Overview

Dataset statistics

Number of variables14
Number of observations772
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory87.6 KiB
Average record size in memory116.2 B

Variable types

Numeric4
Text4
Categorical5
DateTime1

Dataset

Description객체id,현황도형 관리번호,도형 대분류코드,도형 중분류코드,도형 소분류코드,도형 속성코드,도형 조서관리 코드,결정고시관리코드,라벨명,시군구코드,도면번호,현황도형 생성일시,면적(도형),길이(도형)
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21164/S/1/datasetView.do

Alerts

도형 중분류코드 has constant value ""Constant
도형 소분류코드 has constant value ""Constant
면적(도형) is highly overall correlated with 길이(도형)High correlation
길이(도형) is highly overall correlated with 면적(도형)High correlation
도형 대분류코드 is highly imbalanced (98.6%)Imbalance
도형 속성코드 is highly imbalanced (98.6%)Imbalance
도면번호 is highly imbalanced (68.5%)Imbalance
객체id has unique valuesUnique
면적(도형) has unique valuesUnique
길이(도형) has unique valuesUnique

Reproduction

Analysis started2024-05-11 08:01:39.115773
Analysis finished2024-05-11 08:01:42.159654
Duration3.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

객체id
Real number (ℝ)

UNIQUE 

Distinct772
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25026.5
Minimum24641
Maximum25412
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-05-11T17:01:42.238989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24641
5-th percentile24679.55
Q124833.75
median25026.5
Q325219.25
95-th percentile25373.45
Maximum25412
Range771
Interquartile range (IQR)385.5

Descriptive statistics

Standard deviation223.00149
Coefficient of variation (CV)0.0089106145
Kurtosis-1.2
Mean25026.5
Median Absolute Deviation (MAD)193
Skewness0
Sum19320458
Variance49729.667
MonotonicityStrictly increasing
2024-05-11T17:01:42.732204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24641 1
 
0.1%
25125 1
 
0.1%
25151 1
 
0.1%
25152 1
 
0.1%
25153 1
 
0.1%
25154 1
 
0.1%
25155 1
 
0.1%
25156 1
 
0.1%
25157 1
 
0.1%
25158 1
 
0.1%
Other values (762) 762
98.7%
ValueCountFrequency (%)
24641 1
0.1%
24642 1
0.1%
24643 1
0.1%
24644 1
0.1%
24645 1
0.1%
24646 1
0.1%
24647 1
0.1%
24648 1
0.1%
24649 1
0.1%
24650 1
0.1%
ValueCountFrequency (%)
25412 1
0.1%
25411 1
0.1%
25410 1
0.1%
25409 1
0.1%
25408 1
0.1%
25407 1
0.1%
25406 1
0.1%
25405 1
0.1%
25404 1
0.1%
25403 1
0.1%
Distinct771
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T17:01:43.012611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters18528
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique770 ?
Unique (%)99.7%

Sample

1st row11000UQ165PS201912150288
2nd row11000UQ165PS201912150289
3rd row11000UQ165PS202307250001
4th row11000UQ165PS202307250002
5th row11440UQ165PS202308180001
ValueCountFrequency (%)
11215uq165ps202401240016 2
 
0.3%
11000uq165ps201912150373 1
 
0.1%
11000uq165ps202012225022 1
 
0.1%
11000uq165ps201912150055 1
 
0.1%
11000uq165ps202309270002 1
 
0.1%
11320uq165ps202210110001 1
 
0.1%
11320uq165ps202210110002 1
 
0.1%
11380uq165ps202211030001 1
 
0.1%
11000uq165ps202204010006 1
 
0.1%
11200uq165ps202103050005 1
 
0.1%
Other values (761) 761
98.6%
2024-05-11T17:01:43.432898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5106
27.6%
1 4017
21.7%
2 2223
12.0%
5 1472
 
7.9%
6 925
 
5.0%
U 772
 
4.2%
Q 772
 
4.2%
P 772
 
4.2%
S 772
 
4.2%
3 495
 
2.7%
Other values (4) 1202
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15440
83.3%
Uppercase Letter 3088
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5106
33.1%
1 4017
26.0%
2 2223
14.4%
5 1472
 
9.5%
6 925
 
6.0%
3 495
 
3.2%
9 402
 
2.6%
4 373
 
2.4%
7 286
 
1.9%
8 141
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
U 772
25.0%
Q 772
25.0%
P 772
25.0%
S 772
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15440
83.3%
Latin 3088
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5106
33.1%
1 4017
26.0%
2 2223
14.4%
5 1472
 
9.5%
6 925
 
6.0%
3 495
 
3.2%
9 402
 
2.6%
4 373
 
2.4%
7 286
 
1.9%
8 141
 
0.9%
Latin
ValueCountFrequency (%)
U 772
25.0%
Q 772
25.0%
P 772
25.0%
S 772
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18528
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5106
27.6%
1 4017
21.7%
2 2223
12.0%
5 1472
 
7.9%
6 925
 
5.0%
U 772
 
4.2%
Q 772
 
4.2%
P 772
 
4.2%
S 772
 
4.2%
3 495
 
2.7%
Other values (4) 1202
 
6.5%

도형 대분류코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
UQQ302
771 
UQQ301
 
1

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowUQQ302
2nd rowUQQ302
3rd rowUQQ302
4th rowUQQ302
5th rowUQQ302

Common Values

ValueCountFrequency (%)
UQQ302 771
99.9%
UQQ301 1
 
0.1%

Length

2024-05-11T17:01:43.586117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:43.683470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqq302 771
99.9%
uqq301 1
 
0.1%

도형 중분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
772 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
772
100.0%

Length

2024-05-11T17:01:43.784443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:43.879387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

도형 소분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
772 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
772
100.0%

Length

2024-05-11T17:01:43.976814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:44.069631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

도형 속성코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
UQQ302
771 
UQQ301
 
1

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowUQQ302
2nd rowUQQ302
3rd rowUQQ302
4th rowUQQ302
5th rowUQQ302

Common Values

ValueCountFrequency (%)
UQQ302 771
99.9%
UQQ301 1
 
0.1%

Length

2024-05-11T17:01:44.167531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T17:01:44.272606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqq302 771
99.9%
uqq301 1
 
0.1%
Distinct768
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T17:01:44.537511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters15440
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique765 ?
Unique (%)99.1%

Sample

1st row11000UTZ201205114077
2nd row11000UTZ201205114070
3rd row11000UTZ202307070002
4th row11000UTZ202307070003
5th row11440UTZ202307100001
ValueCountFrequency (%)
11000utz000000001651 3
 
0.4%
11000utz202001290002 2
 
0.3%
11380utz202006220002 2
 
0.3%
11000utz201206084083 1
 
0.1%
11200utz202102020006 1
 
0.1%
11000utz201111104030 1
 
0.1%
11545utz202011240002 1
 
0.1%
11000utz201712014451 1
 
0.1%
11000utz202306220005 1
 
0.1%
11320utz202208020003 1
 
0.1%
Other values (758) 758
98.2%
2024-05-11T17:01:44.951111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5290
34.3%
1 2793
18.1%
2 2214
14.3%
U 772
 
5.0%
T 772
 
5.0%
Z 772
 
5.0%
3 577
 
3.7%
6 463
 
3.0%
4 462
 
3.0%
8 362
 
2.3%
Other values (3) 963
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13124
85.0%
Uppercase Letter 2316
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5290
40.3%
1 2793
21.3%
2 2214
16.9%
3 577
 
4.4%
6 463
 
3.5%
4 462
 
3.5%
8 362
 
2.8%
5 347
 
2.6%
9 323
 
2.5%
7 293
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
U 772
33.3%
T 772
33.3%
Z 772
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 13124
85.0%
Latin 2316
 
15.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5290
40.3%
1 2793
21.3%
2 2214
16.9%
3 577
 
4.4%
6 463
 
3.5%
4 462
 
3.5%
8 362
 
2.8%
5 347
 
2.6%
9 323
 
2.5%
7 293
 
2.2%
Latin
ValueCountFrequency (%)
U 772
33.3%
T 772
33.3%
Z 772
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15440
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5290
34.3%
1 2793
18.1%
2 2214
14.3%
U 772
 
5.0%
T 772
 
5.0%
Z 772
 
5.0%
3 577
 
3.7%
6 463
 
3.0%
4 462
 
3.0%
8 362
 
2.3%
Other values (3) 963
 
6.2%
Distinct339
Distinct (%)43.9%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T17:01:45.208356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.926166
Min length1

Characters and Unicode

Total characters15383
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique227 ?
Unique (%)29.4%

Sample

1st row11000NTC201201266393
2nd row11000NTC201201266393
3rd row11000NTC202307070001
4th row11000NTC202307070001
5th row11440NTC202307100001
ValueCountFrequency (%)
11000ntc202310040001 35
 
4.6%
11000ntc200206202718 19
 
2.5%
11000ntc201007085142 19
 
2.5%
11000ntc200601179549 17
 
2.2%
11215ntc202309190012 16
 
2.1%
11650ntc202309080003 14
 
1.8%
11470ntc202309190008 14
 
1.8%
11000ntc201903213050 14
 
1.8%
11000ntc201012025681 13
 
1.7%
11000ntc202111030002 13
 
1.7%
Other values (328) 595
77.4%
2024-05-11T17:01:45.629662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5261
34.2%
1 2812
18.3%
2 2148
14.0%
N 769
 
5.0%
T 769
 
5.0%
C 769
 
5.0%
3 587
 
3.8%
7 409
 
2.7%
6 402
 
2.6%
4 394
 
2.6%
Other values (4) 1063
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13073
85.0%
Uppercase Letter 2307
 
15.0%
Space Separator 3
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5261
40.2%
1 2812
21.5%
2 2148
16.4%
3 587
 
4.5%
7 409
 
3.1%
6 402
 
3.1%
4 394
 
3.0%
5 386
 
3.0%
9 357
 
2.7%
8 317
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
N 769
33.3%
T 769
33.3%
C 769
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13076
85.0%
Latin 2307
 
15.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5261
40.2%
1 2812
21.5%
2 2148
16.4%
3 587
 
4.5%
7 409
 
3.1%
6 402
 
3.1%
4 394
 
3.0%
5 386
 
3.0%
9 357
 
2.7%
8 317
 
2.4%
Latin
ValueCountFrequency (%)
N 769
33.3%
T 769
33.3%
C 769
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15383
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5261
34.2%
1 2812
18.3%
2 2148
14.0%
N 769
 
5.0%
T 769
 
5.0%
C 769
 
5.0%
3 587
 
3.8%
7 409
 
2.7%
6 402
 
2.6%
4 394
 
2.6%
Other values (4) 1063
 
6.9%
Distinct578
Distinct (%)74.9%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
2024-05-11T17:01:45.954920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length10.716321
Min length1

Characters and Unicode

Total characters8273
Distinct characters336
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique527 ?
Unique (%)68.3%

Sample

1st rowⅤ구역
2nd rowⅦ-5구역
3rd row특별계획구역1
4th row특별계획구역2
5th row특별계획6구역
ValueCountFrequency (%)
특별계획구역 350
27.8%
특별계획가능구역 38
 
3.0%
특별계획구역1 21
 
1.7%
특별계획구역2 14
 
1.1%
일대 10
 
0.8%
특별계획구역3 10
 
0.8%
2 10
 
0.8%
1 9
 
0.7%
부지 6
 
0.5%
특별계획 6
 
0.5%
Other values (630) 787
62.4%
2024-05-11T17:01:46.399305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
815
 
9.9%
770
 
9.3%
715
 
8.6%
712
 
8.6%
711
 
8.6%
708
 
8.6%
489
 
5.9%
184
 
2.2%
1 174
 
2.1%
2 108
 
1.3%
Other values (326) 2887
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6837
82.6%
Decimal Number 582
 
7.0%
Space Separator 489
 
5.9%
Open Punctuation 72
 
0.9%
Close Punctuation 70
 
0.8%
Dash Punctuation 61
 
0.7%
Other Number 59
 
0.7%
Uppercase Letter 45
 
0.5%
Letter Number 42
 
0.5%
Other Punctuation 11
 
0.1%
Other values (2) 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
815
11.9%
770
 
11.3%
715
 
10.5%
712
 
10.4%
711
 
10.4%
708
 
10.4%
184
 
2.7%
106
 
1.6%
95
 
1.4%
94
 
1.4%
Other values (280) 1927
28.2%
Uppercase Letter
ValueCountFrequency (%)
C 7
15.6%
B 7
15.6%
A 6
13.3%
T 5
11.1%
K 5
11.1%
L 5
11.1%
D 2
 
4.4%
G 2
 
4.4%
J 2
 
4.4%
E 2
 
4.4%
Other values (2) 2
 
4.4%
Decimal Number
ValueCountFrequency (%)
1 174
29.9%
2 108
18.6%
3 75
12.9%
4 53
 
9.1%
5 40
 
6.9%
7 34
 
5.8%
6 31
 
5.3%
0 25
 
4.3%
9 22
 
3.8%
8 20
 
3.4%
Other Number
ValueCountFrequency (%)
13
22.0%
13
22.0%
12
20.3%
11
18.6%
5
 
8.5%
4
 
6.8%
1
 
1.7%
Letter Number
ValueCountFrequency (%)
10
23.8%
8
19.0%
7
16.7%
6
14.3%
6
14.3%
3
 
7.1%
2
 
4.8%
Other Symbol
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 7
63.6%
? 4
36.4%
Space Separator
ValueCountFrequency (%)
489
100.0%
Open Punctuation
ValueCountFrequency (%)
( 72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6836
82.6%
Common 1348
 
16.3%
Latin 88
 
1.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
815
11.9%
770
 
11.3%
715
 
10.5%
712
 
10.4%
711
 
10.4%
708
 
10.4%
184
 
2.7%
106
 
1.6%
95
 
1.4%
94
 
1.4%
Other values (279) 1926
28.2%
Common
ValueCountFrequency (%)
489
36.3%
1 174
 
12.9%
2 108
 
8.0%
3 75
 
5.6%
( 72
 
5.3%
) 70
 
5.2%
- 61
 
4.5%
4 53
 
3.9%
5 40
 
3.0%
7 34
 
2.5%
Other values (16) 172
 
12.8%
Latin
ValueCountFrequency (%)
10
11.4%
8
 
9.1%
C 7
 
8.0%
7
 
8.0%
B 7
 
8.0%
A 6
 
6.8%
6
 
6.8%
6
 
6.8%
T 5
 
5.7%
K 5
 
5.7%
Other values (10) 21
23.9%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6835
82.6%
ASCII 1331
 
16.1%
Enclosed Alphanum 63
 
0.8%
Number Forms 42
 
0.5%
CJK 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
815
11.9%
770
 
11.3%
715
 
10.5%
712
 
10.4%
711
 
10.4%
708
 
10.4%
184
 
2.7%
106
 
1.6%
95
 
1.4%
94
 
1.4%
Other values (278) 1925
28.2%
ASCII
ValueCountFrequency (%)
489
36.7%
1 174
 
13.1%
2 108
 
8.1%
3 75
 
5.6%
( 72
 
5.4%
) 70
 
5.3%
- 61
 
4.6%
4 53
 
4.0%
5 40
 
3.0%
7 34
 
2.6%
Other values (19) 155
 
11.6%
Enclosed Alphanum
ValueCountFrequency (%)
13
20.6%
13
20.6%
12
19.0%
11
17.5%
5
 
7.9%
4
 
6.3%
2
 
3.2%
1
 
1.6%
1
 
1.6%
1
 
1.6%
Number Forms
ValueCountFrequency (%)
10
23.8%
8
19.0%
7
16.7%
6
14.3%
6
14.3%
3
 
7.1%
2
 
4.8%
CJK
ValueCountFrequency (%)
1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

시군구코드
Real number (ℝ)

Distinct26
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11096.418
Minimum11000
Maximum11740
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-05-11T17:01:46.533670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11000
5-th percentile11000
Q111000
median11000
Q311000
95-th percentile11560
Maximum11740
Range740
Interquartile range (IQR)0

Descriptive statistics

Standard deviation190.71091
Coefficient of variation (CV)0.017186709
Kurtosis2.1112437
Mean11096.418
Median Absolute Deviation (MAD)0
Skewness1.8507144
Sum8566435
Variance36370.651
MonotonicityNot monotonic
2024-05-11T17:01:46.667425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
11000 585
75.8%
11215 24
 
3.1%
11545 14
 
1.8%
11305 13
 
1.7%
11380 13
 
1.7%
11650 11
 
1.4%
11230 11
 
1.4%
11530 10
 
1.3%
11410 10
 
1.3%
11200 10
 
1.3%
Other values (16) 71
 
9.2%
ValueCountFrequency (%)
11000 585
75.8%
11110 2
 
0.3%
11140 3
 
0.4%
11170 9
 
1.2%
11200 10
 
1.3%
11215 24
 
3.1%
11230 11
 
1.4%
11260 1
 
0.1%
11290 7
 
0.9%
11305 13
 
1.7%
ValueCountFrequency (%)
11740 1
 
0.1%
11710 4
 
0.5%
11680 8
1.0%
11650 11
1.4%
11620 5
 
0.6%
11590 6
0.8%
11560 6
0.8%
11545 14
1.8%
11530 10
1.3%
11500 4
 
0.5%

도면번호
Categorical

IMBALANCE 

Distinct48
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
609 
 
17
1
 
14
 
12
2
 
11
Other values (43)
109 

Length

Max length7
Median length1
Mean length1.0531088
Min length1

Unique

Unique26 ?
Unique (%)3.4%

Sample

1st row
2nd row
3rd row1
4th row2
5th row

Common Values

ValueCountFrequency (%)
609
78.9%
17
 
2.2%
1 14
 
1.8%
12
 
1.6%
2 11
 
1.4%
9
 
1.2%
9
 
1.2%
3 9
 
1.2%
4 8
 
1.0%
6 7
 
0.9%
Other values (38) 67
 
8.7%

Length

2024-05-11T17:01:46.817218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
17
 
10.4%
1 14
 
8.6%
12
 
7.4%
2 11
 
6.7%
9
 
5.5%
9
 
5.5%
3 9
 
5.5%
4 8
 
4.9%
5 7
 
4.3%
7
 
4.3%
Other values (37) 60
36.8%
Distinct154
Distinct (%)19.9%
Missing0
Missing (%)0.0%
Memory size6.2 KiB
Minimum1899-12-30 00:00:00
Maximum2024-04-24 00:00:00
2024-05-11T17:01:46.960765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:47.128346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

면적(도형)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct772
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26963.842
Minimum489.54139
Maximum530399.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-05-11T17:01:47.326849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum489.54139
5-th percentile1329.2543
Q14071.6691
median8781.4139
Q324757.443
95-th percentile120642.65
Maximum530399.29
Range529909.75
Interquartile range (IQR)20685.774

Descriptive statistics

Standard deviation52341.834
Coefficient of variation (CV)1.941186
Kurtosis27.852248
Mean26963.842
Median Absolute Deviation (MAD)6027.0448
Skewness4.5566268
Sum20816086
Variance2.7396676 × 109
MonotonicityNot monotonic
2024-05-11T17:01:47.502589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41575.1542948 1
 
0.1%
2079.1429155 1
 
0.1%
61641.31693551 1
 
0.1%
2244.9817 1
 
0.1%
1839.54665 1
 
0.1%
8745.8096395 1
 
0.1%
5966.47537256 1
 
0.1%
39485.6732815 1
 
0.1%
2166.89507672 1
 
0.1%
2404.1297564 1
 
0.1%
Other values (762) 762
98.7%
ValueCountFrequency (%)
489.541387 1
0.1%
582.97828894 1
0.1%
589.64207201 1
0.1%
599.955559 1
0.1%
638.0450557 1
0.1%
651.55542538 1
0.1%
659.06889449 1
0.1%
660.85279869 1
0.1%
668.3678411 1
0.1%
672.42660566 1
0.1%
ValueCountFrequency (%)
530399.286905 1
0.1%
441908.559933 1
0.1%
399736.660755 1
0.1%
397816.22804164 1
0.1%
371407.91396705 1
0.1%
334989.982492 1
0.1%
250685.27448397 1
0.1%
246210.733349 1
0.1%
235644.321449 1
0.1%
225141.55757455 1
0.1%

길이(도형)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct772
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean602.4207
Minimum95.689645
Maximum3841.2051
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.9 KiB
2024-05-11T17:01:47.680494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum95.689645
5-th percentile153.90215
Q1274.35429
median423.51739
Q3739.2172
95-th percentile1719.1746
Maximum3841.2051
Range3745.5154
Interquartile range (IQR)464.86291

Descriptive statistics

Standard deviation530.43076
Coefficient of variation (CV)0.88049889
Kurtosis8.1930726
Mean602.4207
Median Absolute Deviation (MAD)177.82471
Skewness2.4695012
Sum465068.78
Variance281356.79
MonotonicityNot monotonic
2024-05-11T17:01:47.884625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
917.26767041 1
 
0.1%
188.94288743 1
 
0.1%
997.03690127 1
 
0.1%
190.61328676 1
 
0.1%
175.14744983 1
 
0.1%
465.70244793 1
 
0.1%
310.73444791 1
 
0.1%
792.00383271 1
 
0.1%
202.91545227 1
 
0.1%
220.09619571 1
 
0.1%
Other values (762) 762
98.7%
ValueCountFrequency (%)
95.68964517 1
0.1%
99.89778389 1
0.1%
102.37347722 1
0.1%
102.429182 1
0.1%
103.47765556 1
0.1%
104.017595 1
0.1%
104.24353386 1
0.1%
107.70713962 1
0.1%
108.3883516 1
0.1%
108.85224104 1
0.1%
ValueCountFrequency (%)
3841.20505327 1
0.1%
3779.25304421 1
0.1%
3565.07002964 1
0.1%
3555.34422493 1
0.1%
3378.33717828 1
0.1%
2918.89766853 1
0.1%
2911.83342532 1
0.1%
2733.85871419 1
0.1%
2708.92321986 1
0.1%
2631.38566972 1
0.1%

Interactions

2024-05-11T17:01:41.270247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:39.839647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:40.315549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:40.780166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:41.435670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:39.959651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:40.447100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:40.892009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:41.564806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:40.087018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:40.565330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:41.007432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:41.671302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:40.194113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:40.669060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T17:01:41.126962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T17:01:48.023754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id도형 대분류코드도형 속성코드시군구코드도면번호면적(도형)길이(도형)
객체id1.0000.0070.0070.6080.0000.1970.267
도형 대분류코드0.0071.0000.7050.1240.1250.0000.000
도형 속성코드0.0070.7051.0000.1240.1250.0000.000
시군구코드0.6080.1240.1241.0000.2960.2990.281
도면번호0.0000.1250.1250.2961.0000.0000.000
면적(도형)0.1970.0000.0000.2990.0001.0000.861
길이(도형)0.2670.0000.0000.2810.0000.8611.000
2024-05-11T17:01:48.140066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도형 속성코드도형 대분류코드도면번호
도형 속성코드1.0000.4980.096
도형 대분류코드0.4981.0000.096
도면번호0.0960.0961.000
2024-05-11T17:01:48.248555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id시군구코드면적(도형)길이(도형)도형 대분류코드도형 속성코드도면번호
객체id1.0000.133-0.113-0.1100.0060.0060.000
시군구코드0.1331.000-0.162-0.1420.2230.2230.149
면적(도형)-0.113-0.1621.0000.9830.0000.0000.000
길이(도형)-0.110-0.1420.9831.0000.0000.0000.000
도형 대분류코드0.0060.2230.0000.0001.0000.4980.096
도형 속성코드0.0060.2230.0000.0000.4981.0000.096
도면번호0.0000.1490.0000.0000.0960.0961.000

Missing values

2024-05-11T17:01:41.867819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T17:01:42.075058image/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.

Sample

객체id현황도형 관리번호도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명시군구코드도면번호현황도형 생성일시면적(도형)길이(도형)
02464111000UQ165PS201912150288UQQ302UQQ30211000UTZ20120511407711000NTC201201266393Ⅴ구역110002019-12-15 00:00:00.041575.154295917.26767
12464211000UQ165PS201912150289UQQ302UQQ30211000UTZ20120511407011000NTC201201266393Ⅶ-5구역110002019-12-15 00:00:00.06222.850291350.175896
22464311000UQ165PS202307250001UQQ302UQQ30211000UTZ20230707000211000NTC202307070001특별계획구역11100012023-07-25 00:00:00.046525.689831982.78416
32464411000UQ165PS202307250002UQQ302UQQ30211000UTZ20230707000311000NTC202307070001특별계획구역21100022023-07-25 00:00:00.011719.087388439.737053
42464511440UQ165PS202308180001UQQ302UQQ30211440UTZ20230710000111440NTC202307100001특별계획6구역114402023-08-18 00:00:00.04080.31439261.675883
52464611000UQ165PS202212230002UQQ302UQQ30211000UTZ20220321000211000NTC202206290001대학생연합 기숙사부지 특별계획구역110002022-12-23 00:00:00.03699.068405343.922401
62464711000UQ165PS201912150320UQQ302UQQ30211000UTZ20180601451211000NTC201805109540문배업무지구 특별계획구역④110002019-12-15 00:00:00.02404.204961233.795757
72464811000UQ165PS201912150026UQQ302UQQ30211000UTZ20180905008511000NTC201802190001독산4-2 특별계획구역110002019-12-15 00:00:00.02835.336535211.639862
82464911000UQ165PS202007050022UQQ302UQQ30211000UTZ20200618007911000NTC200901022599성대시장 특별계획구역110002020-06-18 00:00:00.05059.729519307.279008
92465011560UQ165PS202306120002UQQ302UQQ30211560UTZ20230503000311560NTC202306070002특별계획구역2115602023-06-12 00:00:00.011235.11424723.70664
객체id현황도형 관리번호도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명시군구코드도면번호현황도형 생성일시면적(도형)길이(도형)
7622540311170UQ165PS202302070001UQQ302UQQ30211170UTZ20230130000111170NTC202301300007신용산역 북측1 특별계획구역111702023-02-07 00:00:00.014056.749712543.621784
7632540411620UQ165PS202301180001UQQ302UQQ30211620UTZ20221220000211620NTC202301050002양지병원 특별계획구역116202023-01-18 00:00:00.04568.606006337.490612
7642540511000UQ165PS201912150054UQQ302UQQ30211000UTZ20181109003511000NTC201510300001용산공원정비구역 복합시설조성지구110002019-12-15 00:00:00.051535.9628441009.846265
7652540611000UQ165PS201912150429UQQ302UQQ30211000UTZ20190823000111560NTC201908230003특별계획구역 Ⅰ-3110002019-12-15 00:00:00.05324.545929321.207532
7662540711000UQ165PS201912150248UQQ302UQQ30211000UTZ20120511407411000NTC201201266393Ⅶ-2구역110002019-12-15 00:00:00.04335.599134296.013216
7672540811000UQ165PS201912150249UQQ302UQQ30211000UTZ20120608408311000NTC201112086332특별계획구역2110002019-12-15 00:00:00.04886.335352285.89615
7682540911000UQ165PS201912150136UQQ302UQQ30211000UTZ20060120358211000NTC200601179549특별계획구역8(고덕시영아파트부지)110002019-12-15 00:00:00.0194302.7532041908.485851
7692541011000UQ165PS201912150137UQQ302UQQ30211000UTZ20060120359011000NTC200601179549특별계획구역16(고덕우성아파트)110002019-12-15 00:00:00.041578.512667905.936849
7702541111000UQ165PS202012175534UQQ302UQQ30211000UTZ20200129000211000NTC202001290002송파나루지구 특별계획구역110002020-11-23 00:00:00.03133.058088256.97271
7712541211000UQ165PS202012175537UQQ302UQQ30211000UTZ20201202008811000NTC202012020036문정특별계획구역Ⅲ110002020-12-17 00:00:00.017310.586448570.09038