Overview

Dataset statistics

Number of variables5
Number of observations109
Missing cells15
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory42.2 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description전라남도 나주시 관내의 사업장폐기물 배출자에 대한 정보(구분, 업체명, 연락처, 주소, 폐기물종류 등)를 제공합니다.
Author전라남도 나주시
URLhttps://www.data.go.kr/data/3033311/fileData.do

Alerts

전화번호 has 15 (13.8%) missing valuesMissing
번호 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 19:19:44.351283
Analysis finished2023-12-12 19:19:45.103338
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55
Minimum1
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T04:19:45.219991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.4
Q128
median55
Q382
95-th percentile103.6
Maximum109
Range108
Interquartile range (IQR)54

Descriptive statistics

Standard deviation31.609598
Coefficient of variation (CV)0.57471996
Kurtosis-1.2
Mean55
Median Absolute Deviation (MAD)27
Skewness0
Sum5995
Variance999.16667
MonotonicityStrictly increasing
2023-12-13T04:19:45.403590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
70 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
Other values (99) 99
90.8%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%

생활계구분
Categorical

Distinct3
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1004.0 B
배출시설계
84 
생활계
24 
생활계,배출시설계
 
1

Length

Max length9
Median length5
Mean length4.5963303
Min length3

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st row배출시설계
2nd row생활계
3rd row배출시설계
4th row배출시설계
5th row생활계

Common Values

ValueCountFrequency (%)
배출시설계 84
77.1%
생활계 24
 
22.0%
생활계,배출시설계 1
 
0.9%

Length

2023-12-13T04:19:45.553505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:19:45.690850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
배출시설계 84
77.1%
생활계 24
 
22.0%
생활계,배출시설계 1
 
0.9%

업소명
Text

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2023-12-13T04:19:45.905192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length16
Mean length9.4220183
Min length3

Characters and Unicode

Total characters1027
Distinct characters214
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)100.0%

Sample

1st row(주)농협사료 전남지사
2nd row빛가람종합병원
3rd row(주)선진
4th row농업회사법인(유)평화농장
5th row즐거운요양병원
ValueCountFrequency (%)
주식회사 10
 
7.0%
농업회사법인 4
 
2.8%
나주공장 3
 
2.1%
유한회사 2
 
1.4%
세화의료재단 2
 
1.4%
한영식품 1
 
0.7%
에코우드(주 1
 
0.7%
자연과농부들 1
 
0.7%
주)미주산업 1
 
0.7%
나사렛요양병원 1
 
0.7%
Other values (117) 117
81.8%
2023-12-13T04:19:46.298850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 88
 
8.6%
) 60
 
5.8%
( 60
 
5.8%
34
 
3.3%
사 33
 
3.2%
업 30
 
2.9%
회 22
 
2.1%
산 20
 
1.9%
나 19
 
1.9%
식 18
 
1.8%
Other values (204) 643
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 871
84.8%
Close Punctuation 60
 
5.8%
Open Punctuation 60
 
5.8%
Space Separator 34
 
3.3%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 88
 
10.1%
사 33
 
3.8%
업 30
 
3.4%
회 22
 
2.5%
산 20
 
2.3%
나 19
 
2.2%
식 18
 
2.1%
원 18
 
2.1%
농 17
 
2.0%
지 15
 
1.7%
Other values (200) 591
67.9%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 871
84.8%
Common 154
 
15.0%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 88
 
10.1%
사 33
 
3.8%
업 30
 
3.4%
회 22
 
2.5%
산 20
 
2.3%
나 19
 
2.2%
식 18
 
2.1%
원 18
 
2.1%
농 17
 
2.0%
지 15
 
1.7%
Other values (200) 591
67.9%
Common
ValueCountFrequency (%)
) 60
39.0%
( 60
39.0%
34
22.1%
Latin
ValueCountFrequency (%)
C 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 871
84.8%
ASCII 156
 
15.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 88
 
10.1%
사 33
 
3.8%
업 30
 
3.4%
회 22
 
2.5%
산 20
 
2.3%
나 19
 
2.2%
식 18
 
2.1%
원 18
 
2.1%
농 17
 
2.0%
지 15
 
1.7%
Other values (200) 591
67.9%
ASCII
ValueCountFrequency (%)
) 60
38.5%
( 60
38.5%
34
21.8%
C 2
 
1.3%

주소
Text

Distinct106
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2023-12-13T04:19:46.766445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length31
Mean length23.981651
Min length17

Characters and Unicode

Total characters2614
Distinct characters135
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)94.5%

Sample

1st row전라남도 나주시 문평면 다시로 40_ 농협사료배합사료공장
2nd row전라남도 나주시 정보화길 49 (빛가람동)
3rd row전라남도 나주시 왕곡면 혁신산단2길 13_ 나주축산물공판장
4th row전라남도 나주시 동강면 옥정로 335_ 화정부화장
5th row전라남도 나주시 노안면 노안삼도로 507-14
ValueCountFrequency (%)
전라남도 108
20.3%
나주시 108
20.3%
동수동 16
 
3.0%
남평읍 15
 
2.8%
운곡동 12
 
2.3%
금천면 11
 
2.1%
산포면 10
 
1.9%
봉황면 8
 
1.5%
동수농공단지길 5
 
0.9%
와우리 5
 
0.9%
Other values (187) 235
44.1%
2023-12-13T04:19:47.404057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
510
19.5%
남 130
 
5.0%
도 117
 
4.5%
주 116
 
4.4%
시 112
 
4.3%
나 110
 
4.2%
전 109
 
4.2%
라 108
 
4.1%
1 90
 
3.4%
지 90
 
3.4%
Other values (125) 1122
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1602
61.3%
Space Separator 510
 
19.5%
Decimal Number 397
 
15.2%
Dash Punctuation 72
 
2.8%
Open Punctuation 12
 
0.5%
Close Punctuation 12
 
0.5%
Connector Punctuation 6
 
0.2%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 130
 
8.1%
도 117
 
7.3%
주 116
 
7.2%
시 112
 
7.0%
나 110
 
6.9%
전 109
 
6.8%
라 108
 
6.7%
지 90
 
5.6%
번 84
 
5.2%
동 70
 
4.4%
Other values (107) 556
34.7%
Decimal Number
ValueCountFrequency (%)
1 90
22.7%
2 52
13.1%
3 49
12.3%
4 43
10.8%
5 36
 
9.1%
7 29
 
7.3%
0 26
 
6.5%
8 24
 
6.0%
9 24
 
6.0%
6 24
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
E 1
33.3%
N 1
33.3%
T 1
33.3%
Space Separator
ValueCountFrequency (%)
510
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1602
61.3%
Common 1009
38.6%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 130
 
8.1%
도 117
 
7.3%
주 116
 
7.2%
시 112
 
7.0%
나 110
 
6.9%
전 109
 
6.8%
라 108
 
6.7%
지 90
 
5.6%
번 84
 
5.2%
동 70
 
4.4%
Other values (107) 556
34.7%
Common
ValueCountFrequency (%)
510
50.5%
1 90
 
8.9%
- 72
 
7.1%
2 52
 
5.2%
3 49
 
4.9%
4 43
 
4.3%
5 36
 
3.6%
7 29
 
2.9%
0 26
 
2.6%
8 24
 
2.4%
Other values (5) 78
 
7.7%
Latin
ValueCountFrequency (%)
E 1
33.3%
N 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1602
61.3%
ASCII 1012
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
510
50.4%
1 90
 
8.9%
- 72
 
7.1%
2 52
 
5.1%
3 49
 
4.8%
4 43
 
4.2%
5 36
 
3.6%
7 29
 
2.9%
0 26
 
2.6%
8 24
 
2.4%
Other values (8) 81
 
8.0%
Hangul
ValueCountFrequency (%)
남 130
 
8.1%
도 117
 
7.3%
주 116
 
7.2%
시 112
 
7.0%
나 110
 
6.9%
전 109
 
6.8%
라 108
 
6.7%
지 90
 
5.6%
번 84
 
5.2%
동 70
 
4.4%
Other values (107) 556
34.7%

전화번호
Text

MISSING 

Distinct91
Distinct (%)96.8%
Missing15
Missing (%)13.8%
Memory size1004.0 B
2023-12-13T04:19:47.706518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.021277
Min length12

Characters and Unicode

Total characters1130
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

Unique89 ?
Unique (%)94.7%

Sample

1st row061-335-4577
2nd row061-820-0820
3rd row061-820-7810
4th row061-332-3500
5th row061-339-1236
ValueCountFrequency (%)
061-337-8001 3
 
3.2%
061-330-1700 2
 
2.1%
061-339-9000 1
 
1.1%
061-332-0555 1
 
1.1%
061-331-2204 1
 
1.1%
061-350-7800 1
 
1.1%
061-339-7691 1
 
1.1%
061-333-0001 1
 
1.1%
061-382-0681 1
 
1.1%
061-332-8537 1
 
1.1%
Other values (81) 81
86.2%
2023-12-13T04:19:48.201800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 205
18.1%
0 203
18.0%
- 188
16.6%
1 142
12.6%
6 122
10.8%
5 60
 
5.3%
7 53
 
4.7%
8 46
 
4.1%
9 39
 
3.5%
2 37
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 942
83.4%
Dash Punctuation 188
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 205
21.8%
0 203
21.5%
1 142
15.1%
6 122
13.0%
5 60
 
6.4%
7 53
 
5.6%
8 46
 
4.9%
9 39
 
4.1%
2 37
 
3.9%
4 35
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 205
18.1%
0 203
18.0%
- 188
16.6%
1 142
12.6%
6 122
10.8%
5 60
 
5.3%
7 53
 
4.7%
8 46
 
4.1%
9 39
 
3.5%
2 37
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 205
18.1%
0 203
18.0%
- 188
16.6%
1 142
12.6%
6 122
10.8%
5 60
 
5.3%
7 53
 
4.7%
8 46
 
4.1%
9 39
 
3.5%
2 37
 
3.3%

Interactions

2023-12-13T04:19:44.760524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:19:48.355733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호생활계구분전화번호
번호1.0000.0000.936
생활계구분0.0001.0001.000
전화번호0.9361.0001.000
2023-12-13T04:19:48.474863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호생활계구분
번호1.0000.000
생활계구분0.0001.000

Missing values

2023-12-13T04:19:44.902946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:19:45.054060image/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

번호생활계구분업소명주소전화번호
01배출시설계(주)농협사료 전남지사전라남도 나주시 문평면 다시로 40_ 농협사료배합사료공장061-335-4577
12생활계빛가람종합병원전라남도 나주시 정보화길 49 (빛가람동)061-820-0820
23배출시설계(주)선진전라남도 나주시 왕곡면 혁신산단2길 13_ 나주축산물공판장061-820-7810
34배출시설계농업회사법인(유)평화농장전라남도 나주시 동강면 옥정로 335_ 화정부화장<NA>
45생활계즐거운요양병원전라남도 나주시 노안면 노안삼도로 507-14061-332-3500
56배출시설계(재)전라남도생물산업진흥재단식품산업연구센터전라남도 나주시 동수동 산 15-1번지061-339-1236
67배출시설계남선레미콘(주)전라남도 나주시 남평읍 우산리 2413-82번지061-337-8001
78배출시설계남양유업주식회사 나주공장전라남도 나주시 금천면 영산로 5785061-339-7554
89배출시설계가람환경에너지(주)전라남도 나주시 금천면 오강리 52-10번지061-334-8851
910배출시설계(주)켐포트전라남도 나주시 동수동 산 15-4번지<NA>
번호생활계구분업소명주소전화번호
99100배출시설계(주)에이치엠텍전라남도 나주시 동수동 326-1번지061-336-8067
100101생활계나노크린텍전라남도 나주시 운곡동 243-2번지061-331-8365
101102배출시설계주식회사 누리전라남도 나주시 산포면 등정리 936-4번지070-4909-4839
102103배출시설계(주)오성그린콘크리트전라남도 나주시 다시면 월태리 1203번지061-335-5559
103104생활계빛가람병원전라남도 나주시 산포면 매성리 1188-1번지061-330-8000
104105배출시설계한결우리요양병원전라남도 나주시 왕곡면 장산리 10-5번지 한결우리요양병원061-930-0003
105106배출시설계대영합성(주)전라남도 나주시 남평읍 풍림리 467-5061-334-5484
106107배출시설계한원푸드시스템(주)전라남도 나주시 동수농공단지길 30-117 (운곡동)061-333-9503
107108배출시설계주식회사 동부산업전라남도 나주시 금천면 원곡리 919번지061-332-0555
108109배출시설계신우케미칼(주)전라남도 나주시 동수동 401-1번지061-335-0859