Overview

Dataset statistics

Number of variables68
Number of observations10000
Missing cells56745
Missing cells (%)8.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 MiB
Average record size in memory595.0 B

Variable types

Numeric37
Text9
Categorical17
Unsupported1
DateTime4

Dataset

Description경상남도 김해시 건축물 현황(건축물대장 표제부)대한 데이터로 번지주소,도로명주소,위도,경도 등의 항목을 제공합니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15033374/fileData.do

Alerts

새주소지상지하코드 has constant value ""Constant
대장종류코드명 is highly imbalanced (66.2%)Imbalance
특수지명 is highly imbalanced (97.7%)Imbalance
블록 is highly imbalanced (98.1%)Imbalance
로트 is highly imbalanced (98.3%)Imbalance
새주소도로코드 is highly imbalanced (55.8%)Imbalance
주부속구분코드 is highly imbalanced (51.8%)Imbalance
주부속구분코드명 is highly imbalanced (51.8%)Imbalance
지하층수 is highly imbalanced (79.1%)Imbalance
허가번호기관코드명 is highly imbalanced (57.0%)Imbalance
허가번호구분코드명 is highly imbalanced (59.8%)Imbalance
건물명 has 8286 (82.9%) missing valuesMissing
새주소법정동코드 has 916 (9.2%) missing valuesMissing
새주소본번 has 870 (8.7%) missing valuesMissing
새주소부번 has 3628 (36.3%) missing valuesMissing
동명칭 has 7968 (79.7%) missing valuesMissing
허가일 has 2936 (29.4%) missing valuesMissing
착공일 has 3546 (35.5%) missing valuesMissing
사용승인일 has 438 (4.4%) missing valuesMissing
허가번호년 has 6144 (61.4%) missing valuesMissing
허가번호기관코드 has 6168 (61.7%) missing valuesMissing
허가번호구분코드 has 6139 (61.4%) missing valuesMissing
내진능력 has 9660 (96.6%) missing valuesMissing
is highly skewed (γ1 = 24.94568085)Skewed
외필지수 is highly skewed (γ1 = 20.29523366)Skewed
대지면적(제곱미터) is highly skewed (γ1 = 70.86278547)Skewed
부속건축물면적(제곱미터) is highly skewed (γ1 = 31.44201863)Skewed
옥내기계식대수(대) is highly skewed (γ1 = 31.70306311)Skewed
옥내기계식면적(제곱미터) is highly skewed (γ1 = 29.3591687)Skewed
옥외기계식대수(대) is highly skewed (γ1 = 57.7855683)Skewed
옥외기계식면적(제곱미터) is highly skewed (γ1 = 40.71611337)Skewed
옥내자주식대수(대) is highly skewed (γ1 = 24.60693948)Skewed
옥외자주식대수(대) is highly skewed (γ1 = 26.76751008)Skewed
옥외자주식면적(제곱미터) is highly skewed (γ1 = 31.11790144)Skewed
호수(호) is highly skewed (γ1 = 32.55811403)Skewed
순번 has unique valuesUnique
관리건축물대장 has unique valuesUnique
주용도코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported
has 144 (1.4%) zerosZeros
has 2419 (24.2%) zerosZeros
외필지수 has 8979 (89.8%) zerosZeros
새주소부번 has 2043 (20.4%) zerosZeros
대지면적(제곱미터) has 4074 (40.7%) zerosZeros
건축면적(제곱미터) has 374 (3.7%) zerosZeros
건폐율(퍼센트) has 4099 (41.0%) zerosZeros
용적률산정연면적(제곱미터) has 178 (1.8%) zerosZeros
용적률(퍼센트) has 4099 (41.0%) zerosZeros
세대수(세대) has 9126 (91.3%) zerosZeros
가구수(가구) has 5008 (50.1%) zerosZeros
높이(미터) has 3369 (33.7%) zerosZeros
지상층수 has 121 (1.2%) zerosZeros
승용승강기수 has 9491 (94.9%) zerosZeros
비상용승강기수 has 9767 (97.7%) zerosZeros
부속건축물수 has 8567 (85.7%) zerosZeros
부속건축물면적(제곱미터) has 8577 (85.8%) zerosZeros
총동연면적(제곱미터) has 151 (1.5%) zerosZeros
옥내기계식대수(대) has 9951 (99.5%) zerosZeros
옥내기계식면적(제곱미터) has 9956 (99.6%) zerosZeros
옥외기계식대수(대) has 9992 (99.9%) zerosZeros
옥외기계식면적(제곱미터) has 9993 (99.9%) zerosZeros
옥내자주식대수(대) has 9125 (91.2%) zerosZeros
옥내자주식면적(제곱미터) has 9154 (91.5%) zerosZeros
옥외자주식대수(대) has 5867 (58.7%) zerosZeros
옥외자주식면적(제곱미터) has 5937 (59.4%) zerosZeros
호수(호) has 9790 (97.9%) zerosZeros

Reproduction

Analysis started2023-12-12 06:06:03.734528
Analysis finished2023-12-12 06:06:07.013743
Duration3.28 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%
Mean12550.233
Minimum1
Maximum25059
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:07.146037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1252.95
Q16169
median12609.5
Q318824.5
95-th percentile23821.05
Maximum25059
Range25058
Interquartile range (IQR)12655.5

Descriptive statistics

Standard deviation7253.1959
Coefficient of variation (CV)0.57793319
Kurtosis-1.2075728
Mean12550.233
Median Absolute Deviation (MAD)6318.5
Skewness-0.0046539285
Sum1.2550232 × 108
Variance52608851
MonotonicityNot monotonic
2023-12-12T15:06:07.331609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6918 1
 
< 0.1%
23926 1
 
< 0.1%
537 1
 
< 0.1%
5922 1
 
< 0.1%
10696 1
 
< 0.1%
12394 1
 
< 0.1%
15787 1
 
< 0.1%
17422 1
 
< 0.1%
19516 1
 
< 0.1%
7832 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
5 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
13 1
< 0.1%
16 1
< 0.1%
18 1
< 0.1%
ValueCountFrequency (%)
25059 1
< 0.1%
25054 1
< 0.1%
25053 1
< 0.1%
25051 1
< 0.1%
25050 1
< 0.1%
25049 1
< 0.1%
25044 1
< 0.1%
25043 1
< 0.1%
25042 1
< 0.1%
25040 1
< 0.1%
Distinct8903
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T15:06:07.652450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length43
Mean length20.9719
Min length11

Characters and Unicode

Total characters209719
Distinct characters121
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8330 ?
Unique (%)83.3%

Sample

1st row경상남도 김해시 외동 743번지
2nd row경상남도 김해시 삼정동 70-3번지
3rd row경상남도 김해시 내동 산 2번지
4th row경상남도 김해시 무계동 492-1번지
5th row경상남도 김해시 명법동 629-8번지
ValueCountFrequency (%)
경상남도 10000
23.2%
김해시 10000
23.2%
진영읍 1705
 
4.0%
주촌면 1025
 
2.4%
진영리 590
 
1.4%
삼방동 525
 
1.2%
내동 451
 
1.0%
외동 429
 
1.0%
삼계동 400
 
0.9%
삼정동 389
 
0.9%
Other values (7095) 17564
40.8%
2023-12-12T15:06:08.453525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33078
 
15.8%
10507
 
5.0%
10461
 
5.0%
10016
 
4.8%
10011
 
4.8%
10011
 
4.8%
10007
 
4.8%
10000
 
4.8%
10000
 
4.8%
9855
 
4.7%
Other values (111) 85773
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 128310
61.2%
Decimal Number 40686
 
19.4%
Space Separator 33078
 
15.8%
Dash Punctuation 7614
 
3.6%
Uppercase Letter 31
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10507
 
8.2%
10461
 
8.2%
10016
 
7.8%
10011
 
7.8%
10011
 
7.8%
10007
 
7.8%
10000
 
7.8%
10000
 
7.8%
9855
 
7.7%
7962
 
6.2%
Other values (96) 29480
23.0%
Decimal Number
ValueCountFrequency (%)
1 9159
22.5%
2 4770
11.7%
3 4173
10.3%
4 3787
9.3%
6 3558
 
8.7%
5 3489
 
8.6%
7 3106
 
7.6%
0 3067
 
7.5%
8 2825
 
6.9%
9 2752
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
B 12
38.7%
L 12
38.7%
A 7
22.6%
Space Separator
ValueCountFrequency (%)
33078
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7614
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 128310
61.2%
Common 81378
38.8%
Latin 31
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10507
 
8.2%
10461
 
8.2%
10016
 
7.8%
10011
 
7.8%
10011
 
7.8%
10007
 
7.8%
10000
 
7.8%
10000
 
7.8%
9855
 
7.7%
7962
 
6.2%
Other values (96) 29480
23.0%
Common
ValueCountFrequency (%)
33078
40.6%
1 9159
 
11.3%
- 7614
 
9.4%
2 4770
 
5.9%
3 4173
 
5.1%
4 3787
 
4.7%
6 3558
 
4.4%
5 3489
 
4.3%
7 3106
 
3.8%
0 3067
 
3.8%
Other values (2) 5577
 
6.9%
Latin
ValueCountFrequency (%)
B 12
38.7%
L 12
38.7%
A 7
22.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 128309
61.2%
ASCII 81409
38.8%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33078
40.6%
1 9159
 
11.3%
- 7614
 
9.4%
2 4770
 
5.9%
3 4173
 
5.1%
4 3787
 
4.7%
6 3558
 
4.4%
5 3489
 
4.3%
7 3106
 
3.8%
0 3067
 
3.8%
Other values (5) 5608
 
6.9%
Hangul
ValueCountFrequency (%)
10507
 
8.2%
10461
 
8.2%
10016
 
7.8%
10011
 
7.8%
10011
 
7.8%
10007
 
7.8%
10000
 
7.8%
10000
 
7.8%
9855
 
7.7%
7962
 
6.2%
Other values (95) 29479
23.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%


Real number (ℝ)

ZEROS 

Distinct1515
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean587.1594
Minimum0
Maximum9190
Zeros144
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:08.628113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile35
Q1227
median494
Q3883
95-th percentile1433.05
Maximum9190
Range9190
Interquartile range (IQR)656

Descriptive statistics

Standard deviation457.5032
Coefficient of variation (CV)0.77918058
Kurtosis18.607656
Mean587.1594
Median Absolute Deviation (MAD)304
Skewness1.8458276
Sum5871594
Variance209309.18
MonotonicityNot monotonic
2023-12-12T15:06:08.799359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 144
 
1.4%
1417 62
 
0.6%
275 50
 
0.5%
319 40
 
0.4%
309 32
 
0.3%
274 30
 
0.3%
700 29
 
0.3%
312 29
 
0.3%
268 28
 
0.3%
61 28
 
0.3%
Other values (1505) 9528
95.3%
ValueCountFrequency (%)
0 144
1.4%
1 1
 
< 0.1%
2 14
 
0.1%
3 4
 
< 0.1%
4 9
 
0.1%
5 11
 
0.1%
6 7
 
0.1%
7 9
 
0.1%
8 17
 
0.2%
9 14
 
0.1%
ValueCountFrequency (%)
9190 1
 
< 0.1%
6820 1
 
< 0.1%
5401 1
 
< 0.1%
5357 1
 
< 0.1%
5280 1
 
< 0.1%
2650 1
 
< 0.1%
1923 3
< 0.1%
1909 3
< 0.1%
1889 1
 
< 0.1%
1885 3
< 0.1%


Real number (ℝ)

SKEWED  ZEROS 

Distinct159
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1982
Minimum0
Maximum1772
Zeros2419
Zeros (%)24.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:08.967943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q38
95-th percentile21
Maximum1772
Range1772
Interquartile range (IQR)7

Descriptive statistics

Standard deviation37.376065
Coefficient of variation (CV)4.5590574
Kurtosis842.51492
Mean8.1982
Median Absolute Deviation (MAD)3
Skewness24.945681
Sum81982
Variance1396.9702
MonotonicityNot monotonic
2023-12-12T15:06:09.195723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2419
24.2%
1 1282
12.8%
2 884
 
8.8%
3 764
 
7.6%
4 617
 
6.2%
5 464
 
4.6%
6 445
 
4.5%
7 365
 
3.6%
8 352
 
3.5%
9 312
 
3.1%
Other values (149) 2096
21.0%
ValueCountFrequency (%)
0 2419
24.2%
1 1282
12.8%
2 884
 
8.8%
3 764
 
7.6%
4 617
 
6.2%
5 464
 
4.6%
6 445
 
4.5%
7 365
 
3.6%
8 352
 
3.5%
9 312
 
3.1%
ValueCountFrequency (%)
1772 1
< 0.1%
1121 1
< 0.1%
1084 1
< 0.1%
1044 1
< 0.1%
912 1
< 0.1%
862 1
< 0.1%
852 1
< 0.1%
842 1
< 0.1%
789 1
< 0.1%
484 1
< 0.1%
Distinct7975
Distinct (%)79.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T15:06:09.552973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length19.9187
Min length1

Characters and Unicode

Total characters199187
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

Unique7429 ?
Unique (%)74.3%

Sample

1st row 경상남도 김해시 금관대로 1239
2nd row 경상남도 김해시 분성로 458
3rd row 경상남도 김해시 분성로3번길 235-2
4th row
5th row 경상남도 김해시 금관대로804번길 72
ValueCountFrequency (%)
경상남도 8903
23.3%
김해시 8903
23.3%
진영읍 1490
 
3.9%
주촌면 942
 
2.5%
김해대로 205
 
0.5%
분성로 154
 
0.4%
진례면 122
 
0.3%
서부로 119
 
0.3%
9 113
 
0.3%
진영로 112
 
0.3%
Other values (3761) 17105
44.8%
2023-12-12T15:06:10.095164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39265
19.7%
1 10131
 
5.1%
9761
 
4.9%
9670
 
4.9%
8933
 
4.5%
8909
 
4.5%
8903
 
4.5%
8903
 
4.5%
8903
 
4.5%
8636
 
4.3%
Other values (116) 77173
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111547
56.0%
Decimal Number 44127
 
22.2%
Space Separator 39265
 
19.7%
Dash Punctuation 4248
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9761
 
8.8%
9670
 
8.7%
8933
 
8.0%
8909
 
8.0%
8903
 
8.0%
8903
 
8.0%
8903
 
8.0%
8636
 
7.7%
6433
 
5.8%
6247
 
5.6%
Other values (104) 26249
23.5%
Decimal Number
ValueCountFrequency (%)
1 10131
23.0%
2 6286
14.2%
3 4831
10.9%
4 4078
9.2%
5 3717
 
8.4%
6 3404
 
7.7%
7 3324
 
7.5%
9 3028
 
6.9%
0 2743
 
6.2%
8 2585
 
5.9%
Space Separator
ValueCountFrequency (%)
39265
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4248
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111547
56.0%
Common 87640
44.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9761
 
8.8%
9670
 
8.7%
8933
 
8.0%
8909
 
8.0%
8903
 
8.0%
8903
 
8.0%
8903
 
8.0%
8636
 
7.7%
6433
 
5.8%
6247
 
5.6%
Other values (104) 26249
23.5%
Common
ValueCountFrequency (%)
39265
44.8%
1 10131
 
11.6%
2 6286
 
7.2%
3 4831
 
5.5%
- 4248
 
4.8%
4 4078
 
4.7%
5 3717
 
4.2%
6 3404
 
3.9%
7 3324
 
3.8%
9 3028
 
3.5%
Other values (2) 5328
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111547
56.0%
ASCII 87640
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39265
44.8%
1 10131
 
11.6%
2 6286
 
7.2%
3 4831
 
5.5%
- 4248
 
4.8%
4 4078
 
4.7%
5 3717
 
4.2%
6 3404
 
3.9%
7 3324
 
3.8%
9 3028
 
3.5%
Other values (2) 5328
 
6.1%
Hangul
ValueCountFrequency (%)
9761
 
8.8%
9670
 
8.7%
8933
 
8.0%
8909
 
8.0%
8903
 
8.0%
8903
 
8.0%
8903
 
8.0%
8636
 
7.7%
6433
 
5.8%
6247
 
5.6%
Other values (104) 26249
23.5%
Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T15:06:10.404428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length12.3307
Min length10

Characters and Unicode

Total characters123307
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 row48250-102070162
2nd row48250-31063
3rd row48250-8039
4th row48250-50273
5th row48250-102063148
ValueCountFrequency (%)
48250-102070162 1
 
< 0.1%
48250-102052059 1
 
< 0.1%
48250-21556 1
 
< 0.1%
48250-102059139 1
 
< 0.1%
48250-41682 1
 
< 0.1%
48250-33146 1
 
< 0.1%
48250-51011 1
 
< 0.1%
48250-55708 1
 
< 0.1%
48250-55131 1
 
< 0.1%
48250-102008350 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-12T15:06:10.873627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20123
16.3%
2 19056
15.5%
4 15717
12.7%
5 15478
12.6%
8 14375
11.7%
1 10190
8.3%
- 10000
8.1%
3 5689
 
4.6%
9 4236
 
3.4%
7 4233
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 113307
91.9%
Dash Punctuation 10000
 
8.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20123
17.8%
2 19056
16.8%
4 15717
13.9%
5 15478
13.7%
8 14375
12.7%
1 10190
9.0%
3 5689
 
5.0%
9 4236
 
3.7%
7 4233
 
3.7%
6 4210
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 123307
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20123
16.3%
2 19056
15.5%
4 15717
12.7%
5 15478
12.6%
8 14375
11.7%
1 10190
8.3%
- 10000
8.1%
3 5689
 
4.6%
9 4236
 
3.4%
7 4233
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123307
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20123
16.3%
2 19056
15.5%
4 15717
12.7%
5 15478
12.6%
8 14375
11.7%
1 10190
8.3%
- 10000
8.1%
3 5689
 
4.6%
9 4236
 
3.4%
7 4233
 
3.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반
8782 
집합
1218 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 8782
87.8%
집합 1218
 
12.2%

Length

2023-12-12T15:06:11.077173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:11.184127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 8782
87.8%
집합 1218
 
12.2%

대장종류코드명
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반건축물
8781 
표제부
1218 
c
 
1

Length

Max length5
Median length5
Mean length4.756
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
일반건축물 8781
87.8%
표제부 1218
 
12.2%
c 1
 
< 0.1%

Length

2023-12-12T15:06:11.299199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:11.449381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반건축물 8781
87.8%
표제부 1218
 
12.2%
c 1
 
< 0.1%

건물명
Text

MISSING 

Distinct997
Distinct (%)58.2%
Missing8286
Missing (%)82.9%
Memory size156.2 KiB
2023-12-12T15:06:11.642575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length8.1271879
Min length1

Characters and Unicode

Total characters13930
Distinct characters467
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique753 ?
Unique (%)43.9%

Sample

1st row한국전기통신공사 연수원
2nd row하모니빌-2
3rd row천자빌라
4th row내덕 서희스타힐스 아파트
5th row사충단
ValueCountFrequency (%)
김해 90
 
3.6%
워터파크 61
 
2.4%
롯데 61
 
2.4%
부영아파트 35
 
1.4%
푸르지오 33
 
1.3%
아파트 28
 
1.1%
화정마을 24
 
1.0%
율현마을 23
 
0.9%
진영 20
 
0.8%
장유 18
 
0.7%
Other values (1133) 2124
84.4%
2023-12-12T15:06:12.026497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
803
 
5.8%
431
 
3.1%
426
 
3.1%
388
 
2.8%
350
 
2.5%
321
 
2.3%
307
 
2.2%
273
 
2.0%
248
 
1.8%
244
 
1.8%
Other values (457) 10139
72.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12138
87.1%
Space Separator 803
 
5.8%
Decimal Number 509
 
3.7%
Uppercase Letter 138
 
1.0%
Close Punctuation 110
 
0.8%
Open Punctuation 110
 
0.8%
Dash Punctuation 62
 
0.4%
Lowercase Letter 44
 
0.3%
Other Punctuation 16
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
431
 
3.6%
426
 
3.5%
388
 
3.2%
350
 
2.9%
321
 
2.6%
307
 
2.5%
273
 
2.2%
248
 
2.0%
244
 
2.0%
241
 
2.0%
Other values (408) 8909
73.4%
Uppercase Letter
ValueCountFrequency (%)
A 18
13.0%
I 14
 
10.1%
S 13
 
9.4%
C 10
 
7.2%
Q 8
 
5.8%
B 7
 
5.1%
G 7
 
5.1%
E 7
 
5.1%
D 6
 
4.3%
H 6
 
4.3%
Other values (13) 42
30.4%
Decimal Number
ValueCountFrequency (%)
1 143
28.1%
2 121
23.8%
3 61
12.0%
5 33
 
6.5%
4 29
 
5.7%
7 29
 
5.7%
0 26
 
5.1%
9 24
 
4.7%
6 23
 
4.5%
8 20
 
3.9%
Lowercase Letter
ValueCountFrequency (%)
e 31
70.5%
o 4
 
9.1%
t 3
 
6.8%
h 3
 
6.8%
d 2
 
4.5%
i 1
 
2.3%
Other Punctuation
ValueCountFrequency (%)
. 5
31.2%
/ 3
18.8%
& 3
18.8%
# 3
18.8%
* 1
 
6.2%
, 1
 
6.2%
Space Separator
ValueCountFrequency (%)
803
100.0%
Close Punctuation
ValueCountFrequency (%)
) 110
100.0%
Open Punctuation
ValueCountFrequency (%)
( 110
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12135
87.1%
Common 1610
 
11.6%
Latin 182
 
1.3%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
431
 
3.6%
426
 
3.5%
388
 
3.2%
350
 
2.9%
321
 
2.6%
307
 
2.5%
273
 
2.2%
248
 
2.0%
244
 
2.0%
241
 
2.0%
Other values (406) 8906
73.4%
Latin
ValueCountFrequency (%)
e 31
17.0%
A 18
 
9.9%
I 14
 
7.7%
S 13
 
7.1%
C 10
 
5.5%
Q 8
 
4.4%
B 7
 
3.8%
G 7
 
3.8%
E 7
 
3.8%
D 6
 
3.3%
Other values (19) 61
33.5%
Common
ValueCountFrequency (%)
803
49.9%
1 143
 
8.9%
2 121
 
7.5%
) 110
 
6.8%
( 110
 
6.8%
- 62
 
3.9%
3 61
 
3.8%
5 33
 
2.0%
4 29
 
1.8%
7 29
 
1.8%
Other values (10) 109
 
6.8%
Han
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12135
87.1%
ASCII 1792
 
12.9%
CJK 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
803
44.8%
1 143
 
8.0%
2 121
 
6.8%
) 110
 
6.1%
( 110
 
6.1%
- 62
 
3.5%
3 61
 
3.4%
5 33
 
1.8%
e 31
 
1.7%
4 29
 
1.6%
Other values (39) 289
 
16.1%
Hangul
ValueCountFrequency (%)
431
 
3.6%
426
 
3.5%
388
 
3.2%
350
 
2.9%
321
 
2.6%
307
 
2.5%
273
 
2.2%
248
 
2.0%
244
 
2.0%
241
 
2.0%
Other values (406) 8906
73.4%
CJK
ValueCountFrequency (%)
2
66.7%
1
33.3%

특수지명
Categorical

IMBALANCE 

Distinct36
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9901 
주촌선천지구
 
29
삼어지구
 
12
선천지구
 
11
김해율하2지구
 
7
Other values (31)
 
40

Length

Max length16
Median length4
Mean length4.0246
Min length1

Unique

Unique26 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9901
99.0%
주촌선천지구 29
 
0.3%
삼어지구 12
 
0.1%
선천지구 11
 
0.1%
김해율하2지구 7
 
0.1%
무계지구 도시개발사업조합지구내 5
 
0.1%
김해삼어지구 3
 
< 0.1%
. 2
 
< 0.1%
삼어택지개발지구 2
 
< 0.1%
본산준공업단지 2
 
< 0.1%
Other values (26) 26
 
0.3%

Length

2023-12-12T15:06:12.180498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9901
98.8%
주촌선천지구 29
 
0.3%
삼어지구 12
 
0.1%
선천지구 11
 
0.1%
김해율하2지구 7
 
0.1%
무계지구 5
 
< 0.1%
도시개발사업조합지구내 5
 
< 0.1%
김해삼어지구 4
 
< 0.1%
본산준공업단지 2
 
< 0.1%
삼어택지개발지구 2
 
< 0.1%
Other values (38) 39
 
0.4%

블록
Categorical

IMBALANCE 

Distinct38
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9925 
28블럭
 
11
89B
 
8
A-1블록
 
7
5블록
 
5
Other values (33)
 
44

Length

Max length5
Median length4
Mean length3.9964
Min length1

Unique

Unique23 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9925
99.2%
28블럭 11
 
0.1%
89B 8
 
0.1%
A-1블록 7
 
0.1%
5블록 5
 
0.1%
1블록 3
 
< 0.1%
14블록 2
 
< 0.1%
17 2
 
< 0.1%
19블록 2
 
< 0.1%
2블록 2
 
< 0.1%
Other values (28) 33
 
0.3%

Length

2023-12-12T15:06:12.381795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9925
99.2%
28블럭 11
 
0.1%
89b 8
 
0.1%
a-1블록 7
 
0.1%
5블록 5
 
< 0.1%
1블록 3
 
< 0.1%
39블록 2
 
< 0.1%
85블록 2
 
< 0.1%
49블록 2
 
< 0.1%
8블록 2
 
< 0.1%
Other values (28) 33
 
0.3%

로트
Categorical

IMBALANCE 

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9932 
1로트
 
13
1-1L
 
8
8-2로트
 
5
6로트
 
4
Other values (29)
 
38

Length

Max length7
Median length4
Mean length3.9965
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> 9932
99.3%
1로트 13
 
0.1%
1-1L 8
 
0.1%
8-2로트 5
 
0.1%
6로트 4
 
< 0.1%
1 3
 
< 0.1%
7로트 3
 
< 0.1%
4로트 2
 
< 0.1%
2로트 2
 
< 0.1%
19로트 2
 
< 0.1%
Other values (24) 26
 
0.3%

Length

2023-12-12T15:06:12.516982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9932
99.3%
1로트 13
 
0.1%
1-1l 8
 
0.1%
8-2로트 5
 
< 0.1%
6로트 4
 
< 0.1%
1 3
 
< 0.1%
7로트 3
 
< 0.1%
19로트 2
 
< 0.1%
5-1로트 2
 
< 0.1%
10로트 2
 
< 0.1%
Other values (25) 27
 
0.3%

외필지수
Real number (ℝ)

SKEWED  ZEROS 

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5036
Minimum0
Maximum154
Zeros8979
Zeros (%)89.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:12.651929image/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 deviation4.9684661
Coefficient of variation (CV)9.8658978
Kurtosis503.37597
Mean0.5036
Median Absolute Deviation (MAD)0
Skewness20.295234
Sum5036
Variance24.685656
MonotonicityNot monotonic
2023-12-12T15:06:12.783770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 8979
89.8%
1 625
 
6.2%
2 143
 
1.4%
3 64
 
0.6%
4 56
 
0.6%
5 17
 
0.2%
6 16
 
0.2%
7 11
 
0.1%
26 11
 
0.1%
9 9
 
0.1%
Other values (24) 69
 
0.7%
ValueCountFrequency (%)
0 8979
89.8%
1 625
 
6.2%
2 143
 
1.4%
3 64
 
0.6%
4 56
 
0.6%
5 17
 
0.2%
6 16
 
0.2%
7 11
 
0.1%
8 6
 
0.1%
9 9
 
0.1%
ValueCountFrequency (%)
154 4
< 0.1%
108 3
< 0.1%
98 2
 
< 0.1%
77 3
< 0.1%
66 2
 
< 0.1%
60 7
0.1%
47 7
0.1%
46 1
 
< 0.1%
35 2
 
< 0.1%
31 1
 
< 0.1%

새주소도로코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
483000000000
9084 
<NA>
916 

Length

Max length12
Median length12
Mean length11.2672
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row483000000000
2nd row483000000000
3rd row483000000000
4th row483000000000
5th row483000000000

Common Values

ValueCountFrequency (%)
483000000000 9084
90.8%
<NA> 916
 
9.2%

Length

2023-12-12T15:06:12.944850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:13.054882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
483000000000 9084
90.8%
na 916
 
9.2%

새주소법정동코드
Real number (ℝ)

MISSING 

Distinct131
Distinct (%)1.4%
Missing916
Missing (%)9.2%
Infinite0
Infinite (%)0.0%
Mean16228.382
Minimum10101
Maximum34002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:13.187379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile10301
Q110901
median12001
Q325001
95-th percentile32001
Maximum34002
Range23901
Interquartile range (IQR)14100

Descriptive statistics

Standard deviation7729.0245
Coefficient of variation (CV)0.47626587
Kurtosis-0.4468386
Mean16228.382
Median Absolute Deviation (MAD)1200
Skewness1.1082669
Sum1.4741862 × 108
Variance59737819
MonotonicityNot monotonic
2023-12-12T15:06:13.346345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25001 1431
 
14.3%
32001 901
 
9.0%
10801 432
 
4.3%
11901 423
 
4.2%
10101 335
 
3.4%
10901 286
 
2.9%
11701 286
 
2.9%
10701 276
 
2.8%
11801 273
 
2.7%
13002 230
 
2.3%
Other values (121) 4211
42.1%
(Missing) 916
 
9.2%
ValueCountFrequency (%)
10101 335
3.4%
10201 80
 
0.8%
10202 36
 
0.4%
10301 171
1.7%
10302 102
 
1.0%
10303 16
 
0.2%
10401 99
 
1.0%
10402 83
 
0.8%
10403 18
 
0.2%
10501 84
 
0.8%
ValueCountFrequency (%)
34002 2
 
< 0.1%
33004 16
 
0.2%
33002 21
 
0.2%
33001 85
 
0.9%
32007 1
 
< 0.1%
32003 47
 
0.5%
32002 19
 
0.2%
32001 901
9.0%
31001 1
 
< 0.1%
25012 79
 
0.8%

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

2023-12-12T15:06:13.488142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:13.595686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 10000
100.0%

새주소본번
Real number (ℝ)

MISSING 

Distinct723
Distinct (%)7.9%
Missing870
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean128.32574
Minimum0
Maximum2794
Zeros48
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:13.724380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q114
median34
Q3102
95-th percentile463
Maximum2794
Range2794
Interquartile range (IQR)88

Descriptive statistics

Standard deviation318.19932
Coefficient of variation (CV)2.4796219
Kurtosis31.794149
Mean128.32574
Median Absolute Deviation (MAD)26
Skewness5.2923392
Sum1171614
Variance101250.81
MonotonicityNot monotonic
2023-12-12T15:06:13.882852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 237
 
2.4%
9 219
 
2.2%
4 213
 
2.1%
6 194
 
1.9%
5 191
 
1.9%
8 186
 
1.9%
12 181
 
1.8%
11 180
 
1.8%
14 176
 
1.8%
7 174
 
1.7%
Other values (713) 7179
71.8%
(Missing) 870
 
8.7%
ValueCountFrequency (%)
0 48
 
0.5%
1 80
 
0.8%
2 59
 
0.6%
3 237
2.4%
4 213
2.1%
5 191
1.9%
6 194
1.9%
7 174
1.7%
8 186
1.9%
9 219
2.2%
ValueCountFrequency (%)
2794 1
< 0.1%
2793 1
< 0.1%
2791 1
< 0.1%
2787 1
< 0.1%
2785 1
< 0.1%
2777 1
< 0.1%
2776 1
< 0.1%
2773 1
< 0.1%
2752 1
< 0.1%
2724 1
< 0.1%

새주소부번
Real number (ℝ)

MISSING  ZEROS 

Distinct155
Distinct (%)2.4%
Missing3628
Missing (%)36.3%
Infinite0
Infinite (%)0.0%
Mean12.614564
Minimum0
Maximum688
Zeros2043
Zeros (%)20.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:14.028316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q316
95-th percentile49
Maximum688
Range688
Interquartile range (IQR)16

Descriptive statistics

Standard deviation26.062014
Coefficient of variation (CV)2.0660258
Kurtosis148.41964
Mean12.614564
Median Absolute Deviation (MAD)5
Skewness8.6441131
Sum80380
Variance679.22859
MonotonicityNot monotonic
2023-12-12T15:06:14.223582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2043
20.4%
1 651
 
6.5%
3 178
 
1.8%
5 167
 
1.7%
6 166
 
1.7%
7 166
 
1.7%
10 157
 
1.6%
8 157
 
1.6%
9 154
 
1.5%
12 153
 
1.5%
Other values (145) 2380
23.8%
(Missing) 3628
36.3%
ValueCountFrequency (%)
0 2043
20.4%
1 651
 
6.5%
2 146
 
1.5%
3 178
 
1.8%
4 130
 
1.3%
5 167
 
1.7%
6 166
 
1.7%
7 166
 
1.7%
8 157
 
1.6%
9 154
 
1.5%
ValueCountFrequency (%)
688 1
< 0.1%
563 1
< 0.1%
561 1
< 0.1%
246 1
< 0.1%
244 1
< 0.1%
237 2
< 0.1%
230 1
< 0.1%
225 2
< 0.1%
224 1
< 0.1%
221 1
< 0.1%

동명칭
Text

MISSING 

Distinct578
Distinct (%)28.4%
Missing7968
Missing (%)79.7%
Memory size156.2 KiB
2023-12-12T15:06:14.522724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length3.3346457
Min length1

Characters and Unicode

Total characters6776
Distinct characters289
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

Unique424 ?
Unique (%)20.9%

Sample

1st row기숙사
2nd row가동
3rd row조정계단실
4th row117동
5th row카바나36
ValueCountFrequency (%)
b동 236
 
11.5%
a동 226
 
11.0%
c동 95
 
4.6%
가동 95
 
4.6%
나동 88
 
4.3%
다동 33
 
1.6%
d동 32
 
1.6%
주건축물제1동 28
 
1.4%
2동 28
 
1.4%
1동 27
 
1.3%
Other values (574) 1170
56.9%
2023-12-12T15:06:14.987426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1657
24.5%
1 624
 
9.2%
0 418
 
6.2%
2 286
 
4.2%
B 256
 
3.8%
A 247
 
3.6%
3 205
 
3.0%
149
 
2.2%
138
 
2.0%
128
 
1.9%
Other values (279) 2668
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3886
57.3%
Decimal Number 1987
29.3%
Uppercase Letter 739
 
10.9%
Close Punctuation 39
 
0.6%
Open Punctuation 39
 
0.6%
Other Punctuation 34
 
0.5%
Space Separator 26
 
0.4%
Dash Punctuation 21
 
0.3%
Lowercase Letter 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1657
42.6%
149
 
3.8%
138
 
3.6%
128
 
3.3%
102
 
2.6%
69
 
1.8%
56
 
1.4%
56
 
1.4%
54
 
1.4%
54
 
1.4%
Other values (234) 1423
36.6%
Uppercase Letter
ValueCountFrequency (%)
B 256
34.6%
A 247
33.4%
C 108
14.6%
D 40
 
5.4%
E 23
 
3.1%
F 15
 
2.0%
G 6
 
0.8%
H 6
 
0.8%
P 5
 
0.7%
I 5
 
0.7%
Other values (13) 28
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 624
31.4%
0 418
21.0%
2 286
14.4%
3 205
 
10.3%
4 111
 
5.6%
5 103
 
5.2%
6 73
 
3.7%
7 72
 
3.6%
8 48
 
2.4%
9 47
 
2.4%
Other Punctuation
ValueCountFrequency (%)
, 21
61.8%
/ 9
26.5%
. 3
 
8.8%
& 1
 
2.9%
Lowercase Letter
ValueCountFrequency (%)
b 2
40.0%
a 1
20.0%
s 1
20.0%
u 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3886
57.3%
Common 2146
31.7%
Latin 744
 
11.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1657
42.6%
149
 
3.8%
138
 
3.6%
128
 
3.3%
102
 
2.6%
69
 
1.8%
56
 
1.4%
56
 
1.4%
54
 
1.4%
54
 
1.4%
Other values (234) 1423
36.6%
Latin
ValueCountFrequency (%)
B 256
34.4%
A 247
33.2%
C 108
14.5%
D 40
 
5.4%
E 23
 
3.1%
F 15
 
2.0%
G 6
 
0.8%
H 6
 
0.8%
P 5
 
0.7%
I 5
 
0.7%
Other values (17) 33
 
4.4%
Common
ValueCountFrequency (%)
1 624
29.1%
0 418
19.5%
2 286
13.3%
3 205
 
9.6%
4 111
 
5.2%
5 103
 
4.8%
6 73
 
3.4%
7 72
 
3.4%
8 48
 
2.2%
9 47
 
2.2%
Other values (8) 159
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3886
57.3%
ASCII 2890
42.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1657
42.6%
149
 
3.8%
138
 
3.6%
128
 
3.3%
102
 
2.6%
69
 
1.8%
56
 
1.4%
56
 
1.4%
54
 
1.4%
54
 
1.4%
Other values (234) 1423
36.6%
ASCII
ValueCountFrequency (%)
1 624
21.6%
0 418
14.5%
2 286
9.9%
B 256
8.9%
A 247
 
8.5%
3 205
 
7.1%
4 111
 
3.8%
C 108
 
3.7%
5 103
 
3.6%
6 73
 
2.5%
Other values (35) 459
15.9%

주부속구분코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8957 
1
1043 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 8957
89.6%
1 1043
 
10.4%

Length

2023-12-12T15:06:15.136838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:15.243848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8957
89.6%
1 1043
 
10.4%

주부속구분코드명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주건축물
8957 
부속건축물
1043 

Length

Max length5
Median length4
Mean length4.1043
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주건축물 8957
89.6%
부속건축물 1043
 
10.4%

Length

2023-12-12T15:06:15.348002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:15.464193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주건축물 8957
89.6%
부속건축물 1043
 
10.4%

대지면적(제곱미터)
Real number (ℝ)

SKEWED  ZEROS 

Distinct3316
Distinct (%)33.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1517.794
Minimum0
Maximum3344502
Zeros4074
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:15.632144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median197.55
Q3363
95-th percentile1815.05
Maximum3344502
Range3344502
Interquartile range (IQR)363

Descriptive statistics

Standard deviation38156.377
Coefficient of variation (CV)25.139364
Kurtosis5950.7102
Mean1517.794
Median Absolute Deviation (MAD)197.55
Skewness70.862785
Sum15177940
Variance1.4559091 × 109
MonotonicityNot monotonic
2023-12-12T15:06:15.820156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4074
40.7%
330.0 29
 
0.3%
228.0 23
 
0.2%
331.0 17
 
0.2%
165.0 14
 
0.1%
198.0 14
 
0.1%
202.0 13
 
0.1%
268.0 13
 
0.1%
257.0 11
 
0.1%
221.0 11
 
0.1%
Other values (3306) 5781
57.8%
ValueCountFrequency (%)
0.0 4074
40.7%
1.567 1
 
< 0.1%
4.5 1
 
< 0.1%
16.631 1
 
< 0.1%
25.0 1
 
< 0.1%
26.0 1
 
< 0.1%
29.0 2
 
< 0.1%
30.0 1
 
< 0.1%
36.0 1
 
< 0.1%
38.01 1
 
< 0.1%
ValueCountFrequency (%)
3344502.0 1
 
< 0.1%
621551.5 8
0.1%
434346.0 1
 
< 0.1%
122397.27 2
 
< 0.1%
78720.0 1
 
< 0.1%
64146.0 1
 
< 0.1%
60524.7 1
 
< 0.1%
52993.0 2
 
< 0.1%
49375.6 4
< 0.1%
42088.56 2
 
< 0.1%

건축면적(제곱미터)
Real number (ℝ)

ZEROS 

Distinct7308
Distinct (%)73.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean278.07938
Minimum0
Maximum15684.47
Zeros374
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:15.956239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.4515
Q171.045
median127.96
Q3231.6025
95-th percentile876.817
Maximum15684.47
Range15684.47
Interquartile range (IQR)160.5575

Descriptive statistics

Standard deviation678.47517
Coefficient of variation (CV)2.4398615
Kurtosis140.95852
Mean278.07938
Median Absolute Deviation (MAD)67.97
Skewness9.9093234
Sum2780793.8
Variance460328.56
MonotonicityNot monotonic
2023-12-12T15:06:16.104206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 374
 
3.7%
6.25 50
 
0.5%
26.45 29
 
0.3%
19.83 24
 
0.2%
23.14 24
 
0.2%
33.06 21
 
0.2%
46.28 19
 
0.2%
39.67 18
 
0.2%
99.0 17
 
0.2%
33.0 16
 
0.2%
Other values (7298) 9408
94.1%
ValueCountFrequency (%)
0.0 374
3.7%
0.81 1
 
< 0.1%
0.99 1
 
< 0.1%
1.0 3
 
< 0.1%
1.44 1
 
< 0.1%
1.5 2
 
< 0.1%
1.56 2
 
< 0.1%
1.65 1
 
< 0.1%
1.77 1
 
< 0.1%
2.0 2
 
< 0.1%
ValueCountFrequency (%)
15684.47 1
< 0.1%
14099.83 1
< 0.1%
13893.53 1
< 0.1%
12714.0 1
< 0.1%
11788.98 1
< 0.1%
11767.86 1
< 0.1%
11668.8 1
< 0.1%
11379.11 1
< 0.1%
9590.88 1
< 0.1%
8960.9 1
< 0.1%

건폐율(퍼센트)
Real number (ℝ)

ZEROS 

Distinct3063
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.02492
Minimum0
Maximum172.75
Zeros4099
Zeros (%)41.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:16.609403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median23.96
Q358.05
95-th percentile62.1115
Maximum172.75
Range172.75
Interquartile range (IQR)58.05

Descriptive statistics

Standard deviation27.104777
Coefficient of variation (CV)0.96716698
Kurtosis-1.5907353
Mean28.02492
Median Absolute Deviation (MAD)23.96
Skewness0.18339619
Sum280249.2
Variance734.66893
MonotonicityNot monotonic
2023-12-12T15:06:16.760463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4099
41.0%
59.65 26
 
0.3%
59.58 25
 
0.2%
59.3 25
 
0.2%
59.5 25
 
0.2%
59.43 25
 
0.2%
59.44 24
 
0.2%
59.35 24
 
0.2%
59.74 23
 
0.2%
59.87 23
 
0.2%
Other values (3053) 5681
56.8%
ValueCountFrequency (%)
0.0 4099
41.0%
0.0006 1
 
< 0.1%
0.0015 1
 
< 0.1%
0.0025 1
 
< 0.1%
0.0048 1
 
< 0.1%
0.01 2
 
< 0.1%
0.0119 1
 
< 0.1%
0.02 1
 
< 0.1%
0.03 1
 
< 0.1%
0.0442 1
 
< 0.1%
ValueCountFrequency (%)
172.75 1
 
< 0.1%
124.45 1
 
< 0.1%
100.0 3
< 0.1%
96.3 1
 
< 0.1%
91.79 1
 
< 0.1%
91.43 1
 
< 0.1%
90.27 1
 
< 0.1%
90.08 1
 
< 0.1%
89.44 1
 
< 0.1%
88.59 1
 
< 0.1%

연면적(제곱미터)
Real number (ℝ)

Distinct8177
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean891.66806
Minimum0
Maximum116481.36
Zeros32
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:16.946233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile21.837
Q184.84
median242.205
Q3490.4625
95-th percentile4801.828
Maximum116481.36
Range116481.36
Interquartile range (IQR)405.6225

Descriptive statistics

Standard deviation2933.8163
Coefficient of variation (CV)3.2902561
Kurtosis378.61644
Mean891.66806
Median Absolute Deviation (MAD)175.06
Skewness14.210027
Sum8916680.6
Variance8607277.9
MonotonicityNot monotonic
2023-12-12T15:06:17.110991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.25 50
 
0.5%
0.0 32
 
0.3%
26.45 30
 
0.3%
19.83 26
 
0.3%
23.14 24
 
0.2%
33.06 21
 
0.2%
46.28 19
 
0.2%
39.67 17
 
0.2%
99.0 16
 
0.2%
33.0 16
 
0.2%
Other values (8167) 9749
97.5%
ValueCountFrequency (%)
0.0 32
0.3%
0.81 1
 
< 0.1%
0.99 1
 
< 0.1%
1.0 4
 
< 0.1%
1.21 1
 
< 0.1%
1.44 3
 
< 0.1%
1.5 2
 
< 0.1%
1.56 2
 
< 0.1%
1.65 1
 
< 0.1%
1.77 1
 
< 0.1%
ValueCountFrequency (%)
116481.3569 1
< 0.1%
78954.2133 1
< 0.1%
67228.415 1
< 0.1%
64715.9374 1
< 0.1%
59909.2762 1
< 0.1%
42784.28 1
< 0.1%
41917.596 1
< 0.1%
35917.3732 1
< 0.1%
30799.6776 1
< 0.1%
30702.35 1
< 0.1%
Distinct8048
Distinct (%)80.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean764.16194
Minimum0
Maximum38423.27
Zeros178
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:17.289226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16.53
Q181.3325
median229.81
Q3472.61
95-th percentile4187.264
Maximum38423.27
Range38423.27
Interquartile range (IQR)391.2775

Descriptive statistics

Standard deviation2002.5285
Coefficient of variation (CV)2.6205552
Kurtosis47.101916
Mean764.16194
Median Absolute Deviation (MAD)169.095
Skewness5.7172982
Sum7641619.4
Variance4010120.4
MonotonicityNot monotonic
2023-12-12T15:06:17.468199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 178
 
1.8%
6.25 50
 
0.5%
26.45 30
 
0.3%
19.83 25
 
0.2%
23.14 24
 
0.2%
33.06 21
 
0.2%
46.28 19
 
0.2%
39.67 17
 
0.2%
33.0 16
 
0.2%
99.0 16
 
0.2%
Other values (8038) 9604
96.0%
ValueCountFrequency (%)
0.0 178
1.8%
0.81 1
 
< 0.1%
0.99 1
 
< 0.1%
1.0 4
 
< 0.1%
1.21 1
 
< 0.1%
1.44 3
 
< 0.1%
1.5 2
 
< 0.1%
1.56 2
 
< 0.1%
1.65 1
 
< 0.1%
1.77 1
 
< 0.1%
ValueCountFrequency (%)
38423.27 1
< 0.1%
30723.507 1
< 0.1%
28894.13 1
< 0.1%
25697.69 1
< 0.1%
22332.04 1
< 0.1%
21745.393 1
< 0.1%
21532.25 1
< 0.1%
21365.189 1
< 0.1%
21043.28 1
< 0.1%
20532.24 1
< 0.1%

용적률(퍼센트)
Real number (ℝ)

ZEROS 

Distinct4978
Distinct (%)49.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.965682
Minimum0
Maximum1432.0918
Zeros4099
Zeros (%)41.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:17.676929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median29.04
Q3113.925
95-th percentile184.445
Maximum1432.0918
Range1432.0918
Interquartile range (IQR)113.925

Descriptive statistics

Standard deviation84.417625
Coefficient of variation (CV)1.3406926
Kurtosis17.253001
Mean62.965682
Median Absolute Deviation (MAD)29.04
Skewness2.6612076
Sum629656.82
Variance7126.3353
MonotonicityNot monotonic
2023-12-12T15:06:17.836995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4099
41.0%
19.7 5
 
0.1%
22.18 5
 
0.1%
50.0 5
 
0.1%
59.68 5
 
0.1%
47.4 5
 
0.1%
59.3 5
 
0.1%
57.02 4
 
< 0.1%
30.35 4
 
< 0.1%
59.77 4
 
< 0.1%
Other values (4968) 5859
58.6%
ValueCountFrequency (%)
0.0 4099
41.0%
0.0006 1
 
< 0.1%
0.0012 1
 
< 0.1%
0.0048 1
 
< 0.1%
0.01 1
 
< 0.1%
0.0107 1
 
< 0.1%
0.0114 1
 
< 0.1%
0.02 2
 
< 0.1%
0.0442 1
 
< 0.1%
0.047 1
 
< 0.1%
ValueCountFrequency (%)
1432.0918 1
< 0.1%
897.31 1
< 0.1%
797.53 1
< 0.1%
757.45 1
< 0.1%
751.93 1
< 0.1%
741.15 1
< 0.1%
730.08 1
< 0.1%
726.8 1
< 0.1%
722.24 1
< 0.1%
709.27 1
< 0.1%

구조코드
Real number (ℝ)

Distinct19
Distinct (%)0.2%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean24.688069
Minimum10
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:18.019308image/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 deviation11.17319
Coefficient of variation (CV)0.45257449
Kurtosis2.2544613
Mean24.688069
Median Absolute Deviation (MAD)9
Skewness1.2576745
Sum246856
Variance124.84018
MonotonicityNot monotonic
2023-12-12T15:06:18.167908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
21 4232
42.3%
31 1624
 
16.2%
12 1015
 
10.2%
11 940
 
9.4%
51 936
 
9.4%
32 838
 
8.4%
19 289
 
2.9%
33 27
 
0.3%
41 26
 
0.3%
42 19
 
0.2%
Other values (9) 53
 
0.5%
ValueCountFrequency (%)
10 13
 
0.1%
11 940
 
9.4%
12 1015
 
10.2%
13 2
 
< 0.1%
19 289
 
2.9%
21 4232
42.3%
22 1
 
< 0.1%
29 8
 
0.1%
31 1624
 
16.2%
32 838
 
8.4%
ValueCountFrequency (%)
99 9
 
0.1%
74 3
 
< 0.1%
63 2
 
< 0.1%
51 936
9.4%
50 8
 
0.1%
42 19
 
0.2%
41 26
 
0.3%
39 7
 
0.1%
33 27
 
0.3%
32 838
8.4%

구조코드명
Categorical

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
철근콘크리트구조
4232 
일반철골구조
1624 
블록구조
1015 
벽돌구조
940 
일반목구조
936 
Other values (15)
1253 

Length

Max length11
Median length10
Mean length6.3681
Min length3

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 4232
42.3%
일반철골구조 1624
 
16.2%
블록구조 1015
 
10.2%
벽돌구조 940
 
9.4%
일반목구조 936
 
9.4%
경량철골구조 838
 
8.4%
기타조적구조 289
 
2.9%
강파이프구조 27
 
0.3%
철골콘크리트구조 26
 
0.3%
철골철근콘크리트구조 19
 
0.2%
Other values (10) 54
 
0.5%

Length

2023-12-12T15:06:18.351434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
철근콘크리트구조 4232
42.3%
일반철골구조 1624
 
16.2%
블록구조 1015
 
10.2%
벽돌구조 940
 
9.4%
일반목구조 936
 
9.4%
경량철골구조 838
 
8.4%
기타조적구조 289
 
2.9%
강파이프구조 27
 
0.3%
철골콘크리트구조 26
 
0.3%
철골철근콘크리트구조 19
 
0.2%
Other values (10) 54
 
0.5%
Distinct443
Distinct (%)4.4%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2023-12-12T15:06:18.715062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length6.4001601
Min length2

Characters and Unicode

Total characters63944
Distinct characters78
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique257 ?
Unique (%)2.6%

Sample

1st row경량철골구조
2nd row철근콘크리트조/벽돌조/철골조
3rd row철근콘크리트 라멘조
4th row블럭조
5th row일반철골구조
ValueCountFrequency (%)
철근콘크리트구조 2084
20.3%
철근콘크리트조 1345
13.1%
일반철골구조 1003
9.8%
조적조 856
 
8.4%
목조 653
 
6.4%
경량철골구조 505
 
4.9%
블럭조 448
 
4.4%
철골조 409
 
4.0%
철근콘크리트조/조적조 374
 
3.6%
블록조 299
 
2.9%
Other values (369) 2271
22.2%
2023-12-12T15:06:19.240796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13010
20.3%
7214
11.3%
4746
 
7.4%
4439
 
6.9%
4400
 
6.9%
4399
 
6.9%
4388
 
6.9%
4188
 
6.5%
2825
 
4.4%
1467
 
2.3%
Other values (68) 12868
20.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 61856
96.7%
Other Punctuation 1727
 
2.7%
Space Separator 256
 
0.4%
Open Punctuation 44
 
0.1%
Close Punctuation 44
 
0.1%
Uppercase Letter 15
 
< 0.1%
Math Symbol 1
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13010
21.0%
7214
11.7%
4746
 
7.7%
4439
 
7.2%
4400
 
7.1%
4399
 
7.1%
4388
 
7.1%
4188
 
6.8%
2825
 
4.6%
1467
 
2.4%
Other values (55) 10780
17.4%
Uppercase Letter
ValueCountFrequency (%)
C 7
46.7%
R 5
33.3%
A 1
 
6.7%
L 1
 
6.7%
P 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
/ 1427
82.6%
, 295
 
17.1%
. 5
 
0.3%
Space Separator
ValueCountFrequency (%)
256
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 61856
96.7%
Common 2073
 
3.2%
Latin 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
13010
21.0%
7214
11.7%
4746
 
7.7%
4439
 
7.2%
4400
 
7.1%
4399
 
7.1%
4388
 
7.1%
4188
 
6.8%
2825
 
4.6%
1467
 
2.4%
Other values (55) 10780
17.4%
Common
ValueCountFrequency (%)
/ 1427
68.8%
, 295
 
14.2%
256
 
12.3%
( 44
 
2.1%
) 44
 
2.1%
. 5
 
0.2%
+ 1
 
< 0.1%
1 1
 
< 0.1%
Latin
ValueCountFrequency (%)
C 7
46.7%
R 5
33.3%
A 1
 
6.7%
L 1
 
6.7%
P 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 61856
96.7%
ASCII 2088
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
13010
21.0%
7214
11.7%
4746
 
7.7%
4439
 
7.2%
4400
 
7.1%
4399
 
7.1%
4388
 
7.1%
4188
 
6.8%
2825
 
4.6%
1467
 
2.4%
Other values (55) 10780
17.4%
ASCII
ValueCountFrequency (%)
/ 1427
68.3%
, 295
 
14.1%
256
 
12.3%
( 44
 
2.1%
) 44
 
2.1%
C 7
 
0.3%
. 5
 
0.2%
R 5
 
0.2%
A 1
 
< 0.1%
L 1
 
< 0.1%
Other values (3) 3
 
0.1%

주용도코드
Unsupported

REJECTED  UNSUPPORTED 

Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단독주택
4817 
공장
1221 
제2종근린생활시설
1167 
공동주택
1046 
제1종근린생활시설
720 
Other values (26)
1029 

Length

Max length10
Median length4
Mean length4.9047
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row교육연구시설
2nd row제2종근린생활시설
3rd row교육연구시설
4th row창고시설
5th row제1종근린생활시설

Common Values

ValueCountFrequency (%)
단독주택 4817
48.2%
공장 1221
 
12.2%
제2종근린생활시설 1167
 
11.7%
공동주택 1046
 
10.5%
제1종근린생활시설 720
 
7.2%
창고시설 177
 
1.8%
동.식물관련시설 124
 
1.2%
교육연구시설 119
 
1.2%
위험물저장및처리시설 93
 
0.9%
운동시설 78
 
0.8%
Other values (21) 438
 
4.4%

Length

2023-12-12T15:06:19.441380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 4817
48.2%
공장 1221
 
12.2%
제2종근린생활시설 1167
 
11.7%
공동주택 1046
 
10.5%
제1종근린생활시설 720
 
7.2%
창고시설 177
 
1.8%
동.식물관련시설 124
 
1.2%
교육연구시설 119
 
1.2%
위험물저장및처리시설 93
 
0.9%
운동시설 78
 
0.8%
Other values (21) 438
 
4.4%
Distinct1055
Distinct (%)10.6%
Missing6
Missing (%)0.1%
Memory size156.2 KiB
2023-12-12T15:06:19.746373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length54
Mean length7.6179708
Min length2

Characters and Unicode

Total characters76134
Distinct characters273
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique730 ?
Unique (%)7.3%

Sample

1st row교육연구시설
2nd row제2종근린생활시설/단독주택
3rd row교육연구시설
4th row창고
5th row제1종근린생활시설
ValueCountFrequency (%)
단독주택 2728
25.1%
공장 1021
 
9.4%
제2종근린생활시설 859
 
7.9%
공동주택 532
 
4.9%
주택 379
 
3.5%
제1종근린생활시설 346
 
3.2%
근린생활시설 267
 
2.5%
255
 
2.3%
근린생활시설/단독주택 241
 
2.2%
단독주택/제2종근린생활시설 239
 
2.2%
Other values (910) 4006
36.8%
2023-12-12T15:06:20.167282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6126
 
8.0%
6037
 
7.9%
4793
 
6.3%
4788
 
6.3%
4625
 
6.1%
4616
 
6.1%
3613
 
4.7%
3603
 
4.7%
3571
 
4.7%
3554
 
4.7%
Other values (263) 30808
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66101
86.8%
Decimal Number 3965
 
5.2%
Other Punctuation 3028
 
4.0%
Close Punctuation 1055
 
1.4%
Open Punctuation 1052
 
1.4%
Space Separator 884
 
1.2%
Uppercase Letter 41
 
0.1%
Dash Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6126
 
9.3%
6037
 
9.1%
4793
 
7.3%
4788
 
7.2%
4625
 
7.0%
4616
 
7.0%
3613
 
5.5%
3603
 
5.5%
3571
 
5.4%
3554
 
5.4%
Other values (237) 20775
31.4%
Decimal Number
ValueCountFrequency (%)
2 2135
53.8%
1 1327
33.5%
4 154
 
3.9%
3 85
 
2.1%
8 70
 
1.8%
5 47
 
1.2%
0 45
 
1.1%
6 42
 
1.1%
7 41
 
1.0%
9 19
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
F 11
26.8%
D 11
26.8%
M 11
26.8%
E 3
 
7.3%
V 2
 
4.9%
L 1
 
2.4%
G 1
 
2.4%
X 1
 
2.4%
Other Punctuation
ValueCountFrequency (%)
/ 2183
72.1%
, 790
 
26.1%
. 54
 
1.8%
# 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 1055
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1052
100.0%
Space Separator
ValueCountFrequency (%)
884
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66101
86.8%
Common 9992
 
13.1%
Latin 41
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6126
 
9.3%
6037
 
9.1%
4793
 
7.3%
4788
 
7.2%
4625
 
7.0%
4616
 
7.0%
3613
 
5.5%
3603
 
5.5%
3571
 
5.4%
3554
 
5.4%
Other values (237) 20775
31.4%
Common
ValueCountFrequency (%)
/ 2183
21.8%
2 2135
21.4%
1 1327
13.3%
) 1055
10.6%
( 1052
10.5%
884
8.8%
, 790
 
7.9%
4 154
 
1.5%
3 85
 
0.9%
8 70
 
0.7%
Other values (8) 257
 
2.6%
Latin
ValueCountFrequency (%)
F 11
26.8%
D 11
26.8%
M 11
26.8%
E 3
 
7.3%
V 2
 
4.9%
L 1
 
2.4%
G 1
 
2.4%
X 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66101
86.8%
ASCII 10033
 
13.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6126
 
9.3%
6037
 
9.1%
4793
 
7.3%
4788
 
7.2%
4625
 
7.0%
4616
 
7.0%
3613
 
5.5%
3603
 
5.5%
3571
 
5.4%
3554
 
5.4%
Other values (237) 20775
31.4%
ASCII
ValueCountFrequency (%)
/ 2183
21.8%
2 2135
21.3%
1 1327
13.2%
) 1055
10.5%
( 1052
10.5%
884
8.8%
, 790
 
7.9%
4 154
 
1.5%
3 85
 
0.8%
8 70
 
0.7%
Other values (16) 298
 
3.0%

지붕코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
10
5340 
90
2910 
30
1073 
20
663 
<NA>
 
14

Length

Max length4
Median length2
Mean length2.0028
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row90
2nd row10
3rd row10
4th row30
5th row90

Common Values

ValueCountFrequency (%)
10 5340
53.4%
90 2910
29.1%
30 1073
 
10.7%
20 663
 
6.6%
<NA> 14
 
0.1%

Length

2023-12-12T15:06:20.374367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:20.489248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 5340
53.4%
90 2910
29.1%
30 1073
 
10.7%
20 663
 
6.6%
na 14
 
0.1%

지붕코드명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
(철근)콘크리트
5340 
기타지붕
2910 
슬레이트
1073 
기와
663 
<NA>
 
14

Length

Max length8
Median length8
Mean length6.0034
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
(철근)콘크리트 5340
53.4%
기타지붕 2910
29.1%
슬레이트 1073
 
10.7%
기와 663
 
6.6%
<NA> 14
 
0.1%

Length

2023-12-12T15:06:20.626791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:20.758260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근)콘크리트 5340
53.4%
기타지붕 2910
29.1%
슬레이트 1073
 
10.7%
기와 663
 
6.6%
na 14
 
0.1%
Distinct679
Distinct (%)6.8%
Missing28
Missing (%)0.3%
Memory size156.2 KiB
2023-12-12T15:06:21.042301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length4.8589049
Min length2

Characters and Unicode

Total characters48453
Distinct characters209
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

Unique440 ?
Unique (%)4.4%

Sample

1st row샌드위치판넬
2nd row슬라브/샌드위치판넬
3rd row경사슬라브
4th row스레이트
5th row판넬
ValueCountFrequency (%)
슬라브 3060
30.1%
철근)콘크리트 934
 
9.2%
샌드위치판넬 888
 
8.7%
스레이트 857
 
8.4%
판넬 357
 
3.5%
기타지붕 316
 
3.1%
기와 308
 
3.0%
스라브 266
 
2.6%
경사슬라브 165
 
1.6%
기와/스레이트 122
 
1.2%
Other values (594) 2910
28.6%
2023-12-12T15:06:21.513610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4508
 
9.3%
4311
 
8.9%
3775
 
7.8%
2957
 
6.1%
2231
 
4.6%
2133
 
4.4%
2047
 
4.2%
1418
 
2.9%
1395
 
2.9%
1320
 
2.7%
Other values (199) 22358
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44810
92.5%
Close Punctuation 1177
 
2.4%
Open Punctuation 1177
 
2.4%
Other Punctuation 932
 
1.9%
Space Separator 211
 
0.4%
Decimal Number 78
 
0.2%
Uppercase Letter 47
 
0.1%
Lowercase Letter 12
 
< 0.1%
Math Symbol 5
 
< 0.1%
Other Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4508
 
10.1%
4311
 
9.6%
3775
 
8.4%
2957
 
6.6%
2231
 
5.0%
2133
 
4.8%
2047
 
4.6%
1418
 
3.2%
1395
 
3.1%
1320
 
2.9%
Other values (165) 18715
41.8%
Uppercase Letter
ValueCountFrequency (%)
T 14
29.8%
K 6
12.8%
M 5
 
10.6%
S 4
 
8.5%
A 3
 
6.4%
E 3
 
6.4%
D 2
 
4.3%
H 2
 
4.3%
C 2
 
4.3%
P 2
 
4.3%
Other values (3) 4
 
8.5%
Decimal Number
ValueCountFrequency (%)
0 24
30.8%
1 16
20.5%
5 16
20.5%
2 12
15.4%
7 6
 
7.7%
3 2
 
2.6%
4 1
 
1.3%
8 1
 
1.3%
Lowercase Letter
ValueCountFrequency (%)
m 8
66.7%
t 2
 
16.7%
h 1
 
8.3%
k 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
/ 744
79.8%
, 185
 
19.8%
. 3
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 1177
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1177
100.0%
Space Separator
ValueCountFrequency (%)
211
100.0%
Math Symbol
ValueCountFrequency (%)
= 5
100.0%
Other Symbol
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44810
92.5%
Common 3584
 
7.4%
Latin 59
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4508
 
10.1%
4311
 
9.6%
3775
 
8.4%
2957
 
6.6%
2231
 
5.0%
2133
 
4.8%
2047
 
4.6%
1418
 
3.2%
1395
 
3.1%
1320
 
2.9%
Other values (165) 18715
41.8%
Common
ValueCountFrequency (%)
) 1177
32.8%
( 1177
32.8%
/ 744
20.8%
211
 
5.9%
, 185
 
5.2%
0 24
 
0.7%
1 16
 
0.4%
5 16
 
0.4%
2 12
 
0.3%
7 6
 
0.2%
Other values (7) 16
 
0.4%
Latin
ValueCountFrequency (%)
T 14
23.7%
m 8
13.6%
K 6
10.2%
M 5
 
8.5%
S 4
 
6.8%
A 3
 
5.1%
E 3
 
5.1%
D 2
 
3.4%
H 2
 
3.4%
C 2
 
3.4%
Other values (7) 10
16.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44810
92.5%
ASCII 3640
 
7.5%
CJK Compat 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4508
 
10.1%
4311
 
9.6%
3775
 
8.4%
2957
 
6.6%
2231
 
5.0%
2133
 
4.8%
2047
 
4.6%
1418
 
3.2%
1395
 
3.1%
1320
 
2.9%
Other values (165) 18715
41.8%
ASCII
ValueCountFrequency (%)
) 1177
32.3%
( 1177
32.3%
/ 744
20.4%
211
 
5.8%
, 185
 
5.1%
0 24
 
0.7%
1 16
 
0.4%
5 16
 
0.4%
T 14
 
0.4%
2 12
 
0.3%
Other values (23) 64
 
1.8%
CJK Compat
ValueCountFrequency (%)
3
100.0%

세대수(세대)
Real number (ℝ)

ZEROS 

Distinct117
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5129
Minimum0
Maximum346
Zeros9126
Zeros (%)91.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:21.664076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile9.05
Maximum346
Range346
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16.860625
Coefficient of variation (CV)4.7996312
Kurtosis57.994564
Mean3.5129
Median Absolute Deviation (MAD)0
Skewness6.5845725
Sum35129
Variance284.28066
MonotonicityNot monotonic
2023-12-12T15:06:21.795203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9126
91.3%
8 253
 
2.5%
1 55
 
0.5%
60 52
 
0.5%
16 23
 
0.2%
72 21
 
0.2%
90 20
 
0.2%
7 19
 
0.2%
12 15
 
0.1%
84 15
 
0.1%
Other values (107) 401
 
4.0%
ValueCountFrequency (%)
0 9126
91.3%
1 55
 
0.5%
2 1
 
< 0.1%
3 10
 
0.1%
4 14
 
0.1%
5 3
 
< 0.1%
6 15
 
0.1%
7 19
 
0.2%
8 253
 
2.5%
9 4
 
< 0.1%
ValueCountFrequency (%)
346 1
< 0.1%
274 1
< 0.1%
215 1
< 0.1%
195 1
< 0.1%
190 1
< 0.1%
185 1
< 0.1%
183 2
< 0.1%
180 1
< 0.1%
176 1
< 0.1%
168 1
< 0.1%

가구수(가구)
Real number (ℝ)

ZEROS 

Distinct30
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2614
Minimum0
Maximum114
Zeros5008
Zeros (%)50.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:21.921957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5
Maximum114
Range114
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.294777
Coefficient of variation (CV)2.6120002
Kurtosis446.33778
Mean1.2614
Median Absolute Deviation (MAD)0
Skewness16.409213
Sum12614
Variance10.855556
MonotonicityNot monotonic
2023-12-12T15:06:22.050603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 5008
50.1%
1 3211
32.1%
4 580
 
5.8%
3 447
 
4.5%
2 186
 
1.9%
5 116
 
1.2%
6 108
 
1.1%
8 85
 
0.9%
7 53
 
0.5%
11 49
 
0.5%
Other values (20) 157
 
1.6%
ValueCountFrequency (%)
0 5008
50.1%
1 3211
32.1%
2 186
 
1.9%
3 447
 
4.5%
4 580
 
5.8%
5 116
 
1.2%
6 108
 
1.1%
7 53
 
0.5%
8 85
 
0.9%
9 20
 
0.2%
ValueCountFrequency (%)
114 1
< 0.1%
108 1
< 0.1%
99 1
< 0.1%
86 1
< 0.1%
80 1
< 0.1%
70 1
< 0.1%
66 1
< 0.1%
58 1
< 0.1%
39 1
< 0.1%
21 1
< 0.1%

높이(미터)
Real number (ℝ)

ZEROS 

Distinct1236
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1538561
Minimum0
Maximum163.9
Zeros3369
Zeros (%)33.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:22.219024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.65
Q311.5
95-th percentile23.7
Maximum163.9
Range163.9
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation11.024553
Coefficient of variation (CV)1.3520661
Kurtosis18.586535
Mean8.1538561
Median Absolute Deviation (MAD)6.05
Skewness3.4901203
Sum81538.561
Variance121.54076
MonotonicityNot monotonic
2023-12-12T15:06:22.375564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3369
33.7%
3.9 89
 
0.9%
12.0 84
 
0.8%
4.5 83
 
0.8%
7.9 69
 
0.7%
11.7 65
 
0.7%
4.0 63
 
0.6%
12.2 62
 
0.6%
7.7 59
 
0.6%
12.1 59
 
0.6%
Other values (1226) 5998
60.0%
ValueCountFrequency (%)
0.0 3369
33.7%
0.85 1
 
< 0.1%
0.95 1
 
< 0.1%
1.8 2
 
< 0.1%
1.95 1
 
< 0.1%
2.0 1
 
< 0.1%
2.1 1
 
< 0.1%
2.2 1
 
< 0.1%
2.23 1
 
< 0.1%
2.3 3
 
< 0.1%
ValueCountFrequency (%)
163.9 1
 
< 0.1%
111.1 2
 
< 0.1%
109.35 1
 
< 0.1%
106.95 2
 
< 0.1%
85.4 1
 
< 0.1%
83.35 1
 
< 0.1%
82.6 5
0.1%
81.95 1
 
< 0.1%
79.8 1
 
< 0.1%
79.1 1
 
< 0.1%

지상층수
Real number (ℝ)

ZEROS 

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6082
Minimum0
Maximum40
Zeros121
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:22.518063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile6
Maximum40
Range40
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.5005883
Coefficient of variation (CV)1.3421472
Kurtosis23.091296
Mean2.6082
Median Absolute Deviation (MAD)1
Skewness4.4525485
Sum26082
Variance12.254118
MonotonicityNot monotonic
2023-12-12T15:06:22.670678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 4609
46.1%
2 2049
20.5%
3 1777
 
17.8%
4 633
 
6.3%
5 267
 
2.7%
0 121
 
1.2%
15 116
 
1.2%
6 68
 
0.7%
20 41
 
0.4%
18 38
 
0.4%
Other values (24) 281
 
2.8%
ValueCountFrequency (%)
0 121
 
1.2%
1 4609
46.1%
2 2049
20.5%
3 1777
 
17.8%
4 633
 
6.3%
5 267
 
2.7%
6 68
 
0.7%
7 20
 
0.2%
8 23
 
0.2%
9 21
 
0.2%
ValueCountFrequency (%)
40 1
 
< 0.1%
38 2
 
< 0.1%
32 2
 
< 0.1%
30 1
 
< 0.1%
29 7
 
0.1%
28 3
 
< 0.1%
27 2
 
< 0.1%
26 2
 
< 0.1%
25 30
0.3%
24 6
 
0.1%

지하층수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
9096 
1
 
819
2
 
70
3
 
10
4
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 9096
91.0%
1 819
 
8.2%
2 70
 
0.7%
3 10
 
0.1%
4 5
 
0.1%

Length

2023-12-12T15:06:22.810344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:22.914124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 9096
91.0%
1 819
 
8.2%
2 70
 
0.7%
3 10
 
0.1%
4 5
 
< 0.1%

승용승강기수
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0871
Minimum0
Maximum13
Zeros9491
Zeros (%)94.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:23.036336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4943056
Coefficient of variation (CV)5.6751504
Kurtosis225.66245
Mean0.0871
Median Absolute Deviation (MAD)0
Skewness11.706008
Sum871
Variance0.24433802
MonotonicityNot monotonic
2023-12-12T15:06:23.205797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 9491
94.9%
1 308
 
3.1%
2 123
 
1.2%
3 50
 
0.5%
4 15
 
0.1%
5 4
 
< 0.1%
13 4
 
< 0.1%
6 3
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
0 9491
94.9%
1 308
 
3.1%
2 123
 
1.2%
3 50
 
0.5%
4 15
 
0.1%
5 4
 
< 0.1%
6 3
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
13 4
 
< 0.1%
ValueCountFrequency (%)
13 4
 
< 0.1%
9 1
 
< 0.1%
8 1
 
< 0.1%
6 3
 
< 0.1%
5 4
 
< 0.1%
4 15
 
0.1%
3 50
 
0.5%
2 123
 
1.2%
1 308
 
3.1%
0 9491
94.9%

비상용승강기수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0439
Minimum0
Maximum5
Zeros9767
Zeros (%)97.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:23.317236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation0.30229444
Coefficient of variation (CV)6.8859781
Kurtosis61.480238
Mean0.0439
Median Absolute Deviation (MAD)0
Skewness7.5384518
Sum439
Variance0.091381928
MonotonicityNot monotonic
2023-12-12T15:06:23.422945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 9767
97.7%
2 138
 
1.4%
1 63
 
0.6%
3 29
 
0.3%
4 2
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
0 9767
97.7%
1 63
 
0.6%
2 138
 
1.4%
3 29
 
0.3%
4 2
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
4 2
 
< 0.1%
3 29
 
0.3%
2 138
 
1.4%
1 63
 
0.6%
0 9767
97.7%

부속건축물수
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2244
Minimum0
Maximum25
Zeros8567
Zeros (%)85.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:23.609579image/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 deviation0.7837768
Coefficient of variation (CV)3.4927665
Kurtosis147.78581
Mean0.2244
Median Absolute Deviation (MAD)0
Skewness8.6584102
Sum2244
Variance0.61430607
MonotonicityNot monotonic
2023-12-12T15:06:23.779566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 8567
85.7%
1 1057
 
10.6%
2 234
 
2.3%
3 48
 
0.5%
4 27
 
0.3%
5 21
 
0.2%
6 15
 
0.1%
7 14
 
0.1%
9 7
 
0.1%
8 4
 
< 0.1%
Other values (4) 6
 
0.1%
ValueCountFrequency (%)
0 8567
85.7%
1 1057
 
10.6%
2 234
 
2.3%
3 48
 
0.5%
4 27
 
0.3%
5 21
 
0.2%
6 15
 
0.1%
7 14
 
0.1%
8 4
 
< 0.1%
9 7
 
0.1%
ValueCountFrequency (%)
25 1
 
< 0.1%
13 1
 
< 0.1%
11 1
 
< 0.1%
10 3
 
< 0.1%
9 7
 
0.1%
8 4
 
< 0.1%
7 14
0.1%
6 15
0.1%
5 21
0.2%
4 27
0.3%

부속건축물면적(제곱미터)
Real number (ℝ)

SKEWED  ZEROS 

Distinct967
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.06066
Minimum0
Maximum79689.73
Zeros8577
Zeros (%)85.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:23.918452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile63
Maximum79689.73
Range79689.73
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1720.0167
Coefficient of variation (CV)17.540334
Kurtosis1176.3211
Mean98.06066
Median Absolute Deviation (MAD)0
Skewness31.442019
Sum980606.6
Variance2958457.4
MonotonicityNot monotonic
2023-12-12T15:06:24.069360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8577
85.8%
2.0 54
 
0.5%
2.88 29
 
0.3%
1.0 24
 
0.2%
3.0 23
 
0.2%
1.44 16
 
0.2%
10.0 11
 
0.1%
2.4 10
 
0.1%
6.0 9
 
0.1%
15.0 9
 
0.1%
Other values (957) 1238
 
12.4%
ValueCountFrequency (%)
0.0 8577
85.8%
0.88 1
 
< 0.1%
0.9 1
 
< 0.1%
1.0 24
 
0.2%
1.1 4
 
< 0.1%
1.2 9
 
0.1%
1.21 3
 
< 0.1%
1.32 1
 
< 0.1%
1.38 1
 
< 0.1%
1.44 16
 
0.2%
ValueCountFrequency (%)
79689.7298 1
 
< 0.1%
69618.8443 2
< 0.1%
51804.2448 1
 
< 0.1%
45861.98 1
 
< 0.1%
37372.6704 1
 
< 0.1%
25082.1681 1
 
< 0.1%
23675.2912 1
 
< 0.1%
23331.2064 1
 
< 0.1%
23216.986 1
 
< 0.1%
22376.0945 4
< 0.1%

총동연면적(제곱미터)
Real number (ℝ)

ZEROS 

Distinct8028
Distinct (%)80.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean857.44524
Minimum0
Maximum116481.36
Zeros151
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:24.248565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18.89861
Q183.175
median238.04
Q3483.4725
95-th percentile4616.6847
Maximum116481.36
Range116481.36
Interquartile range (IQR)400.2975

Descriptive statistics

Standard deviation2844.1876
Coefficient of variation (CV)3.3170487
Kurtosis420.07171
Mean857.44524
Median Absolute Deviation (MAD)173.09
Skewness14.971474
Sum8574452.4
Variance8089403
MonotonicityNot monotonic
2023-12-12T15:06:24.811999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 151
 
1.5%
6.25 50
 
0.5%
26.45 30
 
0.3%
19.83 26
 
0.3%
23.14 24
 
0.2%
33.06 21
 
0.2%
46.28 19
 
0.2%
39.67 17
 
0.2%
20.0 16
 
0.2%
33.0 16
 
0.2%
Other values (8018) 9630
96.3%
ValueCountFrequency (%)
0.0 151
1.5%
0.81 1
 
< 0.1%
0.99 1
 
< 0.1%
1.0 3
 
< 0.1%
1.44 1
 
< 0.1%
1.5 2
 
< 0.1%
1.56 2
 
< 0.1%
1.65 1
 
< 0.1%
1.77 1
 
< 0.1%
2.0 3
 
< 0.1%
ValueCountFrequency (%)
116481.3569 1
< 0.1%
78954.2133 1
< 0.1%
65063.3312 1
< 0.1%
64715.9374 1
< 0.1%
59909.2762 1
< 0.1%
42784.28 1
< 0.1%
35917.3732 1
< 0.1%
30799.6776 1
< 0.1%
30702.35 1
< 0.1%
30659.914 1
< 0.1%

옥내기계식대수(대)
Real number (ℝ)

SKEWED  ZEROS 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1242
Minimum0
Maximum136
Zeros9951
Zeros (%)99.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:24.977639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum136
Range136
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.4772541
Coefficient of variation (CV)19.945685
Kurtosis1315.0724
Mean0.1242
Median Absolute Deviation (MAD)0
Skewness31.703063
Sum1242
Variance6.136788
MonotonicityNot monotonic
2023-12-12T15:06:25.153869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 9951
99.5%
8 4
 
< 0.1%
24 3
 
< 0.1%
40 3
 
< 0.1%
4 2
 
< 0.1%
10 2
 
< 0.1%
9 2
 
< 0.1%
6 2
 
< 0.1%
19 2
 
< 0.1%
34 2
 
< 0.1%
Other values (21) 27
 
0.3%
ValueCountFrequency (%)
0 9951
99.5%
1 1
 
< 0.1%
2 2
 
< 0.1%
4 2
 
< 0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
8 4
 
< 0.1%
9 2
 
< 0.1%
10 2
 
< 0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
136 1
 
< 0.1%
96 1
 
< 0.1%
72 1
 
< 0.1%
58 1
 
< 0.1%
48 2
< 0.1%
44 1
 
< 0.1%
40 3
< 0.1%
38 1
 
< 0.1%
36 1
 
< 0.1%
35 1
 
< 0.1%

옥내기계식면적(제곱미터)
Real number (ℝ)

SKEWED  ZEROS 

Distinct44
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7050338
Minimum0
Maximum739.58
Zeros9956
Zeros (%)99.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:25.292005image/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 deviation14.712908
Coefficient of variation (CV)20.868373
Kurtosis1054.1306
Mean0.7050338
Median Absolute Deviation (MAD)0
Skewness29.359169
Sum7050.338
Variance216.46967
MonotonicityNot monotonic
2023-12-12T15:06:25.433420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0.0 9956
99.6%
50.4 2
 
< 0.1%
343.65 1
 
< 0.1%
336.0 1
 
< 0.1%
54.56 1
 
< 0.1%
46.8 1
 
< 0.1%
37.7 1
 
< 0.1%
511.0 1
 
< 0.1%
98.0 1
 
< 0.1%
274.16 1
 
< 0.1%
Other values (34) 34
 
0.3%
ValueCountFrequency (%)
0.0 9956
99.6%
11.5 1
 
< 0.1%
20.4 1
 
< 0.1%
20.52 1
 
< 0.1%
32.5 1
 
< 0.1%
37.7 1
 
< 0.1%
39.52 1
 
< 0.1%
46.8 1
 
< 0.1%
47.0 1
 
< 0.1%
47.36 1
 
< 0.1%
ValueCountFrequency (%)
739.58 1
< 0.1%
511.0 1
< 0.1%
420.85 1
< 0.1%
384.86 1
< 0.1%
343.65 1
< 0.1%
336.0 1
< 0.1%
320.44 1
< 0.1%
305.7 1
< 0.1%
290.94 1
< 0.1%
274.16 1
< 0.1%

옥외기계식대수(대)
Real number (ℝ)

SKEWED  ZEROS 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0088
Minimum0
Maximum30
Zeros9992
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:25.557123image/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 deviation0.40833716
Coefficient of variation (CV)46.40195
Kurtosis3679.0657
Mean0.0088
Median Absolute Deviation (MAD)0
Skewness57.785568
Sum88
Variance0.16673923
MonotonicityNot monotonic
2023-12-12T15:06:25.664668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 9992
99.9%
18 2
 
< 0.1%
3 1
 
< 0.1%
1 1
 
< 0.1%
30 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
0 9992
99.9%
1 1
 
< 0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
18 2
 
< 0.1%
30 1
 
< 0.1%
ValueCountFrequency (%)
30 1
 
< 0.1%
18 2
 
< 0.1%
7 1
 
< 0.1%
6 1
 
< 0.1%
5 1
 
< 0.1%
3 1
 
< 0.1%
1 1
 
< 0.1%
0 9992
99.9%

옥외기계식면적(제곱미터)
Real number (ℝ)

SKEWED  ZEROS 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.033995
Minimum0
Maximum69
Zeros9993
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:25.767101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum69
Range69
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.3180618
Coefficient of variation (CV)38.772224
Kurtosis1732.5156
Mean0.033995
Median Absolute Deviation (MAD)0
Skewness40.716113
Sum339.95
Variance1.7372868
MonotonicityNot monotonic
2023-12-12T15:06:25.906066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 9993
99.9%
34.5 1
 
< 0.1%
47.95 1
 
< 0.1%
51.68 1
 
< 0.1%
69.0 1
 
< 0.1%
37.5 1
 
< 0.1%
57.5 1
 
< 0.1%
41.82 1
 
< 0.1%
ValueCountFrequency (%)
0.0 9993
99.9%
34.5 1
 
< 0.1%
37.5 1
 
< 0.1%
41.82 1
 
< 0.1%
47.95 1
 
< 0.1%
51.68 1
 
< 0.1%
57.5 1
 
< 0.1%
69.0 1
 
< 0.1%
ValueCountFrequency (%)
69.0 1
 
< 0.1%
57.5 1
 
< 0.1%
51.68 1
 
< 0.1%
47.95 1
 
< 0.1%
41.82 1
 
< 0.1%
37.5 1
 
< 0.1%
34.5 1
 
< 0.1%
0.0 9993
99.9%

옥내자주식대수(대)
Real number (ℝ)

SKEWED  ZEROS 

Distinct92
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3119
Minimum0
Maximum2223
Zeros9125
Zeros (%)91.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:26.053492image/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 deviation43.613973
Coefficient of variation (CV)13.168868
Kurtosis863.78173
Mean3.3119
Median Absolute Deviation (MAD)0
Skewness24.606939
Sum33119
Variance1902.1786
MonotonicityNot monotonic
2023-12-12T15:06:26.219623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9125
91.2%
1 147
 
1.5%
2 133
 
1.3%
6 110
 
1.1%
3 82
 
0.8%
4 81
 
0.8%
5 56
 
0.6%
8 37
 
0.4%
7 19
 
0.2%
11 12
 
0.1%
Other values (82) 198
 
2.0%
ValueCountFrequency (%)
0 9125
91.2%
1 147
 
1.5%
2 133
 
1.3%
3 82
 
0.8%
4 81
 
0.8%
5 56
 
0.6%
6 110
 
1.1%
7 19
 
0.2%
8 37
 
0.4%
9 11
 
0.1%
ValueCountFrequency (%)
2223 1
 
< 0.1%
917 3
< 0.1%
837 3
< 0.1%
776 6
0.1%
653 2
 
< 0.1%
593 3
< 0.1%
544 1
 
< 0.1%
520 1
 
< 0.1%
515 3
< 0.1%
498 2
 
< 0.1%

옥내자주식면적(제곱미터)
Real number (ℝ)

ZEROS 

Distinct456
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78.647804
Minimum0
Maximum31132.91
Zeros9154
Zeros (%)91.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:26.358639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile46
Maximum31132.91
Range31132.91
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1077.3423
Coefficient of variation (CV)13.698314
Kurtosis439.5336
Mean78.647804
Median Absolute Deviation (MAD)0
Skewness19.808172
Sum786478.04
Variance1160666.4
MonotonicityNot monotonic
2023-12-12T15:06:26.498050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 9154
91.5%
104.68 61
 
0.6%
23.0 57
 
0.6%
46.0 46
 
0.5%
34.5 33
 
0.3%
11.5 31
 
0.3%
69.0 30
 
0.3%
57.5 23
 
0.2%
92.0 19
 
0.2%
80.5 7
 
0.1%
Other values (446) 539
 
5.4%
ValueCountFrequency (%)
0.0 9154
91.5%
5.4 1
 
< 0.1%
8.7 1
 
< 0.1%
10.53 1
 
< 0.1%
11.5 31
 
0.3%
12.0 3
 
< 0.1%
12.15 1
 
< 0.1%
12.5 2
 
< 0.1%
12.63 1
 
< 0.1%
13.23 1
 
< 0.1%
ValueCountFrequency (%)
31132.91 3
< 0.1%
25852.0 1
 
< 0.1%
23225.93 3
< 0.1%
21018.4411 6
0.1%
17264.343 3
< 0.1%
17171.49 2
 
< 0.1%
16318.188 1
 
< 0.1%
15474.02 1
 
< 0.1%
14757.16 1
 
< 0.1%
12116.77 1
 
< 0.1%

옥외자주식대수(대)
Real number (ℝ)

SKEWED  ZEROS 

Distinct113
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.4186
Minimum0
Maximum4671
Zeros5867
Zeros (%)58.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:26.651792image/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 deviation146.07445
Coefficient of variation (CV)11.762554
Kurtosis828.96454
Mean12.4186
Median Absolute Deviation (MAD)0
Skewness26.76751
Sum124186
Variance21337.746
MonotonicityNot monotonic
2023-12-12T15:06:26.819560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5867
58.7%
2 973
 
9.7%
1 807
 
8.1%
4 502
 
5.0%
3 436
 
4.4%
5 395
 
4.0%
6 189
 
1.9%
8 162
 
1.6%
7 100
 
1.0%
726 61
 
0.6%
Other values (103) 508
 
5.1%
ValueCountFrequency (%)
0 5867
58.7%
1 807
 
8.1%
2 973
 
9.7%
3 436
 
4.4%
4 502
 
5.0%
5 395
 
4.0%
6 189
 
1.9%
7 100
 
1.0%
8 162
 
1.6%
9 50
 
0.5%
ValueCountFrequency (%)
4671 8
 
0.1%
726 61
0.6%
657 3
 
< 0.1%
607 2
 
< 0.1%
602 2
 
< 0.1%
479 2
 
< 0.1%
468 2
 
< 0.1%
463 2
 
< 0.1%
413 1
 
< 0.1%
351 1
 
< 0.1%

옥외자주식면적(제곱미터)
Real number (ℝ)

SKEWED  ZEROS 

Distinct335
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean283.80867
Minimum0
Maximum163799
Zeros5937
Zeros (%)59.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:26.983944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q323
95-th percentile103.55
Maximum163799
Range163799
Interquartile range (IQR)23

Descriptive statistics

Standard deviation4841.8224
Coefficient of variation (CV)17.060164
Kurtosis1039.3887
Mean283.80867
Median Absolute Deviation (MAD)0
Skewness31.117901
Sum2838086.7
Variance23443244
MonotonicityNot monotonic
2023-12-12T15:06:27.148594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 5937
59.4%
23.0 889
 
8.9%
11.5 659
 
6.6%
46.0 389
 
3.9%
34.5 364
 
3.6%
57.5 280
 
2.8%
69.0 158
 
1.6%
92.0 148
 
1.5%
58.0 80
 
0.8%
80.5 78
 
0.8%
Other values (325) 1018
 
10.2%
ValueCountFrequency (%)
0.0 5937
59.4%
1.5 1
 
< 0.1%
6.0 1
 
< 0.1%
7.2 2
 
< 0.1%
7.36 1
 
< 0.1%
8.4 1
 
< 0.1%
10.0 10
 
0.1%
11.0 1
 
< 0.1%
11.05 1
 
< 0.1%
11.5 659
 
6.6%
ValueCountFrequency (%)
163799.0 8
 
0.1%
18900.0 2
 
< 0.1%
17621.11 61
0.6%
9869.75 2
 
< 0.1%
7579.65 3
 
< 0.1%
7066.5 2
 
< 0.1%
4255.0 2
 
< 0.1%
4158.0 2
 
< 0.1%
4061.5 3
 
< 0.1%
4036.5 1
 
< 0.1%

허가일
Date

MISSING 

Distinct4149
Distinct (%)58.7%
Missing2936
Missing (%)29.4%
Memory size156.2 KiB
Minimum1961-11-12 00:00:00
Maximum2021-02-03 00:00:00
2023-12-12T15:06:27.355410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:27.550236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공일
Date

MISSING 

Distinct4014
Distinct (%)62.2%
Missing3546
Missing (%)35.5%
Memory size156.2 KiB
Minimum1975-04-23 00:00:00
Maximum2021-03-15 00:00:00
2023-12-12T15:06:27.702250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:27.847008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용승인일
Date

MISSING 

Distinct5125
Distinct (%)53.6%
Missing438
Missing (%)4.4%
Memory size156.2 KiB
Minimum1900-04-30 00:00:00
Maximum2021-05-20 00:00:00
2023-12-12T15:06:28.016034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:28.184407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

허가번호년
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)0.7%
Missing6144
Missing (%)61.4%
Infinite0
Infinite (%)0.0%
Mean2011.4235
Minimum1992
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:28.339104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1992
5-th percentile2003
Q12008
median2012
Q32015
95-th percentile2018
Maximum2021
Range29
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.5780572
Coefficient of variation (CV)0.0022760285
Kurtosis-0.43785255
Mean2011.4235
Median Absolute Deviation (MAD)3
Skewness-0.35575199
Sum7756049
Variance20.958607
MonotonicityNot monotonic
2023-12-12T15:06:28.476210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2011 417
 
4.2%
2012 386
 
3.9%
2016 322
 
3.2%
2014 282
 
2.8%
2015 281
 
2.8%
2013 273
 
2.7%
2007 229
 
2.3%
2010 226
 
2.3%
2017 190
 
1.9%
2006 185
 
1.8%
Other values (16) 1065
 
10.7%
(Missing) 6144
61.4%
ValueCountFrequency (%)
1992 1
 
< 0.1%
1994 2
 
< 0.1%
1995 1
 
< 0.1%
1999 1
 
< 0.1%
2000 2
 
< 0.1%
2001 19
 
0.2%
2002 136
1.4%
2003 101
1.0%
2004 72
0.7%
2005 120
1.2%
ValueCountFrequency (%)
2021 3
 
< 0.1%
2020 79
 
0.8%
2019 90
 
0.9%
2018 129
 
1.3%
2017 190
1.9%
2016 322
3.2%
2015 281
2.8%
2014 282
2.8%
2013 273
2.7%
2012 386
3.9%

허가번호기관코드
Real number (ℝ)

MISSING 

Distinct28
Distinct (%)0.7%
Missing6168
Missing (%)61.7%
Infinite0
Infinite (%)0.0%
Mean5358427.6
Minimum5350019
Maximum6480624
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:28.630728image/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 deviation96248.93
Coefficient of variation (CV)0.017962159
Kurtosis132.03825
Mean5358427.6
Median Absolute Deviation (MAD)24
Skewness11.57451
Sum2.0533495 × 1010
Variance9.2638566 × 109
MonotonicityNot monotonic
2023-12-12T15:06:28.780729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
5350178 1587
 
15.9%
5350154 593
 
5.9%
5350141 385
 
3.9%
5350276 359
 
3.6%
5350140 209
 
2.1%
5350109 171
 
1.7%
5350245 113
 
1.1%
5350093 92
 
0.9%
5350108 76
 
0.8%
5350152 74
 
0.7%
Other values (18) 173
 
1.7%
(Missing) 6168
61.7%
ValueCountFrequency (%)
5350019 41
0.4%
5350023 3
 
< 0.1%
5350024 10
 
0.1%
5350047 3
 
< 0.1%
5350048 2
 
< 0.1%
5350055 1
 
< 0.1%
5350059 2
 
< 0.1%
5350060 3
 
< 0.1%
5350062 2
 
< 0.1%
5350093 92
0.9%
ValueCountFrequency (%)
6480624 5
 
0.1%
6480040 18
 
0.2%
6480000 5
 
0.1%
5350321 3
 
< 0.1%
5350276 359
 
3.6%
5350275 30
 
0.3%
5350245 113
 
1.1%
5350244 16
 
0.2%
5350178 1587
15.9%
5350177 26
 
0.3%

허가번호기관코드명
Categorical

IMBALANCE 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6168 
허가민원과
1682 
허가과
915 
도시관리과
 
593
건축과
 
315
Other values (14)
 
327

Length

Max length7
Median length4
Mean length4.1515
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6168
61.7%
허가민원과 1682
 
16.8%
허가과 915
 
9.2%
도시관리과 593
 
5.9%
건축과 315
 
3.1%
공동주택관리과 113
 
1.1%
장유출장소 74
 
0.7%
건축민원과 41
 
0.4%
주택과 33
 
0.3%
도시계획과 28
 
0.3%
Other values (9) 38
 
0.4%

Length

2023-12-12T15:06:28.939647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6168
61.7%
허가민원과 1682
 
16.8%
허가과 915
 
9.2%
도시관리과 593
 
5.9%
건축과 315
 
3.1%
공동주택관리과 113
 
1.1%
장유출장소 74
 
0.7%
건축민원과 41
 
0.4%
주택과 33
 
0.3%
도시계획과 28
 
0.3%
Other values (9) 38
 
0.4%

허가번호구분코드
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)0.4%
Missing6139
Missing (%)61.4%
Infinite0
Infinite (%)0.0%
Mean1306.9795
Minimum1101
Maximum5702
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:29.054872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1101
5-th percentile1101
Q11101
median1101
Q31102
95-th percentile2101
Maximum5702
Range4601
Interquartile range (IQR)1

Descriptive statistics

Standard deviation673.54673
Coefficient of variation (CV)0.51534604
Kurtosis25.080449
Mean1306.9795
Median Absolute Deviation (MAD)0
Skewness4.8170992
Sum5046248
Variance453665.2
MonotonicityNot monotonic
2023-12-12T15:06:29.160973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
1101 2716
27.2%
1201 389
 
3.9%
2101 362
 
3.6%
1102 202
 
2.0%
1202 79
 
0.8%
5310 36
 
0.4%
5200 23
 
0.2%
2301 21
 
0.2%
5100 15
 
0.1%
5701 10
 
0.1%
Other values (4) 8
 
0.1%
(Missing) 6139
61.4%
ValueCountFrequency (%)
1101 2716
27.2%
1102 202
 
2.0%
1103 3
 
< 0.1%
1104 2
 
< 0.1%
1107 1
 
< 0.1%
1201 389
 
3.9%
1202 79
 
0.8%
2101 362
 
3.6%
2301 21
 
0.2%
5100 15
 
0.1%
ValueCountFrequency (%)
5702 2
 
< 0.1%
5701 10
 
0.1%
5310 36
 
0.4%
5200 23
 
0.2%
5100 15
 
0.1%
2301 21
 
0.2%
2101 362
3.6%
1202 79
 
0.8%
1201 389
3.9%
1107 1
 
< 0.1%

허가번호구분코드명
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6139 
신축허가
2716 
신축신고
 
389
주택건설사업계획승인
 
362
증축허가
 
202
Other values (10)
 
192

Length

Max length12
Median length4
Mean length4.2727
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6139
61.4%
신축허가 2716
27.2%
신축신고 389
 
3.9%
주택건설사업계획승인 362
 
3.6%
증축허가 202
 
2.0%
증축신고 79
 
0.8%
개발제한구역내 건축허가 36
 
0.4%
공용건축물 23
 
0.2%
임대주택건설사업계획승인 21
 
0.2%
협의건축물 15
 
0.1%
Other values (5) 18
 
0.2%

Length

2023-12-12T15:06:29.313164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6139
61.2%
신축허가 2716
27.1%
신축신고 389
 
3.9%
주택건설사업계획승인 362
 
3.6%
증축허가 202
 
2.0%
증축신고 79
 
0.8%
개발제한구역내 36
 
0.4%
건축허가 36
 
0.4%
공용건축물 23
 
0.2%
임대주택건설사업계획승인 21
 
0.2%
Other values (6) 33
 
0.3%

호수(호)
Real number (ℝ)

SKEWED  ZEROS 

Distinct59
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3997
Minimum0
Maximum300
Zeros9790
Zeros (%)97.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:29.489528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum300
Range300
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.8266229
Coefficient of variation (CV)14.57749
Kurtosis1371.6395
Mean0.3997
Median Absolute Deviation (MAD)0
Skewness32.558114
Sum3997
Variance33.949535
MonotonicityNot monotonic
2023-12-12T15:06:30.055408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9790
97.9%
1 37
 
0.4%
7 13
 
0.1%
2 12
 
0.1%
4 11
 
0.1%
3 10
 
0.1%
8 8
 
0.1%
10 7
 
0.1%
6 7
 
0.1%
12 7
 
0.1%
Other values (49) 98
 
1.0%
ValueCountFrequency (%)
0 9790
97.9%
1 37
 
0.4%
2 12
 
0.1%
3 10
 
0.1%
4 11
 
0.1%
5 5
 
0.1%
6 7
 
0.1%
7 13
 
0.1%
8 8
 
0.1%
9 6
 
0.1%
ValueCountFrequency (%)
300 1
< 0.1%
254 1
< 0.1%
233 1
< 0.1%
121 1
< 0.1%
100 1
< 0.1%
99 1
< 0.1%
91 1
< 0.1%
81 1
< 0.1%
79 1
< 0.1%
75 1
< 0.1%
Distinct1108
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2009-03-21 00:00:00
Maximum2021-06-01 00:00:00
2023-12-12T15:06:30.197632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:06:30.360159image/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
<NA>
3979 
0
3905 
1
2116 

Length

Max length4
Median length1
Mean length2.1937
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3979
39.8%
0 3905
39.1%
1 2116
21.2%

Length

2023-12-12T15:06:30.515200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:06:30.635864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3979
39.8%
0 3905
39.1%
1 2116
21.2%

내진능력
Text

MISSING 

Distinct110
Distinct (%)32.4%
Missing9660
Missing (%)96.6%
Memory size156.2 KiB
2023-12-12T15:06:30.934672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length37
Mean length9.4529412
Min length1

Characters and Unicode

Total characters3214
Distinct characters90
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

Unique65 ?
Unique (%)19.1%

Sample

1st rowVII-0.173g
2nd rowVII-0.2159g
3rd row1등급
4th rowVII-0.1992g
5th rowⅦ-0.182g
ValueCountFrequency (%)
ⅶ-0.199g 29
 
7.1%
ⅶ-0.214g 27
 
6.6%
24
 
5.9%
vii-0.182g 22
 
5.4%
vii-0.199g 17
 
4.1%
ⅶ-0.191g 15
 
3.7%
vii-0.173g 12
 
2.9%
vii-0.214g 11
 
2.7%
11
 
2.7%
vii-0.169g 10
 
2.4%
Other values (115) 232
56.6%
2023-12-12T15:06:31.454991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 356
11.1%
. 324
10.1%
- 301
9.4%
1 300
9.3%
g 300
9.3%
I 269
8.4%
9 198
 
6.2%
2 192
 
6.0%
171
 
5.3%
V 138
 
4.3%
Other values (80) 665
20.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1339
41.7%
Uppercase Letter 432
 
13.4%
Other Punctuation 353
 
11.0%
Lowercase Letter 339
 
10.5%
Dash Punctuation 301
 
9.4%
Letter Number 176
 
5.5%
Other Letter 173
 
5.4%
Space Separator 75
 
2.3%
Close Punctuation 10
 
0.3%
Open Punctuation 10
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18
 
10.4%
18
 
10.4%
13
 
7.5%
10
 
5.8%
9
 
5.2%
9
 
5.2%
9
 
5.2%
8
 
4.6%
7
 
4.0%
7
 
4.0%
Other values (35) 65
37.6%
Lowercase Letter
ValueCountFrequency (%)
g 300
88.5%
l 22
 
6.5%
v 5
 
1.5%
i 4
 
1.2%
k 2
 
0.6%
e 1
 
0.3%
f 1
 
0.3%
x 1
 
0.3%
y 1
 
0.3%
h 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
0 356
26.6%
1 300
22.4%
9 198
14.8%
2 192
14.3%
4 63
 
4.7%
7 61
 
4.6%
8 56
 
4.2%
3 47
 
3.5%
6 37
 
2.8%
5 29
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
I 269
62.3%
V 138
31.9%
M 12
 
2.8%
D 3
 
0.7%
C 2
 
0.5%
S 2
 
0.5%
N 2
 
0.5%
G 2
 
0.5%
E 1
 
0.2%
L 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 324
91.8%
: 11
 
3.1%
/ 9
 
2.5%
, 8
 
2.3%
; 1
 
0.3%
Letter Number
ValueCountFrequency (%)
171
97.2%
3
 
1.7%
1
 
0.6%
1
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 301
100.0%
Space Separator
ValueCountFrequency (%)
75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Math Symbol
ValueCountFrequency (%)
= 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2094
65.2%
Latin 947
29.5%
Hangul 173
 
5.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18
 
10.4%
18
 
10.4%
13
 
7.5%
10
 
5.8%
9
 
5.2%
9
 
5.2%
9
 
5.2%
8
 
4.6%
7
 
4.0%
7
 
4.0%
Other values (35) 65
37.6%
Latin
ValueCountFrequency (%)
g 300
31.7%
I 269
28.4%
171
18.1%
V 138
14.6%
l 22
 
2.3%
M 12
 
1.3%
v 5
 
0.5%
i 4
 
0.4%
3
 
0.3%
D 3
 
0.3%
Other values (15) 20
 
2.1%
Common
ValueCountFrequency (%)
0 356
17.0%
. 324
15.5%
- 301
14.4%
1 300
14.3%
9 198
9.5%
2 192
9.2%
75
 
3.6%
4 63
 
3.0%
7 61
 
2.9%
8 56
 
2.7%
Other values (10) 168
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2865
89.1%
Number Forms 176
 
5.5%
Hangul 173
 
5.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 356
12.4%
. 324
11.3%
- 301
10.5%
1 300
10.5%
g 300
10.5%
I 269
9.4%
9 198
6.9%
2 192
6.7%
V 138
 
4.8%
75
 
2.6%
Other values (31) 412
14.4%
Number Forms
ValueCountFrequency (%)
171
97.2%
3
 
1.7%
1
 
0.6%
1
 
0.6%
Hangul
ValueCountFrequency (%)
18
 
10.4%
18
 
10.4%
13
 
7.5%
10
 
5.8%
9
 
5.2%
9
 
5.2%
9
 
5.2%
8
 
4.6%
7
 
4.0%
7
 
4.0%
Other values (35) 65
37.6%

위도
Real number (ℝ)

Distinct8728
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.238918
Minimum35.156332
Maximum35.327138
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:31.625768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.156332
5-th percentile35.178077
Q135.22091
median35.235107
Q335.253621
95-th percentile35.308797
Maximum35.327138
Range0.17080646
Interquartile range (IQR)0.032710827

Descriptive statistics

Standard deviation0.036380535
Coefficient of variation (CV)0.0010323965
Kurtosis-0.16980182
Mean35.238918
Median Absolute Deviation (MAD)0.016577055
Skewness0.37485021
Sum352389.18
Variance0.0013235433
MonotonicityNot monotonic
2023-12-12T15:06:31.786954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.17891261 61
 
0.6%
35.18959136 18
 
0.2%
35.2263586 16
 
0.2%
35.21800727 16
 
0.2%
35.22689899 15
 
0.1%
35.23677849 14
 
0.1%
35.251633 13
 
0.1%
35.31012968 12
 
0.1%
35.30732755 10
 
0.1%
35.254847 10
 
0.1%
Other values (8718) 9815
98.2%
ValueCountFrequency (%)
35.15633158 8
0.1%
35.16228717 1
 
< 0.1%
35.16316868 3
 
< 0.1%
35.16370065 8
0.1%
35.16481319 1
 
< 0.1%
35.16506123 2
 
< 0.1%
35.16556122 1
 
< 0.1%
35.16645311 8
0.1%
35.16652324 1
 
< 0.1%
35.1667939 1
 
< 0.1%
ValueCountFrequency (%)
35.32713804 3
< 0.1%
35.32697415 1
 
< 0.1%
35.32527357 1
 
< 0.1%
35.32518331 1
 
< 0.1%
35.32518192 1
 
< 0.1%
35.32517486 1
 
< 0.1%
35.32514973 1
 
< 0.1%
35.3249926 1
 
< 0.1%
35.32494229 1
 
< 0.1%
35.32486803 1
 
< 0.1%

경도
Real number (ℝ)

Distinct8711
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.83693
Minimum128.70585
Maximum128.93054
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:06:31.945808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.70585
5-th percentile128.72764
Q1128.80469
median128.85155
Q3128.88162
95-th percentile128.91375
Maximum128.93054
Range0.2246862
Interquartile range (IQR)0.076933625

Descriptive statistics

Standard deviation0.057974467
Coefficient of variation (CV)0.0004499833
Kurtosis-0.70172862
Mean128.83693
Median Absolute Deviation (MAD)0.0374589
Skewness-0.57157952
Sum1288369.3
Variance0.0033610388
MonotonicityNot monotonic
2023-12-12T15:06:32.082242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8285602 61
 
0.6%
128.8433276 18
 
0.2%
128.8486299 16
 
0.2%
128.8594501 16
 
0.2%
128.8937084 15
 
0.1%
128.825249 14
 
0.1%
128.8937494 13
 
0.1%
128.7203496 12
 
0.1%
128.8366542 10
 
0.1%
128.8720923 10
 
0.1%
Other values (8701) 9815
98.2%
ValueCountFrequency (%)
128.7058502 1
< 0.1%
128.705852 1
< 0.1%
128.7061557 1
< 0.1%
128.7065176 2
< 0.1%
128.7066123 1
< 0.1%
128.706738 1
< 0.1%
128.7068123 1
< 0.1%
128.7068988 1
< 0.1%
128.70708 1
< 0.1%
128.7073054 1
< 0.1%
ValueCountFrequency (%)
128.9305364 1
< 0.1%
128.9304827 1
< 0.1%
128.9303307 1
< 0.1%
128.929974 1
< 0.1%
128.9299565 2
< 0.1%
128.9297442 1
< 0.1%
128.9296942 1
< 0.1%
128.9296119 1
< 0.1%
128.9295942 1
< 0.1%
128.9292988 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
69176918경상남도 김해시 외동 743번지7430경상남도 김해시 금관대로 123948250-102070162일반일반건축물<NA><NA><NA><NA>04830000000001090201239<NA><NA>1부속건축물0.00.00.072.00.00.032경량철골구조경량철골구조10000교육연구시설교육연구시설90기타지붕샌드위치판넬000.0000000.072.000.000.000.000.0<NA><NA><NA><NA><NA><NA><NA><NA>02019-01-260<NA>35.237237128.855269
97659766경상남도 김해시 삼정동 70-3번지703경상남도 김해시 분성로 45848250-31063일반일반건축물<NA><NA><NA><NA>0483000000000117050458<NA><NA>0주건축물632.8268.7242.47376.28376.2859.4611벽돌구조철근콘크리트조/벽돌조/철골조4000제2종근린생활시설제2종근린생활시설/단독주택10(철근)콘크리트슬라브/샌드위치판넬015.9200000.0376.2800.000.000.0223.0<NA><NA>1989-01-07<NA><NA><NA><NA><NA>02017-11-18<NA><NA>35.234859128.896048
58825883경상남도 김해시 내동 산 2번지20경상남도 김해시 분성로3번길 235-248250-8039일반일반건축물한국전기통신공사 연수원<NA><NA><NA>04830000000001080102352기숙사0주건축물91.4342590.962.8314446.59709.010.6221철근콘크리트구조철근콘크리트 라멘조10000교육연구시설교육연구시설10(철근)콘크리트경사슬라브0021.25410200.014446.500.000.0923825.700.01990-06-041990-10-101994-08-09<NA><NA><NA><NA><NA>02017-02-21<NA><NA>35.250015128.860821
1485014851경상남도 김해시 무계동 492-1번지492148250-50273일반일반건축물<NA><NA><NA><NA>04830000000001280104411<NA>0주건축물0.065.470.065.4765.470.012블록구조블럭조18000창고시설창고30슬레이트스레이트000.0100000.065.4700.000.000.000.0<NA><NA>1970-12-20<NA><NA><NA><NA><NA>02013-09-27<NA><NA>35.19767128.811411
77387739경상남도 김해시 명법동 629-8번지6298경상남도 김해시 금관대로804번길 7248250-102063148일반일반건축물<NA><NA><NA><NA>0483000000000112010720<NA>0주건축물1196.0237.6219.87475.24475.2439.7431일반철골구조일반철골구조3000제1종근린생활시설제1종근린생활시설90기타지붕판넬0010.77200000.0475.2400.000.000.0223.02012-06-132012-10-062013-02-0520125350178허가민원과1101신축허가02020-07-080<NA>35.200273128.836838
1965219653경상남도 김해시 진영읍 진영리 343-46번지34346경상남도 김해시 진영읍 진영로 72-348250-102085765집합표제부하모니빌-2<NA><NA><NA>0483000000000250010723<NA>0주건축물1153.0256.058422.211834.24451834.2445159.0821철근콘크리트구조철근콘크리트구조2000공동주택공동주택10(철근)콘크리트(철근)콘크리트18027.351001000.01834.244500.000.000.018218.52012-08-222012-12-032014-04-1820125350178허가민원과1101신축허가02019-05-301<NA>35.303894128.721537
1838818389경상남도 김해시 진영읍 좌곤리 25-3번지253경상남도 김해시 진영읍 김해대로 170-1048250-25234일반일반건축물<NA><NA><NA><NA>048300000000025012017010<NA>0주건축물0.0115.740.0153.06153.060.021철근콘크리트구조블록조/철근콘크리트조1000단독주택단독주택10(철근)콘크리트스레이트/슬라브010.0200000.0153.0600.000.000.000.0<NA><NA>1983-04-29<NA><NA><NA><NA><NA>02012-05-30<NA><NA>35.302416128.710902
1779617797경상남도 김해시 응달동 9190번지9190048250-21245일반일반건축물<NA><NA><NA><NA>0<NA><NA>0<NA><NA><NA>0주건축물0.0120.720.0120.72120.720.012블록구조블럭조1000단독주택주택20기와기와010.0100000.0120.7200.000.000.000.01989-08-15<NA><NA><NA><NA><NA><NA><NA>02013-09-27<NA><NA>35.177045128.843198
2283222833경상남도 김해시 주촌면 덕암리 200번지2000경상남도 김해시 주촌면 서부로1701번길 300-648250-43935일반일반건축물<NA><NA><NA><NA>04830000000003200103006<NA>0주건축물843.064.067.664.0664.067.651일반목구조목조1000단독주택단독주택90기타지붕시멘트기와010.01000132.0332.0300.000.000.000.0<NA><NA>1938-12-20<NA><NA><NA><NA><NA>02020-01-230<NA>35.258687128.821933
1260312604경상남도 김해시 안동 402-23번지40223경상남도 김해시 김해대로2579번길 76-2048250-102069321일반일반건축물<NA><NA><NA><NA>04830000000001200107620<NA>0주건축물329.0213.6464.94423.68423.68128.7831일반철골구조일반철골구조17000공장공장90기타지붕판넬0010.8200000.0423.6800.000.000.0111.52010-08-092013-05-172013-07-0920105350178허가민원과1201신축신고02018-06-280<NA>35.235257128.910313
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
50615062경상남도 김해시 내동 1109-4번지11094경상남도 김해시 우암로63번길 848250-102110428일반일반건축물<NA><NA><NA><NA>048300000000010801080<NA>0주건축물295.0175.6859.55480.12480.12162.7521철근콘크리트구조철근콘크리트구조1000단독주택단독주택(8가구),제1종근린생활시설10(철근)콘크리트(철근)콘크리트0812.0300000.0480.1200.000.000.0892.02015-06-102015-06-132015-11-1020155350178허가민원과1101신축허가02019-05-301<NA>35.236705128.860406
1992819929경상남도 김해시 진영읍 진영리 787번지7870경상남도 김해시 진영읍 진산대로 229-248250-102108210일반일반건축물<NA><NA><NA><NA>04830000000002500102292<NA>0주건축물1622.0646.839.881284.01284.079.1631일반철골구조일반철골구조3000제1종근린생활시설제1종근린생활시설, 제2종근린생활시설90기타지붕불연판넬위 아스팔트싱글0010.02200000.01284.000.000.000.09103.52015-01-232015-03-122015-09-2420155350178허가민원과1101신축허가02020-04-161<NA>35.323318128.718674
94119412경상남도 김해시 삼정동 602-1번지6021경상남도 김해시 김해대로2471번길 2248250-44956집합표제부화목파크빌라<NA><NA><NA>048300000000011701022<NA>B동0주건축물368.3207.8256.43657.2657.2178.4421철근콘크리트구조철근콘크리트조2000공동주택공동주택(다세대)10(철근)콘크리트슬라브8012.7400000.0657.200.000.000.0669.01996-03-081996-03-141996-09-06<NA><NA><NA><NA><NA>02020-03-030<NA>35.229875128.897223
26472648경상남도 김해시 대성동 126번지126048250-21363일반일반건축물<NA><NA><NA><NA>0<NA><NA>0<NA><NA><NA>0주건축물0.028.860.028.8628.860.051일반목구조목조1000단독주택단독주택20기와기와010.0100000.028.8600.000.000.000.0<NA><NA><NA><NA><NA><NA><NA><NA>02020-04-270<NA>35.238184128.877726
2160221603경상남도 김해시 진영읍 내룡리 314-3번지3143경상남도 김해시 진영읍 진영로454번길 97-2948250-102095825일반일반건축물<NA><NA><NA><NA>14830000000002500109729<NA>0주건축물1430.0483.5733.82483.57483.5733.8231일반철골구조일반철골구조4000제2종근린생활시설제2종근린생활시설90기타지붕난연판넬0011.68100000.0483.5700.000.000.0334.52014-08-262014-09-112014-12-2320145350178허가민원과1101신축허가02017-02-09<NA><NA>35.292899128.755027
1051610517경상남도 김해시 어방동 44-20번지4420경상남도 김해시 김해대로2575번길 3348250-102048885일반일반건축물<NA><NA><NA><NA>048300000000011801033<NA>C동1부속건축물0.022.410.022.4122.410.021철근콘크리트구조철골조17000공장공장90기타지붕샌드위치판넬000.0100000.022.4100.000.000.020230.01992-09-211992-10-271993-03-12<NA><NA><NA><NA><NA>02020-04-270<NA>35.231457128.908622
49364937경상남도 김해시 내동 1091-1번지10911경상남도 김해시 금관대로 130848250-31733일반일반건축물<NA><NA><NA><NA>048300000000010801013080<NA>0주건축물196.6116.959.46340.88340.88173.3821철근콘크리트구조철근콘크리트조/조적조1000단독주택근린생활시설/단독주택10(철근)콘크리트슬라브0311.1300011.2340.8800.000.000.0223.01997-06-20<NA>1997-10-29<NA><NA><NA><NA><NA>02017-05-31<NA><NA>35.240449128.862412
1587915880경상남도 김해시 대청동 276-5번지2765경상남도 김해시 계동로129번길 42-1248250-102062518일반일반건축물<NA><NA><NA><NA>04830000000001290204212<NA>0주건축물200.5119.8859.79336.89336.89168.0221철근콘크리트구조철근콘크리트구조1000단독주택단독주택 및 제2종근린생활시설10(철근)콘크리트슬라브0411.0300000.0336.8900.000.000.0446.52012-09-042012-09-082013-01-1420125350154도시관리과1101신축허가02019-05-301<NA>35.189969128.794282
1381213813경상남도 김해시 내덕동 219-8번지2198경상남도 김해시 금관대로599번길 2448250-26267일반일반건축물<NA><NA><NA><NA>0483000000000124020240<NA>0주건축물239.6142.9259.65423.08423.08176.5811벽돌구조철근콘크리트구조/벽돌조1000단독주택단독주택/2종 근린생활시설10(철근)콘크리트(철근)콘크리트0311.2300000.0423.0800.000.000.0223.02002-09-112002-09-122003-01-0920025350093허가민원과1101신축허가02018-10-030<NA>35.20415128.8142
81518152경상남도 김해시 화목동 147-19번지1471948250-24140일반일반건축물<NA><NA><NA><NA>04830000000001140107413A,B동0주건축물93.067.2572.367.2567.2572.351일반목구조목조1000단독주택단독주택30슬레이트스레이트010.01000133.2167.2500.000.000.000.0<NA><NA>1947-12-20<NA><NA><NA><NA><NA>02020-08-120<NA>35.197901128.862653