Overview

Dataset statistics

Number of variables5
Number of observations1579
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory64.9 KiB
Average record size in memory42.1 B

Variable types

Text1
Categorical1
Numeric2
DateTime1

Dataset

Description경기도 양주시 도시계획정보시스템(UPIS) 관리지역, 자연환경보전지역 현황으로 현황도형 관리번호, 라벨명, 면적(도형), 면적(길이), 현황도형 생성일 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15115909/fileData.do

Alerts

면적(도형) is highly overall correlated with 면적(길이)High correlation
면적(길이) is highly overall correlated with 면적(도형)High correlation
현황도형 관리번호 has unique valuesUnique
면적(도형) has unique valuesUnique
면적(길이) has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:57:58.021833
Analysis finished2023-12-12 16:57:58.784563
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

현황도형 관리번호
Text

UNIQUE 

Distinct1579
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
2023-12-13T01:57:58.939907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters37896
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

Unique1579 ?
Unique (%)100.0%

Sample

1st row41630UQ112PS201706281320
2nd row41630UQ112PS201706281296
3rd row41630UQ112PS201706281295
4th row41630UQ112PS201706281294
5th row41630UQ112PS201706281293
ValueCountFrequency (%)
41630uq112ps201706281320 1
 
0.1%
41630uq112ps201706280427 1
 
0.1%
41630uq112ps201706280429 1
 
0.1%
41630uq112ps201706280430 1
 
0.1%
41630uq112ps201706280431 1
 
0.1%
41630uq112ps201706280280 1
 
0.1%
41630uq112ps201706280404 1
 
0.1%
41630uq112ps201706280405 1
 
0.1%
41630uq112ps201706280406 1
 
0.1%
41630uq112ps201706280407 1
 
0.1%
Other values (1569) 1569
99.4%
2023-12-13T01:57:59.335644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8034
21.2%
0 6609
17.4%
2 5312
14.0%
6 3307
8.7%
3 2045
 
5.4%
4 1993
 
5.3%
8 1728
 
4.6%
7 1725
 
4.6%
U 1579
 
4.2%
Q 1579
 
4.2%
Other values (4) 3985
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31580
83.3%
Uppercase Letter 6316
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8034
25.4%
0 6609
20.9%
2 5312
16.8%
6 3307
10.5%
3 2045
 
6.5%
4 1993
 
6.3%
8 1728
 
5.5%
7 1725
 
5.5%
5 415
 
1.3%
9 412
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
U 1579
25.0%
Q 1579
25.0%
P 1579
25.0%
S 1579
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 31580
83.3%
Latin 6316
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8034
25.4%
0 6609
20.9%
2 5312
16.8%
6 3307
10.5%
3 2045
 
6.5%
4 1993
 
6.3%
8 1728
 
5.5%
7 1725
 
5.5%
5 415
 
1.3%
9 412
 
1.3%
Latin
ValueCountFrequency (%)
U 1579
25.0%
Q 1579
25.0%
P 1579
25.0%
S 1579
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37896
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8034
21.2%
0 6609
17.4%
2 5312
14.0%
6 3307
8.7%
3 2045
 
5.4%
4 1993
 
5.3%
8 1728
 
4.6%
7 1725
 
4.6%
U 1579
 
4.2%
Q 1579
 
4.2%
Other values (4) 3985
10.5%

라벨명
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
보전관리지역
929 
계획관리지역
413 
생산관리지역
237 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보전관리지역 929
58.8%
계획관리지역 413
26.2%
생산관리지역 237
 
15.0%

Length

2023-12-13T01:57:59.480950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:59.587781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보전관리지역 929
58.8%
계획관리지역 413
26.2%
생산관리지역 237
 
15.0%

면적(도형)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1579
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34218.118
Minimum0.023748
Maximum1467030.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.0 KiB
2023-12-13T01:57:59.732682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.023748
5-th percentile30.926238
Q1484.00412
median2140.7745
Q314868.976
95-th percentile153452
Maximum1467030.2
Range1467030.2
Interquartile range (IQR)14384.972

Descriptive statistics

Standard deviation119911.11
Coefficient of variation (CV)3.5043164
Kurtosis64.960669
Mean34218.118
Median Absolute Deviation (MAD)2028.2144
Skewness7.2740616
Sum54030408
Variance1.4378675 × 1010
MonotonicityNot monotonic
2023-12-13T01:57:59.894567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
123525.0235 1
 
0.1%
36800.38786 1
 
0.1%
1017296.066 1
 
0.1%
142531.6508 1
 
0.1%
1026.759206 1
 
0.1%
39.768715 1
 
0.1%
3234.083533 1
 
0.1%
1186.710283 1
 
0.1%
1881.987138 1
 
0.1%
17990.49601 1
 
0.1%
Other values (1569) 1569
99.4%
ValueCountFrequency (%)
0.023748 1
0.1%
0.093466 1
0.1%
0.0979145 1
0.1%
0.4421465 1
0.1%
1.007334 1
0.1%
1.3448295 1
0.1%
1.9008945 1
0.1%
2.6948475 1
0.1%
2.7190285 1
0.1%
3.0400875 1
0.1%
ValueCountFrequency (%)
1467030.204 1
0.1%
1386759.915 1
0.1%
1375725.459 1
0.1%
1375332.259 1
0.1%
1131848.817 1
0.1%
1097534.107 1
0.1%
1076775.718 1
0.1%
1017296.066 1
0.1%
998810.1187 1
0.1%
891729.1937 1
0.1%

면적(길이)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1579
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean895.37046
Minimum0.8528288
Maximum24921.901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.0 KiB
2023-12-13T01:58:00.063931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.8528288
5-th percentile36.015802
Q1116.10847
median271.01535
Q3763.53845
95-th percentile4093.8906
Maximum24921.901
Range24921.049
Interquartile range (IQR)647.42999

Descriptive statistics

Standard deviation1907.9282
Coefficient of variation (CV)2.1308814
Kurtosis41.13203
Mean895.37046
Median Absolute Deviation (MAD)199.73271
Skewness5.4344664
Sum1413790
Variance3640190.2
MonotonicityNot monotonic
2023-12-13T01:58:00.211508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3138.532468 1
 
0.1%
903.8912526 1
 
0.1%
13480.73103 1
 
0.1%
2275.086886 1
 
0.1%
154.3820631 1
 
0.1%
30.24575764 1
 
0.1%
352.8879898 1
 
0.1%
134.1220587 1
 
0.1%
285.7729787 1
 
0.1%
599.3342401 1
 
0.1%
Other values (1569) 1569
99.4%
ValueCountFrequency (%)
0.852828801 1
0.1%
1.502040641 1
0.1%
1.5694504 1
0.1%
6.048633309 1
0.1%
6.605035217 1
0.1%
8.460416315 1
0.1%
8.519204112 1
0.1%
9.740085973 1
0.1%
10.50770424 1
0.1%
10.6337686 1
0.1%
ValueCountFrequency (%)
24921.90135 1
0.1%
18706.75175 1
0.1%
18165.5146 1
0.1%
18014.13932 1
0.1%
16302.60973 1
0.1%
16288.83867 1
0.1%
14422.23368 1
0.1%
13480.73103 1
0.1%
11887.76186 1
0.1%
11219.51382 1
0.1%

현황도형 생성일
Date

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size12.5 KiB
Minimum2017-06-28 00:00:00
Maximum2021-11-01 00:00:00
2023-12-13T01:58:00.328704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:00.444843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)

Interactions

2023-12-13T01:57:58.450233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:58.243889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:58.544117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:58.354667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:58:00.527058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
라벨명면적(도형)면적(길이)현황도형 생성일
라벨명1.0000.0450.0000.080
면적(도형)0.0451.0000.8990.000
면적(길이)0.0000.8991.0000.073
현황도형 생성일0.0800.0000.0731.000
2023-12-13T01:58:00.623120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(도형)면적(길이)라벨명
면적(도형)1.0000.9720.019
면적(길이)0.9721.0000.000
라벨명0.0190.0001.000

Missing values

2023-12-13T01:57:58.656991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:57:58.745436image/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

현황도형 관리번호라벨명면적(도형)면적(길이)현황도형 생성일
041630UQ112PS201706281320보전관리지역123525.02353138.5324682017-06-28
141630UQ112PS201706281296보전관리지역281.513706115.5897982017-06-28
241630UQ112PS201706281295보전관리지역96.90721391.5428942017-06-28
341630UQ112PS201706281294보전관리지역1.3448296.0486332017-06-28
441630UQ112PS201706281293보전관리지역204.629066118.3113822017-06-28
541630UQ112PS201706281292보전관리지역2436.816229271.7733532017-06-28
641630UQ112PS201706281291생산관리지역2018.501515188.2515632017-06-28
741630UQ112PS201706281290생산관리지역1169.850863197.0180392017-06-28
841630UQ112PS201706281141보전관리지역174413.4092297.8120982017-06-28
941630UQ112PS201706281248계획관리지역287.87281777.9017362017-06-28
현황도형 관리번호라벨명면적(도형)면적(길이)현황도형 생성일
156941630UQ112PS202111010183보전관리지역217.163422144.5696842021-11-01
157041630UQ112PS202111010202보전관리지역481.955311104.2998092021-11-01
157141630UQ112PS202111010203보전관리지역1097.618845150.7098592021-11-01
157241630UQ112PS202111010056계획관리지역342.242954157.9265692021-11-01
157341630UQ112PS202111010204보전관리지역1650.883453354.4908372021-11-01
157441630UQ112PS202111010113생산관리지역23761.18319797.5798472021-11-01
157541630UQ112PS202111010205보전관리지역3.35117713.6351392021-11-01
157641630UQ112PS202111010058계획관리지역4.07951216.2723012021-11-01
157741630UQ112PS202111010059계획관리지역5739.158405819.2022572021-11-01
157841630UQ112PS202111010060계획관리지역16615.058131305.0089372021-11-01