Overview

Dataset statistics

Number of variables3
Number of observations59
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

Description한국광해광업공단에서 시행하는 광물찌꺼기유실방지 사업지(전국 57개)에 대한 정보로, 광물찌꺼기유실방지사업지, 위치 등의 정보를 제공
URLhttps://www.data.go.kr/data/15055172/fileData.do

Alerts

순번 has unique valuesUnique
시설명 has unique valuesUnique
위치 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:49:33.673261
Analysis finished2023-12-12 16:49:34.129083
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30
Minimum1
Maximum59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2023-12-13T01:49:34.202005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.9
Q115.5
median30
Q344.5
95-th percentile56.1
Maximum59
Range58
Interquartile range (IQR)29

Descriptive statistics

Standard deviation17.175564
Coefficient of variation (CV)0.5725188
Kurtosis-1.2
Mean30
Median Absolute Deviation (MAD)15
Skewness0
Sum1770
Variance295
MonotonicityStrictly increasing
2023-12-13T01:49:34.356835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.7%
2 1
 
1.7%
33 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%
Other values (49) 49
83.1%
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 (%)
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%
50 1
1.7%

시설명
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-13T01:49:34.635857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length2
Mean length3.0338983
Min length2

Characters and Unicode

Total characters179
Distinct characters86
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

Unique59 ?
Unique (%)100.0%

Sample

1st row금왕(금계)
2nd row여수(팔보)
3rd row삼보
4th row영중
5th row용석
ValueCountFrequency (%)
금왕(금계 1
 
1.7%
상동 1
 
1.7%
동아 1
 
1.7%
옥동 1
 
1.7%
금장 1
 
1.7%
달성 1
 
1.7%
고로(석산 1
 
1.7%
금정 1
 
1.7%
토현 1
 
1.7%
서점(나지역 1
 
1.7%
Other values (50) 50
83.3%
2023-12-13T01:49:35.052047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 10
 
5.6%
) 10
 
5.6%
동 9
 
5.0%
곡 5
 
2.8%
일 5
 
2.8%
보 5
 
2.8%
덕 5
 
2.8%
구 5
 
2.8%
금 4
 
2.2%
지 4
 
2.2%
Other values (76) 117
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 154
86.0%
Open Punctuation 10
 
5.6%
Close Punctuation 10
 
5.6%
Decimal Number 3
 
1.7%
Space Separator 1
 
0.6%
Other Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9
 
5.8%
곡 5
 
3.2%
일 5
 
3.2%
보 5
 
3.2%
덕 5
 
3.2%
구 5
 
3.2%
금 4
 
2.6%
지 4
 
2.6%
양 4
 
2.6%
전 4
 
2.6%
Other values (71) 104
67.5%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
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 154
86.0%
Common 25
 
14.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9
 
5.8%
곡 5
 
3.2%
일 5
 
3.2%
보 5
 
3.2%
덕 5
 
3.2%
구 5
 
3.2%
금 4
 
2.6%
지 4
 
2.6%
양 4
 
2.6%
전 4
 
2.6%
Other values (71) 104
67.5%
Common
ValueCountFrequency (%)
( 10
40.0%
) 10
40.0%
2 3
 
12.0%
1
 
4.0%
, 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 154
86.0%
ASCII 25
 
14.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 10
40.0%
) 10
40.0%
2 3
 
12.0%
1
 
4.0%
, 1
 
4.0%
Hangul
ValueCountFrequency (%)
동 9
 
5.8%
곡 5
 
3.2%
일 5
 
3.2%
보 5
 
3.2%
덕 5
 
3.2%
구 5
 
3.2%
금 4
 
2.6%
지 4
 
2.6%
양 4
 
2.6%
전 4
 
2.6%
Other values (71) 104
67.5%

위치
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-13T01:49:35.453398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length19.050847
Min length12

Characters and Unicode

Total characters1124
Distinct characters136
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

Unique59 ?
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
 
5.4%
강원 11
 
3.7%
경기 6
 
2.0%
경남 6
 
2.0%
충남 6
 
2.0%
봉화군 6
 
2.0%
충북 5
 
1.7%
고성군 4
 
1.3%
전남 4
 
1.3%
울진군 3
 
1.0%
Other values (209) 230
77.4%
2023-12-13T01:49:36.026549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
239
21.3%
리 58
 
5.2%
면 55
 
4.9%
군 44
 
3.9%
1 42
 
3.7%
산 38
 
3.4%
2 30
 
2.7%
경 28
 
2.5%
- 26
 
2.3%
북 26
 
2.3%
Other values (126) 538
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 662
58.9%
Space Separator 239
 
21.3%
Decimal Number 194
 
17.3%
Dash Punctuation 26
 
2.3%
Other Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 58
 
8.8%
면 55
 
8.3%
군 44
 
6.6%
산 38
 
5.7%
경 28
 
4.2%
북 26
 
3.9%
남 19
 
2.9%
원 18
 
2.7%
시 18
 
2.7%
성 16
 
2.4%
Other values (113) 342
51.7%
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 (%)
239
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 662
58.9%
Common 462
41.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 58
 
8.8%
면 55
 
8.3%
군 44
 
6.6%
산 38
 
5.7%
경 28
 
4.2%
북 26
 
3.9%
남 19
 
2.9%
원 18
 
2.7%
시 18
 
2.7%
성 16
 
2.4%
Other values (113) 342
51.7%
Common
ValueCountFrequency (%)
239
51.7%
1 42
 
9.1%
2 30
 
6.5%
- 26
 
5.6%
3 22
 
4.8%
8 19
 
4.1%
6 16
 
3.5%
5 16
 
3.5%
4 16
 
3.5%
7 13
 
2.8%
Other values (3) 23
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 662
58.9%
ASCII 462
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
239
51.7%
1 42
 
9.1%
2 30
 
6.5%
- 26
 
5.6%
3 22
 
4.8%
8 19
 
4.1%
6 16
 
3.5%
5 16
 
3.5%
4 16
 
3.5%
7 13
 
2.8%
Other values (3) 23
 
5.0%
Hangul
ValueCountFrequency (%)
리 58
 
8.8%
면 55
 
8.3%
군 44
 
6.6%
산 38
 
5.7%
경 28
 
4.2%
북 26
 
3.9%
남 19
 
2.9%
원 18
 
2.7%
시 18
 
2.7%
성 16
 
2.4%
Other values (113) 342
51.7%

Interactions

2023-12-13T01:49:33.866195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:49:36.145202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시설명위치
순번1.0001.0001.000
시설명1.0001.0001.000
위치1.0001.0001.000

Missing values

2023-12-13T01:49:33.997958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:49:34.092378image/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

순번시설명위치
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
67제2연화(직내골, 댐골)강원 삼척시 가곡면 풍곡리 산128, 53
78옥계강원 강릉시 옥계면 산계리 764
89고명강원 고성군 현내면 명파리 484
910동명강원 정선군 임계면 봉산리 89
순번시설명위치
4950삼산제일경남 고성군 삼산면 병산리 631-1
5051대두전북 정읍시 덕천면 하학리 산118-3
5152전주일전북 완주군 운주면 장선리 산 74-1
5253덕음전남 나주시 공산면 신곡리 123
5354명봉전남 보성군 노동면 명봉리 226-2
5455전보전남 보성군 문덕면 봉정리 582
5556영대전남 장수군 산서면 오산리 8-1
5657구운동(양구동)경남 밀양시 무안면 마흘리 5, 산267
5758군북경남 함안군 군북면 오곡리 산1019-1
5859다락경북 성주군 수륜면 송계1리 460-1