Overview

Dataset statistics

Number of variables44
Number of observations10000
Missing cells117986
Missing cells (%)26.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 MiB
Average record size in memory375.0 B

Variable types

Numeric14
Categorical9
Text19
DateTime2

Dataset

Description인천광역시 미추홀구 건축물 착공신고 현황에 대한 데이터로 연번, 도로명주소, 좌표값, 대지면적 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15029300/fileData.do

Alerts

건축구분 is highly imbalanced (67.9%)Imbalance
지목 is highly imbalanced (84.3%)Imbalance
구조 is highly imbalanced (66.0%)Imbalance
하수처리시설명 is highly imbalanced (74.5%)Imbalance
용도지구 is highly imbalanced (64.7%)Imbalance
용도구역 is highly imbalanced (75.3%)Imbalance
인근기계식주차장(대) is highly imbalanced (95.1%)Imbalance
증축연면적(제곱미터) has 7882 (78.8%) missing valuesMissing
최종설계변경일 has 7697 (77.0%) missing valuesMissing
착공예정일 has 693 (6.9%) missing valuesMissing
사용승인일 has 670 (6.7%) missing valuesMissing
건축허가최초접수일 has 130 (1.3%) missing valuesMissing
최대지상층수 has 173 (1.7%) missing valuesMissing
최대지하층수 has 3238 (32.4%) missing valuesMissing
최고높이(m) has 497 (5.0%) missing valuesMissing
승강기합 has 7096 (71.0%) missing valuesMissing
비상승강기합 has 9427 (94.3%) missing valuesMissing
하수처리시설용량(제곱미터) has 7390 (73.9%) missing valuesMissing
부속용도 has 2440 (24.4%) missing valuesMissing
자주식옥내주차장(대) has 6519 (65.2%) missing valuesMissing
자주식옥외주차장(대) has 3577 (35.8%) missing valuesMissing
기계식옥내주차장(대) has 9420 (94.2%) missing valuesMissing
기계식옥외주차장(대) has 9771 (97.7%) missing valuesMissing
인근자주식주차장(대) has 9799 (98.0%) missing valuesMissing
총주차대수 has 1357 (13.6%) missing valuesMissing
총주차장면적(제곱미터) has 1357 (13.6%) missing valuesMissing
세대수 has 4163 (41.6%) missing valuesMissing
호수 has 9091 (90.9%) missing valuesMissing
가구수 has 5745 (57.5%) missing valuesMissing
주건축물수 has 440 (4.4%) missing valuesMissing
부속건축물수 has 9301 (93.0%) missing valuesMissing
최대지상층수 is highly skewed (γ1 = 69.84440156)Skewed
주건축물수 is highly skewed (γ1 = 20.02454013)Skewed
연번 has unique valuesUnique
최대지하층수 has 4062 (40.6%) zerosZeros
동수 has 434 (4.3%) zerosZeros
승강기합 has 719 (7.2%) zerosZeros
비상승강기합 has 406 (4.1%) zerosZeros
기계식옥내주차장(대) has 164 (1.6%) zerosZeros
기계식옥외주차장(대) has 171 (1.7%) zerosZeros
인근자주식주차장(대) has 160 (1.6%) zerosZeros
세대수 has 1726 (17.3%) zerosZeros
가구수 has 1761 (17.6%) zerosZeros
부속건축물수 has 288 (2.9%) zerosZeros

Reproduction

Analysis started2023-12-12 23:13:29.787171
Analysis finished2023-12-12 23:13:31.968486
Duration2.18 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5374.8144
Minimum1
Maximum10753
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:32.034876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile537.95
Q12681.75
median5378.5
Q38066.25
95-th percentile10220.05
Maximum10753
Range10752
Interquartile range (IQR)5384.5

Descriptive statistics

Standard deviation3105.4986
Coefficient of variation (CV)0.57778714
Kurtosis-1.2013135
Mean5374.8144
Median Absolute Deviation (MAD)2692
Skewness0.00056496663
Sum53748144
Variance9644121.8
MonotonicityNot monotonic
2023-12-13T08:13:32.145337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3836 1
 
< 0.1%
8130 1
 
< 0.1%
6340 1
 
< 0.1%
3338 1
 
< 0.1%
6536 1
 
< 0.1%
9038 1
 
< 0.1%
5959 1
 
< 0.1%
9162 1
 
< 0.1%
2479 1
 
< 0.1%
10306 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
10753 1
< 0.1%
10752 1
< 0.1%
10751 1
< 0.1%
10750 1
< 0.1%
10749 1
< 0.1%
10748 1
< 0.1%
10746 1
< 0.1%
10745 1
< 0.1%
10744 1
< 0.1%
10743 1
< 0.1%

건축구분
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
신축
7534 
증축
2172 
대수선
 
246
개축
 
18
용도변경
 
14
Other values (3)
 
16

Length

Max length9
Median length2
Mean length2.033
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row신축
2nd row신축
3rd row증축
4th row신축
5th row신축

Common Values

ValueCountFrequency (%)
신축 7534
75.3%
증축 2172
 
21.7%
대수선 246
 
2.5%
개축 18
 
0.2%
용도변경 14
 
0.1%
재축 8
 
0.1%
가설건축물축조허가 7
 
0.1%
허가/신고사항변경 1
 
< 0.1%

Length

2023-12-13T08:13:32.251973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:13:32.363268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 7534
75.3%
증축 2172
 
21.7%
대수선 246
 
2.5%
개축 18
 
0.2%
용도변경 14
 
0.1%
재축 8
 
0.1%
가설건축물축조허가 7
 
0.1%
허가/신고사항변경 1
 
< 0.1%
Distinct9797
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T08:13:32.595627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length17.0494
Min length15

Characters and Unicode

Total characters170494
Distinct characters57
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

Unique9594 ?
Unique (%)95.9%

Sample

1st row2015-건축과-신축허가-60
2nd row2009-건축과-신축허가-5
3rd row2001-종합민원과-증축허가-27
4th row2002-건축과-신축허가-751
5th row2022-건축과-신축허가-11
ValueCountFrequency (%)
2019-건축과-신축허가-73 2
 
< 0.1%
2018-건축과-신축허가-25 2
 
< 0.1%
2018-건축과-신축신고-4 2
 
< 0.1%
2007-건축과-대수선허가-2 2
 
< 0.1%
2018-건축과-신축허가-66 2
 
< 0.1%
2007-건축과-신축허가-26 2
 
< 0.1%
2019-건축과-신축허가-86 2
 
< 0.1%
2018-건축과-신축허가-35 2
 
< 0.1%
2005-건축과-대수선신고-1 2
 
< 0.1%
2007-건축과-신축허가-4 2
 
< 0.1%
Other values (9787) 9980
99.8%
2023-12-13T08:13:32.931459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 30000
17.6%
0 18273
10.7%
18004
10.6%
2 14683
8.6%
1 11197
 
6.6%
9989
 
5.9%
9203
 
5.4%
8405
 
4.9%
8120
 
4.8%
8116
 
4.8%
Other values (47) 34504
20.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 75846
44.5%
Decimal Number 64548
37.9%
Dash Punctuation 30000
 
17.6%
Close Punctuation 50
 
< 0.1%
Open Punctuation 50
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18004
23.7%
9989
13.2%
9203
12.1%
8405
11.1%
8120
10.7%
8116
10.7%
2155
 
2.8%
1783
 
2.4%
1685
 
2.2%
1685
 
2.2%
Other values (34) 6701
 
8.8%
Decimal Number
ValueCountFrequency (%)
0 18273
28.3%
2 14683
22.7%
1 11197
17.3%
3 3513
 
5.4%
9 3262
 
5.1%
4 2888
 
4.5%
5 2826
 
4.4%
6 2817
 
4.4%
8 2548
 
3.9%
7 2541
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%
Close Punctuation
ValueCountFrequency (%)
) 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 94648
55.5%
Hangul 75846
44.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18004
23.7%
9989
13.2%
9203
12.1%
8405
11.1%
8120
10.7%
8116
10.7%
2155
 
2.8%
1783
 
2.4%
1685
 
2.2%
1685
 
2.2%
Other values (34) 6701
 
8.8%
Common
ValueCountFrequency (%)
- 30000
31.7%
0 18273
19.3%
2 14683
15.5%
1 11197
 
11.8%
3 3513
 
3.7%
9 3262
 
3.4%
4 2888
 
3.1%
5 2826
 
3.0%
6 2817
 
3.0%
8 2548
 
2.7%
Other values (3) 2641
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 94648
55.5%
Hangul 75846
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 30000
31.7%
0 18273
19.3%
2 14683
15.5%
1 11197
 
11.8%
3 3513
 
3.7%
9 3262
 
3.4%
4 2888
 
3.1%
5 2826
 
3.0%
6 2817
 
3.0%
8 2548
 
2.7%
Other values (3) 2641
 
2.8%
Hangul
ValueCountFrequency (%)
18004
23.7%
9989
13.2%
9203
12.1%
8405
11.1%
8120
10.7%
8116
10.7%
2155
 
2.8%
1783
 
2.4%
1685
 
2.2%
1685
 
2.2%
Other values (34) 6701
 
8.8%
Distinct8983
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T08:13:33.322161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length36
Mean length21.6126
Min length1

Characters and Unicode

Total characters216126
Distinct characters88
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8219 ?
Unique (%)82.2%

Sample

1st row인천광역시 미추홀구 도화동 369-1
2nd row인천광역시 미추홀구 숭의동 340-13
3rd row인천광역시 미추홀구 주안동 1582-2
4th row인천광역시 미추홀구 주안동 730-21 외1필지
5th row인천광역시 미추홀구 주안동 1560-3 외1필지
ValueCountFrequency (%)
인천광역시 9999
23.7%
미추홀구 9903
23.4%
주안동 3471
 
8.2%
용현동 2219
 
5.3%
도화동 1494
 
3.5%
외1필지 1493
 
3.5%
숭의동 1236
 
2.9%
학익동 707
 
1.7%
문학동 704
 
1.7%
외2필지 326
 
0.8%
Other values (8230) 10701
25.3%
2023-12-13T08:13:33.812090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32256
 
14.9%
10203
 
4.7%
10090
 
4.7%
10081
 
4.7%
10000
 
4.6%
10000
 
4.6%
9999
 
4.6%
1 9977
 
4.6%
9928
 
4.6%
9903
 
4.6%
Other values (78) 93689
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 127234
58.9%
Decimal Number 47051
 
21.8%
Space Separator 32256
 
14.9%
Dash Punctuation 9561
 
4.4%
Uppercase Letter 16
 
< 0.1%
Other Punctuation 5
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Letter Number 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10203
 
8.0%
10090
 
7.9%
10081
 
7.9%
10000
 
7.9%
10000
 
7.9%
9999
 
7.9%
9928
 
7.8%
9903
 
7.8%
9903
 
7.8%
9903
 
7.8%
Other values (55) 27224
21.4%
Decimal Number
ValueCountFrequency (%)
1 9977
21.2%
2 6234
13.2%
3 4815
10.2%
4 4555
9.7%
6 4509
9.6%
5 4354
9.3%
7 3634
 
7.7%
8 3340
 
7.1%
9 3040
 
6.5%
0 2593
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
L 6
37.5%
B 3
18.8%
T 3
18.8%
X 2
 
12.5%
I 1
 
6.2%
V 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Space Separator
ValueCountFrequency (%)
32256
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9561
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 127234
58.9%
Common 88875
41.1%
Latin 17
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10203
 
8.0%
10090
 
7.9%
10081
 
7.9%
10000
 
7.9%
10000
 
7.9%
9999
 
7.9%
9928
 
7.8%
9903
 
7.8%
9903
 
7.8%
9903
 
7.8%
Other values (55) 27224
21.4%
Common
ValueCountFrequency (%)
32256
36.3%
1 9977
 
11.2%
- 9561
 
10.8%
2 6234
 
7.0%
3 4815
 
5.4%
4 4555
 
5.1%
6 4509
 
5.1%
5 4354
 
4.9%
7 3634
 
4.1%
8 3340
 
3.8%
Other values (6) 5640
 
6.3%
Latin
ValueCountFrequency (%)
L 6
35.3%
B 3
17.6%
T 3
17.6%
X 2
 
11.8%
I 1
 
5.9%
1
 
5.9%
V 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 127234
58.9%
ASCII 88891
41.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32256
36.3%
1 9977
 
11.2%
- 9561
 
10.8%
2 6234
 
7.0%
3 4815
 
5.4%
4 4555
 
5.1%
6 4509
 
5.1%
5 4354
 
4.9%
7 3634
 
4.1%
8 3340
 
3.8%
Other values (12) 5656
 
6.4%
Hangul
ValueCountFrequency (%)
10203
 
8.0%
10090
 
7.9%
10081
 
7.9%
10000
 
7.9%
10000
 
7.9%
9999
 
7.9%
9928
 
7.8%
9903
 
7.8%
9903
 
7.8%
9903
 
7.8%
Other values (55) 27224
21.4%
Number Forms
ValueCountFrequency (%)
1
100.0%

지목
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
9114 
공장용지
 
295
<NA>
 
278
잡종지
 
69
주유소용지
 
45
Other values (15)
 
199

Length

Max length5
Median length1
Mean length1.235
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
9114
91.1%
공장용지 295
 
2.9%
<NA> 278
 
2.8%
잡종지 69
 
0.7%
주유소용지 45
 
0.4%
41
 
0.4%
종교용지 39
 
0.4%
학교용지 26
 
0.3%
임야 20
 
0.2%
18
 
0.2%
Other values (10) 55
 
0.5%

Length

2023-12-13T08:13:33.952270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9114
91.1%
공장용지 295
 
2.9%
na 278
 
2.8%
잡종지 69
 
0.7%
주유소용지 45
 
0.4%
41
 
0.4%
종교용지 39
 
0.4%
학교용지 26
 
0.3%
임야 20
 
0.2%
18
 
0.2%
Other values (10) 55
 
0.5%
Distinct4533
Distinct (%)45.3%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T08:13:34.293848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length4.7690307
Min length2

Characters and Unicode

Total characters47676
Distinct characters12
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

Unique2465 ?
Unique (%)24.7%

Sample

1st row342.1
2nd row222.5
3rd row298.2
4th row385
5th row367.1
ValueCountFrequency (%)
140 84
 
0.8%
149 26
 
0.3%
202 26
 
0.3%
165 22
 
0.2%
198 21
 
0.2%
141 21
 
0.2%
192 19
 
0.2%
826.4 19
 
0.2%
300 19
 
0.2%
195 19
 
0.2%
Other values (4523) 9721
97.2%
2023-12-13T08:13:34.804202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 7111
14.9%
1 6828
14.3%
2 5768
12.1%
3 4230
8.9%
4 3588
7.5%
5 3481
7.3%
6 3344
7.0%
0 3188
6.7%
7 3023
6.3%
8 3015
6.3%
Other values (2) 4100
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39422
82.7%
Other Punctuation 8254
 
17.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6828
17.3%
2 5768
14.6%
3 4230
10.7%
4 3588
9.1%
5 3481
8.8%
6 3344
8.5%
0 3188
8.1%
7 3023
7.7%
8 3015
7.6%
9 2957
7.5%
Other Punctuation
ValueCountFrequency (%)
. 7111
86.2%
, 1143
 
13.8%

Most occurring scripts

ValueCountFrequency (%)
Common 47676
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 7111
14.9%
1 6828
14.3%
2 5768
12.1%
3 4230
8.9%
4 3588
7.5%
5 3481
7.3%
6 3344
7.0%
0 3188
6.7%
7 3023
6.3%
8 3015
6.3%
Other values (2) 4100
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 7111
14.9%
1 6828
14.3%
2 5768
12.1%
3 4230
8.9%
4 3588
7.5%
5 3481
7.3%
6 3344
7.0%
0 3188
6.7%
7 3023
6.3%
8 3015
6.3%
Other values (2) 4100
8.6%
Distinct7829
Distinct (%)78.3%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T08:13:35.246848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length5.6793038
Min length1

Characters and Unicode

Total characters56776
Distinct characters12
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

Unique6249 ?
Unique (%)62.5%

Sample

1st row243.6
2nd row159.36
3rd row167.45
4th row180.68
5th row217.27
ValueCountFrequency (%)
1,273 8
 
0.1%
124.32 8
 
0.1%
83.22 8
 
0.1%
183.95 7
 
0.1%
96 7
 
0.1%
89.3 6
 
0.1%
83.2 6
 
0.1%
184.9 6
 
0.1%
132 6
 
0.1%
83.7 6
 
0.1%
Other values (7819) 9929
99.3%
2023-12-13T08:13:35.800652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9650
17.0%
1 8709
15.3%
2 5528
9.7%
8 4439
7.8%
4 4371
7.7%
6 4365
7.7%
3 4165
7.3%
9 4020
7.1%
5 3904
6.9%
7 3843
 
6.8%
Other values (2) 3782
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46481
81.9%
Other Punctuation 10295
 
18.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8709
18.7%
2 5528
11.9%
8 4439
9.6%
4 4371
9.4%
6 4365
9.4%
3 4165
9.0%
9 4020
8.6%
5 3904
8.4%
7 3843
8.3%
0 3137
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 9650
93.7%
, 645
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
Common 56776
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9650
17.0%
1 8709
15.3%
2 5528
9.7%
8 4439
7.8%
4 4371
7.7%
6 4365
7.7%
3 4165
7.3%
9 4020
7.1%
5 3904
6.9%
7 3843
 
6.8%
Other values (2) 3782
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56776
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9650
17.0%
1 8709
15.3%
2 5528
9.7%
8 4439
7.8%
4 4371
7.7%
6 4365
7.7%
3 4165
7.3%
9 4020
7.1%
5 3904
6.9%
7 3843
 
6.8%
Other values (2) 3782
 
6.7%
Distinct9122
Distinct (%)91.2%
Missing3
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-13T08:13:36.145373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6.229969
Min length1

Characters and Unicode

Total characters62281
Distinct characters12
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

Unique8450 ?
Unique (%)84.5%

Sample

1st row2,590.61
2nd row625.16
3rd row737.63
4th row659.13
5th row1,136.56
ValueCountFrequency (%)
659.76 10
 
0.1%
659.78 8
 
0.1%
659.94 7
 
0.1%
659.6 7
 
0.1%
659.52 7
 
0.1%
659.84 7
 
0.1%
635.58 6
 
0.1%
659.16 6
 
0.1%
659.58 6
 
0.1%
659.36 5
 
0.1%
Other values (9112) 9928
99.3%
2023-12-13T08:13:36.627582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9740
15.6%
4 5839
9.4%
1 5767
9.3%
6 5577
9.0%
2 5509
8.8%
5 5504
8.8%
3 5186
8.3%
9 4951
7.9%
8 4770
7.7%
7 4231
6.8%
Other values (2) 5207
8.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50438
81.0%
Other Punctuation 11843
 
19.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 5839
11.6%
1 5767
11.4%
6 5577
11.1%
2 5509
10.9%
5 5504
10.9%
3 5186
10.3%
9 4951
9.8%
8 4770
9.5%
7 4231
8.4%
0 3104
6.2%
Other Punctuation
ValueCountFrequency (%)
. 9740
82.2%
, 2103
 
17.8%

Most occurring scripts

ValueCountFrequency (%)
Common 62281
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9740
15.6%
4 5839
9.4%
1 5767
9.3%
6 5577
9.0%
2 5509
8.8%
5 5504
8.8%
3 5186
8.3%
9 4951
7.9%
8 4770
7.7%
7 4231
6.8%
Other values (2) 5207
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62281
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9740
15.6%
4 5839
9.4%
1 5767
9.3%
6 5577
9.0%
2 5509
8.8%
5 5504
8.8%
3 5186
8.3%
9 4951
7.9%
8 4770
7.7%
7 4231
6.8%
Other values (2) 5207
8.4%
Distinct1907
Distinct (%)90.0%
Missing7882
Missing (%)78.8%
Memory size156.2 KiB
2023-12-13T08:13:36.961618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.1010387
Min length1

Characters and Unicode

Total characters10804
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1751 ?
Unique (%)82.7%

Sample

1st row131.97
2nd row16.02
3rd row18.9
4th row244.21
5th row173.34
ValueCountFrequency (%)
0 18
 
0.8%
84 7
 
0.3%
18 6
 
0.3%
19.2 5
 
0.2%
23.04 5
 
0.2%
9 5
 
0.2%
7.5 4
 
0.2%
17.1 4
 
0.2%
30 4
 
0.2%
24 4
 
0.2%
Other values (1896) 2056
97.1%
2023-12-13T08:13:37.481149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1952
18.1%
1 1193
11.0%
2 1068
9.9%
4 999
9.2%
5 885
8.2%
3 876
8.1%
6 871
8.1%
8 844
7.8%
7 718
 
6.6%
9 687
 
6.4%
Other values (3) 711
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8663
80.2%
Other Punctuation 2130
 
19.7%
Dash Punctuation 11
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1193
13.8%
2 1068
12.3%
4 999
11.5%
5 885
10.2%
3 876
10.1%
6 871
10.1%
8 844
9.7%
7 718
8.3%
9 687
7.9%
0 522
6.0%
Other Punctuation
ValueCountFrequency (%)
. 1952
91.6%
, 178
 
8.4%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10804
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1952
18.1%
1 1193
11.0%
2 1068
9.9%
4 999
9.2%
5 885
8.2%
3 876
8.1%
6 871
8.1%
8 844
7.8%
7 718
 
6.6%
9 687
 
6.4%
Other values (3) 711
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10804
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1952
18.1%
1 1193
11.0%
2 1068
9.9%
4 999
9.2%
5 885
8.2%
3 876
8.1%
6 871
8.1%
8 844
7.8%
7 718
 
6.6%
9 687
 
6.4%
Other values (3) 711
 
6.6%
Distinct3900
Distinct (%)39.1%
Missing25
Missing (%)0.2%
Memory size156.2 KiB
2023-12-13T08:13:37.886922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.034787
Min length1

Characters and Unicode

Total characters50222
Distinct characters12
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

Unique2430 ?
Unique (%)24.4%

Sample

1st row71.21
2nd row71.62
3rd row56.15
4th row46.93
5th row59.19
ValueCountFrequency (%)
59.91 66
 
0.7%
59.94 61
 
0.6%
59.93 61
 
0.6%
59.87 61
 
0.6%
59.86 59
 
0.6%
59.82 57
 
0.6%
59.88 56
 
0.6%
59.76 54
 
0.5%
59.96 53
 
0.5%
59.95 52
 
0.5%
Other values (3890) 9395
94.2%
2023-12-13T08:13:38.438320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9896
19.7%
5 8960
17.8%
9 6443
12.8%
7 4605
9.2%
6 3953
 
7.9%
8 3839
 
7.6%
4 3329
 
6.6%
3 2886
 
5.7%
2 2594
 
5.2%
1 2500
 
5.0%
Other values (2) 1217
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 40325
80.3%
Other Punctuation 9897
 
19.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 8960
22.2%
9 6443
16.0%
7 4605
11.4%
6 3953
9.8%
8 3839
9.5%
4 3329
 
8.3%
3 2886
 
7.2%
2 2594
 
6.4%
1 2500
 
6.2%
0 1216
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 9896
> 99.9%
, 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 50222
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9896
19.7%
5 8960
17.8%
9 6443
12.8%
7 4605
9.2%
6 3953
 
7.9%
8 3839
 
7.6%
4 3329
 
6.6%
3 2886
 
5.7%
2 2594
 
5.2%
1 2500
 
5.0%
Other values (2) 1217
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50222
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9896
19.7%
5 8960
17.8%
9 6443
12.8%
7 4605
9.2%
6 3953
 
7.9%
8 3839
 
7.6%
4 3329
 
6.6%
3 2886
 
5.7%
2 2594
 
5.2%
1 2500
 
5.0%
Other values (2) 1217
 
2.4%
Distinct8459
Distinct (%)84.9%
Missing35
Missing (%)0.4%
Memory size156.2 KiB
2023-12-13T08:13:38.851640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length5.8097341
Min length1

Characters and Unicode

Total characters57894
Distinct characters12
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

Unique7221 ?
Unique (%)72.5%

Sample

1st row698.82
2nd row280.97
3rd row247.06
4th row171.2
5th row305.79
ValueCountFrequency (%)
199.86 7
 
0.1%
230.79 6
 
0.1%
199.69 6
 
0.1%
129.33 5
 
0.1%
249.64 5
 
0.1%
119.58 5
 
0.1%
59.96 5
 
0.1%
199.95 5
 
0.1%
199.83 5
 
0.1%
199.65 4
 
< 0.1%
Other values (8449) 9912
99.5%
2023-12-13T08:13:39.415324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9873
17.1%
2 7460
12.9%
1 7285
12.6%
3 4833
8.3%
9 4723
8.2%
4 4532
7.8%
7 4274
7.4%
5 4090
7.1%
8 4080
7.0%
6 4029
7.0%
Other values (2) 2715
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48016
82.9%
Other Punctuation 9878
 
17.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 7460
15.5%
1 7285
15.2%
3 4833
10.1%
9 4723
9.8%
4 4532
9.4%
7 4274
8.9%
5 4090
8.5%
8 4080
8.5%
6 4029
8.4%
0 2710
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 9873
99.9%
, 5
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 57894
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9873
17.1%
2 7460
12.9%
1 7285
12.6%
3 4833
8.3%
9 4723
8.2%
4 4532
7.8%
7 4274
7.4%
5 4090
7.1%
8 4080
7.0%
6 4029
7.0%
Other values (2) 2715
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57894
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9873
17.1%
2 7460
12.9%
1 7285
12.6%
3 4833
8.3%
9 4723
8.2%
4 4532
7.8%
7 4274
7.4%
5 4090
7.1%
8 4080
7.0%
6 4029
7.0%
Other values (2) 2715
 
4.7%

구조
Categorical

IMBALANCE 

Distinct24
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
철근콘크리트구조
7143 
일반철골구조
1141 
벽돌구조
 
604
경량철골구조
 
559
<NA>
 
271
Other values (19)
 
282

Length

Max length12
Median length8
Mean length7.2701
Min length3

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 7143
71.4%
일반철골구조 1141
 
11.4%
벽돌구조 604
 
6.0%
경량철골구조 559
 
5.6%
<NA> 271
 
2.7%
철골철근콘크리트구조 65
 
0.7%
기타조적구조 57
 
0.6%
블록구조 44
 
0.4%
기타강구조 22
 
0.2%
강파이프구조 21
 
0.2%
Other values (14) 73
 
0.7%

Length

2023-12-13T08:13:39.548873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
철근콘크리트구조 7143
71.4%
일반철골구조 1141
 
11.4%
벽돌구조 604
 
6.0%
경량철골구조 559
 
5.6%
na 271
 
2.7%
철골철근콘크리트구조 65
 
0.7%
기타조적구조 57
 
0.6%
블록구조 44
 
0.4%
기타강구조 22
 
0.2%
강파이프구조 21
 
0.2%
Other values (14) 73
 
0.7%
Distinct4320
Distinct (%)43.2%
Missing5
Missing (%)< 0.1%
Memory size156.2 KiB
Minimum1982-06-16 00:00:00
Maximum2023-03-17 00:00:00
2023-12-13T08:13:39.666655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:13:39.793149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최종설계변경일
Text

MISSING 

Distinct1699
Distinct (%)73.8%
Missing7697
Missing (%)77.0%
Memory size156.2 KiB
2023-12-13T08:13:40.088174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9982631
Min length8

Characters and Unicode

Total characters23026
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

Unique1281 ?
Unique (%)55.6%

Sample

1st row2015-07-29
2nd row2023-01-26
3rd row2004-09-21
4th row2010-10-19
5th row2002-01-15
ValueCountFrequency (%)
2001-09-25 7
 
0.3%
2001-11-09 6
 
0.3%
2003-12-02 6
 
0.3%
2001-08-31 6
 
0.3%
2002-12-12 5
 
0.2%
2002-05-22 5
 
0.2%
2001-12-07 5
 
0.2%
2001-09-21 5
 
0.2%
2001-12-06 5
 
0.2%
2002-03-13 5
 
0.2%
Other values (1689) 2248
97.6%
2023-12-13T08:13:40.572918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6468
28.1%
- 4606
20.0%
2 4183
18.2%
1 3342
14.5%
3 825
 
3.6%
9 738
 
3.2%
6 625
 
2.7%
5 573
 
2.5%
8 556
 
2.4%
4 556
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18420
80.0%
Dash Punctuation 4606
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6468
35.1%
2 4183
22.7%
1 3342
18.1%
3 825
 
4.5%
9 738
 
4.0%
6 625
 
3.4%
5 573
 
3.1%
8 556
 
3.0%
4 556
 
3.0%
7 554
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 4606
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23026
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6468
28.1%
- 4606
20.0%
2 4183
18.2%
1 3342
14.5%
3 825
 
3.6%
9 738
 
3.2%
6 625
 
2.7%
5 573
 
2.5%
8 556
 
2.4%
4 556
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23026
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6468
28.1%
- 4606
20.0%
2 4183
18.2%
1 3342
14.5%
3 825
 
3.6%
9 738
 
3.2%
6 625
 
2.7%
5 573
 
2.5%
8 556
 
2.4%
4 556
 
2.4%
Distinct4368
Distinct (%)43.9%
Missing39
Missing (%)0.4%
Memory size156.2 KiB
2023-12-13T08:13:40.848243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9857444
Min length6

Characters and Unicode

Total characters99468
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2096 ?
Unique (%)21.0%

Sample

1st row2015-05-08
2nd row2009-02-20
3rd row2001-06-07
4th row2002-09-04
5th row2022-05-03
ValueCountFrequency (%)
2003-06-30 45
 
0.5%
2003-06-28 33
 
0.3%
2001-09-24 22
 
0.2%
2001-05-16 20
 
0.2%
2001-08-24 20
 
0.2%
2001-08-14 19
 
0.2%
2001-10-11 19
 
0.2%
2001-10-24 18
 
0.2%
2001-08-16 18
 
0.2%
2001-07-07 18
 
0.2%
Other values (4358) 9729
97.7%
2023-12-13T08:13:41.515855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28752
28.9%
- 19922
20.0%
2 17346
17.4%
1 13846
13.9%
3 3390
 
3.4%
9 3217
 
3.2%
6 2732
 
2.7%
8 2641
 
2.7%
5 2547
 
2.6%
4 2546
 
2.6%
Other values (2) 2529
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79545
80.0%
Dash Punctuation 19922
 
20.0%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28752
36.1%
2 17346
21.8%
1 13846
17.4%
3 3390
 
4.3%
9 3217
 
4.0%
6 2732
 
3.4%
8 2641
 
3.3%
5 2547
 
3.2%
4 2546
 
3.2%
7 2528
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 19922
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99468
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28752
28.9%
- 19922
20.0%
2 17346
17.4%
1 13846
13.9%
3 3390
 
3.4%
9 3217
 
3.2%
6 2732
 
2.7%
8 2641
 
2.7%
5 2547
 
2.6%
4 2546
 
2.6%
Other values (2) 2529
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99468
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28752
28.9%
- 19922
20.0%
2 17346
17.4%
1 13846
13.9%
3 3390
 
3.4%
9 3217
 
3.2%
6 2732
 
2.7%
8 2641
 
2.7%
5 2547
 
2.6%
4 2546
 
2.6%
Other values (2) 2529
 
2.5%

착공예정일
Text

MISSING 

Distinct4278
Distinct (%)46.0%
Missing693
Missing (%)6.9%
Memory size156.2 KiB
2023-12-13T08:13:41.798984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.8960997
Min length6

Characters and Unicode

Total characters92103
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2150 ?
Unique (%)23.1%

Sample

1st row2015-05-11
2nd row2009-02-18
3rd row2001-06-07
4th row2002-09-05
5th row2022-05-01
ValueCountFrequency (%)
2003-06-30 68
 
0.7%
2000 26
 
0.3%
2000-09 24
 
0.3%
2000-08 21
 
0.2%
2003-07-01 21
 
0.2%
2001-11 21
 
0.2%
2001-08-16 20
 
0.2%
2001-08-24 19
 
0.2%
2001-10-24 18
 
0.2%
2001-08-30 18
 
0.2%
Other values (4269) 9053
97.2%
2023-12-13T08:13:42.212541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26930
29.2%
- 18614
20.2%
2 16153
17.5%
1 12704
13.8%
3 3162
 
3.4%
5 2595
 
2.8%
6 2486
 
2.7%
8 2471
 
2.7%
9 2431
 
2.6%
7 2307
 
2.5%
Other values (2) 2250
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73485
79.8%
Dash Punctuation 18614
 
20.2%
Space Separator 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26930
36.6%
2 16153
22.0%
1 12704
17.3%
3 3162
 
4.3%
5 2595
 
3.5%
6 2486
 
3.4%
8 2471
 
3.4%
9 2431
 
3.3%
7 2307
 
3.1%
4 2246
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 18614
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 92103
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26930
29.2%
- 18614
20.2%
2 16153
17.5%
1 12704
13.8%
3 3162
 
3.4%
5 2595
 
2.8%
6 2486
 
2.7%
8 2471
 
2.7%
9 2431
 
2.6%
7 2307
 
2.5%
Other values (2) 2250
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 92103
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26930
29.2%
- 18614
20.2%
2 16153
17.5%
1 12704
13.8%
3 3162
 
3.4%
5 2595
 
2.8%
6 2486
 
2.7%
8 2471
 
2.7%
9 2431
 
2.6%
7 2307
 
2.5%
Other values (2) 2250
 
2.4%

사용승인일
Text

MISSING 

Distinct4225
Distinct (%)45.3%
Missing670
Missing (%)6.7%
Memory size156.2 KiB
2023-12-13T08:13:42.539864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9993569
Min length6

Characters and Unicode

Total characters93294
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

Unique1984 ?
Unique (%)21.3%

Sample

1st row2016-01-12
2nd row2009-07-16
3rd row2001-09-24
4th row2003-01-09
5th row2002-02-20
ValueCountFrequency (%)
2002-05-31 18
 
0.2%
2002-12-20 16
 
0.2%
2002-07-23 16
 
0.2%
2001-12-13 15
 
0.2%
2002-03-19 15
 
0.2%
2002-02-27 14
 
0.2%
2001-12-28 14
 
0.2%
2001-12-20 14
 
0.2%
2002-01-09 14
 
0.2%
2002-11-04 13
 
0.1%
Other values (4215) 9181
98.4%
2023-12-13T08:13:43.006767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 26348
28.2%
- 18660
20.0%
2 17584
18.8%
1 13117
14.1%
3 3182
 
3.4%
9 2732
 
2.9%
7 2423
 
2.6%
4 2365
 
2.5%
6 2354
 
2.5%
5 2270
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74634
80.0%
Dash Punctuation 18660
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 26348
35.3%
2 17584
23.6%
1 13117
17.6%
3 3182
 
4.3%
9 2732
 
3.7%
7 2423
 
3.2%
4 2365
 
3.2%
6 2354
 
3.2%
5 2270
 
3.0%
8 2259
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 18660
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 93294
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 26348
28.2%
- 18660
20.0%
2 17584
18.8%
1 13117
14.1%
3 3182
 
3.4%
9 2732
 
2.9%
7 2423
 
2.6%
4 2365
 
2.5%
6 2354
 
2.5%
5 2270
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93294
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 26348
28.2%
- 18660
20.0%
2 17584
18.8%
1 13117
14.1%
3 3182
 
3.4%
9 2732
 
2.9%
7 2423
 
2.6%
4 2365
 
2.5%
6 2354
 
2.5%
5 2270
 
2.4%
Distinct4234
Distinct (%)42.9%
Missing130
Missing (%)1.3%
Memory size156.2 KiB
Minimum1982-06-16 00:00:00
Maximum2023-02-20 00:00:00
2023-12-13T08:13:43.152198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:13:43.307202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최대지상층수
Real number (ℝ)

MISSING  SKEWED 

Distinct31
Distinct (%)0.3%
Missing173
Missing (%)1.7%
Infinite0
Infinite (%)0.0%
Mean4.3050778
Minimum0
Maximum523
Zeros11
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:43.437673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median4
Q35
95-th percentile9
Maximum523
Range523
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.8885035
Coefficient of variation (CV)1.3678042
Kurtosis6128.6957
Mean4.3050778
Median Absolute Deviation (MAD)1
Skewness69.844402
Sum42306
Variance34.674474
MonotonicityNot monotonic
2023-12-13T08:13:43.565252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
5 2555
25.6%
4 2072
20.7%
3 1458
14.6%
2 1427
14.3%
1 887
 
8.9%
6 494
 
4.9%
7 232
 
2.3%
8 150
 
1.5%
10 120
 
1.2%
14 107
 
1.1%
Other values (21) 325
 
3.2%
(Missing) 173
 
1.7%
ValueCountFrequency (%)
0 11
 
0.1%
1 887
 
8.9%
2 1427
14.3%
3 1458
14.6%
4 2072
20.7%
5 2555
25.6%
6 494
 
4.9%
7 232
 
2.3%
8 150
 
1.5%
9 99
 
1.0%
ValueCountFrequency (%)
523 1
< 0.1%
44 1
< 0.1%
37 1
< 0.1%
35 1
< 0.1%
32 1
< 0.1%
27 1
< 0.1%
26 2
< 0.1%
25 1
< 0.1%
24 2
< 0.1%
23 1
< 0.1%

최대지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.1%
Missing3238
Missing (%)32.4%
Infinite0
Infinite (%)0.0%
Mean0.45829636
Minimum0
Maximum7
Zeros4062
Zeros (%)40.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:43.672686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.64614493
Coefficient of variation (CV)1.4098845
Kurtosis8.0112655
Mean0.45829636
Median Absolute Deviation (MAD)0
Skewness1.9519717
Sum3099
Variance0.41750326
MonotonicityNot monotonic
2023-12-13T08:13:43.853030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 4062
40.6%
1 2413
24.1%
2 216
 
2.2%
3 45
 
0.4%
4 15
 
0.1%
5 8
 
0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
(Missing) 3238
32.4%
ValueCountFrequency (%)
0 4062
40.6%
1 2413
24.1%
2 216
 
2.2%
3 45
 
0.4%
4 15
 
0.1%
5 8
 
0.1%
6 2
 
< 0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
6 2
 
< 0.1%
5 8
 
0.1%
4 15
 
0.1%
3 45
 
0.4%
2 216
 
2.2%
1 2413
24.1%
0 4062
40.6%

최고높이(m)
Text

MISSING 

Distinct1229
Distinct (%)12.9%
Missing497
Missing (%)5.0%
Memory size156.2 KiB
2023-12-13T08:13:44.251668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.7379775
Min length1

Characters and Unicode

Total characters35522
Distinct characters12
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

Unique629 ?
Unique (%)6.6%

Sample

1st row40.3
2nd row15.9
3rd row16.4
4th row14.6
5th row25.9
ValueCountFrequency (%)
14.6 158
 
1.7%
14.3 137
 
1.4%
14.4 131
 
1.4%
14.7 121
 
1.3%
12.8 121
 
1.3%
14.5 118
 
1.2%
14.2 104
 
1.1%
14.8 103
 
1.1%
9.1 99
 
1.0%
12.9 94
 
1.0%
Other values (1219) 8317
87.5%
2023-12-13T08:13:44.819662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 8563
24.1%
1 7669
21.6%
5 3030
 
8.5%
2 2912
 
8.2%
4 2838
 
8.0%
3 2427
 
6.8%
7 1979
 
5.6%
6 1819
 
5.1%
9 1729
 
4.9%
8 1555
 
4.4%
Other values (2) 1001
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26953
75.9%
Other Punctuation 8569
 
24.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7669
28.5%
5 3030
 
11.2%
2 2912
 
10.8%
4 2838
 
10.5%
3 2427
 
9.0%
7 1979
 
7.3%
6 1819
 
6.7%
9 1729
 
6.4%
8 1555
 
5.8%
0 995
 
3.7%
Other Punctuation
ValueCountFrequency (%)
. 8563
99.9%
, 6
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 35522
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 8563
24.1%
1 7669
21.6%
5 3030
 
8.5%
2 2912
 
8.2%
4 2838
 
8.0%
3 2427
 
6.8%
7 1979
 
5.6%
6 1819
 
5.1%
9 1729
 
4.9%
8 1555
 
4.4%
Other values (2) 1001
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35522
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 8563
24.1%
1 7669
21.6%
5 3030
 
8.5%
2 2912
 
8.2%
4 2838
 
8.0%
3 2427
 
6.8%
7 1979
 
5.6%
6 1819
 
5.1%
9 1729
 
4.9%
8 1555
 
4.4%
Other values (2) 1001
 
2.8%

동수
Real number (ℝ)

ZEROS 

Distinct36
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3062
Minimum0
Maximum83
Zeros434
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:44.971599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum83
Range83
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.8832747
Coefficient of variation (CV)2.2073761
Kurtosis429.12286
Mean1.3062
Median Absolute Deviation (MAD)0
Skewness18.954761
Sum13062
Variance8.3132729
MonotonicityNot monotonic
2023-12-13T08:13:45.124362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1 8509
85.1%
2 692
 
6.9%
0 434
 
4.3%
3 140
 
1.4%
4 64
 
0.6%
5 28
 
0.3%
7 27
 
0.3%
6 19
 
0.2%
8 9
 
0.1%
13 8
 
0.1%
Other values (26) 70
 
0.7%
ValueCountFrequency (%)
0 434
 
4.3%
1 8509
85.1%
2 692
 
6.9%
3 140
 
1.4%
4 64
 
0.6%
5 28
 
0.3%
6 19
 
0.2%
7 27
 
0.3%
8 9
 
0.1%
9 4
 
< 0.1%
ValueCountFrequency (%)
83 1
 
< 0.1%
73 2
< 0.1%
72 3
< 0.1%
71 1
 
< 0.1%
70 1
 
< 0.1%
69 2
< 0.1%
68 1
 
< 0.1%
38 4
< 0.1%
37 2
< 0.1%
36 3
< 0.1%

승강기합
Real number (ℝ)

MISSING  ZEROS 

Distinct16
Distinct (%)0.6%
Missing7096
Missing (%)71.0%
Infinite0
Infinite (%)0.0%
Mean0.95592287
Minimum0
Maximum25
Zeros719
Zeros (%)7.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:45.265532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile2
Maximum25
Range25
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1531619
Coefficient of variation (CV)1.2063336
Kurtosis135.00876
Mean0.95592287
Median Absolute Deviation (MAD)0
Skewness8.8016751
Sum2776
Variance1.3297823
MonotonicityNot monotonic
2023-12-13T08:13:45.395554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 1896
 
19.0%
0 719
 
7.2%
2 190
 
1.9%
3 36
 
0.4%
4 30
 
0.3%
5 12
 
0.1%
6 8
 
0.1%
8 2
 
< 0.1%
7 2
 
< 0.1%
12 2
 
< 0.1%
Other values (6) 7
 
0.1%
(Missing) 7096
71.0%
ValueCountFrequency (%)
0 719
 
7.2%
1 1896
19.0%
2 190
 
1.9%
3 36
 
0.4%
4 30
 
0.3%
5 12
 
0.1%
6 8
 
0.1%
7 2
 
< 0.1%
8 2
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
25 1
 
< 0.1%
20 2
 
< 0.1%
15 1
 
< 0.1%
12 2
 
< 0.1%
11 1
 
< 0.1%
10 1
 
< 0.1%
9 1
 
< 0.1%
8 2
 
< 0.1%
7 2
 
< 0.1%
6 8
0.1%

비상승강기합
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)1.6%
Missing9427
Missing (%)94.3%
Infinite0
Infinite (%)0.0%
Mean0.48516579
Minimum0
Maximum16
Zeros406
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:45.558982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum16
Range16
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.186406
Coefficient of variation (CV)2.4453621
Kurtosis65.653839
Mean0.48516579
Median Absolute Deviation (MAD)0
Skewness6.4932272
Sum278
Variance1.4075593
MonotonicityNot monotonic
2023-12-13T08:13:45.704806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 406
 
4.1%
1 115
 
1.1%
2 32
 
0.3%
4 9
 
0.1%
3 7
 
0.1%
7 1
 
< 0.1%
11 1
 
< 0.1%
8 1
 
< 0.1%
16 1
 
< 0.1%
(Missing) 9427
94.3%
ValueCountFrequency (%)
0 406
4.1%
1 115
 
1.1%
2 32
 
0.3%
3 7
 
0.1%
4 9
 
0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
11 1
 
< 0.1%
16 1
 
< 0.1%
ValueCountFrequency (%)
16 1
 
< 0.1%
11 1
 
< 0.1%
8 1
 
< 0.1%
7 1
 
< 0.1%
4 9
 
0.1%
3 7
 
0.1%
2 32
 
0.3%
1 115
 
1.1%
0 406
4.1%

하수처리시설명
Categorical

IMBALANCE 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부패탱크방법
8290 
접촉폭기방법
 
497
<NA>
 
299
현수미생물접촉방법
 
251
기타단독정화조
 
177
Other values (20)
 
486

Length

Max length13
Median length6
Mean length6.1432
Min length4

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row부패탱크방법
2nd row부패탱크방법
3rd row부패탱크방법
4th row부패탱크방법
5th row기타단독정화조

Common Values

ValueCountFrequency (%)
부패탱크방법 8290
82.9%
접촉폭기방법 497
 
5.0%
<NA> 299
 
3.0%
현수미생물접촉방법 251
 
2.5%
기타단독정화조 177
 
1.8%
기타오수처리시설 173
 
1.7%
혐기및호기성미생물조정방법 83
 
0.8%
접촉산화방법 73
 
0.7%
하수종말처리장연결 36
 
0.4%
임호프탱크방법 21
 
0.2%
Other values (15) 100
 
1.0%

Length

2023-12-13T08:13:45.877031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부패탱크방법 8290
82.9%
접촉폭기방법 497
 
5.0%
na 299
 
3.0%
현수미생물접촉방법 251
 
2.5%
기타단독정화조 177
 
1.8%
기타오수처리시설 173
 
1.7%
혐기및호기성미생물조정방법 83
 
0.8%
접촉산화방법 73
 
0.7%
하수종말처리장연결 36
 
0.4%
임호프탱크방법 21
 
0.2%
Other values (15) 100
 
1.0%
Distinct591
Distinct (%)22.6%
Missing7390
Missing (%)73.9%
Memory size156.2 KiB
2023-12-13T08:13:46.227995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length2.8854406
Min length1

Characters and Unicode

Total characters7531
Distinct characters12
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

Unique361 ?
Unique (%)13.8%

Sample

1st row6.24
2nd row5.365
3rd row5
4th row70
5th row12
ValueCountFrequency (%)
0 116
 
4.4%
8 99
 
3.8%
5 90
 
3.4%
6 86
 
3.3%
12 75
 
2.9%
10 70
 
2.7%
7.2 67
 
2.6%
6.1 64
 
2.5%
2 59
 
2.3%
4 47
 
1.8%
Other values (581) 1837
70.4%
2023-12-13T08:13:46.764157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1423
18.9%
1 924
12.3%
6 815
10.8%
2 764
10.1%
5 742
9.9%
0 682
9.1%
4 595
7.9%
8 516
 
6.9%
3 462
 
6.1%
7 405
 
5.4%
Other values (2) 203
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6095
80.9%
Other Punctuation 1436
 
19.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 924
15.2%
6 815
13.4%
2 764
12.5%
5 742
12.2%
0 682
11.2%
4 595
9.8%
8 516
8.5%
3 462
7.6%
7 405
6.6%
9 190
 
3.1%
Other Punctuation
ValueCountFrequency (%)
. 1423
99.1%
, 13
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Common 7531
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1423
18.9%
1 924
12.3%
6 815
10.8%
2 764
10.1%
5 742
9.9%
0 682
9.1%
4 595
7.9%
8 516
 
6.9%
3 462
 
6.1%
7 405
 
5.4%
Other values (2) 203
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7531
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1423
18.9%
1 924
12.3%
6 815
10.8%
2 764
10.1%
5 742
9.9%
0 682
9.1%
4 595
7.9%
8 516
 
6.9%
3 462
 
6.1%
7 405
 
5.4%
Other values (2) 203
 
2.7%

주용도
Categorical

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
공동주택
3498 
단독주택
2015 
제2종근린생활시설
1555 
제1종근린생활시설
931 
공장
709 
Other values (23)
1292 

Length

Max length10
Median length4
Mean length5.2351
Min length2

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
공동주택 3498
35.0%
단독주택 2015
20.2%
제2종근린생활시설 1555
15.6%
제1종근린생활시설 931
 
9.3%
공장 709
 
7.1%
업무시설 495
 
5.0%
숙박시설 136
 
1.4%
노유자시설 114
 
1.1%
자동차관련시설 101
 
1.0%
문화및집회시설 68
 
0.7%
Other values (18) 378
 
3.8%

Length

2023-12-13T08:13:46.952424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공동주택 3498
35.0%
단독주택 2015
20.2%
제2종근린생활시설 1555
15.6%
제1종근린생활시설 931
 
9.3%
공장 709
 
7.1%
업무시설 495
 
5.0%
숙박시설 136
 
1.4%
노유자시설 114
 
1.1%
자동차관련시설 101
 
1.0%
문화및집회시설 68
 
0.7%
Other values (18) 378
 
3.8%

부속용도
Text

MISSING 

Distinct1567
Distinct (%)20.7%
Missing2440
Missing (%)24.4%
Memory size156.2 KiB
2023-12-13T08:13:47.210439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length39
Mean length6.7580688
Min length1

Characters and Unicode

Total characters51091
Distinct characters251
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1148 ?
Unique (%)15.2%

Sample

1st row아파트
2nd row다세대주택/제1종근린생활시설
3rd row근,생(소매점,사무소)
4th row다세대주택
5th row제1,2종근린생활시설
ValueCountFrequency (%)
다세대주택 2065
23.2%
다가구주택 716
 
8.0%
472
 
5.3%
근린생활시설 365
 
4.1%
주택 332
 
3.7%
오피스텔 289
 
3.2%
단독주택 249
 
2.8%
소매점 182
 
2.0%
다세대 181
 
2.0%
일반음식점 172
 
1.9%
Other values (1191) 3875
43.5%
2023-12-13T08:13:47.697161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4619
 
9.0%
4560
 
8.9%
3729
 
7.3%
2671
 
5.2%
2664
 
5.2%
2091
 
4.1%
1774
 
3.5%
1726
 
3.4%
1497
 
2.9%
1392
 
2.7%
Other values (241) 24368
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45901
89.8%
Space Separator 1357
 
2.7%
Other Punctuation 1352
 
2.6%
Decimal Number 910
 
1.8%
Close Punctuation 739
 
1.4%
Open Punctuation 733
 
1.4%
Dash Punctuation 72
 
0.1%
Uppercase Letter 15
 
< 0.1%
Math Symbol 11
 
< 0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4619
 
10.1%
4560
 
9.9%
3729
 
8.1%
2671
 
5.8%
2664
 
5.8%
2091
 
4.6%
1774
 
3.9%
1726
 
3.8%
1497
 
3.3%
1392
 
3.0%
Other values (213) 19178
41.8%
Decimal Number
ValueCountFrequency (%)
2 431
47.4%
1 389
42.7%
8 27
 
3.0%
0 14
 
1.5%
3 11
 
1.2%
6 10
 
1.1%
4 8
 
0.9%
5 8
 
0.9%
7 7
 
0.8%
9 5
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 1053
77.9%
/ 217
 
16.1%
. 69
 
5.1%
: 9
 
0.7%
& 4
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
P 5
33.3%
T 4
26.7%
A 4
26.7%
L 1
 
6.7%
G 1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 733
99.2%
] 6
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 727
99.2%
[ 6
 
0.8%
Space Separator
ValueCountFrequency (%)
1357
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%
Math Symbol
ValueCountFrequency (%)
+ 11
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45901
89.8%
Common 5175
 
10.1%
Latin 15
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4619
 
10.1%
4560
 
9.9%
3729
 
8.1%
2671
 
5.8%
2664
 
5.8%
2091
 
4.6%
1774
 
3.9%
1726
 
3.8%
1497
 
3.3%
1392
 
3.0%
Other values (213) 19178
41.8%
Common
ValueCountFrequency (%)
1357
26.2%
, 1053
20.3%
) 733
14.2%
( 727
14.0%
2 431
 
8.3%
1 389
 
7.5%
/ 217
 
4.2%
- 72
 
1.4%
. 69
 
1.3%
8 27
 
0.5%
Other values (13) 100
 
1.9%
Latin
ValueCountFrequency (%)
P 5
33.3%
T 4
26.7%
A 4
26.7%
L 1
 
6.7%
G 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45901
89.8%
ASCII 5190
 
10.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4619
 
10.1%
4560
 
9.9%
3729
 
8.1%
2671
 
5.8%
2664
 
5.8%
2091
 
4.6%
1774
 
3.9%
1726
 
3.8%
1497
 
3.3%
1392
 
3.0%
Other values (213) 19178
41.8%
ASCII
ValueCountFrequency (%)
1357
26.1%
, 1053
20.3%
) 733
14.1%
( 727
14.0%
2 431
 
8.3%
1 389
 
7.5%
/ 217
 
4.2%
- 72
 
1.4%
. 69
 
1.3%
8 27
 
0.5%
Other values (18) 115
 
2.2%

용도지역
Categorical

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
제2종일반주거지역
2217 
일반주거지역
2204 
일반상업지역
2127 
준주거지역
1841 
일반공업지역
603 
Other values (18)
1008 

Length

Max length10
Median length9
Mean length6.4904
Min length4

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st row일반상업지역
2nd row일반상업지역
3rd row일반주거지역
4th row일반주거지역
5th row준주거지역

Common Values

ValueCountFrequency (%)
제2종일반주거지역 2217
22.2%
일반주거지역 2204
22.0%
일반상업지역 2127
21.3%
준주거지역 1841
18.4%
일반공업지역 603
 
6.0%
준공업지역 296
 
3.0%
제1종일반주거지역 241
 
2.4%
도시지역 174
 
1.7%
<NA> 131
 
1.3%
제3종일반주거지역 85
 
0.9%
Other values (13) 81
 
0.8%

Length

2023-12-13T08:13:47.868041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2종일반주거지역 2217
22.2%
일반주거지역 2204
22.0%
일반상업지역 2127
21.3%
준주거지역 1841
18.4%
일반공업지역 603
 
6.0%
준공업지역 296
 
3.0%
제1종일반주거지역 241
 
2.4%
도시지역 174
 
1.7%
na 131
 
1.3%
제3종일반주거지역 85
 
0.9%
Other values (13) 81
 
0.8%

용도지구
Categorical

IMBALANCE 

Distinct27
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
6507 
방화지구
1919 
일반미관지구
817 
최고고도지구
 
224
중심지미관지구
 
156
Other values (22)
 
377

Length

Max length11
Median length4
Mean length4.3452
Min length4

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 6507
65.1%
방화지구 1919
 
19.2%
일반미관지구 817
 
8.2%
최고고도지구 224
 
2.2%
중심지미관지구 156
 
1.6%
주거환경개선지구 109
 
1.1%
주차장정비지구 68
 
0.7%
고도지구 37
 
0.4%
기타지구 29
 
0.3%
산업단지 24
 
0.2%
Other values (17) 110
 
1.1%

Length

2023-12-13T08:13:48.022005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 6507
65.1%
방화지구 1919
 
19.2%
일반미관지구 817
 
8.2%
최고고도지구 224
 
2.2%
중심지미관지구 156
 
1.6%
주거환경개선지구 109
 
1.1%
주차장정비지구 68
 
0.7%
고도지구 37
 
0.4%
기타지구 29
 
0.3%
산업단지 24
 
0.2%
Other values (17) 110
 
1.1%

용도구역
Categorical

IMBALANCE 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8340 
상대보호구역
 
513
제1종지구단위계획구역
 
420
지구단위계획구역
 
261
상대정화구역
 
127
Other values (17)
 
339

Length

Max length11
Median length4
Mean length4.5839
Min length4

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8340
83.4%
상대보호구역 513
 
5.1%
제1종지구단위계획구역 420
 
4.2%
지구단위계획구역 261
 
2.6%
상대정화구역 127
 
1.3%
상세계획구역 114
 
1.1%
산업시설구역 82
 
0.8%
기타구역 76
 
0.8%
절대정화구역 18
 
0.2%
도시계획구역 17
 
0.2%
Other values (12) 32
 
0.3%

Length

2023-12-13T08:13:48.183909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8340
83.4%
상대보호구역 513
 
5.1%
제1종지구단위계획구역 420
 
4.2%
지구단위계획구역 261
 
2.6%
상대정화구역 127
 
1.3%
상세계획구역 114
 
1.1%
산업시설구역 82
 
0.8%
기타구역 76
 
0.8%
절대정화구역 18
 
0.2%
도시계획구역 17
 
0.2%
Other values (13) 36
 
0.4%
Distinct136
Distinct (%)3.9%
Missing6519
Missing (%)65.2%
Memory size156.2 KiB
2023-12-13T08:13:48.485242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.2392991
Min length1

Characters and Unicode

Total characters4314
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

Unique61 ?
Unique (%)1.8%

Sample

1st row7
2nd row6
3rd row14
4th row7
5th row36
ValueCountFrequency (%)
8 539
15.5%
4 499
14.3%
2 310
8.9%
3 294
 
8.4%
6 281
 
8.1%
5 260
 
7.5%
1 204
 
5.9%
7 171
 
4.9%
0 105
 
3.0%
10 83
 
2.4%
Other values (126) 735
21.1%
2023-12-13T08:13:48.977885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 757
17.5%
4 629
14.6%
8 603
14.0%
2 558
12.9%
3 426
9.9%
6 373
8.6%
5 345
8.0%
7 248
 
5.7%
0 241
 
5.6%
9 127
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4307
99.8%
Other Punctuation 7
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 757
17.6%
4 629
14.6%
8 603
14.0%
2 558
13.0%
3 426
9.9%
6 373
8.7%
5 345
8.0%
7 248
 
5.8%
0 241
 
5.6%
9 127
 
2.9%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4314
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 757
17.5%
4 629
14.6%
8 603
14.0%
2 558
12.9%
3 426
9.9%
6 373
8.6%
5 345
8.0%
7 248
 
5.7%
0 241
 
5.6%
9 127
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4314
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 757
17.5%
4 629
14.6%
8 603
14.0%
2 558
12.9%
3 426
9.9%
6 373
8.6%
5 345
8.0%
7 248
 
5.7%
0 241
 
5.6%
9 127
 
2.9%

자주식옥외주차장(대)
Real number (ℝ)

MISSING 

Distinct125
Distinct (%)1.9%
Missing3577
Missing (%)35.8%
Infinite0
Infinite (%)0.0%
Mean11.318387
Minimum0
Maximum1571
Zeros37
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:49.146387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q37
95-th percentile19
Maximum1571
Range1571
Interquartile range (IQR)5

Descriptive statistics

Standard deviation75.128166
Coefficient of variation (CV)6.6377096
Kurtosis290.409
Mean11.318387
Median Absolute Deviation (MAD)2
Skewness16.515326
Sum72698
Variance5644.2413
MonotonicityNot monotonic
2023-12-13T08:13:49.323743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 1271
 
12.7%
4 1020
 
10.2%
3 897
 
9.0%
1 757
 
7.6%
8 484
 
4.8%
6 378
 
3.8%
5 374
 
3.7%
7 261
 
2.6%
10 118
 
1.2%
12 99
 
1.0%
Other values (115) 764
 
7.6%
(Missing) 3577
35.8%
ValueCountFrequency (%)
0 37
 
0.4%
1 757
7.6%
2 1271
12.7%
3 897
9.0%
4 1020
10.2%
5 374
 
3.7%
6 378
 
3.8%
7 261
 
2.6%
8 484
 
4.8%
9 84
 
0.8%
ValueCountFrequency (%)
1571 2
< 0.1%
1505 1
 
< 0.1%
1398 1
 
< 0.1%
1391 1
 
< 0.1%
1390 1
 
< 0.1%
1378 4
< 0.1%
1327 2
< 0.1%
1248 1
 
< 0.1%
1246 1
 
< 0.1%
1242 1
 
< 0.1%

기계식옥내주차장(대)
Real number (ℝ)

MISSING  ZEROS 

Distinct75
Distinct (%)12.9%
Missing9420
Missing (%)94.2%
Infinite0
Infinite (%)0.0%
Mean25.701724
Minimum0
Maximum456
Zeros164
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:49.506824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median19
Q335.25
95-th percentile70
Maximum456
Range456
Interquartile range (IQR)35.25

Descriptive statistics

Standard deviation36.454562
Coefficient of variation (CV)1.4183703
Kurtosis61.300191
Mean25.701724
Median Absolute Deviation (MAD)19
Skewness6.0936539
Sum14907
Variance1328.9351
MonotonicityNot monotonic
2023-12-13T08:13:49.649496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 164
 
1.6%
18 22
 
0.2%
30 21
 
0.2%
26 18
 
0.2%
44 17
 
0.2%
20 17
 
0.2%
28 16
 
0.2%
14 16
 
0.2%
32 15
 
0.1%
34 14
 
0.1%
Other values (65) 260
 
2.6%
(Missing) 9420
94.2%
ValueCountFrequency (%)
0 164
1.6%
2 2
 
< 0.1%
4 2
 
< 0.1%
5 3
 
< 0.1%
6 2
 
< 0.1%
7 3
 
< 0.1%
8 7
 
0.1%
9 8
 
0.1%
10 10
 
0.1%
11 8
 
0.1%
ValueCountFrequency (%)
456 1
 
< 0.1%
434 1
 
< 0.1%
196 1
 
< 0.1%
162 1
 
< 0.1%
156 1
 
< 0.1%
150 1
 
< 0.1%
148 1
 
< 0.1%
144 1
 
< 0.1%
127 1
 
< 0.1%
124 3
< 0.1%

기계식옥외주차장(대)
Real number (ℝ)

MISSING  ZEROS 

Distinct35
Distinct (%)15.3%
Missing9771
Missing (%)97.7%
Infinite0
Infinite (%)0.0%
Mean6.0960699
Minimum0
Maximum120
Zeros171
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:49.797655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile36.6
Maximum120
Range120
Interquartile range (IQR)1

Descriptive statistics

Standard deviation15.133599
Coefficient of variation (CV)2.4825173
Kurtosis18.629541
Mean6.0960699
Median Absolute Deviation (MAD)0
Skewness3.7786546
Sum1396
Variance229.02582
MonotonicityNot monotonic
2023-12-13T08:13:49.977792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0 171
 
1.7%
12 7
 
0.1%
8 5
 
0.1%
7 4
 
< 0.1%
20 4
 
< 0.1%
26 2
 
< 0.1%
30 2
 
< 0.1%
11 2
 
< 0.1%
1 2
 
< 0.1%
18 2
 
< 0.1%
Other values (25) 28
 
0.3%
(Missing) 9771
97.7%
ValueCountFrequency (%)
0 171
1.7%
1 2
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
5 1
 
< 0.1%
7 4
 
< 0.1%
8 5
 
0.1%
9 1
 
< 0.1%
10 2
 
< 0.1%
11 2
 
< 0.1%
ValueCountFrequency (%)
120 1
< 0.1%
84 1
< 0.1%
68 1
< 0.1%
58 2
< 0.1%
50 1
< 0.1%
48 1
< 0.1%
44 1
< 0.1%
42 1
< 0.1%
40 1
< 0.1%
38 1
< 0.1%

인근자주식주차장(대)
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)10.9%
Missing9799
Missing (%)98.0%
Infinite0
Infinite (%)0.0%
Mean4.8756219
Minimum0
Maximum150
Zeros160
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:50.135349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile24
Maximum150
Range150
Interquartile range (IQR)0

Descriptive statistics

Standard deviation19.317336
Coefficient of variation (CV)3.9620249
Kurtosis34.6028
Mean4.8756219
Median Absolute Deviation (MAD)0
Skewness5.5735902
Sum980
Variance373.15945
MonotonicityNot monotonic
2023-12-13T08:13:50.278150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 160
 
1.6%
2 9
 
0.1%
4 3
 
< 0.1%
7 3
 
< 0.1%
8 3
 
< 0.1%
6 2
 
< 0.1%
64 2
 
< 0.1%
1 2
 
< 0.1%
3 2
 
< 0.1%
24 2
 
< 0.1%
Other values (12) 13
 
0.1%
(Missing) 9799
98.0%
ValueCountFrequency (%)
0 160
1.6%
1 2
 
< 0.1%
2 9
 
0.1%
3 2
 
< 0.1%
4 3
 
< 0.1%
5 1
 
< 0.1%
6 2
 
< 0.1%
7 3
 
< 0.1%
8 3
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
150 2
< 0.1%
91 1
< 0.1%
75 1
< 0.1%
72 1
< 0.1%
64 2
< 0.1%
52 1
< 0.1%
35 1
< 0.1%
26 1
< 0.1%
24 2
< 0.1%
23 1
< 0.1%

인근기계식주차장(대)
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9833 
0
 
162
13
 
2
28
 
1
150
 
1

Length

Max length4
Median length4
Mean length3.9505
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9833
98.3%
0 162
 
1.6%
13 2
 
< 0.1%
28 1
 
< 0.1%
150 1
 
< 0.1%
38 1
 
< 0.1%

Length

2023-12-13T08:13:50.462211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:13:50.572718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9833
98.3%
0 162
 
1.6%
13 2
 
< 0.1%
28 1
 
< 0.1%
150 1
 
< 0.1%
38 1
 
< 0.1%

총주차대수
Text

MISSING 

Distinct208
Distinct (%)2.4%
Missing1357
Missing (%)13.6%
Memory size156.2 KiB
2023-12-13T08:13:50.833045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.2410043
Min length1

Characters and Unicode

Total characters10726
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

Unique78 ?
Unique (%)0.9%

Sample

1st row25
2nd row7
3rd row5
4th row8
5th row8
ValueCountFrequency (%)
4 1195
13.8%
8 1166
13.5%
2 1077
12.5%
3 1012
11.7%
1 633
 
7.3%
6 599
 
6.9%
5 541
 
6.3%
7 415
 
4.8%
10 190
 
2.2%
12 186
 
2.2%
Other values (198) 1629
18.8%
2023-12-13T08:13:51.275659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1937
18.1%
2 1669
15.6%
4 1514
14.1%
3 1402
13.1%
8 1335
12.4%
6 863
8.0%
5 777
7.2%
7 600
 
5.6%
0 372
 
3.5%
9 233
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10702
99.8%
Other Punctuation 24
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1937
18.1%
2 1669
15.6%
4 1514
14.1%
3 1402
13.1%
8 1335
12.5%
6 863
8.1%
5 777
7.3%
7 600
 
5.6%
0 372
 
3.5%
9 233
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10726
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1937
18.1%
2 1669
15.6%
4 1514
14.1%
3 1402
13.1%
8 1335
12.4%
6 863
8.0%
5 777
7.2%
7 600
 
5.6%
0 372
 
3.5%
9 233
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10726
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1937
18.1%
2 1669
15.6%
4 1514
14.1%
3 1402
13.1%
8 1335
12.4%
6 863
8.0%
5 777
7.2%
7 600
 
5.6%
0 372
 
3.5%
9 233
 
2.2%
Distinct1683
Distinct (%)19.5%
Missing1357
Missing (%)13.6%
Memory size156.2 KiB
2023-12-13T08:13:51.671993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.3232674
Min length1

Characters and Unicode

Total characters28723
Distinct characters12
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

Unique1390 ?
Unique (%)16.1%

Sample

1st row184.54
2nd row80.5
3rd row57.5
4th row92
5th row100
ValueCountFrequency (%)
46 875
 
10.1%
92 859
 
9.9%
23 838
 
9.7%
34.5 637
 
7.4%
11.5 461
 
5.3%
69 455
 
5.3%
0 397
 
4.6%
57.5 366
 
4.2%
80.5 293
 
3.4%
35 164
 
1.9%
Other values (1673) 3298
38.2%
2023-12-13T08:13:52.234373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4105
14.3%
5 3994
13.9%
2 3312
11.5%
1 3095
10.8%
3 2843
9.9%
4 2677
9.3%
6 2274
7.9%
9 2103
7.3%
0 1587
 
5.5%
7 1368
 
4.8%
Other values (2) 1365
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24421
85.0%
Other Punctuation 4302
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 3994
16.4%
2 3312
13.6%
1 3095
12.7%
3 2843
11.6%
4 2677
11.0%
6 2274
9.3%
9 2103
8.6%
0 1587
 
6.5%
7 1368
 
5.6%
8 1168
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 4105
95.4%
, 197
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 28723
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4105
14.3%
5 3994
13.9%
2 3312
11.5%
1 3095
10.8%
3 2843
9.9%
4 2677
9.3%
6 2274
7.9%
9 2103
7.3%
0 1587
 
5.5%
7 1368
 
4.8%
Other values (2) 1365
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28723
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4105
14.3%
5 3994
13.9%
2 3312
11.5%
1 3095
10.8%
3 2843
9.9%
4 2677
9.3%
6 2274
7.9%
9 2103
7.3%
0 1587
 
5.5%
7 1368
 
4.8%
Other values (2) 1365
 
4.8%

세대수
Real number (ℝ)

MISSING  ZEROS 

Distinct85
Distinct (%)1.5%
Missing4163
Missing (%)41.6%
Infinite0
Infinite (%)0.0%
Mean7.6261778
Minimum0
Maximum280
Zeros1726
Zeros (%)17.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:52.721110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q310
95-th percentile19
Maximum280
Range280
Interquartile range (IQR)10

Descriptive statistics

Standard deviation12.624584
Coefficient of variation (CV)1.6554274
Kurtosis145.3442
Mean7.6261778
Median Absolute Deviation (MAD)5
Skewness9.4156762
Sum44514
Variance159.38011
MonotonicityNot monotonic
2023-12-13T08:13:52.880477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1726
17.3%
8 1353
 
13.5%
1 341
 
3.4%
10 309
 
3.1%
12 301
 
3.0%
6 241
 
2.4%
7 191
 
1.9%
9 183
 
1.8%
16 176
 
1.8%
11 141
 
1.4%
Other values (75) 875
 
8.8%
(Missing) 4163
41.6%
ValueCountFrequency (%)
0 1726
17.3%
1 341
 
3.4%
2 48
 
0.5%
3 66
 
0.7%
4 129
 
1.3%
5 53
 
0.5%
6 241
 
2.4%
7 191
 
1.9%
8 1353
13.5%
9 183
 
1.8%
ValueCountFrequency (%)
280 1
< 0.1%
264 1
< 0.1%
254 1
< 0.1%
243 1
< 0.1%
186 1
< 0.1%
171 1
< 0.1%
158 1
< 0.1%
149 1
< 0.1%
144 1
< 0.1%
140 2
< 0.1%

호수
Text

MISSING 

Distinct109
Distinct (%)12.0%
Missing9091
Missing (%)90.9%
Memory size156.2 KiB
2023-12-13T08:13:53.103544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length1.6028603
Min length1

Characters and Unicode

Total characters1457
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

Unique49 ?
Unique (%)5.4%

Sample

1st row9
2nd row2
3rd row36
4th row32
5th row15
ValueCountFrequency (%)
4 88
 
9.7%
2 74
 
8.1%
1 52
 
5.7%
3 47
 
5.2%
6 43
 
4.7%
12 36
 
4.0%
8 32
 
3.5%
14 28
 
3.1%
16 26
 
2.9%
10 25
 
2.8%
Other values (99) 458
50.4%
2023-12-13T08:13:53.512959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 336
23.1%
2 267
18.3%
4 198
13.6%
3 161
11.1%
6 114
 
7.8%
8 90
 
6.2%
0 82
 
5.6%
5 82
 
5.6%
9 67
 
4.6%
7 59
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1456
99.9%
Other Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 336
23.1%
2 267
18.3%
4 198
13.6%
3 161
11.1%
6 114
 
7.8%
8 90
 
6.2%
0 82
 
5.6%
5 82
 
5.6%
9 67
 
4.6%
7 59
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1457
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 336
23.1%
2 267
18.3%
4 198
13.6%
3 161
11.1%
6 114
 
7.8%
8 90
 
6.2%
0 82
 
5.6%
5 82
 
5.6%
9 67
 
4.6%
7 59
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1457
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 336
23.1%
2 267
18.3%
4 198
13.6%
3 161
11.1%
6 114
 
7.8%
8 90
 
6.2%
0 82
 
5.6%
5 82
 
5.6%
9 67
 
4.6%
7 59
 
4.0%

가구수
Real number (ℝ)

MISSING  ZEROS 

Distinct22
Distinct (%)0.5%
Missing5745
Missing (%)57.5%
Infinite0
Infinite (%)0.0%
Mean2.9050529
Minimum0
Maximum31
Zeros1761
Zeros (%)17.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:53.645423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile16
Maximum31
Range31
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.8717362
Coefficient of variation (CV)1.6769871
Kurtosis3.3719455
Mean2.9050529
Median Absolute Deviation (MAD)1
Skewness2.071362
Sum12361
Variance23.733813
MonotonicityNot monotonic
2023-12-13T08:13:53.749446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 1761
 
17.6%
1 1021
 
10.2%
2 307
 
3.1%
3 260
 
2.6%
5 139
 
1.4%
19 93
 
0.9%
13 71
 
0.7%
9 60
 
0.6%
12 59
 
0.6%
4 59
 
0.6%
Other values (12) 425
 
4.2%
(Missing) 5745
57.5%
ValueCountFrequency (%)
0 1761
17.6%
1 1021
10.2%
2 307
 
3.1%
3 260
 
2.6%
4 59
 
0.6%
5 139
 
1.4%
6 43
 
0.4%
7 58
 
0.6%
8 51
 
0.5%
9 60
 
0.6%
ValueCountFrequency (%)
31 1
 
< 0.1%
27 1
 
< 0.1%
19 93
0.9%
18 49
0.5%
17 31
 
0.3%
16 39
0.4%
15 44
0.4%
14 35
 
0.4%
13 71
0.7%
12 59
0.6%

주건축물수
Real number (ℝ)

MISSING  SKEWED 

Distinct35
Distinct (%)0.4%
Missing440
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean1.2949791
Minimum0
Maximum83
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:53.862822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum83
Range83
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.7986845
Coefficient of variation (CV)2.1611813
Kurtosis469.51274
Mean1.2949791
Median Absolute Deviation (MAD)0
Skewness20.02454
Sum12380
Variance7.8326351
MonotonicityNot monotonic
2023-12-13T08:13:53.982775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 8819
88.2%
2 470
 
4.7%
3 84
 
0.8%
4 49
 
0.5%
7 22
 
0.2%
5 20
 
0.2%
6 17
 
0.2%
13 8
 
0.1%
8 8
 
0.1%
10 6
 
0.1%
Other values (25) 57
 
0.6%
(Missing) 440
 
4.4%
ValueCountFrequency (%)
0 4
 
< 0.1%
1 8819
88.2%
2 470
 
4.7%
3 84
 
0.8%
4 49
 
0.5%
5 20
 
0.2%
6 17
 
0.2%
7 22
 
0.2%
8 8
 
0.1%
9 5
 
0.1%
ValueCountFrequency (%)
83 1
 
< 0.1%
73 2
< 0.1%
72 3
< 0.1%
71 1
 
< 0.1%
70 1
 
< 0.1%
69 1
 
< 0.1%
68 1
 
< 0.1%
38 4
< 0.1%
37 2
< 0.1%
36 3
< 0.1%

부속건축물수
Real number (ℝ)

MISSING  ZEROS 

Distinct13
Distinct (%)1.9%
Missing9301
Missing (%)93.0%
Infinite0
Infinite (%)0.0%
Mean0.97567954
Minimum0
Maximum69
Zeros288
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T08:13:54.073751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum69
Range69
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.9900951
Coefficient of variation (CV)3.0646282
Kurtosis387.83043
Mean0.97567954
Median Absolute Deviation (MAD)1
Skewness17.713129
Sum682
Variance8.9406684
MonotonicityNot monotonic
2023-12-13T08:13:54.169407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1 332
 
3.3%
0 288
 
2.9%
2 43
 
0.4%
3 16
 
0.2%
4 7
 
0.1%
11 4
 
< 0.1%
5 2
 
< 0.1%
7 2
 
< 0.1%
6 1
 
< 0.1%
19 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
(Missing) 9301
93.0%
ValueCountFrequency (%)
0 288
2.9%
1 332
3.3%
2 43
 
0.4%
3 16
 
0.2%
4 7
 
0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
7 2
 
< 0.1%
10 1
 
< 0.1%
11 4
 
< 0.1%
ValueCountFrequency (%)
69 1
 
< 0.1%
19 1
 
< 0.1%
16 1
 
< 0.1%
11 4
 
< 0.1%
10 1
 
< 0.1%
7 2
 
< 0.1%
6 1
 
< 0.1%
5 2
 
< 0.1%
4 7
0.1%
3 16
0.2%

Sample

연번건축구분허가번호대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율용적률구조허가일최종설계변경일착공처리일착공예정일사용승인일건축허가최초접수일최대지상층수최대지하층수최고높이(m)동수승강기합비상승강기합하수처리시설명하수처리시설용량(제곱미터)주용도부속용도용도지역용도지구용도구역자주식옥내주차장(대)자주식옥외주차장(대)기계식옥내주차장(대)기계식옥외주차장(대)인근자주식주차장(대)인근기계식주차장(대)총주차대수총주차장면적(제곱미터)세대수호수가구수주건축물수부속건축물수
38353836신축2015-건축과-신축허가-60인천광역시 미추홀구 도화동 369-1342.1243.62,590.61<NA>71.21698.82철근콘크리트구조2015-03-252015-07-292015-05-082015-05-112016-01-122015-03-0313140.311<NA>부패탱크방법<NA>공동주택아파트일반상업지역방화지구<NA>7<NA>18<NA><NA><NA>25184.54269<NA>1<NA>
54845485신축2009-건축과-신축허가-5인천광역시 미추홀구 숭의동 340-13222.5159.36625.16<NA>71.62280.97철근콘크리트구조2009-01-20<NA>2009-02-202009-02-182009-07-162009-01-135015.91<NA><NA>부패탱크방법<NA>공동주택다세대주택/제1종근린생활시설일반상업지역방화지구<NA><NA>7<NA><NA><NA><NA>780.562<NA>1<NA>
95439544증축2001-종합민원과-증축허가-27인천광역시 미추홀구 주안동 1582-2298.2167.45737.63131.9756.15247.06철근콘크리트구조2001-04-30<NA>2001-06-072001-06-072001-09-242001-04-255<NA>16.41<NA><NA>부패탱크방법<NA>단독주택근,생(소매점,사무소)일반주거지역<NA><NA><NA>5<NA><NA><NA><NA>557.5<NA><NA>121<NA>
71617162신축2002-건축과-신축허가-751인천광역시 미추홀구 주안동 730-21 외1필지385180.68659.13<NA>46.93171.2철근콘크리트구조2002-09-03<NA>2002-09-042002-09-052003-01-092002-08-245014.611<NA>부패탱크방법6.24공동주택다세대주택일반주거지역<NA><NA>62<NA><NA><NA><NA>8928<NA>01<NA>
20312032신축2022-건축과-신축허가-11인천광역시 미추홀구 주안동 1560-3 외1필지367.1217.271,136.56<NA>59.19305.79철근콘크리트구조2022-02-112023-01-262022-05-032022-05-01<NA>2021-12-306125.911<NA>기타단독정화조<NA>제2종근린생활시설제1,2종근린생활시설준주거지역<NA><NA><NA>8<NA><NA><NA><NA>8100<NA><NA><NA>1<NA>
88838884신축2001-종합민원과-신축허가-936인천광역시 미추홀구 문학동 401-8229.5135.82479.44<NA>59.18149.72철근콘크리트구조2001-08-08<NA>2001-08-162001-08-162002-02-202001-07-193112.031<NA><NA>부패탱크방법5.365단독주택다가구주택제1종일반주거지역<NA><NA><NA>3<NA><NA><NA><NA>335.5<NA><NA>171<NA>
99919992신축2000-종합민원과-신축허가-26인천광역시 남구 남구 394-45공장용지725415.351,999.76<NA>57.28209.92철근콘크리트구조2000-10-10<NA>2000-10-06<NA><NA>2000-08-2541<NA>11<NA>기타오수처리시설<NA>공동주택연립주택일반상업지역<NA><NA>14<NA><NA><NA><NA><NA>1416116<NA><NA>1<NA>
72687269신축2002-건축과-신축허가-634인천광역시 미추홀구 주안동 383-25292.8174.03595.08<NA>59.44203.24철근콘크리트구조2002-07-30<NA>2002-08-212002-08-222003-01-292002-07-135014.3100부패탱크방법5공동주택다세대주택일반주거지역<NA><NA>7<NA><NA><NA><NA><NA>780.58<NA>01<NA>
73867387신축2002-건축과-신축허가-512인천광역시 미추홀구 용현동 627-351 외2필지479207.151,252.98<NA>43.25245.94철근콘크리트구조2002-06-222004-09-212004-02-172004-02-172004-10-182002-03-236125.111<NA>혐기및호기성미생물조정방법70제2종근린생활시설<NA>준주거지역일반미관지구<NA><NA>8<NA><NA><NA><NA>8920<NA>01<NA>
87298730신축2001-종합민원과-신축허가-1094인천광역시 미추홀구 문학동 366-14366.9154.56723.19<NA>42.12197.1철근콘크리트구조2001-08-31<NA>2001-09-042001-09-012002-04-192001-08-105<NA>16.91<NA><NA>부패탱크방법12제2종근린생활시설및 다가구주택제2종일반주거지역일반미관지구기타구역<NA>4<NA><NA><NA><NA>446<NA><NA>171<NA>
연번건축구분허가번호대지위치지목대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율용적률구조허가일최종설계변경일착공처리일착공예정일사용승인일건축허가최초접수일최대지상층수최대지하층수최고높이(m)동수승강기합비상승강기합하수처리시설명하수처리시설용량(제곱미터)주용도부속용도용도지역용도지구용도구역자주식옥내주차장(대)자주식옥외주차장(대)기계식옥내주차장(대)기계식옥외주차장(대)인근자주식주차장(대)인근기계식주차장(대)총주차대수총주차장면적(제곱미터)세대수호수가구수주건축물수부속건축물수
91839184신축2001-종합민원과-신축허가-628인천광역시 미추홀구 숭의동 147-54103.872.42337.74<NA>69.77273.06철근콘크리트구조2001-07-04<NA>2001-07-312001-08-012002-05-092001-06-164112.851<NA><NA>부패탱크방법<NA>공동주택다세대주택 및 제1종근생일반상업지역방화지구<NA>11<NA><NA><NA><NA>2234<NA><NA>1<NA>
42784279신축2013-건축과-신축허가-105인천광역시 미추홀구 학익동 306-8013076.66208.93<NA>58.97160.72철근콘크리트구조2013-08-06<NA>2013-09-302013-09-302014-02-252013-07-31308.881<NA><NA>부패탱크방법<NA>단독주택다가구 주택제2종일반주거지역<NA>상대보호구역<NA>3<NA><NA><NA><NA>334.5<NA><NA>31<NA>
89148915신축2001-종합민원과-신축허가-896인천광역시 미추홀구 용현동 48-40148.488.52248.92<NA>59.65167.74철근콘크리트구조2001-08-03<NA>2001-08-072001-08-072002-06-242001-07-303<NA>91<NA><NA>접촉폭기방법4.63단독주택다가구주택일반주거지역<NA><NA>1<NA><NA><NA><NA><NA>1120<NA>91<NA>
13021303신축2003-건축과-신축신고-36인천광역시 미추홀구 도화동 624-217771.2971.29<NA>40.2740.27철근콘크리트구조2003-10-27<NA>2003-11-142003-11-142003-11-262003-10-101<NA>41<NA><NA>부패탱크방법3.06단독주택근린생활시설(사무실)일반상업지역방화지구<NA><NA><NA><NA><NA><NA><NA><NA><NA>1<NA>01<NA>
1061910620신축1997-건축지적과-신축허가-457인천광역시 미추홀구 용현동 203-28202.3118.49404.66<NA>58.57149.33철근콘크리트구조1997-11-12<NA>1997-11-121998-02-2015-06-261997-10-303111.91<NA><NA>기타단독정화조<NA>단독주택다가구주택일반주거지역<NA><NA><NA>4<NA><NA><NA><NA>446<NA><NA>131<NA>
60306031증축2007-건축과-증축허가-9인천광역시 미추홀구 주안동 1389-2 외1필지42,155.7010,449.6528,019.871,530.0624.7962.79철근콘크리트구조2007-03-07<NA>2007-03-152007-03-152007-09-202007-02-153<NA>13.4314<NA><NA><NA><NA>교육연구시설<NA>일반공업지역<NA><NA><NA>8<NA><NA><NA><NA>8920<NA>014<NA>
26892690신축2018-건축과-신축허가-21인천광역시 미추홀구 도화동 6-42287.2170.77659.96<NA>59.46229.79철근콘크리트구조2018-08-03<NA>2018-08-222018-08-222018-11-302018-07-185015.851<NA><NA>부패탱크방법<NA>공동주택다세대주택준주거지역<NA>상대보호구역<NA>8<NA><NA><NA><NA>8928<NA><NA>1<NA>
13651366증축2003-건축과-증축신고-60인천광역시 미추홀구 학익동 288-216573.2199.5315.644.3760.32경량철골구조2003-06-26<NA>2003-07-032003-07-032003-07-242003-06-202<NA><NA>2<NA><NA>부패탱크방법<NA>단독주택단독주택준주거지역<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0<NA>111
94079408신축2001-종합민원과-신축허가-417인천광역시 미추홀구 도화동 498-4157.893.18470.01<NA>59.05231.1철근콘크리트구조2001-05-24<NA>2001-05-262001-05-262001-10-242001-05-164112.451<NA><NA>부패탱크방법<NA>공동주택다세대주택준주거지역<NA><NA>21<NA><NA><NA><NA>334.59<NA><NA>1<NA>
14731474증축2002-건축과-증축신고-142인천광역시 미추홀구 용현동 623-135164.998.77170.04059.985.14벽돌구조2002-10-30<NA>2002-11-052002-11-052002-11-192002-10-291<NA>3.61<NA><NA>부패탱크방법4.5단독주택근생 및 주택준주거지역<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>0<NA>21<NA>