Overview

Dataset statistics

Number of variables29
Number of observations5502
Missing cells20354
Missing cells (%)12.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory244.0 B

Variable types

Text7
Numeric12
Categorical10

Alerts

MAIN_ATACH_BULD_CLSF_CD is highly imbalanced (62.7%)Imbalance
BF_BULD_MUSES_NM is highly imbalanced (75.2%)Imbalance
BULD_STRU_NM is highly imbalanced (50.2%)Imbalance
BF_BULD_STRU_NM is highly imbalanced (72.1%)Imbalance
CLSG_ERSR_CLSF_NM is highly imbalanced (56.5%)Imbalance
CLSG_ERSR_ATACH_BULD_CNT is highly imbalanced (95.3%)Imbalance
NWCC_BILD_INFO_RN_ADRES_CD has 295 (5.4%) missing valuesMissing
RN has 293 (5.3%) missing valuesMissing
PRPOS_DISTRICT_NM has 4803 (87.3%) missing valuesMissing
PRPOS_AREA_NM has 3578 (65.0%) missing valuesMissing
BULD_NM has 4580 (83.2%) missing valuesMissing
DONG_NM has 2027 (36.8%) missing valuesMissing
CLSG_ERSR_YMD has 4519 (82.1%) missing valuesMissing
BILDNG_STWRK_YMD has 259 (4.7%) missing valuesMissing
PLOT_DIMS is highly skewed (γ1 = 23.42182678)Skewed
GRFA is highly skewed (γ1 = 29.98282791)Skewed
BF_GRFA is highly skewed (γ1 = 51.89302327)Skewed
BDRG_INNB has unique valuesUnique
PLOT_DIMS has 1091 (19.8%) zerosZeros
BULD_AREA has 65 (1.2%) zerosZeros
BF_BULD_DIMS has 4605 (83.7%) zerosZeros
BF_GRFA has 4521 (82.2%) zerosZeros
CLSG_ERSR_MAIN_BULD_CNT has 4516 (82.1%) zerosZeros

Reproduction

Analysis started2023-12-11 22:30:56.935254
Analysis finished2023-12-11 22:30:58.442750
Duration1.51 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

BDRG_INNB
Text

UNIQUE 

Distinct5502
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size43.1 KiB
2023-12-12T07:30:58.566124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length28
Mean length27.997637
Min length15

Characters and Unicode

Total characters154043
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

Unique5502 ?
Unique (%)100.0%

Sample

1st row11110-1000000000000002080313
2nd row11110-1000000000000002080423
3rd row11110-1000000000000002071344
4th row11110-1000000000000002071815
5th row11110-1000000000000002071816
ValueCountFrequency (%)
11110-1000000000000002080313 1
 
< 0.1%
46790-1000000000000002050507 1
 
< 0.1%
46800-1000000000000002090865 1
 
< 0.1%
46790-1000000000000002069710 1
 
< 0.1%
46790-1000000000000002029622 1
 
< 0.1%
46790-1000000000000002029621 1
 
< 0.1%
46790-1000000000000002092681 1
 
< 0.1%
46790-1000000000000002091701 1
 
< 0.1%
46790-1000000000000001994193 1
 
< 0.1%
46780-1000000000000002109307 1
 
< 0.1%
Other values (5492) 5492
99.8%
2023-12-12T07:30:58.841351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 88323
57.3%
1 16103
 
10.5%
2 10475
 
6.8%
4 7780
 
5.1%
- 5502
 
3.6%
7 5014
 
3.3%
5 4525
 
2.9%
3 4518
 
2.9%
6 4382
 
2.8%
8 4325
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 148541
96.4%
Dash Punctuation 5502
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 88323
59.5%
1 16103
 
10.8%
2 10475
 
7.1%
4 7780
 
5.2%
7 5014
 
3.4%
5 4525
 
3.0%
3 4518
 
3.0%
6 4382
 
3.0%
8 4325
 
2.9%
9 3096
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 5502
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 154043
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 88323
57.3%
1 16103
 
10.5%
2 10475
 
6.8%
4 7780
 
5.1%
- 5502
 
3.6%
7 5014
 
3.3%
5 4525
 
2.9%
3 4518
 
2.9%
6 4382
 
2.8%
8 4325
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 154043
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 88323
57.3%
1 16103
 
10.5%
2 10475
 
6.8%
4 7780
 
5.1%
- 5502
 
3.6%
7 5014
 
3.3%
5 4525
 
2.9%
3 4518
 
2.9%
6 4382
 
2.8%
8 4325
 
2.8%

PNU
Real number (ℝ)

Distinct4139
Distinct (%)75.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2854025 × 1018
Minimum1.1110159 × 1018
Maximum5.183035 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.5 KiB
2023-12-12T07:30:58.959062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.1110159 × 1018
5-th percentile2.7260111 × 1018
Q14.150037 × 1018
median4.418032 × 1018
Q34.7250345 × 1018
95-th percentile5.172025 × 1018
Maximum5.183035 × 1018
Range4.0720191 × 1018
Interquartile range (IQR)5.7499751 × 1017

Descriptive statistics

Standard deviation7.9345845 × 1017
Coefficient of variation (CV)0.18515377
Kurtosis5.8438414
Mean4.2854025 × 1018
Median Absolute Deviation (MAD)2.7190655 × 1017
Skewness-2.2360968
Sum3.3456497 × 1018
Variance6.2957631 × 1035
MonotonicityIncreasing
2023-12-12T07:30:59.070830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4889032025005050000 31
 
0.6%
4150025329003760000 23
 
0.4%
5113039023006930005 19
 
0.3%
4413134022000720006 16
 
0.3%
4311425028006340000 14
 
0.3%
4481025326012570000 13
 
0.2%
4613014100013760000 11
 
0.2%
4415025034002350000 11
 
0.2%
4165038023006350000 11
 
0.2%
4413137026003930000 10
 
0.2%
Other values (4129) 5343
97.1%
ValueCountFrequency (%)
1111015900000660060 1
< 0.1%
1111015900000660067 1
< 0.1%
1111016700001080000 1
< 0.1%
1111018300000920005 2
< 0.1%
1111018700000461901 1
< 0.1%
1114013700000030005 1
< 0.1%
1114014300000490008 1
< 0.1%
1114016200002510130 1
< 0.1%
1114016200003720003 1
< 0.1%
1114017100004960000 1
< 0.1%
ValueCountFrequency (%)
5183035037001440001 9
0.2%
5183035036009590005 1
 
< 0.1%
5183035036004770002 1
 
< 0.1%
5183035036002410002 1
 
< 0.1%
5183035030000470001 1
 
< 0.1%
5183035021003620001 1
 
< 0.1%
5183034036000620029 1
 
< 0.1%
5183034034000910001 1
 
< 0.1%
5183034033000710006 5
0.1%
5183034031002620004 1
 
< 0.1%

LNNO_ADRES
Text

Distinct4139
Distinct (%)75.2%
Missing0
Missing (%)0.0%
Memory size43.1 KiB
2023-12-12T07:30:59.370782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length23.351509
Min length15

Characters and Unicode

Total characters128480
Distinct characters357
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

Unique3371 ?
Unique (%)61.3%

Sample

1st row서울특별시 종로구 원남동 66-60번지
2nd row서울특별시 종로구 원남동 66-67번지
3rd row서울특별시 종로구 충신동 108번지
4th row서울특별시 종로구 평창동 92-5번지
5th row서울특별시 종로구 평창동 92-5번지
ValueCountFrequency (%)
경기도 1621
 
6.1%
경상북도 524
 
2.0%
충청남도 506
 
1.9%
강원특별자치도 476
 
1.8%
전라남도 441
 
1.7%
경상남도 426
 
1.6%
충청북도 373
 
1.4%
전라북도 283
 
1.1%
제주특별자치도 223
 
0.8%
서울특별시 174
 
0.7%
Other values (7127) 21671
81.1%
2023-12-12T07:30:59.786850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21234
 
16.5%
지 5739
 
4.5%
번 5504
 
4.3%
도 5210
 
4.1%
1 4183
 
3.3%
리 4152
 
3.2%
- 4044
 
3.1%
시 3827
 
3.0%
면 2994
 
2.3%
2 2943
 
2.3%
Other values (347) 68650
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81312
63.3%
Decimal Number 21890
 
17.0%
Space Separator 21234
 
16.5%
Dash Punctuation 4044
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 5739
 
7.1%
번 5504
 
6.8%
도 5210
 
6.4%
리 4152
 
5.1%
시 3827
 
4.7%
면 2994
 
3.7%
경 2729
 
3.4%
남 2107
 
2.6%
동 2062
 
2.5%
군 1953
 
2.4%
Other values (335) 45035
55.4%
Decimal Number
ValueCountFrequency (%)
1 4183
19.1%
2 2943
13.4%
3 2480
11.3%
4 2255
10.3%
5 2015
9.2%
6 1816
8.3%
7 1658
 
7.6%
0 1557
 
7.1%
8 1514
 
6.9%
9 1469
 
6.7%
Space Separator
ValueCountFrequency (%)
21234
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4044
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81312
63.3%
Common 47168
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 5739
 
7.1%
번 5504
 
6.8%
도 5210
 
6.4%
리 4152
 
5.1%
시 3827
 
4.7%
면 2994
 
3.7%
경 2729
 
3.4%
남 2107
 
2.6%
동 2062
 
2.5%
군 1953
 
2.4%
Other values (335) 45035
55.4%
Common
ValueCountFrequency (%)
21234
45.0%
1 4183
 
8.9%
- 4044
 
8.6%
2 2943
 
6.2%
3 2480
 
5.3%
4 2255
 
4.8%
5 2015
 
4.3%
6 1816
 
3.9%
7 1658
 
3.5%
0 1557
 
3.3%
Other values (2) 2983
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81312
63.3%
ASCII 47168
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21234
45.0%
1 4183
 
8.9%
- 4044
 
8.6%
2 2943
 
6.2%
3 2480
 
5.3%
4 2255
 
4.8%
5 2015
 
4.3%
6 1816
 
3.9%
7 1658
 
3.5%
0 1557
 
3.3%
Other values (2) 2983
 
6.3%
Hangul
ValueCountFrequency (%)
지 5739
 
7.1%
번 5504
 
6.8%
도 5210
 
6.4%
리 4152
 
5.1%
시 3827
 
4.7%
면 2994
 
3.7%
경 2729
 
3.4%
남 2107
 
2.6%
동 2062
 
2.5%
군 1953
 
2.4%
Other values (335) 45035
55.4%

NWCC_BILD_INFO_RN_ADRES_CD
Real number (ℝ)

MISSING 

Distinct3443
Distinct (%)66.1%
Missing295
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean4.2689542 × 1027
Minimum1.111041 × 1027
Maximum5.1830486 × 1027
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.5 KiB
2023-12-12T07:30:59.898847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111041 × 1027
5-th percentile2.7230424 × 1027
Q14.1500335 × 1027
median4.4133225 × 1027
Q34.7230402 × 1027
95-th percentile5.1230447 × 1027
Maximum5.1830486 × 1027
Range4.0720076 × 1027
Interquartile range (IQR)5.7300668 × 1026

Descriptive statistics

Standard deviation8.0320807 × 1026
Coefficient of variation (CV)0.18815102
Kurtosis5.5924402
Mean4.2689542 × 1027
Median Absolute Deviation (MAD)2.7227849 × 1026
Skewness-2.1953685
Sum2.2228444 × 1031
Variance6.4514321 × 1053
MonotonicityNot monotonic
2023-12-12T07:31:00.035086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.91404853182132e+27 33
 
0.6%
4.15003351932253e+27 23
 
0.4%
4.13604391401256e+27 21
 
0.4%
5.1130445735239e+27 19
 
0.3%
4.376045384824e+27 17
 
0.3%
4.4131454729634e+27 16
 
0.3%
4.3114452030625e+27 14
 
0.3%
5.0130485073525e+27 14
 
0.3%
4.4810301509225294e+27 13
 
0.2%
4.12853193004101e+27 13
 
0.2%
Other values (3433) 5024
91.3%
(Missing) 295
 
5.4%
ValueCountFrequency (%)
1.1110410022016702e+27 1
< 0.1%
1.11104100406159e+27 2
< 0.1%
1.11104100483187e+27 1
< 0.1%
1.11104100500183e+27 2
< 0.1%
1.1140310102317102e+27 1
< 0.1%
1.11404103028162e+27 1
< 0.1%
1.11404103269143e+27 1
< 0.1%
1.11404103335137e+27 1
< 0.1%
1.11404103375162e+27 1
< 0.1%
1.11704106082108e+27 1
< 0.1%
ValueCountFrequency (%)
5.1830486176835e+27 1
 
< 0.1%
5.1830485926635e+27 1
 
< 0.1%
5.1830450521533e+27 1
 
< 0.1%
5.1830450521425e+27 1
 
< 0.1%
5.1830450519535e+27 1
 
< 0.1%
5.1830450519434e+27 1
 
< 0.1%
5.1830450518335e+27 1
 
< 0.1%
5.1830450517932e+27 1
 
< 0.1%
5.1830450517034e+27 5
0.1%
5.1830450516234e+27 1
 
< 0.1%

RN
Text

MISSING 

Distinct4078
Distinct (%)78.3%
Missing293
Missing (%)5.3%
Memory size43.1 KiB
2023-12-12T07:31:00.313298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length30
Mean length22.166443
Min length13

Characters and Unicode

Total characters115465
Distinct characters493
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

Unique3403 ?
Unique (%)65.3%

Sample

1st row서울특별시 종로구 창경궁로18길 20
2nd row서울특별시 종로구 창경궁로18길 20
3rd row서울특별시 종로구 율곡로16길 32
4th row서울특별시 종로구 평창25길 22
5th row서울특별시 종로구 평창25길 22
ValueCountFrequency (%)
경기도 1576
 
6.2%
충청남도 477
 
1.9%
경상북도 462
 
1.8%
강원특별자치도 451
 
1.8%
전라남도 396
 
1.6%
경상남도 368
 
1.5%
충청북도 363
 
1.4%
전라북도 265
 
1.1%
제주특별자치도 222
 
0.9%
서울특별시 172
 
0.7%
Other values (6856) 20486
81.2%
2023-12-12T07:31:00.685705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20047
 
17.4%
도 4940
 
4.3%
1 4415
 
3.8%
시 3706
 
3.2%
길 3545
 
3.1%
로 2971
 
2.6%
2 2915
 
2.5%
면 2785
 
2.4%
- 2762
 
2.4%
경 2626
 
2.3%
Other values (483) 64753
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71695
62.1%
Decimal Number 20961
 
18.2%
Space Separator 20047
 
17.4%
Dash Punctuation 2762
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 4940
 
6.9%
시 3706
 
5.2%
길 3545
 
4.9%
로 2971
 
4.1%
면 2785
 
3.9%
경 2626
 
3.7%
남 2001
 
2.8%
군 1814
 
2.5%
기 1698
 
2.4%
주 1497
 
2.1%
Other values (471) 44112
61.5%
Decimal Number
ValueCountFrequency (%)
1 4415
21.1%
2 2915
13.9%
3 2284
10.9%
4 2050
9.8%
5 1849
8.8%
7 1705
 
8.1%
6 1678
 
8.0%
9 1368
 
6.5%
8 1366
 
6.5%
0 1331
 
6.3%
Space Separator
ValueCountFrequency (%)
20047
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2762
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71695
62.1%
Common 43770
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 4940
 
6.9%
시 3706
 
5.2%
길 3545
 
4.9%
로 2971
 
4.1%
면 2785
 
3.9%
경 2626
 
3.7%
남 2001
 
2.8%
군 1814
 
2.5%
기 1698
 
2.4%
주 1497
 
2.1%
Other values (471) 44112
61.5%
Common
ValueCountFrequency (%)
20047
45.8%
1 4415
 
10.1%
2 2915
 
6.7%
- 2762
 
6.3%
3 2284
 
5.2%
4 2050
 
4.7%
5 1849
 
4.2%
7 1705
 
3.9%
6 1678
 
3.8%
9 1368
 
3.1%
Other values (2) 2697
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71695
62.1%
ASCII 43770
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20047
45.8%
1 4415
 
10.1%
2 2915
 
6.7%
- 2762
 
6.3%
3 2284
 
5.2%
4 2050
 
4.7%
5 1849
 
4.2%
7 1705
 
3.9%
6 1678
 
3.8%
9 1368
 
3.1%
Other values (2) 2697
 
6.2%
Hangul
ValueCountFrequency (%)
도 4940
 
6.9%
시 3706
 
5.2%
길 3545
 
4.9%
로 2971
 
4.1%
면 2785
 
3.9%
경 2626
 
3.7%
남 2001
 
2.8%
군 1814
 
2.5%
기 1698
 
2.4%
주 1497
 
2.1%
Other values (471) 44112
61.5%

LNDCGR_NM
Categorical

Distinct24
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size43.1 KiB
대
1725 
전
1123 
답
993 
임야
653 
<NA>
461 
Other values (19)
547 

Length

Max length5
Median length1
Mean length1.6150491
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
대 1725
31.4%
전 1123
20.4%
답 993
18.0%
임야 653
 
11.9%
<NA> 461
 
8.4%
공장용지 163
 
3.0%
잡종지 154
 
2.8%
과수원 74
 
1.3%
목장용지 35
 
0.6%
창고용지 29
 
0.5%
Other values (14) 92
 
1.7%

Length

2023-12-12T07:31:00.799421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대 1725
31.4%
전 1123
20.4%
답 993
18.0%
임야 653
 
11.9%
na 461
 
8.4%
공장용지 163
 
3.0%
잡종지 154
 
2.8%
과수원 74
 
1.3%
목장용지 35
 
0.6%
창고용지 29
 
0.5%
Other values (14) 92
 
1.7%

SUSAR_NM
Categorical

Distinct33
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size43.1 KiB
계획관리지역
1385 
<NA>
1337 
자연녹지지역
439 
생산관리지역
343 
보전관리지역
338 
Other values (28)
1660 

Length

Max length13
Median length10
Mean length5.6815703
Min length4

Unique

Unique6 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
계획관리지역 1385
25.2%
<NA> 1337
24.3%
자연녹지지역 439
 
8.0%
생산관리지역 343
 
6.2%
보전관리지역 338
 
6.1%
도시지역 326
 
5.9%
제1종일반주거지역 293
 
5.3%
제2종일반주거지역 289
 
5.3%
농림지역 254
 
4.6%
가축사육제한구역 108
 
2.0%
Other values (23) 390
 
7.1%

Length

2023-12-12T07:31:00.898056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계획관리지역 1385
25.2%
na 1337
24.3%
자연녹지지역 439
 
8.0%
생산관리지역 343
 
6.2%
보전관리지역 338
 
6.1%
도시지역 326
 
5.9%
제1종일반주거지역 293
 
5.3%
제2종일반주거지역 289
 
5.3%
농림지역 254
 
4.6%
가축사육제한구역 108
 
2.0%
Other values (23) 390
 
7.1%

PRPOS_DISTRICT_NM
Text

MISSING 

Distinct69
Distinct (%)9.9%
Missing4803
Missing (%)87.3%
Memory size43.1 KiB
2023-12-12T07:31:01.048703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.4263233
Min length3

Characters and Unicode

Total characters5191
Distinct characters117
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)3.7%

Sample

1st row자연경관지구
2nd row방화지구
3rd row최고고도지구
4th row대공방어협조구역
5th row자연경관지구
ValueCountFrequency (%)
자연취락지구 263
37.6%
비행안전제6구역(전술 63
 
9.0%
고도지구 50
 
7.2%
방화지구 38
 
5.4%
주거개발진흥지구 30
 
4.3%
대공방어협조구역 30
 
4.3%
시가지경관지구(일반 29
 
4.1%
비행안전제5구역(전술 15
 
2.1%
비행안전제2구역(전술 12
 
1.7%
경제자유구역 10
 
1.4%
Other values (59) 159
22.7%
2023-12-12T07:31:01.319247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 695
 
13.4%
지 607
 
11.7%
자 287
 
5.5%
연 275
 
5.3%
취 273
 
5.3%
락 273
 
5.3%
전 217
 
4.2%
역 170
 
3.3%
) 139
 
2.7%
( 139
 
2.7%
Other values (107) 2116
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4799
92.4%
Close Punctuation 139
 
2.7%
Open Punctuation 139
 
2.7%
Decimal Number 114
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 695
 
14.5%
지 607
 
12.6%
자 287
 
6.0%
연 275
 
5.7%
취 273
 
5.7%
락 273
 
5.7%
전 217
 
4.5%
역 170
 
3.5%
제 123
 
2.6%
비 110
 
2.3%
Other values (100) 1769
36.9%
Decimal Number
ValueCountFrequency (%)
6 63
55.3%
5 18
 
15.8%
2 16
 
14.0%
3 10
 
8.8%
4 7
 
6.1%
Close Punctuation
ValueCountFrequency (%)
) 139
100.0%
Open Punctuation
ValueCountFrequency (%)
( 139
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4799
92.4%
Common 392
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 695
 
14.5%
지 607
 
12.6%
자 287
 
6.0%
연 275
 
5.7%
취 273
 
5.7%
락 273
 
5.7%
전 217
 
4.5%
역 170
 
3.5%
제 123
 
2.6%
비 110
 
2.3%
Other values (100) 1769
36.9%
Common
ValueCountFrequency (%)
) 139
35.5%
( 139
35.5%
6 63
16.1%
5 18
 
4.6%
2 16
 
4.1%
3 10
 
2.6%
4 7
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4798
92.4%
ASCII 392
 
7.6%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 695
 
14.5%
지 607
 
12.7%
자 287
 
6.0%
연 275
 
5.7%
취 273
 
5.7%
락 273
 
5.7%
전 217
 
4.5%
역 170
 
3.5%
제 123
 
2.6%
비 110
 
2.3%
Other values (99) 1768
36.8%
ASCII
ValueCountFrequency (%)
) 139
35.5%
( 139
35.5%
6 63
16.1%
5 18
 
4.6%
2 16
 
4.1%
3 10
 
2.6%
4 7
 
1.8%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

PRPOS_AREA_NM
Text

MISSING 

Distinct66
Distinct (%)3.4%
Missing3578
Missing (%)65.0%
Memory size43.1 KiB
2023-12-12T07:31:01.490512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length8
Mean length7.9334719
Min length2

Characters and Unicode

Total characters15264
Distinct characters122
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)0.9%

Sample

1st row중점경관관리구역
2nd row중점경관관리구역
3rd row지구단위계획구역
4th row중점경관관리구역
5th row가축사육제한구역
ValueCountFrequency (%)
가축사육제한구역 781
39.5%
지구단위계획구역 292
 
14.8%
상대보호구역 146
 
7.4%
제1종지구단위계획구역 101
 
5.1%
성장관리계획구역 96
 
4.9%
농업진흥구역 51
 
2.6%
중점경관관리구역 47
 
2.4%
토지거래계약에관한허가구역 35
 
1.8%
하수처리구역 31
 
1.6%
수산자원보호구역 27
 
1.4%
Other values (60) 369
18.7%
2023-12-12T07:31:01.763889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 2288
15.0%
역 1893
 
12.4%
제 928
 
6.1%
한 859
 
5.6%
가 833
 
5.5%
사 794
 
5.2%
축 786
 
5.1%
육 785
 
5.1%
계 551
 
3.6%
획 516
 
3.4%
Other values (112) 5031
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15085
98.8%
Decimal Number 125
 
0.8%
Space Separator 52
 
0.3%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2288
15.2%
역 1893
 
12.5%
제 928
 
6.2%
한 859
 
5.7%
가 833
 
5.5%
사 794
 
5.3%
축 786
 
5.2%
육 785
 
5.2%
계 551
 
3.7%
획 516
 
3.4%
Other values (106) 4852
32.2%
Decimal Number
ValueCountFrequency (%)
1 102
81.6%
2 17
 
13.6%
3 6
 
4.8%
Space Separator
ValueCountFrequency (%)
52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15085
98.8%
Common 179
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2288
15.2%
역 1893
 
12.5%
제 928
 
6.2%
한 859
 
5.7%
가 833
 
5.5%
사 794
 
5.3%
축 786
 
5.2%
육 785
 
5.2%
계 551
 
3.7%
획 516
 
3.4%
Other values (106) 4852
32.2%
Common
ValueCountFrequency (%)
1 102
57.0%
52
29.1%
2 17
 
9.5%
3 6
 
3.4%
( 1
 
0.6%
) 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15085
98.8%
ASCII 179
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 2288
15.2%
역 1893
 
12.5%
제 928
 
6.2%
한 859
 
5.7%
가 833
 
5.5%
사 794
 
5.3%
축 786
 
5.2%
육 785
 
5.2%
계 551
 
3.7%
획 516
 
3.4%
Other values (106) 4852
32.2%
ASCII
ValueCountFrequency (%)
1 102
57.0%
52
29.1%
2 17
 
9.5%
3 6
 
3.4%
( 1
 
0.6%
) 1
 
0.6%

NWCC_CLSF_NM
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size43.1 KiB
신축신고
3317 
신축허가
2185 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신축신고 3317
60.3%
신축허가 2185
39.7%

Length

2023-12-12T07:31:01.857882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:31:01.931648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축신고 3317
60.3%
신축허가 2185
39.7%

MAIN_ATACH_BULD_CLSF_CD
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size43.1 KiB
주건축물
5107 
부속건축물
 
395

Length

Max length5
Median length4
Mean length4.0717921
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
주건축물 5107
92.8%
부속건축물 395
 
7.2%

Length

2023-12-12T07:31:02.014665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:31:02.270077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주건축물 5107
92.8%
부속건축물 395
 
7.2%

BULD_NM
Text

MISSING 

Distinct721
Distinct (%)78.2%
Missing4580
Missing (%)83.2%
Memory size43.1 KiB
2023-12-12T07:31:02.456061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length29
Mean length10.560738
Min length1

Characters and Unicode

Total characters9737
Distinct characters503
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique617 ?
Unique (%)66.9%

Sample

1st row휴스턴오피스텔 창경궁 A
2nd row휴스턴오피스텔 창경궁 B
3rd row브릴란테 남산
4th row카임타워
5th row더그레이스
ValueCountFrequency (%)
단독주택 107
 
5.4%
그랑빌더포레 22
 
1.1%
제1종근린생활시설 21
 
1.1%
더 16
 
0.8%
제2종근린생활시설 13
 
0.7%
신축공사 12
 
0.6%
주)백천글로벌 11
 
0.6%
외동읍 9
 
0.5%
광양제철소 9
 
0.5%
sng공장 9
 
0.5%
Other values (1282) 1763
88.5%
2023-12-12T07:31:02.789869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1082
 
11.1%
1 324
 
3.3%
리 272
 
2.8%
주 229
 
2.4%
동 215
 
2.2%
2 200
 
2.1%
- 185
 
1.9%
) 182
 
1.9%
( 180
 
1.8%
스 157
 
1.6%
Other values (493) 6711
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6399
65.7%
Decimal Number 1362
 
14.0%
Space Separator 1082
 
11.1%
Uppercase Letter 250
 
2.6%
Dash Punctuation 185
 
1.9%
Close Punctuation 183
 
1.9%
Open Punctuation 181
 
1.9%
Lowercase Letter 52
 
0.5%
Other Punctuation 26
 
0.3%
Control 13
 
0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 272
 
4.3%
주 229
 
3.6%
동 215
 
3.4%
스 157
 
2.5%
택 134
 
2.1%
단 121
 
1.9%
면 117
 
1.8%
독 117
 
1.8%
빌 117
 
1.8%
이 111
 
1.7%
Other values (429) 4809
75.2%
Uppercase Letter
ValueCountFrequency (%)
S 25
 
10.0%
G 21
 
8.4%
N 19
 
7.6%
T 18
 
7.2%
I 17
 
6.8%
A 16
 
6.4%
H 15
 
6.0%
E 14
 
5.6%
K 14
 
5.6%
D 14
 
5.6%
Other values (13) 77
30.8%
Lowercase Letter
ValueCountFrequency (%)
o 10
19.2%
e 8
15.4%
s 8
15.4%
a 5
9.6%
u 4
 
7.7%
h 3
 
5.8%
n 2
 
3.8%
i 2
 
3.8%
l 2
 
3.8%
r 2
 
3.8%
Other values (6) 6
11.5%
Decimal Number
ValueCountFrequency (%)
1 324
23.8%
2 200
14.7%
4 140
10.3%
0 135
9.9%
3 130
9.5%
9 107
 
7.9%
5 102
 
7.5%
7 87
 
6.4%
8 72
 
5.3%
6 65
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 14
53.8%
. 5
 
19.2%
& 3
 
11.5%
' 2
 
7.7%
# 1
 
3.8%
/ 1
 
3.8%
Close Punctuation
ValueCountFrequency (%)
) 182
99.5%
] 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 180
99.4%
[ 1
 
0.6%
Space Separator
ValueCountFrequency (%)
1082
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%
Control
ValueCountFrequency (%)
13
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6396
65.7%
Common 3034
31.2%
Latin 304
 
3.1%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 272
 
4.3%
주 229
 
3.6%
동 215
 
3.4%
스 157
 
2.5%
택 134
 
2.1%
단 121
 
1.9%
면 117
 
1.8%
독 117
 
1.8%
빌 117
 
1.8%
이 111
 
1.7%
Other values (426) 4806
75.1%
Latin
ValueCountFrequency (%)
S 25
 
8.2%
G 21
 
6.9%
N 19
 
6.2%
T 18
 
5.9%
I 17
 
5.6%
A 16
 
5.3%
H 15
 
4.9%
E 14
 
4.6%
K 14
 
4.6%
D 14
 
4.6%
Other values (30) 131
43.1%
Common
ValueCountFrequency (%)
1082
35.7%
1 324
 
10.7%
2 200
 
6.6%
- 185
 
6.1%
) 182
 
6.0%
( 180
 
5.9%
4 140
 
4.6%
0 135
 
4.4%
3 130
 
4.3%
9 107
 
3.5%
Other values (14) 369
 
12.2%
Han
ValueCountFrequency (%)
家 1
33.3%
美 1
33.3%
笑 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6396
65.7%
ASCII 3336
34.3%
CJK 3
 
< 0.1%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1082
32.4%
1 324
 
9.7%
2 200
 
6.0%
- 185
 
5.5%
) 182
 
5.5%
( 180
 
5.4%
4 140
 
4.2%
0 135
 
4.0%
3 130
 
3.9%
9 107
 
3.2%
Other values (53) 671
20.1%
Hangul
ValueCountFrequency (%)
리 272
 
4.3%
주 229
 
3.6%
동 215
 
3.4%
스 157
 
2.5%
택 134
 
2.1%
단 121
 
1.9%
면 117
 
1.8%
독 117
 
1.8%
빌 117
 
1.8%
이 111
 
1.7%
Other values (426) 4806
75.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
CJK
ValueCountFrequency (%)
家 1
33.3%
美 1
33.3%
笑 1
33.3%

DONG_NM
Text

MISSING 

Distinct403
Distinct (%)11.6%
Missing2027
Missing (%)36.8%
Memory size43.1 KiB
2023-12-12T07:31:02.985712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length4.3027338
Min length1

Characters and Unicode

Total characters14952
Distinct characters252
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique298 ?
Unique (%)8.6%

Sample

1st row주건축물제1동
2nd row주건축물제1동
3rd row주건축물제1동
4th row주건축물제1동
5th row주건축물제1동
ValueCountFrequency (%)
주건축물제1동 907
25.4%
주1동 373
 
10.4%
1동 312
 
8.7%
가동 170
 
4.8%
2동 125
 
3.5%
제1동 107
 
3.0%
나동 96
 
2.7%
주건축물제2동 91
 
2.5%
주2동 75
 
2.1%
주1 72
 
2.0%
Other values (426) 1247
34.9%
2023-12-12T07:31:03.282099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 3234
21.6%
1 2217
14.8%
주 1722
11.5%
제 1382
9.2%
물 1170
 
7.8%
건 1166
 
7.8%
축 1165
 
7.8%
2 457
 
3.1%
부 205
 
1.4%
가 186
 
1.2%
Other values (242) 2048
13.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11324
75.7%
Decimal Number 3265
 
21.8%
Uppercase Letter 201
 
1.3%
Space Separator 100
 
0.7%
Close Punctuation 24
 
0.2%
Open Punctuation 24
 
0.2%
Lowercase Letter 6
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Connector Punctuation 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3234
28.6%
주 1722
15.2%
제 1382
12.2%
물 1170
 
10.3%
건 1166
 
10.3%
축 1165
 
10.3%
부 205
 
1.8%
가 186
 
1.6%
나 99
 
0.9%
속 95
 
0.8%
Other values (202) 900
 
7.9%
Uppercase Letter
ValueCountFrequency (%)
A 64
31.8%
B 48
23.9%
C 23
 
11.4%
E 17
 
8.5%
D 15
 
7.5%
H 5
 
2.5%
T 4
 
2.0%
S 4
 
2.0%
N 4
 
2.0%
F 3
 
1.5%
Other values (9) 14
 
7.0%
Decimal Number
ValueCountFrequency (%)
1 2217
67.9%
2 457
 
14.0%
3 161
 
4.9%
0 157
 
4.8%
4 83
 
2.5%
5 62
 
1.9%
6 43
 
1.3%
7 39
 
1.2%
9 23
 
0.7%
8 23
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
a 3
50.0%
n 1
 
16.7%
t 1
 
16.7%
y 1
 
16.7%
Space Separator
ValueCountFrequency (%)
100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11324
75.7%
Common 3421
 
22.9%
Latin 207
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3234
28.6%
주 1722
15.2%
제 1382
12.2%
물 1170
 
10.3%
건 1166
 
10.3%
축 1165
 
10.3%
부 205
 
1.8%
가 186
 
1.6%
나 99
 
0.9%
속 95
 
0.8%
Other values (202) 900
 
7.9%
Latin
ValueCountFrequency (%)
A 64
30.9%
B 48
23.2%
C 23
 
11.1%
E 17
 
8.2%
D 15
 
7.2%
H 5
 
2.4%
T 4
 
1.9%
S 4
 
1.9%
N 4
 
1.9%
a 3
 
1.4%
Other values (13) 20
 
9.7%
Common
ValueCountFrequency (%)
1 2217
64.8%
2 457
 
13.4%
3 161
 
4.7%
0 157
 
4.6%
100
 
2.9%
4 83
 
2.4%
5 62
 
1.8%
6 43
 
1.3%
7 39
 
1.1%
) 24
 
0.7%
Other values (7) 78
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11324
75.7%
ASCII 3628
 
24.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 3234
28.6%
주 1722
15.2%
제 1382
12.2%
물 1170
 
10.3%
건 1166
 
10.3%
축 1165
 
10.3%
부 205
 
1.8%
가 186
 
1.6%
나 99
 
0.9%
속 95
 
0.8%
Other values (202) 900
 
7.9%
ASCII
ValueCountFrequency (%)
1 2217
61.1%
2 457
 
12.6%
3 161
 
4.4%
0 157
 
4.3%
100
 
2.8%
4 83
 
2.3%
A 64
 
1.8%
5 62
 
1.7%
B 48
 
1.3%
6 43
 
1.2%
Other values (30) 236
 
6.5%

PLOT_DIMS
Real number (ℝ)

SKEWED  ZEROS 

Distinct1904
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1732.7455
Minimum0
Maximum376586.8
Zeros1091
Zeros (%)19.8%
Negative0
Negative (%)0.0%
Memory size48.5 KiB
2023-12-12T07:31:03.385120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1202
median466
Q3851
95-th percentile4202
Maximum376586.8
Range376586.8
Interquartile range (IQR)649

Descriptive statistics

Standard deviation15448.516
Coefficient of variation (CV)8.9156292
Kurtosis564.83496
Mean1732.7455
Median Absolute Deviation (MAD)314
Skewness23.421827
Sum9533565.8
Variance2.3865666 × 108
MonotonicityNot monotonic
2023-12-12T07:31:03.487413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1091
 
19.8%
660.0 93
 
1.7%
659.0 35
 
0.6%
26170.0 31
 
0.6%
330.0 24
 
0.4%
500.0 20
 
0.4%
1000.0 18
 
0.3%
331.0 17
 
0.3%
658.0 17
 
0.3%
8877.0 16
 
0.3%
Other values (1894) 4140
75.2%
ValueCountFrequency (%)
0.0 1091
19.8%
14.0 1
 
< 0.1%
24.1 1
 
< 0.1%
29.7 1
 
< 0.1%
45.3 1
 
< 0.1%
50.6 1
 
< 0.1%
57.0 2
 
< 0.1%
58.1 1
 
< 0.1%
67.0 1
 
< 0.1%
67.6 1
 
< 0.1%
ValueCountFrequency (%)
376586.8 9
 
0.2%
39078.0 1
 
< 0.1%
29990.0 1
 
< 0.1%
27744.7 6
 
0.1%
27581.0 1
 
< 0.1%
26170.0 31
0.6%
24444.4 1
 
< 0.1%
22963.0 1
 
< 0.1%
19998.0 2
 
< 0.1%
19956.0 1
 
< 0.1%

BULD_AREA
Real number (ℝ)

ZEROS 

Distinct3763
Distinct (%)68.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean215.3215
Minimum0
Maximum14660.67
Zeros65
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size48.5 KiB
2023-12-12T07:31:03.591656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile18
Q170.1575
median109.62
Q3195.8625
95-th percentile662.4
Maximum14660.67
Range14660.67
Interquartile range (IQR)125.705

Descriptive statistics

Standard deviation542.21881
Coefficient of variation (CV)2.5181824
Kurtosis247.65035
Mean215.3215
Median Absolute Deviation (MAD)54.31
Skewness13.056679
Sum1184698.9
Variance294001.24
MonotonicityNot monotonic
2023-12-12T07:31:03.691406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198.0 138
 
2.5%
18.0 83
 
1.5%
0.0 65
 
1.2%
99.0 35
 
0.6%
27.0 22
 
0.4%
6.0 21
 
0.4%
222.87 20
 
0.4%
36.0 20
 
0.4%
40.0 20
 
0.4%
196.0 19
 
0.3%
Other values (3753) 5059
91.9%
ValueCountFrequency (%)
0.0 65
1.2%
0.82 2
 
< 0.1%
1.32 1
 
< 0.1%
1.4 1
 
< 0.1%
1.71 1
 
< 0.1%
1.8 1
 
< 0.1%
2.24 1
 
< 0.1%
2.25 1
 
< 0.1%
2.64 1
 
< 0.1%
3.0 9
 
0.2%
ValueCountFrequency (%)
14660.67 1
< 0.1%
12736.048 1
< 0.1%
11977.75 1
< 0.1%
10958.62 1
< 0.1%
7878.35 1
< 0.1%
7110.41 1
< 0.1%
6486.59 1
< 0.1%
6243.29 1
< 0.1%
6150.97 1
< 0.1%
6060.49 1
< 0.1%

BF_BULD_DIMS
Real number (ℝ)

ZEROS 

Distinct699
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.869928
Minimum0
Maximum9075.85
Zeros4605
Zeros (%)83.7%
Negative0
Negative (%)0.0%
Memory size48.5 KiB
2023-12-12T07:31:03.807148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile132.0475
Maximum9075.85
Range9075.85
Interquartile range (IQR)0

Descriptive statistics

Standard deviation246.35295
Coefficient of variation (CV)6.3378804
Kurtosis457.39635
Mean38.869928
Median Absolute Deviation (MAD)0
Skewness17.475814
Sum213862.34
Variance60689.777
MonotonicityNot monotonic
2023-12-12T07:31:03.906300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4605
83.7%
88.05 11
 
0.2%
2065.92 10
 
0.2%
39.67 9
 
0.2%
49.5 8
 
0.1%
468.0 7
 
0.1%
99.0 6
 
0.1%
3074.78 6
 
0.1%
2121.04 5
 
0.1%
44.0 4
 
0.1%
Other values (689) 831
 
15.1%
ValueCountFrequency (%)
0.0 4605
83.7%
12.0 1
 
< 0.1%
12.51 1
 
< 0.1%
13.22 1
 
< 0.1%
14.0 1
 
< 0.1%
15.0 1
 
< 0.1%
15.2 1
 
< 0.1%
16.53 1
 
< 0.1%
18.0 2
 
< 0.1%
18.75 1
 
< 0.1%
ValueCountFrequency (%)
9075.85 1
 
< 0.1%
6150.97 1
 
< 0.1%
3695.96 2
 
< 0.1%
3074.78 6
0.1%
2157.6 1
 
< 0.1%
2121.04 5
0.1%
2065.92 10
0.2%
1959.75 3
 
0.1%
1947.97 1
 
< 0.1%
1935.73 1
 
< 0.1%

GRFA
Real number (ℝ)

SKEWED 

Distinct3875
Distinct (%)70.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean570.78015
Minimum0
Maximum194813
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size48.5 KiB
2023-12-12T07:31:04.005496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile19.6
Q180.9475
median140.66
Q3294.885
95-th percentile1414.539
Maximum194813
Range194813
Interquartile range (IQR)213.9375

Descriptive statistics

Standard deviation4202.5094
Coefficient of variation (CV)7.3627461
Kurtosis1149.6546
Mean570.78015
Median Absolute Deviation (MAD)73.53
Skewness29.982828
Sum3140432.4
Variance17661085
MonotonicityNot monotonic
2023-12-12T07:31:04.115086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198.0 142
 
2.6%
18.0 82
 
1.5%
99.0 32
 
0.6%
27.0 23
 
0.4%
196.0 22
 
0.4%
36.0 21
 
0.4%
6.0 21
 
0.4%
222.87 20
 
0.4%
40.0 18
 
0.3%
189.84 16
 
0.3%
Other values (3865) 5105
92.8%
ValueCountFrequency (%)
0.0 2
 
< 0.1%
0.82 2
 
< 0.1%
1.32 1
 
< 0.1%
1.4 1
 
< 0.1%
1.71 1
 
< 0.1%
1.8 1
 
< 0.1%
2.24 1
 
< 0.1%
2.25 1
 
< 0.1%
2.64 1
 
< 0.1%
3.0 9
0.2%
ValueCountFrequency (%)
194813.0 1
< 0.1%
143533.03 1
< 0.1%
86147.523 1
< 0.1%
84669.3566 1
< 0.1%
54458.739 1
< 0.1%
49772.19 1
< 0.1%
44414.45 1
< 0.1%
40347.76 1
< 0.1%
40330.33 1
< 0.1%
38801.9961 1
< 0.1%

BF_GRFA
Real number (ℝ)

SKEWED  ZEROS 

Distinct762
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.949421
Minimum0
Maximum54458.739
Zeros4521
Zeros (%)82.2%
Negative0
Negative (%)0.0%
Memory size48.5 KiB
2023-12-12T07:31:04.231443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile236.708
Maximum54458.739
Range54458.739
Interquartile range (IQR)0

Descriptive statistics

Standard deviation838.10054
Coefficient of variation (CV)11.648468
Kurtosis3254.8014
Mean71.949421
Median Absolute Deviation (MAD)0
Skewness51.893023
Sum395865.71
Variance702412.51
MonotonicityNot monotonic
2023-12-12T07:31:04.342786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 4521
82.2%
88.05 11
 
0.2%
2122.65 10
 
0.2%
49.5 9
 
0.2%
99.0 7
 
0.1%
468.0 7
 
0.1%
3074.78 6
 
0.1%
99.17 6
 
0.1%
4856.12 5
 
0.1%
236.85 5
 
0.1%
Other values (752) 915
 
16.6%
ValueCountFrequency (%)
0.0 4521
82.2%
12.0 1
 
< 0.1%
12.51 1
 
< 0.1%
13.22 1
 
< 0.1%
14.0 1
 
< 0.1%
15.0 1
 
< 0.1%
15.2 1
 
< 0.1%
15.4 1
 
< 0.1%
16.53 1
 
< 0.1%
18.0 2
 
< 0.1%
ValueCountFrequency (%)
54458.739 1
 
< 0.1%
15437.76 1
 
< 0.1%
11821.47 1
 
< 0.1%
5885.74 1
 
< 0.1%
5686.62 2
 
< 0.1%
5016.44 1
 
< 0.1%
4856.12 5
0.1%
4354.88 1
 
< 0.1%
3964.64 1
 
< 0.1%
3717.5 1
 
< 0.1%

BULD_MUSES_NM
Categorical

Distinct24
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size43.1 KiB
단독주택
2372 
제2종근린생활시설
1014 
제1종근린생활시설
519 
창고시설
395 
동물및식물관련시설
359 
Other values (19)
843 

Length

Max length10
Median length4
Mean length5.7320974
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row업무시설
2nd row업무시설
3rd row제1종근린생활시설
4th row단독주택
5th row제1종근린생활시설

Common Values

ValueCountFrequency (%)
단독주택 2372
43.1%
제2종근린생활시설 1014
18.4%
제1종근린생활시설 519
 
9.4%
창고시설 395
 
7.2%
동물및식물관련시설 359
 
6.5%
공동주택 230
 
4.2%
공장 227
 
4.1%
야영장시설 107
 
1.9%
업무시설 54
 
1.0%
발전시설 39
 
0.7%
Other values (14) 186
 
3.4%

Length

2023-12-12T07:31:04.450837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 2372
43.1%
제2종근린생활시설 1014
18.4%
제1종근린생활시설 519
 
9.4%
창고시설 395
 
7.2%
동물및식물관련시설 359
 
6.5%
공동주택 230
 
4.2%
공장 227
 
4.1%
야영장시설 107
 
1.9%
업무시설 54
 
1.0%
발전시설 39
 
0.7%
Other values (14) 186
 
3.4%

BF_BULD_MUSES_NM
Categorical

IMBALANCE 

Distinct19
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size43.1 KiB
<NA>
4520 
단독주택
607 
제1종근린생활시설
 
88
제2종근린생활시설
 
86
동물및식물관련시설
 
66
Other values (14)
 
135

Length

Max length10
Median length4
Mean length4.2182843
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row창고시설
2nd row단독주택
3rd row제2종근린생활시설
4th row단독주택
5th row단독주택

Common Values

ValueCountFrequency (%)
<NA> 4520
82.2%
단독주택 607
 
11.0%
제1종근린생활시설 88
 
1.6%
제2종근린생활시설 86
 
1.6%
동물및식물관련시설 66
 
1.2%
공장 40
 
0.7%
창고시설 39
 
0.7%
숙박시설 10
 
0.2%
공동주택 10
 
0.2%
판매시설 6
 
0.1%
Other values (9) 30
 
0.5%

Length

2023-12-12T07:31:04.553402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4520
82.2%
단독주택 607
 
11.0%
제1종근린생활시설 88
 
1.6%
제2종근린생활시설 86
 
1.6%
동물및식물관련시설 66
 
1.2%
공장 40
 
0.7%
창고시설 39
 
0.7%
숙박시설 10
 
0.2%
공동주택 10
 
0.2%
업무시설 6
 
0.1%
Other values (9) 30
 
0.5%

BULD_STRU_NM
Categorical

IMBALANCE 

Distinct24
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size43.1 KiB
철근콘크리트구조
1744 
경량철골구조
1730 
일반철골구조
1191 
일반목구조
482 
강파이프구조
 
127
Other values (19)
228 

Length

Max length13
Median length6
Mean length6.5345329
Min length3

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 1744
31.7%
경량철골구조 1730
31.4%
일반철골구조 1191
21.6%
일반목구조 482
 
8.8%
강파이프구조 127
 
2.3%
컨테이너조 78
 
1.4%
기타강구조 36
 
0.7%
조립식판넬조 32
 
0.6%
벽돌구조 16
 
0.3%
시멘트블럭조 10
 
0.2%
Other values (14) 56
 
1.0%

Length

2023-12-12T07:31:04.648165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
철근콘크리트구조 1744
31.7%
경량철골구조 1730
31.4%
일반철골구조 1191
21.6%
일반목구조 482
 
8.7%
강파이프구조 127
 
2.3%
컨테이너조 78
 
1.4%
기타강구조 36
 
0.7%
조립식판넬조 32
 
0.6%
벽돌구조 16
 
0.3%
시멘트블럭조 10
 
0.2%
Other values (16) 64
 
1.2%

BF_BULD_STRU_NM
Categorical

IMBALANCE 

Distinct19
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size43.1 KiB
<NA>
4519 
일반목구조
 
243
벽돌구조
 
236
블록구조
 
133
경량철골구조
 
126
Other values (14)
 
245

Length

Max length10
Median length4
Mean length4.2159215
Min length3

Unique

Unique3 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4519
82.1%
일반목구조 243
 
4.4%
벽돌구조 236
 
4.3%
블록구조 133
 
2.4%
경량철골구조 126
 
2.3%
철근콘크리트구조 115
 
2.1%
기타조적구조 44
 
0.8%
일반철골구조 41
 
0.7%
강파이프구조 17
 
0.3%
목구조 5
 
0.1%
Other values (9) 23
 
0.4%

Length

2023-12-12T07:31:04.743876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4519
82.1%
일반목구조 243
 
4.4%
벽돌구조 236
 
4.3%
블록구조 133
 
2.4%
경량철골구조 126
 
2.3%
철근콘크리트구조 115
 
2.1%
기타조적구조 44
 
0.8%
일반철골구조 41
 
0.7%
강파이프구조 17
 
0.3%
철골구조 5
 
0.1%
Other values (9) 23
 
0.4%

CLSG_ERSR_YMD
Real number (ℝ)

MISSING 

Distinct534
Distinct (%)54.3%
Missing4519
Missing (%)82.1%
Infinite0
Infinite (%)0.0%
Mean20208158
Minimum20000621
Maximum20230724
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.5 KiB
2023-12-12T07:31:04.847327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000621
5-th percentile20110654
Q120210718
median20220729
Q320230216
95-th percentile20230630
Maximum20230724
Range230103
Interquartile range (IQR)19498.5

Descriptive statistics

Standard deviation39483.645
Coefficient of variation (CV)0.0019538469
Kurtosis8.6788699
Mean20208158
Median Absolute Deviation (MAD)9585
Skewness-2.9454086
Sum1.9864619 × 1010
Variance1.5589582 × 109
MonotonicityNot monotonic
2023-12-12T07:31:04.950258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230713 15
 
0.3%
20220926 11
 
0.2%
20230630 9
 
0.2%
20210413 8
 
0.1%
20210503 7
 
0.1%
20220711 7
 
0.1%
20220427 7
 
0.1%
20221123 7
 
0.1%
20230516 7
 
0.1%
20230704 7
 
0.1%
Other values (524) 898
 
16.3%
(Missing) 4519
82.1%
ValueCountFrequency (%)
20000621 2
< 0.1%
20000929 1
< 0.1%
20001018 1
< 0.1%
20020220 1
< 0.1%
20031016 1
< 0.1%
20040105 1
< 0.1%
20040131 1
< 0.1%
20040206 1
< 0.1%
20040531 1
< 0.1%
20040722 1
< 0.1%
ValueCountFrequency (%)
20230724 2
 
< 0.1%
20230721 1
 
< 0.1%
20230719 1
 
< 0.1%
20230717 2
 
< 0.1%
20230714 2
 
< 0.1%
20230713 15
0.3%
20230711 3
 
0.1%
20230710 2
 
< 0.1%
20230709 1
 
< 0.1%
20230707 4
 
0.1%

BILDNG_PRMS_YMD
Real number (ℝ)

Distinct1049
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20214547
Minimum20010412
Maximum20230717
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.5 KiB
2023-12-12T07:31:05.057801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010412
5-th percentile20180206
Q120211012
median20220722
Q320221212
95-th percentile20230417
Maximum20230717
Range220305
Interquartile range (IQR)10200

Descriptive statistics

Standard deviation20637.458
Coefficient of variation (CV)0.0010209211
Kurtosis17.675639
Mean20214547
Median Absolute Deviation (MAD)9387
Skewness-3.5277199
Sum1.1122044 × 1011
Variance4.2590466 × 108
MonotonicityNot monotonic
2023-12-12T07:31:05.166949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20221109 39
 
0.7%
20230405 32
 
0.6%
20190329 32
 
0.6%
20230614 31
 
0.6%
20220526 29
 
0.5%
20221102 28
 
0.5%
20220331 27
 
0.5%
20221215 25
 
0.5%
20220628 25
 
0.5%
20220929 24
 
0.4%
Other values (1039) 5210
94.7%
ValueCountFrequency (%)
20010412 2
< 0.1%
20021014 1
< 0.1%
20050630 1
< 0.1%
20060227 2
< 0.1%
20061228 1
< 0.1%
20070523 1
< 0.1%
20070827 1
< 0.1%
20070917 1
< 0.1%
20070921 1
< 0.1%
20080702 2
< 0.1%
ValueCountFrequency (%)
20230717 3
 
0.1%
20230706 1
 
< 0.1%
20230705 1
 
< 0.1%
20230704 1
 
< 0.1%
20230629 2
 
< 0.1%
20230627 3
 
0.1%
20230622 4
0.1%
20230621 1
 
< 0.1%
20230620 8
0.1%
20230619 2
 
< 0.1%

BILDNG_STWRK_YMD
Real number (ℝ)

MISSING 

Distinct924
Distinct (%)17.6%
Missing259
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean20218396
Minimum20010522
Maximum20231214
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.5 KiB
2023-12-12T07:31:05.279749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010522
5-th percentile20190308
Q120220415
median20221021
Q320230223
95-th percentile20230504
Maximum20231214
Range220692
Interquartile range (IQR)9808

Descriptive statistics

Standard deviation18428.891
Coefficient of variation (CV)0.00091149125
Kurtosis24.519155
Mean20218396
Median Absolute Deviation (MAD)9106
Skewness-4.1549229
Sum1.0600505 × 1011
Variance3.3962404 × 108
MonotonicityNot monotonic
2023-12-12T07:31:05.382095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20221110 46
 
0.8%
20221121 43
 
0.8%
20230228 37
 
0.7%
20230317 37
 
0.7%
20230320 36
 
0.7%
20230329 34
 
0.6%
20230327 33
 
0.6%
20230615 32
 
0.6%
20230220 31
 
0.6%
20190507 31
 
0.6%
Other values (914) 4883
88.7%
(Missing) 259
 
4.7%
ValueCountFrequency (%)
20010522 2
< 0.1%
20041013 1
< 0.1%
20060317 1
< 0.1%
20060320 1
< 0.1%
20070110 1
< 0.1%
20070706 1
< 0.1%
20070906 1
< 0.1%
20081118 1
< 0.1%
20081203 2
< 0.1%
20091109 1
< 0.1%
ValueCountFrequency (%)
20231214 1
 
< 0.1%
20231019 1
 
< 0.1%
20231004 1
 
< 0.1%
20230928 1
 
< 0.1%
20230826 1
 
< 0.1%
20230720 3
0.1%
20230707 2
< 0.1%
20230705 1
 
< 0.1%
20230704 1
 
< 0.1%
20230703 2
< 0.1%

USE_APRV_YMD
Real number (ℝ)

Distinct31
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20230715
Minimum20230701
Maximum20230731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.5 KiB
2023-12-12T07:31:05.497669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20230701
5-th percentile20230704
Q120230707
median20230714
Q320230721
95-th percentile20230727
Maximum20230731
Range30
Interquartile range (IQR)14

Descriptive statistics

Standard deviation7.8543885
Coefficient of variation (CV)3.8824078 × 10-7
Kurtosis-1.2143374
Mean20230715
Median Absolute Deviation (MAD)7
Skewness0.12161061
Sum1.1130939 × 1011
Variance61.691418
MonotonicityNot monotonic
2023-12-12T07:31:05.590022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
20230706 361
 
6.6%
20230720 327
 
5.9%
20230705 318
 
5.8%
20230707 317
 
5.8%
20230713 316
 
5.7%
20230711 304
 
5.5%
20230704 280
 
5.1%
20230714 279
 
5.1%
20230719 272
 
4.9%
20230718 268
 
4.9%
Other values (21) 2460
44.7%
ValueCountFrequency (%)
20230701 1
 
< 0.1%
20230702 8
 
0.1%
20230703 226
4.1%
20230704 280
5.1%
20230705 318
5.8%
20230706 361
6.6%
20230707 317
5.8%
20230708 4
 
0.1%
20230709 2
 
< 0.1%
20230710 265
4.8%
ValueCountFrequency (%)
20230731 42
 
0.8%
20230730 2
 
< 0.1%
20230729 6
 
0.1%
20230728 179
3.3%
20230727 231
4.2%
20230726 213
3.9%
20230725 265
4.8%
20230724 266
4.8%
20230723 1
 
< 0.1%
20230722 1
 
< 0.1%

CLSG_ERSR_CLSF_NM
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size43.1 KiB
<NA>
4514 
말소
981 
폐쇄
 
7

Length

Max length4
Median length4
Mean length3.6408579
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 4514
82.0%
말소 981
 
17.8%
폐쇄 7
 
0.1%

Length

2023-12-12T07:31:05.687822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:31:05.765852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 4514
82.0%
말소 981
 
17.8%
폐쇄 7
 
0.1%

CLSG_ERSR_MAIN_BULD_CNT
Real number (ℝ)

ZEROS 

Distinct9
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.22700836
Minimum0
Maximum11
Zeros4516
Zeros (%)82.1%
Negative0
Negative (%)0.0%
Memory size48.5 KiB
2023-12-12T07:31:06.025815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.70310638
Coefficient of variation (CV)3.0972709
Kurtosis116.33641
Mean0.22700836
Median Absolute Deviation (MAD)0
Skewness8.7793203
Sum1249
Variance0.49435858
MonotonicityNot monotonic
2023-12-12T07:31:06.121534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 4516
82.1%
1 880
 
16.0%
2 66
 
1.2%
3 19
 
0.3%
11 10
 
0.2%
7 6
 
0.1%
4 3
 
0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
0 4516
82.1%
1 880
 
16.0%
2 66
 
1.2%
3 19
 
0.3%
4 3
 
0.1%
6 1
 
< 0.1%
7 6
 
0.1%
10 1
 
< 0.1%
11 10
 
0.2%
ValueCountFrequency (%)
11 10
 
0.2%
10 1
 
< 0.1%
7 6
 
0.1%
6 1
 
< 0.1%
4 3
 
0.1%
3 19
 
0.3%
2 66
 
1.2%
1 880
 
16.0%
0 4516
82.1%

CLSG_ERSR_ATACH_BULD_CNT
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size43.1 KiB
0
5434 
1
 
54
2
 
10
3
 
2
4
 
2

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 5434
98.8%
1 54
 
1.0%
2 10
 
0.2%
3 2
 
< 0.1%
4 2
 
< 0.1%

Length

2023-12-12T07:31:06.213501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:31:06.292825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 5434
98.8%
1 54
 
1.0%
2 10
 
0.2%
3 2
 
< 0.1%
4 2
 
< 0.1%

Sample

BDRG_INNBPNULNNO_ADRESNWCC_BILD_INFO_RN_ADRES_CDRNLNDCGR_NMSUSAR_NMPRPOS_DISTRICT_NMPRPOS_AREA_NMNWCC_CLSF_NMMAIN_ATACH_BULD_CLSF_CDBULD_NMDONG_NMPLOT_DIMSBULD_AREABF_BULD_DIMSGRFABF_GRFABULD_MUSES_NMBF_BULD_MUSES_NMBULD_STRU_NMBF_BULD_STRU_NMCLSG_ERSR_YMDBILDNG_PRMS_YMDBILDNG_STWRK_YMDUSE_APRV_YMDCLSG_ERSR_CLSF_NMCLSG_ERSR_MAIN_BULD_CNTCLSG_ERSR_ATACH_BULD_CNT
011110-10000000000000020803131111015900000660060서울특별시 종로구 원남동 66-60번지1111041004061590100002000000서울특별시 종로구 창경궁로18길 20대도시지역<NA>중점경관관리구역신축허가주건축물휴스턴오피스텔 창경궁 A<NA>341.22194.60.01870.5565.29업무시설창고시설철근콘크리트구조일반목구조20190103201908122019120120230713말소10
111110-10000000000000020804231111015900000660067서울특별시 종로구 원남동 66-67번지1111041004061590100002000000서울특별시 종로구 창경궁로18길 20대도시지역<NA>중점경관관리구역신축허가주건축물휴스턴오피스텔 창경궁 B<NA>314.08187.90.01736.73105.79업무시설단독주택철근콘크리트구조일반목구조20190103201908122019120120230713말소10
211110-10000000000000020713441111016700001080000서울특별시 종로구 충신동 108번지1111041002201670200003200000서울특별시 종로구 율곡로16길 32대도시지역<NA>지구단위계획구역신축허가주건축물<NA><NA>198.24115.3589.1949.22574.2제1종근린생활시설제2종근린생활시설철근콘크리트구조철근콘크리트구조20220816202202232022061620230712말소10
311110-10000000000000020718151111018300000920005서울특별시 종로구 평창동 92-5번지1111041005001830100002200000서울특별시 종로구 평창25길 22대<NA><NA><NA>신축허가주건축물<NA><NA>693.0129.270.0328.04234.01단독주택단독주택철근콘크리트구조벽돌구조20210914202202182022051320230712말소10
411110-10000000000000020718161111018300000920005서울특별시 종로구 평창동 92-5번지1111041005001830100002200000서울특별시 종로구 평창25길 22대<NA><NA><NA>신축허가주건축물<NA><NA>693.0167.840.0337.45234.01제1종근린생활시설단독주택철근콘크리트구조벽돌구조20210914202202182022051320230712말소10
511110-10000000000000020198211111018700000461901서울특별시 종로구 무악동 46-1901번지1111041004831870100001900002서울특별시 종로구 통일로18나길 19-2대도시지역자연경관지구중점경관관리구역신축허가주건축물<NA>주건축물제1동195.2677.320.0197.360.0단독주택<NA>철근콘크리트구조<NA><NA>202011272022110120230704<NA>00
611140-10000000000000020958801114013700000030005서울특별시 중구 필동1가 3-5번지1114041033351370100001600000서울특별시 중구 퇴계로27길 16대일반상업지역방화지구가축사육제한구역신축허가주건축물브릴란테 남산주건축물제1동1022.0607.330.08712.423474.15업무시설업무시설철근콘크리트구조철근콘크리트구조20210518202012242021052720230717말소10
711140-10000000000000021657721114014300000490008서울특별시 중구 장충동1가 49-8번지1114041032691430100003200000서울특별시 중구 장충단로6가길 32대제2종일반주거지역<NA>지구단위계획구역신축허가주건축물<NA>주건축물제1동82.649.390.0145.21138.61단독주택단독주택철근콘크리트구조벽돌구조20220421202106152022041120230728말소10
811140-10000000000000020301861114016200002510130서울특별시 중구 신당동 251-130번지1114041033751620100003400003서울특별시 중구 퇴계로71길 34-3대일반상업지역<NA>지구단위계획구역신축허가주건축물카임타워주건축물제1동117.069.720.0758.6439.67제2종근린생활시설제1종근린생활시설철근콘크리트구조일반목구조20200519202109012021122420230707말소10
911140-10000000000000020804971114016200003720003서울특별시 중구 신당동 372-3번지1114041030281620100002100000서울특별시 중구 다산로10길 21대준주거지역<NA>제1종지구단위계획구역신축허가주건축물더그레이스<NA>655.0387.980.02946.091151.11제1종근린생활시설제1종근린생활시설철근콘크리트구조철근콘크리트구조20220112202109142021123120230714말소10
BDRG_INNBPNULNNO_ADRESNWCC_BILD_INFO_RN_ADRES_CDRNLNDCGR_NMSUSAR_NMPRPOS_DISTRICT_NMPRPOS_AREA_NMNWCC_CLSF_NMMAIN_ATACH_BULD_CLSF_CDBULD_NMDONG_NMPLOT_DIMSBULD_AREABF_BULD_DIMSGRFABF_GRFABULD_MUSES_NMBF_BULD_MUSES_NMBULD_STRU_NMBF_BULD_STRU_NMCLSG_ERSR_YMDBILDNG_PRMS_YMDBILDNG_STWRK_YMDUSE_APRV_YMDCLSG_ERSR_CLSF_NMCLSG_ERSR_MAIN_BULD_CNTCLSG_ERSR_ATACH_BULD_CNT
549251830-10000000000000020170425183035036009590005강원특별자치도 양양군 강현면 정암리 959-5번지5183048617683500100004000000강원특별자치도 양양군 강현면 정암전원마을길 40대계획관리지역비행안전구역진입표면구역신축신고주건축물<NA><NA>650.343.40.065.80.0단독주택<NA>경량철골구조<NA><NA>202301252023022720230705<NA>00
549351830-10000000000000021595225183035037001440001강원특별자치도 양양군 강현면 용호리 144-1번지5183045051563500100001100000강원특별자치도 양양군 강현면 용호길 11답계획관리지역<NA>소하천예정지신축신고주건축물<NA>주1동7742.052.840.052.840.0야영장시설<NA>경량철골구조<NA><NA>202209272022110420230727<NA>00
549451830-10000000000000021595235183035037001440001강원특별자치도 양양군 강현면 용호리 144-1번지5183045051563500100001100000강원특별자치도 양양군 강현면 용호길 11답계획관리지역<NA>소하천예정지신축신고주건축물<NA>주2동7742.033.9250.033.9250.0야영장시설<NA>경량철골구조<NA><NA>202209272022110420230727<NA>00
549551830-10000000000000021595245183035037001440001강원특별자치도 양양군 강현면 용호리 144-1번지5183045051563500100001100000강원특별자치도 양양군 강현면 용호길 11답계획관리지역<NA>소하천예정지신축신고주건축물<NA>주3동7742.033.9250.033.9250.0야영장시설<NA>경량철골구조<NA><NA>202209272022110420230727<NA>00
549651830-10000000000000021595255183035037001440001강원특별자치도 양양군 강현면 용호리 144-1번지5183045051563500100001100000강원특별자치도 양양군 강현면 용호길 11답계획관리지역<NA>소하천예정지신축신고주건축물<NA>주4동7742.027.020.027.020.0야영장시설<NA>경량철골구조<NA><NA>202209272022110420230727<NA>00
549751830-10000000000000021595265183035037001440001강원특별자치도 양양군 강현면 용호리 144-1번지5183045051563500100001100000강원특별자치도 양양군 강현면 용호길 11답계획관리지역<NA>소하천예정지신축신고주건축물<NA>주5동7742.030.00.030.00.0야영장시설<NA>경량철골구조<NA><NA>202209272022110420230727<NA>00
549851830-10000000000000021595275183035037001440001강원특별자치도 양양군 강현면 용호리 144-1번지5183045051563500100001100000강원특별자치도 양양군 강현면 용호길 11답계획관리지역<NA>소하천예정지신축신고주건축물<NA>주6동7742.030.00.030.00.0야영장시설<NA>경량철골구조<NA><NA>202209272022110420230727<NA>00
549951830-10000000000000021595285183035037001440001강원특별자치도 양양군 강현면 용호리 144-1번지5183045051563500100001100000강원특별자치도 양양군 강현면 용호길 11답계획관리지역<NA>소하천예정지신축신고주건축물<NA>주7동7742.030.00.030.00.0야영장시설<NA>경량철골구조<NA><NA>202209272022110420230727<NA>00
550051830-10000000000000021595295183035037001440001강원특별자치도 양양군 강현면 용호리 144-1번지5183045051563500100001100000강원특별자치도 양양군 강현면 용호길 11답계획관리지역<NA>소하천예정지신축신고주건축물<NA>주8동7742.030.00.030.00.0야영장시설<NA>경량철골구조<NA><NA>202209272022110420230727<NA>00
550151830-10000000000000021595305183035037001440001강원특별자치도 양양군 강현면 용호리 144-1번지5183045051563500100001100000강원특별자치도 양양군 강현면 용호길 11답계획관리지역<NA>소하천예정지신축신고주건축물<NA>주9동7742.030.00.030.00.0야영장시설<NA>경량철골구조<NA><NA>202209272022110420230727<NA>00