Overview

Dataset statistics

Number of variables23
Number of observations4822
Missing cells16801
Missing cells (%)15.1%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory918.4 KiB
Average record size in memory195.0 B

Variable types

Categorical6
Text3
Numeric11
DateTime3

Dataset

Description대지위치, 면적, 용적률, 허가일, 층수, 용도 등 등 서울특별시 광진구 관내 건축물사용승인허가현황에 관한 정보를 조회할 수 있는 데이터입니다.
Author서울특별시 광진구
URLhttps://www.data.go.kr/data/15044746/fileData.do

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
건축구분 is highly imbalanced (64.6%)Imbalance
구조 is highly imbalanced (88.3%)Imbalance
주용도 is highly imbalanced (51.4%)Imbalance
용도지구 is highly imbalanced (66.9%)Imbalance
용도구역 is highly imbalanced (63.9%)Imbalance
건물명 has 1401 (29.1%) missing valuesMissing
증축연면적(제곱미터) has 4546 (94.3%) missing valuesMissing
허가일 has 78 (1.6%) missing valuesMissing
착공처리일 has 501 (10.4%) missing valuesMissing
최대지하층수 has 208 (4.3%) missing valuesMissing
부속용도 has 322 (6.7%) missing valuesMissing
세대수 has 2480 (51.4%) missing valuesMissing
호수 has 4195 (87.0%) missing valuesMissing
가구수 has 3065 (63.6%) missing valuesMissing
연면적(제곱미터) is highly skewed (γ1 = 68.53415674)Skewed
용적률(퍼센트) is highly skewed (γ1 = 69.4081598)Skewed
세대수 is highly skewed (γ1 = 24.17941608)Skewed
호수 is highly skewed (γ1 = 20.01053581)Skewed
최대지하층수 has 3275 (67.9%) zerosZeros

Reproduction

Analysis started2024-04-17 18:11:51.746776
Analysis finished2024-04-17 18:11:52.507788
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

건축구분
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size37.8 KiB
신축
4020 
용도변경
 
317
증축
 
277
대수선
 
204
가설건축물축조허가
 
3

Length

Max length9
Median length2
Mean length2.1781418
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
신축 4020
83.4%
용도변경 317
 
6.6%
증축 277
 
5.7%
대수선 204
 
4.2%
가설건축물축조허가 3
 
0.1%
개축 1
 
< 0.1%

Length

2024-04-18T03:11:52.560393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T03:11:52.642420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신축 4020
83.4%
용도변경 317
 
6.6%
증축 277
 
5.7%
대수선 204
 
4.2%
가설건축물축조허가 3
 
0.1%
개축 1
 
< 0.1%

건물명
Text

MISSING 

Distinct3089
Distinct (%)90.3%
Missing1401
Missing (%)29.1%
Memory size37.8 KiB
2024-04-18T03:11:52.902127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length37
Mean length12.37796
Min length1

Characters and Unicode

Total characters42345
Distinct characters572
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2909 ?
Unique (%)85.0%

Sample

1st row화양동 18-12 주거복합 신축공사
2nd row건대 트레비앙 오피스텔
3rd row엘케이플레이스5차
4th row성산교회
5th row군자동 91-6
ValueCountFrequency (%)
단독주택 537
 
6.6%
중곡동 489
 
6.0%
공동주택 424
 
5.2%
구의동 319
 
3.9%
자양동 271
 
3.3%
제2종근린생활시설 219
 
2.7%
화양동 194
 
2.4%
능동 130
 
1.6%
군자동 113
 
1.4%
제1종근린생활시설 61
 
0.7%
Other values (4347) 5419
66.3%
2024-04-18T03:11:53.292328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4893
 
11.6%
동 2165
 
5.1%
- 1477
 
3.5%
2 1469
 
3.5%
) 1353
 
3.2%
( 1352
 
3.2%
주 1300
 
3.1%
1 1273
 
3.0%
택 1190
 
2.8%
3 753
 
1.8%
Other values (562) 25120
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25447
60.1%
Decimal Number 7187
 
17.0%
Space Separator 4893
 
11.6%
Dash Punctuation 1477
 
3.5%
Close Punctuation 1353
 
3.2%
Open Punctuation 1352
 
3.2%
Uppercase Letter 365
 
0.9%
Lowercase Letter 181
 
0.4%
Other Punctuation 62
 
0.1%
Letter Number 24
 
0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2165
 
8.5%
주 1300
 
5.1%
택 1190
 
4.7%
빌 738
 
2.9%
양 579
 
2.3%
단 565
 
2.2%
독 547
 
2.1%
자 535
 
2.1%
중 532
 
2.1%
곡 516
 
2.0%
Other values (484) 16780
65.9%
Uppercase Letter
ValueCountFrequency (%)
A 37
 
10.1%
B 28
 
7.7%
S 28
 
7.7%
E 26
 
7.1%
K 25
 
6.8%
H 23
 
6.3%
I 22
 
6.0%
N 16
 
4.4%
M 15
 
4.1%
L 14
 
3.8%
Other values (16) 131
35.9%
Lowercase Letter
ValueCountFrequency (%)
i 22
12.2%
a 16
 
8.8%
e 16
 
8.8%
s 15
 
8.3%
l 14
 
7.7%
o 12
 
6.6%
t 11
 
6.1%
n 11
 
6.1%
r 10
 
5.5%
c 10
 
5.5%
Other values (11) 44
24.3%
Decimal Number
ValueCountFrequency (%)
2 1469
20.4%
1 1273
17.7%
3 753
10.5%
4 643
8.9%
6 637
8.9%
5 614
8.5%
0 490
 
6.8%
7 462
 
6.4%
9 444
 
6.2%
8 402
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 20
32.3%
/ 17
27.4%
. 17
27.4%
: 3
 
4.8%
& 2
 
3.2%
# 1
 
1.6%
？ 1
 
1.6%
* 1
 
1.6%
Letter Number
ValueCountFrequency (%)
Ⅱ 10
41.7%
Ⅰ 7
29.2%
Ⅳ 2
 
8.3%
Ⅲ 2
 
8.3%
ⅱ 1
 
4.2%
Ⅶ 1
 
4.2%
Ⅴ 1
 
4.2%
Space Separator
ValueCountFrequency (%)
4893
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1477
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1353
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1352
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25439
60.1%
Common 16328
38.6%
Latin 569
 
1.3%
Han 8
 
< 0.1%
Greek 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2165
 
8.5%
주 1300
 
5.1%
택 1190
 
4.7%
빌 738
 
2.9%
양 579
 
2.3%
단 565
 
2.2%
독 547
 
2.2%
자 535
 
2.1%
중 532
 
2.1%
곡 516
 
2.0%
Other values (477) 16772
65.9%
Latin
ValueCountFrequency (%)
A 37
 
6.5%
B 28
 
4.9%
S 28
 
4.9%
E 26
 
4.6%
K 25
 
4.4%
H 23
 
4.0%
I 22
 
3.9%
i 22
 
3.9%
a 16
 
2.8%
N 16
 
2.8%
Other values (43) 326
57.3%
Common
ValueCountFrequency (%)
4893
30.0%
- 1477
 
9.0%
2 1469
 
9.0%
) 1353
 
8.3%
( 1352
 
8.3%
1 1273
 
7.8%
3 753
 
4.6%
4 643
 
3.9%
6 637
 
3.9%
5 614
 
3.8%
Other values (14) 1864
 
11.4%
Han
ValueCountFrequency (%)
愛 2
25.0%
一 1
12.5%
空 1
12.5%
三 1
12.5%
寨 1
12.5%
東 1
12.5%
休 1
12.5%
Greek
ValueCountFrequency (%)
Ι 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25439
60.1%
ASCII 16872
39.8%
Number Forms 24
 
0.1%
CJK 8
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4893
29.0%
- 1477
 
8.8%
2 1469
 
8.7%
) 1353
 
8.0%
( 1352
 
8.0%
1 1273
 
7.5%
3 753
 
4.5%
4 643
 
3.8%
6 637
 
3.8%
5 614
 
3.6%
Other values (59) 2408
14.3%
Hangul
ValueCountFrequency (%)
동 2165
 
8.5%
주 1300
 
5.1%
택 1190
 
4.7%
빌 738
 
2.9%
양 579
 
2.3%
단 565
 
2.2%
독 547
 
2.2%
자 535
 
2.1%
중 532
 
2.1%
곡 516
 
2.0%
Other values (477) 16772
65.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 10
41.7%
Ⅰ 7
29.2%
Ⅳ 2
 
8.3%
Ⅲ 2
 
8.3%
ⅱ 1
 
4.2%
Ⅶ 1
 
4.2%
Ⅴ 1
 
4.2%
CJK
ValueCountFrequency (%)
愛 2
25.0%
一 1
12.5%
空 1
12.5%
三 1
12.5%
寨 1
12.5%
東 1
12.5%
休 1
12.5%
None
ValueCountFrequency (%)
？ 1
50.0%
Ι 1
50.0%

대지위치
Text

Distinct4535
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size37.8 KiB
2024-04-18T03:11:53.494320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length20.363957
Min length15

Characters and Unicode

Total characters98195
Distinct characters33
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

Unique4315 ?
Unique (%)89.5%

Sample

1st row서울특별시 광진구 화양동 18-12
2nd row서울특별시 광진구 화양동 174
3rd row서울특별시 광진구 자양동 832-29
4th row서울특별시 광진구 자양동 658-1
5th row서울특별시 광진구 군자동 91-6
ValueCountFrequency (%)
서울특별시 4822
23.7%
광진구 4822
23.7%
중곡동 1568
 
7.7%
구의동 1054
 
5.2%
자양동 964
 
4.7%
외1필지 775
 
3.8%
화양동 461
 
2.3%
능동 351
 
1.7%
군자동 325
 
1.6%
외2필지 151
 
0.7%
Other values (4281) 5034
24.8%
2024-04-18T03:11:53.791879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15505
15.8%
구 5876
 
6.0%
광 4921
 
5.0%
서 4822
 
4.9%
특 4822
 
4.9%
별 4822
 
4.9%
시 4822
 
4.9%
진 4822
 
4.9%
울 4822
 
4.9%
동 4822
 
4.9%
Other values (23) 38139
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55808
56.8%
Decimal Number 22180
 
22.6%
Space Separator 15505
 
15.8%
Dash Punctuation 4702
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 5876
10.5%
광 4921
8.8%
서 4822
8.6%
특 4822
8.6%
별 4822
8.6%
시 4822
8.6%
진 4822
8.6%
울 4822
8.6%
동 4822
8.6%
곡 1568
 
2.8%
Other values (11) 9689
17.4%
Decimal Number
ValueCountFrequency (%)
1 4445
20.0%
2 3958
17.8%
3 2426
10.9%
4 2023
9.1%
6 2015
9.1%
5 1936
8.7%
7 1523
 
6.9%
9 1365
 
6.2%
0 1260
 
5.7%
8 1229
 
5.5%
Space Separator
ValueCountFrequency (%)
15505
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4702
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55808
56.8%
Common 42387
43.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 5876
10.5%
광 4921
8.8%
서 4822
8.6%
특 4822
8.6%
별 4822
8.6%
시 4822
8.6%
진 4822
8.6%
울 4822
8.6%
동 4822
8.6%
곡 1568
 
2.8%
Other values (11) 9689
17.4%
Common
ValueCountFrequency (%)
15505
36.6%
- 4702
 
11.1%
1 4445
 
10.5%
2 3958
 
9.3%
3 2426
 
5.7%
4 2023
 
4.8%
6 2015
 
4.8%
5 1936
 
4.6%
7 1523
 
3.6%
9 1365
 
3.2%
Other values (2) 2489
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55808
56.8%
ASCII 42387
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15505
36.6%
- 4702
 
11.1%
1 4445
 
10.5%
2 3958
 
9.3%
3 2426
 
5.7%
4 2023
 
4.8%
6 2015
 
4.8%
5 1936
 
4.6%
7 1523
 
3.6%
9 1365
 
3.2%
Other values (2) 2489
 
5.9%
Hangul
ValueCountFrequency (%)
구 5876
10.5%
광 4921
8.8%
서 4822
8.6%
특 4822
8.6%
별 4822
8.6%
시 4822
8.6%
진 4822
8.6%
울 4822
8.6%
동 4822
8.6%
곡 1568
 
2.8%
Other values (11) 9689
17.4%

대지면적(제곱미터)
Real number (ℝ)

Distinct2704
Distinct (%)56.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2484.5152
Minimum37
Maximum536088.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.5 KiB
2024-04-18T03:11:54.124435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37
5-th percentile111.72
Q1154.54
median204.3
Q3320.47
95-th percentile1005
Maximum536088.5
Range536051.5
Interquartile range (IQR)165.93

Descriptive statistics

Standard deviation28101.168
Coefficient of variation (CV)11.310524
Kurtosis240.60061
Mean2484.5152
Median Absolute Deviation (MAD)63.8
Skewness15.163067
Sum11977848
Variance7.8967566 × 108
MonotonicityNot monotonic
2024-04-18T03:11:54.226532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
165.3 30
 
0.6%
165.0 22
 
0.5%
166.0 21
 
0.4%
162.0 16
 
0.3%
165.6 15
 
0.3%
157.0 14
 
0.3%
167.0 13
 
0.3%
175.5 12
 
0.2%
460443.2 12
 
0.2%
221.0 12
 
0.2%
Other values (2694) 4654
96.5%
ValueCountFrequency (%)
37.0 1
 
< 0.1%
64.5 3
0.1%
70.0 1
 
< 0.1%
70.2 1
 
< 0.1%
70.44 1
 
< 0.1%
71.5 1
 
< 0.1%
73.28 1
 
< 0.1%
73.42 1
 
< 0.1%
73.78 1
 
< 0.1%
74.39 1
 
< 0.1%
ValueCountFrequency (%)
536088.5 2
 
< 0.1%
460443.2 12
0.2%
261288.0 9
0.2%
118420.2 2
 
< 0.1%
117804.2 3
 
0.1%
60235.4 1
 
< 0.1%
57033.0 2
 
< 0.1%
56424.0 1
 
< 0.1%
39792.2 1
 
< 0.1%
35977.0 4
 
0.1%

건축면적(제곱미터)
Real number (ℝ)

Distinct3879
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean545.86034
Minimum18.21
Maximum115575
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.5 KiB
2024-04-18T03:11:54.323769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18.21
5-th percentile64.5335
Q189.005
median117.5
Q3176.825
95-th percentile488.9585
Maximum115575
Range115556.79
Interquartile range (IQR)87.82

Descriptive statistics

Standard deviation4697.8897
Coefficient of variation (CV)8.6063951
Kurtosis277.95003
Mean545.86034
Median Absolute Deviation (MAD)35.485
Skewness15.906924
Sum2632138.5
Variance22070168
MonotonicityNot monotonic
2024-04-18T03:11:54.441726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
79.2 10
 
0.2%
3234.42 8
 
0.2%
89.1 7
 
0.1%
1204.72 6
 
0.1%
13319.84 6
 
0.1%
98.99 6
 
0.1%
91.8 6
 
0.1%
106.4 6
 
0.1%
87.36 5
 
0.1%
82.4 5
 
0.1%
Other values (3869) 4757
98.7%
ValueCountFrequency (%)
18.21 1
< 0.1%
20.5 1
< 0.1%
29.67 1
< 0.1%
30.23 1
< 0.1%
31.11 1
< 0.1%
35.04 1
< 0.1%
35.65 1
< 0.1%
37.13 1
< 0.1%
37.8 1
< 0.1%
37.94 1
< 0.1%
ValueCountFrequency (%)
115575.0 1
 
< 0.1%
80888.27 1
 
< 0.1%
80095.57 1
 
< 0.1%
80072.68 1
 
< 0.1%
79891.41 4
0.1%
79593.41 1
 
< 0.1%
79346.7 2
< 0.1%
78030.79 1
 
< 0.1%
77822.28 1
 
< 0.1%
34330.81 1
 
< 0.1%

연면적(제곱미터)
Real number (ℝ)

SKEWED 

Distinct4511
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98315.635
Minimum20.5
Maximum4.1794818 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size42.5 KiB
2024-04-18T03:11:54.546403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20.5
5-th percentile190.1085
Q1289.6925
median407.76
Q3658.5825
95-th percentile2943.1415
Maximum4.1794818 × 108
Range4.1794816 × 108
Interquartile range (IQR)368.89

Descriptive statistics

Standard deviation6046856.8
Coefficient of variation (CV)61.504528
Kurtosis4732.9106
Mean98315.635
Median Absolute Deviation (MAD)154.915
Skewness68.534157
Sum4.7407799 × 108
Variance3.6564477 × 1013
MonotonicityNot monotonic
2024-04-18T03:11:54.648050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70372.67 8
 
0.2%
11284.43 6
 
0.1%
259730.85 6
 
0.1%
4247.18 5
 
0.1%
659.97 4
 
0.1%
3068.29 4
 
0.1%
47814.77 4
 
0.1%
1947.02 4
 
0.1%
330.12 3
 
0.1%
659.79 3
 
0.1%
Other values (4501) 4775
99.0%
ValueCountFrequency (%)
20.5 1
< 0.1%
31.11 1
< 0.1%
35.65 1
< 0.1%
45.0 1
< 0.1%
47.49 1
< 0.1%
50.86 1
< 0.1%
56.93 1
< 0.1%
62.81 1
< 0.1%
69.55 1
< 0.1%
92.3 1
< 0.1%
ValueCountFrequency (%)
417948182.0 1
< 0.1%
40496677.0 1
< 0.1%
434741.26 1
< 0.1%
434581.12 2
< 0.1%
412542.14 1
< 0.1%
405203.63 1
< 0.1%
403972.65 1
< 0.1%
403749.39 1
< 0.1%
403116.2 1
< 0.1%
403007.7 1
< 0.1%

증축연면적(제곱미터)
Real number (ℝ)

MISSING 

Distinct268
Distinct (%)97.1%
Missing4546
Missing (%)94.3%
Infinite0
Infinite (%)0.0%
Mean1617.4882
Minimum0
Maximum71304.72
Zeros3
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size42.5 KiB
2024-04-18T03:11:54.756483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.855
Q135.2125
median67.575
Q3278.3825
95-th percentile3509.485
Maximum71304.72
Range71304.72
Interquartile range (IQR)243.17

Descriptive statistics

Standard deviation7424.3492
Coefficient of variation (CV)4.5900484
Kurtosis45.252351
Mean1617.4882
Median Absolute Deviation (MAD)47.03
Skewness6.42019
Sum446426.74
Variance55120961
MonotonicityNot monotonic
2024-04-18T03:11:54.860740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
0.1%
34.8 3
 
0.1%
33.0 2
 
< 0.1%
36.02 2
 
< 0.1%
6.58 2
 
< 0.1%
967.38 2
 
< 0.1%
72.04 1
 
< 0.1%
223.26 1
 
< 0.1%
30.78 1
 
< 0.1%
44.14 1
 
< 0.1%
Other values (258) 258
 
5.4%
(Missing) 4546
94.3%
ValueCountFrequency (%)
0.0 3
0.1%
3.6 1
 
< 0.1%
6.48 1
 
< 0.1%
6.58 2
< 0.1%
8.33 1
 
< 0.1%
10.17 1
 
< 0.1%
10.5 1
 
< 0.1%
10.72 1
 
< 0.1%
11.7 1
 
< 0.1%
11.9 1
 
< 0.1%
ValueCountFrequency (%)
71304.72 1
< 0.1%
50022.04 1
< 0.1%
47303.49 1
< 0.1%
45800.51 1
< 0.1%
31165.86 1
< 0.1%
29778.38 1
< 0.1%
27188.66 1
< 0.1%
25365.86 1
< 0.1%
18294.59 1
< 0.1%
12743.17 1
< 0.1%

건폐율(퍼센트)
Real number (ℝ)

Distinct1417
Distinct (%)29.4%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean56.150246
Minimum0
Maximum98.1947
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size42.5 KiB
2024-04-18T03:11:54.973480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile45.97
Q154.54
median59.04
Q359.76
95-th percentile59.96
Maximum98.1947
Range98.1947
Interquartile range (IQR)5.22

Descriptive statistics

Standard deviation6.7658686
Coefficient of variation (CV)0.1204958
Kurtosis16.058613
Mean56.150246
Median Absolute Deviation (MAD)0.89
Skewness-2.7926574
Sum270700.34
Variance45.776978
MonotonicityNot monotonic
2024-04-18T03:11:55.079333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59.96 68
 
1.4%
59.95 65
 
1.3%
59.9 62
 
1.3%
59.98 58
 
1.2%
59.94 56
 
1.2%
59.89 55
 
1.1%
59.85 55
 
1.1%
59.97 53
 
1.1%
59.91 52
 
1.1%
59.81 50
 
1.0%
Other values (1407) 4247
88.1%
ValueCountFrequency (%)
0.0 1
< 0.1%
0.01 2
< 0.1%
0.9389 1
< 0.1%
2.11 1
< 0.1%
2.9926 1
< 0.1%
7.84 1
< 0.1%
11.17 1
< 0.1%
11.28 1
< 0.1%
12.4 1
< 0.1%
12.44 2
< 0.1%
ValueCountFrequency (%)
98.1947 1
< 0.1%
96.47 1
< 0.1%
96.1 1
< 0.1%
92.78 1
< 0.1%
91.83 1
< 0.1%
85.5463 1
< 0.1%
84.02 1
< 0.1%
83.16 1
< 0.1%
83.03 1
< 0.1%
80.83 1
< 0.1%

용적률(퍼센트)
Real number (ℝ)

SKEWED 

Distinct2951
Distinct (%)61.2%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean285.11725
Minimum0
Maximum414900.05
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size42.5 KiB
2024-04-18T03:11:55.214758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile133.3445
Q1161.405
median195.595
Q3199.82
95-th percentile348.2205
Maximum414900.05
Range414900.05
Interquartile range (IQR)38.415

Descriptive statistics

Standard deviation5973.7796
Coefficient of variation (CV)20.952011
Kurtosis4818.3272
Mean285.11725
Median Absolute Deviation (MAD)17.16
Skewness69.40816
Sum1374265.1
Variance35686043
MonotonicityNot monotonic
2024-04-18T03:11:55.326587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
199.93 31
 
0.6%
199.96 28
 
0.6%
199.97 28
 
0.6%
199.92 24
 
0.5%
199.86 23
 
0.5%
199.87 22
 
0.5%
199.98 22
 
0.5%
199.91 21
 
0.4%
199.9 21
 
0.4%
199.6 20
 
0.4%
Other values (2941) 4580
95.0%
ValueCountFrequency (%)
0.0 1
< 0.1%
0.01 2
< 0.1%
1.15 1
< 0.1%
2.9341 1
< 0.1%
2.9926 1
< 0.1%
16.45 1
< 0.1%
17.53 1
< 0.1%
20.535 1
< 0.1%
31.43 1
< 0.1%
31.99 1
< 0.1%
ValueCountFrequency (%)
414900.05 1
 
< 0.1%
799.82 1
 
< 0.1%
798.4146 1
 
< 0.1%
798.41 1
 
< 0.1%
797.56 1
 
< 0.1%
795.9947 5
0.1%
795.99 3
0.1%
789.2 1
 
< 0.1%
787.8818 2
 
< 0.1%
782.97 1
 
< 0.1%

구조
Categorical

IMBALANCE 

Distinct15
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size37.8 KiB
철근콘크리트구조
4550 
벽돌구조
 
88
<NA>
 
70
일반철골구조
 
50
철골철근콘크리트구조
 
29
Other values (10)
 
35

Length

Max length12
Median length8
Mean length7.8488179
Min length3

Unique

Unique5 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
철근콘크리트구조 4550
94.4%
벽돌구조 88
 
1.8%
<NA> 70
 
1.5%
일반철골구조 50
 
1.0%
철골철근콘크리트구조 29
 
0.6%
경량철골구조 16
 
0.3%
철골콘크리트구조 7
 
0.1%
블록구조 3
 
0.1%
철골철근콘크리트합성구조 2
 
< 0.1%
조립식판넬조 2
 
< 0.1%
Other values (5) 5
 
0.1%

Length

2024-04-18T03:11:55.417252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
철근콘크리트구조 4550
94.4%
벽돌구조 88
 
1.8%
na 70
 
1.5%
일반철골구조 50
 
1.0%
철골철근콘크리트구조 29
 
0.6%
경량철골구조 16
 
0.3%
철골콘크리트구조 7
 
0.1%
블록구조 3
 
0.1%
철골철근콘크리트합성구조 2
 
< 0.1%
조립식판넬조 2
 
< 0.1%
Other values (5) 5
 
0.1%

허가일
Date

MISSING 

Distinct2267
Distinct (%)47.8%
Missing78
Missing (%)1.6%
Memory size37.8 KiB
Minimum1985-08-06 00:00:00
Maximum2023-11-30 00:00:00
2024-04-18T03:11:55.507329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:11:55.609307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공처리일
Date

MISSING 

Distinct2184
Distinct (%)50.5%
Missing501
Missing (%)10.4%
Memory size37.8 KiB
Minimum2003-06-30 00:00:00
Maximum2023-12-22 00:00:00
2024-04-18T03:11:55.720183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:11:55.816023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용승인일
Date

Distinct2365
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Memory size37.8 KiB
Minimum2010-01-06 00:00:00
Maximum2024-01-31 00:00:00
2024-04-18T03:11:55.917133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T03:11:56.014658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최대지상층수
Real number (ℝ)

Distinct26
Distinct (%)0.5%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean5.2246422
Minimum0
Maximum50
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size42.5 KiB
2024-04-18T03:11:56.099887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q14
median5
Q35
95-th percentile8
Maximum50
Range50
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.7221129
Coefficient of variation (CV)0.52101423
Kurtosis86.016121
Mean5.2246422
Median Absolute Deviation (MAD)1
Skewness7.4502021
Sum25188
Variance7.4098989
MonotonicityNot monotonic
2024-04-18T03:11:56.191732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
5 2033
42.2%
4 1304
27.0%
6 635
 
13.2%
3 262
 
5.4%
7 193
 
4.0%
8 101
 
2.1%
2 79
 
1.6%
9 44
 
0.9%
10 38
 
0.8%
11 17
 
0.4%
Other values (16) 115
 
2.4%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 15
 
0.3%
2 79
 
1.6%
3 262
 
5.4%
4 1304
27.0%
5 2033
42.2%
6 635
 
13.2%
7 193
 
4.0%
8 101
 
2.1%
9 44
 
0.9%
ValueCountFrequency (%)
50 3
 
0.1%
39 6
0.1%
26 2
 
< 0.1%
25 4
 
0.1%
24 11
0.2%
20 14
0.3%
19 2
 
< 0.1%
18 6
0.1%
17 5
 
0.1%
16 1
 
< 0.1%

최대지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct8
Distinct (%)0.2%
Missing208
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean0.39986996
Minimum0
Maximum8
Zeros3275
Zeros (%)67.9%
Negative0
Negative (%)0.0%
Memory size42.5 KiB
2024-04-18T03:11:56.273929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.82019279
Coefficient of variation (CV)2.0511488
Kurtosis16.673545
Mean0.39986996
Median Absolute Deviation (MAD)0
Skewness3.4877301
Sum1845
Variance0.67271622
MonotonicityNot monotonic
2024-04-18T03:11:56.355544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 3275
67.9%
1 1094
 
22.7%
2 125
 
2.6%
3 43
 
0.9%
4 36
 
0.7%
6 20
 
0.4%
5 20
 
0.4%
8 1
 
< 0.1%
(Missing) 208
 
4.3%
ValueCountFrequency (%)
0 3275
67.9%
1 1094
 
22.7%
2 125
 
2.6%
3 43
 
0.9%
4 36
 
0.7%
5 20
 
0.4%
6 20
 
0.4%
8 1
 
< 0.1%
ValueCountFrequency (%)
8 1
 
< 0.1%
6 20
 
0.4%
5 20
 
0.4%
4 36
 
0.7%
3 43
 
0.9%
2 125
 
2.6%
1 1094
 
22.7%
0 3275
67.9%

주용도
Categorical

IMBALANCE 

Distinct18
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size37.8 KiB
공동주택
2248 
단독주택
1495 
제2종근린생활시설
553 
제1종근린생활시설
 
185
업무시설
 
156
Other values (13)
 
185

Length

Max length10
Median length4
Mean length4.8013273
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row공동주택
2nd row업무시설
3rd row공동주택
4th row문화및집회시설
5th row제2종근린생활시설

Common Values

ValueCountFrequency (%)
공동주택 2248
46.6%
단독주택 1495
31.0%
제2종근린생활시설 553
 
11.5%
제1종근린생활시설 185
 
3.8%
업무시설 156
 
3.2%
노유자시설 50
 
1.0%
교육연구시설 42
 
0.9%
숙박시설 26
 
0.5%
판매시설 24
 
0.5%
종교시설 15
 
0.3%
Other values (8) 28
 
0.6%

Length

2024-04-18T03:11:56.457407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공동주택 2248
46.6%
단독주택 1495
31.0%
제2종근린생활시설 553
 
11.5%
제1종근린생활시설 185
 
3.8%
업무시설 156
 
3.2%
노유자시설 50
 
1.0%
교육연구시설 42
 
0.9%
숙박시설 26
 
0.5%
판매시설 24
 
0.5%
종교시설 15
 
0.3%
Other values (8) 28
 
0.6%

부속용도
Text

MISSING 

Distinct1457
Distinct (%)32.4%
Missing322
Missing (%)6.7%
Memory size37.8 KiB
2024-04-18T03:11:56.635715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length41
Mean length10.875778
Min length2

Characters and Unicode

Total characters48941
Distinct characters203
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1149 ?
Unique (%)25.5%

Sample

1st row공동주택(아파트-도시형생활주택),업무시설(오피스텔),근린생활시설
2nd row업무시설(오피스텔), 근린생활시설
3rd row다세대주택 및 근린생활시설
4th row교회
5th row사무소
ValueCountFrequency (%)
다세대주택 843
 
13.5%
다가구주택 749
 
12.0%
및 513
 
8.2%
근린생활시설 321
 
5.1%
근생 181
 
2.9%
도시형생활주택 180
 
2.9%
도시형생활주택(단지형다세대 146
 
2.3%
다세대 134
 
2.1%
제2종근린생활시설 121
 
1.9%
사무소 103
 
1.6%
Other values (1069) 2958
47.3%
2024-04-18T03:11:56.953074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 3941
 
8.1%
택 3927
 
8.0%
다 3475
 
7.1%
시 2438
 
5.0%
생 2425
 
5.0%
대 2249
 
4.6%
세 2236
 
4.6%
활 2031
 
4.1%
구 1808
 
3.7%
가 1786
 
3.6%
Other values (193) 22625
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41194
84.2%
Space Separator 1770
 
3.6%
Decimal Number 1580
 
3.2%
Open Punctuation 1541
 
3.1%
Close Punctuation 1538
 
3.1%
Other Punctuation 1206
 
2.5%
Dash Punctuation 102
 
0.2%
Math Symbol 9
 
< 0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 3941
 
9.6%
택 3927
 
9.5%
다 3475
 
8.4%
시 2438
 
5.9%
생 2425
 
5.9%
대 2249
 
5.5%
세 2236
 
5.4%
활 2031
 
4.9%
구 1808
 
4.4%
가 1786
 
4.3%
Other values (167) 14878
36.1%
Decimal Number
ValueCountFrequency (%)
2 600
38.0%
1 407
25.8%
5 135
 
8.5%
8 79
 
5.0%
0 73
 
4.6%
6 73
 
4.6%
7 72
 
4.6%
4 58
 
3.7%
9 44
 
2.8%
3 39
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 861
71.4%
/ 245
 
20.3%
. 75
 
6.2%
: 21
 
1.7%
& 4
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 1531
99.4%
[ 7
 
0.5%
{ 3
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 1527
99.3%
] 8
 
0.5%
} 3
 
0.2%
Math Symbol
ValueCountFrequency (%)
+ 8
88.9%
= 1
 
11.1%
Space Separator
ValueCountFrequency (%)
1770
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 102
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41194
84.2%
Common 7747
 
15.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 3941
 
9.6%
택 3927
 
9.5%
다 3475
 
8.4%
시 2438
 
5.9%
생 2425
 
5.9%
대 2249
 
5.5%
세 2236
 
5.4%
활 2031
 
4.9%
구 1808
 
4.4%
가 1786
 
4.3%
Other values (167) 14878
36.1%
Common
ValueCountFrequency (%)
1770
22.8%
( 1531
19.8%
) 1527
19.7%
, 861
11.1%
2 600
 
7.7%
1 407
 
5.3%
/ 245
 
3.2%
5 135
 
1.7%
- 102
 
1.3%
8 79
 
1.0%
Other values (16) 490
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41194
84.2%
ASCII 7747
 
15.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 3941
 
9.6%
택 3927
 
9.5%
다 3475
 
8.4%
시 2438
 
5.9%
생 2425
 
5.9%
대 2249
 
5.5%
세 2236
 
5.4%
활 2031
 
4.9%
구 1808
 
4.4%
가 1786
 
4.3%
Other values (167) 14878
36.1%
ASCII
ValueCountFrequency (%)
1770
22.8%
( 1531
19.8%
) 1527
19.7%
, 861
11.1%
2 600
 
7.7%
1 407
 
5.3%
/ 245
 
3.2%
5 135
 
1.7%
- 102
 
1.3%
8 79
 
1.0%
Other values (16) 490
 
6.3%

용도지역
Categorical

Distinct17
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size37.8 KiB
제2종일반주거지역
2105 
도시지역
1290 
제1종일반주거지역
530 
제3종일반주거지역
341 
준주거지역
240 
Other values (12)
316 

Length

Max length15
Median length9
Mean length7.2911655
Min length4

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st row도시지역
2nd row도시지역
3rd row제2종일반주거지역
4th row제3종일반주거지역
5th row가로구역별최고높이제한지역

Common Values

ValueCountFrequency (%)
제2종일반주거지역 2105
43.7%
도시지역 1290
26.8%
제1종일반주거지역 530
 
11.0%
제3종일반주거지역 341
 
7.1%
준주거지역 240
 
5.0%
<NA> 140
 
2.9%
일반상업지역 80
 
1.7%
가로구역별최고높이제한지역 46
 
1.0%
건축용도지역기타 23
 
0.5%
일반주거지역 16
 
0.3%
Other values (7) 11
 
0.2%

Length

2024-04-18T03:11:57.057068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제2종일반주거지역 2105
43.7%
도시지역 1290
26.8%
제1종일반주거지역 530
 
11.0%
제3종일반주거지역 341
 
7.1%
준주거지역 240
 
5.0%
na 140
 
2.9%
일반상업지역 80
 
1.7%
가로구역별최고높이제한지역 46
 
1.0%
건축용도지역기타 23
 
0.5%
일반주거지역 16
 
0.3%
Other values (7) 11
 
0.2%

용도지구
Categorical

IMBALANCE 

Distinct21
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size37.8 KiB
<NA>
3572 
대공방어협조구역
637 
중심지미관지구
 
165
일반미관지구
 
145
최고고도지구
 
124
Other values (16)
 
179

Length

Max length15
Median length4
Mean length4.8430112
Min length4

Unique

Unique6 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3572
74.1%
대공방어협조구역 637
 
13.2%
중심지미관지구 165
 
3.4%
일반미관지구 145
 
3.0%
최고고도지구 124
 
2.6%
역사문화미관지구 50
 
1.0%
고도지구 33
 
0.7%
조망가로미관지구 29
 
0.6%
조망가로특화경관지구 12
 
0.2%
재정비촉진지구 12
 
0.2%
Other values (11) 43
 
0.9%

Length

2024-04-18T03:11:57.150190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3572
74.1%
대공방어협조구역 637
 
13.2%
중심지미관지구 165
 
3.4%
일반미관지구 145
 
3.0%
최고고도지구 124
 
2.6%
역사문화미관지구 50
 
1.0%
고도지구 33
 
0.7%
조망가로미관지구 29
 
0.6%
조망가로특화경관지구 12
 
0.2%
재정비촉진지구 12
 
0.2%
Other values (11) 43
 
0.9%

용도구역
Categorical

IMBALANCE 

Distinct27
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size37.8 KiB
<NA>
3428 
학교환경위생정화구역
370 
제1종지구단위계획구역
 
324
지구단위계획구역
 
228
중점경관관리구역
 
129
Other values (22)
343 

Length

Max length17
Median length4
Mean length5.4966819
Min length4

Unique

Unique7 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3428
71.1%
학교환경위생정화구역 370
 
7.7%
제1종지구단위계획구역 324
 
6.7%
지구단위계획구역 228
 
4.7%
중점경관관리구역 129
 
2.7%
가축사육제한구역 98
 
2.0%
대공방어 협조구역 85
 
1.8%
상수원보호기타 76
 
1.6%
대공방어협조구역 20
 
0.4%
상대보호구역 13
 
0.3%
Other values (17) 51
 
1.1%

Length

2024-04-18T03:11:57.262206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3428
69.8%
학교환경위생정화구역 370
 
7.5%
제1종지구단위계획구역 324
 
6.6%
지구단위계획구역 228
 
4.6%
중점경관관리구역 129
 
2.6%
가축사육제한구역 98
 
2.0%
대공방어 85
 
1.7%
협조구역 85
 
1.7%
상수원보호기타 76
 
1.5%
대공방어협조구역 20
 
0.4%
Other values (19) 67
 
1.4%

세대수
Real number (ℝ)

MISSING  SKEWED 

Distinct54
Distinct (%)2.3%
Missing2480
Missing (%)51.4%
Infinite0
Infinite (%)0.0%
Mean13.152861
Minimum0
Maximum1177
Zeros7
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size42.5 KiB
2024-04-18T03:11:57.391105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q18
median10
Q313
95-th percentile22
Maximum1177
Range1177
Interquartile range (IQR)5

Descriptive statistics

Standard deviation31.631119
Coefficient of variation (CV)2.4048851
Kurtosis804.32931
Mean13.152861
Median Absolute Deviation (MAD)3
Skewness24.179416
Sum30804
Variance1000.5277
MonotonicityNot monotonic
2024-04-18T03:11:57.508765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 357
 
7.4%
10 330
 
6.8%
7 263
 
5.5%
12 193
 
4.0%
6 163
 
3.4%
9 146
 
3.0%
11 134
 
2.8%
16 108
 
2.2%
14 87
 
1.8%
13 84
 
1.7%
Other values (44) 477
 
9.9%
(Missing) 2480
51.4%
ValueCountFrequency (%)
0 7
 
0.1%
1 21
 
0.4%
2 4
 
0.1%
3 10
 
0.2%
4 54
 
1.1%
5 49
 
1.0%
6 163
3.4%
7 263
5.5%
8 357
7.4%
9 146
3.0%
ValueCountFrequency (%)
1177 1
 
< 0.1%
299 1
 
< 0.1%
296 1
 
< 0.1%
291 1
 
< 0.1%
260 3
0.1%
252 6
0.1%
181 1
 
< 0.1%
162 2
 
< 0.1%
146 2
 
< 0.1%
99 2
 
< 0.1%

호수
Real number (ℝ)

MISSING  SKEWED 

Distinct72
Distinct (%)11.5%
Missing4195
Missing (%)87.0%
Infinite0
Infinite (%)0.0%
Mean22.912281
Minimum0
Maximum3819
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size42.5 KiB
2024-04-18T03:11:57.837650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q35.5
95-th percentile71.5
Maximum3819
Range3819
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation164.57655
Coefficient of variation (CV)7.1828969
Kurtosis454.45543
Mean22.912281
Median Absolute Deviation (MAD)1
Skewness20.010536
Sum14366
Variance27085.441
MonotonicityNot monotonic
2024-04-18T03:11:57.942785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 257
 
5.3%
2 110
 
2.3%
3 47
 
1.0%
4 35
 
0.7%
6 24
 
0.5%
5 20
 
0.4%
8 15
 
0.3%
10 6
 
0.1%
7 6
 
0.1%
21 6
 
0.1%
Other values (62) 101
 
2.1%
(Missing) 4195
87.0%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 257
5.3%
2 110
2.3%
3 47
 
1.0%
4 35
 
0.7%
5 20
 
0.4%
6 24
 
0.5%
7 6
 
0.1%
8 15
 
0.3%
9 6
 
0.1%
ValueCountFrequency (%)
3819 1
< 0.1%
537 1
< 0.1%
535 2
< 0.1%
514 1
< 0.1%
464 1
< 0.1%
446 1
< 0.1%
419 2
< 0.1%
398 1
< 0.1%
366 1
< 0.1%
291 1
< 0.1%

가구수
Real number (ℝ)

MISSING 

Distinct21
Distinct (%)1.2%
Missing3065
Missing (%)63.6%
Infinite0
Infinite (%)0.0%
Mean5.2686397
Minimum0
Maximum28
Zeros6
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size42.5 KiB
2024-04-18T03:11:58.053944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median5
Q36
95-th percentile10
Maximum28
Range28
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.7004178
Coefficient of variation (CV)0.51254554
Kurtosis5.1187291
Mean5.2686397
Median Absolute Deviation (MAD)1
Skewness1.3075256
Sum9257
Variance7.2922563
MonotonicityNot monotonic
2024-04-18T03:11:58.156714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
5 499
 
10.3%
6 219
 
4.5%
4 195
 
4.0%
7 193
 
4.0%
3 177
 
3.7%
1 130
 
2.7%
2 94
 
1.9%
9 71
 
1.5%
8 64
 
1.3%
10 39
 
0.8%
Other values (11) 76
 
1.6%
(Missing) 3065
63.6%
ValueCountFrequency (%)
0 6
 
0.1%
1 130
 
2.7%
2 94
 
1.9%
3 177
 
3.7%
4 195
 
4.0%
5 499
10.3%
6 219
4.5%
7 193
 
4.0%
8 64
 
1.3%
9 71
 
1.5%
ValueCountFrequency (%)
28 1
 
< 0.1%
19 2
 
< 0.1%
18 2
 
< 0.1%
17 2
 
< 0.1%
16 3
 
0.1%
15 6
 
0.1%
14 6
 
0.1%
13 9
 
0.2%
12 23
0.5%
11 16
0.3%

Sample

건축구분건물명대지위치대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일사용승인일최대지상층수최대지하층수주용도부속용도용도지역용도지구용도구역세대수호수가구수
0신축화양동 18-12 주거복합 신축공사서울특별시 광진구 화양동 18-12736.9439.36657827.92<NA>59.62659.75철근콘크리트구조2021-04-212021-09-232024-01-31184공동주택공동주택(아파트-도시형생활주택),업무시설(오피스텔),근린생활시설도시지역<NA>지구단위계획구역9933<NA>
1대수선건대 트레비앙 오피스텔서울특별시 광진구 화양동 1741809.01069.6118289.01<NA>59.13720.51철근콘크리트구조2023-10-312023-12-222024-01-30184업무시설업무시설(오피스텔), 근린생활시설도시지역<NA>지구단위계획구역<NA>419<NA>
2신축엘케이플레이스5차서울특별시 광진구 자양동 832-29134.080.23254.61<NA>59.87190.01철근콘크리트구조2022-08-092022-10-212024-01-2350공동주택다세대주택 및 근린생활시설제2종일반주거지역<NA><NA>61<NA>
3대수선성산교회서울특별시 광진구 자양동 658-1773.6468.192102.89<NA>60.52209.76철근콘크리트구조2023-07-052023-08-042024-01-1751문화및집회시설교회제3종일반주거지역<NA><NA><NA><NA><NA>
4신축군자동 91-6서울특별시 광진구 군자동 91-6202.399.51132.46<NA>49.189365.477일반철골구조2023-04-282023-08-102024-01-0320제2종근린생활시설사무소가로구역별최고높이제한지역대공방어협조구역<NA><NA><NA><NA>
5신축<NA>서울특별시 광진구 화양동 23-3 외1필지252.2117.221086.54<NA>46.479386.8279철근콘크리트구조2022-05-132022-09-142024-01-03101숙박시설호스텔도시지역<NA>지구단위계획구역<NA><NA><NA>
6증축워커힐 호텔서울특별시 광진구 광장동 22-1 외173필지261288.034079.36193804.461324.6113.0443.498막구조2023-06-142023-06-292024-01-02154숙박시설관광호텔도시지역역사문화미관지구중점경관관리구역<NA><NA><NA>
7대수선중앙농업협동조합서울특별시 광진구 자양동 635-81463.3844.864838.62<NA>57.7366187.5876<NA>2023-07-212023-11-212023-12-2942업무시설판매시설제2종일반주거지역<NA><NA><NA><NA><NA>
8신축구의동 220-34 다가구주택서울특별시 광진구 구의동 220-34146.187.15363.7<NA>59.65185.0171철근콘크리트구조2021-12-012023-02-272023-12-2941단독주택다가구도시지역대공방어협조구역<NA><NA><NA>6
9신축상진라인빌서울특별시 광진구 중곡동 196-8 외1필지239.4143.04478.48<NA>59.75199.87철근콘크리트구조2022-07-122022-09-262023-12-2250공동주택다세대주택도시지역대공방어협조구역<NA>10<NA><NA>
건축구분건물명대지위치대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일사용승인일최대지상층수최대지하층수주용도부속용도용도지역용도지구용도구역세대수호수가구수
4812신축화양빌딩서울특별시 광진구 화양동 20-23180.23107.99604.22<NA>59.92335.25철근콘크리트구조2009-06-152009-06-192010-01-1870제2종근린생활시설사뭄실, 1종근생한의원준주거지역기타지구기타구역<NA><NA><NA>
4813신축화양동 20-47 제2종근린생활시설 (김흥기)서울특별시 광진구 화양동 20-47180.45107.99604.22<NA>59.84334.84철근콘크리트구조2009-06-102009-06-222010-01-1870제2종근린생활시설사무실.1종근생(한의원)준주거지역기타지구기타구역<NA><NA><NA>
4814신축군자동 117-24 공동주택서울특별시 광진구 군자동 117-24186.5111.83372.5<NA>59.96199.73철근콘크리트구조2009-09-102009-10-122010-01-1450공동주택다세대주택제2종일반주거지역<NA><NA>12<NA><NA>
4815신축<NA>서울특별시 광진구 화양동 36-95176.9105.69348.96<NA>59.75197.26철근콘크리트구조2009-09-212009-09-242010-01-1350공동주택다세대주택제2종일반주거지역<NA><NA>13<NA><NA>
4816신축<NA>서울특별시 광진구 중곡동 241-16345.5156.46690.32<NA>45.29199.8철근콘크리트구조2009-06-112009-07-022010-01-1350제1종근린생활시설의원,소매점제2종일반주거지역일반미관지구대공방어협조구역<NA><NA><NA>
4817신축구의동다세대주택서울특별시 광진구 구의동 225-12 외1필지230.0137.88438.57<NA>59.95190.68철근콘크리트구조2003-06-232003-06-302010-01-1350공동주택다세대주택일반주거지역<NA><NA>6<NA><NA>
4818용도변경구의동 56-2 제2종근린생활시설 (강희봉)서울특별시 광진구 구의동 56-2306.1141.69795.12<NA>46.2888210.1601철근콘크리트구조2010-01-06<NA>2010-01-1151제2종근린생활시설사무소제2종일반주거지역<NA><NA><NA><NA><NA>
4819대수선능동 244-22 단독주택 (이익상)서울특별시 광진구 능동 244-22202.3120.53302.76<NA>59.5798149.6589철근콘크리트구조2009-12-242009-12-292010-01-064<NA>단독주택다가구주택제1종일반주거지역<NA><NA><NA><NA>9
4820신축<NA>서울특별시 광진구 자양동 667-7172.7103.43233.98<NA>59.89135.48철근콘크리트구조2009-08-312009-09-042010-01-0630단독주택<NA><NA><NA><NA><NA><NA><NA>
4821신축능동 펠리시움Ι서울특별시 광진구 능동 232-3 외4필지321.8193.02477.29<NA>59.98148.32철근콘크리트구조2009-07-312009-08-042010-01-0640공동주택다세대주택제1종일반주거지역최고고도지구<NA>8<NA><NA>

Duplicate rows

Most frequently occurring

건축구분건물명대지위치대지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)증축연면적(제곱미터)건폐율(퍼센트)용적률(퍼센트)구조허가일착공처리일사용승인일최대지상층수최대지하층수주용도부속용도용도지역용도지구용도구역세대수호수가구수# duplicates
0증축<NA>서울특별시 광진구 중곡동 150-383324.0184.7682.3734.857.0210.6철근콘크리트구조2010-11-01<NA>2012-02-135<NA>공동주택다세대주택제2종일반주거지역<NA><NA>12<NA><NA>3