Overview

Dataset statistics

Number of variables14
Number of observations56
Missing cells56
Missing cells (%)7.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory118.4 B

Variable types

Categorical9
Numeric2
Text2
Unsupported1

Dataset

Description도시계획정보 시스템에 등록된 하동군의 교통시설 현황, 도형 속성코드, 현황도형 생성일시, 면적과 길이의 도형, 라벨명, 도면번호, 집행상태코드 심볼, 도형 대분류코드, 도형 중분류코드, 결정고시관리코드, 현황도형 관리번호, 도형 소분류코드, 시군구 코드, 도형조서관리 코드 정보
Author경상남도 하동군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15123706

Alerts

시군구코드 has constant value ""Constant
도형 중분류코드 is highly overall correlated with 면적_도형 and 5 other fieldsHigh correlation
도형 대분류코드 is highly overall correlated with 면적_도형 and 5 other fieldsHigh correlation
도형 속성코드 is highly overall correlated with 면적_도형 and 5 other fieldsHigh correlation
라벨명 is highly overall correlated with 면적_도형 and 5 other fieldsHigh correlation
면적_도형 is highly overall correlated with 길이_도형 and 4 other fieldsHigh correlation
길이_도형 is highly overall correlated with 면적_도형 and 6 other fieldsHigh correlation
현황도형 생성일시 is highly overall correlated with 길이_도형 and 1 other fieldsHigh correlation
결정고시관리코드 is highly overall correlated with 길이_도형 and 5 other fieldsHigh correlation
도형 대분류코드 is highly imbalanced (50.9%)Imbalance
도형 소분류코드 has 56 (100.0%) missing valuesMissing
현황도형 관리번호 has unique valuesUnique
도형 소분류코드 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 23:05:22.918725
Analysis finished2023-12-10 23:05:24.100998
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도형 속성코드
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size580.0 B
UQS290
22 
UQS210
22 
UQS510
5 
UQS720
3 
UQS310
3 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st rowUQS290
2nd rowUQS290
3rd rowUQS551
4th rowUQS290
5th rowUQS210

Common Values

ValueCountFrequency (%)
UQS290 22
39.3%
UQS210 22
39.3%
UQS510 5
 
8.9%
UQS720 3
 
5.4%
UQS310 3
 
5.4%
UQS551 1
 
1.8%

Length

2023-12-11T08:05:24.158558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:05:24.256101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqs290 22
39.3%
uqs210 22
39.3%
uqs510 5
 
8.9%
uqs720 3
 
5.4%
uqs310 3
 
5.4%
uqs551 1
 
1.8%

현황도형 생성일시
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2013-11-11
19 
2020-06-14
14 
2018-08-01
6 
2019-10-23
3 
2016-05-22
3 
Other values (9)
11 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique7 ?
Unique (%)12.5%

Sample

1st row2022-05-31
2nd row2013-11-11
3rd row2022-02-11
4th row2020-06-14
5th row2021-06-14

Common Values

ValueCountFrequency (%)
2013-11-11 19
33.9%
2020-06-14 14
25.0%
2018-08-01 6
 
10.7%
2019-10-23 3
 
5.4%
2016-05-22 3
 
5.4%
2017-05-21 2
 
3.6%
2023-05-12 2
 
3.6%
2022-05-31 1
 
1.8%
2022-02-11 1
 
1.8%
2021-06-14 1
 
1.8%
Other values (4) 4
 
7.1%

Length

2023-12-11T08:05:24.440239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2013-11-11 19
33.9%
2020-06-14 14
25.0%
2018-08-01 6
 
10.7%
2019-10-23 3
 
5.4%
2016-05-22 3
 
5.4%
2017-05-21 2
 
3.6%
2023-05-12 2
 
3.6%
2022-05-31 1
 
1.8%
2022-02-11 1
 
1.8%
2021-06-14 1
 
1.8%
Other values (4) 4
 
7.1%

면적_도형
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11229.744
Minimum249.51
Maximum184000.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-11T08:05:24.566794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum249.51
5-th percentile429.3425
Q11219.18
median2261.55
Q37417.165
95-th percentile50982.362
Maximum184000.36
Range183750.85
Interquartile range (IQR)6197.985

Descriptive statistics

Standard deviation29960.856
Coefficient of variation (CV)2.6679909
Kurtosis22.371898
Mean11229.744
Median Absolute Deviation (MAD)1777.34
Skewness4.5499619
Sum628865.68
Variance8.976529 × 108
MonotonicityNot monotonic
2023-12-11T08:05:24.965133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5813.68 2
 
3.6%
6880.77 1
 
1.8%
574.73 1
 
1.8%
7501.99 1
 
1.8%
4071.38 1
 
1.8%
2002.62 1
 
1.8%
8343.1 1
 
1.8%
2002.87 1
 
1.8%
2835.05 1
 
1.8%
2141.42 1
 
1.8%
Other values (45) 45
80.4%
ValueCountFrequency (%)
249.51 1
1.8%
284.9 1
1.8%
421.07 1
1.8%
432.1 1
1.8%
516.7 1
1.8%
522.46 1
1.8%
525.94 1
1.8%
574.73 1
1.8%
777.18 1
1.8%
833.84 1
1.8%
ValueCountFrequency (%)
184000.36 1
1.8%
110850.96 1
1.8%
81440.68 1
1.8%
40829.59 1
1.8%
28364.73 1
1.8%
12136.29 1
1.8%
11824.12 1
1.8%
10260.71 1
1.8%
9443.7 1
1.8%
8343.1 1
1.8%

길이_도형
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean806.18071
Minimum63.93
Maximum21334.26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2023-12-11T08:05:25.145751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum63.93
5-th percentile84.5875
Q1158.21
median276.02
Q3378.185
95-th percentile1490.7725
Maximum21334.26
Range21270.33
Interquartile range (IQR)219.975

Descriptive statistics

Standard deviation2899.4898
Coefficient of variation (CV)3.5965755
Kurtosis47.940227
Mean806.18071
Median Absolute Deviation (MAD)110.9
Skewness6.7732887
Sum45146.12
Variance8407041.2
MonotonicityNot monotonic
2023-12-11T08:05:25.314075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
299.51 2
 
3.6%
435.35 1
 
1.8%
134.94 1
 
1.8%
357.5 1
 
1.8%
331.06 1
 
1.8%
291.57 1
 
1.8%
377.46 1
 
1.8%
191.23 1
 
1.8%
231.13 1
 
1.8%
200.55 1
 
1.8%
Other values (45) 45
80.4%
ValueCountFrequency (%)
63.93 1
1.8%
76.29 1
1.8%
83.11 1
1.8%
85.08 1
1.8%
100.22 1
1.8%
100.45 1
1.8%
112.74 1
1.8%
113.06 1
1.8%
114.17 1
1.8%
134.94 1
1.8%
ValueCountFrequency (%)
21334.26 1
1.8%
5665.55 1
1.8%
1579.34 1
1.8%
1461.25 1
1.8%
1297.84 1
1.8%
1092.74 1
1.8%
576.68 1
1.8%
517.25 1
1.8%
488.15 1
1.8%
463.18 1
1.8%

라벨명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size580.0 B
UQS290
22 
UQS210
22 
UQS510
5 
UQS720
3 
UQS310
3 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st rowUQS290
2nd rowUQS290
3rd rowUQS551
4th rowUQS290
5th rowUQS210

Common Values

ValueCountFrequency (%)
UQS290 22
39.3%
UQS210 22
39.3%
UQS510 5
 
8.9%
UQS720 3
 
5.4%
UQS310 3
 
5.4%
UQS551 1
 
1.8%

Length

2023-12-11T08:05:25.468465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:05:25.601022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqs290 22
39.3%
uqs210 22
39.3%
uqs510 5
 
8.9%
uqs720 3
 
5.4%
uqs310 3
 
5.4%
uqs551 1
 
1.8%

도면번호
Categorical

Distinct26
Distinct (%)46.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
2
7 
1
7 
3
6 
4
 
3
5
 
3
Other values (21)
30 

Length

Max length4
Median length1
Mean length1.4285714
Min length1

Unique

Unique13 ?
Unique (%)23.2%

Sample

1st row2
2nd row1
3rd row1
4th rowⅡ-1
5th row21

Common Values

ValueCountFrequency (%)
2 7
 
12.5%
1 7
 
12.5%
3 6
 
10.7%
4 3
 
5.4%
5 3
 
5.4%
A 3
 
5.4%
11 2
 
3.6%
13 2
 
3.6%
8 2
 
3.6%
12 2
 
3.6%
Other values (16) 19
33.9%

Length

2023-12-11T08:05:25.773513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 7
 
12.5%
1 7
 
12.5%
3 6
 
10.7%
4 3
 
5.4%
5 3
 
5.4%
a 3
 
5.4%
14 2
 
3.6%
6 2
 
3.6%
9 2
 
3.6%
12 2
 
3.6%
Other values (16) 19
33.9%

집행상태코드 심볼
Categorical

Distinct3
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
EMA0002
36 
EMA0001
18 
EMA0003
 
2

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
EMA0002 36
64.3%
EMA0001 18
32.1%
EMA0003 2
 
3.6%

Length

2023-12-11T08:05:25.897366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:05:26.004186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ema0002 36
64.3%
ema0001 18
32.1%
ema0003 2
 
3.6%

도형 대분류코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size580.0 B
UQS200
44 
UQS500
5 
UQS700
 
3
UQS300
 
3
UQS550
 
1

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st rowUQS200
2nd rowUQS200
3rd rowUQS550
4th rowUQS200
5th rowUQS200

Common Values

ValueCountFrequency (%)
UQS200 44
78.6%
UQS500 5
 
8.9%
UQS700 3
 
5.4%
UQS300 3
 
5.4%
UQS550 1
 
1.8%

Length

2023-12-11T08:05:26.107741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:05:26.225967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqs200 44
78.6%
uqs500 5
 
8.9%
uqs700 3
 
5.4%
uqs300 3
 
5.4%
uqs550 1
 
1.8%

도형 중분류코드
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size580.0 B
UQS290
22 
UQS210
22 
UQS510
5 
UQS720
3 
UQS310
3 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st rowUQS290
2nd rowUQS290
3rd rowUQS551
4th rowUQS290
5th rowUQS210

Common Values

ValueCountFrequency (%)
UQS290 22
39.3%
UQS210 22
39.3%
UQS510 5
 
8.9%
UQS720 3
 
5.4%
UQS310 3
 
5.4%
UQS551 1
 
1.8%

Length

2023-12-11T08:05:26.339320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:05:26.442111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqs290 22
39.3%
uqs210 22
39.3%
uqs510 5
 
8.9%
uqs720 3
 
5.4%
uqs310 3
 
5.4%
uqs551 1
 
1.8%

결정고시관리코드
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)41.1%
Missing0
Missing (%)0.0%
Memory size580.0 B
48850NTC202105130759
13 
48850NTC201106302010
9 
48850NTC201202091000
4 
48850NTC201807050576
3 
48850NTC201307040354
3 
Other values (18)
24 

Length

Max length20
Median length20
Mean length20
Min length20

Unique

Unique14 ?
Unique (%)25.0%

Sample

1st row48850NTC202109020781
2nd row48850NTC200803270193
3rd row48850NTC202202100813
4th row48850NTC202105130759
5th row48850NTC201710190530

Common Values

ValueCountFrequency (%)
48850NTC202105130759 13
23.2%
48850NTC201106302010 9
16.1%
48850NTC201202091000 4
 
7.1%
48850NTC201807050576 3
 
5.4%
48850NTC201307040354 3
 
5.4%
48850NTC201807260575 3
 
5.4%
48850NTC201603100485 3
 
5.4%
48850NTC202205170826 2
 
3.6%
48850NTC201910170642 2
 
3.6%
48850NTC201602180478 1
 
1.8%
Other values (13) 13
23.2%

Length

2023-12-11T08:05:26.545851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
48850ntc202105130759 13
23.2%
48850ntc201106302010 9
16.1%
48850ntc201202091000 4
 
7.1%
48850ntc201807050576 3
 
5.4%
48850ntc201307040354 3
 
5.4%
48850ntc201807260575 3
 
5.4%
48850ntc201603100485 3
 
5.4%
48850ntc202205170826 2
 
3.6%
48850ntc201910170642 2
 
3.6%
48850ntc202109020781 1
 
1.8%
Other values (13) 13
23.2%

현황도형 관리번호
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2023-12-11T08:05:26.768881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters1344
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

Unique56 ?
Unique (%)100.0%

Sample

1st row48850UQ152PS202205310001
2nd row48850UQ152PS200803270016
3rd row48850UQ152PS202202110002
4th row48850UQ152PS202106140012
5th row48850UQ152PS202106140016
ValueCountFrequency (%)
48850uq152ps202205310001 1
 
1.8%
48850uq152ps200803270016 1
 
1.8%
48850uq152ps201602180001 1
 
1.8%
48850uq152ps201808010065 1
 
1.8%
48850uq152ps201808010062 1
 
1.8%
48850uq152ps201808010064 1
 
1.8%
48850uq152ps202106140002 1
 
1.8%
48850uq152ps202106140005 1
 
1.8%
48850uq152ps201808010063 1
 
1.8%
48850uq152ps201603100001 1
 
1.8%
Other values (46) 46
82.1%
2023-12-11T08:05:27.142876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 337
25.1%
1 173
12.9%
2 170
12.6%
8 130
 
9.7%
5 128
 
9.5%
4 95
 
7.1%
U 56
 
4.2%
Q 56
 
4.2%
P 56
 
4.2%
S 56
 
4.2%
Other values (4) 87
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1120
83.3%
Uppercase Letter 224
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 337
30.1%
1 173
15.4%
2 170
15.2%
8 130
 
11.6%
5 128
 
11.4%
4 95
 
8.5%
6 39
 
3.5%
3 29
 
2.6%
7 10
 
0.9%
9 9
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
U 56
25.0%
Q 56
25.0%
P 56
25.0%
S 56
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1120
83.3%
Latin 224
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 337
30.1%
1 173
15.4%
2 170
15.2%
8 130
 
11.6%
5 128
 
11.4%
4 95
 
8.5%
6 39
 
3.5%
3 29
 
2.6%
7 10
 
0.9%
9 9
 
0.8%
Latin
ValueCountFrequency (%)
U 56
25.0%
Q 56
25.0%
P 56
25.0%
S 56
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1344
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 337
25.1%
1 173
12.9%
2 170
12.6%
8 130
 
9.7%
5 128
 
9.5%
4 95
 
7.1%
U 56
 
4.2%
Q 56
 
4.2%
P 56
 
4.2%
S 56
 
4.2%
Other values (4) 87
 
6.5%

도형 소분류코드
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
48850
56 

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 56
100.0%

Length

2023-12-11T08:05:27.308261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:05:27.420089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48850 56
100.0%

도형조서관리 코드
Text

Distinct55
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size580.0 B
2023-12-11T08:05:27.650383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters1120
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

Unique54 ?
Unique (%)96.4%

Sample

1st row48850URZ202110290005
2nd row48850URZ200803270703
3rd row48850URZ202202102604
4th row48850URZ202105132473
5th row48850URZ201710191952
ValueCountFrequency (%)
48850urz201106303384 2
 
3.6%
48850urz201602184438 1
 
1.8%
48850urz202105132368 1
 
1.8%
48850urz201807262011 1
 
1.8%
48850urz201807052025 1
 
1.8%
48850urz201807262013 1
 
1.8%
48850urz202105132370 1
 
1.8%
48850urz202105132367 1
 
1.8%
48850urz201807262012 1
 
1.8%
48850urz201603104445 1
 
1.8%
Other values (45) 45
80.4%
2023-12-11T08:05:28.039304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 222
19.8%
2 143
12.8%
8 132
11.8%
1 118
10.5%
4 88
 
7.9%
5 88
 
7.9%
3 68
 
6.1%
U 56
 
5.0%
R 56
 
5.0%
Z 56
 
5.0%
Other values (3) 93
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 952
85.0%
Uppercase Letter 168
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 222
23.3%
2 143
15.0%
8 132
13.9%
1 118
12.4%
4 88
 
9.2%
5 88
 
9.2%
3 68
 
7.1%
7 38
 
4.0%
6 33
 
3.5%
9 22
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
U 56
33.3%
R 56
33.3%
Z 56
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 952
85.0%
Latin 168
 
15.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 222
23.3%
2 143
15.0%
8 132
13.9%
1 118
12.4%
4 88
 
9.2%
5 88
 
9.2%
3 68
 
7.1%
7 38
 
4.0%
6 33
 
3.5%
9 22
 
2.3%
Latin
ValueCountFrequency (%)
U 56
33.3%
R 56
33.3%
Z 56
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 222
19.8%
2 143
12.8%
8 132
11.8%
1 118
10.5%
4 88
 
7.9%
5 88
 
7.9%
3 68
 
6.1%
U 56
 
5.0%
R 56
 
5.0%
Z 56
 
5.0%
Other values (3) 93
8.3%

Interactions

2023-12-11T08:05:23.673695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:05:23.506876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:05:23.747172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:05:23.600744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:05:28.181324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도형 속성코드현황도형 생성일시면적_도형길이_도형라벨명도면번호집행상태코드 심볼도형 대분류코드도형 중분류코드결정고시관리코드현황도형 관리번호도형조서관리 코드
도형 속성코드1.0000.7700.9300.9551.0000.0000.6941.0001.0000.9031.0001.000
현황도형 생성일시0.7701.0000.5830.9050.7700.0000.7050.7730.7701.0001.0001.000
면적_도형0.9300.5831.0001.0000.9300.0000.0000.8140.9300.5331.0001.000
길이_도형0.9550.9051.0001.0000.9550.0000.1910.7490.9550.8991.0001.000
라벨명1.0000.7700.9300.9551.0000.0000.6941.0001.0000.9031.0001.000
도면번호0.0000.0000.0000.0000.0001.0000.0000.0000.0000.0001.0001.000
집행상태코드 심볼0.6940.7050.0000.1910.6940.0001.0000.4550.6940.7531.0001.000
도형 대분류코드1.0000.7730.8140.7491.0000.0000.4551.0001.0000.9051.0001.000
도형 중분류코드1.0000.7700.9300.9551.0000.0000.6941.0001.0000.9031.0001.000
결정고시관리코드0.9031.0000.5330.8990.9030.0000.7530.9050.9031.0001.0001.000
현황도형 관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도형조서관리 코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-11T08:05:28.345328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도형 중분류코드도형 대분류코드도형 속성코드현황도형 생성일시집행상태코드 심볼결정고시관리코드라벨명도면번호
도형 중분류코드1.0000.9901.0000.4710.3640.5571.0000.000
도형 대분류코드0.9901.0000.9900.4890.3780.5810.9900.000
도형 속성코드1.0000.9901.0000.4710.3640.5571.0000.000
현황도형 생성일시0.4710.4890.4711.0000.4660.8860.4710.000
집행상태코드 심볼0.3640.3780.3640.4661.0000.4260.3640.000
결정고시관리코드0.5570.5810.5570.8860.4261.0000.5570.000
라벨명1.0000.9901.0000.4710.3640.5571.0000.000
도면번호0.0000.0000.0000.0000.0000.0000.0001.000
2023-12-11T08:05:28.504660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적_도형길이_도형도형 속성코드현황도형 생성일시라벨명도면번호집행상태코드 심볼도형 대분류코드도형 중분류코드결정고시관리코드
면적_도형1.0000.8700.6170.3030.6170.0000.0000.7010.6170.223
길이_도형0.8701.0000.7220.7270.7220.0000.0530.7340.7220.599
도형 속성코드0.6170.7221.0000.4711.0000.0000.3640.9901.0000.557
현황도형 생성일시0.3030.7270.4711.0000.4710.0000.4660.4890.4710.886
라벨명0.6170.7221.0000.4711.0000.0000.3640.9901.0000.557
도면번호0.0000.0000.0000.0000.0001.0000.0000.0000.0000.000
집행상태코드 심볼0.0000.0530.3640.4660.3640.0001.0000.3780.3640.426
도형 대분류코드0.7010.7340.9900.4890.9900.0000.3781.0000.9900.581
도형 중분류코드0.6170.7221.0000.4711.0000.0000.3640.9901.0000.557
결정고시관리코드0.2230.5990.5570.8860.5570.0000.4260.5810.5571.000

Missing values

2023-12-11T08:05:23.859272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:05:24.032533image/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
0UQS2902022-05-316880.77435.35UQS2902EMA0001UQS200UQS29048850NTC20210902078148850UQ152PS202205310001<NA>4885048850URZ202110290005
1UQS2902013-11-111116.09142.82UQS2901EMA0002UQS200UQS29048850NTC20080327019348850UQ152PS200803270016<NA>4885048850URZ200803270703
2UQS5512022-02-1140829.595665.55UQS5511EMA0001UQS550UQS55148850NTC20220210081348850UQ152PS202202110002<NA>4885048850URZ202202102604
3UQS2902020-06-147388.89380.36UQS290Ⅱ-1EMA0002UQS200UQS29048850NTC20210513075948850UQ152PS202106140012<NA>4885048850URZ202105132473
4UQS2102021-06-1411824.12488.15UQS21021EMA0001UQS200UQS21048850NTC20171019053048850UQ152PS202106140016<NA>4885048850URZ201710191952
5UQS2902020-06-141483.08209.14UQS2906EMA0002UQS200UQS29048850NTC20210513075948850UQ152PS202106140010<NA>4885048850URZ202105132425
6UQS2902020-06-141827.83171.64UQS290II-2EMA0002UQS200UQS29048850NTC20210513075948850UQ152PS202106140013<NA>4885048850URZ202105132474
7UQS2102019-10-2312136.29576.68UQS2102EMA0002UQS200UQS21048850NTC20191017064248850UQ152PS200801240002<NA>4885048850URZ201910172078
8UQS7202013-11-1128364.731092.74UQS7203EMA0002UQS700UQS72048850NTC20120209100048850UQ152PS201202090017<NA>4885048850URZ201202091021
9UQS2102019-10-232464.97302.56UQS2101EMA0002UQS200UQS21048850NTC20191017064248850UQ152PS200801240003<NA>4885048850URZ201910172077
도형 속성코드현황도형 생성일시면적_도형길이_도형라벨명도면번호집행상태코드 심볼도형 대분류코드도형 중분류코드결정고시관리코드현황도형 관리번호도형 소분류코드시군구코드도형조서관리 코드
46UQS2902021-12-032788.37285.63UQS2903EMA0002UQS200UQS29048850NTC20211125079548850UQ152PS202112030001<NA>4885048850URZ202111252578
47UQS2102017-10-1910260.71440.6UQS2101EMA0002UQS200UQS21048850NTC20051124005248850UQ152PS201808010052<NA>4885048850URZ200511240577
48UQS2902017-05-211863.25234.12UQS29014EMA0002UQS200UQS29048850NTC20170406202248850UQ152PS201704060053<NA>4885048850URZ201704062136
49UQS2102019-10-232087.42261.47UQS2103EMA0002UQS200UQS21048850NTC20150212042148850UQ152PS200511240005<NA>4885048850URZ201502129009
50UQS2902013-11-111251.77454.32UQS290AEMA0002UQS200UQS29048850NTC20101125200448850UQ152PS201011250001<NA>4885048850URZ201011253031
51UQS5102023-05-12833.841579.34UQS5103-2EMA0001UQS500UQS51048850NTC20220517082648850UQ152PS202305120001<NA>4885048850URZ202205172613
52UQS5102023-05-12184000.3621334.26UQS5102EMA0001UQS500UQS51048850NTC20220517082648850UQ152PS202305120002<NA>4885048850URZ202205172612
53UQS2902020-06-141407.98155.59UQS2904EMA0002UQS200UQS29048850NTC20210513075948850UQ152PS202106140015<NA>4885048850URZ202105132362
54UQS2902013-11-11525.94100.45UQS2902EMA0002UQS200UQS29048850NTC20110630201048850UQ152PS201106300026<NA>4885048850URZ201106303384
55UQS2102020-06-14849.82113.06UQS210AEMA0002UQS200UQS21048850NTC20210513076048850UQ152PS202106140014<NA>4885048850URZ202105130029