Overview

Dataset statistics

Number of variables14
Number of observations392
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory44.5 KiB
Average record size in memory116.3 B

Variable types

Numeric4
Text4
Categorical6

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-21125/S/1/datasetView.do

Alerts

도형 대분류코드 has constant value ""Constant
도형 중분류코드 has constant value ""Constant
도형 소분류코드 has constant value ""Constant
도형 속성코드 has constant value ""Constant
도면번호 has constant value ""Constant
시군구코드 is highly overall correlated with 현황도형 생성일시High correlation
면적(도형) is highly overall correlated with 길이(도형)High correlation
길이(도형) is highly overall correlated with 면적(도형)High correlation
현황도형 생성일시 is highly overall correlated with 시군구코드High correlation
현황도형 생성일시 is highly imbalanced (74.4%)Imbalance
객체id has unique valuesUnique
현황도형 관리번호 has unique valuesUnique

Reproduction

Analysis started2024-05-04 02:59:20.241367
Analysis finished2024-05-04 02:59:27.715147
Duration7.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

객체id
Real number (ℝ)

UNIQUE 

Distinct392
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean106498.85
Minimum106048
Maximum106695
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-04T02:59:28.123019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum106048
5-th percentile106323.55
Q1106401.75
median106499.5
Q3106597.25
95-th percentile106675.45
Maximum106695
Range647
Interquartile range (IQR)195.5

Descriptive statistics

Standard deviation115.15721
Coefficient of variation (CV)0.0010813001
Kurtosis-0.72544485
Mean106498.85
Median Absolute Deviation (MAD)98
Skewness-0.12525466
Sum41747548
Variance13261.184
MonotonicityStrictly decreasing
2024-05-04T02:59:28.694925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
106695 1
 
0.3%
106425 1
 
0.3%
106427 1
 
0.3%
106428 1
 
0.3%
106429 1
 
0.3%
106430 1
 
0.3%
106431 1
 
0.3%
106432 1
 
0.3%
106433 1
 
0.3%
106434 1
 
0.3%
Other values (382) 382
97.4%
ValueCountFrequency (%)
106048 1
0.3%
106305 1
0.3%
106306 1
0.3%
106307 1
0.3%
106308 1
0.3%
106309 1
0.3%
106310 1
0.3%
106311 1
0.3%
106312 1
0.3%
106313 1
0.3%
ValueCountFrequency (%)
106695 1
0.3%
106694 1
0.3%
106693 1
0.3%
106692 1
0.3%
106691 1
0.3%
106690 1
0.3%
106689 1
0.3%
106688 1
0.3%
106687 1
0.3%
106686 1
0.3%

현황도형 관리번호
Text

UNIQUE 

Distinct392
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-04T02:59:29.430403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters9408
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

Unique392 ?
Unique (%)100.0%

Sample

1st row11000UQ171PS201912150062
2nd row11000UQ171PS201912150061
3rd row11000UQ171PS201912150060
4th row11000UQ171PS201912150059
5th row11000UQ171PS201912150058
ValueCountFrequency (%)
11000uq171ps201912150062 1
 
0.3%
11000uq171ps201912150141 1
 
0.3%
11000uq171ps201912150143 1
 
0.3%
11000uq171ps201912150290 1
 
0.3%
11000uq171ps201912150291 1
 
0.3%
11000uq171ps201912150292 1
 
0.3%
11000uq171ps201912150293 1
 
0.3%
11000uq171ps201912150294 1
 
0.3%
11000uq171ps201912150295 1
 
0.3%
11000uq171ps201912150296 1
 
0.3%
Other values (382) 382
97.4%
2024-05-04T02:59:30.810883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2857
30.4%
0 2204
23.4%
2 998
 
10.6%
7 494
 
5.3%
5 417
 
4.4%
9 404
 
4.3%
U 392
 
4.2%
Q 392
 
4.2%
P 392
 
4.2%
S 392
 
4.2%
Other values (4) 466
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7840
83.3%
Uppercase Letter 1568
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2857
36.4%
0 2204
28.1%
2 998
 
12.7%
7 494
 
6.3%
5 417
 
5.3%
9 404
 
5.2%
3 157
 
2.0%
4 118
 
1.5%
8 104
 
1.3%
6 87
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
U 392
25.0%
Q 392
25.0%
P 392
25.0%
S 392
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7840
83.3%
Latin 1568
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2857
36.4%
0 2204
28.1%
2 998
 
12.7%
7 494
 
6.3%
5 417
 
5.3%
9 404
 
5.2%
3 157
 
2.0%
4 118
 
1.5%
8 104
 
1.3%
6 87
 
1.1%
Latin
ValueCountFrequency (%)
U 392
25.0%
Q 392
25.0%
P 392
25.0%
S 392
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2857
30.4%
0 2204
23.4%
2 998
 
10.6%
7 494
 
5.3%
5 417
 
4.4%
9 404
 
4.3%
U 392
 
4.2%
Q 392
 
4.2%
P 392
 
4.2%
S 392
 
4.2%
Other values (4) 466
 
5.0%

도형 대분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
UQQ900
392 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUQQ900
2nd rowUQQ900
3rd rowUQQ900
4th rowUQQ900
5th rowUQQ900

Common Values

ValueCountFrequency (%)
UQQ900 392
100.0%

Length

2024-05-04T02:59:31.425146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:59:31.856279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqq900 392
100.0%

도형 중분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
392 

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 (%)
392
100.0%

Length

2024-05-04T02:59:32.294308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:59:32.840225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

도형 소분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
392 

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 (%)
392
100.0%

Length

2024-05-04T02:59:33.365462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:59:33.710813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

도형 속성코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
UQQ900
392 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUQQ900
2nd rowUQQ900
3rd rowUQQ900
4th rowUQQ900
5th rowUQQ900

Common Values

ValueCountFrequency (%)
UQQ900 392
100.0%

Length

2024-05-04T02:59:34.012724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:59:34.443631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqq900 392
100.0%

도형 조서관리 코드
Text

Distinct234
Distinct (%)59.7%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-04T02:59:35.211974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters7840
Distinct characters12
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

Unique232 ?
Unique (%)59.2%

Sample

1st row11000EZZ200901301803
2nd row11000EZZ000000001711
3rd row11000EZZ201704182162
4th row11000EZZ000000001711
5th row11000EZZ000000001711
ValueCountFrequency (%)
11000ezz000000001711 158
40.3%
11000ezz201203132058 2
 
0.5%
11000ezz201005141948 1
 
0.3%
11000ezz201005181951 1
 
0.3%
11000ezz200912141893 1
 
0.3%
11000ezz200901301815 1
 
0.3%
11000ezz201211152099 1
 
0.3%
11410ezz202303160001 1
 
0.3%
11440ezz202101050002 1
 
0.3%
11320ezz202109280001 1
 
0.3%
Other values (224) 224
57.1%
2024-05-04T02:59:36.682750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3191
40.7%
1 1834
23.4%
Z 784
 
10.0%
2 516
 
6.6%
E 392
 
5.0%
7 322
 
4.1%
9 183
 
2.3%
4 141
 
1.8%
3 136
 
1.7%
8 127
 
1.6%
Other values (2) 214
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6664
85.0%
Uppercase Letter 1176
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3191
47.9%
1 1834
27.5%
2 516
 
7.7%
7 322
 
4.8%
9 183
 
2.7%
4 141
 
2.1%
3 136
 
2.0%
8 127
 
1.9%
5 112
 
1.7%
6 102
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
Z 784
66.7%
E 392
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 6664
85.0%
Latin 1176
 
15.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3191
47.9%
1 1834
27.5%
2 516
 
7.7%
7 322
 
4.8%
9 183
 
2.7%
4 141
 
2.1%
3 136
 
2.0%
8 127
 
1.9%
5 112
 
1.7%
6 102
 
1.5%
Latin
ValueCountFrequency (%)
Z 784
66.7%
E 392
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3191
40.7%
1 1834
23.4%
Z 784
 
10.0%
2 516
 
6.6%
E 392
 
5.0%
7 322
 
4.1%
9 183
 
2.3%
4 141
 
1.8%
3 136
 
1.7%
8 127
 
1.6%
Other values (2) 214
 
2.7%

결정고시관리코드
Text

Distinct101
Distinct (%)25.8%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-04T02:59:37.622099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length12.341837
Min length1

Characters and Unicode

Total characters4838
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

Unique67 ?
Unique (%)17.1%

Sample

1st row11000NTC200901152681
2nd row
3rd row11000NTC201612227968
4th row
5th row
ValueCountFrequency (%)
11000ntc201005134922 24
 
10.3%
11000ntc200811202367 16
 
6.8%
11000ntc200901152681 14
 
6.0%
11470ntc202307260003 13
 
5.6%
11710ntc202309190002 8
 
3.4%
11000ntc200902032739 8
 
3.4%
11000ntc201008125276 8
 
3.4%
11000ntc200912174264 7
 
3.0%
11560ntc202312290002 6
 
2.6%
11000ntc201003104602 5
 
2.1%
Other values (90) 125
53.4%
2024-05-04T02:59:38.802614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1449
30.0%
1 900
18.6%
2 637
13.2%
N 234
 
4.8%
T 234
 
4.8%
C 234
 
4.8%
3 171
 
3.5%
158
 
3.3%
9 151
 
3.1%
5 149
 
3.1%
Other values (4) 521
 
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3978
82.2%
Uppercase Letter 702
 
14.5%
Space Separator 158
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1449
36.4%
1 900
22.6%
2 637
16.0%
3 171
 
4.3%
9 151
 
3.8%
5 149
 
3.7%
7 145
 
3.6%
4 142
 
3.6%
6 131
 
3.3%
8 103
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
N 234
33.3%
T 234
33.3%
C 234
33.3%
Space Separator
ValueCountFrequency (%)
158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4136
85.5%
Latin 702
 
14.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1449
35.0%
1 900
21.8%
2 637
15.4%
3 171
 
4.1%
158
 
3.8%
9 151
 
3.7%
5 149
 
3.6%
7 145
 
3.5%
4 142
 
3.4%
6 131
 
3.2%
Latin
ValueCountFrequency (%)
N 234
33.3%
T 234
33.3%
C 234
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4838
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1449
30.0%
1 900
18.6%
2 637
13.2%
N 234
 
4.8%
T 234
 
4.8%
C 234
 
4.8%
3 171
 
3.5%
158
 
3.3%
9 151
 
3.1%
5 149
 
3.1%
Other values (4) 521
 
10.8%

라벨명
Text

Distinct71
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2024-05-04T02:59:39.712701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length10
Mean length11.022959
Min length4

Characters and Unicode

Total characters4321
Distinct characters130
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)15.6%

Sample

1st row방배동 주택재건축사업 예정지역
2nd row개발행위허가제한지역
3rd row개발행위허가제한
4th row개발행위허가제한지역
5th row개발행위허가제한지역
ValueCountFrequency (%)
개발행위허가제한지역 300
59.9%
주택재건축사업 14
 
2.8%
예정지역 14
 
2.8%
방배동 14
 
2.8%
목동신시가지아파트 12
 
2.4%
개발행위허가 6
 
1.2%
개발행위허가제한 6
 
1.2%
특별계획구역 4
 
0.8%
지구단위계획(안 3
 
0.6%
행위제한 3
 
0.6%
Other values (96) 125
25.0%
2024-05-04T02:59:40.912606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 389
9.0%
역 361
 
8.4%
위 342
 
7.9%
제 334
 
7.7%
개 329
 
7.6%
가 329
 
7.6%
행 324
 
7.5%
발 322
 
7.5%
한 322
 
7.5%
허 317
 
7.3%
Other values (120) 952
22.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4112
95.2%
Space Separator 109
 
2.5%
Decimal Number 64
 
1.5%
Close Punctuation 15
 
0.3%
Open Punctuation 15
 
0.3%
Connector Punctuation 3
 
0.1%
Other Punctuation 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 389
9.5%
역 361
8.8%
위 342
8.3%
제 334
8.1%
개 329
8.0%
가 329
8.0%
행 324
7.9%
발 322
7.8%
한 322
7.8%
허 317
7.7%
Other values (104) 743
18.1%
Decimal Number
ValueCountFrequency (%)
1 18
28.1%
2 14
21.9%
4 8
12.5%
3 5
 
7.8%
5 5
 
7.8%
6 4
 
6.2%
8 4
 
6.2%
7 3
 
4.7%
9 2
 
3.1%
0 1
 
1.6%
Space Separator
ValueCountFrequency (%)
109
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4112
95.2%
Common 209
 
4.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 389
9.5%
역 361
8.8%
위 342
8.3%
제 334
8.1%
개 329
8.0%
가 329
8.0%
행 324
7.9%
발 322
7.8%
한 322
7.8%
허 317
7.7%
Other values (104) 743
18.1%
Common
ValueCountFrequency (%)
109
52.2%
1 18
 
8.6%
) 15
 
7.2%
( 15
 
7.2%
2 14
 
6.7%
4 8
 
3.8%
3 5
 
2.4%
5 5
 
2.4%
6 4
 
1.9%
8 4
 
1.9%
Other values (6) 12
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4112
95.2%
ASCII 209
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 389
9.5%
역 361
8.8%
위 342
8.3%
제 334
8.1%
개 329
8.0%
가 329
8.0%
행 324
7.9%
발 322
7.8%
한 322
7.8%
허 317
7.7%
Other values (104) 743
18.1%
ASCII
ValueCountFrequency (%)
109
52.2%
1 18
 
8.6%
) 15
 
7.2%
( 15
 
7.2%
2 14
 
6.7%
4 8
 
3.8%
3 5
 
2.4%
5 5
 
2.4%
6 4
 
1.9%
8 4
 
1.9%
Other values (6) 12
 
5.7%

시군구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11067.832
Minimum11000
Maximum11710
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-04T02:59:41.424871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11000
5-th percentile11000
Q111000
median11000
Q311000
95-th percentile11470
Maximum11710
Range710
Interquartile range (IQR)0

Descriptive statistics

Standard deviation174.91545
Coefficient of variation (CV)0.015803949
Kurtosis4.8692494
Mean11067.832
Median Absolute Deviation (MAD)0
Skewness2.4859648
Sum4338590
Variance30595.414
MonotonicityNot monotonic
2024-05-04T02:59:41.816316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
11000 333
84.9%
11470 15
 
3.8%
11710 10
 
2.6%
11440 8
 
2.0%
11560 7
 
1.8%
11170 7
 
1.8%
11305 2
 
0.5%
11290 2
 
0.5%
11590 2
 
0.5%
11110 2
 
0.5%
Other values (4) 4
 
1.0%
ValueCountFrequency (%)
11000 333
84.9%
11110 2
 
0.5%
11170 7
 
1.8%
11230 1
 
0.3%
11260 1
 
0.3%
11290 2
 
0.5%
11305 2
 
0.5%
11320 1
 
0.3%
11410 1
 
0.3%
11440 8
 
2.0%
ValueCountFrequency (%)
11710 10
2.6%
11590 2
 
0.5%
11560 7
1.8%
11470 15
3.8%
11440 8
2.0%
11410 1
 
0.3%
11320 1
 
0.3%
11305 2
 
0.5%
11290 2
 
0.5%
11260 1
 
0.3%

도면번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
392 

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 (%)
392
100.0%

Length

2024-05-04T02:59:42.261460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T02:59:42.587814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

현황도형 생성일시
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct31
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
2019-12-15 00:00:00.0
332 
2023-08-08 00:00:00.0
 
13
2023-11-16 00:00:00.0
 
8
2024-01-08 00:00:00.0
 
6
2023-12-08 00:00:00.0
 
2
Other values (26)
 
31

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique21 ?
Unique (%)5.4%

Sample

1st row2019-12-15 00:00:00.0
2nd row2019-12-15 00:00:00.0
3rd row2019-12-15 00:00:00.0
4th row2019-12-15 00:00:00.0
5th row2019-12-15 00:00:00.0

Common Values

ValueCountFrequency (%)
2019-12-15 00:00:00.0 332
84.7%
2023-08-08 00:00:00.0 13
 
3.3%
2023-11-16 00:00:00.0 8
 
2.0%
2024-01-08 00:00:00.0 6
 
1.5%
2023-12-08 00:00:00.0 2
 
0.5%
2022-03-15 00:00:00.0 2
 
0.5%
2023-12-28 00:00:00.0 2
 
0.5%
2022-04-26 00:00:00.0 2
 
0.5%
2024-04-23 00:00:00.0 2
 
0.5%
2023-11-30 00:00:00.0 2
 
0.5%
Other values (21) 21
 
5.4%

Length

2024-05-04T02:59:43.030730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:00:00.0 392
50.0%
2019-12-15 332
42.3%
2023-08-08 13
 
1.7%
2023-11-16 8
 
1.0%
2024-01-08 6
 
0.8%
2022-04-26 2
 
0.3%
2024-04-23 2
 
0.3%
2023-11-30 2
 
0.3%
2023-12-28 2
 
0.3%
2022-03-15 2
 
0.3%
Other values (22) 23
 
2.9%

면적(도형)
Real number (ℝ)

HIGH CORRELATION 

Distinct391
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63893.877
Minimum50.694193
Maximum1107611.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-04T02:59:43.576481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50.694193
5-th percentile317.36227
Q12493.3911
median19802.526
Q365394.151
95-th percentile281162.77
Maximum1107611.5
Range1107560.8
Interquartile range (IQR)62900.76

Descriptive statistics

Standard deviation127971.1
Coefficient of variation (CV)2.0028696
Kurtosis22.195465
Mean63893.877
Median Absolute Deviation (MAD)18886.776
Skewness4.2141805
Sum25046400
Variance1.6376603 × 1010
MonotonicityNot monotonic
2024-05-04T02:59:44.538042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
563423.552599 2
 
0.5%
17362.9876928 1
 
0.3%
86.34257969 1
 
0.3%
546.71798463 1
 
0.3%
35823.369902 1
 
0.3%
111153.054553 1
 
0.3%
133203.811852 1
 
0.3%
23953.4367263 1
 
0.3%
3042.0645397 1
 
0.3%
69049.8092315 1
 
0.3%
Other values (381) 381
97.2%
ValueCountFrequency (%)
50.69419294 1
0.3%
73.6879236 1
0.3%
86.34257969 1
0.3%
94.3666302 1
0.3%
107.14863379 1
0.3%
109.03274128 1
0.3%
110.24142821 1
0.3%
114.47661499 1
0.3%
135.61055944 1
0.3%
148.41194803 1
0.3%
ValueCountFrequency (%)
1107611.53728 1
0.3%
896431.991136 1
0.3%
761551.167198 1
0.3%
708068.90641 1
0.3%
647991.39747 1
0.3%
628158.845348 1
0.3%
563423.552599 2
0.5%
554572.92539547 1
0.3%
457745.16576 1
0.3%
438567.413007 1
0.3%

길이(도형)
Real number (ℝ)

HIGH CORRELATION 

Distinct390
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1064.1063
Minimum34.107899
Maximum13713.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.6 KiB
2024-05-04T02:59:45.135889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.107899
5-th percentile79.179659
Q1235.9805
median724.74103
Q31361.0425
95-th percentile3133.6141
Maximum13713.5
Range13679.392
Interquartile range (IQR)1125.062

Descriptive statistics

Standard deviation1339.0239
Coefficient of variation (CV)1.2583554
Kurtosis25.728027
Mean1064.1063
Median Absolute Deviation (MAD)517.40703
Skewness4.0431614
Sum417129.66
Variance1792985
MonotonicityNot monotonic
2024-05-04T02:59:45.763618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
724.74102783 2
 
0.5%
5775.66992188 2
 
0.5%
49.13539886 1
 
0.3%
101.15499878 1
 
0.3%
1129.29003906 1
 
0.3%
1803.89001465 1
 
0.3%
2237.55004883 1
 
0.3%
963.97998047 1
 
0.3%
226.022995 1
 
0.3%
1777.13000488 1
 
0.3%
Other values (380) 380
96.9%
ValueCountFrequency (%)
34.10789871 1
0.3%
38.51739883 1
0.3%
45.75899887 1
0.3%
47.66329956 1
0.3%
47.93709946 1
0.3%
49.13539886 1
0.3%
50.26779938 1
0.3%
51.5868988 1
0.3%
59.66730118 1
0.3%
62.2580986 1
0.3%
ValueCountFrequency (%)
13713.5 1
0.3%
8599.37011719 1
0.3%
7161.87988281 1
0.3%
7144.85986328 1
0.3%
6263.7459718 1
0.3%
5775.66992188 2
0.5%
5580.16015625 1
0.3%
5558.25976563 1
0.3%
5345.97021484 1
0.3%
5337.0 1
0.3%

Interactions

2024-05-04T02:59:25.388963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:21.290668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:22.677917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:24.233685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:25.673800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:21.570412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:23.224726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:24.509431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:26.056171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:21.859162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:23.663072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:24.848626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:26.336918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:22.179093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:23.942343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T02:59:25.103663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T02:59:46.127664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id라벨명시군구코드현황도형 생성일시면적(도형)길이(도형)
객체id1.0000.0000.7500.5280.1330.175
라벨명0.0001.0000.0000.7000.6190.372
시군구코드0.7500.0001.0000.9940.0000.612
현황도형 생성일시0.5280.7000.9941.0000.0000.128
면적(도형)0.1330.6190.0000.0001.0000.905
길이(도형)0.1750.3720.6120.1280.9051.000
2024-05-04T02:59:46.487970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id시군구코드면적(도형)길이(도형)현황도형 생성일시
객체id1.000-0.199-0.151-0.1480.199
시군구코드-0.1991.0000.2960.2930.953
면적(도형)-0.1510.2961.0000.9770.000
길이(도형)-0.1480.2930.9771.0000.047
현황도형 생성일시0.1990.9530.0000.0471.000

Missing values

2024-05-04T02:59:26.817719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T02:59:27.498258image/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)
010669511000UQ171PS201912150062UQQ900UQQ90011000EZZ20090130180311000NTC200901152681방배동 주택재건축사업 예정지역110002019-12-15 00:00:00.017362.987693543.97998
110669411000UQ171PS201912150061UQQ900UQQ90011000EZZ000000001711개발행위허가제한지역110002019-12-15 00:00:00.0811.076011123.731003
210669311000UQ171PS201912150060UQQ900UQQ90011000EZZ20170418216211000NTC201612227968개발행위허가제한110002019-12-15 00:00:00.065465.2029131683.98999
310669211000UQ171PS201912150059UQQ900UQQ90011000EZZ000000001711개발행위허가제한지역110002019-12-15 00:00:00.01029.592143128.332993
410669111000UQ171PS201912150058UQQ900UQQ90011000EZZ000000001711개발행위허가제한지역110002019-12-15 00:00:00.0991.226436180.516998
510669011000UQ171PS201912150056UQQ900UQQ90011000EZZ000000001711개발행위허가제한지역110002019-12-15 00:00:00.0511.32741496.802498
610668911000UQ171PS201912150055UQQ900UQQ90011000EZZ000000001711개발행위허가제한지역110002019-12-15 00:00:00.0987.226385125.126999
710668811000UQ171PS201912150054UQQ900UQQ90011000EZZ000000001711개발행위허가제한지역110002019-12-15 00:00:00.05186.598061332.179993
810668711000UQ171PS201912150053UQQ900UQQ90011000EZZ20081212173911000NTC200810162271개발행위허가제한지역110002019-12-15 00:00:00.019268.638275970.583984
910668611000UQ171PS201912150052UQQ900UQQ90011000EZZ000000001711개발행위허가제한지역110002019-12-15 00:00:00.01577.781658189.070007
객체id현황도형 관리번호도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명시군구코드도면번호현황도형 생성일시면적(도형)길이(도형)
38210631311000UQ171PS201912150265UQQ900UQQ90011000EZZ20081212173611000NTC200810162271개발행위허가제한지역110002019-12-15 00:00:00.023731.604681478.319946
38310631211000UQ171PS201912150264UQQ900UQQ90011000EZZ20090130181311000NTC200901152681방배동 주택재건축사업 예정지역110002019-12-15 00:00:00.0151262.3008491935.959961
38410631111000UQ171PS201912150305UQQ900UQQ90011000EZZ000000001711개발행위허가제한지역110002019-12-15 00:00:00.02534.293672243.354996
38510631011000UQ171PS201912150304UQQ900UQQ90011000EZZ20081223175211000NTC200811202367개발행위허가제한지역110002019-12-15 00:00:00.09998.953194513.291992
38610630911000UQ171PS201912150303UQQ900UQQ90011000EZZ000000001711개발행위허가제한지역110002019-12-15 00:00:00.0714.932605113.273003
38710630811000UQ171PS201912150335UQQ900UQQ90011000EZZ20101007201011000NTC201008125276개발행위허가제한지역110002019-12-15 00:00:00.014102.760201776.713013
38810630711000UQ171PS201912150334UQQ900UQQ90011000EZZ20100415194511000NTC201004154773개발행위허가제한지역110002019-12-15 00:00:00.072247.1504231309.359985
38910630611000UQ171PS201912150332UQQ900UQQ90011000EZZ000000001711개발행위허가제한지역110002019-12-15 00:00:00.0300.37920173.740402
39010630511000UQ171PS201912150331UQQ900UQQ90011000EZZ000000001711개발행위허가제한지역110002019-12-15 00:00:00.02840.278506231.194
39110604811000UQ171PS201912150330UQQ900UQQ90011000EZZ000000001711개발행위허가제한지역110002019-12-15 00:00:00.0382773.4887954623.100098