation 109
 
0.8%
Open Punctuation 109
 
0.8%
Dash Punctuation 51
 
0.4%
Lowercase Letter 38
 
0.3%
Other Punctuation 18
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
478
 
3.9%
464
 
3.8%
428
 
3.5%
352
 
2.8%
323
 
2.6%
316
 
2.6%
301
 
2.4%
274
 
2.2%
238
 
1.9%
232
 
1.9%
Other values (400) 8945
72.4%
Uppercase Letter
ValueCountFrequency (%)
C 15
11.7%
I 15
11.7%
A 14
10.9%
S 13
10.2%
M 9
 
7.0%
Q 8
 
6.2%
E 8
 
6.2%
D 6
 
4.7%
B 6
 
4.7%
G 5
 
3.9%
Other values (11) 29
22.7%
Decimal Number
ValueCountFrequency (%)
1 121
25.4%
2 101
21.2%
3 55
11.5%
4 36
 
7.5%
9 32
 
6.7%
6 31
 
6.5%
5 29
 
6.1%
8 25
 
5.2%
0 24
 
5.0%
7 23
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
e 30
78.9%
t 2
 
5.3%
o 2
 
5.3%
k 1
 
2.6%
d 1
 
2.6%
i 1
 
2.6%
h 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 9
50.0%
& 3
 
16.7%
, 2
 
11.1%
/ 2
 
11.1%
: 1
 
5.6%
# 1
 
5.6%
Space Separator
ValueCountFrequency (%)
838
100.0%
Close Punctuation
ValueCountFrequency (%)
) 109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12349
87.5%
Common 1602
 
11.3%
Latin 167
 
1.2%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
478
 
3.9%
464
 
3.8%
428
 
3.5%
352
 
2.9%
323
 
2.6%
316
 
2.6%
301
 
2.4%
274
 
2.2%
238
 
1.9%
232
 
1.9%
Other values (398) 8943
72.4%
Latin
ValueCountFrequency (%)
e 30
18.0%
C 15
 
9.0%
I 15
 
9.0%
A 14
 
8.4%
S 13
 
7.8%
M 9
 
5.4%
Q 8
 
4.8%
E 8
 
4.8%
D 6
 
3.6%
B 6
 
3.6%
Other values (19) 43
25.7%
Common
ValueCountFrequency (%)
838
52.3%
1 121
 
7.6%
) 109
 
6.8%
( 109
 
6.8%
2 101
 
6.3%
3 55
 
3.4%
- 51
 
3.2%
4 36
 
2.2%
9 32
 
2.0%
6 31
 
1.9%
Other values (10) 119
 
7.4%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12349
87.5%
ASCII 1768
 
12.5%
CJK 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
838
47.4%
1 121
 
6.8%
) 109
 
6.2%
( 109
 
6.2%
2 101
 
5.7%
3 55
 
3.1%
- 51
 
2.9%
4 36
 
2.0%
9 32
 
1.8%
6 31
 
1.8%
Other values (38) 285
 
16.1%
Hangul
ValueCountFrequency (%)
478
 
3.9%
464
 
3.8%
428
 
3.5%
352
 
2.9%
323
 
2.6%
316
 
2.6%
301
 
2.4%
274
 
2.2%
238
 
1.9%
232
 
1.9%
Other values (398) 8943
72.4%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

특수지명
Categorical

IMBALANCE 

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9906 
주촌선천지구
 
27
선천지구
 
13
삼어지구
 
9
무계지구 도시개발사업조합지구내
 
7
Other values (29)
 
38

Length

Max length19
Median length4
Mean length4.0273
Min length1

Unique

Unique25 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9906
99.1%
주촌선천지구 27
 
0.3%
선천지구 13
 
0.1%
삼어지구 9
 
0.1%
무계지구 도시개발사업조합지구내 7
 
0.1%
김해율하2지구 6
 
0.1%
고모리 테크노밸리 3
 
< 0.1%
본산준공업단지 2
 
< 0.1%
. 2
 
< 0.1%
20블럭16롯트 1
 
< 0.1%
Other values (24) 24
 
0.2%

Length

2023-12-11T08:24:15.915784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9906
98.9%
주촌선천지구 27
 
0.3%
선천지구 13
 
0.1%
삼어지구 10
 
0.1%
무계지구 7
 
0.1%
도시개발사업조합지구내 7
 
0.1%
김해율하2지구 6
 
0.1%
고모리 3
 
< 0.1%
테크노밸리 3
 
< 0.1%
김해삼어지구 2
 
< 0.1%
Other values (34) 36
 
0.4%

블록
Categorical

IMBALANCE 

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9928 
28블럭
 
13
89B
 
8
5블록
 
7
A-1블록
 
6
Other values (27)
 
38

Length

Max length5
Median length4
Mean length3.9972
Min length1

Unique

Unique21 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9928
99.3%
28블럭 13
 
0.1%
89B 8
 
0.1%
5블록 7
 
0.1%
A-1블록 6
 
0.1%
19블록 5
 
0.1%
1블록 3
 
< 0.1%
70블록 3
 
< 0.1%
17 2
 
< 0.1%
35블록 2
 
< 0.1%
Other values (22) 23
 
0.2%

Length

2023-12-11T08:24:16.072306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9928
99.3%
28블럭 13
 
0.1%
89b 8
 
0.1%
5블록 7
 
0.1%
a-1블록 6
 
0.1%
19블록 5
 
< 0.1%
1블록 3
 
< 0.1%
70블록 3
 
< 0.1%
35블록 2
 
< 0.1%
84블록 2
 
< 0.1%
Other values (22) 23
 
0.2%

로트
Categorical

IMBALANCE 

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9934 
1로트
 
13
8-2로트
 
9
1-1L
 
8
7로트
 
6
Other values (25)
 
30

Length

Max length7
Median length4
Mean length3.9978
Min length1

Unique

Unique22 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9934
99.3%
1로트 13
 
0.1%
8-2로트 9
 
0.1%
1-1L 8
 
0.1%
7로트 6
 
0.1%
4로트 4
 
< 0.1%
1 2
 
< 0.1%
5로트 2
 
< 0.1%
9로트 1
 
< 0.1%
12 1
 
< 0.1%
Other values (20) 20
 
0.2%

Length

2023-12-11T08:24:16.203441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9934
99.3%
1로트 13
 
0.1%
8-2로트 9
 
0.1%
1-1l 8
 
0.1%
7로트 6
 
0.1%
4로트 4
 
< 0.1%
1 2
 
< 0.1%
5로트 2
 
< 0.1%
01일 1
 
< 0.1%
10-2로트 1
 
< 0.1%
Other values (21) 21
 
0.2%

외필지수
Real number (ℝ)

SKEWED  ZEROS 

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4602
Minimum0
Maximum154
Zeros9044
Zeros (%)90.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:16.341495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum154
Range154
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.9189669
Coefficient of variation (CV)10.688759
Kurtosis539.46402
Mean0.4602
Median Absolute Deviation (MAD)0
Skewness21.268412
Sum4602
Variance24.196236
MonotonicityNot monotonic
2023-12-11T08:24:16.467533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 9044
90.4%
1 592
 
5.9%
2 162
 
1.6%
3 51
 
0.5%
4 38
 
0.4%
7 14
 
0.1%
5 13
 
0.1%
6 12
 
0.1%
26 11
 
0.1%
60 10
 
0.1%
Other values (24) 53
 
0.5%
ValueCountFrequency (%)
0 9044
90.4%
1 592
 
5.9%
2 162
 
1.6%
3 51
 
0.5%
4 38
 
0.4%
5 13
 
0.1%
6 12
 
0.1%
7 14
 
0.1%
8 5
 
0.1%
9 9
 
0.1%
ValueCountFrequency (%)
154 4
 
< 0.1%
112 1
 
< 0.1%
108 3
 
< 0.1%
98 2
 
< 0.1%
77 1
 
< 0.1%
66 1
 
< 0.1%
60 10
0.1%
47 3
 
< 0.1%
41 1
 
< 0.1%
36 2
 
< 0.1%

새주소도로코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
483000000000
9109 
<NA>
 
891

Length

Max length12
Median length12
Mean length11.2872
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row483000000000
2nd row483000000000
3rd row483000000000
4th row<NA>
5th row483000000000

Common Values

ValueCountFrequency (%)
483000000000 9109
91.1%
<NA> 891
 
8.9%

Length

2023-12-11T08:24:16.658509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:24:16.792901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
483000000000 9109
91.1%
na 891
 
8.9%

새주소법정동코드
Real number (ℝ)

MISSING 

Distinct123
Distinct (%)1.4%
Missing891
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean16098.092
Minimum10101
Maximum33004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:16.945994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile10202
Q110901
median12001
Q325001
95-th percentile32001
Maximum33004
Range22903
Interquartile range (IQR)14100

Descriptive statistics

Standard deviation7641.5234
Coefficient of variation (CV)0.47468503
Kurtosis-0.36433242
Mean16098.092
Median Absolute Deviation (MAD)1200
Skewness1.1416088
Sum1.4663752 × 108
Variance58392880
MonotonicityNot monotonic
2023-12-11T08:24:17.374846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25001 1417
 
14.2%
32001 890
 
8.9%
10801 428
 
4.3%
11901 415
 
4.2%
10101 349
 
3.5%
11801 297
 
3.0%
10901 277
 
2.8%
11701 268
 
2.7%
10701 256
 
2.6%
13002 235
 
2.4%
Other values (113) 4277
42.8%
(Missing) 891
 
8.9%
ValueCountFrequency (%)
10101 349
3.5%
10201 81
 
0.8%
10202 34
 
0.3%
10301 181
1.8%
10302 118
 
1.2%
10303 21
 
0.2%
10401 112
 
1.1%
10402 83
 
0.8%
10403 20
 
0.2%
10501 79
 
0.8%
ValueCountFrequency (%)
33004 13
 
0.1%
33002 18
 
0.2%
33001 69
 
0.7%
32003 39
 
0.4%
32002 17
 
0.2%
32001 890
8.9%
31001 1
 
< 0.1%
25012 86
 
0.9%
25002 3
 
< 0.1%
25001 1417
14.2%

새주소지상지하코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 10000
100.0%

Length

2023-12-11T08:24:17.510027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:24:17.610975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

새주소본번
Real number (ℝ)

MISSING 

Distinct742
Distinct (%)8.1%
Missing845
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean128.08957
Minimum0
Maximum2793
Zeros50
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:17.731050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q113
median33
Q3102
95-th percentile461.3
Maximum2793
Range2793
Interquartile range (IQR)89

Descriptive statistics

Standard deviation322.13881
Coefficient of variation (CV)2.5149496
Kurtosis32.290823
Mean128.08957
Median Absolute Deviation (MAD)25
Skewness5.3564141
Sum1172660
Variance103773.41
MonotonicityNot monotonic
2023-12-11T08:24:17.894200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 218
 
2.2%
9 215
 
2.1%
3 212
 
2.1%
8 203
 
2.0%
10 198
 
2.0%
12 193
 
1.9%
11 187
 
1.9%
7 186
 
1.9%
5 185
 
1.8%
6 184
 
1.8%
Other values (732) 7174
71.7%
(Missing) 845
 
8.5%
ValueCountFrequency (%)
0 50
 
0.5%
1 80
 
0.8%
2 81
 
0.8%
3 212
2.1%
4 218
2.2%
5 185
1.8%
6 184
1.8%
7 186
1.9%
8 203
2.0%
9 215
2.1%
ValueCountFrequency (%)
2793 2
< 0.1%
2787 2
< 0.1%
2785 1
< 0.1%
2778 1
< 0.1%
2777 1
< 0.1%
2776 1
< 0.1%
2752 1
< 0.1%
2733 1
< 0.1%
2724 1
< 0.1%
2721 1
< 0.1%

새주소부번
Real number (ℝ)

MISSING  ZEROS 

Distinct142
Distinct (%)2.2%
Missing3559
Missing (%)35.6%
Infinite0
Infinite (%)0.0%
Mean12.239559
Minimum0
Maximum688
Zeros2019
Zeros (%)20.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:18.055447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q316
95-th percentile46
Maximum688
Range688
Interquartile range (IQR)16

Descriptive statistics

Standard deviation23.364714
Coefficient of variation (CV)1.9089506
Kurtosis180.75531
Mean12.239559
Median Absolute Deviation (MAD)5
Skewness9.071889
Sum78835
Variance545.90984
MonotonicityNot monotonic
2023-12-11T08:24:18.217917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2019
20.2%
1 628
 
6.3%
7 170
 
1.7%
6 166
 
1.7%
5 165
 
1.7%
9 164
 
1.6%
14 163
 
1.6%
3 162
 
1.6%
11 159
 
1.6%
8 159
 
1.6%
Other values (132) 2486
24.9%
(Missing) 3559
35.6%
ValueCountFrequency (%)
0 2019
20.2%
1 628
 
6.3%
2 157
 
1.6%
3 162
 
1.6%
4 131
 
1.3%
5 165
 
1.7%
6 166
 
1.7%
7 170
 
1.7%
8 159
 
1.6%
9 164
 
1.6%
ValueCountFrequency (%)
688 1
 
< 0.1%
563 1
 
< 0.1%
400 1
 
< 0.1%
237 1
 
< 0.1%
221 1
 
< 0.1%
215 1
 
< 0.1%
213 1
 
< 0.1%
194 3
< 0.1%
193 1
 
< 0.1%
191 1
 
< 0.1%

동명칭
Text

MISSING 

Distinct552
Distinct (%)27.6%
Missing7998
Missing (%)80.0%
Memory size156.2 KiB
2023-12-11T08:24:18.562972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length3.3176823
Min length1

Characters and Unicode

Total characters6642
Distinct characters265
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique398 ?
Unique (%)19.9%

Sample

1st row133(상가4)
2nd rowB동
3rd row102동(관리사무실)
4th row경마관람장-5
5th row경비실3
ValueCountFrequency (%)
b동 225
 
11.1%
a동 216
 
10.6%
c동 91
 
4.5%
가동 81
 
4.0%
나동 80
 
3.9%
d동 42
 
2.1%
다동 36
 
1.8%
주건축물제1동 36
 
1.8%
1동 32
 
1.6%
2동 29
 
1.4%
Other values (548) 1164
57.3%
2023-12-11T08:24:19.109223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1663
25.0%
1 656
 
9.9%
0 471
 
7.1%
2 264
 
4.0%
B 241
 
3.6%
A 241
 
3.6%
3 204
 
3.1%
4 130
 
2.0%
129
 
1.9%
123
 
1.9%
Other values (255) 2520
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3667
55.2%
Decimal Number 2089
31.5%
Uppercase Letter 720
 
10.8%
Close Punctuation 38
 
0.6%
Open Punctuation 38
 
0.6%
Other Punctuation 35
 
0.5%
Space Separator 30
 
0.5%
Dash Punctuation 24
 
0.4%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1663
45.4%
129
 
3.5%
123
 
3.4%
121
 
3.3%
92
 
2.5%
77
 
2.1%
51
 
1.4%
50
 
1.4%
50
 
1.4%
49
 
1.3%
Other values (215) 1262
34.4%
Uppercase Letter
ValueCountFrequency (%)
B 241
33.5%
A 241
33.5%
C 101
14.0%
D 46
 
6.4%
E 28
 
3.9%
F 12
 
1.7%
H 9
 
1.2%
T 6
 
0.8%
O 5
 
0.7%
K 5
 
0.7%
Other values (11) 26
 
3.6%
Decimal Number
ValueCountFrequency (%)
1 656
31.4%
0 471
22.5%
2 264
12.6%
3 204
 
9.8%
4 130
 
6.2%
5 88
 
4.2%
6 87
 
4.2%
7 79
 
3.8%
9 58
 
2.8%
8 52
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 22
62.9%
/ 9
25.7%
. 3
 
8.6%
& 1
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3667
55.2%
Common 2254
33.9%
Latin 721
 
10.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1663
45.4%
129
 
3.5%
123
 
3.4%
121
 
3.3%
92
 
2.5%
77
 
2.1%
51
 
1.4%
50
 
1.4%
50
 
1.4%
49
 
1.3%
Other values (215) 1262
34.4%
Latin
ValueCountFrequency (%)
B 241
33.4%
A 241
33.4%
C 101
14.0%
D 46
 
6.4%
E 28
 
3.9%
F 12
 
1.7%
H 9
 
1.2%
T 6
 
0.8%
O 5
 
0.7%
K 5
 
0.7%
Other values (12) 27
 
3.7%
Common
ValueCountFrequency (%)
1 656
29.1%
0 471
20.9%
2 264
11.7%
3 204
 
9.1%
4 130
 
5.8%
5 88
 
3.9%
6 87
 
3.9%
7 79
 
3.5%
9 58
 
2.6%
8 52
 
2.3%
Other values (8) 165
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3667
55.2%
ASCII 2975
44.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1663
45.4%
129
 
3.5%
123
 
3.4%
121
 
3.3%
92
 
2.5%
77
 
2.1%
51
 
1.4%
50
 
1.4%
50
 
1.4%
49
 
1.3%
Other values (215) 1262
34.4%
ASCII
ValueCountFrequency (%)
1 656
22.1%
0 471
15.8%
2 264
8.9%
B 241
 
8.1%
A 241
 
8.1%
3 204
 
6.9%
4 130
 
4.4%
C 101
 
3.4%
5 88
 
3.0%
6 87
 
2.9%
Other values (30) 492
16.5%

주부속구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8990 
1
1010 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 8990
89.9%
1 1010
 
10.1%

Length

2023-12-11T08:24:19.246784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:24:19.366203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8990
89.9%
1 1010
 
10.1%

주부속구분코드명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주건축물
8990 
부속건축물
1010 

Length

Max length5
Median length4
Mean length4.101
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주건축물 8990
89.9%
부속건축물 1010
 
10.1%

Length

2023-12-11T08:24:19.480679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:24:19.577865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주건축물 8990
89.9%
부속건축물 1010
 
10.1%

대지면적(제곱미터)
Real number (ℝ)

SKEWED  ZEROS 

Distinct3383
Distinct (%)33.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1204.1347
Minimum0
Maximum621551.5
Zeros4054
Zeros (%)40.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:19.708916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median198
Q3368
95-th percentile1861.195
Maximum621551.5
Range621551.5
Interquartile range (IQR)368

Descriptive statistics

Standard deviation17967.863
Coefficient of variation (CV)14.921805
Kurtosis1135.2831
Mean1204.1347
Median Absolute Deviation (MAD)198
Skewness33.090283
Sum12041347
Variance3.228441 × 108
MonotonicityNot monotonic
2023-12-11T08:24:19.883755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4054
40.5%
330.0 23
 
0.2%
208.0 16
 
0.2%
228.0 14
 
0.1%
165.0 13
 
0.1%
257.0 13
 
0.1%
145.0 12
 
0.1%
199.0 12
 
0.1%
221.0 12
 
0.1%
215.0 11
 
0.1%
Other values (3373) 5820
58.2%
ValueCountFrequency (%)
0.0 4054
40.5%
16.631 1
 
< 0.1%
25.0 2
 
< 0.1%
26.0 2
 
< 0.1%
29.0 1
 
< 0.1%
30.0 1
 
< 0.1%
38.01 1
 
< 0.1%
40.0 1
 
< 0.1%
42.0 1
 
< 0.1%
44.0 2
 
< 0.1%
ValueCountFrequency (%)
621551.5 8
0.1%
122397.27 3
 
< 0.1%
73500.0 2
 
< 0.1%
57920.4 1
 
< 0.1%
52993.0 2
 
< 0.1%
49375.6 9
0.1%
44131.1 3
 
< 0.1%
42088.56 3
 
< 0.1%
41933.0 1
 
< 0.1%
41392.2 2
 
< 0.1%

건축면적(제곱미터)
Real number (ℝ)

ZEROS 

Distinct7337
Distinct (%)73.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean287.89811
Minimum0
Maximum29558.68
Zeros399
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:20.064300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.25
Q172
median129.31
Q3237.155
95-th percentile877.6385
Maximum29558.68
Range29558.68
Interquartile range (IQR)165.155

Descriptive statistics

Standard deviation847.45211
Coefficient of variation (CV)2.9435834
Kurtosis339.35647
Mean287.89811
Median Absolute Deviation (MAD)69.14
Skewness15.166609
Sum2878981.1
Variance718175.08
MonotonicityNot monotonic
2023-12-11T08:24:20.199233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 399
 
4.0%
6.25 38
 
0.4%
19.83 32
 
0.3%
23.14 28
 
0.3%
26.45 26
 
0.3%
33.06 17
 
0.2%
46.28 17
 
0.2%
29.75 16
 
0.2%
60.0 15
 
0.1%
84.0 15
 
0.1%
Other values (7327) 9397
94.0%
ValueCountFrequency (%)
0.0 399
4.0%
0.6 1
 
< 0.1%
0.99 1
 
< 0.1%
1.0 3
 
< 0.1%
1.1 1
 
< 0.1%
1.44 2
 
< 0.1%
1.65 1
 
< 0.1%
1.77 1
 
< 0.1%
1.8 1
 
< 0.1%
1.82 1
 
< 0.1%
ValueCountFrequency (%)
29558.68 1
< 0.1%
23133.25 1
< 0.1%
20852.95 1
< 0.1%
18713.81 1
< 0.1%
16555.22 1
< 0.1%
15684.47 1
< 0.1%
15407.94 1
< 0.1%
14640.92 1
< 0.1%
14007.47 1
< 0.1%
13893.53 1
< 0.1%

건폐율(퍼센트)
Real number (ℝ)

ZEROS 

Distinct3068
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.292127
Minimum0
Maximum813.88
Zeros4071
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:20.335199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median23.99
Q358.24
95-th percentile62.4505
Maximum813.88
Range813.88
Interquartile range (IQR)58.24

Descriptive statistics

Standard deviation28.329844
Coefficient of variation (CV)1.0013331
Kurtosis57.436328
Mean28.292127
Median Absolute Deviation (MAD)23.99
Skewness2.2906297
Sum282921.27
Variance802.58004
MonotonicityNot monotonic
2023-12-11T08:24:20.478105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4071
40.7%
59.44 27
 
0.3%
59.64 26
 
0.3%
59.35 25
 
0.2%
59.6 25
 
0.2%
59.74 24
 
0.2%
59.69 24
 
0.2%
59.51 23
 
0.2%
59.73 23
 
0.2%
59.56 23
 
0.2%
Other values (3058) 5709
57.1%
ValueCountFrequency (%)
0.0 4071
40.7%
0.0014 2
 
< 0.1%
0.0015 1
 
< 0.1%
0.0088543 1
 
< 0.1%
0.01 3
 
< 0.1%
0.02 1
 
< 0.1%
0.0298 1
 
< 0.1%
0.0373 1
 
< 0.1%
0.0454611 1
 
< 0.1%
0.05 1
 
< 0.1%
ValueCountFrequency (%)
813.88 1
< 0.1%
184.66 1
< 0.1%
172.75 1
< 0.1%
124.45 1
< 0.1%
100.0 2
< 0.1%
99.62 1
< 0.1%
96.3 1
< 0.1%
91.79 1
< 0.1%
90.08 1
< 0.1%
87.1 1
< 0.1%

연면적(제곱미터)
Real number (ℝ)

Distinct8189
Distinct (%)81.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean936.90043
Minimum0
Maximum116481.36
Zeros28
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:20.624634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile22.4385
Q186.7425
median248.71055
Q3493.2925
95-th percentile5124.249
Maximum116481.36
Range116481.36
Interquartile range (IQR)406.55

Descriptive statistics

Standard deviation3036.4776
Coefficient of variation (CV)3.2409821
Kurtosis296.55431
Mean936.90043
Median Absolute Deviation (MAD)178.71055
Skewness12.393677
Sum9369004.3
Variance9220195.9
MonotonicityNot monotonic
2023-12-11T08:24:20.762896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.25 38
 
0.4%
19.83 36
 
0.4%
0.0 28
 
0.3%
23.14 28
 
0.3%
26.45 26
 
0.3%
60.0 18
 
0.2%
33.06 18
 
0.2%
84.0 17
 
0.2%
46.28 17
 
0.2%
39.67 16
 
0.2%
Other values (8179) 9758
97.6%
ValueCountFrequency (%)
0.0 28
0.3%
0.6 1
 
< 0.1%
0.99 1
 
< 0.1%
1.0 5
 
0.1%
1.1 1
 
< 0.1%
1.21 1
 
< 0.1%
1.44 4
 
< 0.1%
1.65 1
 
< 0.1%
1.77 1
 
< 0.1%
1.8 1
 
< 0.1%
ValueCountFrequency (%)
116481.3569 1
< 0.1%
64715.9374 1
< 0.1%
59909.2762 1
< 0.1%
54934.33 1
< 0.1%
47778.9245 1
< 0.1%
46674.83 1
< 0.1%
45501.79 1
< 0.1%
43633.7 1
< 0.1%
42741.723 1
< 0.1%
42223.63 1
< 0.1%
Distinct8062
Distinct (%)80.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean808.45463
Minimum0
Maximum54498.95
Zeros193
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:20.922941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16.5
Q182.8425
median233.83
Q3480.3075
95-th percentile4613.964
Maximum54498.95
Range54498.95
Interquartile range (IQR)397.465

Descriptive statistics

Standard deviation2191.1634
Coefficient of variation (CV)2.7103109
Kurtosis75.465406
Mean808.45463
Median Absolute Deviation (MAD)169.77
Skewness6.6290682
Sum8084546.3
Variance4801197.1
MonotonicityNot monotonic
2023-12-11T08:24:21.053430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 193
 
1.9%
6.25 38
 
0.4%
19.83 35
 
0.4%
23.14 28
 
0.3%
26.45 26
 
0.3%
33.06 18
 
0.2%
46.28 17
 
0.2%
84.0 17
 
0.2%
39.67 16
 
0.2%
29.75 16
 
0.2%
Other values (8052) 9596
96.0%
ValueCountFrequency (%)
0.0 193
1.9%
0.6 1
 
< 0.1%
0.99 1
 
< 0.1%
1.0 4
 
< 0.1%
1.1 1
 
< 0.1%
1.21 1
 
< 0.1%
1.44 4
 
< 0.1%
1.65 1
 
< 0.1%
1.77 1
 
< 0.1%
1.8 1
 
< 0.1%
ValueCountFrequency (%)
54498.95 1
< 0.1%
33878.42 1
< 0.1%
33099.99 1
< 0.1%
32300.84 1
< 0.1%
28894.13 1
< 0.1%
26871.522 1
< 0.1%
25697.69 1
< 0.1%
24887.096 1
< 0.1%
23150.9215 1
< 0.1%
22124.16 1
< 0.1%

용적률(퍼센트)
Real number (ℝ)

ZEROS 

Distinct5021
Distinct (%)50.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.76049
Minimum0
Maximum978.11
Zeros4072
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:21.210511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median29.895
Q3114.165
95-th percentile191.9015
Maximum978.11
Range978.11
Interquartile range (IQR)114.165

Descriptive statistics

Standard deviation83.453296
Coefficient of variation (CV)1.3088559
Kurtosis9.4663177
Mean63.76049
Median Absolute Deviation (MAD)29.895
Skewness2.1609717
Sum637604.9
Variance6964.4527
MonotonicityNot monotonic
2023-12-11T08:24:21.350996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4072
40.7%
192.84 9
 
0.1%
59.68 6
 
0.1%
269.37 6
 
0.1%
59.64 5
 
0.1%
19.1 4
 
< 0.1%
59.86 4
 
< 0.1%
59.74 4
 
< 0.1%
52.65 4
 
< 0.1%
28.8 4
 
< 0.1%
Other values (5011) 5882
58.8%
ValueCountFrequency (%)
0.0 4072
40.7%
0.0012 1
 
< 0.1%
0.0014 2
 
< 0.1%
0.0088543 1
 
< 0.1%
0.01 3
 
< 0.1%
0.02 1
 
< 0.1%
0.0298 1
 
< 0.1%
0.0373 1
 
< 0.1%
0.047 1
 
< 0.1%
0.07 1
 
< 0.1%
ValueCountFrequency (%)
978.11 1
< 0.1%
769.25 1
< 0.1%
751.93 1
< 0.1%
741.15 1
< 0.1%
722.24 1
< 0.1%
709.27 1
< 0.1%
701.26 1
< 0.1%
698.24 1
< 0.1%
697.69 1
< 0.1%
697.16 1
< 0.1%

구조코드
Real number (ℝ)

Distinct20
Distinct (%)0.2%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean24.643929
Minimum10
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:21.486823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile11
Q121
median21
Q331
95-th percentile51
Maximum99
Range89
Interquartile range (IQR)10

Descriptive statistics

Standard deviation11.307298
Coefficient of variation (CV)0.45882694
Kurtosis3.0006742
Mean24.643929
Median Absolute Deviation (MAD)9
Skewness1.3557138
Sum246390
Variance127.855
MonotonicityNot monotonic
2023-12-11T08:24:21.602183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
21 4196
42.0%
31 1615
 
16.2%
12 1006
 
10.1%
11 986
 
9.9%
51 913
 
9.1%
32 829
 
8.3%
19 296
 
3.0%
41 39
 
0.4%
33 28
 
0.3%
10 20
 
0.2%
Other values (10) 70
 
0.7%
ValueCountFrequency (%)
10 20
 
0.2%
11 986
 
9.9%
12 1006
 
10.1%
19 296
 
3.0%
21 4196
42.0%
22 2
 
< 0.1%
29 9
 
0.1%
31 1615
 
16.2%
32 829
 
8.3%
33 28
 
0.3%
ValueCountFrequency (%)
99 14
 
0.1%
74 5
 
0.1%
63 2
 
< 0.1%
61 1
 
< 0.1%
53 1
 
< 0.1%
51 913
9.1%
50 8
 
0.1%
42 20
 
0.2%
41 39
 
0.4%
39 8
 
0.1%

구조코드명
Categorical

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
철근콘크리트구조
4196 
일반철골구조
1615 
블록구조
1006 
벽돌구조
986 
일반목구조
913 
Other values (16)
1284 

Length

Max length11
Median length10
Mean length6.3572
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row철근콘크리트구조
2nd row벽돌구조
3rd row철근콘크리트구조
4th row블록구조
5th row일반목구조

Common Values

ValueCountFrequency (%)
철근콘크리트구조 4196
42.0%
일반철골구조 1615
 
16.2%
블록구조 1006
 
10.1%
벽돌구조 986
 
9.9%
일반목구조 913
 
9.1%
경량철골구조 829
 
8.3%
기타조적구조 296
 
3.0%
철골콘크리트구조 39
 
0.4%
강파이프구조 28
 
0.3%
철골철근콘크리트구조 20
 
0.2%
Other values (11) 72
 
0.7%

Length

2023-12-11T08:24:21.753097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
철근콘크리트구조 4196
42.0%
일반철골구조 1615
 
16.2%
블록구조 1006
 
10.1%
벽돌구조 986
 
9.9%
일반목구조 913
 
9.1%
경량철골구조 829
 
8.3%
기타조적구조 296
 
3.0%
철골콘크리트구조 39
 
0.4%
강파이프구조 28
 
0.3%
조적구조 20
 
0.2%
Other values (11) 72
 
0.7%
Distinct461
Distinct (%)4.6%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2023-12-11T08:24:21.998268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length6.3765389
Min length2

Characters and Unicode

Total characters63708
Distinct characters78
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

Unique276 ?
Unique (%)2.8%

Sample

1st row철근콘크리트구조
2nd row시멘트벽돌조
3rd row철근콘크리트구조
4th row블럭조
5th row목조
ValueCountFrequency (%)
철근콘크리트구조 2037
19.9%
철근콘크리트조 1382
13.5%
일반철골구조 965
9.4%
조적조 886
 
8.6%
목조 641
 
6.2%
경량철골구조 518
 
5.0%
철골조 442
 
4.3%
블럭조 440
 
4.3%
철근콘크리트조/조적조 349
 
3.4%
블록조 294
 
2.9%
Other values (373) 2304
22.5%
2023-12-11T08:24:22.407335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12952
20.3%
7186
11.3%
4747
 
7.5%
4410
 
6.9%
4365
 
6.9%
4364
 
6.9%
4354
 
6.8%
4146
 
6.5%
2829
 
4.4%
1454
 
2.3%
Other values (68) 12901
20.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61642
96.8%
Other Punctuation 1710
 
2.7%
Space Separator 267
 
0.4%
Open Punctuation 39
 
0.1%
Close Punctuation 38
 
0.1%
Uppercase Letter 10
 
< 0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12952
21.0%
7186
11.7%
4747
 
7.7%
4410
 
7.2%
4365
 
7.1%
4364
 
7.1%
4354
 
7.1%
4146
 
6.7%
2829
 
4.6%
1454
 
2.4%
Other values (59) 10835
17.6%
Other Punctuation
ValueCountFrequency (%)
/ 1407
82.3%
, 298
 
17.4%
. 5
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
R 5
50.0%
C 5
50.0%
Space Separator
ValueCountFrequency (%)
267
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61642
96.8%
Common 2056
 
3.2%
Latin 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12952
21.0%
7186
11.7%
4747
 
7.7%
4410
 
7.2%
4365
 
7.1%
4364
 
7.1%
4354
 
7.1%
4146
 
6.7%
2829
 
4.6%
1454
 
2.4%
Other values (59) 10835
17.6%
Common
ValueCountFrequency (%)
/ 1407
68.4%
, 298
 
14.5%
267
 
13.0%
( 39
 
1.9%
) 38
 
1.8%
. 5
 
0.2%
1 2
 
0.1%
Latin
ValueCountFrequency (%)
R 5
50.0%
C 5
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61642
96.8%
ASCII 2066
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
12952
21.0%
7186
11.7%
4747
 
7.7%
4410
 
7.2%
4365
 
7.1%
4364
 
7.1%
4354
 
7.1%
4146
 
6.7%
2829
 
4.6%
1454
 
2.4%
Other values (59) 10835
17.6%
ASCII
ValueCountFrequency (%)
/ 1407
68.1%
, 298
 
14.4%
267
 
12.9%
( 39
 
1.9%
) 38
 
1.8%
R 5
 
0.2%
. 5
 
0.2%
C 5
 
0.2%
1 2
 
0.1%

주용도코드
Unsupported

REJECTED  UNSUPPORTED 

Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단독주택
4803 
공장
1234 
제2종근린생활시설
1175 
공동주택
1074 
제1종근린생활시설
716 
Other values (25)
998 

Length

Max length10
Median length4
Mean length4.8941
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row단독주택
2nd row공동주택
3rd row단독주택
4th row단독주택
5th row단독주택

Common Values

ValueCountFrequency (%)
단독주택 4803
48.0%
공장 1234
 
12.3%
제2종근린생활시설 1175
 
11.8%
공동주택 1074
 
10.7%
제1종근린생활시설 716
 
7.2%
창고시설 179
 
1.8%
교육연구시설 123
 
1.2%
동.식물관련시설 108
 
1.1%
위험물저장및처리시설 94
 
0.9%
자동차관련시설 74
 
0.7%
Other values (20) 420
 
4.2%

Length

2023-12-11T08:24:22.558304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 4803
48.0%
공장 1234
 
12.3%
제2종근린생활시설 1175
 
11.8%
공동주택 1074
 
10.7%
제1종근린생활시설 716
 
7.2%
창고시설 179
 
1.8%
교육연구시설 123
 
1.2%
동.식물관련시설 108
 
1.1%
위험물저장및처리시설 94
 
0.9%
자동차관련시설 74
 
0.7%
Other values (20) 420
 
4.2%
Distinct1042
Distinct (%)10.4%
Missing5
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-11T08:24:22.745367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length41
Mean length7.5708854
Min length2

Characters and Unicode

Total characters75671
Distinct characters255
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique716 ?
Unique (%)7.2%

Sample

1st row단독주택(5가구)
2nd row공동주택
3rd row단독주택(10가구)
4th row주택
5th row단독주택
ValueCountFrequency (%)
단독주택 2720
25.1%
공장 1035
 
9.6%
제2종근린생활시설 833
 
7.7%
공동주택 561
 
5.2%
주택 372
 
3.4%
제1종근린생활시설 320
 
3.0%
근린생활시설 288
 
2.7%
근린생활시설/단독주택 242
 
2.2%
241
 
2.2%
단독주택/제2종근린생활시설 218
 
2.0%
Other values (882) 4005
37.0%
2023-12-11T08:24:23.087526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6155
 
8.1%
6076
 
8.0%
4760
 
6.3%
4754
 
6.3%
4619
 
6.1%
4610
 
6.1%
3596
 
4.8%
3590
 
4.7%
3540
 
4.7%
3533
 
4.7%
Other values (245) 30438
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 65696
86.8%
Decimal Number 3928
 
5.2%
Other Punctuation 3015
 
4.0%
Close Punctuation 1072
 
1.4%
Open Punctuation 1070
 
1.4%
Space Separator 842
 
1.1%
Uppercase Letter 41
 
0.1%
Dash Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6155
 
9.4%
6076
 
9.2%
4760
 
7.2%
4754
 
7.2%
4619
 
7.0%
4610
 
7.0%
3596
 
5.5%
3590
 
5.5%
3540
 
5.4%
3533
 
5.4%
Other values (219) 20463
31.1%
Decimal Number
ValueCountFrequency (%)
2 2119
53.9%
1 1301
33.1%
4 169
 
4.3%
3 92
 
2.3%
8 60
 
1.5%
5 48
 
1.2%
0 48
 
1.2%
7 34
 
0.9%
6 34
 
0.9%
9 23
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
D 12
29.3%
F 11
26.8%
M 11
26.8%
X 2
 
4.9%
G 2
 
4.9%
A 1
 
2.4%
E 1
 
2.4%
V 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
/ 2209
73.3%
, 749
 
24.8%
. 56
 
1.9%
· 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 1072
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1070
100.0%
Space Separator
ValueCountFrequency (%)
842
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 65696
86.8%
Common 9934
 
13.1%
Latin 41
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6155
 
9.4%
6076
 
9.2%
4760
 
7.2%
4754
 
7.2%
4619
 
7.0%
4610
 
7.0%
3596
 
5.5%
3590
 
5.5%
3540
 
5.4%
3533
 
5.4%
Other values (219) 20463
31.1%
Common
ValueCountFrequency (%)
/ 2209
22.2%
2 2119
21.3%
1 1301
13.1%
) 1072
10.8%
( 1070
10.8%
842
 
8.5%
, 749
 
7.5%
4 169
 
1.7%
3 92
 
0.9%
8 60
 
0.6%
Other values (8) 251
 
2.5%
Latin
ValueCountFrequency (%)
D 12
29.3%
F 11
26.8%
M 11
26.8%
X 2
 
4.9%
G 2
 
4.9%
A 1
 
2.4%
E 1
 
2.4%
V 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 65696
86.8%
ASCII 9974
 
13.2%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6155
 
9.4%
6076
 
9.2%
4760
 
7.2%
4754
 
7.2%
4619
 
7.0%
4610
 
7.0%
3596
 
5.5%
3590
 
5.5%
3540
 
5.4%
3533
 
5.4%
Other values (219) 20463
31.1%
ASCII
ValueCountFrequency (%)
/ 2209
22.1%
2 2119
21.2%
1 1301
13.0%
) 1072
10.7%
( 1070
10.7%
842
 
8.4%
, 749
 
7.5%
4 169
 
1.7%
3 92
 
0.9%
8 60
 
0.6%
Other values (15) 291
 
2.9%
None
ValueCountFrequency (%)
· 1
100.0%

지붕코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
10
5370 
90
2913 
30
1082 
20
617 
<NA>
 
18

Length

Max length4
Median length2
Mean length2.0036
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10
2nd row10
3rd row10
4th row30
5th row30

Common Values

ValueCountFrequency (%)
10 5370
53.7%
90 2913
29.1%
30 1082
 
10.8%
20 617
 
6.2%
<NA> 18
 
0.2%

Length

2023-12-11T08:24:23.228569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:24:23.337368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 5370
53.7%
90 2913
29.1%
30 1082
 
10.8%
20 617
 
6.2%
na 18
 
0.2%

지붕코드명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
(철근)콘크리트
5370 
기타지붕
2913 
슬레이트
1082 
기와
617 
<NA>
 
18

Length

Max length8
Median length8
Mean length6.0246
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row(철근)콘크리트
2nd row(철근)콘크리트
3rd row(철근)콘크리트
4th row슬레이트
5th row슬레이트

Common Values

ValueCountFrequency (%)
(철근)콘크리트 5370
53.7%
기타지붕 2913
29.1%
슬레이트 1082
 
10.8%
기와 617
 
6.2%
<NA> 18
 
0.2%

Length

2023-12-11T08:24:23.442210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:24:23.539442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근)콘크리트 5370
53.7%
기타지붕 2913
29.1%
슬레이트 1082
 
10.8%
기와 617
 
6.2%
na 18
 
0.2%
Distinct649
Distinct (%)6.5%
Missing27
Missing (%)0.3%
Memory size156.2 KiB
2023-12-11T08:24:23.710543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length25
Mean length4.8690464
Min length2

Characters and Unicode

Total characters48559
Distinct characters207
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique387 ?
Unique (%)3.9%

Sample

1st row슬라브
2nd row슬라브
3rd row경사스라브
4th row스레이트
5th row스레이트
ValueCountFrequency (%)
슬라브 3134
30.8%
철근)콘크리트 890
 
8.7%
샌드위치판넬 864
 
8.5%
스레이트 844
 
8.3%
판넬 362
 
3.6%
기타지붕 299
 
2.9%
기와 285
 
2.8%
스라브 262
 
2.6%
경사슬라브 171
 
1.7%
경사스라브 131
 
1.3%
Other values (570) 2932
28.8%
2023-12-11T08:24:24.335580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4660
 
9.6%
4449
 
9.2%
3862
 
8.0%
2885
 
5.9%
2259
 
4.7%
2138
 
4.4%
2053
 
4.2%
1412
 
2.9%
1381
 
2.8%
1294
 
2.7%
Other values (197) 22166
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44918
92.5%
Open Punctuation 1153
 
2.4%
Close Punctuation 1153
 
2.4%
Other Punctuation 979
 
2.0%
Space Separator 201
 
0.4%
Decimal Number 74
 
0.2%
Uppercase Letter 56
 
0.1%
Lowercase Letter 21
 
< 0.1%
Other Symbol 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4660
 
10.4%
4449
 
9.9%
3862
 
8.6%
2885
 
6.4%
2259
 
5.0%
2138
 
4.8%
2053
 
4.6%
1412
 
3.1%
1381
 
3.1%
1294
 
2.9%
Other values (160) 18525
41.2%
Uppercase Letter
ValueCountFrequency (%)
T 9
16.1%
P 6
10.7%
K 5
8.9%
E 5
8.9%
A 5
8.9%
S 5
8.9%
C 3
 
5.4%
R 3
 
5.4%
H 3
 
5.4%
M 2
 
3.6%
Other values (7) 10
17.9%
Decimal Number
ValueCountFrequency (%)
0 21
28.4%
5 16
21.6%
1 15
20.3%
2 13
17.6%
7 7
 
9.5%
8 1
 
1.4%
3 1
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
m 14
66.7%
t 3
 
14.3%
h 2
 
9.5%
k 2
 
9.5%
Other Punctuation
ValueCountFrequency (%)
/ 769
78.5%
, 208
 
21.2%
. 2
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 1153
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1153
100.0%
Space Separator
ValueCountFrequency (%)
201
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44918
92.5%
Common 3564
 
7.3%
Latin 77
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4660
 
10.4%
4449
 
9.9%
3862
 
8.6%
2885
 
6.4%
2259
 
5.0%
2138
 
4.8%
2053
 
4.6%
1412
 
3.1%
1381
 
3.1%
1294
 
2.9%
Other values (160) 18525
41.2%
Latin
ValueCountFrequency (%)
m 14
18.2%
T 9
11.7%
P 6
 
7.8%
K 5
 
6.5%
E 5
 
6.5%
A 5
 
6.5%
S 5
 
6.5%
t 3
 
3.9%
C 3
 
3.9%
R 3
 
3.9%
Other values (11) 19
24.7%
Common
ValueCountFrequency (%)
( 1153
32.4%
) 1153
32.4%
/ 769
21.6%
, 208
 
5.8%
201
 
5.6%
0 21
 
0.6%
5 16
 
0.4%
1 15
 
0.4%
2 13
 
0.4%
7 7
 
0.2%
Other values (6) 8
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44918
92.5%
ASCII 3639
 
7.5%
CJK Compat 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4660
 
10.4%
4449
 
9.9%
3862
 
8.6%
2885
 
6.4%
2259
 
5.0%
2138
 
4.8%
2053
 
4.6%
1412
 
3.1%
1381
 
3.1%
1294
 
2.9%
Other values (160) 18525
41.2%
ASCII
ValueCountFrequency (%)
( 1153
31.7%
) 1153
31.7%
/ 769
21.1%
, 208
 
5.7%
201
 
5.5%
0 21
 
0.6%
5 16
 
0.4%
1 15
 
0.4%
m 14
 
0.4%
2 13
 
0.4%
Other values (26) 76
 
2.1%
CJK Compat
ValueCountFrequency (%)
2
100.0%

세대수(세대)
Real number (ℝ)

ZEROS 

Distinct125
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9797
Minimum0
Maximum346
Zeros9083
Zeros (%)90.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:24.475208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile16
Maximum346
Range346
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.350552
Coefficient of variation (CV)4.611039
Kurtosis51.365865
Mean3.9797
Median Absolute Deviation (MAD)0
Skewness6.2589557
Sum39797
Variance336.74276
MonotonicityNot monotonic
2023-12-11T08:24:24.619837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9083
90.8%
8 235
 
2.4%
60 66
 
0.7%
1 51
 
0.5%
90 27
 
0.3%
7 26
 
0.3%
72 22
 
0.2%
16 20
 
0.2%
4 17
 
0.2%
80 17
 
0.2%
Other values (115) 436
 
4.4%
ValueCountFrequency (%)
0 9083
90.8%
1 51
 
0.5%
2 3
 
< 0.1%
3 9
 
0.1%
4 17
 
0.2%
5 5
 
0.1%
6 15
 
0.1%
7 26
 
0.3%
8 235
 
2.4%
9 7
 
0.1%
ValueCountFrequency (%)
346 1
< 0.1%
298 1
< 0.1%
220 1
< 0.1%
215 1
< 0.1%
200 1
< 0.1%
197 1
< 0.1%
195 1
< 0.1%
194 1
< 0.1%
190 1
< 0.1%
184 1
< 0.1%

가구수(가구)
Real number (ℝ)

SKEWED  ZEROS 

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3023
Minimum0
Maximum194
Zeros5000
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:24.748988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.5
Q31
95-th percentile5
Maximum194
Range194
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.7734518
Coefficient of variation (CV)2.8975288
Kurtosis897.9502
Mean1.3023
Median Absolute Deviation (MAD)0.5
Skewness22.941798
Sum13023
Variance14.238939
MonotonicityNot monotonic
2023-12-11T08:24:24.901856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 5000
50.0%
1 3164
31.6%
4 580
 
5.8%
3 472
 
4.7%
2 205
 
2.1%
5 118
 
1.2%
6 107
 
1.1%
8 66
 
0.7%
7 55
 
0.5%
11 54
 
0.5%
Other values (22) 179
 
1.8%
ValueCountFrequency (%)
0 5000
50.0%
1 3164
31.6%
2 205
 
2.1%
3 472
 
4.7%
4 580
 
5.8%
5 118
 
1.2%
6 107
 
1.1%
7 55
 
0.5%
8 66
 
0.7%
9 26
 
0.3%
ValueCountFrequency (%)
194 1
< 0.1%
108 1
< 0.1%
105 1
< 0.1%
99 1
< 0.1%
80 1
< 0.1%
78 1
< 0.1%
66 1
< 0.1%
58 1
< 0.1%
40 1
< 0.1%
39 1
< 0.1%

높이(미터)
Real number (ℝ)

ZEROS 

Distinct1223
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.2662534
Minimum0
Maximum163.9
Zeros3396
Zeros (%)34.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:25.101732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.7
Q311.45
95-th percentile25.605
Maximum163.9
Range163.9
Interquartile range (IQR)11.45

Descriptive statistics

Standard deviation11.315804
Coefficient of variation (CV)1.3689157
Kurtosis17.187135
Mean8.2662534
Median Absolute Deviation (MAD)6.1
Skewness3.4077128
Sum82662.534
Variance128.04743
MonotonicityNot monotonic
2023-12-11T08:24:25.345501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3396
34.0%
4.5 76
 
0.8%
7.9 76
 
0.8%
11.0 69
 
0.7%
3.9 68
 
0.7%
12.0 65
 
0.7%
4.0 65
 
0.7%
7.3 62
 
0.6%
11.7 58
 
0.6%
7.5 55
 
0.5%
Other values (1213) 6010
60.1%
ValueCountFrequency (%)
0.0 3396
34.0%
0.85 1
 
< 0.1%
0.95 1
 
< 0.1%
1.7 1
 
< 0.1%
1.95 1
 
< 0.1%
2.1 1
 
< 0.1%
2.2 4
 
< 0.1%
2.23 1
 
< 0.1%
2.25 1
 
< 0.1%
2.3 3
 
< 0.1%
ValueCountFrequency (%)
163.9 1
 
< 0.1%
123.0 1
 
< 0.1%
111.1 1
 
< 0.1%
106.95 1
 
< 0.1%
98.8 1
 
< 0.1%
85.4 2
< 0.1%
83.35 2
< 0.1%
82.6 3
< 0.1%
82.25 1
 
< 0.1%
81.95 1
 
< 0.1%

지상층수
Real number (ℝ)

ZEROS 

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6865
Minimum0
Maximum39
Zeros127
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:25.502252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile7
Maximum39
Range39
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.658409
Coefficient of variation (CV)1.3617752
Kurtosis20.041156
Mean2.6865
Median Absolute Deviation (MAD)1
Skewness4.2149178
Sum26865
Variance13.383956
MonotonicityNot monotonic
2023-12-11T08:24:25.646636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 4523
45.2%
2 2117
21.2%
3 1750
 
17.5%
4 616
 
6.2%
5 271
 
2.7%
15 132
 
1.3%
0 127
 
1.3%
6 67
 
0.7%
20 63
 
0.6%
7 42
 
0.4%
Other values (24) 292
 
2.9%
ValueCountFrequency (%)
0 127
 
1.3%
1 4523
45.2%
2 2117
21.2%
3 1750
 
17.5%
4 616
 
6.2%
5 271
 
2.7%
6 67
 
0.7%
7 42
 
0.4%
8 18
 
0.2%
9 17
 
0.2%
ValueCountFrequency (%)
39 1
 
< 0.1%
38 1
 
< 0.1%
35 1
 
< 0.1%
32 1
 
< 0.1%
30 2
 
< 0.1%
29 7
 
0.1%
28 3
 
< 0.1%
26 4
 
< 0.1%
25 35
0.4%
24 5
 
0.1%

지하층수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1056
Minimum0
Maximum5
Zeros9043
Zeros (%)90.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:25.773627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.34476155
Coefficient of variation (CV)3.2647874
Kurtosis19.881346
Mean0.1056
Median Absolute Deviation (MAD)0
Skewness3.8414837
Sum1056
Variance0.11886053
MonotonicityNot monotonic
2023-12-11T08:24:25.927527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 9043
90.4%
1 876
 
8.8%
2 67
 
0.7%
3 11
 
0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
0 9043
90.4%
1 876
 
8.8%
2 67
 
0.7%
3 11
 
0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
4 2
 
< 0.1%
3 11
 
0.1%
2 67
 
0.7%
1 876
 
8.8%
0 9043
90.4%

승용승강기수
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0946
Minimum0
Maximum25
Zeros9472
Zeros (%)94.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:26.044509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum25
Range25
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5598948
Coefficient of variation (CV)5.9185497
Kurtosis504.12255
Mean0.0946
Median Absolute Deviation (MAD)0
Skewness16.211814
Sum946
Variance0.31348219
MonotonicityNot monotonic
2023-12-11T08:24:26.175338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 9472
94.7%
1 304
 
3.0%
2 142
 
1.4%
3 47
 
0.5%
4 15
 
0.1%
5 7
 
0.1%
6 7
 
0.1%
13 3
 
< 0.1%
25 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
0 9472
94.7%
1 304
 
3.0%
2 142
 
1.4%
3 47
 
0.5%
4 15
 
0.1%
5 7
 
0.1%
6 7
 
0.1%
7 1
 
< 0.1%
9 1
 
< 0.1%
13 3
 
< 0.1%
ValueCountFrequency (%)
25 1
 
< 0.1%
13 3
 
< 0.1%
9 1
 
< 0.1%
7 1
 
< 0.1%
6 7
 
0.1%
5 7
 
0.1%
4 15
 
0.1%
3 47
 
0.5%
2 142
1.4%
1 304
3.0%

비상용승강기수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0486
Minimum0
Maximum9
Zeros9749
Zeros (%)97.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:26.278556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.32840345
Coefficient of variation (CV)6.7572726
Kurtosis102.93429
Mean0.0486
Median Absolute Deviation (MAD)0
Skewness8.4491732
Sum486
Variance0.10784882
MonotonicityNot monotonic
2023-12-11T08:24:26.376399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 9749
97.5%
2 154
 
1.5%
1 62
 
0.6%
3 30
 
0.3%
4 3
 
< 0.1%
5 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
0 9749
97.5%
1 62
 
0.6%
2 154
 
1.5%
3 30
 
0.3%
4 3
 
< 0.1%
5 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
9 1
 
< 0.1%
5 1
 
< 0.1%
4 3
 
< 0.1%
3 30
 
0.3%
2 154
 
1.5%
1 62
 
0.6%
0 9749
97.5%

부속건축물수
Real number (ℝ)

SKEWED  ZEROS 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2359
Minimum0
Maximum212
Zeros8601
Zeros (%)86.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:26.503200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum212
Range212
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.2574678
Coefficient of variation (CV)9.5695964
Kurtosis7748.0936
Mean0.2359
Median Absolute Deviation (MAD)0
Skewness82.959452
Sum2359
Variance5.0961608
MonotonicityNot monotonic
2023-12-11T08:24:26.637162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 8601
86.0%
1 1071
 
10.7%
2 197
 
2.0%
3 46
 
0.5%
4 22
 
0.2%
7 15
 
0.1%
5 15
 
0.1%
6 14
 
0.1%
9 6
 
0.1%
8 4
 
< 0.1%
Other values (6) 9
 
0.1%
ValueCountFrequency (%)
0 8601
86.0%
1 1071
 
10.7%
2 197
 
2.0%
3 46
 
0.5%
4 22
 
0.2%
5 15
 
0.1%
6 14
 
0.1%
7 15
 
0.1%
8 4
 
< 0.1%
9 6
 
0.1%
ValueCountFrequency (%)
212 1
 
< 0.1%
25 1
 
< 0.1%
16 1
 
< 0.1%
12 1
 
< 0.1%
11 3
 
< 0.1%
10 2
 
< 0.1%
9 6
 
0.1%
8 4
 
< 0.1%
7 15
0.1%
6 14
0.1%

부속건축물면적(제곱미터)
Real number (ℝ)

SKEWED  ZEROS 

Distinct951
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.924128
Minimum0
Maximum69618.844
Zeros8616
Zeros (%)86.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:26.776471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile56.267
Maximum69618.844
Range69618.844
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1489.8148
Coefficient of variation (CV)17.542892
Kurtosis1232.2779
Mean84.924128
Median Absolute Deviation (MAD)0
Skewness31.864458
Sum849241.28
Variance2219548.2
MonotonicityNot monotonic
2023-12-11T08:24:26.915207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8616
86.2%
2.0 49
 
0.5%
1.0 26
 
0.3%
2.88 22
 
0.2%
1.44 15
 
0.1%
6.0 14
 
0.1%
3.0 14
 
0.1%
8.0 10
 
0.1%
1.2 9
 
0.1%
7.2 9
 
0.1%
Other values (941) 1216
 
12.2%
ValueCountFrequency (%)
0.0 8616
86.2%
0.81 4
 
< 0.1%
0.9 1
 
< 0.1%
1.0 26
 
0.3%
1.08 2
 
< 0.1%
1.1 2
 
< 0.1%
1.15 1
 
< 0.1%
1.2 9
 
0.1%
1.21 1
 
< 0.1%
1.32 2
 
< 0.1%
ValueCountFrequency (%)
69618.8443 2
< 0.1%
51804.2448 1
 
< 0.1%
37372.6704 2
< 0.1%
27318.0168 1
 
< 0.1%
23675.2912 1
 
< 0.1%
23331.2064 2
< 0.1%
23216.986 1
 
< 0.1%
22775.75 1
 
< 0.1%
22376.0945 3
< 0.1%
18671.156 1
 
< 0.1%

총동연면적(제곱미터)
Real number (ℝ)

ZEROS 

Distinct8043
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean913.21932
Minimum0
Maximum122661.03
Zeros157
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:27.118038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19.033
Q184
median241
Q3489.925
95-th percentile4884.975
Maximum122661.03
Range122661.03
Interquartile range (IQR)405.925

Descriptive statistics

Standard deviation3229.9971
Coefficient of variation (CV)3.5369347
Kurtosis442.6197
Mean913.21932
Median Absolute Deviation (MAD)175
Skewness15.889087
Sum9132193.2
Variance10432882
MonotonicityNot monotonic
2023-12-11T08:24:27.308728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 157
 
1.6%
6.25 38
 
0.4%
19.83 36
 
0.4%
23.14 28
 
0.3%
26.45 26
 
0.3%
84.0 18
 
0.2%
60.0 18
 
0.2%
39.67 17
 
0.2%
33.06 17
 
0.2%
46.28 17
 
0.2%
Other values (8033) 9628
96.3%
ValueCountFrequency (%)
0.0 157
1.6%
0.6 1
 
< 0.1%
0.99 1
 
< 0.1%
1.0 4
 
< 0.1%
1.1 1
 
< 0.1%
1.44 2
 
< 0.1%
1.65 1
 
< 0.1%
1.77 1
 
< 0.1%
1.8 1
 
< 0.1%
1.82 1
 
< 0.1%
ValueCountFrequency (%)
122661.03 1
< 0.1%
116481.3569 1
< 0.1%
65063.3312 1
< 0.1%
64715.9374 1
< 0.1%
59909.2762 1
< 0.1%
54395.4 1
< 0.1%
47778.9245 1
< 0.1%
46674.83 1
< 0.1%
43633.7 1
< 0.1%
42741.723 1
< 0.1%

옥내기계식대수(대)
Real number (ℝ)

SKEWED  ZEROS 

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1148
Minimum0
Maximum104
Zeros9951
Zeros (%)99.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:27.498388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum104
Range104
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.2206112
Coefficient of variation (CV)19.343303
Kurtosis1068.1446
Mean0.1148
Median Absolute Deviation (MAD)0
Skewness29.292699
Sum1148
Variance4.9311141
MonotonicityNot monotonic
2023-12-11T08:24:27.645433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 9951
99.5%
8 7
 
0.1%
14 3
 
< 0.1%
15 3
 
< 0.1%
9 3
 
< 0.1%
7 2
 
< 0.1%
19 2
 
< 0.1%
40 2
 
< 0.1%
10 2
 
< 0.1%
24 2
 
< 0.1%
Other values (22) 23
 
0.2%
ValueCountFrequency (%)
0 9951
99.5%
1 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
7 2
 
< 0.1%
8 7
 
0.1%
9 3
 
< 0.1%
10 2
 
< 0.1%
11 1
 
< 0.1%
14 3
 
< 0.1%
ValueCountFrequency (%)
104 1
< 0.1%
96 1
< 0.1%
70 1
< 0.1%
58 1
< 0.1%
48 1
< 0.1%
46 1
< 0.1%
40 2
< 0.1%
38 1
< 0.1%
35 1
< 0.1%
34 1
< 0.1%

옥내기계식면적(제곱미터)
Real number (ℝ)

SKEWED  ZEROS 

Distinct45
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8241888
Minimum0
Maximum739.58
Zeros9956
Zeros (%)99.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:27.780227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum739.58
Range739.58
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16.293002
Coefficient of variation (CV)19.768531
Kurtosis811.07967
Mean0.8241888
Median Absolute Deviation (MAD)0
Skewness26.121463
Sum8241.888
Variance265.46192
MonotonicityNot monotonic
2023-12-11T08:24:27.926062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0.0 9956
99.6%
79.38 1
 
< 0.1%
11.5 1
 
< 0.1%
37.7 1
 
< 0.1%
68.64 1
 
< 0.1%
211.29 1
 
< 0.1%
49.58 1
 
< 0.1%
476.68 1
 
< 0.1%
143.51 1
 
< 0.1%
94.72 1
 
< 0.1%
Other values (35) 35
 
0.4%
ValueCountFrequency (%)
0.0 9956
99.6%
11.5 1
 
< 0.1%
37.7 1
 
< 0.1%
42.0 1
 
< 0.1%
42.3 1
 
< 0.1%
42.84 1
 
< 0.1%
43.8 1
 
< 0.1%
46.8 1
 
< 0.1%
47.36 1
 
< 0.1%
48.6 1
 
< 0.1%
ValueCountFrequency (%)
739.58 1
< 0.1%
476.68 1
< 0.1%
446.72 1
< 0.1%
427.68 1
< 0.1%
416.13 1
< 0.1%
406.7 1
< 0.1%
384.86 1
< 0.1%
383.66 1
< 0.1%
324.41 1
< 0.1%
320.44 1
< 0.1%

옥외기계식대수(대)
Real number (ℝ)

SKEWED  ZEROS 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0133
Minimum0
Maximum30
Zeros9987
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:28.040978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum30
Range30
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.50274087
Coefficient of variation (CV)37.800066
Kurtosis2358.7505
Mean0.0133
Median Absolute Deviation (MAD)0
Skewness46.554898
Sum133
Variance0.25274838
MonotonicityNot monotonic
2023-12-11T08:24:28.137305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 9987
99.9%
1 2
 
< 0.1%
4 2
 
< 0.1%
18 2
 
< 0.1%
30 1
 
< 0.1%
13 1
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
3 1
 
< 0.1%
2 1
 
< 0.1%
ValueCountFrequency (%)
0 9987
99.9%
1 2
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 2
 
< 0.1%
5 1
 
< 0.1%
8 1
 
< 0.1%
13 1
 
< 0.1%
18 2
 
< 0.1%
26 1
 
< 0.1%
ValueCountFrequency (%)
30 1
< 0.1%
26 1
< 0.1%
18 2
< 0.1%
13 1
< 0.1%
8 1
< 0.1%
5 1
< 0.1%
4 2
< 0.1%
3 1
< 0.1%
2 1
< 0.1%
1 2
< 0.1%

옥외기계식면적(제곱미터)
Real number (ℝ)

SKEWED  ZEROS 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.052543
Minimum0
Maximum92
Zeros9988
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:28.233354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum92
Range92
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.670125
Coefficient of variation (CV)31.785871
Kurtosis1525.9479
Mean0.052543
Median Absolute Deviation (MAD)0
Skewness36.828451
Sum525.43
Variance2.7893176
MonotonicityNot monotonic
2023-12-11T08:24:28.325210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.0 9988
99.9%
11.5 1
 
< 0.1%
47.95 1
 
< 0.1%
57.6 1
 
< 0.1%
29.0 1
 
< 0.1%
57.5 1
 
< 0.1%
92.0 1
 
< 0.1%
51.68 1
 
< 0.1%
41.82 1
 
< 0.1%
34.5 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
ValueCountFrequency (%)
0.0 9988
99.9%
11.5 1
 
< 0.1%
23.0 1
 
< 0.1%
27.04 1
 
< 0.1%
29.0 1
 
< 0.1%
34.5 1
 
< 0.1%
41.82 1
 
< 0.1%
47.95 1
 
< 0.1%
51.68 1
 
< 0.1%
51.84 1
 
< 0.1%
ValueCountFrequency (%)
92.0 1
< 0.1%
57.6 1
< 0.1%
57.5 1
< 0.1%
51.84 1
< 0.1%
51.68 1
< 0.1%
47.95 1
< 0.1%
41.82 1
< 0.1%
34.5 1
< 0.1%
29.0 1
< 0.1%
27.04 1
< 0.1%

옥내자주식대수(대)
Real number (ℝ)

SKEWED  ZEROS 

Distinct85
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.567
Minimum0
Maximum2223
Zeros9124
Zeros (%)91.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:28.453249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum2223
Range2223
Interquartile range (IQR)0

Descriptive statistics

Standard deviation42.603847
Coefficient of variation (CV)11.943888
Kurtosis889.74532
Mean3.567
Median Absolute Deviation (MAD)0
Skewness24.04745
Sum35670
Variance1815.0878
MonotonicityNot monotonic
2023-12-11T08:24:28.573121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9124
91.2%
1 139
 
1.4%
2 120
 
1.2%
6 92
 
0.9%
4 84
 
0.8%
3 83
 
0.8%
5 48
 
0.5%
8 47
 
0.5%
7 32
 
0.3%
11 16
 
0.2%
Other values (75) 215
 
2.1%
ValueCountFrequency (%)
0 9124
91.2%
1 139
 
1.4%
2 120
 
1.2%
3 83
 
0.8%
4 84
 
0.8%
5 48
 
0.5%
6 92
 
0.9%
7 32
 
0.3%
8 47
 
0.5%
9 14
 
0.1%
ValueCountFrequency (%)
2223 1
 
< 0.1%
917 2
 
< 0.1%
837 2
 
< 0.1%
776 2
 
< 0.1%
653 3
< 0.1%
593 3
< 0.1%
540 1
 
< 0.1%
520 1
 
< 0.1%
515 6
0.1%
498 3
< 0.1%

옥내자주식면적(제곱미터)
Real number (ℝ)

ZEROS 

Distinct454
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.663738
Minimum0
Maximum31132.91
Zeros9161
Zeros (%)91.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:28.710336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile50.039
Maximum31132.91
Range31132.91
Interquartile range (IQR)0

Descriptive statistics

Standard deviation980.32467
Coefficient of variation (CV)12.787332
Kurtosis445.21366
Mean76.663738
Median Absolute Deviation (MAD)0
Skewness19.375289
Sum766637.38
Variance961036.46
MonotonicityNot monotonic
2023-12-11T08:24:28.857826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9161
91.6%
104.68 51
 
0.5%
23.0 44
 
0.4%
46.0 39
 
0.4%
11.5 38
 
0.4%
34.5 37
 
0.4%
92.0 28
 
0.3%
69.0 23
 
0.2%
57.5 18
 
0.2%
80.5 7
 
0.1%
Other values (444) 554
 
5.5%
ValueCountFrequency (%)
0.0 9161
91.6%
5.4 1
 
< 0.1%
11.22 1
 
< 0.1%
11.5 38
 
0.4%
12.0 1
 
< 0.1%
12.25 1
 
< 0.1%
12.5 2
 
< 0.1%
12.63 1
 
< 0.1%
13.39 1
 
< 0.1%
13.5 1
 
< 0.1%
ValueCountFrequency (%)
31132.91 2
< 0.1%
25852.0 1
 
< 0.1%
23225.93 2
< 0.1%
21018.4411 2
< 0.1%
17264.343 3
< 0.1%
17171.49 3
< 0.1%
14757.16 4
< 0.1%
12116.77 1
 
< 0.1%
10813.76 3
< 0.1%
9640.989 1
 
< 0.1%

옥외자주식대수(대)
Real number (ℝ)

SKEWED  ZEROS 

Distinct109
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.115
Minimum0
Maximum4671
Zeros5909
Zeros (%)59.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:29.248789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile10
Maximum4671
Range4671
Interquartile range (IQR)2

Descriptive statistics

Standard deviation144.80473
Coefficient of variation (CV)11.952516
Kurtosis858.18425
Mean12.115
Median Absolute Deviation (MAD)0
Skewness27.376846
Sum121150
Variance20968.41
MonotonicityNot monotonic
2023-12-11T08:24:29.362336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5909
59.1%
2 942
 
9.4%
1 814
 
8.1%
4 526
 
5.3%
5 418
 
4.2%
3 394
 
3.9%
6 174
 
1.7%
8 155
 
1.6%
7 114
 
1.1%
10 52
 
0.5%
Other values (99) 502
 
5.0%
ValueCountFrequency (%)
0 5909
59.1%
1 814
 
8.1%
2 942
 
9.4%
3 394
 
3.9%
4 526
 
5.3%
5 418
 
4.2%
6 174
 
1.7%
7 114
 
1.1%
8 155
 
1.6%
9 49
 
0.5%
ValueCountFrequency (%)
4671 8
 
0.1%
726 51
0.5%
657 2
 
< 0.1%
607 1
 
< 0.1%
602 2
 
< 0.1%
575 1
 
< 0.1%
500 1
 
< 0.1%
479 3
 
< 0.1%
468 3
 
< 0.1%
463 1
 
< 0.1%

옥외자주식면적(제곱미터)
Real number (ℝ)

SKEWED  ZEROS 

Distinct322
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean266.08016
Minimum0
Maximum163799
Zeros5989
Zeros (%)59.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:29.474169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q323
95-th percentile103.5
Maximum163799
Range163799
Interquartile range (IQR)23

Descriptive statistics

Standard deviation4807.5533
Coefficient of variation (CV)18.068064
Kurtosis1069.7056
Mean266.08016
Median Absolute Deviation (MAD)0
Skewness31.746361
Sum2660801.6
Variance23112569
MonotonicityNot monotonic
2023-12-11T08:24:29.581959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 5989
59.9%
23.0 863
 
8.6%
11.5 674
 
6.7%
46.0 404
 
4.0%
34.5 320
 
3.2%
57.5 289
 
2.9%
69.0 145
 
1.5%
92.0 132
 
1.3%
58.0 94
 
0.9%
80.5 88
 
0.9%
Other values (312) 1002
 
10.0%
ValueCountFrequency (%)
0.0 5989
59.9%
1.5 1
 
< 0.1%
6.0 2
 
< 0.1%
7.2 2
 
< 0.1%
7.36 1
 
< 0.1%
8.4 1
 
< 0.1%
10.0 9
 
0.1%
11.0 2
 
< 0.1%
11.3 1
 
< 0.1%
11.5 674
 
6.7%
ValueCountFrequency (%)
163799.0 8
 
0.1%
18900.0 1
 
< 0.1%
17621.11 51
0.5%
9869.75 2
 
< 0.1%
7579.65 2
 
< 0.1%
7066.5 1
 
< 0.1%
5750.0 1
 
< 0.1%
4404.5 6
 
0.1%
4255.0 1
 
< 0.1%
4158.0 1
 
< 0.1%

허가일
Date

MISSING 

Distinct4214
Distinct (%)59.4%
Missing2902
Missing (%)29.0%
Memory size156.2 KiB
Minimum1974-03-21 00:00:00
Maximum2021-02-15 00:00:00
2023-12-11T08:24:29.698796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:29.819240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공일
Date

MISSING 

Distinct4033
Distinct (%)62.8%
Missing3578
Missing (%)35.8%
Memory size156.2 KiB
Minimum1974-03-25 00:00:00
Maximum2021-03-15 00:00:00
2023-12-11T08:24:29.935220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:30.057053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용승인일
Date

MISSING 

Distinct5109
Distinct (%)53.3%
Missing414
Missing (%)4.1%
Memory size156.2 KiB
Minimum1900-04-30 00:00:00
Maximum2021-05-21 00:00:00
2023-12-11T08:24:30.179364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:30.311004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

허가번호년
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)0.7%
Missing6215
Missing (%)62.2%
Infinite0
Infinite (%)0.0%
Mean2011.3112
Minimum1993
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:30.444951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1993
5-th percentile2003
Q12008
median2012
Q32015
95-th percentile2018
Maximum2021
Range28
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.6127917
Coefficient of variation (CV)0.0022934251
Kurtosis-0.50946858
Mean2011.3112
Median Absolute Deviation (MAD)3
Skewness-0.31793845
Sum7612813
Variance21.277847
MonotonicityNot monotonic
2023-12-11T08:24:30.569457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2011 382
 
3.8%
2012 373
 
3.7%
2016 313
 
3.1%
2015 284
 
2.8%
2014 270
 
2.7%
2013 246
 
2.5%
2010 234
 
2.3%
2007 225
 
2.2%
2006 190
 
1.9%
2017 177
 
1.8%
Other values (17) 1091
 
10.9%
(Missing) 6215
62.2%
ValueCountFrequency (%)
1993 1
 
< 0.1%
1994 1
 
< 0.1%
1996 1
 
< 0.1%
1997 1
 
< 0.1%
1999 3
 
< 0.1%
2000 4
 
< 0.1%
2001 14
 
0.1%
2002 156
1.6%
2003 89
0.9%
2004 70
0.7%
ValueCountFrequency (%)
2021 7
 
0.1%
2020 78
 
0.8%
2019 74
 
0.7%
2018 131
 
1.3%
2017 177
1.8%
2016 313
3.1%
2015 284
2.8%
2014 270
2.7%
2013 246
2.5%
2012 373
3.7%

허가번호기관코드
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)0.9%
Missing6243
Missing (%)62.4%
Infinite0
Infinite (%)0.0%
Mean5359192.8
Minimum5350019
Maximum6480624
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:30.689734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5350019
5-th percentile5350108
Q15350141
median5350178
Q35350178
95-th percentile5350276
Maximum6480624
Range1130605
Interquartile range (IQR)37

Descriptive statistics

Standard deviation100584.12
Coefficient of variation (CV)0.018768521
Kurtosis120.40312
Mean5359192.8
Median Absolute Deviation (MAD)24
Skewness11.060696
Sum2.0134487 × 1010
Variance1.0117165 × 1010
MonotonicityNot monotonic
2023-12-11T08:24:30.824553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
5350178 1541
 
15.4%
5350154 590
 
5.9%
5350141 375
 
3.8%
5350276 341
 
3.4%
5350140 213
 
2.1%
5350109 163
 
1.6%
5350093 101
 
1.0%
5350245 94
 
0.9%
5350152 92
 
0.9%
5350108 73
 
0.7%
Other values (22) 174
 
1.7%
(Missing) 6243
62.4%
ValueCountFrequency (%)
5350019 42
0.4%
5350023 2
 
< 0.1%
5350024 10
 
0.1%
5350047 2
 
< 0.1%
5350048 1
 
< 0.1%
5350055 1
 
< 0.1%
5350058 1
 
< 0.1%
5350059 2
 
< 0.1%
5350060 5
 
0.1%
5350061 1
 
< 0.1%
ValueCountFrequency (%)
6480624 6
 
0.1%
6480040 22
 
0.2%
6480000 2
 
< 0.1%
5350321 5
 
0.1%
5350276 341
 
3.4%
5350275 23
 
0.2%
5350245 94
 
0.9%
5350244 12
 
0.1%
5350178 1541
15.4%
5350177 29
 
0.3%

허가번호기관코드명
Categorical

IMBALANCE 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6243 
허가민원과
1647 
허가과
879 
도시관리과
 
590
건축과
 
309
Other values (18)
 
332

Length

Max length7
Median length4
Mean length4.1469
Min length3

Unique

Unique6 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6243
62.4%
허가민원과 1647
 
16.5%
허가과 879
 
8.8%
도시관리과 590
 
5.9%
건축과 309
 
3.1%
공동주택관리과 94
 
0.9%
장유출장소 92
 
0.9%
건축민원과 42
 
0.4%
주택과 38
 
0.4%
도시계획과 30
 
0.3%
Other values (13) 36
 
0.4%

Length

2023-12-11T08:24:30.972739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6243
62.4%
허가민원과 1647
 
16.5%
허가과 879
 
8.8%
도시관리과 590
 
5.9%
건축과 309
 
3.1%
공동주택관리과 94
 
0.9%
장유출장소 92
 
0.9%
건축민원과 42
 
0.4%
주택과 38
 
0.4%
도시계획과 30
 
0.3%
Other values (13) 36
 
0.4%

허가번호구분코드
Real number (ℝ)

MISSING 

Distinct17
Distinct (%)0.4%
Missing6213
Missing (%)62.1%
Infinite0
Infinite (%)0.0%
Mean1306.6686
Minimum1101
Maximum5801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:31.074025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1101
5-th percentile1101
Q11101
median1101
Q31102
95-th percentile2101
Maximum5801
Range4700
Interquartile range (IQR)1

Descriptive statistics

Standard deviation674.18683
Coefficient of variation (CV)0.51595855
Kurtosis25.025564
Mean1306.6686
Median Absolute Deviation (MAD)0
Skewness4.8185402
Sum4948354
Variance454527.89
MonotonicityNot monotonic
2023-12-11T08:24:31.186960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1101 2666
26.7%
1201 392
 
3.9%
2101 359
 
3.6%
1102 193
 
1.9%
1202 69
 
0.7%
5310 39
 
0.4%
5200 22
 
0.2%
2301 14
 
0.1%
5100 12
 
0.1%
5701 8
 
0.1%
Other values (7) 13
 
0.1%
(Missing) 6213
62.1%
ValueCountFrequency (%)
1101 2666
26.7%
1102 193
 
1.9%
1103 2
 
< 0.1%
1104 4
 
< 0.1%
1107 1
 
< 0.1%
1201 392
 
3.9%
1202 69
 
0.7%
1204 1
 
< 0.1%
1207 1
 
< 0.1%
2101 359
 
3.6%
ValueCountFrequency (%)
5801 1
 
< 0.1%
5701 8
 
0.1%
5320 3
 
< 0.1%
5310 39
 
0.4%
5200 22
 
0.2%
5100 12
 
0.1%
2301 14
 
0.1%
2101 359
3.6%
1207 1
 
< 0.1%
1204 1
 
< 0.1%

허가번호구분코드명
Categorical

IMBALANCE 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6213 
신축허가
2666 
신축신고
 
392
주택건설사업계획승인
 
359
증축허가
 
193
Other values (13)
 
177

Length

Max length12
Median length4
Mean length4.2686
Min length4

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6213
62.1%
신축허가 2666
26.7%
신축신고 392
 
3.9%
주택건설사업계획승인 359
 
3.6%
증축허가 193
 
1.9%
증축신고 69
 
0.7%
개발제한구역내 건축허가 39
 
0.4%
공용건축물 22
 
0.2%
임대주택건설사업계획승인 14
 
0.1%
협의건축물 12
 
0.1%
Other values (8) 21
 
0.2%

Length

2023-12-11T08:24:31.310778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6213
61.9%
신축허가 2666
26.5%
신축신고 392
 
3.9%
주택건설사업계획승인 359
 
3.6%
증축허가 193
 
1.9%
증축신고 69
 
0.7%
개발제한구역내 42
 
0.4%
건축허가 39
 
0.4%
공용건축물 22
 
0.2%
임대주택건설사업계획승인 14
 
0.1%
Other values (9) 33
 
0.3%

호수(호)
Real number (ℝ)

SKEWED  ZEROS 

Distinct56
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3607
Minimum0
Maximum253
Zeros9787
Zeros (%)97.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:31.430973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum253
Range253
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.9866705
Coefficient of variation (CV)13.82498
Kurtosis1194.1523
Mean0.3607
Median Absolute Deviation (MAD)0
Skewness29.508593
Sum3607
Variance24.866882
MonotonicityNot monotonic
2023-12-11T08:24:31.570000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9787
97.9%
1 42
 
0.4%
2 18
 
0.2%
4 15
 
0.1%
7 11
 
0.1%
6 10
 
0.1%
12 10
 
0.1%
3 9
 
0.1%
22 6
 
0.1%
5 6
 
0.1%
Other values (46) 86
 
0.9%
ValueCountFrequency (%)
0 9787
97.9%
1 42
 
0.4%
2 18
 
0.2%
3 9
 
0.1%
4 15
 
0.1%
5 6
 
0.1%
6 10
 
0.1%
7 11
 
0.1%
8 4
 
< 0.1%
9 5
 
0.1%
ValueCountFrequency (%)
253 1
< 0.1%
226 1
< 0.1%
120 1
< 0.1%
93 1
< 0.1%
91 1
< 0.1%
86 1
< 0.1%
85 1
< 0.1%
84 1
< 0.1%
81 1
< 0.1%
79 1
< 0.1%
Distinct1109
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2009-03-21 00:00:00
Maximum2021-06-01 00:00:00
2023-12-11T08:24:31.698808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:24:31.826272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
3935 
<NA>
3929 
1
2136 

Length

Max length4
Median length1
Mean length2.1787
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row<NA>
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
0 3935
39.4%
<NA> 3929
39.3%
1 2136
21.4%

Length

2023-12-11T08:24:31.950191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:24:32.042570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 3935
39.4%
na 3929
39.3%
1 2136
21.4%

내진능력
Text

MISSING 

Distinct114
Distinct (%)35.8%
Missing9682
Missing (%)96.8%
Memory size156.2 KiB
2023-12-11T08:24:32.296832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29
Mean length9.1509434
Min length1

Characters and Unicode

Total characters2910
Distinct characters68
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)23.6%

Sample

1st rowVII-0.2159g
2nd rowⅦ-0.239g
3rd rowⅦ-0.199g
4th rowⅦ-0.185g
5th rowⅦ-0.199g
ValueCountFrequency (%)
ⅶ-0.214g 32
 
8.7%
ⅶ-0.199g 25
 
6.8%
ⅶ-0.191g 17
 
4.6%
vii-0.182g 15
 
4.1%
vii-0.173g 14
 
3.8%
13
 
3.5%
vii-0.214g 12
 
3.3%
vii-0.2159g 10
 
2.7%
vii-0.199g 9
 
2.4%
ⅶ-0.173g 9
 
2.4%
Other values (115) 212
57.6%
2023-12-11T08:24:32.744943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 328
11.3%
. 298
10.2%
- 285
9.8%
g 283
9.7%
1 277
9.5%
I 226
7.8%
9 185
 
6.4%
2 183
 
6.3%
169
 
5.8%
V 121
 
4.2%
Other values (58) 555
19.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1241
42.6%
Uppercase Letter 363
 
12.5%
Lowercase Letter 325
 
11.2%
Other Punctuation 311
 
10.7%
Dash Punctuation 285
 
9.8%
Letter Number 173
 
5.9%
Other Letter 134
 
4.6%
Space Separator 55
 
1.9%
Open Punctuation 9
 
0.3%
Close Punctuation 9
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
19
14.2%
19
14.2%
10
 
7.5%
8
 
6.0%
7
 
5.2%
7
 
5.2%
7
 
5.2%
7
 
5.2%
6
 
4.5%
6
 
4.5%
Other values (22) 38
28.4%
Decimal Number
ValueCountFrequency (%)
0 328
26.4%
1 277
22.3%
9 185
14.9%
2 183
14.7%
4 61
 
4.9%
7 58
 
4.7%
3 47
 
3.8%
8 43
 
3.5%
6 32
 
2.6%
5 27
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
I 226
62.3%
V 121
33.3%
M 6
 
1.7%
D 4
 
1.1%
S 2
 
0.6%
C 2
 
0.6%
G 2
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
g 283
87.1%
l 28
 
8.6%
v 6
 
1.8%
i 6
 
1.8%
y 1
 
0.3%
x 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 298
95.8%
: 5
 
1.6%
, 4
 
1.3%
/ 3
 
1.0%
; 1
 
0.3%
Letter Number
ValueCountFrequency (%)
169
97.7%
3
 
1.7%
1
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 285
100.0%
Space Separator
ValueCountFrequency (%)
55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Math Symbol
ValueCountFrequency (%)
= 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1915
65.8%
Latin 861
29.6%
Hangul 134
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
19
14.2%
19
14.2%
10
 
7.5%
8
 
6.0%
7
 
5.2%
7
 
5.2%
7
 
5.2%
7
 
5.2%
6
 
4.5%
6
 
4.5%
Other values (22) 38
28.4%
Common
ValueCountFrequency (%)
0 328
17.1%
. 298
15.6%
- 285
14.9%
1 277
14.5%
9 185
9.7%
2 183
9.6%
4 61
 
3.2%
7 58
 
3.0%
55
 
2.9%
3 47
 
2.5%
Other values (10) 138
7.2%
Latin
ValueCountFrequency (%)
g 283
32.9%
I 226
26.2%
169
19.6%
V 121
14.1%
l 28
 
3.3%
M 6
 
0.7%
v 6
 
0.7%
i 6
 
0.7%
D 4
 
0.5%
3
 
0.3%
Other values (6) 9
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2603
89.5%
Number Forms 173
 
5.9%
Hangul 134
 
4.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 328
12.6%
. 298
11.4%
- 285
10.9%
g 283
10.9%
1 277
10.6%
I 226
8.7%
9 185
7.1%
2 183
7.0%
V 121
 
4.6%
4 61
 
2.3%
Other values (23) 356
13.7%
Number Forms
ValueCountFrequency (%)
169
97.7%
3
 
1.7%
1
 
0.6%
Hangul
ValueCountFrequency (%)
19
14.2%
19
14.2%
10
 
7.5%
8
 
6.0%
7
 
5.2%
7
 
5.2%
7
 
5.2%
7
 
5.2%
6
 
4.5%
6
 
4.5%
Other values (22) 38
28.4%

위도
Real number (ℝ)

Distinct8706
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.23862
Minimum35.156332
Maximum35.327138
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:32.905132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.156332
5-th percentile35.178137
Q135.220602
median35.234939
Q335.252809
95-th percentile35.307884
Maximum35.327138
Range0.17080646
Interquartile range (IQR)0.0322071

Descriptive statistics

Standard deviation0.036098167
Coefficient of variation (CV)0.0010243922
Kurtosis-0.13903334
Mean35.23862
Median Absolute Deviation (MAD)0.01654285
Skewness0.38986435
Sum352386.2
Variance0.0013030777
MonotonicityNot monotonic
2023-12-11T08:24:33.074502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.17891261 51
 
0.5%
35.18959136 23
 
0.2%
35.2263586 21
 
0.2%
35.21800727 20
 
0.2%
35.23677849 15
 
0.1%
35.19726774 14
 
0.1%
35.22689899 12
 
0.1%
35.26540217 12
 
0.1%
35.23488009 11
 
0.1%
35.17892199 10
 
0.1%
Other values (8696) 9811
98.1%
ValueCountFrequency (%)
35.15633158 8
0.1%
35.16316868 2
 
< 0.1%
35.1633574 1
 
< 0.1%
35.16370065 8
0.1%
35.16416817 1
 
< 0.1%
35.16481319 1
 
< 0.1%
35.16506123 3
 
< 0.1%
35.16527889 1
 
< 0.1%
35.16556122 1
 
< 0.1%
35.16583369 1
 
< 0.1%
ValueCountFrequency (%)
35.32713804 3
< 0.1%
35.32629501 1
 
< 0.1%
35.32579416 1
 
< 0.1%
35.32564048 1
 
< 0.1%
35.32537338 1
 
< 0.1%
35.32527357 1
 
< 0.1%
35.32526967 1
 
< 0.1%
35.32514973 1
 
< 0.1%
35.3250935 1
 
< 0.1%
35.32494229 1
 
< 0.1%

경도
Real number (ℝ)

Distinct8687
Distinct (%)86.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.83724
Minimum128.70351
Maximum128.93054
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:24:33.236880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.70351
5-th percentile128.72715
Q1128.80512
median128.85208
Q3128.88186
95-th percentile128.91419
Maximum128.93054
Range0.2270311
Interquartile range (IQR)0.076745425

Descriptive statistics

Standard deviation0.057957827
Coefficient of variation (CV)0.00044985308
Kurtosis-0.68085617
Mean128.83724
Median Absolute Deviation (MAD)0.037792
Skewness-0.57966064
Sum1288372.4
Variance0.0033591098
MonotonicityNot monotonic
2023-12-11T08:24:33.391216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8285602 51
 
0.5%
128.8433276 23
 
0.2%
128.8486299 21
 
0.2%
128.8594501 20
 
0.2%
128.825249 15
 
0.1%
128.8000964 14
 
0.1%
128.8937084 12
 
0.1%
128.8708647 12
 
0.1%
128.8772066 11
 
0.1%
128.7976766 10
 
0.1%
Other values (8677) 9811
98.1%
ValueCountFrequency (%)
128.7035053 1
< 0.1%
128.7058502 1
< 0.1%
128.705852 1
< 0.1%
128.7060642 1
< 0.1%
128.7061557 1
< 0.1%
128.7065176 1
< 0.1%
128.7065482 1
< 0.1%
128.7066123 1
< 0.1%
128.7066623 1
< 0.1%
128.706738 1
< 0.1%
ValueCountFrequency (%)
128.9305364 1
< 0.1%
128.9303586 1
< 0.1%
128.9303307 1
< 0.1%
128.9300136 1
< 0.1%
128.929974 1
< 0.1%
128.9296119 1
< 0.1%
128.9295942 1
< 0.1%
128.9295418 1
< 0.1%
128.9294211 1
< 0.1%
128.9292698 1
< 0.1%

Sample

순번번지주소도로명주소관리건축물대장대장구분코드명대장종류코드명건물명특수지명블록로트외필지수새주소도로코드새주소법정동코드새주소지상지하코드새주소본번새주소부번동명칭주부속구분코드주부속구분코드명대지면적(제곱미터)건축면적(제곱미터)건폐율(퍼센트)연면적(제곱미터)용적률산정연면적(제곱미터)용적률(퍼센트)구조코드구조코드명기타구조주용도코드주용도코드명기타용도지붕코드지붕코드명기타지붕세대수(세대)가구수(가구)높이(미터)지상층수지하층수승용승강기수비상용승강기수부속건축물수부속건축물면적(제곱미터)총동연면적(제곱미터)옥내기계식대수(대)옥내기계식면적(제곱미터)옥외기계식대수(대)옥외기계식면적(제곱미터)옥내자주식대수(대)옥내자주식면적(제곱미터)옥외자주식대수(대)옥외자주식면적(제곱미터)허가일착공일사용승인일허가번호년허가번호기관코드허가번호기관코드명허가번호구분코드허가번호구분코드명호수(호)생성일자내진설계적용여부내진능력위도경도
48824883경상남도 김해시 내동 1083-10번지108310경상남도 김해시 경원로11번길 31-1048250-102011395일반일반건축물<NA><NA><NA><NA>04830000000001080103110<NA>0주건축물213.2125.959.05351.57351.57164.921철근콘크리트구조철근콘크리트구조1000단독주택단독주택(5가구)10(철근)콘크리트슬라브059.72300000.0351.5700.000.0223.0223.02008-06-132008-06-172008-09-0920085350141허가과1101신축허가02019-05-301<NA>35.24113128.864254
58205821경상남도 김해시 내동 530번지5300경상남도 김해시 금관대로 1269-148250-35816집합표제부<NA><NA><NA><NA>048300000000010801012691<NA>0주건축물202.0102.0850.53181.38181.3889.7911벽돌구조시멘트벽돌조2000공동주택공동주택10(철근)콘크리트슬라브300.0200000.0181.3800.000.000.000.01989-07-21<NA>1991-10-08<NA><NA><NA><NA><NA>02017-02-22<NA><NA>35.238534128.859184
60776078경상남도 김해시 외동 1199-3번지11993경상남도 김해시 함박로45번길 23-1148250-102047439일반일반건축물<NA><NA><NA><NA>04830000000001090102311<NA>0주건축물282.3163.4457.9443.37443.37157.0621철근콘크리트구조철근콘크리트구조1000단독주택단독주택(10가구)10(철근)콘크리트경사스라브0109.35300000.0443.3700.000.000.0892.52011-07-142011-07-162011-10-2520115350178허가민원과1101신축허가02019-05-301<NA>35.234541128.857911
1484914850경상남도 김해시 무계동 491번지491048250-32614일반일반건축물<NA><NA><NA><NA>0<NA><NA>0<NA><NA><NA>0주건축물0.00.00.029.050.00.012블록구조블럭조1000단독주택주택30슬레이트스레이트000.0100000.029.0500.000.000.000.0<NA><NA>1970-12-20<NA><NA><NA><NA><NA>02013-09-27<NA><NA>35.197894128.811578
70777078경상남도 김해시 흥동 322-2번지3222경상남도 김해시 전하로124번길 38-1548250-40064일반일반건축물<NA><NA><NA><NA>04830000000001100103815<NA>0주건축물142.070.4449.670.4470.4449.651일반목구조목조1000단독주택단독주택30슬레이트스레이트010.01000136.070.4400.000.000.000.0<NA><NA>1938-12-20<NA><NA><NA><NA><NA>02017-03-21<NA><NA>35.217254128.861386
2486924870경상남도 김해시 진례면 청천리 438번지4380경상남도 김해시 진례면 서부로396번길 8348250-21151일반일반건축물<NA><NA><NA><NA>0483000000000330020830<NA>0주건축물574.0145.225.3142.8142.824.8819기타조적구조조적조1000단독주택단독주택10(철근)콘크리트슬라브014.31000145.6142.800.000.000.000.01991-05-111991-05-111999-08-16<NA><NA><NA><NA><NA>02014-04-09<NA><NA>35.271964128.748567
1364513646경상남도 김해시 유하동 509-4번지5094경상남도 김해시 유하로133번길 92-148250-102132185일반일반건축물<NA><NA><NA><NA>1483000000000123020921<NA>0주건축물1284.0725.5656.5789.56789.5661.4931일반철골구조일반철골구조17000공장공장90기타지붕일반철골구조/준불연판넬0012.010001141.56648.000.000.000.0334.52016-04-052016-06-102017-03-2120165350154도시관리과1101신축허가02017-04-21<NA><NA>35.218707128.809007
2346123462경상남도 김해시 주촌면 내삼리 117-2번지1172경상남도 김해시 주촌면 서부로1541번길 164-2348250-37033일반일반건축물<NA><NA><NA><NA>048300000000032001016423<NA>0주건축물0.0251.860.0300.86300.860.031일반철골구조철골조17000공장공장90기타지붕불연판넬009.9200000.0300.8600.000.000.000.02005-04-292005-05-042005-07-19<NA><NA><NA><NA><NA>02017-04-22<NA><NA>35.241832128.809742
97009701경상남도 김해시 삼정동 659-1번지6591경상남도 김해시 김해대로2491번길 2448250-47556일반일반건축물<NA><NA><NA><NA>048300000000011701024<NA><NA>0주건축물365.8139.8738.24134.52134.5236.7721철근콘크리트구조철근콘크리트조/조립식판넬4000제2종근린생활시설제1.2종근린생활시설90기타지붕판넬/슬라브003.4100013.0134.5200.000.000.000.01994-12-01<NA>1995-09-06<NA><NA><NA><NA><NA>02017-11-18<NA><NA>35.230187128.898809
47224723경상남도 김해시 삼계동 807-3번지807348250-102093919일반일반건축물<NA><NA><NA><NA>148300000000010701067<NA><NA>0주건축물187.071.632.2971.671.632.2932경량철골구조경량철골구조4000제2종근린생활시설제2종근린생활시설90기타지붕판넬004.85100000.071.600.000.000.000.02013-11-052013-12-032014-10-2920135350178허가민원과1201신축신고02021-03-290<NA>35.275979128.867944
순번번지주소도로명주소관리건축물대장대장구분코드명대장종류코드명건물명특수지명블록로트외필지수새주소도로코드새주소법정동코드새주소지상지하코드새주소본번새주소부번동명칭주부속구분코드주부속구분코드명대지면적(제곱미터)건축면적(제곱미터)건폐율(퍼센트)연면적(제곱미터)용적률산정연면적(제곱미터)용적률(퍼센트)구조코드구조코드명기타구조주용도코드주용도코드명기타용도지붕코드지붕코드명기타지붕세대수(세대)가구수(가구)높이(미터)지상층수지하층수승용승강기수비상용승강기수부속건축물수부속건축물면적(제곱미터)총동연면적(제곱미터)옥내기계식대수(대)옥내기계식면적(제곱미터)옥외기계식대수(대)옥외기계식면적(제곱미터)옥내자주식대수(대)옥내자주식면적(제곱미터)옥외자주식대수(대)옥외자주식면적(제곱미터)허가일착공일사용승인일허가번호년허가번호기관코드허가번호기관코드명허가번호구분코드허가번호구분코드명호수(호)생성일자내진설계적용여부내진능력위도경도
2405924060경상남도 김해시 주촌면 양동리 115번지1150경상남도 김해시 주촌면 서부로1499번길 188-2648250-6646일반일반건축물<NA><NA><NA><NA>048300000000032001018826<NA>0주건축물1841.191028.2355.851067.631067.6357.9921철근콘크리트구조철근콘크리트17000공장공장30슬레이트대골스레이트000.0200000.01067.6300.000.000.0446.01992-12-071993-01-07<NA><NA><NA><NA><NA><NA>02017-03-16<NA><NA>35.228175128.803114
1594215943경상남도 김해시 대청동 288-1번지2881경상남도 김해시 대청로167번길 2748250-102085619일반일반건축물<NA><NA><NA><NA>048300000000012902027<NA><NA>0주건축물235.7137.7458.44399.5374.06158.721철근콘크리트구조철근콘크리트구조1000단독주택단독주택 및 근린생활시설10(철근)콘크리트(철근)콘크리트0411.3300000.0399.500.000.0223.0223.02013-08-122013-08-272014-04-1120135350154도시관리과1101신축허가02019-05-301<NA>35.188622128.7935
55305531경상남도 김해시 내동 165-1번지1651경상남도 김해시 금관대로1297번길 14-2348250-18489일반일반건축물<NA><NA><NA><NA>04830000000001080101423<NA>0주건축물240.4143.7659.8268.97268.97111.8821철근콘크리트구조철근콘크리트조/조적조1000단독주택단독주택10(철근)콘크리트슬라브057.4200000.0268.9700.000.000.0223.01990-09-241990-12-141997-12-31<NA><NA><NA><NA><NA>02017-04-06<NA><NA>35.241701128.861315
42044205경상남도 김해시 삼계동 1446-3번지14463경상남도 김해시 가야로157번길 5-1648250-18347일반일반건축물<NA><NA><NA><NA>0483000000000107010516<NA>0주건축물248.5148.059.56410.68410.68165.2621철근콘크리트구조철근콘크리트구조1000단독주택단독주택(3가구)/제2종근린생활시설10(철근)콘크리트슬라브0312.2300000.0410.6800.000.000.0446.02006-08-172006-08-252006-11-1620065350141허가과1101신축허가02020-07-071<NA>35.264165128.872445
939940경상남도 김해시 서상동 126-2번지1262경상남도 김해시 분성로 33048250-30750일반일반건축물<NA><NA><NA><NA>34830000000001020203300<NA>0주건축물446.0307.6968.991722.281513.0339.2421철근콘크리트구조철근콘크리트조4000제2종근린생활시설근린생활시설/위락시설10(철근)콘크리트슬라브0020.96100147.361722.281847.3600.000.000.01991-11-271992-01-311992-11-16<NA><NA><NA><NA><NA>02020-02-171<NA>35.233277128.882001
31693170경상남도 김해시 구산동 1052-3번지10523경상남도 김해시 구산로5번길 5548250-9825집합표제부구지마을동원아파트<NA><NA><NA>048300000000010601055<NA>111동0주건축물0.0387.960.01551.841163.880.021철근콘크리트구조철근콘크리트조4000제2종근린생활시설근린생활시설10(철근)콘크리트경사슬라브0010.35310000.06835.3200.000.000.000.01998-11-241999-03-302001-12-28<NA><NA><NA><NA><NA>452021-06-010<NA>35.253161128.868426
1030010301경상남도 김해시 어방동 1115-3번지11153경상남도 김해시 김해대로2541번길 648250-27562일반일반건축물<NA><NA><NA><NA>04830000000001180106<NA><NA>0주건축물339.8199.4258.69467.84467.84137.6821철근콘크리트구조철근콘크리트조/목조4000제2종근린생활시설제2종근린생활시설/단독주택10(철근)콘크리트슬라브/샌드위치판넬0111.15300000.0467.8400.000.000.0223.02001-01-112001-01-152001-03-20<NA><NA><NA><NA><NA>02017-11-18<NA><NA>35.229078128.904938
337338경상남도 김해시 동상동 325-32번지32532경상남도 김해시 호계로 528-1648250-45539일반일반건축물<NA><NA><NA><NA>048300000000010101052816<NA>0주건축물0.032.20.032.232.20.012블록구조블럭조1000단독주택단독주택30슬레이트스레이트010.0100000.032.200.000.000.000.0<NA><NA>1966-12-20<NA><NA><NA><NA><NA>02020-04-270<NA>35.237403128.884804
89078908경상남도 김해시 강동 373번지373048250-8179일반일반건축물<NA><NA><NA><NA>048300000000011601027<NA><NA>0주건축물274.055.3420.255.3455.3420.212블록구조블럭조1000단독주택단독주택30슬레이트스레이트010.0100000.055.3400.000.000.000.0<NA><NA>1968-12-20<NA><NA><NA><NA><NA>02020-04-280<NA>35.217869128.877397
2197421975경상남도 김해시 진영읍 죽곡리 9-1번지9148250-102016423일반일반건축물<NA><NA><NA><NA>0<NA><NA>0<NA><NA>B동1부속건축물0.01227.920.03189.623063.920.021철근콘크리트구조철골조/철근콘크리트조/경량철골조17000공장야외창고90기타지붕불연판넬경사지붕0013.4310000.03189.6200.000.000.033379.5<NA><NA>1991-07-23<NA><NA><NA><NA><NA>02020-04-270<NA>35.288498128.772554