Overview

Dataset statistics

Number of variables9
Number of observations53
Missing cells20
Missing cells (%)4.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory76.5 B

Variable types

Numeric2
Text4
Categorical3

Dataset

Description서울특별시 동대문구 개발행위허가정보 목록(해당년도, 위치명, 지목명, 허가면적, 용도지역 및 용도지구, 허가일자, 개발행위 목적 및 사유 등)
Author서울특별시 동대문구
URLhttps://www.data.go.kr/data/15036615/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
개발행위 목적 및 사유 is highly overall correlated with 해당년도 and 2 other fieldsHigh correlation
개발행위구분 is highly overall correlated with 해당년도 and 2 other fieldsHigh correlation
해당년도 is highly overall correlated with 개발행위구분 and 1 other fieldsHigh correlation
허가면적(제곱미터) is highly overall correlated with 개발행위구분 and 1 other fieldsHigh correlation
개발행위구분 is highly imbalanced (57.3%)Imbalance
개발행위 목적 및 사유 is highly imbalanced (59.6%)Imbalance
위치명 has 5 (9.4%) missing valuesMissing
지목명 has 5 (9.4%) missing valuesMissing
허가면적(제곱미터) has 5 (9.4%) missing valuesMissing
용도지역 및 지구 has 5 (9.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 13:03:46.686355
Analysis finished2023-12-12 13:03:47.984476
Duration1.3 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

해당년도
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.6792
Minimum2009
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T22:03:48.035841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2009
5-th percentile2011.6
Q12017
median2019
Q32021
95-th percentile2022.4
Maximum2023
Range14
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.4739336
Coefficient of variation (CV)0.0017208943
Kurtosis0.53023445
Mean2018.6792
Median Absolute Deviation (MAD)2
Skewness-1.0408019
Sum106990
Variance12.068215
MonotonicityIncreasing
2023-12-12T22:03:48.176133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2022 10
18.9%
2019 7
13.2%
2021 7
13.2%
2020 6
11.3%
2017 5
9.4%
2018 4
 
7.5%
2015 3
 
5.7%
2023 3
 
5.7%
2014 2
 
3.8%
2009 1
 
1.9%
Other values (5) 5
9.4%
ValueCountFrequency (%)
2009 1
 
1.9%
2010 1
 
1.9%
2011 1
 
1.9%
2012 1
 
1.9%
2013 1
 
1.9%
2014 2
 
3.8%
2015 3
5.7%
2016 1
 
1.9%
2017 5
9.4%
2018 4
7.5%
ValueCountFrequency (%)
2023 3
 
5.7%
2022 10
18.9%
2021 7
13.2%
2020 6
11.3%
2019 7
13.2%
2018 4
 
7.5%
2017 5
9.4%
2016 1
 
1.9%
2015 3
 
5.7%
2014 2
 
3.8%

위치명
Text

MISSING 

Distinct47
Distinct (%)97.9%
Missing5
Missing (%)9.4%
Memory size556.0 B
2023-12-12T22:03:48.459476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length9
Min length4

Characters and Unicode

Total characters432
Distinct characters106
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)95.8%

Sample

1st row휘경동 43-153호 외 2필지
2nd row휘경동 43-154호 외 5필지
3rd row한사랑 태양광발전소
4th row완후 태양광발전소
5th row동답공영주차장
ValueCountFrequency (%)
장안동 5
 
5.8%
휘경동 4
 
4.7%
외 4
 
4.7%
전농동 3
 
3.5%
제기동 3
 
3.5%
태양광발전소 2
 
2.3%
신설동 2
 
2.3%
이문동 2
 
2.3%
국립산림과학원 2
 
2.3%
답십리동 2
 
2.3%
Other values (57) 57
66.3%
2023-12-12T22:03:48.894949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
9.0%
동 29
 
6.7%
1 19
 
4.4%
- 19
 
4.4%
2 19
 
4.4%
3 13
 
3.0%
전 10
 
2.3%
5 10
 
2.3%
6 10
 
2.3%
장 10
 
2.3%
Other values (96) 254
58.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 267
61.8%
Decimal Number 101
 
23.4%
Space Separator 39
 
9.0%
Dash Punctuation 19
 
4.4%
Open Punctuation 2
 
0.5%
Close Punctuation 2
 
0.5%
Uppercase Letter 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 29
 
10.9%
전 10
 
3.7%
장 10
 
3.7%
대 9
 
3.4%
문 9
 
3.4%
소 8
 
3.0%
안 7
 
2.6%
휘 6
 
2.2%
경 6
 
2.2%
외 6
 
2.2%
Other values (80) 167
62.5%
Decimal Number
ValueCountFrequency (%)
1 19
18.8%
2 19
18.8%
3 13
12.9%
5 10
9.9%
6 10
9.9%
4 8
7.9%
0 7
 
6.9%
9 7
 
6.9%
8 5
 
5.0%
7 3
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 267
61.8%
Common 163
37.7%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 29
 
10.9%
전 10
 
3.7%
장 10
 
3.7%
대 9
 
3.4%
문 9
 
3.4%
소 8
 
3.0%
안 7
 
2.6%
휘 6
 
2.2%
경 6
 
2.2%
외 6
 
2.2%
Other values (80) 167
62.5%
Common
ValueCountFrequency (%)
39
23.9%
1 19
11.7%
- 19
11.7%
2 19
11.7%
3 13
 
8.0%
5 10
 
6.1%
6 10
 
6.1%
4 8
 
4.9%
0 7
 
4.3%
9 7
 
4.3%
Other values (4) 12
 
7.4%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 267
61.8%
ASCII 165
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
23.6%
1 19
11.5%
- 19
11.5%
2 19
11.5%
3 13
 
7.9%
5 10
 
6.1%
6 10
 
6.1%
4 8
 
4.8%
0 7
 
4.2%
9 7
 
4.2%
Other values (6) 14
 
8.5%
Hangul
ValueCountFrequency (%)
동 29
 
10.9%
전 10
 
3.7%
장 10
 
3.7%
대 9
 
3.4%
문 9
 
3.4%
소 8
 
3.0%
안 7
 
2.6%
휘 6
 
2.2%
경 6
 
2.2%
외 6
 
2.2%
Other values (80) 167
62.5%

지목명
Text

MISSING 

Distinct46
Distinct (%)95.8%
Missing5
Missing (%)9.4%
Memory size556.0 B
2023-12-12T22:03:49.206864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length10
Min length7

Characters and Unicode

Total characters480
Distinct characters38
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

Unique44 ?
Unique (%)91.7%

Sample

1st row휘경동 43-153호 외 2필지
2nd row휘경동 43-154호 외 5필지
3rd row장안동 331-9
4th row이문동 264-211
5th row답십리동 2-283
ValueCountFrequency (%)
장안동 10
 
9.3%
답십리동 8
 
7.5%
휘경동 6
 
5.6%
전농동 5
 
4.7%
외 5
 
4.7%
이문동 5
 
4.7%
용두동 4
 
3.7%
청량리동 4
 
3.7%
제기동 3
 
2.8%
39-9 2
 
1.9%
Other values (52) 55
51.4%
2023-12-12T22:03:49.657406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
59
 
12.3%
동 48
 
10.0%
- 42
 
8.8%
2 33
 
6.9%
1 32
 
6.7%
3 27
 
5.6%
6 23
 
4.8%
4 22
 
4.6%
9 20
 
4.2%
0 14
 
2.9%
Other values (28) 160
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 206
42.9%
Other Letter 173
36.0%
Space Separator 59
 
12.3%
Dash Punctuation 42
 
8.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 48
27.7%
리 12
 
6.9%
안 10
 
5.8%
장 10
 
5.8%
답 8
 
4.6%
십 8
 
4.6%
경 6
 
3.5%
외 6
 
3.5%
휘 6
 
3.5%
전 5
 
2.9%
Other values (16) 54
31.2%
Decimal Number
ValueCountFrequency (%)
2 33
16.0%
1 32
15.5%
3 27
13.1%
6 23
11.2%
4 22
10.7%
9 20
9.7%
0 14
6.8%
5 13
 
6.3%
8 11
 
5.3%
7 11
 
5.3%
Space Separator
ValueCountFrequency (%)
59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 307
64.0%
Hangul 173
36.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 48
27.7%
리 12
 
6.9%
안 10
 
5.8%
장 10
 
5.8%
답 8
 
4.6%
십 8
 
4.6%
경 6
 
3.5%
외 6
 
3.5%
휘 6
 
3.5%
전 5
 
2.9%
Other values (16) 54
31.2%
Common
ValueCountFrequency (%)
59
19.2%
- 42
13.7%
2 33
10.7%
1 32
10.4%
3 27
8.8%
6 23
 
7.5%
4 22
 
7.2%
9 20
 
6.5%
0 14
 
4.6%
5 13
 
4.2%
Other values (2) 22
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 307
64.0%
Hangul 173
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
59
19.2%
- 42
13.7%
2 33
10.7%
1 32
10.4%
3 27
8.8%
6 23
 
7.5%
4 22
 
7.2%
9 20
 
6.5%
0 14
 
4.6%
5 13
 
4.2%
Other values (2) 22
 
7.2%
Hangul
ValueCountFrequency (%)
동 48
27.7%
리 12
 
6.9%
안 10
 
5.8%
장 10
 
5.8%
답 8
 
4.6%
십 8
 
4.6%
경 6
 
3.5%
외 6
 
3.5%
휘 6
 
3.5%
전 5
 
2.9%
Other values (16) 54
31.2%

허가면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct45
Distinct (%)93.8%
Missing5
Missing (%)9.4%
Infinite0
Infinite (%)0.0%
Mean159.75063
Minimum7.36
Maximum629.64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T22:03:49.822010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.36
5-th percentile37.0045
Q153.35
median89.04
Q3244.0775
95-th percentile418.9175
Maximum629.64
Range622.28
Interquartile range (IQR)190.7275

Descriptive statistics

Standard deviation150.01252
Coefficient of variation (CV)0.93904182
Kurtosis2.1356849
Mean159.75063
Median Absolute Deviation (MAD)43.89
Skewness1.5628031
Sum7668.03
Variance22503.756
MonotonicityNot monotonic
2023-12-12T22:03:49.974135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
45.33 3
 
5.7%
86.17 2
 
3.8%
7.36 1
 
1.9%
618.24 1
 
1.9%
421.0 1
 
1.9%
243.32 1
 
1.9%
65.0 1
 
1.9%
246.35 1
 
1.9%
60.79 1
 
1.9%
121.67 1
 
1.9%
Other values (35) 35
66.0%
(Missing) 5
 
9.4%
ValueCountFrequency (%)
7.36 1
 
1.9%
35.8 1
 
1.9%
36.0 1
 
1.9%
38.87 1
 
1.9%
43.0 1
 
1.9%
45.0 1
 
1.9%
45.3 1
 
1.9%
45.33 3
5.7%
46.79 1
 
1.9%
48.7 1
 
1.9%
ValueCountFrequency (%)
629.64 1
1.9%
618.24 1
1.9%
421.0 1
1.9%
415.05 1
1.9%
401.83 1
1.9%
339.2 1
1.9%
330.89 1
1.9%
300.0 1
1.9%
289.0 1
1.9%
288.0 1
1.9%

용도지역 및 지구
Text

MISSING 

Distinct32
Distinct (%)66.7%
Missing5
Missing (%)9.4%
Memory size556.0 B
2023-12-12T22:03:50.214787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length35
Mean length20.729167
Min length5

Characters and Unicode

Total characters995
Distinct characters67
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)45.8%

Sample

1st row도시지역, 제2종일반주거지역
2nd row도시지역, 제2종일반주거지역
3rd row도시지역, 제3종일반주거지역
4th row도시지역, 제2종일반주거지역
5th row도시지역, 제3종일반주거지역, 주차장
ValueCountFrequency (%)
도시지역 40
27.6%
19
13.1%
제2종일반주거지역 17
11.7%
제3종일반주거지역 11
 
7.6%
일반상업지역 9
 
6.2%
준주거지역 5
 
3.4%
제1종일반주거지역 5
 
3.4%
도로(접합 5
 
3.4%
주차장 3
 
2.1%
제2종일반주거지역(7층이하 3
 
2.1%
Other values (22) 28
19.3%
2023-12-12T22:03:50.617636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 103
 
10.4%
역 100
 
10.1%
97
 
9.7%
, 77
 
7.7%
도 47
 
4.7%
일 46
 
4.6%
반 45
 
4.5%
주 44
 
4.4%
시 41
 
4.1%
거 41
 
4.1%
Other values (57) 354
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 734
73.8%
Space Separator 97
 
9.7%
Other Punctuation 77
 
7.7%
Decimal Number 49
 
4.9%
Close Punctuation 19
 
1.9%
Open Punctuation 19
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 103
14.0%
역 100
13.6%
도 47
 
6.4%
일 46
 
6.3%
반 45
 
6.1%
주 44
 
6.0%
시 41
 
5.6%
거 41
 
5.6%
종 38
 
5.2%
제 38
 
5.2%
Other values (49) 191
26.0%
Decimal Number
ValueCountFrequency (%)
2 21
42.9%
3 15
30.6%
1 10
20.4%
7 3
 
6.1%
Space Separator
ValueCountFrequency (%)
97
100.0%
Other Punctuation
ValueCountFrequency (%)
, 77
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 734
73.8%
Common 261
 
26.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 103
14.0%
역 100
13.6%
도 47
 
6.4%
일 46
 
6.3%
반 45
 
6.1%
주 44
 
6.0%
시 41
 
5.6%
거 41
 
5.6%
종 38
 
5.2%
제 38
 
5.2%
Other values (49) 191
26.0%
Common
ValueCountFrequency (%)
97
37.2%
, 77
29.5%
2 21
 
8.0%
) 19
 
7.3%
( 19
 
7.3%
3 15
 
5.7%
1 10
 
3.8%
7 3
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 734
73.8%
ASCII 261
 
26.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 103
14.0%
역 100
13.6%
도 47
 
6.4%
일 46
 
6.3%
반 45
 
6.1%
주 44
 
6.0%
시 41
 
5.6%
거 41
 
5.6%
종 38
 
5.2%
제 38
 
5.2%
Other values (49) 191
26.0%
ASCII
ValueCountFrequency (%)
97
37.2%
, 77
29.5%
2 21
 
8.0%
) 19
 
7.3%
( 19
 
7.3%
3 15
 
5.7%
1 10
 
3.8%
7 3
 
1.1%

개발행위구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
공작물 설치
46 
<NA>
5 
토지형질변경
 
2

Length

Max length6
Median length6
Mean length5.8113208
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공작물 설치 46
86.8%
<NA> 5
 
9.4%
토지형질변경 2
 
3.8%

Length

2023-12-12T22:03:50.785953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:03:50.924775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공작물 46
46.5%
설치 46
46.5%
na 5
 
5.1%
토지형질변경 2
 
2.0%

허가일자
Text

Distinct39
Distinct (%)73.6%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T22:03:51.177641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.6226415
Min length6

Characters and Unicode

Total characters510
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)60.4%

Sample

1st row허가내역없음
2nd row허가내역없음
3rd row허가내역없음
4th row허가내역없음
5th row허가내역없음
ValueCountFrequency (%)
허가내역없음 5
 
9.4%
2017-06-16 3
 
5.7%
2018-06-11 3
 
5.7%
2022-11-14 3
 
5.7%
2022-03-07 3
 
5.7%
2014-11-27 2
 
3.8%
2020-12-31 2
 
3.8%
2021-11-29 1
 
1.9%
2021-02-15 1
 
1.9%
2021-05-10 1
 
1.9%
Other values (29) 29
54.7%
2023-12-12T22:03:51.573771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 111
21.8%
0 102
20.0%
- 96
18.8%
1 83
16.3%
7 16
 
3.1%
9 14
 
2.7%
5 14
 
2.7%
3 13
 
2.5%
6 13
 
2.5%
8 9
 
1.8%
Other values (7) 39
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 384
75.3%
Dash Punctuation 96
 
18.8%
Other Letter 30
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 111
28.9%
0 102
26.6%
1 83
21.6%
7 16
 
4.2%
9 14
 
3.6%
5 14
 
3.6%
3 13
 
3.4%
6 13
 
3.4%
8 9
 
2.3%
4 9
 
2.3%
Other Letter
ValueCountFrequency (%)
음 5
16.7%
가 5
16.7%
없 5
16.7%
역 5
16.7%
내 5
16.7%
허 5
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 480
94.1%
Hangul 30
 
5.9%

Most frequent character per script

Common
ValueCountFrequency (%)
2 111
23.1%
0 102
21.2%
- 96
20.0%
1 83
17.3%
7 16
 
3.3%
9 14
 
2.9%
5 14
 
2.9%
3 13
 
2.7%
6 13
 
2.7%
8 9
 
1.9%
Hangul
ValueCountFrequency (%)
음 5
16.7%
가 5
16.7%
없 5
16.7%
역 5
16.7%
내 5
16.7%
허 5
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 480
94.1%
Hangul 30
 
5.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 111
23.1%
0 102
21.2%
- 96
20.0%
1 83
17.3%
7 16
 
3.3%
9 14
 
2.9%
5 14
 
2.9%
3 13
 
2.7%
6 13
 
2.7%
8 9
 
1.9%
Hangul
ValueCountFrequency (%)
음 5
16.7%
가 5
16.7%
없 5
16.7%
역 5
16.7%
내 5
16.7%
허 5
16.7%

개발행위 목적 및 사유
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size556.0 B
태양광 설치
45 
<NA>
5 
건축물 건축을 위한 토지형질변경
 
2
방음벽 설치
 
1

Length

Max length17
Median length6
Mean length6.2264151
Min length4

Unique

Unique1 ?
Unique (%)1.9%

Sample

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

Common Values

ValueCountFrequency (%)
태양광 설치 45
84.9%
<NA> 5
 
9.4%
건축물 건축을 위한 토지형질변경 2
 
3.8%
방음벽 설치 1
 
1.9%

Length

2023-12-12T22:03:51.748289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:03:51.859884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
설치 46
43.8%
태양광 45
42.9%
na 5
 
4.8%
건축물 2
 
1.9%
건축을 2
 
1.9%
위한 2
 
1.9%
토지형질변경 2
 
1.9%
방음벽 1
 
1.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-09-20
53 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-20
2nd row2023-09-20
3rd row2023-09-20
4th row2023-09-20
5th row2023-09-20

Common Values

ValueCountFrequency (%)
2023-09-20 53
100.0%

Length

2023-12-12T22:03:51.991755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:03:52.121852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-20 53
100.0%

Interactions

2023-12-12T22:03:47.287510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:03:47.116233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:03:47.463511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:03:47.208533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:03:52.204622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
해당년도위치명지목명허가면적(제곱미터)용도지역 및 지구개발행위구분허가일자개발행위 목적 및 사유
해당년도1.0000.9450.9020.5410.7451.0000.7940.748
위치명0.9451.0001.0001.0001.0001.0000.9881.000
지목명0.9021.0001.0000.9491.0001.0000.9531.000
허가면적(제곱미터)0.5411.0000.9491.0000.8730.9300.5810.787
용도지역 및 지구0.7451.0001.0000.8731.0000.0000.9640.558
개발행위구분1.0001.0001.0000.9300.0001.0001.0001.000
허가일자0.7940.9880.9530.5810.9641.0001.0001.000
개발행위 목적 및 사유0.7481.0001.0000.7870.5581.0001.0001.000
2023-12-12T22:03:52.339010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개발행위 목적 및 사유개발행위구분
개발행위 목적 및 사유1.0000.989
개발행위구분0.9891.000
2023-12-12T22:03:52.453067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
해당년도허가면적(제곱미터)개발행위구분개발행위 목적 및 사유
해당년도1.000-0.1760.9440.647
허가면적(제곱미터)-0.1761.0000.7170.663
개발행위구분0.9440.7171.0000.989
개발행위 목적 및 사유0.6470.6630.9891.000

Missing values

2023-12-12T22:03:47.594676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:03:47.769874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T22:03:47.903587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

해당년도위치명지목명허가면적(제곱미터)용도지역 및 지구개발행위구분허가일자개발행위 목적 및 사유데이터기준일자
02009<NA><NA><NA><NA><NA>허가내역없음<NA>2023-09-20
12010<NA><NA><NA><NA><NA>허가내역없음<NA>2023-09-20
22011<NA><NA><NA><NA><NA>허가내역없음<NA>2023-09-20
32012<NA><NA><NA><NA><NA>허가내역없음<NA>2023-09-20
42013<NA><NA><NA><NA><NA>허가내역없음<NA>2023-09-20
52014휘경동 43-153호 외 2필지휘경동 43-153호 외 2필지289.0도시지역, 제2종일반주거지역토지형질변경2014-11-27건축물 건축을 위한 토지형질변경2023-09-20
62014휘경동 43-154호 외 5필지휘경동 43-154호 외 5필지288.0도시지역, 제2종일반주거지역토지형질변경2014-11-27건축물 건축을 위한 토지형질변경2023-09-20
72015한사랑 태양광발전소장안동 331-9195.1도시지역, 제3종일반주거지역공작물 설치2015-04-29태양광 설치2023-09-20
82015완후 태양광발전소이문동 264-211104.0도시지역, 제2종일반주거지역공작물 설치2015-06-24태양광 설치2023-09-20
92015동답공영주차장답십리동 2-28385.77도시지역, 제3종일반주거지역, 주차장공작물 설치2015-12-17태양광 설치2023-09-20
해당년도위치명지목명허가면적(제곱미터)용도지역 및 지구개발행위구분허가일자개발행위 목적 및 사유데이터기준일자
432022동대문구청사(옥상)용두동 39-9401.83도시지역, 제2종일반주거지역, 공공청사공작물 설치2022-03-08태양광 설치2023-09-20
442022휘경동 281-1 외 7휘경동 281-1 외 7415.05도시지역, 제3종일반주거지역공작물 설치2022-10-11태양광 설치2023-09-20
452022제기동 1110제기동 111045.0제2종일반주거지역공작물 설치2022-11-14태양광 설치2023-09-20
462022장안동 106-6장안동 106-686.17제3종일반주거지역공작물 설치2022-11-14태양광 설치2023-09-20
472022장안동 106-26장안동 106-2686.17제3종일반주거지역공작물 설치2022-11-14태양광 설치2023-09-20
482022장안동 330-3장안동 330-3339.2준주거지역공작물 설치2022-12-07태양광 설치2023-09-20
492022장안동 432-4장안동 432-443.0일반상업지역공작물 설치2022-12-09태양광 설치2023-09-20
502023전농동 620-6외 2전농동 620-6외 264.3일반상업지역공작물 설치2023-01-27태양광 설치2023-09-20
512023답십리동 952-8답십리동 952-871.41일반상업지역공작물 설치2023-05-02태양광 설치2023-09-20
522023전농동 498-21전농동 498-2191.91제3종일반주거지역공작물 설치2023-05-30태양광 설치2023-09-20