Overview

Dataset statistics

Number of variables13
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.9 KiB
Average record size in memory110.7 B

Variable types

Categorical10
Numeric1
Text2

Alerts

탐사일 has constant value ""Constant
지점명 has constant value ""Constant
시도명 has constant value ""Constant
시군명 has constant value ""Constant
물리검층장비명 has constant value ""Constant
분석프로그램명 has constant value ""Constant
측점개수 has constant value ""Constant
지층내용 has constant value ""Constant
법정동코드 is highly overall correlated with 읍면동명High correlation
읍면동명 is highly overall correlated with 법정동코드 and 1 other fieldsHigh correlation
전기탐사결과내용 is highly overall correlated with 읍면동명High correlation
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:19:12.850277
Analysis finished2023-12-10 13:19:14.025848
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

탐사일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
20210201
36 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20210201
2nd row20210201
3rd row20210201
4th row20210201
5th row20210201

Common Values

ValueCountFrequency (%)
20210201 36
100.0%

Length

2023-12-10T22:19:14.141721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:19:14.302250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20210201 36
100.0%

지점명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
영주지역
36 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영주지역 36
100.0%

Length

2023-12-10T22:19:14.489870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:19:14.643625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영주지역 36
100.0%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7210342 × 109
Minimum4.7210107 × 109
Maximum4.721039 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-10T22:19:14.792183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.7210107 × 109
5-th percentile4.7210261 × 109
Q14.721032 × 109
median4.721037 × 109
Q34.721038 × 109
95-th percentile4.721039 × 109
Maximum4.721039 × 109
Range28329
Interquartile range (IQR)6001.25

Descriptive statistics

Standard deviation6451.434
Coefficient of variation (CV)1.3665298 × 10-6
Kurtosis8.2761355
Mean4.7210342 × 109
Median Absolute Deviation (MAD)1990.5
Skewness-2.7322266
Sum1.6995723 × 1011
Variance41621001
MonotonicityNot monotonic
2023-12-10T22:19:14.999614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
4721032023 4
 
11.1%
4721038024 3
 
8.3%
4721037022 3
 
8.3%
4721031022 2
 
5.6%
4721031026 2
 
5.6%
4721038028 2
 
5.6%
4721038025 2
 
5.6%
4721038022 2
 
5.6%
4721037024 1
 
2.8%
4721035033 1
 
2.8%
Other values (14) 14
38.9%
ValueCountFrequency (%)
4721010700 1
 
2.8%
4721011300 1
 
2.8%
4721031022 2
5.6%
4721031024 1
 
2.8%
4721031026 2
5.6%
4721031028 1
 
2.8%
4721032022 1
 
2.8%
4721032023 4
11.1%
4721035031 1
 
2.8%
4721035032 1
 
2.8%
ValueCountFrequency (%)
4721039029 1
 
2.8%
4721039028 1
 
2.8%
4721039024 1
 
2.8%
4721039023 1
 
2.8%
4721038028 2
5.6%
4721038025 2
5.6%
4721038024 3
8.3%
4721038023 1
 
2.8%
4721038022 2
5.6%
4721038021 1
 
2.8%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
경상북도
36 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 36
100.0%

Length

2023-12-10T22:19:15.353339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:19:15.514757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 36
100.0%

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
영주시
36 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영주시 36
100.0%

Length

2023-12-10T22:19:15.695251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:19:15.857264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영주시 36
100.0%

읍면동명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)22.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
단산면
11 
이산면
6 
평은면
5 
순흥면
5 
부석면
4 
Other values (3)
5 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)5.6%

Sample

1st row부석면
2nd row부석면
3rd row부석면
4th row부석면
5th row이산면

Common Values

ValueCountFrequency (%)
단산면 11
30.6%
이산면 6
16.7%
평은면 5
13.9%
순흥면 5
13.9%
부석면 4
 
11.1%
안정면 3
 
8.3%
아지동 1
 
2.8%
고현동 1
 
2.8%

Length

2023-12-10T22:19:16.010181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:19:16.248140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단산면 11
30.6%
이산면 6
16.7%
평은면 5
13.9%
순흥면 5
13.9%
부석면 4
 
11.1%
안정면 3
 
8.3%
아지동 1
 
2.8%
고현동 1
 
2.8%

리명
Text

Distinct23
Distinct (%)63.9%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T22:19:16.665144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.8888889
Min length1

Characters and Unicode

Total characters104
Distinct characters33
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

Unique14 ?
Unique (%)38.9%

Sample

1st row임곡리
2nd row소천리
3rd row상석리
4th row감곡리
5th row신암리
ValueCountFrequency (%)
오운리 4
 
11.1%
지동리 3
 
8.3%
병산리 3
 
8.3%
옥대리 2
 
5.6%
사천리 2
 
5.6%
신암리 2
 
5.6%
0 2
 
5.6%
신천리 2
 
5.6%
마락리 2
 
5.6%
구구리 1
 
2.8%
Other values (13) 13
36.1%
2023-12-10T22:19:17.212225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 34
32.7%
오 5
 
4.8%
천 5
 
4.8%
지 4
 
3.8%
동 4
 
3.8%
신 4
 
3.8%
운 4
 
3.8%
병 3
 
2.9%
산 3
 
2.9%
내 3
 
2.9%
Other values (23) 35
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102
98.1%
Decimal Number 2
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 34
33.3%
오 5
 
4.9%
천 5
 
4.9%
지 4
 
3.9%
동 4
 
3.9%
신 4
 
3.9%
운 4
 
3.9%
병 3
 
2.9%
산 3
 
2.9%
내 3
 
2.9%
Other values (22) 33
32.4%
Decimal Number
ValueCountFrequency (%)
0 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102
98.1%
Common 2
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 34
33.3%
오 5
 
4.9%
천 5
 
4.9%
지 4
 
3.9%
동 4
 
3.9%
신 4
 
3.9%
운 4
 
3.9%
병 3
 
2.9%
산 3
 
2.9%
내 3
 
2.9%
Other values (22) 33
32.4%
Common
ValueCountFrequency (%)
0 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102
98.1%
ASCII 2
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 34
33.3%
오 5
 
4.9%
천 5
 
4.9%
지 4
 
3.9%
동 4
 
3.9%
신 4
 
3.9%
운 4
 
3.9%
병 3
 
2.9%
산 3
 
2.9%
내 3
 
2.9%
Other values (22) 33
32.4%
ASCII
ValueCountFrequency (%)
0 2
100.0%

주소
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-10T22:19:17.546190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.4722222
Min length2

Characters and Unicode

Total characters161
Distinct characters12
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

Unique36 ?
Unique (%)100.0%

Sample

1st row1273
2nd row454-6
3rd row482-2
4th row44-5
5th row807-1
ValueCountFrequency (%)
1273 1
 
2.8%
454-6 1
 
2.8%
186-2 1
 
2.8%
552-2 1
 
2.8%
80-1 1
 
2.8%
663-6 1
 
2.8%
216 1
 
2.8%
361-2 1
 
2.8%
458-1 1
 
2.8%
372-2 1
 
2.8%
Other values (26) 26
72.2%
2023-12-10T22:19:18.272948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 28
17.4%
2 21
13.0%
1 20
12.4%
3 14
8.7%
5 14
8.7%
7 13
8.1%
6 13
8.1%
4 12
7.5%
8 12
7.5%
0 8
 
5.0%
Other values (2) 6
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 132
82.0%
Dash Punctuation 28
 
17.4%
Other Letter 1
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 21
15.9%
1 20
15.2%
3 14
10.6%
5 14
10.6%
7 13
9.8%
6 13
9.8%
4 12
9.1%
8 12
9.1%
0 8
 
6.1%
9 5
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Other Letter
ValueCountFrequency (%)
산 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 160
99.4%
Hangul 1
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
- 28
17.5%
2 21
13.1%
1 20
12.5%
3 14
8.8%
5 14
8.8%
7 13
8.1%
6 13
8.1%
4 12
7.5%
8 12
7.5%
0 8
 
5.0%
Hangul
ValueCountFrequency (%)
산 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 160
99.4%
Hangul 1
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 28
17.5%
2 21
13.1%
1 20
12.5%
3 14
8.8%
5 14
8.8%
7 13
8.1%
6 13
8.1%
4 12
7.5%
8 12
7.5%
0 8
 
5.0%
Hangul
ValueCountFrequency (%)
산 1
100.0%

물리검층장비명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
ABEM TERRAMETER LS2
36 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowABEM TERRAMETER LS2
2nd rowABEM TERRAMETER LS2
3rd rowABEM TERRAMETER LS2
4th rowABEM TERRAMETER LS2
5th rowABEM TERRAMETER LS2

Common Values

ValueCountFrequency (%)
ABEM TERRAMETER LS2 36
100.0%

Length

2023-12-10T22:19:18.509043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:19:18.661927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
abem 36
33.3%
terrameter 36
33.3%
ls2 36
33.3%

분석프로그램명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
IXID V2
36 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIXID V2
2nd rowIXID V2
3rd rowIXID V2
4th rowIXID V2
5th rowIXID V2

Common Values

ValueCountFrequency (%)
IXID V2 36
100.0%

Length

2023-12-10T22:19:18.877144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:19:19.089373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ixid 36
50.0%
v2 36
50.0%

전기탐사결과내용
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
충적. 풍화대. 암반순으로 분포
30 
충적. 풍화대순으로 분포
6 

Length

Max length17
Median length17
Mean length16.333333
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충적. 풍화대. 암반순으로 분포
2nd row충적. 풍화대. 암반순으로 분포
3rd row충적. 풍화대. 암반순으로 분포
4th row충적. 풍화대. 암반순으로 분포
5th row충적. 풍화대. 암반순으로 분포

Common Values

ValueCountFrequency (%)
충적. 풍화대. 암반순으로 분포 30
83.3%
충적. 풍화대순으로 분포 6
 
16.7%

Length

2023-12-10T22:19:19.292665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:19:19.512889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충적 36
26.1%
분포 36
26.1%
풍화대 30
21.7%
암반순으로 30
21.7%
풍화대순으로 6
 
4.3%

측점개수
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
13
36 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13
2nd row13
3rd row13
4th row13
5th row13

Common Values

ValueCountFrequency (%)
13 36
100.0%

Length

2023-12-10T22:19:19.691778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:19:19.858911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 36
100.0%

지층내용
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
충적층
36 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충적층 36
100.0%

Length

2023-12-10T22:19:20.021613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:19:20.178054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충적층 36
100.0%

Interactions

2023-12-10T22:19:13.292108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:19:20.627577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동코드읍면동명리명주소전기탐사결과내용
법정동코드1.0001.0001.0001.0000.315
읍면동명1.0001.0000.9551.0000.808
리명1.0000.9551.0001.0000.853
주소1.0001.0001.0001.0001.000
전기탐사결과내용0.3150.8080.8531.0001.000
2023-12-10T22:19:20.781590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명전기탐사결과내용
읍면동명1.0000.567
전기탐사결과내용0.5671.000
2023-12-10T22:19:20.914355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동코드읍면동명전기탐사결과내용
법정동코드1.0000.9350.216
읍면동명0.9351.0000.567
전기탐사결과내용0.2160.5671.000

Missing values

2023-12-10T22:19:13.547882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:19:13.914522image/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

탐사일지점명법정동코드시도명시군명읍면동명리명주소물리검층장비명분석프로그램명전기탐사결과내용측점개수지층내용
020210201영주지역4721039023경상북도영주시부석면임곡리1273ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
120210201영주지역4721039024경상북도영주시부석면소천리454-6ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
220210201영주지역4721039028경상북도영주시부석면상석리482-2ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
320210201영주지역4721039029경상북도영주시부석면감곡리44-5ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
420210201영주지역4721031022경상북도영주시이산면신암리807-1ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
520210201영주지역4721031022경상북도영주시이산면신암리679-4ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
620210201영주지역4721031024경상북도영주시이산면석포리797-1ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
720210201영주지역4721031028경상북도영주시이산면내림리367ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
820210201영주지역4721032023경상북도영주시평은면오운리1220-4ABEM TERRAMETER LS2IXID V2충적. 풍화대순으로 분포13충적층
920210201영주지역4721032023경상북도영주시평은면오운리1510-3ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
탐사일지점명법정동코드시도명시군명읍면동명리명주소물리검층장비명분석프로그램명전기탐사결과내용측점개수지층내용
2620210201영주지역4721037022경상북도영주시순흥면지동리186-2ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
2720210201영주지역4721037022경상북도영주시순흥면지동리372-2ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
2820210201영주지역4721038021경상북도영주시단산면동원리726-1ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
2920210201영주지역4721011300경상북도영주시아지동018ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
3020210201영주지역4721010700경상북도영주시고현동053-2ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
3120210201영주지역4721035031경상북도영주시안정면단촌리372-10ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
3220210201영주지역4721035032경상북도영주시안정면대평리90-8ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
3320210201영주지역4721035033경상북도영주시안정면오계리397-36ABEM TERRAMETER LS2IXID V2충적. 풍화대. 암반순으로 분포13충적층
3420210201영주지역4721032023경상북도영주시평은면오운리10ABEM TERRAMETER LS2IXID V2충적. 풍화대순으로 분포13충적층
3520210201영주지역4721032023경상북도영주시평은면오운리122-1ABEM TERRAMETER LS2IXID V2충적. 풍화대순으로 분포13충적층