Overview

Dataset statistics

Number of variables5
Number of observations50
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory44.6 B

Variable types

Numeric2
Text2
DateTime1

Dataset

Description전북특별자치도 토석채취현황 데이터 제공입니다. 소재지, 지번, 수량(1000㎥), 허가일 등의 정보를 포함하고 있습니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055651/fileData.do

Alerts

일련 번호 has unique valuesUnique
지번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 14:42:09.663181
Analysis finished2024-03-14 14:42:11.667701
Duration2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련 번호
Real number (ℝ)

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.5
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size578.0 B
2024-03-14T23:42:11.887117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.45
Q113.25
median25.5
Q337.75
95-th percentile47.55
Maximum50
Range49
Interquartile range (IQR)24.5

Descriptive statistics

Standard deviation14.57738
Coefficient of variation (CV)0.57166195
Kurtosis-1.2
Mean25.5
Median Absolute Deviation (MAD)12.5
Skewness0
Sum1275
Variance212.5
MonotonicityStrictly increasing
2024-03-14T23:42:12.330297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
2.0%
39 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
36 1
 
2.0%
Other values (40) 40
80.0%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
50 1
2.0%
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%

소재지
Text

Distinct36
Distinct (%)72.0%
Missing0
Missing (%)0.0%
Memory size528.0 B
2024-03-14T23:42:13.415429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.98
Min length7

Characters and Unicode

Total characters549
Distinct characters80
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)54.0%

Sample

1st row고창군 무장면 교흥리
2nd row고창군 무장면 교흥리
3rd row고창군 성송면 계당리
4th row고창군 성송면 암치리
5th row고창군 부안면 검산리
ValueCountFrequency (%)
남원시 11
 
7.4%
익산시 9
 
6.0%
낭산면 7
 
4.7%
고창군 6
 
4.0%
낭산리 6
 
4.0%
정읍시 5
 
3.4%
완주군 5
 
3.4%
군산시 3
 
2.0%
부안군 3
 
2.0%
순창군 3
 
2.0%
Other values (65) 91
61.1%
2024-03-14T23:42:14.541030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
102
18.6%
리 49
 
8.9%
면 46
 
8.4%
산 43
 
7.8%
시 28
 
5.1%
군 25
 
4.6%
낭 13
 
2.4%
동 13
 
2.4%
남 13
 
2.4%
창 12
 
2.2%
Other values (70) 205
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 447
81.4%
Space Separator 102
 
18.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 49
 
11.0%
면 46
 
10.3%
산 43
 
9.6%
시 28
 
6.3%
군 25
 
5.6%
낭 13
 
2.9%
동 13
 
2.9%
남 13
 
2.9%
창 12
 
2.7%
원 11
 
2.5%
Other values (69) 194
43.4%
Space Separator
ValueCountFrequency (%)
102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 447
81.4%
Common 102
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 49
 
11.0%
면 46
 
10.3%
산 43
 
9.6%
시 28
 
6.3%
군 25
 
5.6%
낭 13
 
2.9%
동 13
 
2.9%
남 13
 
2.9%
창 12
 
2.7%
원 11
 
2.5%
Other values (69) 194
43.4%
Common
ValueCountFrequency (%)
102
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 447
81.4%
ASCII 102
 
18.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
102
100.0%
Hangul
ValueCountFrequency (%)
리 49
 
11.0%
면 46
 
10.3%
산 43
 
9.6%
시 28
 
6.3%
군 25
 
5.6%
낭 13
 
2.9%
동 13
 
2.9%
남 13
 
2.9%
창 12
 
2.7%
원 11
 
2.5%
Other values (69) 194
43.4%

지번
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size528.0 B
2024-03-14T23:42:15.337449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length8.36
Min length3

Characters and Unicode

Total characters418
Distinct characters17
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

Unique50 ?
Unique (%)100.0%

Sample

1st row산29외 2필지
2nd row산30외 2필지
3rd row산36외 9필지
4th row산81외 5필지
5th row산74외 3필지
ValueCountFrequency (%)
외 11
 
11.2%
2필지 4
 
4.1%
1필 4
 
4.1%
4필 4
 
4.1%
4필지 3
 
3.1%
11필지 2
 
2.0%
6필지 2
 
2.0%
7필 2
 
2.0%
6필 2
 
2.0%
1필지 2
 
2.0%
Other values (60) 62
63.3%
2024-03-14T23:42:16.339852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 56
13.4%
50
12.0%
산 46
11.0%
필 43
10.3%
외 41
9.8%
- 24
 
5.7%
5 22
 
5.3%
2 22
 
5.3%
3 22
 
5.3%
지 21
 
5.0%
Other values (7) 71
17.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 191
45.7%
Other Letter 153
36.6%
Space Separator 50
 
12.0%
Dash Punctuation 24
 
5.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 56
29.3%
5 22
 
11.5%
2 22
 
11.5%
3 22
 
11.5%
4 17
 
8.9%
6 16
 
8.4%
7 14
 
7.3%
9 8
 
4.2%
0 8
 
4.2%
8 6
 
3.1%
Other Letter
ValueCountFrequency (%)
산 46
30.1%
필 43
28.1%
외 41
26.8%
지 21
13.7%
번 2
 
1.3%
Space Separator
ValueCountFrequency (%)
50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 265
63.4%
Hangul 153
36.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 56
21.1%
50
18.9%
- 24
9.1%
5 22
 
8.3%
2 22
 
8.3%
3 22
 
8.3%
4 17
 
6.4%
6 16
 
6.0%
7 14
 
5.3%
9 8
 
3.0%
Other values (2) 14
 
5.3%
Hangul
ValueCountFrequency (%)
산 46
30.1%
필 43
28.1%
외 41
26.8%
지 21
13.7%
번 2
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 265
63.4%
Hangul 153
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 56
21.1%
50
18.9%
- 24
9.1%
5 22
 
8.3%
2 22
 
8.3%
3 22
 
8.3%
4 17
 
6.4%
6 16
 
6.0%
7 14
 
5.3%
9 8
 
3.0%
Other values (2) 14
 
5.3%
Hangul
ValueCountFrequency (%)
산 46
30.1%
필 43
28.1%
외 41
26.8%
지 21
13.7%
번 2
 
1.3%

수량(1000제곱미터)
Real number (ℝ)

Distinct49
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1266.42
Minimum2
Maximum5047
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size578.0 B
2024-03-14T23:42:16.583320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile34.75
Q1285.75
median949
Q31665.75
95-th percentile3774.3
Maximum5047
Range5045
Interquartile range (IQR)1380

Descriptive statistics

Standard deviation1231.358
Coefficient of variation (CV)0.97231407
Kurtosis1.5542897
Mean1266.42
Median Absolute Deviation (MAD)713.5
Skewness1.3286691
Sum63321
Variance1516242.5
MonotonicityNot monotonic
2024-03-14T23:42:16.838867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1656 2
 
4.0%
812 1
 
2.0%
941 1
 
2.0%
820 1
 
2.0%
5047 1
 
2.0%
225 1
 
2.0%
69 1
 
2.0%
62 1
 
2.0%
56 1
 
2.0%
2333 1
 
2.0%
Other values (39) 39
78.0%
ValueCountFrequency (%)
2 1
2.0%
9 1
2.0%
28 1
2.0%
43 1
2.0%
56 1
2.0%
62 1
2.0%
69 1
2.0%
128 1
2.0%
173 1
2.0%
181 1
2.0%
ValueCountFrequency (%)
5047 1
2.0%
4677 1
2.0%
4101 1
2.0%
3375 1
2.0%
2882 1
2.0%
2845 1
2.0%
2543 1
2.0%
2450 1
2.0%
2447 1
2.0%
2333 1
2.0%

허가일
Date

Distinct48
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size528.0 B
Minimum2001-07-03 00:00:00
Maximum2020-02-06 00:00:00
2024-03-14T23:42:17.084336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:42:17.415181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)

Interactions

2024-03-14T23:42:10.677903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:42:10.202923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:42:10.915579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:42:10.437755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:42:17.577250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련 번호소재지지번수량(1000제곱미터)허가일
일련 번호1.0000.9791.0000.3391.000
소재지0.9791.0001.0000.0000.994
지번1.0001.0001.0001.0001.000
수량(1000제곱미터)0.3390.0001.0001.0001.000
허가일1.0000.9941.0001.0001.000
2024-03-14T23:42:17.751523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련 번호수량(1000제곱미터)
일련 번호1.000-0.220
수량(1000제곱미터)-0.2201.000

Missing values

2024-03-14T23:42:11.230987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:42:11.545362image/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

일련 번호소재지지번수량(1000제곱미터)허가일
01고창군 무장면 교흥리산29외 2필지8122015-03-09
12고창군 무장면 교흥리산30외 2필지1812016-10-05
23고창군 성송면 계당리산36외 9필지5942014-06-05
34고창군 성송면 암치리산81외 5필지16692012-05-01
45고창군 부안면 검산리산74외 3필지46772013-01-14
56고창군 부안면 선운리산52외 4필지16562014-05-09
67군산시 성산면 성덕리산2-1 외 4필3642019-07-11
78군산시 나포면 나포리산236 외 10필지12042016-01-15
89군산시 옥산면 당북리산21-1 외 73필지33752016-07-25
910남원시 광치동산51-13외 6필지11362018-10-02
일련 번호소재지지번수량(1000제곱미터)허가일
4041진안군 진안읍 구룡리479-492015-08-07
4142진안군 동향면 성산리산12-6 외 1필282019-12-17
4243완주군 소양면 해월리산208-114392011-11-17
4344완주군 고산면 삼기리산1 외 6필432012-01-01
4445완주군 고산면 소향리산1371282012-01-01
4546완주군 고산면 삼기리산13-1 외 6필13072014-06-27
4647완주군 소양면 죽절리196-24102017-12-15
4748순창군 동계면 수정리산11 외 11필지20352012-11-20
4849순창군 동계면 수정리산4번지 외 6필지10972015-10-19
4950순창군 풍산면 죽곡리산50-3번지 외 1필지22019-03-18