Overview

Dataset statistics

Number of variables5
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory44.7 B

Variable types

Numeric2
Text2
DateTime1

Dataset

Description전북특별자치도 토석채취현황(2018년 기준)소재지 지번 수량(천㎥) 허가일전주, 군산, 익산, 정읍, 남원, 김제, 완주, 진안, 무주, 장수, 임실, 순창, 고창, 부안
Author전북특별자치도
URLhttps://www.data.go.kr/data/15119361/fileData.do

Alerts

연번 has unique valuesUnique
지번 has unique valuesUnique

Reproduction

Analysis started2024-03-15 00:10:40.748684
Analysis finished2024-03-15 00:10:43.303361
Duration2.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.5
Minimum1
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-03-15T09:10:43.607734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.35
Q112.75
median24.5
Q336.25
95-th percentile45.65
Maximum48
Range47
Interquartile range (IQR)23.5

Descriptive statistics

Standard deviation14
Coefficient of variation (CV)0.57142857
Kurtosis-1.2
Mean24.5
Median Absolute Deviation (MAD)12
Skewness0
Sum1176
Variance196
MonotonicityStrictly increasing
2024-03-15T09:10:44.363794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
1 1
 
2.1%
26 1
 
2.1%
28 1
 
2.1%
29 1
 
2.1%
30 1
 
2.1%
31 1
 
2.1%
32 1
 
2.1%
33 1
 
2.1%
34 1
 
2.1%
35 1
 
2.1%
Other values (38) 38
79.2%
ValueCountFrequency (%)
1 1
2.1%
2 1
2.1%
3 1
2.1%
4 1
2.1%
5 1
2.1%
6 1
2.1%
7 1
2.1%
8 1
2.1%
9 1
2.1%
10 1
2.1%
ValueCountFrequency (%)
48 1
2.1%
47 1
2.1%
46 1
2.1%
45 1
2.1%
44 1
2.1%
43 1
2.1%
42 1
2.1%
41 1
2.1%
40 1
2.1%
39 1
2.1%

소재지
Text

Distinct30
Distinct (%)62.5%
Missing0
Missing (%)0.0%
Memory size512.0 B
2024-03-15T09:10:45.593310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.125
Min length7

Characters and Unicode

Total characters486
Distinct characters73
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

Unique20 ?
Unique (%)41.7%

Sample

1st row군산시 성산면 성덕리
2nd row군산시 성산면 여방리
3rd row군산시 성산면 여방리
4th row군산시 나포면 장상리
5th row익산 함열 흘산
ValueCountFrequency (%)
낭산 19
 
13.3%
익산 13
 
9.1%
남원시 10
 
7.0%
고창군 6
 
4.2%
정읍시 5
 
3.5%
완주군 5
 
3.5%
황등 4
 
2.8%
군산시 4
 
2.8%
옹동면 3
 
2.1%
상산리 3
 
2.1%
Other values (48) 71
49.7%
2024-03-15T09:10:47.302488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
96
19.8%
산 54
 
11.1%
리 34
 
7.0%
면 34
 
7.0%
군 20
 
4.1%
낭 19
 
3.9%
시 19
 
3.9%
동 14
 
2.9%
익 13
 
2.7%
남 11
 
2.3%
Other values (63) 172
35.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 390
80.2%
Space Separator 96
 
19.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 54
 
13.8%
리 34
 
8.7%
면 34
 
8.7%
군 20
 
5.1%
낭 19
 
4.9%
시 19
 
4.9%
동 14
 
3.6%
익 13
 
3.3%
남 11
 
2.8%
주 10
 
2.6%
Other values (62) 162
41.5%
Space Separator
ValueCountFrequency (%)
96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 390
80.2%
Common 96
 
19.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 54
 
13.8%
리 34
 
8.7%
면 34
 
8.7%
군 20
 
5.1%
낭 19
 
4.9%
시 19
 
4.9%
동 14
 
3.6%
익 13
 
3.3%
남 11
 
2.8%
주 10
 
2.6%
Other values (62) 162
41.5%
Common
ValueCountFrequency (%)
96
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 390
80.2%
ASCII 96
 
19.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
96
100.0%
Hangul
ValueCountFrequency (%)
산 54
 
13.8%
리 34
 
8.7%
면 34
 
8.7%
군 20
 
5.1%
낭 19
 
4.9%
시 19
 
4.9%
동 14
 
3.6%
익 13
 
3.3%
남 11
 
2.8%
주 10
 
2.6%
Other values (62) 162
41.5%

지번
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size512.0 B
2024-03-15T09:10:48.479106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length8.2083333
Min length3

Characters and Unicode

Total characters394
Distinct characters16
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

Unique48 ?
Unique (%)100.0%

Sample

1st row산2-1 외 5필
2nd row산2 외 4필
3rd row산2 외 6필
4th row산236 외 10필
5th row산19-1외 1필
ValueCountFrequency (%)
외 14
 
14.7%
4필 5
 
5.3%
1필 4
 
4.2%
산2 3
 
3.2%
7필 3
 
3.2%
15필 2
 
2.1%
2필지 2
 
2.1%
6필 2
 
2.1%
5필 2
 
2.1%
산37 1
 
1.1%
Other values (57) 57
60.0%
2024-03-15T09:10:49.933828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 55
14.0%
47
11.9%
산 46
11.7%
외 43
10.9%
필 43
10.9%
2 21
 
5.3%
5 21
 
5.3%
3 21
 
5.3%
- 20
 
5.1%
4 16
 
4.1%
Other values (6) 61
15.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 181
45.9%
Other Letter 146
37.1%
Space Separator 47
 
11.9%
Dash Punctuation 20
 
5.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 55
30.4%
2 21
 
11.6%
5 21
 
11.6%
3 21
 
11.6%
4 16
 
8.8%
6 12
 
6.6%
7 11
 
6.1%
0 9
 
5.0%
8 8
 
4.4%
9 7
 
3.9%
Other Letter
ValueCountFrequency (%)
산 46
31.5%
외 43
29.5%
필 43
29.5%
지 14
 
9.6%
Space Separator
ValueCountFrequency (%)
47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 248
62.9%
Hangul 146
37.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 55
22.2%
47
19.0%
2 21
 
8.5%
5 21
 
8.5%
3 21
 
8.5%
- 20
 
8.1%
4 16
 
6.5%
6 12
 
4.8%
7 11
 
4.4%
0 9
 
3.6%
Other values (2) 15
 
6.0%
Hangul
ValueCountFrequency (%)
산 46
31.5%
외 43
29.5%
필 43
29.5%
지 14
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 248
62.9%
Hangul 146
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 55
22.2%
47
19.0%
2 21
 
8.5%
5 21
 
8.5%
3 21
 
8.5%
- 20
 
8.1%
4 16
 
6.5%
6 12
 
4.8%
7 11
 
4.4%
0 9
 
3.6%
Other values (2) 15
 
6.0%
Hangul
ValueCountFrequency (%)
산 46
31.5%
외 43
29.5%
필 43
29.5%
지 14
 
9.6%

수량
Real number (ℝ)

Distinct47
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1537.1042
Minimum12
Maximum4677
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size560.0 B
2024-03-15T09:10:50.342588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile218
Q1807.75
median1281.5
Q31853.25
95-th percentile4486.75
Maximum4677
Range4665
Interquartile range (IQR)1045.5

Descriptive statistics

Standard deviation1219.9363
Coefficient of variation (CV)0.79365882
Kurtosis1.228213
Mean1537.1042
Median Absolute Deviation (MAD)513.5
Skewness1.3140608
Sum73781
Variance1488244.5
MonotonicityNot monotonic
2024-03-15T09:10:50.835962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
218 2
 
4.2%
1256 1
 
2.1%
2081 1
 
2.1%
12 1
 
2.1%
994 1
 
2.1%
931 1
 
2.1%
957 1
 
2.1%
1439 1
 
2.1%
306 1
 
2.1%
1469 1
 
2.1%
Other values (37) 37
77.1%
ValueCountFrequency (%)
12 1
2.1%
181 1
2.1%
218 2
4.2%
225 1
2.1%
267 1
2.1%
306 1
2.1%
387 1
2.1%
410 1
2.1%
483 1
2.1%
594 1
2.1%
ValueCountFrequency (%)
4677 1
2.1%
4584 1
2.1%
4492 1
2.1%
4477 1
2.1%
3833 1
2.1%
3378 1
2.1%
2543 1
2.1%
2450 1
2.1%
2447 1
2.1%
2081 1
2.1%

허가일
Date

Distinct43
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Memory size512.0 B
Minimum2001-07-03 00:00:00
Maximum2017-12-15 00:00:00
2024-03-15T09:10:51.532279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:10:52.003860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)

Interactions

2024-03-15T09:10:41.709526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:10:41.182997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:10:42.008585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:10:41.437124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:10:52.297139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소재지지번수량허가일
연번1.0000.9601.0000.3540.834
소재지0.9601.0001.0000.0000.964
지번1.0001.0001.0001.0001.000
수량0.3540.0001.0001.0000.956
허가일0.8340.9641.0000.9561.000
2024-03-15T09:10:52.584236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번수량
연번1.000-0.081
수량-0.0811.000

Missing values

2024-03-15T09:10:42.344571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:10:42.940150image/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

연번소재지지번수량허가일
01군산시 성산면 성덕리산2-1 외 5필12562014-05-02
12군산시 성산면 여방리산2 외 4필45842011-08-09
23군산시 성산면 여방리산2 외 6필44922015-05-28
34군산시 나포면 장상리산236 외 10필13732016-01-15
45익산 함열 흘산산19-1외 1필4832009-04-17
56익산 낭산 낭산산88-1외 9필33782009-05-04
67익산 낭산 낭산산94-115302008-04-11
78익산 낭산 낭산산111-3외 7필3872007-06-18
89익산 낭산 낭산산160-1외 1필18222008-05-07
910익산 낭산 석천산141외 4필24472011-01-04
연번소재지지번수량허가일
3839순창군 동계면 수정리산4 외 6필지10972015-10-19
3940고창군 무장면 교흥리산29 외 2필지8122015-03-09
4041고창군 무장면 교흥리산30 외 2필지1812016-10-05
4142고창군 성송면 계당리산36 외 10필지5942014-06-05
4243고창군 성송면 암치리산81 외 5필지16682012-05-01
4344고창군 부안면 검산리산74 외 3필지46772013-01-14
4445고창군 부안면 선운리산52 외 4필지14512014-05-09
4546부안군 주산면 사산리산73외2필24502010-05-04
4647부안군 보안면 월천리산37외3필지15992009-04-20
4748부안군 주산면 소산리산4-5외6필지25432012-07-09