Overview

Dataset statistics

Number of variables14
Number of observations107
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory116.2 B

Variable types

Categorical10
Numeric2
Text2

Dataset

Description도시계획 정보시스템에 기록된 하동군 공간시설 현황 데이터, 도형 속성코드, 현황도형 생성일시, 면적 도형, 길이 도형, 라벨명, 도면번호, 집행상태코드 심볼, 도형대분류코드, 도형 중분류코드, 결정고시관리코드, 현황도형 관리번호, 도형 소분류코드, 시군구코드, 도형조서관리 코드
Author경상남도 하동군
URLhttps://www.data.go.kr/data/15123599/fileData.do

Alerts

시군구코드 has constant value ""Constant
도형 중분류코드 is highly overall correlated with 도형 속성코드 and 4 other fieldsHigh correlation
라벨명 is highly overall correlated with 도형 속성코드 and 5 other fieldsHigh correlation
도형 대분류코드 is highly overall correlated with 도형 속성코드 and 3 other fieldsHigh correlation
도형 속성코드 is highly overall correlated with 라벨명 and 3 other fieldsHigh correlation
도형 소분류코드 is highly overall correlated with 도형 속성코드 and 5 other fieldsHigh correlation
면적 도형 is highly overall correlated with 길이 도형 and 3 other fieldsHigh correlation
길이 도형 is highly overall correlated with 면적 도형High correlation
현황도형 생성일시 is highly overall correlated with 면적 도형 and 2 other fieldsHigh correlation
도면번호 is highly overall correlated with 도형 소분류코드High correlation
집행상태코드 심볼 is highly overall correlated with 면적 도형 and 4 other fieldsHigh correlation
결정고시관리코드 is highly overall correlated with 면적 도형 and 4 other fieldsHigh correlation
도형 소분류코드 is highly imbalanced (72.4%)Imbalance
면적 도형 has unique valuesUnique
길이 도형 has unique valuesUnique
현황도형 관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:40:54.704983
Analysis finished2023-12-12 20:40:57.112035
Duration2.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도형 속성코드
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Memory size988.0 B
UQT310
42 
UQT290
20 
UQT320
15 
UQT119
9 
UQT220
6 
Other values (8)
15 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique5 ?
Unique (%)4.7%

Sample

1st rowUQT310
2nd rowUQT119
3rd rowUQT119
4th rowUQT290
5th rowUQT310

Common Values

ValueCountFrequency (%)
UQT310 42
39.3%
UQT290 20
18.7%
UQT320 15
 
14.0%
UQT119 9
 
8.4%
UQT220 6
 
5.6%
UQT250 5
 
4.7%
UQT210 3
 
2.8%
UQT390 2
 
1.9%
UQT510 1
 
0.9%
UQT122 1
 
0.9%
Other values (3) 3
 
2.8%

Length

2023-12-13T05:40:57.207669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
uqt310 42
39.3%
uqt290 20
18.7%
uqt320 15
 
14.0%
uqt119 9
 
8.4%
uqt220 6
 
5.6%
uqt250 5
 
4.7%
uqt210 3
 
2.8%
uqt390 2
 
1.9%
uqt510 1
 
0.9%
uqt122 1
 
0.9%
Other values (3) 3
 
2.8%

현황도형 생성일시
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Memory size988.0 B
2020-06-14
31 
2013-11-11
29 
2014-07-01
8 
2018-08-01
6 
2022-02-11
6 
Other values (16)
27 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique9 ?
Unique (%)8.4%

Sample

1st row2014-07-01
2nd row2020-06-14
3rd row2020-06-14
4th row2020-06-14
5th row2014-07-01

Common Values

ValueCountFrequency (%)
2020-06-14 31
29.0%
2013-11-11 29
27.1%
2014-07-01 8
 
7.5%
2018-08-01 6
 
5.6%
2022-02-11 6
 
5.6%
2020-11-30 4
 
3.7%
2019-10-23 4
 
3.7%
2022-03-08 2
 
1.9%
2018-06-07 2
 
1.9%
2019-01-28 2
 
1.9%
Other values (11) 13
12.1%

Length

2023-12-13T05:40:57.361286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-06-14 31
29.0%
2013-11-11 29
27.1%
2014-07-01 8
 
7.5%
2018-08-01 6
 
5.6%
2022-02-11 6
 
5.6%
2020-11-30 4
 
3.7%
2019-10-23 4
 
3.7%
2019-01-28 2
 
1.9%
2019-08-16 2
 
1.9%
2022-12-30 2
 
1.9%
Other values (11) 13
12.1%

면적 도형
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22919.126
Minimum73.47
Maximum217477.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T05:40:57.567502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum73.47
5-th percentile467.937
Q11945.565
median5813.73
Q323879.88
95-th percentile116799.95
Maximum217477.34
Range217403.87
Interquartile range (IQR)21934.315

Descriptive statistics

Standard deviation39108.311
Coefficient of variation (CV)1.7063614
Kurtosis7.6759988
Mean22919.126
Median Absolute Deviation (MAD)4681.27
Skewness2.6770509
Sum2452346.5
Variance1.52946 × 109
MonotonicityNot monotonic
2023-12-13T05:40:57.775265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1100.61 1
 
0.9%
15558.36 1
 
0.9%
7117.91 1
 
0.9%
29577.18 1
 
0.9%
17637.11 1
 
0.9%
33196.84 1
 
0.9%
86868.59 1
 
0.9%
1547.89 1
 
0.9%
1145.2 1
 
0.9%
3741.53 1
 
0.9%
Other values (97) 97
90.7%
ValueCountFrequency (%)
73.47 1
0.9%
90.92 1
0.9%
129.62 1
0.9%
171.68 1
0.9%
281.08 1
0.9%
397.89 1
0.9%
631.38 1
0.9%
652.45 1
0.9%
664.28 1
0.9%
717.39 1
0.9%
ValueCountFrequency (%)
217477.34 1
0.9%
166908.22 1
0.9%
138451.88 1
0.9%
128186.14 1
0.9%
118533.73 1
0.9%
118298.01 1
0.9%
113304.47 1
0.9%
112952.52 1
0.9%
86868.59 1
0.9%
83275.81 1
0.9%

길이 도형
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean913.8429
Minimum39.5
Maximum4149.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T05:40:57.962855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39.5
5-th percentile116.909
Q1343.335
median555.14
Q31171.66
95-th percentile2581.722
Maximum4149.47
Range4109.97
Interquartile range (IQR)828.325

Descriptive statistics

Standard deviation869.28773
Coefficient of variation (CV)0.95124417
Kurtosis2.9153139
Mean913.8429
Median Absolute Deviation (MAD)308.42
Skewness1.7138282
Sum97781.19
Variance755661.16
MonotonicityNot monotonic
2023-12-13T05:40:58.125500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
284.71 1
 
0.9%
683.09 1
 
0.9%
389.04 1
 
0.9%
4016.92 1
 
0.9%
555.14 1
 
0.9%
3240.27 1
 
0.9%
4149.47 1
 
0.9%
157.92 1
 
0.9%
143.95 1
 
0.9%
848.41 1
 
0.9%
Other values (97) 97
90.7%
ValueCountFrequency (%)
39.5 1
0.9%
72.11 1
0.9%
75.01 1
0.9%
88.95 1
0.9%
113.32 1
0.9%
114.68 1
0.9%
122.11 1
0.9%
143.95 1
0.9%
145.96 1
0.9%
153.92 1
0.9%
ValueCountFrequency (%)
4149.47 1
0.9%
4016.92 1
0.9%
3583.49 1
0.9%
3240.27 1
0.9%
2896.48 1
0.9%
2627.61 1
0.9%
2474.65 1
0.9%
2388.68 1
0.9%
2336.89 1
0.9%
2232.13 1
0.9%

라벨명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Memory size988.0 B
완충녹지
42 
기타 공원시설
17 
경관녹지
15 
기타 교통광장시설
5 
체육공원
 
4
Other values (16)
24 

Length

Max length15
Median length4
Mean length5.1495327
Min length4

Unique

Unique12 ?
Unique (%)11.2%

Sample

1st row완충녹지
2nd row기타 교통광장시설
3rd row기타 교통광장시설
4th row옥종2수변공원
5th row완충녹지

Common Values

ValueCountFrequency (%)
완충녹지 42
39.3%
기타 공원시설 17
15.9%
경관녹지 15
 
14.0%
기타 교통광장시설 5
 
4.7%
체육공원 4
 
3.7%
교통광장 4
 
3.7%
근린공원 4
 
3.7%
기타 녹지시설 2
 
1.9%
어린이공원 2
 
1.9%
역사공원 1
 
0.9%
Other values (11) 11
 
10.3%

Length

2023-12-13T05:40:58.294412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
완충녹지 42
31.3%
기타 25
18.7%
공원시설 17
12.7%
경관녹지 15
 
11.2%
교통광장시설 5
 
3.7%
체육공원 4
 
3.0%
교통광장 4
 
3.0%
근린공원 4
 
3.0%
녹지시설 2
 
1.5%
어린이공원 2
 
1.5%
Other values (14) 14
 
10.4%

도면번호
Categorical

HIGH CORRELATION 

Distinct49
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Memory size988.0 B
1
13 
2
10 
3
 
6
5
 
4
25
 
3
Other values (44)
71 

Length

Max length6
Median length2
Mean length1.728972
Min length1

Unique

Unique23 ?
Unique (%)21.5%

Sample

1st row17
2nd row9
3rd row1
4th row24
5th row19

Common Values

ValueCountFrequency (%)
1 13
 
12.1%
2 10
 
9.3%
3 6
 
5.6%
5 4
 
3.7%
25 3
 
2.8%
24 3
 
2.8%
4 3
 
2.8%
16 3
 
2.8%
6 3
 
2.8%
7 3
 
2.8%
Other values (39) 56
52.3%

Length

2023-12-13T05:40:58.471855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 13
 
12.1%
2 10
 
9.3%
3 6
 
5.6%
5 4
 
3.7%
16 3
 
2.8%
17 3
 
2.8%
6 3
 
2.8%
7 3
 
2.8%
4 3
 
2.8%
24 3
 
2.8%
Other values (39) 56
52.3%

집행상태코드 심볼
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size988.0 B
EMA0002
59 
EMA0001
46 
EMA0003
 
2

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEMA0001
2nd rowEMA0002
3rd rowEMA0002
4th rowEMA0002
5th rowEMA0001

Common Values

ValueCountFrequency (%)
EMA0002 59
55.1%
EMA0001 46
43.0%
EMA0003 2
 
1.9%

Length

2023-12-13T05:40:58.621824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:40:58.734351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ema0002 59
55.1%
ema0001 46
43.0%
ema0003 2
 
1.9%

도형 대분류코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size988.0 B
UQT300
59 
UQT200
35 
UQT100
12 
UQT500
 
1

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st rowUQT300
2nd rowUQT100
3rd rowUQT100
4th rowUQT200
5th rowUQT300

Common Values

ValueCountFrequency (%)
UQT300 59
55.1%
UQT200 35
32.7%
UQT100 12
 
11.2%
UQT500 1
 
0.9%

Length

2023-12-13T05:40:58.868014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:40:58.994008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqt300 59
55.1%
uqt200 35
32.7%
uqt100 12
 
11.2%
uqt500 1
 
0.9%

도형 중분류코드
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size988.0 B
UQT310
42 
UQT290
20 
UQT320
15 
UQT110
9 
UQT220
6 
Other values (6)
15 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique2 ?
Unique (%)1.9%

Sample

1st rowUQT310
2nd rowUQT110
3rd rowUQT110
4th rowUQT290
5th rowUQT310

Common Values

ValueCountFrequency (%)
UQT310 42
39.3%
UQT290 20
18.7%
UQT320 15
 
14.0%
UQT110 9
 
8.4%
UQT220 6
 
5.6%
UQT250 5
 
4.7%
UQT210 3
 
2.8%
UQT120 3
 
2.8%
UQT390 2
 
1.9%
UQT510 1
 
0.9%

Length

2023-12-13T05:40:59.121400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
uqt310 42
39.3%
uqt290 20
18.7%
uqt320 15
 
14.0%
uqt110 9
 
8.4%
uqt220 6
 
5.6%
uqt250 5
 
4.7%
uqt210 3
 
2.8%
uqt120 3
 
2.8%
uqt390 2
 
1.9%
uqt510 1
 
0.9%

결정고시관리코드
Categorical

HIGH CORRELATION 

Distinct33
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size988.0 B
48850NTC202105130759
31 
48850NTC201106302010
15 
48850NTC201401160382
9 
48850NTC201807260575
6 
48850NTC202001230654
 
4
Other values (28)
42 

Length

Max length20
Median length20
Mean length20
Min length20

Unique

Unique17 ?
Unique (%)15.9%

Sample

1st row48850NTC201401160382
2nd row48850NTC202105130759
3rd row48850NTC202105130759
4th row48850NTC202105130759
5th row48850NTC201401160382

Common Values

ValueCountFrequency (%)
48850NTC202105130759 31
29.0%
48850NTC201106302010 15
14.0%
48850NTC201401160382 9
 
8.4%
48850NTC201807260575 6
 
5.6%
48850NTC202001230654 4
 
3.7%
48850NTC201910170642 4
 
3.7%
48850NTC201211080316 3
 
2.8%
48850NTC201805160573 2
 
1.9%
48850NTC201307040354 2
 
1.9%
48850NTC201308080362 2
 
1.9%
Other values (23) 29
27.1%

Length

2023-12-13T05:40:59.278559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
48850ntc202105130759 31
29.0%
48850ntc201106302010 15
14.0%
48850ntc201401160382 9
 
8.4%
48850ntc201807260575 6
 
5.6%
48850ntc202001230654 4
 
3.7%
48850ntc201910170642 4
 
3.7%
48850ntc201211080316 3
 
2.8%
48850ntc202201060806 2
 
1.9%
48850ntc201202091000 2
 
1.9%
48850ntc201907110628 2
 
1.9%
Other values (23) 29
27.1%

현황도형 관리번호
Text

UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-13T05:40:59.530603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters2568
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

Unique107 ?
Unique (%)100.0%

Sample

1st row48850UQ153PS201401162017
2nd row48850UQ153PS202106140039
3rd row48850UQ153PS202106140027
4th row48850UQ153PS202106140026
5th row48850UQ153PS201401160019
ValueCountFrequency (%)
48850uq153ps201401162017 1
 
0.9%
48850uq153ps202203030001 1
 
0.9%
48850uq153ps201910230137 1
 
0.9%
48850uq153ps202106140014 1
 
0.9%
48850uq153ps200801240090 1
 
0.9%
48850uq153ps202011300002 1
 
0.9%
48850uq153ps202106140105 1
 
0.9%
48850uq153ps201910230138 1
 
0.9%
48850uq153ps202106140017 1
 
0.9%
48850uq153ps202106140018 1
 
0.9%
Other values (97) 97
90.7%
2023-12-13T05:40:59.930485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 598
23.3%
1 357
13.9%
8 256
10.0%
5 227
 
8.8%
2 219
 
8.5%
4 181
 
7.0%
3 169
 
6.6%
U 107
 
4.2%
Q 107
 
4.2%
P 107
 
4.2%
Other values (4) 240
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2140
83.3%
Uppercase Letter 428
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 598
27.9%
1 357
16.7%
8 256
12.0%
5 227
 
10.6%
2 219
 
10.2%
4 181
 
8.5%
3 169
 
7.9%
6 76
 
3.6%
7 35
 
1.6%
9 22
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
U 107
25.0%
Q 107
25.0%
P 107
25.0%
S 107
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2140
83.3%
Latin 428
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 598
27.9%
1 357
16.7%
8 256
12.0%
5 227
 
10.6%
2 219
 
10.2%
4 181
 
8.5%
3 169
 
7.9%
6 76
 
3.6%
7 35
 
1.6%
9 22
 
1.0%
Latin
ValueCountFrequency (%)
U 107
25.0%
Q 107
25.0%
P 107
25.0%
S 107
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 598
23.3%
1 357
13.9%
8 256
10.0%
5 227
 
8.8%
2 219
 
8.5%
4 181
 
7.0%
3 169
 
6.6%
U 107
 
4.2%
Q 107
 
4.2%
P 107
 
4.2%
Other values (4) 240
9.3%

도형 소분류코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size988.0 B
<NA>
95 
UQT119
 
9
UQT122
 
1
UQT129
 
1
UQT121
 
1

Length

Max length6
Median length4
Mean length4.2242991
Min length4

Unique

Unique3 ?
Unique (%)2.8%

Sample

1st row<NA>
2nd rowUQT119
3rd rowUQT119
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 95
88.8%
UQT119 9
 
8.4%
UQT122 1
 
0.9%
UQT129 1
 
0.9%
UQT121 1
 
0.9%

Length

2023-12-13T05:41:00.109571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:41:00.257025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 95
88.8%
uqt119 9
 
8.4%
uqt122 1
 
0.9%
uqt129 1
 
0.9%
uqt121 1
 
0.9%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size988.0 B
48850
107 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48850
2nd row48850
3rd row48850
4th row48850
5th row48850

Common Values

ValueCountFrequency (%)
48850 107
100.0%

Length

2023-12-13T05:41:00.388451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:41:00.516551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48850 107
100.0%

도형조서관리 코드
Text

Distinct102
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-13T05:41:00.732015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters2140
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

Unique97 ?
Unique (%)90.7%

Sample

1st row48850URZ201401164332
2nd row48850URZ202105132375
3rd row48850URZ202105132372
4th row48850URZ202105132380
5th row48850URZ201401164334
ValueCountFrequency (%)
48850urz201401164332 2
 
1.9%
48850urz200803270704 2
 
1.9%
48850urz201106303398 2
 
1.9%
48850urz200511240579 2
 
1.9%
48850urz201401164339 2
 
1.9%
48850urz201910172086 1
 
0.9%
48850urz202105132379 1
 
0.9%
48850urz201910172082 1
 
0.9%
48850urz202001232144 1
 
0.9%
48850urz202105132478 1
 
0.9%
Other values (92) 92
86.0%
2023-12-13T05:41:01.186565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 404
18.9%
2 282
13.2%
8 264
12.3%
1 229
10.7%
4 186
8.7%
5 170
7.9%
3 140
 
6.5%
U 107
 
5.0%
R 107
 
5.0%
Z 107
 
5.0%
Other values (3) 144
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1819
85.0%
Uppercase Letter 321
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 404
22.2%
2 282
15.5%
8 264
14.5%
1 229
12.6%
4 186
10.2%
5 170
9.3%
3 140
 
7.7%
6 61
 
3.4%
7 45
 
2.5%
9 38
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
U 107
33.3%
R 107
33.3%
Z 107
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1819
85.0%
Latin 321
 
15.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 404
22.2%
2 282
15.5%
8 264
14.5%
1 229
12.6%
4 186
10.2%
5 170
9.3%
3 140
 
7.7%
6 61
 
3.4%
7 45
 
2.5%
9 38
 
2.1%
Latin
ValueCountFrequency (%)
U 107
33.3%
R 107
33.3%
Z 107
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2140
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 404
18.9%
2 282
13.2%
8 264
12.3%
1 229
10.7%
4 186
8.7%
5 170
7.9%
3 140
 
6.5%
U 107
 
5.0%
R 107
 
5.0%
Z 107
 
5.0%
Other values (3) 144
 
6.7%

Interactions

2023-12-13T05:40:56.436124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:40:56.204004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:40:56.556328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:40:56.322938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:41:01.338985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도형 속성코드현황도형 생성일시면적 도형길이 도형라벨명도면번호집행상태코드 심볼도형 대분류코드도형 중분류코드결정고시관리코드도형 소분류코드
도형 속성코드1.0000.7690.5140.5571.0000.0000.6131.0001.0000.8941.000
현황도형 생성일시0.7691.0000.8500.6980.8810.0000.9540.5030.7880.9970.432
면적 도형0.5140.8501.0000.7000.7910.0000.7790.2420.5480.9110.000
길이 도형0.5570.6980.7001.0000.6760.0000.5550.0000.5950.7250.000
라벨명1.0000.8810.7910.6761.0000.0000.8251.0001.0000.9381.000
도면번호0.0000.0000.0000.0000.0001.0000.0000.0000.0000.0001.000
집행상태코드 심볼0.6130.9540.7790.5550.8250.0001.0000.2080.6030.9861.000
도형 대분류코드1.0000.5030.2420.0001.0000.0000.2081.0001.0000.639NaN
도형 중분류코드1.0000.7880.5480.5951.0000.0000.6031.0001.0000.9241.000
결정고시관리코드0.8940.9970.9110.7250.9380.0000.9860.6390.9241.0000.151
도형 소분류코드1.0000.4320.0000.0001.0001.0001.000NaN1.0000.1511.000
2023-12-13T05:41:01.505882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도면번호집행상태코드 심볼도형 중분류코드결정고시관리코드라벨명도형 대분류코드도형 속성코드도형 소분류코드현황도형 생성일시
도면번호1.0000.0000.0000.0000.0000.0000.0000.5480.000
집행상태코드 심볼0.0001.0000.4180.7410.5180.1960.4110.8940.705
도형 중분류코드0.0000.4181.0000.5080.9460.9650.9900.8940.397
결정고시관리코드0.0000.7410.5081.0000.5230.3230.4770.0000.883
라벨명0.0000.5180.9460.5231.0000.9140.9570.9350.365
도형 대분류코드0.0000.1960.9650.3230.9141.0000.9551.0000.266
도형 속성코드0.0000.4110.9900.4770.9570.9551.0001.0000.363
도형 소분류코드0.5480.8940.8940.0000.9351.0001.0001.0000.284
현황도형 생성일시0.0000.7050.3970.8830.3650.2660.3630.2841.000
2023-12-13T05:41:01.710402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적 도형길이 도형도형 속성코드현황도형 생성일시라벨명도면번호집행상태코드 심볼도형 대분류코드도형 중분류코드결정고시관리코드도형 소분류코드
면적 도형1.0000.8590.2530.5270.4450.0000.6770.1050.2900.5640.000
길이 도형0.8591.0000.2620.3210.3030.0000.3840.0000.2990.3050.000
도형 속성코드0.2530.2621.0000.3630.9570.0000.4110.9550.9900.4771.000
현황도형 생성일시0.5270.3210.3631.0000.3650.0000.7050.2660.3970.8830.284
라벨명0.4450.3030.9570.3651.0000.0000.5180.9140.9460.5230.935
도면번호0.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.548
집행상태코드 심볼0.6770.3840.4110.7050.5180.0001.0000.1960.4180.7410.894
도형 대분류코드0.1050.0000.9550.2660.9140.0000.1961.0000.9650.3231.000
도형 중분류코드0.2900.2990.9900.3970.9460.0000.4180.9651.0000.5080.894
결정고시관리코드0.5640.3050.4770.8830.5230.0000.7410.3230.5081.0000.000
도형 소분류코드0.0000.0001.0000.2840.9350.5480.8941.0000.8940.0001.000

Missing values

2023-12-13T05:40:56.712804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:40:57.000863image/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

도형 속성코드현황도형 생성일시면적 도형길이 도형라벨명도면번호집행상태코드 심볼도형 대분류코드도형 중분류코드결정고시관리코드현황도형 관리번호도형 소분류코드시군구코드도형조서관리 코드
0UQT3102014-07-011100.61284.71완충녹지17EMA0001UQT300UQT31048850NTC20140116038248850UQ153PS201401162017<NA>4885048850URZ201401164332
1UQT1192020-06-1453563.881631.0기타 교통광장시설9EMA0002UQT100UQT11048850NTC20210513075948850UQ153PS202106140039UQT1194885048850URZ202105132375
2UQT1192020-06-1423641.631632.74기타 교통광장시설1EMA0002UQT100UQT11048850NTC20210513075948850UQ153PS202106140027UQT1194885048850URZ202105132372
3UQT2902020-06-149980.47497.44옥종2수변공원24EMA0002UQT200UQT29048850NTC20210513075948850UQ153PS202106140026<NA>4885048850URZ202105132380
4UQT3102014-07-012056.38431.28완충녹지19EMA0001UQT300UQT31048850NTC20140116038248850UQ153PS201401160019<NA>4885048850URZ201401164334
5UQT2502016-03-29113304.471939.79체육공원16EMA0002UQT200UQT25048850NTC20160310048348850UQ153PS201603100001<NA>4885048850URZ201603104439
6UQT3102014-07-01281.0875.01완충녹지24EMA0001UQT300UQT31048850NTC20140116038248850UQ153PS201401162024<NA>4885048850URZ201401164339
7UQT2902017-05-2132034.03982.78기타 공원시설2EMA0002UQT200UQT29048850NTC20160512049248850UQ153PS201612010111<NA>4885048850URZ201605124455
8UQT3202016-05-2218575.091105.74경관녹지2EMA0002UQT300UQT32048850NTC20160310048548850UQ153PS201603100004<NA>4885048850URZ201603104450
9UQT3102013-11-11717.39178.51완충녹지1EMA0002UQT300UQT31048850NTC20080327019348850UQ153PS200803270017<NA>4885048850URZ200803270704
도형 속성코드현황도형 생성일시면적 도형길이 도형라벨명도면번호집행상태코드 심볼도형 대분류코드도형 중분류코드결정고시관리코드현황도형 관리번호도형 소분류코드시군구코드도형조서관리 코드
97UQT2502021-03-1627504.25653.88체육공원7EMA0001UQT200UQT25048850NTC20210218072848850UQ153PS202103160003<NA>4885048850URZ202102182165
98UQT3202020-06-1490.92113.32경관녹지45EMA0002UQT300UQT32048850NTC20210513075948850UQ153PS202106140043<NA>4885048850URZ202105132402
99UQT3202013-11-1110618.91546.46경관녹지3EMA0002UQT300UQT32048850NTC20121108031648850UQ153PS201211080094<NA>4885048850URZ201211084146
100UQT3102020-06-145448.371414.82완충녹지35EMA0001UQT300UQT31048850NTC20210513075948850UQ153PS202106140048<NA>4885048850URZ202105132392
101UQT3202020-06-14171.6888.95경관녹지43EMA0002UQT300UQT32048850NTC20210513075948850UQ153PS202106140045<NA>4885048850URZ202105132400
102UQT3102020-06-144538.871065.89완충녹지29EMA0001UQT300UQT31048850NTC20210513075948850UQ153PS202106140047<NA>4885048850URZ202105132386
103UQT3202013-11-1111126.25853.72경관녹지1EMA0002UQT300UQT32048850NTC20121108031648850UQ153PS201211080092<NA>4885048850URZ201211084144
104UQT3102020-06-146946.81508.2완충녹지34EMA0001UQT300UQT31048850NTC20210513075948850UQ153PS202106140049<NA>4885048850URZ202105132391
105UQT3102020-06-142836.99504.85완충녹지25EMA0001UQT300UQT31048850NTC20210513075948850UQ153PS202106140046<NA>4885048850URZ202105132382
106UQT3102014-07-01129.6272.11완충녹지17EMA0001UQT300UQT31048850NTC20140116038248850UQ153PS201401160017<NA>4885048850URZ201401164332