Overview

Dataset statistics

Number of variables11
Number of observations64
Missing cells4
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory93.1 B

Variable types

Text5
Categorical3
Numeric3

Dataset

Description경기도 수원시 폐기물처리업체 명칭, 업종구분, 대표자명, 허가연도, 취급품목, 소재지도로명주소, 소재지지번주소, 위도, 경도, 연락처 정보를 포함합니다
URLhttps://www.data.go.kr/data/15051575/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
업종 is highly overall correlated with 취급품목High correlation
취급품목 is highly overall correlated with 업종High correlation
전화번호 has 4 (6.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 15:51:32.619435
Analysis finished2023-12-12 15:51:34.866389
Duration2.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호명
Text

Distinct61
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size644.0 B
2023-12-13T00:51:35.097051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.296875
Min length2

Characters and Unicode

Total characters339
Distinct characters107
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

Unique58 ?
Unique (%)90.6%

Sample

1st row삼아건설㈜
2nd row백상기업㈜
3rd row고려개발㈜
4th row삼환환경(주)
5th row삼명자원
ValueCountFrequency (%)
고려개발㈜ 2
 
3.1%
백상기업㈜ 2
 
3.1%
삼환환경㈜ 2
 
3.1%
㈜아스테크 1
 
1.5%
㈜비에스 1
 
1.5%
주)용호산업 1
 
1.5%
삼아건설㈜ 1
 
1.5%
다우개발㈜ 1
 
1.5%
태양환경개발㈜ 1
 
1.5%
용문산업㈜ 1
 
1.5%
Other values (52) 52
80.0%
2023-12-13T00:51:35.590955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 46
 
13.6%
환 23
 
6.8%
경 20
 
5.9%
업 11
 
3.2%
스 8
 
2.4%
원 8
 
2.4%
개 8
 
2.4%
발 8
 
2.4%
건 8
 
2.4%
삼 7
 
2.1%
Other values (97) 192
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 286
84.4%
Other Symbol 46
 
13.6%
Open Punctuation 3
 
0.9%
Close Punctuation 3
 
0.9%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
환 23
 
8.0%
경 20
 
7.0%
업 11
 
3.8%
스 8
 
2.8%
원 8
 
2.8%
개 8
 
2.8%
발 8
 
2.8%
건 8
 
2.8%
삼 7
 
2.4%
이 7
 
2.4%
Other values (93) 178
62.2%
Other Symbol
ValueCountFrequency (%)
㈜ 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 332
97.9%
Common 7
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 46
 
13.9%
환 23
 
6.9%
경 20
 
6.0%
업 11
 
3.3%
스 8
 
2.4%
원 8
 
2.4%
개 8
 
2.4%
발 8
 
2.4%
건 8
 
2.4%
삼 7
 
2.1%
Other values (94) 185
55.7%
Common
ValueCountFrequency (%)
( 3
42.9%
) 3
42.9%
1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 286
84.4%
None 46
 
13.6%
ASCII 7
 
2.1%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 46
100.0%
Hangul
ValueCountFrequency (%)
환 23
 
8.0%
경 20
 
7.0%
업 11
 
3.8%
스 8
 
2.8%
원 8
 
2.8%
개 8
 
2.8%
발 8
 
2.8%
건 8
 
2.8%
삼 7
 
2.4%
이 7
 
2.4%
Other values (93) 178
62.2%
ASCII
ValueCountFrequency (%)
( 3
42.9%
) 3
42.9%
1
 
14.3%

업종
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size644.0 B
건설폐기물수집운반업
29 
사업장배출시설계폐기물 수집운반업
15 
사업장비배출시설계폐기물 수집운반업
13 
폐기물재활용업
4 
건설폐기물중간처리업
3 

Length

Max length18
Median length17.5
Mean length13.078125
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사업장배출시설계폐기물 수집운반업
2nd row사업장배출시설계폐기물 수집운반업
3rd row사업장배출시설계폐기물 수집운반업
4th row사업장배출시설계폐기물 수집운반업
5th row사업장배출시설계폐기물 수집운반업

Common Values

ValueCountFrequency (%)
건설폐기물수집운반업 29
45.3%
사업장배출시설계폐기물 수집운반업 15
23.4%
사업장비배출시설계폐기물 수집운반업 13
20.3%
폐기물재활용업 4
 
6.2%
건설폐기물중간처리업 3
 
4.7%

Length

2023-12-13T00:51:35.766906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:51:35.905211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건설폐기물수집운반업 29
31.5%
수집운반업 28
30.4%
사업장배출시설계폐기물 15
16.3%
사업장비배출시설계폐기물 13
14.1%
폐기물재활용업 4
 
4.3%
건설폐기물중간처리업 3
 
3.3%

대표자명
Text

Distinct60
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size644.0 B
2023-12-13T00:51:36.218891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0625
Min length2

Characters and Unicode

Total characters196
Distinct characters79
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

Unique57 ?
Unique (%)89.1%

Sample

1st row박대용
2nd row민병곤
3rd row최경숙
4th row강재성
5th row류오상
ValueCountFrequency (%)
강재성 3
 
4.7%
민병곤 2
 
3.1%
최경숙 2
 
3.1%
이건욱 1
 
1.6%
김희경 1
 
1.6%
김용석 1
 
1.6%
위영미 1
 
1.6%
최인규 1
 
1.6%
김지선 1
 
1.6%
전소영 1
 
1.6%
Other values (50) 50
78.1%
2023-12-13T00:51:36.683989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 15
 
7.7%
영 12
 
6.1%
경 8
 
4.1%
이 8
 
4.1%
최 6
 
3.1%
숙 6
 
3.1%
박 6
 
3.1%
강 5
 
2.6%
윤 5
 
2.6%
신 5
 
2.6%
Other values (69) 120
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 195
99.5%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 15
 
7.7%
영 12
 
6.2%
경 8
 
4.1%
이 8
 
4.1%
최 6
 
3.1%
숙 6
 
3.1%
박 6
 
3.1%
강 5
 
2.6%
윤 5
 
2.6%
신 5
 
2.6%
Other values (68) 119
61.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 195
99.5%
Common 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 15
 
7.7%
영 12
 
6.2%
경 8
 
4.1%
이 8
 
4.1%
최 6
 
3.1%
숙 6
 
3.1%
박 6
 
3.1%
강 5
 
2.6%
윤 5
 
2.6%
신 5
 
2.6%
Other values (68) 119
61.0%
Common
ValueCountFrequency (%)
, 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 195
99.5%
ASCII 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 15
 
7.7%
영 12
 
6.2%
경 8
 
4.1%
이 8
 
4.1%
최 6
 
3.1%
숙 6
 
3.1%
박 6
 
3.1%
강 5
 
2.6%
윤 5
 
2.6%
신 5
 
2.6%
Other values (68) 119
61.0%
ASCII
ValueCountFrequency (%)
, 1
100.0%

허가연도
Real number (ℝ)

Distinct20
Distinct (%)31.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.2031
Minimum1997
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T00:51:36.867937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1997
5-th percentile1998
Q12010.75
median2015
Q32017.25
95-th percentile2020.85
Maximum2023
Range26
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation6.5808276
Coefficient of variation (CV)0.0032688344
Kurtosis0.49085529
Mean2013.2031
Median Absolute Deviation (MAD)3
Skewness-1.0452091
Sum128845
Variance43.307292
MonotonicityNot monotonic
2023-12-13T00:51:37.012182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
2014 10
15.6%
2019 7
10.9%
2015 6
 
9.4%
2016 6
 
9.4%
2017 5
 
7.8%
2013 3
 
4.7%
2023 3
 
4.7%
2008 3
 
4.7%
2003 3
 
4.7%
1998 3
 
4.7%
Other values (10) 15
23.4%
ValueCountFrequency (%)
1997 2
3.1%
1998 3
4.7%
2003 3
4.7%
2005 1
 
1.6%
2006 2
3.1%
2007 1
 
1.6%
2008 3
4.7%
2010 1
 
1.6%
2011 1
 
1.6%
2012 1
 
1.6%
ValueCountFrequency (%)
2023 3
 
4.7%
2021 1
 
1.6%
2020 2
 
3.1%
2019 7
10.9%
2018 3
 
4.7%
2017 5
7.8%
2016 6
9.4%
2015 6
9.4%
2014 10
15.6%
2013 3
 
4.7%

취급품목
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)45.3%
Missing0
Missing (%)0.0%
Memory size644.0 B
폐콘크리트+폐아스콘+폐벽돌+폐블럭+폐기와+폐목재+폐합성수지+폐섬유+폐벽지+건설오니+폐금속류+폐유리+폐타일및폐도자기+폐보드류+폐판넬+건설폐토석+혼합건설폐기물+기타
17 
음식물류폐기물
7 
폐콘크리트+폐아스콘+폐벽돌+폐블럭+폐기와+폐목재+폐합성수지+폐섬유+폐벽지+건설오니+폐금속류+폐유리+폐타일및폐도자기+폐보드류+폐판넬+건설폐토석+혼합건설폐기물
7 
폐콘크리트+폐아스콘+폐벽돌+폐블럭+폐기와+폐목재+폐합성수지+폐섬유+폐벽지+건설오니+폐금속류+폐유리+건설폐토석+혼합건설폐기물
5 
폐합성수지류
 
2
Other values (24)
26 

Length

Max length89
Median length72
Mean length49.078125
Min length4

Unique

Unique22 ?
Unique (%)34.4%

Sample

1st row하순준설토
2nd row배출시설계폐기물
3rd row배출시설계폐기물
4th row폐합성수지+폐목재+고철+그밖의폐기물
5th row폐합성수지류

Common Values

ValueCountFrequency (%)
폐콘크리트+폐아스콘+폐벽돌+폐블럭+폐기와+폐목재+폐합성수지+폐섬유+폐벽지+건설오니+폐금속류+폐유리+폐타일및폐도자기+폐보드류+폐판넬+건설폐토석+혼합건설폐기물+기타 17
26.6%
음식물류폐기물 7
 
10.9%
폐콘크리트+폐아스콘+폐벽돌+폐블럭+폐기와+폐목재+폐합성수지+폐섬유+폐벽지+건설오니+폐금속류+폐유리+폐타일및폐도자기+폐보드류+폐판넬+건설폐토석+혼합건설폐기물 7
 
10.9%
폐콘크리트+폐아스콘+폐벽돌+폐블럭+폐기와+폐목재+폐합성수지+폐섬유+폐벽지+건설오니+폐금속류+폐유리+건설폐토석+혼합건설폐기물 5
 
7.8%
폐합성수지류 2
 
3.1%
폐합성수지류+폐합성고무류+폐목재류+폐섬유 2
 
3.1%
배출시설계폐기물 2
 
3.1%
폐식용유+그밖의식물성잔재물+음식물류폐기물처리잔재물 1
 
1.6%
폐합성고분자화합물+오니류+분진류+소각재+폐목재류+폐토사류 1
 
1.6%
폐합성수지류+임목폐목재 1
 
1.6%
Other values (19) 19
29.7%

Length

2023-12-13T00:51:37.169075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
폐콘크리트+폐아스콘+폐벽돌+폐블럭+폐기와+폐목재+폐합성수지+폐섬유+폐벽지+건설오니+폐금속류+폐유리+폐타일및폐도자기+폐보드류+폐판넬+건설폐토석+혼합건설폐기물+기타 17
26.6%
폐콘크리트+폐아스콘+폐벽돌+폐블럭+폐기와+폐목재+폐합성수지+폐섬유+폐벽지+건설오니+폐금속류+폐유리+폐타일및폐도자기+폐보드류+폐판넬+건설폐토석+혼합건설폐기물 7
 
10.9%
음식물류폐기물 7
 
10.9%
폐콘크리트+폐아스콘+폐벽돌+폐블럭+폐기와+폐목재+폐합성수지+폐섬유+폐벽지+건설오니+폐금속류+폐유리+건설폐토석+혼합건설폐기물 5
 
7.8%
폐합성수지류 2
 
3.1%
폐합성수지류+폐합성고무류+폐목재류+폐섬유 2
 
3.1%
배출시설계폐기물 2
 
3.1%
폐콘크리트+폐아스콘+폐벽돌+폐기와+폐목재+폐합성수지+폐섬유+폐벽지+폐유리+폐타일및폐도자기+폐보드류+폐판넬+건설폐토석+혼합건설폐기물 1
 
1.6%
폐합성수지+임목폐목재 1
 
1.6%
음식물류 1
 
1.6%
Other values (19) 19
29.7%

소재지도로명주소
Text

Distinct54
Distinct (%)84.4%
Missing0
Missing (%)0.0%
Memory size644.0 B
2023-12-13T00:51:37.500678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length22.5625
Min length18

Characters and Unicode

Total characters1444
Distinct characters72
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

Unique48 ?
Unique (%)75.0%

Sample

1st row경기도 수원시 권선구 곡선로 42
2nd row경기도 수원시 권선구 서수원로63번길 139
3rd row경기도 수원시 권선구 매송고색로 848
4th row경기도 수원시 권선구 삼천병마로 1519
5th row경기도 수원시 권선구 매송고색로804번길 54
ValueCountFrequency (%)
경기도 64
20.0%
수원시 64
20.0%
권선구 37
 
11.6%
팔달구 11
 
3.4%
영통구 9
 
2.8%
장안구 6
 
1.9%
권선로 5
 
1.6%
308-18 5
 
1.6%
정조로 5
 
1.6%
수성로 4
 
1.2%
Other values (92) 110
34.4%
2023-12-13T00:51:38.014316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
256
17.7%
수 78
 
5.4%
원 72
 
5.0%
경 69
 
4.8%
구 65
 
4.5%
도 64
 
4.4%
시 64
 
4.4%
로 64
 
4.4%
기 64
 
4.4%
1 54
 
3.7%
Other values (62) 594
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 867
60.0%
Decimal Number 282
 
19.5%
Space Separator 256
 
17.7%
Dash Punctuation 29
 
2.0%
Close Punctuation 4
 
0.3%
Open Punctuation 4
 
0.3%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 78
 
9.0%
원 72
 
8.3%
경 69
 
8.0%
구 65
 
7.5%
도 64
 
7.4%
시 64
 
7.4%
로 64
 
7.4%
기 64
 
7.4%
권 45
 
5.2%
선 44
 
5.1%
Other values (47) 238
27.5%
Decimal Number
ValueCountFrequency (%)
1 54
19.1%
2 38
13.5%
3 36
12.8%
5 27
9.6%
9 24
8.5%
4 24
8.5%
8 23
8.2%
6 22
7.8%
0 18
 
6.4%
7 16
 
5.7%
Space Separator
ValueCountFrequency (%)
256
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 867
60.0%
Common 577
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 78
 
9.0%
원 72
 
8.3%
경 69
 
8.0%
구 65
 
7.5%
도 64
 
7.4%
시 64
 
7.4%
로 64
 
7.4%
기 64
 
7.4%
권 45
 
5.2%
선 44
 
5.1%
Other values (47) 238
27.5%
Common
ValueCountFrequency (%)
256
44.4%
1 54
 
9.4%
2 38
 
6.6%
3 36
 
6.2%
- 29
 
5.0%
5 27
 
4.7%
9 24
 
4.2%
4 24
 
4.2%
8 23
 
4.0%
6 22
 
3.8%
Other values (5) 44
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 867
60.0%
ASCII 577
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
256
44.4%
1 54
 
9.4%
2 38
 
6.6%
3 36
 
6.2%
- 29
 
5.0%
5 27
 
4.7%
9 24
 
4.2%
4 24
 
4.2%
8 23
 
4.0%
6 22
 
3.8%
Other values (5) 44
 
7.6%
Hangul
ValueCountFrequency (%)
수 78
 
9.0%
원 72
 
8.3%
경 69
 
8.0%
구 65
 
7.5%
도 64
 
7.4%
시 64
 
7.4%
로 64
 
7.4%
기 64
 
7.4%
권 45
 
5.2%
선 44
 
5.1%
Other values (47) 238
27.5%

소재지지번주소
Text

Distinct52
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Memory size644.0 B
2023-12-13T00:51:38.341199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length20.921875
Min length17

Characters and Unicode

Total characters1339
Distinct characters56
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

Unique44 ?
Unique (%)68.8%

Sample

1st row경기도 수원시 권선구 곡반정동 564-5
2nd row경기도 수원시 권선구 오목천동 885
3rd row경기도 수원시 권선구 평동 53
4th row경기도 수원시 권선구 오목천동 415-3
5th row경기도 수원시 권선구 고색동 114-5
ValueCountFrequency (%)
경기도 64
20.0%
수원시 64
20.0%
권선구 38
 
11.9%
팔달구 11
 
3.4%
고색동 10
 
3.1%
영통구 9
 
2.8%
장안구 6
 
1.9%
곡반정동 6
 
1.9%
오목천동 5
 
1.6%
986 5
 
1.6%
Other values (69) 102
31.9%
2023-12-13T00:51:38.800671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
256
19.1%
구 67
 
5.0%
원 66
 
4.9%
경 64
 
4.8%
도 64
 
4.8%
수 64
 
4.8%
시 64
 
4.8%
동 64
 
4.8%
기 64
 
4.8%
1 54
 
4.0%
Other values (46) 512
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 775
57.9%
Decimal Number 258
 
19.3%
Space Separator 256
 
19.1%
Dash Punctuation 50
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 67
 
8.6%
원 66
 
8.5%
경 64
 
8.3%
도 64
 
8.3%
수 64
 
8.3%
시 64
 
8.3%
동 64
 
8.3%
기 64
 
8.3%
권 41
 
5.3%
선 41
 
5.3%
Other values (34) 176
22.7%
Decimal Number
ValueCountFrequency (%)
1 54
20.9%
6 33
12.8%
3 33
12.8%
4 31
12.0%
5 24
9.3%
8 22
8.5%
9 21
 
8.1%
2 21
 
8.1%
0 10
 
3.9%
7 9
 
3.5%
Space Separator
ValueCountFrequency (%)
256
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 775
57.9%
Common 564
42.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 67
 
8.6%
원 66
 
8.5%
경 64
 
8.3%
도 64
 
8.3%
수 64
 
8.3%
시 64
 
8.3%
동 64
 
8.3%
기 64
 
8.3%
권 41
 
5.3%
선 41
 
5.3%
Other values (34) 176
22.7%
Common
ValueCountFrequency (%)
256
45.4%
1 54
 
9.6%
- 50
 
8.9%
6 33
 
5.9%
3 33
 
5.9%
4 31
 
5.5%
5 24
 
4.3%
8 22
 
3.9%
9 21
 
3.7%
2 21
 
3.7%
Other values (2) 19
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 775
57.9%
ASCII 564
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
256
45.4%
1 54
 
9.6%
- 50
 
8.9%
6 33
 
5.9%
3 33
 
5.9%
4 31
 
5.5%
5 24
 
4.3%
8 22
 
3.9%
9 21
 
3.7%
2 21
 
3.7%
Other values (2) 19
 
3.4%
Hangul
ValueCountFrequency (%)
구 67
 
8.6%
원 66
 
8.5%
경 64
 
8.3%
도 64
 
8.3%
수 64
 
8.3%
시 64
 
8.3%
동 64
 
8.3%
기 64
 
8.3%
권 41
 
5.3%
선 41
 
5.3%
Other values (34) 176
22.7%

위도
Real number (ℝ)

Distinct51
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.262997
Minimum37.231777
Maximum37.317295
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T00:51:39.016634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.231777
5-th percentile37.234051
Q137.251684
median37.258181
Q337.281002
95-th percentile37.292334
Maximum37.317295
Range0.08551869
Interquartile range (IQR)0.029318683

Descriptive statistics

Standard deviation0.020361174
Coefficient of variation (CV)0.00054641805
Kurtosis-0.48054148
Mean37.262997
Median Absolute Deviation (MAD)0.01827824
Skewness0.36348289
Sum2384.8318
Variance0.0004145774
MonotonicityNot monotonic
2023-12-13T00:51:39.187149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.25407432 5
 
7.8%
37.23838976 3
 
4.7%
37.28183425 3
 
4.7%
37.25629262 2
 
3.1%
37.23449452 2
 
3.1%
37.23177664 2
 
3.1%
37.25746965 2
 
3.1%
37.28765818 2
 
3.1%
37.23832133 1
 
1.6%
37.26737442 1
 
1.6%
Other values (41) 41
64.1%
ValueCountFrequency (%)
37.23177664 2
3.1%
37.23383208 1
 
1.6%
37.23397223 1
 
1.6%
37.23449452 2
3.1%
37.23611243 1
 
1.6%
37.23638181 1
 
1.6%
37.23832133 1
 
1.6%
37.23838976 3
4.7%
37.23875446 1
 
1.6%
37.24465719 1
 
1.6%
ValueCountFrequency (%)
37.31729533 1
1.6%
37.30794956 1
1.6%
37.29260947 1
1.6%
37.29239163 1
1.6%
37.29200912 1
1.6%
37.29075725 1
1.6%
37.28904829 1
1.6%
37.28765818 2
3.1%
37.28684361 1
1.6%
37.28563289 1
1.6%

경도
Real number (ℝ)

Distinct51
Distinct (%)79.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.00759
Minimum126.95536
Maximum127.07746
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T00:51:39.377967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.95536
5-th percentile126.96274
Q1126.98538
median127.00685
Q3127.02882
95-th percentile127.06419
Maximum127.07746
Range0.1221047
Interquartile range (IQR)0.0434422

Descriptive statistics

Standard deviation0.030865056
Coefficient of variation (CV)0.00024301742
Kurtosis-0.5997618
Mean127.00759
Median Absolute Deviation (MAD)0.02147405
Skewness0.39773448
Sum8128.4856
Variance0.00095265168
MonotonicityNot monotonic
2023-12-13T00:51:39.610216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9853765 5
 
7.8%
126.9614085 3
 
4.7%
126.9887752 3
 
4.7%
126.9959876 2
 
3.1%
126.9886969 2
 
3.1%
126.9709396 2
 
3.1%
127.0165282 2
 
3.1%
127.0281642 2
 
3.1%
127.030719 1
 
1.6%
126.9773064 1
 
1.6%
Other values (41) 41
64.1%
ValueCountFrequency (%)
126.9553557 1
 
1.6%
126.9614085 3
4.7%
126.9702627 1
 
1.6%
126.9709279 1
 
1.6%
126.9709396 2
3.1%
126.9709584 1
 
1.6%
126.971791 1
 
1.6%
126.9719585 1
 
1.6%
126.9749722 1
 
1.6%
126.9773064 1
 
1.6%
ValueCountFrequency (%)
127.0774604 1
1.6%
127.0748967 1
1.6%
127.0700773 1
1.6%
127.064363 1
1.6%
127.063198 1
1.6%
127.0520945 1
1.6%
127.0520686 1
1.6%
127.0465496 1
1.6%
127.0407305 1
1.6%
127.0367453 1
1.6%

전화번호
Text

MISSING 

Distinct55
Distinct (%)91.7%
Missing4
Missing (%)6.2%
Memory size644.0 B
2023-12-13T00:51:39.916233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.033333
Min length12

Characters and Unicode

Total characters722
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

Unique52 ?
Unique (%)86.7%

Sample

1st row031-232-1703
2nd row031-292-4450
3rd row031-292-4500
4th row031-292-8644
5th row031-898-5327
ValueCountFrequency (%)
031-292-8644 4
 
6.7%
031-292-4450 2
 
3.3%
031-292-4500 2
 
3.3%
031-258-5723 1
 
1.7%
031-296-8900 1
 
1.7%
031-224-0079 1
 
1.7%
031-232-1703 1
 
1.7%
031-305-5882 1
 
1.7%
031-205-3944 1
 
1.7%
031-214-6667 1
 
1.7%
Other values (45) 45
75.0%
2023-12-13T00:51:40.340498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 120
16.6%
0 104
14.4%
2 102
14.1%
1 90
12.5%
3 84
11.6%
4 47
 
6.5%
8 42
 
5.8%
5 37
 
5.1%
7 36
 
5.0%
9 35
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 602
83.4%
Dash Punctuation 120
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 104
17.3%
2 102
16.9%
1 90
15.0%
3 84
14.0%
4 47
7.8%
8 42
7.0%
5 37
 
6.1%
7 36
 
6.0%
9 35
 
5.8%
6 25
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 722
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 120
16.6%
0 104
14.4%
2 102
14.1%
1 90
12.5%
3 84
11.6%
4 47
 
6.5%
8 42
 
5.8%
5 37
 
5.1%
7 36
 
5.0%
9 35
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 722
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 120
16.6%
0 104
14.4%
2 102
14.1%
1 90
12.5%
3 84
11.6%
4 47
 
6.5%
8 42
 
5.8%
5 37
 
5.1%
7 36
 
5.0%
9 35
 
4.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size644.0 B
2023-04-21
64 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-04-21
2nd row2023-04-21
3rd row2023-04-21
4th row2023-04-21
5th row2023-04-21

Common Values

ValueCountFrequency (%)
2023-04-21 64
100.0%

Length

2023-12-13T00:51:40.514342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:51:40.624914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-04-21 64
100.0%

Interactions

2023-12-13T00:51:34.170784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:51:33.323559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:51:33.611130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:51:34.252554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:51:33.411709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:51:33.689126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:51:34.345433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:51:33.521377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:51:33.771224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:51:40.710665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호명업종대표자명허가연도취급품목소재지도로명주소소재지지번주소위도경도전화번호
상호명1.0000.0001.0000.0000.9610.9980.9981.0001.0001.000
업종0.0001.0000.0000.7170.9120.2120.8350.5070.5700.000
대표자명1.0000.0001.0000.0000.7480.9980.9981.0001.0001.000
허가연도0.0000.7170.0001.0000.7580.0000.0000.0000.3690.000
취급품목0.9610.9120.7480.7581.0000.9830.9740.8160.7840.828
소재지도로명주소0.9980.2120.9980.0000.9831.0000.9991.0001.0000.995
소재지지번주소0.9980.8350.9980.0000.9740.9991.0001.0001.0000.995
위도1.0000.5071.0000.0000.8161.0001.0001.0000.7400.993
경도1.0000.5701.0000.3690.7841.0001.0000.7401.0000.981
전화번호1.0000.0001.0000.0000.8280.9950.9950.9930.9811.000
2023-12-13T00:51:40.880413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
취급품목업종
취급품목1.0000.548
업종0.5481.000
2023-12-13T00:51:40.971837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가연도위도경도업종취급품목
허가연도1.0000.2480.1760.3740.303
위도0.2481.0000.1150.2190.358
경도0.1760.1151.0000.2550.324
업종0.3740.2190.2551.0000.548
취급품목0.3030.3580.3240.5481.000

Missing values

2023-12-13T00:51:34.513316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:51:34.734724image/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

상호명업종대표자명허가연도취급품목소재지도로명주소소재지지번주소위도경도전화번호데이터기준일자
0삼아건설㈜사업장배출시설계폐기물 수집운반업박대용2007하순준설토경기도 수원시 권선구 곡선로 42경기도 수원시 권선구 곡반정동 564-537.238321127.030719031-232-17032023-04-21
1백상기업㈜사업장배출시설계폐기물 수집운반업민병곤2008배출시설계폐기물경기도 수원시 권선구 서수원로63번길 139경기도 수원시 권선구 오목천동 88537.231777126.97094031-292-44502023-04-21
2고려개발㈜사업장배출시설계폐기물 수집운반업최경숙2008배출시설계폐기물경기도 수원시 권선구 매송고색로 848경기도 수원시 권선구 평동 5337.256293126.995988031-292-45002023-04-21
3삼환환경(주)사업장배출시설계폐기물 수집운반업강재성2008폐합성수지+폐목재+고철+그밖의폐기물경기도 수원시 권선구 삼천병마로 1519경기도 수원시 권선구 오목천동 415-337.23839126.961409031-292-86442023-04-21
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7코스모스환경사업장배출시설계폐기물 수집운반업박영기2014폐합성수지류+폐합성고무류+폐목재류+폐섬유경기도 수원시 영통구 삼성로 274경기도 수원시 영통구 원천동 332-237.265613127.064363031-222-29722023-04-21
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상호명업종대표자명허가연도취급품목소재지도로명주소소재지지번주소위도경도전화번호데이터기준일자
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59삼환환경㈜건설폐기물중간처리업강재성1998폐콘크리트+폐아스콘+폐벽돌+폐블럭+폐기와+폐목재+폐합성수지+폐섬유+폐벽지+건설오니+폐금속류+폐유리+폐타일및폐도자기+폐보드류+폐판넬+건설폐토석+혼합건설폐기물경기도 수원시 권선구 삼천병마로 1519경기도 수원시 권선구 오목천동 923-4837.23839126.961409031-292-86442023-04-21
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62대명기업폐기물재활용업김용석2017음식물류폐기물경기도 수원시 권선구 매송고색로804번길 451경기도 수원시 권선구 고색동 61637.234495126.988697031-291-07202023-04-21
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