Overview

Dataset statistics

Number of variables8
Number of observations325
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.4 KiB
Average record size in memory67.4 B

Variable types

Text1
Categorical5
Numeric2

Dataset

Description경기도 광주시 도시계획정보시스템의 도시지역 현황에 관한 데이터로 라벨명, 면적(도형), 길이(도형), 시군구 등에 대한 항목을 제공합니다.
Author경기도 광주시
URLhttps://www.data.go.kr/data/15123163/fileData.do

Alerts

시군구코드 has constant value ""Constant
시군구 has constant value ""Constant
도형 대분류코드 is highly overall correlated with 라벨명High correlation
라벨명 is highly overall correlated with 도형 대분류코드High correlation
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 (50.9%)Imbalance
현황도형 생성일시 is highly imbalanced (50.3%)Imbalance

Reproduction

Analysis started2023-12-11 22:51:16.870582
Analysis finished2023-12-11 22:51:17.743792
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

현황도형 관리번호
Text

Distinct314
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-12T07:51:17.904769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters7800
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

Unique305 ?
Unique (%)93.8%

Sample

1st row41610UQ111PS201904120010
2nd row41610UQ111PS201904120011
3rd row41610UQ111PS201904120012
4th row41610UQ111PS201904120013
5th row41610UQ111PS201904120014
ValueCountFrequency (%)
41610uq111ps201904120011 4
 
1.2%
41610uq111ps202112270319 2
 
0.6%
41610uq111ps202112270318 2
 
0.6%
41610uq111ps201910310422 2
 
0.6%
41610uq111ps202112270320 2
 
0.6%
41610uq111ps201904120123 2
 
0.6%
41610uq111ps201904120150 2
 
0.6%
41610uq111ps201904120078 2
 
0.6%
41610uq111ps202012310304 2
 
0.6%
41610uq111ps201904120182 1
 
0.3%
Other values (304) 304
93.5%
2023-12-12T07:51:18.255809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2497
32.0%
0 1473
18.9%
2 716
 
9.2%
4 656
 
8.4%
6 398
 
5.1%
9 349
 
4.5%
U 325
 
4.2%
Q 325
 
4.2%
P 325
 
4.2%
S 325
 
4.2%
Other values (4) 411
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6500
83.3%
Uppercase Letter 1300
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2497
38.4%
0 1473
22.7%
2 716
 
11.0%
4 656
 
10.1%
6 398
 
6.1%
9 349
 
5.4%
3 195
 
3.0%
7 87
 
1.3%
5 66
 
1.0%
8 63
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
U 325
25.0%
Q 325
25.0%
P 325
25.0%
S 325
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6500
83.3%
Latin 1300
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2497
38.4%
0 1473
22.7%
2 716
 
11.0%
4 656
 
10.1%
6 398
 
6.1%
9 349
 
5.4%
3 195
 
3.0%
7 87
 
1.3%
5 66
 
1.0%
8 63
 
1.0%
Latin
ValueCountFrequency (%)
U 325
25.0%
Q 325
25.0%
P 325
25.0%
S 325
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2497
32.0%
0 1473
18.9%
2 716
 
9.2%
4 656
 
8.4%
6 398
 
5.1%
9 349
 
4.5%
U 325
 
4.2%
Q 325
 
4.2%
P 325
 
4.2%
S 325
 
4.2%
Other values (4) 411
 
5.3%

도형 대분류코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
UQA100
223 
UQA400
87 
UQA200
 
10
UQA300
 
4
UQA500
 
1

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st rowUQA100
2nd rowUQA100
3rd rowUQA400
4th rowUQA400
5th rowUQA100

Common Values

ValueCountFrequency (%)
UQA100 223
68.6%
UQA400 87
 
26.8%
UQA200 10
 
3.1%
UQA300 4
 
1.2%
UQA500 1
 
0.3%

Length

2023-12-12T07:51:18.392815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:51:18.492275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqa100 223
68.6%
uqa400 87
 
26.8%
uqa200 10
 
3.1%
uqa300 4
 
1.2%
uqa500 1
 
0.3%

라벨명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
제1종일반주거지역
126 
자연녹지지역
59 
제2종일반주거지역
47 
준주거지역
32 
제3종일반주거지역
16 
Other values (7)
45 

Length

Max length14
Median length9
Mean length7.7323077
Min length5

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row제1종일반주거지역
2nd row제2종일반주거지역
3rd row보전녹지지역
4th row보전녹지지역
5th row준주거지역

Common Values

ValueCountFrequency (%)
제1종일반주거지역 126
38.8%
자연녹지지역 59
18.2%
제2종일반주거지역 47
 
14.5%
준주거지역 32
 
9.8%
제3종일반주거지역 16
 
4.9%
보전녹지지역 14
 
4.3%
생산녹지지역 13
 
4.0%
일반상업지역 9
 
2.8%
일반공업지역 4
 
1.2%
광주역세권 지구단위계획구역 3
 
0.9%
Other values (2) 2
 
0.6%

Length

2023-12-12T07:51:18.609521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제1종일반주거지역 126
38.3%
자연녹지지역 59
17.9%
제2종일반주거지역 47
 
14.3%
준주거지역 32
 
9.7%
제3종일반주거지역 16
 
4.9%
보전녹지지역 14
 
4.3%
생산녹지지역 13
 
4.0%
일반상업지역 9
 
2.7%
일반공업지역 4
 
1.2%
광주역세권 3
 
0.9%
Other values (4) 6
 
1.8%

면적(도형)
Real number (ℝ)

HIGH CORRELATION 

Distinct321
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean464609.78
Minimum0
Maximum1.1704653 × 108
Zeros3
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-12T07:51:18.787045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile58.972
Q18633.32
median33561.91
Q389687.88
95-th percentile390503.14
Maximum1.1704653 × 108
Range1.1704653 × 108
Interquartile range (IQR)81054.56

Descriptive statistics

Standard deviation6491425.4
Coefficient of variation (CV)13.97178
Kurtosis324.05814
Mean464609.78
Median Absolute Deviation (MAD)31983.56
Skewness17.988982
Sum1.5099818 × 108
Variance4.2138603 × 1013
MonotonicityNot monotonic
2023-12-12T07:51:18.955423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 3
 
0.9%
45.56 2
 
0.6%
85.29 2
 
0.6%
27913.76 1
 
0.3%
460454.79 1
 
0.3%
40882.72 1
 
0.3%
1518.4 1
 
0.3%
1240.78 1
 
0.3%
786.66 1
 
0.3%
86986.41 1
 
0.3%
Other values (311) 311
95.7%
ValueCountFrequency (%)
0.0 3
0.9%
0.02 1
 
0.3%
0.03 1
 
0.3%
0.05 1
 
0.3%
0.12 1
 
0.3%
0.13 1
 
0.3%
3.2 1
 
0.3%
5.96 1
 
0.3%
19.43 1
 
0.3%
23.41 1
 
0.3%
ValueCountFrequency (%)
117046526.61 1
0.3%
2193347.33 1
0.3%
1975825.46 1
0.3%
1967483.6 1
0.3%
1176981.99 1
0.3%
1173653.47 1
0.3%
862788.17 1
0.3%
829562.08 1
0.3%
752028.57 1
0.3%
747041.78 1
0.3%

길이(도형)
Real number (ℝ)

HIGH CORRELATION 

Distinct323
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2342.3013
Minimum0.62
Maximum224844.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-12T07:51:19.114516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.62
5-th percentile41.82
Q1468.1
median1025.43
Q31882.42
95-th percentile5430.862
Maximum224844.65
Range224844.03
Interquartile range (IQR)1414.32

Descriptive statistics

Standard deviation12654.379
Coefficient of variation (CV)5.4025411
Kurtosis297.61411
Mean2342.3013
Median Absolute Deviation (MAD)651.3
Skewness16.935861
Sum761247.91
Variance1.601333 × 108
MonotonicityNot monotonic
2023-12-12T07:51:19.503887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.04 2
 
0.6%
41.82 2
 
0.6%
3885.34 1
 
0.3%
868.2 1
 
0.3%
5437.82 1
 
0.3%
1219.31 1
 
0.3%
309.88 1
 
0.3%
166.62 1
 
0.3%
196.19 1
 
0.3%
1654.41 1
 
0.3%
Other values (313) 313
96.3%
ValueCountFrequency (%)
0.62 1
0.3%
2.8 1
0.3%
8.47 1
0.3%
9.7 1
0.3%
11.05 1
0.3%
27.5 1
0.3%
29.47 1
0.3%
30.04 2
0.6%
31.07 1
0.3%
32.87 1
0.3%
ValueCountFrequency (%)
224844.65 1
0.3%
33302.54 1
0.3%
15566.48 1
0.3%
14761.25 1
0.3%
14269.93 1
0.3%
8455.34 1
0.3%
7278.6 1
0.3%
6391.51 1
0.3%
6375.31 1
0.3%
6335.91 1
0.3%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
41610
325 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41610
2nd row41610
3rd row41610
4th row41610
5th row41610

Common Values

ValueCountFrequency (%)
41610 325
100.0%

Length

2023-12-12T07:51:19.632146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:51:19.737558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41610 325
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
광주시
325 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
광주시 325
100.0%

Length

2023-12-12T07:51:19.840648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:51:19.944314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
광주시 325
100.0%

현황도형 생성일시
Categorical

IMBALANCE 

Distinct25
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2019-04-12
187 
2019-06-21
67 
2022-12-19
 
11
2023-06-02
 
7
2022-08-17
 
6
Other values (20)
47 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique9 ?
Unique (%)2.8%

Sample

1st row2019-04-12
2nd row2021-12-31
3rd row2019-04-12
4th row2019-04-12
5th row2019-04-12

Common Values

ValueCountFrequency (%)
2019-04-12 187
57.5%
2019-06-21 67
 
20.6%
2022-12-19 11
 
3.4%
2023-06-02 7
 
2.2%
2022-08-17 6
 
1.8%
2020-04-17 5
 
1.5%
2020-12-31 5
 
1.5%
2019-10-02 5
 
1.5%
2023-04-27 4
 
1.2%
2021-12-31 4
 
1.2%
Other values (15) 24
 
7.4%

Length

2023-12-12T07:51:20.030377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-04-12 187
57.5%
2019-06-21 67
 
20.6%
2022-12-19 11
 
3.4%
2023-06-02 7
 
2.2%
2022-08-17 6
 
1.8%
2020-04-17 5
 
1.5%
2020-12-31 5
 
1.5%
2019-10-02 5
 
1.5%
2023-04-27 4
 
1.2%
2021-12-31 4
 
1.2%
Other values (15) 24
 
7.4%

Interactions

2023-12-12T07:51:17.373262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:17.156596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:17.462877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:51:17.274276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:51:20.099862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도형 대분류코드라벨명면적(도형)길이(도형)현황도형 생성일시
도형 대분류코드1.0000.9960.0000.0000.327
라벨명0.9961.0000.0000.0000.689
면적(도형)0.0000.0001.0001.0000.310
길이(도형)0.0000.0001.0001.0000.000
현황도형 생성일시0.3270.6890.3100.0001.000
2023-12-12T07:51:20.186876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
현황도형 생성일시도형 대분류코드라벨명
현황도형 생성일시1.0000.1420.299
도형 대분류코드0.1421.0000.988
라벨명0.2990.9881.000
2023-12-12T07:51:20.306163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(도형)길이(도형)도형 대분류코드라벨명현황도형 생성일시
면적(도형)1.0000.9500.0000.0000.258
길이(도형)0.9501.0000.0000.0000.000
도형 대분류코드0.0000.0001.0000.9880.142
라벨명0.0000.0000.9881.0000.299
현황도형 생성일시0.2580.0000.1420.2991.000

Missing values

2023-12-12T07:51:17.562844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:51:17.687473image/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 관리번호도형 대분류코드라벨명면적(도형)길이(도형)시군구코드시군구현황도형 생성일시
041610UQ111PS201904120010UQA100제1종일반주거지역47720.691741.4841610광주시2019-04-12
141610UQ111PS201904120011UQA100제2종일반주거지역112851.591761.6841610광주시2021-12-31
241610UQ111PS201904120012UQA400보전녹지지역473644.443570.9241610광주시2019-04-12
341610UQ111PS201904120013UQA400보전녹지지역218995.252948.941610광주시2019-04-12
441610UQ111PS201904120014UQA100준주거지역24938.55699.0541610광주시2019-04-12
541610UQ111PS201904120016UQA400자연녹지지역1667.27353.4841610광주시2019-04-12
641610UQ111PS201904120017UQA100준주거지역1722.63219.0941610광주시2019-04-12
741610UQ111PS201904120018UQA100제1종일반주거지역40962.41032.9141610광주시2019-04-12
841610UQ111PS201904120019UQA400보전녹지지역229830.332313.8841610광주시2019-04-12
941610UQ111PS201904120020UQA400자연녹지지역16574.04801.2241610광주시2019-04-12
현황도형 관리번호도형 대분류코드라벨명면적(도형)길이(도형)시군구코드시군구현황도형 생성일시
31541610UQ111PS201910310486UQA100제1종일반주거지역30866.981058.9441610광주시2019-06-21
31641610UQ111PS201910310436UQA100제1종일반주거지역60.956.3241610광주시2020-02-26
31741610UQ111PS202007170298UQA100제2종일반주거지역100074.922249.1841610광주시2022-08-17
31841610UQ111PS201901100235UQA400자연녹지지역44357.712015.2841610광주시2022-08-17
31941610UQ111PS201901100243UQA200일반상업지역13908.0474.1641610광주시2022-08-17
32041610UQ111PS201901100240UQA100준주거지역8633.32384.741610광주시2022-08-17
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