Overview

Dataset statistics

Number of variables7
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory63.3 B

Variable types

Numeric3
Text2
Categorical2

Dataset

Description경상남도 김해시의 지적재조사 사업 현황에 대한 데이터로 사업시작년도, 지구명, 지구위치, 필지수, 면적 등의 항목으로 구성되어 있습니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15105407

Alerts

사업개시일 is highly overall correlated with 사업시작년도 and 1 other fieldsHigh correlation
사업완료일 is highly overall correlated with 사업시작년도 and 1 other fieldsHigh correlation
사업시작년도 is highly overall correlated with 사업개시일 and 1 other fieldsHigh correlation
필지수 is highly overall correlated with 면적(제곱미터)High correlation
면적(제곱미터) is highly overall correlated with 필지수High correlation
지구명 has unique valuesUnique
지구위치 has unique valuesUnique
필지수 has unique valuesUnique
면적(제곱미터) has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:18:31.854212
Analysis finished2023-12-10 23:18:33.191312
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업시작년도
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.4839
Minimum2013
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T08:18:33.252898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2013
Q12016
median2020
Q32021
95-th percentile2022
Maximum2022
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.1923969
Coefficient of variation (CV)0.0015815816
Kurtosis-1.052471
Mean2018.4839
Median Absolute Deviation (MAD)2
Skewness-0.64433759
Sum62573
Variance10.191398
MonotonicityIncreasing
2023-12-11T08:18:33.352227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2021 7
22.6%
2022 5
16.1%
2013 4
12.9%
2020 4
12.9%
2018 3
9.7%
2014 2
 
6.5%
2015 2
 
6.5%
2017 2
 
6.5%
2019 2
 
6.5%
ValueCountFrequency (%)
2013 4
12.9%
2014 2
 
6.5%
2015 2
 
6.5%
2017 2
 
6.5%
2018 3
9.7%
2019 2
 
6.5%
2020 4
12.9%
2021 7
22.6%
2022 5
16.1%
ValueCountFrequency (%)
2022 5
16.1%
2021 7
22.6%
2020 4
12.9%
2019 2
 
6.5%
2018 3
9.7%
2017 2
 
6.5%
2015 2
 
6.5%
2014 2
 
6.5%
2013 4
12.9%

지구명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T08:18:33.535917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7.5483871
Min length7

Characters and Unicode

Total characters234
Distinct characters49
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row생림 봉림지구
2nd row한림 신천지구
3rd row진영 본산1지구
4th row진영 본산2지구
5th row진례 신안지구
ValueCountFrequency (%)
진영 11
17.7%
한림 10
 
16.1%
진례 7
 
11.3%
대동 2
 
3.2%
생림 1
 
1.6%
장원2지구 1
 
1.6%
금봉지구 1
 
1.6%
가산지구 1
 
1.6%
하촌지구 1
 
1.6%
하평지구 1
 
1.6%
Other values (26) 26
41.9%
2023-12-11T08:18:33.888438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 33
14.1%
31
13.2%
지 31
13.2%
진 19
 
8.1%
림 12
 
5.1%
영 11
 
4.7%
한 10
 
4.3%
례 7
 
3.0%
2 7
 
3.0%
1 6
 
2.6%
Other values (39) 67
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 189
80.8%
Space Separator 31
 
13.2%
Decimal Number 14
 
6.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 33
17.5%
지 31
16.4%
진 19
 
10.1%
림 12
 
6.3%
영 11
 
5.8%
한 10
 
5.3%
례 7
 
3.7%
산 5
 
2.6%
신 4
 
2.1%
동 4
 
2.1%
Other values (35) 53
28.0%
Decimal Number
ValueCountFrequency (%)
2 7
50.0%
1 6
42.9%
3 1
 
7.1%
Space Separator
ValueCountFrequency (%)
31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 189
80.8%
Common 45
 
19.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 33
17.5%
지 31
16.4%
진 19
 
10.1%
림 12
 
6.3%
영 11
 
5.8%
한 10
 
5.3%
례 7
 
3.7%
산 5
 
2.6%
신 4
 
2.1%
동 4
 
2.1%
Other values (35) 53
28.0%
Common
ValueCountFrequency (%)
31
68.9%
2 7
 
15.6%
1 6
 
13.3%
3 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 189
80.8%
ASCII 45
 
19.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 33
17.5%
지 31
16.4%
진 19
 
10.1%
림 12
 
6.3%
영 11
 
5.8%
한 10
 
5.3%
례 7
 
3.7%
산 5
 
2.6%
신 4
 
2.1%
동 4
 
2.1%
Other values (35) 53
28.0%
ASCII
ValueCountFrequency (%)
31
68.9%
2 7
 
15.6%
1 6
 
13.3%
3 1
 
2.2%

지구위치
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T08:18:34.097540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length26.064516
Min length24

Characters and Unicode

Total characters808
Distinct characters56
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 생림면 봉림리 417번지 일원
2nd row경상남도 김해시 한림면 신천리 120번지 일원
3rd row경상남도 김해시 진영읍 본산리 745번지 일원
4th row경상남도 김해시 진영읍 진영리 48-2번지 일원
5th row경상남도 김해시 진례면 신안리 262-1번지 일원
ValueCountFrequency (%)
경상남도 31
16.7%
김해시 31
16.7%
일원 31
16.7%
진영읍 11
 
5.9%
한림면 10
 
5.4%
진례면 7
 
3.8%
진영리 5
 
2.7%
용덕리 3
 
1.6%
신천리 3
 
1.6%
대동면 2
 
1.1%
Other values (48) 52
28.0%
2023-12-11T08:18:34.480961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
155
19.2%
시 33
 
4.1%
경 31
 
3.8%
지 31
 
3.8%
번 31
 
3.8%
리 31
 
3.8%
원 31
 
3.8%
상 31
 
3.8%
해 31
 
3.8%
김 31
 
3.8%
Other values (46) 372
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 527
65.2%
Space Separator 155
 
19.2%
Decimal Number 106
 
13.1%
Dash Punctuation 20
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 33
 
6.3%
경 31
 
5.9%
지 31
 
5.9%
번 31
 
5.9%
리 31
 
5.9%
원 31
 
5.9%
상 31
 
5.9%
해 31
 
5.9%
김 31
 
5.9%
도 31
 
5.9%
Other values (34) 215
40.8%
Decimal Number
ValueCountFrequency (%)
2 19
17.9%
1 17
16.0%
3 13
12.3%
4 11
10.4%
6 10
9.4%
7 10
9.4%
8 7
 
6.6%
5 7
 
6.6%
0 6
 
5.7%
9 6
 
5.7%
Space Separator
ValueCountFrequency (%)
155
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 527
65.2%
Common 281
34.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 33
 
6.3%
경 31
 
5.9%
지 31
 
5.9%
번 31
 
5.9%
리 31
 
5.9%
원 31
 
5.9%
상 31
 
5.9%
해 31
 
5.9%
김 31
 
5.9%
도 31
 
5.9%
Other values (34) 215
40.8%
Common
ValueCountFrequency (%)
155
55.2%
- 20
 
7.1%
2 19
 
6.8%
1 17
 
6.0%
3 13
 
4.6%
4 11
 
3.9%
6 10
 
3.6%
7 10
 
3.6%
8 7
 
2.5%
5 7
 
2.5%
Other values (2) 12
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 527
65.2%
ASCII 281
34.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
155
55.2%
- 20
 
7.1%
2 19
 
6.8%
1 17
 
6.0%
3 13
 
4.6%
4 11
 
3.9%
6 10
 
3.6%
7 10
 
3.6%
8 7
 
2.5%
5 7
 
2.5%
Other values (2) 12
 
4.3%
Hangul
ValueCountFrequency (%)
시 33
 
6.3%
경 31
 
5.9%
지 31
 
5.9%
번 31
 
5.9%
리 31
 
5.9%
원 31
 
5.9%
상 31
 
5.9%
해 31
 
5.9%
김 31
 
5.9%
도 31
 
5.9%
Other values (34) 215
40.8%

필지수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean157.45161
Minimum44
Maximum314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T08:18:34.636879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum44
5-th percentile53
Q1103
median156
Q3204.5
95-th percentile282
Maximum314
Range270
Interquartile range (IQR)101.5

Descriptive statistics

Standard deviation74.845102
Coefficient of variation (CV)0.47535303
Kurtosis-0.72122457
Mean157.45161
Median Absolute Deviation (MAD)54
Skewness0.29531265
Sum4881
Variance5601.7892
MonotonicityNot monotonic
2023-12-11T08:18:34.781826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
260 1
 
3.2%
121 1
 
3.2%
131 1
 
3.2%
199 1
 
3.2%
164 1
 
3.2%
172 1
 
3.2%
228 1
 
3.2%
189 1
 
3.2%
119 1
 
3.2%
65 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
44 1
3.2%
47 1
3.2%
59 1
3.2%
64 1
3.2%
65 1
3.2%
72 1
3.2%
78 1
3.2%
91 1
3.2%
115 1
3.2%
119 1
3.2%
ValueCountFrequency (%)
314 1
3.2%
286 1
3.2%
278 1
3.2%
260 1
3.2%
252 1
3.2%
228 1
3.2%
218 1
3.2%
210 1
3.2%
199 1
3.2%
193 1
3.2%

면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61536.71
Minimum9207
Maximum159113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-11T08:18:34.903912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9207
5-th percentile13924.5
Q136659.5
median54457
Q376936.5
95-th percentile133902.5
Maximum159113
Range149906
Interquartile range (IQR)40277

Descriptive statistics

Standard deviation38330.542
Coefficient of variation (CV)0.62288904
Kurtosis0.88296239
Mean61536.71
Median Absolute Deviation (MAD)18835
Skewness1.0092976
Sum1907638
Variance1.4692305 × 109
MonotonicityNot monotonic
2023-12-11T08:18:35.041177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
83753 1
 
3.2%
60408 1
 
3.2%
52089 1
 
3.2%
67359 1
 
3.2%
37697 1
 
3.2%
104853 1
 
3.2%
108963 1
 
3.2%
54457 1
 
3.2%
29020 1
 
3.2%
26969 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
9207 1
3.2%
12975 1
3.2%
14874 1
3.2%
19596 1
3.2%
22502 1
3.2%
26969 1
3.2%
29020 1
3.2%
35622 1
3.2%
37697 1
3.2%
40230 1
3.2%
ValueCountFrequency (%)
159113 1
3.2%
158842 1
3.2%
108963 1
3.2%
104853 1
3.2%
102097 1
3.2%
99819 1
3.2%
98910 1
3.2%
83753 1
3.2%
70120 1
3.2%
68292 1
3.2%

사업개시일
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2021-03-18
7 
2022-03-14
5 
2013-12-19
4 
2020-04-02
4 
2018-01-04
3 
Other values (4)
8 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2013-12-19
2nd row2013-12-19
3rd row2013-12-19
4th row2013-12-19
5th row2014-05-13

Common Values

ValueCountFrequency (%)
2021-03-18 7
22.6%
2022-03-14 5
16.1%
2013-12-19 4
12.9%
2020-04-02 4
12.9%
2018-01-04 3
9.7%
2014-05-13 2
 
6.5%
2014-12-29 2
 
6.5%
2016-12-28 2
 
6.5%
2018-08-01 2
 
6.5%

Length

2023-12-11T08:18:35.174107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:18:35.282696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-03-18 7
22.6%
2022-03-14 5
16.1%
2013-12-19 4
12.9%
2020-04-02 4
12.9%
2018-01-04 3
9.7%
2014-05-13 2
 
6.5%
2014-12-29 2
 
6.5%
2016-12-28 2
 
6.5%
2018-08-01 2
 
6.5%

사업완료일
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2022-06-09
7 
<NA>
5 
2014-12-29
4 
2021-06-15
4 
2019-07-30
3 
Other values (4)
8 

Length

Max length10
Median length10
Mean length9.0322581
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2014-12-29
2nd row2014-12-29
3rd row2014-12-29
4th row2014-12-29
5th row2015-12-31

Common Values

ValueCountFrequency (%)
2022-06-09 7
22.6%
<NA> 5
16.1%
2014-12-29 4
12.9%
2021-06-15 4
12.9%
2019-07-30 3
9.7%
2015-12-31 2
 
6.5%
2016-07-12 2
 
6.5%
2018-07-02 2
 
6.5%
2020-12-31 2
 
6.5%

Length

2023-12-11T08:18:35.421904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:18:35.540198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-06-09 7
22.6%
na 5
16.1%
2014-12-29 4
12.9%
2021-06-15 4
12.9%
2019-07-30 3
9.7%
2015-12-31 2
 
6.5%
2016-07-12 2
 
6.5%
2018-07-02 2
 
6.5%
2020-12-31 2
 
6.5%

Interactions

2023-12-11T08:18:32.711488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:18:32.170589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:18:32.447375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:18:32.798709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:18:32.241091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:18:32.530392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:18:32.878950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:18:32.347359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:18:32.627250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:18:35.628875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업시작년도지구명지구위치필지수면적(제곱미터)사업개시일사업완료일
사업시작년도1.0001.0001.0000.4700.0001.0001.000
지구명1.0001.0001.0001.0001.0001.0001.000
지구위치1.0001.0001.0001.0001.0001.0001.000
필지수0.4701.0001.0001.0000.5050.3040.304
면적(제곱미터)0.0001.0001.0000.5051.0000.0000.000
사업개시일1.0001.0001.0000.3040.0001.0001.000
사업완료일1.0001.0001.0000.3040.0001.0001.000
2023-12-11T08:18:35.727968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업개시일사업완료일
사업개시일1.0001.000
사업완료일1.0001.000
2023-12-11T08:18:35.797307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업시작년도필지수면적(제곱미터)사업개시일사업완료일
사업시작년도1.0000.1080.2601.0001.000
필지수0.1081.0000.8160.0810.035
면적(제곱미터)0.2600.8161.0000.0000.000
사업개시일1.0000.0810.0001.0001.000
사업완료일1.0000.0350.0001.0001.000

Missing values

2023-12-11T08:18:33.023366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:18:33.152651image/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

사업시작년도지구명지구위치필지수면적(제곱미터)사업개시일사업완료일
02013생림 봉림지구경상남도 김해시 생림면 봉림리 417번지 일원260837532013-12-192014-12-29
12013한림 신천지구경상남도 김해시 한림면 신천리 120번지 일원121604082013-12-192014-12-29
22013진영 본산1지구경상남도 김해시 진영읍 본산리 745번지 일원64403072013-12-192014-12-29
32013진영 본산2지구경상남도 김해시 진영읍 진영리 48-2번지 일원218477402013-12-192014-12-29
42014진례 신안지구경상남도 김해시 진례면 신안리 262-1번지 일원78225022014-05-132015-12-31
52014진영 중구2지구경상남도 김해시 진영읍 진영리 202-1번지 일원7292072014-05-132015-12-31
62015진영 좌곤지구경상남도 김해시 진영읍 좌곤리 172번지 일원156483642014-12-292016-07-12
72015진례 초전지구경상남도 김해시 진례면 초전리 703번지 일원252682922014-12-292016-07-12
82017한림 가동지구경상남도 김해시 한림면 가동리 67-1번지 일원286998192016-12-282018-07-02
92017진영 부곡1지구경상남도 김해시 진영읍 진영리 446번지 일원173626012016-12-282018-07-02
사업시작년도지구명지구위치필지수면적(제곱미터)사업개시일사업완료일
212021진례 하평지구경상남도 김해시 진례면 담안리 253-1번지 일원169989102021-03-182022-06-09
222021한림 장원1지구경상남도 김해시 한림면 용덕리 38-2번지 일원91402302021-03-182022-06-09
232021한림 장원2지구경상남도 김해시 한림면 용덕리 324-3번지 일원65269692021-03-182022-06-09
242021진영 서구2지구경상남도 김해시 진영읍 진영리 118번지 일원119290202021-03-182022-06-09
252021진영 용전지구경상남도 김해시 진영읍 신용리 473-5번지 일원189544572021-03-182022-06-09
262022한림 금곡지구경상남도 김해시 한림면 금곡리 750번지 일원2281089632022-03-14<NA>
272022진례 송정1지구경상남도 김해시 진례면 송정리 208-1번지 일원1721048532022-03-14<NA>
282022진례 송정2지구경상남도 김해시 진례면 송정리 105-2번지 일원164376972022-03-14<NA>
292022대동 괴정123지구경상남도 김해시 대동면 괴정리 68번지 일원199673592022-03-14<NA>
302022대동 덕산지구경상남도 김해시 대동면 덕산리 287-2번지 일원131520892022-03-14<NA>