Overview

Dataset statistics

Number of variables7
Number of observations23
Missing cells6
Missing cells (%)3.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory62.6 B

Variable types

Text3
Categorical3
Numeric1

Dataset

Description경상남도 의령군에 소재한 폐기물처리업체 정보를 제공하는 데이터 입니다. 사업장 상호와 업종, 허가연도, 사업장 전화번호, 사업장 분류 정보를 제공합니다.
Author경상남도 의령군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15099443

Alerts

데이터기준일 has constant value ""Constant
허가연도 is highly overall correlated with 업종 and 1 other fieldsHigh correlation
업종 is highly overall correlated with 허가연도 and 1 other fieldsHigh correlation
분류 is highly overall correlated with 허가연도 and 1 other fieldsHigh correlation
전화번호 has 6 (26.1%) missing valuesMissing

Reproduction

Analysis started2024-04-20 13:56:31.359386
Analysis finished2024-04-20 13:56:33.857764
Duration2.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장 상호
Text

Distinct19
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size312.0 B
2024-04-20T22:56:34.365774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length5.3043478
Min length3

Characters and Unicode

Total characters122
Distinct characters58
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)73.9%

Sample

1st row㈜청도산업
2nd row㈜화림테크
3rd row봉수산업㈜
4th row일진산업
5th row미래에코
ValueCountFrequency (%)
동부환경 3
 
13.0%
청호환경산업㈜ 3
 
13.0%
㈜열방 1
 
4.3%
㈜청도산업 1
 
4.3%
토산실업㈜ 1
 
4.3%
문경운수 1
 
4.3%
㈜수경유조 1
 
4.3%
㈜영남환경 1
 
4.3%
㈜탑리사이클링 1
 
4.3%
삼정알텍 1
 
4.3%
Other values (9) 9
39.1%
2024-04-20T22:56:35.494840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 14
 
11.5%
경 9
 
7.4%
산 9
 
7.4%
업 8
 
6.6%
환 7
 
5.7%
청 4
 
3.3%
부 4
 
3.3%
수 4
 
3.3%
동 3
 
2.5%
호 3
 
2.5%
Other values (48) 57
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107
87.7%
Other Symbol 14
 
11.5%
Space Separator 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 9
 
8.4%
산 9
 
8.4%
업 8
 
7.5%
환 7
 
6.5%
청 4
 
3.7%
부 4
 
3.7%
수 4
 
3.7%
동 3
 
2.8%
호 3
 
2.8%
림 3
 
2.8%
Other values (46) 53
49.5%
Other Symbol
ValueCountFrequency (%)
㈜ 14
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 121
99.2%
Common 1
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 14
 
11.6%
경 9
 
7.4%
산 9
 
7.4%
업 8
 
6.6%
환 7
 
5.8%
청 4
 
3.3%
부 4
 
3.3%
수 4
 
3.3%
동 3
 
2.5%
호 3
 
2.5%
Other values (47) 56
46.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 107
87.7%
None 14
 
11.5%
ASCII 1
 
0.8%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 14
100.0%
Hangul
ValueCountFrequency (%)
경 9
 
8.4%
산 9
 
8.4%
업 8
 
7.5%
환 7
 
6.5%
청 4
 
3.7%
부 4
 
3.7%
수 4
 
3.7%
동 3
 
2.8%
호 3
 
2.8%
림 3
 
2.8%
Other values (46) 53
49.5%
ASCII
ValueCountFrequency (%)
1
100.0%

업종
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size312.0 B
폐기물처리업
14 
폐기물수집운반업
7 
건설폐기물중간재활용업
2 

Length

Max length11
Median length6
Mean length7.0434783
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐기물처리업 14
60.9%
폐기물수집운반업 7
30.4%
건설폐기물중간재활용업 2
 
8.7%

Length

2024-04-20T22:56:35.917046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:56:36.224012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐기물처리업 14
60.9%
폐기물수집운반업 7
30.4%
건설폐기물중간재활용업 2
 
8.7%

허가연도
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.5217
Minimum2007
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size335.0 B
2024-04-20T22:56:36.383570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2007.4
Q12012
median2013
Q32017.5
95-th percentile2021.8
Maximum2022
Range15
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation4.1764444
Coefficient of variation (CV)0.0020731692
Kurtosis-0.42602375
Mean2014.5217
Median Absolute Deviation (MAD)2
Skewness0.22285084
Sum46334
Variance17.442688
MonotonicityNot monotonic
2024-04-20T22:56:36.576508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2012 5
21.7%
2013 5
21.7%
2007 2
 
8.7%
2016 2
 
8.7%
2020 2
 
8.7%
2022 2
 
8.7%
2018 1
 
4.3%
2011 1
 
4.3%
2014 1
 
4.3%
2017 1
 
4.3%
ValueCountFrequency (%)
2007 2
 
8.7%
2011 1
 
4.3%
2012 5
21.7%
2013 5
21.7%
2014 1
 
4.3%
2016 2
 
8.7%
2017 1
 
4.3%
2018 1
 
4.3%
2019 1
 
4.3%
2020 2
 
8.7%
ValueCountFrequency (%)
2022 2
 
8.7%
2020 2
 
8.7%
2019 1
 
4.3%
2018 1
 
4.3%
2017 1
 
4.3%
2016 2
 
8.7%
2014 1
 
4.3%
2013 5
21.7%
2012 5
21.7%
2011 1
 
4.3%

소재지 도로명주소
Text

Distinct18
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size312.0 B
2024-04-20T22:56:37.308780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length19.782609
Min length16

Characters and Unicode

Total characters455
Distinct characters43
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

Unique14 ?
Unique (%)60.9%

Sample

1st row경남 의령군 정곡면 법정로 563
2nd row경남 의령군 정곡면 의합대로 986
3rd row경남 의령군 봉수면 직금로 298
4th row경남 의령군 부림면 의합대로 2012-6
5th row경남 의령군 부림면 신번로 41-16
ValueCountFrequency (%)
경남 23
20.4%
의령군 22
19.5%
의합대로 7
 
6.2%
정곡면 5
 
4.4%
용덕면 5
 
4.4%
유곡면 4
 
3.5%
함의로 4
 
3.5%
2236 3
 
2.7%
의령읍 3
 
2.7%
부림면 3
 
2.7%
Other values (28) 34
30.1%
2024-04-20T22:56:38.340435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90
19.8%
의 37
 
8.1%
령 26
 
5.7%
남 24
 
5.3%
경 23
 
5.1%
군 23
 
5.1%
로 21
 
4.6%
면 20
 
4.4%
1 20
 
4.4%
2 20
 
4.4%
Other values (33) 151
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 265
58.2%
Space Separator 90
 
19.8%
Decimal Number 90
 
19.8%
Dash Punctuation 10
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 37
14.0%
령 26
9.8%
남 24
 
9.1%
경 23
 
8.7%
군 23
 
8.7%
로 21
 
7.9%
면 20
 
7.5%
정 11
 
4.2%
곡 9
 
3.4%
덕 7
 
2.6%
Other values (21) 64
24.2%
Decimal Number
ValueCountFrequency (%)
1 20
22.2%
2 20
22.2%
6 11
12.2%
7 10
11.1%
9 7
 
7.8%
3 7
 
7.8%
8 6
 
6.7%
5 4
 
4.4%
0 3
 
3.3%
4 2
 
2.2%
Space Separator
ValueCountFrequency (%)
90
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 265
58.2%
Common 190
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 37
14.0%
령 26
9.8%
남 24
 
9.1%
경 23
 
8.7%
군 23
 
8.7%
로 21
 
7.9%
면 20
 
7.5%
정 11
 
4.2%
곡 9
 
3.4%
덕 7
 
2.6%
Other values (21) 64
24.2%
Common
ValueCountFrequency (%)
90
47.4%
1 20
 
10.5%
2 20
 
10.5%
6 11
 
5.8%
7 10
 
5.3%
- 10
 
5.3%
9 7
 
3.7%
3 7
 
3.7%
8 6
 
3.2%
5 4
 
2.1%
Other values (2) 5
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 265
58.2%
ASCII 190
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
90
47.4%
1 20
 
10.5%
2 20
 
10.5%
6 11
 
5.8%
7 10
 
5.3%
- 10
 
5.3%
9 7
 
3.7%
3 7
 
3.7%
8 6
 
3.2%
5 4
 
2.1%
Other values (2) 5
 
2.6%
Hangul
ValueCountFrequency (%)
의 37
14.0%
령 26
9.8%
남 24
 
9.1%
경 23
 
8.7%
군 23
 
8.7%
로 21
 
7.9%
면 20
 
7.5%
정 11
 
4.2%
곡 9
 
3.4%
덕 7
 
2.6%
Other values (21) 64
24.2%

전화번호
Text

MISSING 

Distinct14
Distinct (%)82.4%
Missing6
Missing (%)26.1%
Memory size312.0 B
2024-04-20T22:56:38.973146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters204
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)70.6%

Sample

1st row055-574-9990
2nd row055-574-8756
3rd row055-574-5500
4th row055-573-0991
5th row055-572-3020
ValueCountFrequency (%)
055-572-2424 3
17.6%
055-574-3449 2
11.8%
055-574-9990 1
 
5.9%
055-574-8756 1
 
5.9%
055-574-5500 1
 
5.9%
055-573-0991 1
 
5.9%
055-572-3020 1
 
5.9%
055-572-0230 1
 
5.9%
055-573-5507 1
 
5.9%
055-573-9711 1
 
5.9%
Other values (4) 4
23.5%
2024-04-20T22:56:40.082728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 56
27.5%
- 34
16.7%
0 29
14.2%
7 22
 
10.8%
4 20
 
9.8%
2 14
 
6.9%
3 10
 
4.9%
9 9
 
4.4%
1 5
 
2.5%
8 3
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 170
83.3%
Dash Punctuation 34
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 56
32.9%
0 29
17.1%
7 22
 
12.9%
4 20
 
11.8%
2 14
 
8.2%
3 10
 
5.9%
9 9
 
5.3%
1 5
 
2.9%
8 3
 
1.8%
6 2
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 204
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 56
27.5%
- 34
16.7%
0 29
14.2%
7 22
 
10.8%
4 20
 
9.8%
2 14
 
6.9%
3 10
 
4.9%
9 9
 
4.4%
1 5
 
2.5%
8 3
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 204
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 56
27.5%
- 34
16.7%
0 29
14.2%
7 22
 
10.8%
4 20
 
9.8%
2 14
 
6.9%
3 10
 
4.9%
9 9
 
4.4%
1 5
 
2.5%
8 3
 
1.5%

분류
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size312.0 B
폐기물종합재활용업
9 
폐기물중간재활용업
4 
사업장배출시설계수집운반업
3 
건설폐기물중간재활용업
2 
사업장배출시설계수집운반
2 
Other values (3)
3 

Length

Max length13
Median length9
Mean length10.26087
Min length9

Unique

Unique3 ?
Unique (%)13.0%

Sample

1st row폐기물중간재활용업
2nd row폐기물종합재활용업
3rd row폐기물 종합재활용업
4th row폐기물종합재활용업
5th row폐기물종합재활용업

Common Values

ValueCountFrequency (%)
폐기물종합재활용업 9
39.1%
폐기물중간재활용업 4
17.4%
사업장배출시설계수집운반업 3
 
13.0%
건설폐기물중간재활용업 2
 
8.7%
사업장배출시설계수집운반 2
 
8.7%
폐기물 종합재활용업 1
 
4.3%
사업장생활계수집운반업 1
 
4.3%
사업장생활계폐기물수집운반 1
 
4.3%

Length

2024-04-20T22:56:40.544037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:56:40.888681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐기물종합재활용업 9
37.5%
폐기물중간재활용업 4
16.7%
사업장배출시설계수집운반업 3
 
12.5%
건설폐기물중간재활용업 2
 
8.3%
사업장배출시설계수집운반 2
 
8.3%
폐기물 1
 
4.2%
종합재활용업 1
 
4.2%
사업장생활계수집운반업 1
 
4.2%
사업장생활계폐기물수집운반 1
 
4.2%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size312.0 B
2022-03-18
23 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-03-18
2nd row2022-03-18
3rd row2022-03-18
4th row2022-03-18
5th row2022-03-18

Common Values

ValueCountFrequency (%)
2022-03-18 23
100.0%

Length

2024-04-20T22:56:41.180206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-20T22:56:41.388820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-03-18 23
100.0%

Interactions

2024-04-20T22:56:32.862407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-20T22:56:41.728364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장 상호업종허가연도소재지 도로명주소전화번호분류
사업장 상호1.0000.0000.0000.9841.0000.000
업종0.0001.0000.8010.5870.0001.000
허가연도0.0000.8011.0000.0000.3050.943
소재지 도로명주소0.9840.5870.0001.0000.9930.000
전화번호1.0000.0000.3050.9931.0000.000
분류0.0001.0000.9430.0000.0001.000
2024-04-20T22:56:41.904907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류업종
분류1.0000.866
업종0.8661.000
2024-04-20T22:56:42.044576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가연도업종분류
허가연도1.0000.5650.580
업종0.5651.0000.866
분류0.5800.8661.000

Missing values

2024-04-20T22:56:33.220863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-20T22:56:33.702083image/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

사업장 상호업종허가연도소재지 도로명주소전화번호분류데이터기준일
0㈜청도산업폐기물처리업2007경남 의령군 정곡면 법정로 563055-574-9990폐기물중간재활용업2022-03-18
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