Overview

Dataset statistics

Number of variables10
Number of observations163
Missing cells10
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.2 KiB
Average record size in memory82.8 B

Variable types

Text4
Categorical4
Numeric2

Dataset

Description대전광역시 대덕구에 소재하는 음식물쓰레기 다량배출 사업장 현황정보입니다.(사업장명, 소재지 도로명주소, 연락처 등)
URLhttps://www.data.go.kr/data/15113624/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
월배출량(KG단위) is highly overall correlated with 연간처리량(KG단위) and 1 other fieldsHigh correlation
연간처리량(KG단위) is highly overall correlated with 월배출량(KG단위) and 1 other fieldsHigh correlation
업종 구분 is highly overall correlated with 월배출량(KG단위) and 1 other fieldsHigh correlation
연락처 has 10 (6.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 12:31:10.594207
Analysis finished2023-12-12 12:31:12.197926
Duration1.6 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct162
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-12T21:31:12.385448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length9.601227
Min length2

Characters and Unicode

Total characters1565
Distinct characters299
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique161 ?
Unique (%)98.8%

Sample

1st row설악칡냉면식당
2nd row설악추어탕식당
3rd row청주남주동해장국
4th row선비숯불갈비식당
5th row홍콩삼겹살식당
ValueCountFrequency (%)
주)아워홈 5
 
2.5%
송촌점 4
 
2.0%
아라마크(주 3
 
1.5%
제주머니 2
 
1.0%
주)신세계푸드 2
 
1.0%
의료법인 2
 
1.0%
대전점 2
 
1.0%
구내식당 2
 
1.0%
명륜진사갈비 2
 
1.0%
샤브쌈주머니 2
 
1.0%
Other values (173) 173
86.9%
2023-12-12T21:31:12.814587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 72
 
4.6%
전 64
 
4.1%
주 59
 
3.8%
) 51
 
3.3%
( 51
 
3.3%
학 40
 
2.6%
교 38
 
2.4%
36
 
2.3%
등 26
 
1.7%
한 25
 
1.6%
Other values (289) 1103
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1417
90.5%
Close Punctuation 51
 
3.3%
Open Punctuation 51
 
3.3%
Space Separator 36
 
2.3%
Decimal Number 6
 
0.4%
Other Symbol 2
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 72
 
5.1%
전 64
 
4.5%
주 59
 
4.2%
학 40
 
2.8%
교 38
 
2.7%
등 26
 
1.8%
한 25
 
1.8%
점 24
 
1.7%
원 21
 
1.5%
식 21
 
1.5%
Other values (279) 1027
72.5%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
2 2
33.3%
3 1
16.7%
5 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
M 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1419
90.7%
Common 144
 
9.2%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 72
 
5.1%
전 64
 
4.5%
주 59
 
4.2%
학 40
 
2.8%
교 38
 
2.7%
등 26
 
1.8%
한 25
 
1.8%
점 24
 
1.7%
원 21
 
1.5%
식 21
 
1.5%
Other values (280) 1029
72.5%
Common
ValueCountFrequency (%)
) 51
35.4%
( 51
35.4%
36
25.0%
1 2
 
1.4%
2 2
 
1.4%
3 1
 
0.7%
5 1
 
0.7%
Latin
ValueCountFrequency (%)
D 1
50.0%
M 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1417
90.5%
ASCII 146
 
9.3%
None 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 72
 
5.1%
전 64
 
4.5%
주 59
 
4.2%
학 40
 
2.8%
교 38
 
2.7%
등 26
 
1.8%
한 25
 
1.8%
점 24
 
1.7%
원 21
 
1.5%
식 21
 
1.5%
Other values (279) 1027
72.5%
ASCII
ValueCountFrequency (%)
) 51
34.9%
( 51
34.9%
36
24.7%
1 2
 
1.4%
2 2
 
1.4%
D 1
 
0.7%
M 1
 
0.7%
3 1
 
0.7%
5 1
 
0.7%
None
ValueCountFrequency (%)
㈜ 2
100.0%

사업장도로명주소
Text

Distinct156
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-12T21:31:13.102977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length40
Mean length27.490798
Min length1

Characters and Unicode

Total characters4481
Distinct characters172
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique150 ?
Unique (%)92.0%

Sample

1st row대전광역시 대덕구 덕암북로58번길 7 (덕암동)
2nd row대전광역시 대덕구 대덕대로1458번길 8 (목상동)
3rd row대전광역시 대덕구 대덕대로1458번길 9 (목상동)
4th row대전광역시 대덕구 비래동로16번길 47 (비래동)
5th row
ValueCountFrequency (%)
대전광역시 161
 
18.9%
대덕구 161
 
18.9%
송촌동 24
 
2.8%
오정동 18
 
2.1%
문평동 16
 
1.9%
대화동 14
 
1.6%
비래동 13
 
1.5%
중리동 12
 
1.4%
1층 9
 
1.1%
법동 9
 
1.1%
Other values (251) 417
48.8%
2023-12-12T21:31:13.566646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
708
 
15.8%
대 405
 
9.0%
덕 187
 
4.2%
동 185
 
4.1%
전 177
 
4.0%
) 175
 
3.9%
( 175
 
3.9%
시 164
 
3.7%
구 162
 
3.6%
역 161
 
3.6%
Other values (162) 1982
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2747
61.3%
Space Separator 708
 
15.8%
Decimal Number 621
 
13.9%
Close Punctuation 175
 
3.9%
Open Punctuation 175
 
3.9%
Connector Punctuation 43
 
1.0%
Dash Punctuation 6
 
0.1%
Uppercase Letter 5
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 405
14.7%
덕 187
 
6.8%
동 185
 
6.7%
전 177
 
6.4%
시 164
 
6.0%
구 162
 
5.9%
역 161
 
5.9%
광 161
 
5.9%
로 155
 
5.6%
길 88
 
3.2%
Other values (141) 902
32.8%
Decimal Number
ValueCountFrequency (%)
1 146
23.5%
2 71
11.4%
5 65
10.5%
4 56
 
9.0%
3 55
 
8.9%
7 53
 
8.5%
0 53
 
8.5%
8 50
 
8.1%
6 45
 
7.2%
9 27
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
D 1
20.0%
M 1
20.0%
G 1
20.0%
T 1
20.0%
K 1
20.0%
Space Separator
ValueCountFrequency (%)
708
100.0%
Close Punctuation
ValueCountFrequency (%)
) 175
100.0%
Open Punctuation
ValueCountFrequency (%)
( 175
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 43
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2747
61.3%
Common 1729
38.6%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 405
14.7%
덕 187
 
6.8%
동 185
 
6.7%
전 177
 
6.4%
시 164
 
6.0%
구 162
 
5.9%
역 161
 
5.9%
광 161
 
5.9%
로 155
 
5.6%
길 88
 
3.2%
Other values (141) 902
32.8%
Common
ValueCountFrequency (%)
708
40.9%
) 175
 
10.1%
( 175
 
10.1%
1 146
 
8.4%
2 71
 
4.1%
5 65
 
3.8%
4 56
 
3.2%
3 55
 
3.2%
7 53
 
3.1%
0 53
 
3.1%
Other values (6) 172
 
9.9%
Latin
ValueCountFrequency (%)
D 1
20.0%
M 1
20.0%
G 1
20.0%
T 1
20.0%
K 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2747
61.3%
ASCII 1734
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
708
40.8%
) 175
 
10.1%
( 175
 
10.1%
1 146
 
8.4%
2 71
 
4.1%
5 65
 
3.7%
4 56
 
3.2%
3 55
 
3.2%
7 53
 
3.1%
0 53
 
3.1%
Other values (11) 177
 
10.2%
Hangul
ValueCountFrequency (%)
대 405
14.7%
덕 187
 
6.8%
동 185
 
6.7%
전 177
 
6.4%
시 164
 
6.0%
구 162
 
5.9%
역 161
 
5.9%
광 161
 
5.9%
로 155
 
5.6%
길 88
 
3.2%
Other values (141) 902
32.8%

사업장지번주소
Text

Distinct156
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-12T21:31:13.911363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length33
Mean length20.460123
Min length1

Characters and Unicode

Total characters3335
Distinct characters125
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique151 ?
Unique (%)92.6%

Sample

1st row대전광역시 대덕구 덕암동 9-7
2nd row대전광역시 대덕구 목상동 147-2
3rd row대전광역시 대덕구 목상동 148-4
4th row대전광역시 대덕구 비래동 143-22
5th row대전광역시 대덕구 송촌동 475-4
ValueCountFrequency (%)
대전광역시 160
24.0%
대덕구 160
24.0%
송촌동 26
 
3.9%
오정동 18
 
2.7%
문평동 16
 
2.4%
대화동 13
 
2.0%
비래동 13
 
2.0%
중리동 12
 
1.8%
법동 9
 
1.4%
신일동 9
 
1.4%
Other values (185) 230
34.5%
2023-12-12T21:31:14.467971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
668
20.0%
대 344
 
10.3%
덕 169
 
5.1%
전 167
 
5.0%
시 162
 
4.9%
구 161
 
4.8%
동 161
 
4.8%
역 160
 
4.8%
광 160
 
4.8%
- 133
 
4.0%
Other values (115) 1050
31.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1901
57.0%
Space Separator 668
 
20.0%
Decimal Number 608
 
18.2%
Dash Punctuation 133
 
4.0%
Close Punctuation 10
 
0.3%
Open Punctuation 10
 
0.3%
Uppercase Letter 3
 
0.1%
Connector Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 344
18.1%
덕 169
8.9%
전 167
8.8%
시 162
8.5%
구 161
8.5%
동 161
8.5%
역 160
8.4%
광 160
8.4%
촌 29
 
1.5%
송 27
 
1.4%
Other values (96) 361
19.0%
Decimal Number
ValueCountFrequency (%)
1 116
19.1%
4 100
16.4%
2 77
12.7%
3 70
11.5%
5 66
10.9%
7 41
 
6.7%
0 40
 
6.6%
9 34
 
5.6%
8 34
 
5.6%
6 30
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
G 1
33.3%
T 1
33.3%
Space Separator
ValueCountFrequency (%)
668
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 133
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1901
57.0%
Common 1431
42.9%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 344
18.1%
덕 169
8.9%
전 167
8.8%
시 162
8.5%
구 161
8.5%
동 161
8.5%
역 160
8.4%
광 160
8.4%
촌 29
 
1.5%
송 27
 
1.4%
Other values (96) 361
19.0%
Common
ValueCountFrequency (%)
668
46.7%
- 133
 
9.3%
1 116
 
8.1%
4 100
 
7.0%
2 77
 
5.4%
3 70
 
4.9%
5 66
 
4.6%
7 41
 
2.9%
0 40
 
2.8%
9 34
 
2.4%
Other values (6) 86
 
6.0%
Latin
ValueCountFrequency (%)
K 1
33.3%
G 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1901
57.0%
ASCII 1434
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
668
46.6%
- 133
 
9.3%
1 116
 
8.1%
4 100
 
7.0%
2 77
 
5.4%
3 70
 
4.9%
5 66
 
4.6%
7 41
 
2.9%
0 40
 
2.8%
9 34
 
2.4%
Other values (9) 89
 
6.2%
Hangul
ValueCountFrequency (%)
대 344
18.1%
덕 169
8.9%
전 167
8.8%
시 162
8.5%
구 161
8.5%
동 161
8.5%
역 160
8.4%
광 160
8.4%
촌 29
 
1.5%
송 27
 
1.4%
Other values (96) 361
19.0%

연락처
Text

MISSING 

Distinct149
Distinct (%)97.4%
Missing10
Missing (%)6.1%
Memory size1.4 KiB
2023-12-12T21:31:14.758758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.797386
Min length1

Characters and Unicode

Total characters1805
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146 ?
Unique (%)95.4%

Sample

1st row042 9333588
2nd row042-932-4466
3rd row042-935-9575
4th row042-633-3339
5th row042-628-6755
ValueCountFrequency (%)
042 5
 
3.2%
042-637-3020 2
 
1.3%
042-629-7325 2
 
1.3%
070-7545-7100 1
 
0.6%
042-626-9666 1
 
0.6%
042-627-8899 1
 
0.6%
042-717-5828 1
 
0.6%
042-628-9277 1
 
0.6%
042-632-3939 1
 
0.6%
042-626-8008 1
 
0.6%
Other values (139) 139
89.7%
2023-12-12T21:31:15.262120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 290
16.1%
2 282
15.6%
0 275
15.2%
4 207
11.5%
6 162
9.0%
3 146
8.1%
9 108
 
6.0%
7 88
 
4.9%
5 85
 
4.7%
8 80
 
4.4%
Other values (2) 82
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1507
83.5%
Dash Punctuation 290
 
16.1%
Space Separator 8
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 282
18.7%
0 275
18.2%
4 207
13.7%
6 162
10.7%
3 146
9.7%
9 108
 
7.2%
7 88
 
5.8%
5 85
 
5.6%
8 80
 
5.3%
1 74
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 290
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1805
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 290
16.1%
2 282
15.6%
0 275
15.2%
4 207
11.5%
6 162
9.0%
3 146
8.1%
9 108
 
6.0%
7 88
 
4.9%
5 85
 
4.7%
8 80
 
4.4%
Other values (2) 82
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1805
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 290
16.1%
2 282
15.6%
0 275
15.2%
4 207
11.5%
6 162
9.0%
3 146
8.1%
9 108
 
6.0%
7 88
 
4.9%
5 85
 
4.7%
8 80
 
4.4%
Other values (2) 82
 
4.5%

업종 구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
집단급식소
99 
일반음식점
63 
농수산물시장
 
1

Length

Max length6
Median length5
Mean length5.006135
Min length5

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
집단급식소 99
60.7%
일반음식점 63
38.7%
농수산물시장 1
 
0.6%

Length

2023-12-12T21:31:15.498169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:31:15.660798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 99
60.7%
일반음식점 63
38.7%
농수산물시장 1
 
0.6%

위탁재활용방법
Categorical

Distinct5
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
사료화
105 
퇴비화
39 
15 
기타
 
3
자가처리
 
1

Length

Max length4
Median length3
Mean length2.803681
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row사료화
2nd row사료화
3rd row사료화
4th row퇴비화
5th row사료화

Common Values

ValueCountFrequency (%)
사료화 105
64.4%
퇴비화 39
 
23.9%
15
 
9.2%
기타 3
 
1.8%
자가처리 1
 
0.6%

Length

2023-12-12T21:31:15.867783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:31:16.036578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사료화 105
70.9%
퇴비화 39
 
26.4%
기타 3
 
2.0%
자가처리 1
 
0.7%

위탁처리구분
Categorical

Distinct5
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
사료퇴비중간처리
101 
52 
축산농가집적재활용
 
5
사료퇴비재생처리
 
4
<NA>
 
1

Length

Max length9
Median length8
Mean length5.7730061
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
사료퇴비중간처리 101
62.0%
52
31.9%
축산농가집적재활용 5
 
3.1%
사료퇴비재생처리 4
 
2.5%
<NA> 1
 
0.6%

Length

2023-12-12T21:31:16.237547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:31:16.399737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사료퇴비중간처리 101
91.0%
축산농가집적재활용 5
 
4.5%
사료퇴비재생처리 4
 
3.6%
na 1
 
0.9%

월배출량(KG단위)
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)36.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2189.1288
Minimum250
Maximum60000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T21:31:16.560242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum250
5-th percentile405
Q1900
median1500
Q32400
95-th percentile4461.2
Maximum60000
Range59750
Interquartile range (IQR)1500

Descriptive statistics

Standard deviation4792.1305
Coefficient of variation (CV)2.1890582
Kurtosis132.75577
Mean2189.1288
Median Absolute Deviation (MAD)630
Skewness11.038419
Sum356828
Variance22964515
MonotonicityNot monotonic
2023-12-12T21:31:17.093374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1200 18
 
11.0%
1500 15
 
9.2%
900 14
 
8.6%
3000 11
 
6.7%
600 10
 
6.1%
2000 7
 
4.3%
1800 6
 
3.7%
2700 4
 
2.5%
2600 4
 
2.5%
300 4
 
2.5%
Other values (50) 70
42.9%
ValueCountFrequency (%)
250 1
 
0.6%
300 4
 
2.5%
350 1
 
0.6%
400 3
 
1.8%
450 1
 
0.6%
500 1
 
0.6%
517 1
 
0.6%
600 10
6.1%
659 1
 
0.6%
690 1
 
0.6%
ValueCountFrequency (%)
60000 1
 
0.6%
12000 1
 
0.6%
7230 1
 
0.6%
7200 1
 
0.6%
6000 2
1.2%
4500 3
1.8%
4112 1
 
0.6%
4000 2
1.2%
3610 1
 
0.6%
3600 4
2.5%

연간처리량(KG단위)
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)36.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26269.546
Minimum3000
Maximum720000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T21:31:17.295000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000
5-th percentile4860
Q110800
median18000
Q328800
95-th percentile53534.4
Maximum720000
Range717000
Interquartile range (IQR)18000

Descriptive statistics

Standard deviation57505.566
Coefficient of variation (CV)2.1890582
Kurtosis132.75577
Mean26269.546
Median Absolute Deviation (MAD)7560
Skewness11.038419
Sum4281936
Variance3.3068901 × 109
MonotonicityNot monotonic
2023-12-12T21:31:17.512264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14400 18
 
11.0%
18000 15
 
9.2%
10800 14
 
8.6%
36000 11
 
6.7%
7200 10
 
6.1%
24000 7
 
4.3%
21600 6
 
3.7%
32400 4
 
2.5%
31200 4
 
2.5%
3600 4
 
2.5%
Other values (50) 70
42.9%
ValueCountFrequency (%)
3000 1
 
0.6%
3600 4
 
2.5%
4200 1
 
0.6%
4800 3
 
1.8%
5400 1
 
0.6%
6000 1
 
0.6%
6204 1
 
0.6%
7200 10
6.1%
7908 1
 
0.6%
8280 1
 
0.6%
ValueCountFrequency (%)
720000 1
 
0.6%
144000 1
 
0.6%
86760 1
 
0.6%
86400 1
 
0.6%
72000 2
1.2%
54000 3
1.8%
49344 1
 
0.6%
48000 2
1.2%
43320 1
 
0.6%
43200 4
2.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-05-02
163 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-05-02
2nd row2023-05-02
3rd row2023-05-02
4th row2023-05-02
5th row2023-05-02

Common Values

ValueCountFrequency (%)
2023-05-02 163
100.0%

Length

2023-12-12T21:31:17.730230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:31:17.881373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-05-02 163
100.0%

Interactions

2023-12-12T21:31:11.550528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:31:11.298219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:31:11.683006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:31:11.416727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:31:17.984690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종 구분위탁재활용방법위탁처리구분월배출량(KG단위)연간처리량(KG단위)
업종 구분1.0000.1100.1010.9430.943
위탁재활용방법0.1101.0000.2100.0000.000
위탁처리구분0.1010.2101.0000.0000.000
월배출량(KG단위)0.9430.0000.0001.0001.000
연간처리량(KG단위)0.9430.0000.0001.0001.000
2023-12-12T21:31:18.135309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위탁처리구분위탁재활용방법업종 구분
위탁처리구분1.0000.1720.095
위탁재활용방법0.1721.0000.081
업종 구분0.0950.0811.000
2023-12-12T21:31:18.256898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월배출량(KG단위)연간처리량(KG단위)업종 구분위탁재활용방법위탁처리구분
월배출량(KG단위)1.0001.0000.7070.0000.000
연간처리량(KG단위)1.0001.0000.7070.0000.000
업종 구분0.7070.7071.0000.0810.095
위탁재활용방법0.0000.0000.0811.0000.172
위탁처리구분0.0000.0000.0950.1721.000

Missing values

2023-12-12T21:31:11.862939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:31:12.101113image/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

사업장명사업장도로명주소사업장지번주소연락처업종 구분위탁재활용방법위탁처리구분월배출량(KG단위)연간처리량(KG단위)데이터기준일자
0설악칡냉면식당대전광역시 대덕구 덕암북로58번길 7 (덕암동)대전광역시 대덕구 덕암동 9-7042 9333588일반음식점사료화사료퇴비중간처리2117254042023-05-02
1설악추어탕식당대전광역시 대덕구 대덕대로1458번길 8 (목상동)대전광역시 대덕구 목상동 147-2042-932-4466일반음식점사료화사료퇴비중간처리1000120002023-05-02
2청주남주동해장국대전광역시 대덕구 대덕대로1458번길 9 (목상동)대전광역시 대덕구 목상동 148-4042-935-9575일반음식점사료화사료퇴비중간처리1500180002023-05-02
3선비숯불갈비식당대전광역시 대덕구 비래동로16번길 47 (비래동)대전광역시 대덕구 비래동 143-22042-633-3339일반음식점퇴비화사료퇴비중간처리1000120002023-05-02
4홍콩삼겹살식당대전광역시 대덕구 송촌동 475-4042-628-6755일반음식점사료화사료퇴비중간처리865103802023-05-02
5새일초등학교대전광역시 대덕구 덕암로125번길 15 (덕암동)대전광역시 대덕구 덕암동 110-1042-931-1414집단급식소퇴비화사료퇴비중간처리2500300002023-05-02
6회덕초등학교대전광역시 대덕구 대전로 1350 (읍내동)대전광역시 대덕구 읍내동 317042-628-8112집단급식소퇴비화사료퇴비중간처리1140136802023-05-02
7중리중학교대전광역시 대덕구 중리동로 85 (중리동)대전광역시 대덕구 중리동 371-4042-620-3015집단급식소퇴비화사료퇴비중간처리869104282023-05-02
8(주)신세계푸드 우송정보대 청운5숙대전광역시 대덕구 우암동로18번길 63 (비래동__5(1층))대전광역시 대덕구 비래동 148-4 _5(1층)042-672-1197집단급식소퇴비화사료퇴비중간처리1500180002023-05-02
9(주)하림제일사료대전점대전광역시 대덕구 대전로1331번길 240 (대화동)대전광역시 대덕구 대화동 40-36042-624-0130집단급식소사료화사료퇴비중간처리1264151682023-05-02
사업장명사업장도로명주소사업장지번주소연락처업종 구분위탁재활용방법위탁처리구분월배출량(KG단위)연간처리량(KG단위)데이터기준일자
153삼성웰스토리(주)한국에스엠씨대전대전광역시 대덕구 신일서로18번길 70 (신일동_ 한국에스엠씨공압(주))대전광역시 대덕구 신일동 1673-2 르네상스042-605-2000집단급식소사료화1500180002023-05-02
154복수한우날고기대전광역시 대덕구 계족산로36번길 33_ 1층 (중리동)대전광역시 대덕구 중리동 504-2042-627-2577일반음식점사료퇴비중간처리2000240002023-05-02
155아라마크(주)한국지엠대전서비스센터대전광역시 대덕구 대화로52번길 137 (대화동)대전광역시 대덕구 대화동 142-2042-630-7802집단급식소사료퇴비중간처리900108002023-05-02
156또랑대전광역시 대덕구 계족로 550 (중리동)대전광역시 대덕구 중리동 122-4042-635-5678일반음식점기타사료퇴비중간처리1500180002023-05-02
157신분준할머니기러기칼국수대전광역시 대덕구 송촌북로4번길 47-18 (송촌동)대전광역시 대덕구 송촌동 475-2042-626-9666일반음식점30036002023-05-02
158두형제푸드 롯데택배대전광역시 대덕구 대전로1331번길 205_ 롯데택배 (대화동)대전광역시 대덕구 대화동 40-40 롯데택배<NA>집단급식소사료화사료퇴비중간처리1200144002023-05-02
159(주)아워홈 근로복지공단대전병원대전광역시 대덕구 계족로 637 (법동_ 대전중앙병원)대전광역시 대덕구 법동 285-3070-7545-7100집단급식소사료화사료퇴비중간처리120001440002023-05-02
160삼성웰스토리(주)한온대전대전광역시 대덕구 신일서로 95_ 한라공조(주) (신일동)대전광역시 대덕구 신일동 1689-1 한라공조(주)042-930-6122집단급식소사료화2000240002023-05-02
161㈜이노베이션이큐브(첨사취)대전광역시 대덕구 송촌북로 48(송촌동)대전광역시 대덕구 송촌동 448-2042-639-2000일반음식점퇴비화2880345602023-05-02
162한마음정육식당 송촌점대전광역시 대덕구 송촌북로4번길 47-18 (송촌동)대전광역시 대덕구 송촌동 475-2042-634-8292일반음식점퇴비화<NA>1500180002023-05-02