Overview

Dataset statistics

Number of variables6
Number of observations29
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory54.6 B

Variable types

Text2
Categorical1
DateTime1
Numeric2

Dataset

Description김해시 골재채취업 등록현황에 대한 자료로 업체명, 업종, 소재지주소, 신고일 등에 대한 데이터로 구성되어 있습니다.
URLhttps://www.data.go.kr/data/15033369/fileData.do

Reproduction

Analysis started2023-12-12 13:29:27.672657
Analysis finished2023-12-12 13:29:29.242953
Duration1.57 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

Distinct21
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T22:29:29.405807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.137931
Min length5

Characters and Unicode

Total characters207
Distinct characters58
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)48.3%

Sample

1st row(주)경부공영
2nd row(주)경부공영
3rd row(주)동남
4th row(주)동남
5th row(주)대동하이텍
ValueCountFrequency (%)
㈜운대산업개발 3
 
9.7%
금광개발(주 2
 
6.5%
에코종합건설(주 2
 
6.5%
주)동남 2
 
6.5%
지유앤주식회사 2
 
6.5%
주)경부공영 2
 
6.5%
주식회사 2
 
6.5%
주)대동하이텍 2
 
6.5%
주)중앙환경 1
 
3.2%
삼계개발(주 1
 
3.2%
Other values (12) 12
38.7%
2023-12-12T22:29:29.920462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 18
 
8.7%
( 14
 
6.8%
) 14
 
6.8%
㈜ 11
 
5.3%
개 10
 
4.8%
발 10
 
4.8%
산 8
 
3.9%
업 7
 
3.4%
대 6
 
2.9%
에 5
 
2.4%
Other values (48) 104
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 166
80.2%
Open Punctuation 14
 
6.8%
Close Punctuation 14
 
6.8%
Other Symbol 11
 
5.3%
Space Separator 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 18
 
10.8%
개 10
 
6.0%
발 10
 
6.0%
산 8
 
4.8%
업 7
 
4.2%
대 6
 
3.6%
에 5
 
3.0%
동 5
 
3.0%
운 4
 
2.4%
사 4
 
2.4%
Other values (44) 89
53.6%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 11
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 177
85.5%
Common 30
 
14.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 18
 
10.2%
㈜ 11
 
6.2%
개 10
 
5.6%
발 10
 
5.6%
산 8
 
4.5%
업 7
 
4.0%
대 6
 
3.4%
에 5
 
2.8%
동 5
 
2.8%
운 4
 
2.3%
Other values (45) 93
52.5%
Common
ValueCountFrequency (%)
( 14
46.7%
) 14
46.7%
2
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 166
80.2%
ASCII 30
 
14.5%
None 11
 
5.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 18
 
10.8%
개 10
 
6.0%
발 10
 
6.0%
산 8
 
4.8%
업 7
 
4.2%
대 6
 
3.6%
에 5
 
3.0%
동 5
 
3.0%
운 4
 
2.4%
사 4
 
2.4%
Other values (44) 89
53.6%
ASCII
ValueCountFrequency (%)
( 14
46.7%
) 14
46.7%
2
 
6.7%
None
ValueCountFrequency (%)
㈜ 11
100.0%

업종
Categorical

Distinct4
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size364.0 B
골재선별·파쇄업
20 
산림골재채취업
7 
수중골재채취업
 
1
육상골재채취업
 
1

Length

Max length8
Median length8
Mean length7.6896552
Min length7

Unique

Unique2 ?
Unique (%)6.9%

Sample

1st row산림골재채취업
2nd row골재선별·파쇄업
3rd row산림골재채취업
4th row골재선별·파쇄업
5th row산림골재채취업

Common Values

ValueCountFrequency (%)
골재선별·파쇄업 20
69.0%
산림골재채취업 7
 
24.1%
수중골재채취업 1
 
3.4%
육상골재채취업 1
 
3.4%

Length

2023-12-12T22:29:30.120471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:29:30.279350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
골재선별·파쇄업 20
69.0%
산림골재채취업 7
 
24.1%
수중골재채취업 1
 
3.4%
육상골재채취업 1
 
3.4%

소재지주소
Text

Distinct21
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Memory size364.0 B
2023-12-12T22:29:30.517527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length25.137931
Min length19

Characters and Unicode

Total characters729
Distinct characters84
Distinct categories7 ?
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 (%)48.3%

Sample

1st row경상남도 김해시 상동면 동북로437번길 83-43
2nd row경상남도 김해시 상동면 동북로437번길 83-43
3rd row경상남도 김해시 주촌면 서부로 1701번안길 58-93
4th row경상남도 김해시 주촌면 서부로 1701번안길 58-93
5th row경상남도 김해시 호계로 435, 케이타운빌딩 2층(부원동)
ValueCountFrequency (%)
경상남도 29
19.9%
김해시 27
18.5%
주촌면 7
 
4.8%
상동면 6
 
4.1%
한림면 4
 
2.7%
김해대로974번길 3
 
2.1%
60 3
 
2.1%
나전로 3
 
2.1%
생림면 3
 
2.1%
동북로437번길 3
 
2.1%
Other values (41) 58
39.7%
2023-12-12T22:29:30.963126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
117
 
16.0%
상 38
 
5.2%
해 34
 
4.7%
김 33
 
4.5%
경 29
 
4.0%
남 29
 
4.0%
도 29
 
4.0%
시 29
 
4.0%
로 27
 
3.7%
0 22
 
3.0%
Other values (74) 342
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 440
60.4%
Decimal Number 145
 
19.9%
Space Separator 117
 
16.0%
Dash Punctuation 13
 
1.8%
Other Punctuation 6
 
0.8%
Open Punctuation 4
 
0.5%
Close Punctuation 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 38
 
8.6%
해 34
 
7.7%
김 33
 
7.5%
경 29
 
6.6%
남 29
 
6.6%
도 29
 
6.6%
시 29
 
6.6%
로 27
 
6.1%
면 20
 
4.5%
동 17
 
3.9%
Other values (59) 155
35.2%
Decimal Number
ValueCountFrequency (%)
0 22
15.2%
1 22
15.2%
3 21
14.5%
7 18
12.4%
4 14
9.7%
6 11
7.6%
8 11
7.6%
9 9
6.2%
5 9
6.2%
2 8
 
5.5%
Space Separator
ValueCountFrequency (%)
117
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 440
60.4%
Common 289
39.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 38
 
8.6%
해 34
 
7.7%
김 33
 
7.5%
경 29
 
6.6%
남 29
 
6.6%
도 29
 
6.6%
시 29
 
6.6%
로 27
 
6.1%
면 20
 
4.5%
동 17
 
3.9%
Other values (59) 155
35.2%
Common
ValueCountFrequency (%)
117
40.5%
0 22
 
7.6%
1 22
 
7.6%
3 21
 
7.3%
7 18
 
6.2%
4 14
 
4.8%
- 13
 
4.5%
6 11
 
3.8%
8 11
 
3.8%
9 9
 
3.1%
Other values (5) 31
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 440
60.4%
ASCII 289
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117
40.5%
0 22
 
7.6%
1 22
 
7.6%
3 21
 
7.3%
7 18
 
6.2%
4 14
 
4.8%
- 13
 
4.5%
6 11
 
3.8%
8 11
 
3.8%
9 9
 
3.1%
Other values (5) 31
 
10.7%
Hangul
ValueCountFrequency (%)
상 38
 
8.6%
해 34
 
7.7%
김 33
 
7.5%
경 29
 
6.6%
남 29
 
6.6%
도 29
 
6.6%
시 29
 
6.6%
로 27
 
6.1%
면 20
 
4.5%
동 17
 
3.9%
Other values (59) 155
35.2%

신고일
Date

Distinct27
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size364.0 B
Minimum1995-02-11 00:00:00
Maximum2023-06-29 00:00:00
2023-12-12T22:29:31.113196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:29:31.250081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)

위도
Real number (ℝ)

Distinct21
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.273924
Minimum35.205246
Maximum35.318422
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T22:29:31.389941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.205246
5-th percentile35.214058
Q135.245434
median35.293526
Q335.310282
95-th percentile35.313041
Maximum35.318422
Range0.11317603
Interquartile range (IQR)0.06484805

Descriptive statistics

Standard deviation0.037731191
Coefficient of variation (CV)0.0010696624
Kurtosis-1.3949257
Mean35.273924
Median Absolute Deviation (MAD)0.02489555
Skewness-0.40428877
Sum1022.9438
Variance0.0014236428
MonotonicityNot monotonic
2023-12-12T22:29:31.542549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
35.31099381 3
 
10.3%
35.30789978 2
 
6.9%
35.22923677 2
 
6.9%
35.26444445 2
 
6.9%
35.21405815 2
 
6.9%
35.24543352 2
 
6.9%
35.31028157 2
 
6.9%
35.26036692 1
 
3.4%
35.2218768 1
 
3.4%
35.25215102 1
 
3.4%
Other values (11) 11
37.9%
ValueCountFrequency (%)
35.20524593 1
3.4%
35.21405815 2
6.9%
35.2218768 1
3.4%
35.22923677 2
6.9%
35.2378746 1
3.4%
35.24543352 2
6.9%
35.25215102 1
3.4%
35.25609414 1
3.4%
35.26036692 1
3.4%
35.26444445 2
6.9%
ValueCountFrequency (%)
35.31842196 1
 
3.4%
35.3144052 1
 
3.4%
35.31099381 3
10.3%
35.31082349 1
 
3.4%
35.3105298 1
 
3.4%
35.31028157 2
6.9%
35.30789978 2
6.9%
35.2978066 1
 
3.4%
35.29457134 1
 
3.4%
35.29441669 1
 
3.4%

경도
Real number (ℝ)

Distinct21
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.86077
Minimum128.7427
Maximum128.9638
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size393.0 B
2023-12-12T22:29:31.693660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.7427
5-th percentile128.76841
Q1128.82808
median128.85771
Q3128.8847
95-th percentile128.96172
Maximum128.9638
Range0.2210978
Interquartile range (IQR)0.0566214

Descriptive statistics

Standard deviation0.058878649
Coefficient of variation (CV)0.00045691678
Kurtosis-0.15585442
Mean128.86077
Median Absolute Deviation (MAD)0.0291036
Skewness0.145556
Sum3736.9624
Variance0.0034666953
MonotonicityNot monotonic
2023-12-12T22:29:31.813002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
128.8047247 3
 
10.3%
128.963799 2
 
6.9%
128.8847039 2
 
6.9%
128.8445214 2
 
6.9%
128.8286103 2
 
6.9%
128.8394123 2
 
6.9%
128.9441325 2
 
6.9%
128.871624 1
 
3.4%
128.8577139 1
 
3.4%
128.8671953 1
 
3.4%
Other values (11) 11
37.9%
ValueCountFrequency (%)
128.7427012 1
 
3.4%
128.7441919 1
 
3.4%
128.8047247 3
10.3%
128.8201629 1
 
3.4%
128.823526 1
 
3.4%
128.8280825 1
 
3.4%
128.8286103 2
6.9%
128.8394123 2
6.9%
128.8445214 2
6.9%
128.8577139 1
 
3.4%
ValueCountFrequency (%)
128.963799 2
6.9%
128.9586033 1
3.4%
128.9441325 2
6.9%
128.9382336 1
3.4%
128.8847039 2
6.9%
128.8735397 1
3.4%
128.8733435 1
3.4%
128.8720019 1
3.4%
128.871624 1
3.4%
128.8671953 1
3.4%

Interactions

2023-12-12T22:29:28.316456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:29:28.070632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:29:28.459147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:29:28.195129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:29:31.912642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명업종소재지주소신고일위도경도
업체명1.0000.0001.0000.9901.0001.000
업종0.0001.0000.0000.0000.0000.252
소재지주소1.0000.0001.0000.9901.0001.000
신고일0.9900.0000.9901.0000.9930.972
위도1.0000.0001.0000.9931.0000.743
경도1.0000.2521.0000.9720.7431.000
2023-12-12T22:29:32.037795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도업종
위도1.000-0.0440.000
경도-0.0441.0000.127
업종0.0000.1271.000

Missing values

2023-12-12T22:29:29.008449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:29:29.182875image/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

업체명업종소재지주소신고일위도경도
0(주)경부공영산림골재채취업경상남도 김해시 상동면 동북로437번길 83-431995-02-1135.3079128.963799
1(주)경부공영골재선별·파쇄업경상남도 김해시 상동면 동북로437번길 83-432018-01-3035.3079128.963799
2(주)동남산림골재채취업경상남도 김해시 주촌면 서부로 1701번안길 58-931998-02-0435.245434128.839412
3(주)동남골재선별·파쇄업경상남도 김해시 주촌면 서부로 1701번안길 58-932020-07-0735.245434128.839412
4(주)대동하이텍산림골재채취업경상남도 김해시 호계로 435, 케이타운빌딩 2층(부원동)2000-08-1835.229237128.884704
5(주)대동하이텍골재선별·파쇄업경상남도 김해시 호계로 435, 케이타운빌딩 2층(부원동)2021-03-2935.229237128.884704
6금광개발(주)골재선별·파쇄업경상남도 김해시 주촌면 원지리 산 752005-02-1635.264444128.844521
7금광개발(주)산림골재채취업경상남도 김해시 주촌면 원지리 산 752005-10-0435.264444128.844521
8진성건설(주)골재선별·파쇄업경상남도 김해시내외중앙로89, 메디존빌딩 301호2007-03-2035.237875128.866955
9㈜지석에이앤씨골재선별·파쇄업경상남도 김해시 진영읍 본산로 702015-02-0435.310823128.742701
업체명업종소재지주소신고일위도경도
19삼계개발(주)산림골재채취업경상남도 김해시해반천로130번길39,코아루센텀오피스텔207호2020-05-2835.260367128.871624
20지유앤주식회사산림골재채취업경상남도 김해시 상동면 상동로 680-772020-11-0635.310282128.944132
21지유앤주식회사골재선별·파쇄업경상남도 김해시 상동면 상동로 680-772020-12-1535.310282128.944132
22에코종합건설(주)산림골재채취업경상남도 김해시 주촌면 골든루트로 103-112020-11-1935.214058128.82861
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