Overview

Dataset statistics

Number of variables3
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory27.2 B

Variable types

Numeric1
Text2

Dataset

Description광해가 발생된 지역의 광산명 및 위치(주소) 등 광물찌꺼기 유실방지사업지 위치 정보로, 광물찌꺼기 유실방지사업 위치 정보를 제공함
Author한국광해광업공단
URLhttps://www.data.go.kr/data/15055173/fileData.do

Alerts

구분 has unique valuesUnique
광산명 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:56:42.173923
Analysis finished2023-12-12 00:56:42.593497
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.5
Minimum1
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-12T09:56:42.682897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.95
Q115.75
median30.5
Q345.25
95-th percentile57.05
Maximum60
Range59
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation17.464249
Coefficient of variation (CV)0.57259833
Kurtosis-1.2
Mean30.5
Median Absolute Deviation (MAD)15
Skewness0
Sum1830
Variance305
MonotonicityStrictly increasing
2023-12-12T09:56:42.857889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.7%
32 1
 
1.7%
34 1
 
1.7%
35 1
 
1.7%
36 1
 
1.7%
37 1
 
1.7%
38 1
 
1.7%
39 1
 
1.7%
40 1
 
1.7%
41 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
1 1
1.7%
2 1
1.7%
3 1
1.7%
4 1
1.7%
5 1
1.7%
6 1
1.7%
7 1
1.7%
8 1
1.7%
9 1
1.7%
10 1
1.7%
ValueCountFrequency (%)
60 1
1.7%
59 1
1.7%
58 1
1.7%
57 1
1.7%
56 1
1.7%
55 1
1.7%
54 1
1.7%
53 1
1.7%
52 1
1.7%
51 1
1.7%

광산명
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-12T09:56:43.127148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length2
Mean length3.0666667
Min length2

Characters and Unicode

Total characters184
Distinct characters87
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row금왕(금계)
2nd row여수(팔보)
3rd row삼보
4th row영중
5th row용석
ValueCountFrequency (%)
금왕(금계 1
 
1.6%
산막 1
 
1.6%
풍정 1
 
1.6%
진곡 1
 
1.6%
옥동 1
 
1.6%
금장 1
 
1.6%
달성 1
 
1.6%
고로(석산 1
 
1.6%
금정 1
 
1.6%
토현 1
 
1.6%
Other values (51) 51
83.6%
2023-12-12T09:56:43.637080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 11
 
6.0%
) 11
 
6.0%
동 9
 
4.9%
곡 5
 
2.7%
일 5
 
2.7%
덕 5
 
2.7%
보 5
 
2.7%
구 5
 
2.7%
금 4
 
2.2%
양 4
 
2.2%
Other values (77) 120
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 157
85.3%
Open Punctuation 11
 
6.0%
Close Punctuation 11
 
6.0%
Decimal Number 3
 
1.6%
Space Separator 1
 
0.5%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9
 
5.7%
곡 5
 
3.2%
일 5
 
3.2%
덕 5
 
3.2%
보 5
 
3.2%
구 5
 
3.2%
금 4
 
2.5%
양 4
 
2.5%
지 4
 
2.5%
천 4
 
2.5%
Other values (72) 107
68.2%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Decimal Number
ValueCountFrequency (%)
2 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 157
85.3%
Common 27
 
14.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9
 
5.7%
곡 5
 
3.2%
일 5
 
3.2%
덕 5
 
3.2%
보 5
 
3.2%
구 5
 
3.2%
금 4
 
2.5%
양 4
 
2.5%
지 4
 
2.5%
천 4
 
2.5%
Other values (72) 107
68.2%
Common
ValueCountFrequency (%)
( 11
40.7%
) 11
40.7%
2 3
 
11.1%
1
 
3.7%
, 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 157
85.3%
ASCII 27
 
14.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 11
40.7%
) 11
40.7%
2 3
 
11.1%
1
 
3.7%
, 1
 
3.7%
Hangul
ValueCountFrequency (%)
동 9
 
5.7%
곡 5
 
3.2%
일 5
 
3.2%
덕 5
 
3.2%
보 5
 
3.2%
구 5
 
3.2%
금 4
 
2.5%
양 4
 
2.5%
지 4
 
2.5%
천 4
 
2.5%
Other values (72) 107
68.2%

주소
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2023-12-12T09:56:44.009759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22.5
Mean length18.983333
Min length12

Characters and Unicode

Total characters1139
Distinct characters139
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row경기 양평군 양동면 계정리 881-3
2nd row경기 여주시 금사면 상호리 29-2
3rd row경기 화성시 봉담읍 내리 351-2
4th row경기 포천시 영중면 금주리 126-1
5th row경기 포천시 창수면 운사리27
ValueCountFrequency (%)
경북 16
 
5.3%
강원 11
 
3.7%
경기 6
 
2.0%
봉화군 6
 
2.0%
충남 6
 
2.0%
경남 6
 
2.0%
충북 5
 
1.7%
고성군 4
 
1.3%
전남 4
 
1.3%
정선군 3
 
1.0%
Other values (213) 234
77.7%
2023-12-12T09:56:44.543972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
242
21.2%
리 59
 
5.2%
면 56
 
4.9%
군 45
 
4.0%
1 42
 
3.7%
산 38
 
3.3%
2 30
 
2.6%
경 28
 
2.5%
북 26
 
2.3%
- 26
 
2.3%
Other values (129) 547
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 674
59.2%
Space Separator 242
 
21.2%
Decimal Number 194
 
17.0%
Dash Punctuation 26
 
2.3%
Other Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 59
 
8.8%
면 56
 
8.3%
군 45
 
6.7%
산 38
 
5.6%
경 28
 
4.2%
북 26
 
3.9%
남 19
 
2.8%
시 18
 
2.7%
원 18
 
2.7%
성 16
 
2.4%
Other values (116) 351
52.1%
Decimal Number
ValueCountFrequency (%)
1 42
21.6%
2 30
15.5%
3 22
11.3%
8 19
9.8%
6 16
 
8.2%
5 16
 
8.2%
4 16
 
8.2%
7 13
 
6.7%
9 13
 
6.7%
0 7
 
3.6%
Space Separator
ValueCountFrequency (%)
242
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 674
59.2%
Common 465
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 59
 
8.8%
면 56
 
8.3%
군 45
 
6.7%
산 38
 
5.6%
경 28
 
4.2%
북 26
 
3.9%
남 19
 
2.8%
시 18
 
2.7%
원 18
 
2.7%
성 16
 
2.4%
Other values (116) 351
52.1%
Common
ValueCountFrequency (%)
242
52.0%
1 42
 
9.0%
2 30
 
6.5%
- 26
 
5.6%
3 22
 
4.7%
8 19
 
4.1%
6 16
 
3.4%
5 16
 
3.4%
4 16
 
3.4%
7 13
 
2.8%
Other values (3) 23
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 674
59.2%
ASCII 465
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
242
52.0%
1 42
 
9.0%
2 30
 
6.5%
- 26
 
5.6%
3 22
 
4.7%
8 19
 
4.1%
6 16
 
3.4%
5 16
 
3.4%
4 16
 
3.4%
7 13
 
2.8%
Other values (3) 23
 
4.9%
Hangul
ValueCountFrequency (%)
리 59
 
8.8%
면 56
 
8.3%
군 45
 
6.7%
산 38
 
5.6%
경 28
 
4.2%
북 26
 
3.9%
남 19
 
2.8%
시 18
 
2.7%
원 18
 
2.7%
성 16
 
2.4%
Other values (116) 351
52.1%

Interactions

2023-12-12T09:56:42.362472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:56:44.669402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분광산명주소
구분1.0001.0001.000
광산명1.0001.0001.000
주소1.0001.0001.000

Missing values

2023-12-12T09:56:42.471717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:56:42.555982image/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

구분광산명주소
01금왕(금계)경기 양평군 양동면 계정리 881-3
12여수(팔보)경기 여주시 금사면 상호리 29-2
23삼보경기 화성시 봉담읍 내리 351-2
34영중경기 포천시 영중면 금주리 126-1
45용석경기 포천시 창수면 운사리27
56포천경기 포천시 영북면 야미리 산93-2
67연평(도)인천 옹진군 연평면 소연평리
78제2연화(직내골, 댐골)강원 삼척시 가곡면 풍곡리 산128, 53
89옥계강원 강릉시 옥계면 산계리 764
910고명강원 고성군 현내면 명파리 484
구분광산명주소
5051삼산제일경남 고성군 삼산면 병산리 631-1
5152대두전북 정읍시 덕천면 하학리 산118-3
5253전주일전북 완주군 운주면 장선리 산 74-1
5354덕음전남 나주시 공산면 신곡리 123
5455명봉전남 보성군 노동면 명봉리 226-2
5556전보전남 보성군 문덕면 봉정리 582
5657영대전남 장수군 산서면 오산리 8-1
5758구운동(양구동)경남 밀양시 무안면 마흘리 5, 산267
5859군북경남 함안군 군북면 오곡리 산1019-1
5960다락경북 성주군 수륜면 송계1리 460-1