Overview

Dataset statistics

Number of variables9
Number of observations220
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.0 KiB
Average record size in memory74.6 B

Variable types

Categorical4
Text3
Numeric2

Dataset

Description충청북도 진천군 음식물폐기물 다량 배출 사업장 목록은 지역, 시군읍, 사업장구분, 상호, 사업장주소, 연락처, 처리방법, 월배출량, 연간처리량 정보를 포함하고 있습니다.일일배출량은 보유, 관리하는 정보가 없어 제외하였습니다.연락처 중 개인정보는 제외하였습니다.
Author충청북도 진천군
URLhttps://www.data.go.kr/data/15094667/fileData.do

Alerts

지역 has constant value ""Constant
시군읍 has constant value ""Constant
월배출량(kg) is highly overall correlated with 연간처리량(kg)High correlation
연간처리량(kg) is highly overall correlated with 월배출량(kg)High correlation
상호 has unique valuesUnique

Reproduction

Analysis started2024-05-11 07:46:56.374585
Analysis finished2024-05-11 07:47:03.710996
Duration7.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
충북
220 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충북 220
100.0%

Length

2024-05-11T16:47:03.870394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:47:04.158958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충북 220
100.0%

시군읍
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
진천군
220 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진천군 220
100.0%

Length

2024-05-11T16:47:04.403403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:47:04.669873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진천군 220
100.0%

사업장구분
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
집단급식소
118 
일반음식점
102 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
집단급식소 118
53.6%
일반음식점 102
46.4%

Length

2024-05-11T16:47:04.934521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:47:05.173601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 118
53.6%
일반음식점 102
46.4%

상호
Text

UNIQUE 

Distinct220
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T16:47:05.640339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length10.436364
Min length2

Characters and Unicode

Total characters2296
Distinct characters346
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

Unique220 ?
Unique (%)100.0%

Sample

1st row그린하우스 (주)윈텍
2nd row화랑유치원
3rd row(주)동진
4th row동원홈푸드 (유진철강산업)
5th row신성FS
ValueCountFrequency (%)
급식소 19
 
6.1%
주)현대그린푸드 4
 
1.3%
주)창조캐터링 3
 
1.0%
주)서윤푸드 2
 
0.6%
주)제이에스지 2
 
0.6%
충북혁신점 2
 
0.6%
주)아워홈 2
 
0.6%
삼성웰스토리 2
 
0.6%
충북혁신도시점 2
 
0.6%
주)동원홈푸드 2
 
0.6%
Other values (268) 273
87.2%
2024-05-11T16:47:06.493314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 97
 
4.2%
( 97
 
4.2%
93
 
4.1%
주 92
 
4.0%
식 49
 
2.1%
드 45
 
2.0%
푸 44
 
1.9%
진 42
 
1.8%
이 41
 
1.8%
점 41
 
1.8%
Other values (336) 1655
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1937
84.4%
Close Punctuation 118
 
5.1%
Open Punctuation 118
 
5.1%
Space Separator 93
 
4.1%
Decimal Number 16
 
0.7%
Uppercase Letter 11
 
0.5%
Dash Punctuation 2
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 92
 
4.7%
식 49
 
2.5%
드 45
 
2.3%
푸 44
 
2.3%
진 42
 
2.2%
이 41
 
2.1%
점 41
 
2.1%
스 41
 
2.1%
천 39
 
2.0%
한 36
 
1.9%
Other values (315) 1467
75.7%
Decimal Number
ValueCountFrequency (%)
2 5
31.2%
1 5
31.2%
3 2
 
12.5%
5 1
 
6.2%
0 1
 
6.2%
7 1
 
6.2%
8 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
S 3
27.3%
J 2
18.2%
F 2
18.2%
C 1
 
9.1%
G 1
 
9.1%
T 1
 
9.1%
A 1
 
9.1%
Close Punctuation
ValueCountFrequency (%)
) 97
82.2%
] 21
 
17.8%
Open Punctuation
ValueCountFrequency (%)
( 97
82.2%
[ 21
 
17.8%
Space Separator
ValueCountFrequency (%)
93
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1937
84.4%
Common 347
 
15.1%
Latin 12
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 92
 
4.7%
식 49
 
2.5%
드 45
 
2.3%
푸 44
 
2.3%
진 42
 
2.2%
이 41
 
2.1%
점 41
 
2.1%
스 41
 
2.1%
천 39
 
2.0%
한 36
 
1.9%
Other values (315) 1467
75.7%
Common
ValueCountFrequency (%)
) 97
28.0%
( 97
28.0%
93
26.8%
[ 21
 
6.1%
] 21
 
6.1%
2 5
 
1.4%
1 5
 
1.4%
3 2
 
0.6%
- 2
 
0.6%
5 1
 
0.3%
Other values (3) 3
 
0.9%
Latin
ValueCountFrequency (%)
S 3
25.0%
J 2
16.7%
F 2
16.7%
C 1
 
8.3%
n 1
 
8.3%
G 1
 
8.3%
T 1
 
8.3%
A 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1937
84.4%
ASCII 359
 
15.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 97
27.0%
( 97
27.0%
93
25.9%
[ 21
 
5.8%
] 21
 
5.8%
2 5
 
1.4%
1 5
 
1.4%
S 3
 
0.8%
3 2
 
0.6%
J 2
 
0.6%
Other values (11) 13
 
3.6%
Hangul
ValueCountFrequency (%)
주 92
 
4.7%
식 49
 
2.5%
드 45
 
2.3%
푸 44
 
2.3%
진 42
 
2.2%
이 41
 
2.1%
점 41
 
2.1%
스 41
 
2.1%
천 39
 
2.0%
한 36
 
1.9%
Other values (315) 1467
75.7%

사업장주소
Text

Distinct209
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T16:47:07.249243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length24.836364
Min length17

Characters and Unicode

Total characters5464
Distinct characters232
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)90.9%

Sample

1st row충청북도 진천군 문백면 문진로 292-19
2nd row충청북도 진천군 진천읍 농다리로 1407
3rd row충청북도 진천군 이월면 수평1길 125
4th row충청북도 진천군 진천읍 진광로 110 (유진철강산업(주))
5th row충청북도 진천군 이월면 중미로 539-7
ValueCountFrequency (%)
충청북도 220
18.3%
진천군 220
18.3%
진천읍 67
 
5.6%
덕산읍 62
 
5.2%
광혜원면 30
 
2.5%
이월면 28
 
2.3%
문백면 15
 
1.2%
초평면 12
 
1.0%
농다리로 11
 
0.9%
진광로 11
 
0.9%
Other values (377) 526
43.8%
2024-05-11T16:47:08.190842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1002
18.3%
진 317
 
5.8%
천 300
 
5.5%
북 227
 
4.2%
청 224
 
4.1%
도 223
 
4.1%
충 222
 
4.1%
군 221
 
4.0%
1 170
 
3.1%
읍 133
 
2.4%
Other values (222) 2425
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3456
63.3%
Space Separator 1002
 
18.3%
Decimal Number 754
 
13.8%
Connector Punctuation 63
 
1.2%
Dash Punctuation 61
 
1.1%
Open Punctuation 52
 
1.0%
Close Punctuation 52
 
1.0%
Uppercase Letter 17
 
0.3%
Other Punctuation 4
 
0.1%
Math Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
진 317
 
9.2%
천 300
 
8.7%
북 227
 
6.6%
청 224
 
6.5%
도 223
 
6.5%
충 222
 
6.4%
군 221
 
6.4%
읍 133
 
3.8%
로 127
 
3.7%
산 114
 
3.3%
Other values (194) 1348
39.0%
Decimal Number
ValueCountFrequency (%)
1 170
22.5%
2 128
17.0%
3 87
11.5%
4 61
 
8.1%
0 60
 
8.0%
7 56
 
7.4%
9 55
 
7.3%
5 53
 
7.0%
6 47
 
6.2%
8 37
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
C 5
29.4%
S 3
17.6%
E 2
 
11.8%
G 1
 
5.9%
D 1
 
5.9%
J 1
 
5.9%
K 1
 
5.9%
P 1
 
5.9%
O 1
 
5.9%
I 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 3
75.0%
/ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
1002
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3456
63.3%
Common 1991
36.4%
Latin 17
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
진 317
 
9.2%
천 300
 
8.7%
북 227
 
6.6%
청 224
 
6.5%
도 223
 
6.5%
충 222
 
6.4%
군 221
 
6.4%
읍 133
 
3.8%
로 127
 
3.7%
산 114
 
3.3%
Other values (194) 1348
39.0%
Common
ValueCountFrequency (%)
1002
50.3%
1 170
 
8.5%
2 128
 
6.4%
3 87
 
4.4%
_ 63
 
3.2%
- 61
 
3.1%
4 61
 
3.1%
0 60
 
3.0%
7 56
 
2.8%
9 55
 
2.8%
Other values (8) 248
 
12.5%
Latin
ValueCountFrequency (%)
C 5
29.4%
S 3
17.6%
E 2
 
11.8%
G 1
 
5.9%
D 1
 
5.9%
J 1
 
5.9%
K 1
 
5.9%
P 1
 
5.9%
O 1
 
5.9%
I 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3456
63.3%
ASCII 2008
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1002
49.9%
1 170
 
8.5%
2 128
 
6.4%
3 87
 
4.3%
_ 63
 
3.1%
- 61
 
3.0%
4 61
 
3.0%
0 60
 
3.0%
7 56
 
2.8%
9 55
 
2.7%
Other values (18) 265
 
13.2%
Hangul
ValueCountFrequency (%)
진 317
 
9.2%
천 300
 
8.7%
북 227
 
6.6%
청 224
 
6.5%
도 223
 
6.5%
충 222
 
6.4%
군 221
 
6.4%
읍 133
 
3.8%
로 127
 
3.7%
산 114
 
3.3%
Other values (194) 1348
39.0%

연락처
Text

Distinct136
Distinct (%)61.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-05-11T16:47:08.808091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.7727273
Min length6

Characters and Unicode

Total characters2150
Distinct characters18
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

Unique133 ?
Unique (%)60.5%

Sample

1st row043-537-3080
2nd row043-532-3301
3rd row043-534-2471
4th row043-539-9539
5th row070-8246-2737
ValueCountFrequency (%)
개인정보포함 82
36.9%
043-532-4866 3
 
1.4%
043-533-1419 2
 
0.9%
043534 1
 
0.5%
043-532-3012 1
 
0.5%
043-880-8218 1
 
0.5%
043-530-1324 1
 
0.5%
043-539-5023 1
 
0.5%
043-539-5749 1
 
0.5%
070-5005-2204 1
 
0.5%
Other values (128) 128
57.7%
2024-05-11T16:47:09.779835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 349
16.2%
- 271
12.6%
0 231
10.7%
4 189
 
8.8%
5 188
 
8.7%
2 90
 
4.2%
인 82
 
3.8%
개 82
 
3.8%
함 82
 
3.8%
포 82
 
3.8%
Other values (8) 504
23.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1385
64.4%
Other Letter 492
 
22.9%
Dash Punctuation 271
 
12.6%
Space Separator 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 349
25.2%
0 231
16.7%
4 189
13.6%
5 188
13.6%
2 90
 
6.5%
1 77
 
5.6%
7 73
 
5.3%
6 72
 
5.2%
8 59
 
4.3%
9 57
 
4.1%
Other Letter
ValueCountFrequency (%)
인 82
16.7%
개 82
16.7%
함 82
16.7%
포 82
16.7%
보 82
16.7%
정 82
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 271
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1658
77.1%
Hangul 492
 
22.9%

Most frequent character per script

Common
ValueCountFrequency (%)
3 349
21.0%
- 271
16.3%
0 231
13.9%
4 189
11.4%
5 188
11.3%
2 90
 
5.4%
1 77
 
4.6%
7 73
 
4.4%
6 72
 
4.3%
8 59
 
3.6%
Other values (2) 59
 
3.6%
Hangul
ValueCountFrequency (%)
인 82
16.7%
개 82
16.7%
함 82
16.7%
포 82
16.7%
보 82
16.7%
정 82
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1658
77.1%
Hangul 492
 
22.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 349
21.0%
- 271
16.3%
0 231
13.9%
4 189
11.4%
5 188
11.3%
2 90
 
5.4%
1 77
 
4.6%
7 73
 
4.4%
6 72
 
4.3%
8 59
 
3.6%
Other values (2) 59
 
3.6%
Hangul
ValueCountFrequency (%)
인 82
16.7%
개 82
16.7%
함 82
16.7%
포 82
16.7%
보 82
16.7%
정 82
16.7%

처리방법
Categorical

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
사료화
142 
퇴비화
78 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사료화 142
64.5%
퇴비화 78
35.5%

Length

2024-05-11T16:47:10.055373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T16:47:10.248193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사료화 142
64.5%
퇴비화 78
35.5%

월배출량(kg)
Real number (ℝ)

HIGH CORRELATION 

Distinct109
Distinct (%)49.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1189.2741
Minimum10
Maximum7500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T16:47:10.461045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile100
Q1447.5
median800
Q31402.5
95-th percentile3520.75
Maximum7500
Range7490
Interquartile range (IQR)955

Descriptive statistics

Standard deviation1259.2091
Coefficient of variation (CV)1.0588048
Kurtosis7.2579252
Mean1189.2741
Median Absolute Deviation (MAD)430
Skewness2.4714891
Sum261640.3
Variance1585607.6
MonotonicityNot monotonic
2024-05-11T16:47:10.770096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000.0 16
 
7.3%
600.0 13
 
5.9%
300.0 11
 
5.0%
2000.0 10
 
4.5%
900.0 9
 
4.1%
500.0 8
 
3.6%
250.0 5
 
2.3%
750.0 5
 
2.3%
3000.0 4
 
1.8%
1100.0 4
 
1.8%
Other values (99) 135
61.4%
ValueCountFrequency (%)
10.0 1
 
0.5%
30.0 2
0.9%
40.0 1
 
0.5%
50.0 1
 
0.5%
62.0 1
 
0.5%
70.0 1
 
0.5%
90.0 3
1.4%
100.0 2
0.9%
110.0 1
 
0.5%
120.0 1
 
0.5%
ValueCountFrequency (%)
7500.0 1
0.5%
7125.0 1
0.5%
6000.0 2
0.9%
5505.0 1
0.5%
5400.0 1
0.5%
5200.0 1
0.5%
5000.0 2
0.9%
3660.0 1
0.5%
3535.0 1
0.5%
3520.0 1
0.5%

연간처리량(kg)
Real number (ℝ)

HIGH CORRELATION 

Distinct114
Distinct (%)51.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14223.809
Minimum120
Maximum90000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-05-11T16:47:11.087606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum120
5-th percentile1200
Q14950
median9540
Q316830
95-th percentile42249
Maximum90000
Range89880
Interquartile range (IQR)11880

Descriptive statistics

Standard deviation15141.731
Coefficient of variation (CV)1.0645342
Kurtosis7.2068687
Mean14223.809
Median Absolute Deviation (MAD)5340
Skewness2.4625075
Sum3129238
Variance2.2927202 × 108
MonotonicityNot monotonic
2024-05-11T16:47:11.507721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12000 15
 
6.8%
7200 12
 
5.5%
3600 11
 
5.0%
24000 10
 
4.5%
6000 8
 
3.6%
10800 7
 
3.2%
13200 5
 
2.3%
3000 5
 
2.3%
36000 4
 
1.8%
9000 4
 
1.8%
Other values (104) 139
63.2%
ValueCountFrequency (%)
120 1
 
0.5%
360 2
0.9%
480 1
 
0.5%
600 1
 
0.5%
744 1
 
0.5%
840 1
 
0.5%
1080 3
1.4%
1200 3
1.4%
1320 1
 
0.5%
1656 1
 
0.5%
ValueCountFrequency (%)
90000 1
0.5%
85500 1
0.5%
72000 2
0.9%
66060 1
0.5%
64800 1
0.5%
62400 1
0.5%
60000 2
0.9%
43920 1
0.5%
42420 1
0.5%
42240 1
0.5%

Interactions

2024-05-11T16:47:02.708151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:47:02.094370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:47:02.953432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T16:47:02.369131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T16:47:11.753376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장구분처리방법월배출량(kg)연간처리량(kg)
사업장구분1.0000.3470.2470.262
처리방법0.3471.0000.2930.309
월배출량(kg)0.2470.2931.0001.000
연간처리량(kg)0.2620.3091.0001.000
2024-05-11T16:47:11.998171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장구분처리방법
사업장구분1.0000.226
처리방법0.2261.000
2024-05-11T16:47:12.332735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
월배출량(kg)연간처리량(kg)사업장구분처리방법
월배출량(kg)1.0000.9950.1830.216
연간처리량(kg)0.9951.0000.1940.229
사업장구분0.1830.1941.0000.226
처리방법0.2160.2290.2261.000

Missing values

2024-05-11T16:47:03.310065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T16:47:03.573841image/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

지역시군읍사업장구분상호사업장주소연락처처리방법월배출량(kg)연간처리량(kg)
0충북진천군집단급식소그린하우스 (주)윈텍충청북도 진천군 문백면 문진로 292-19043-537-3080퇴비화2000.024000
1충북진천군집단급식소화랑유치원충청북도 진천군 진천읍 농다리로 1407043-532-3301퇴비화40.0480
2충북진천군집단급식소(주)동진충청북도 진천군 이월면 수평1길 125043-534-2471퇴비화600.07200
3충북진천군집단급식소동원홈푸드 (유진철강산업)충청북도 진천군 진천읍 진광로 110 (유진철강산업(주))043-539-9539퇴비화800.09600
4충북진천군집단급식소신성FS충청북도 진천군 이월면 중미로 539-7070-8246-2737사료화900.010800
5충북진천군일반음식점산호섬충청북도 진천군 진천읍 포석길 9_ 3층 (화랑벌 청풍도)043-534-5282퇴비화1200.014400
6충북진천군집단급식소아라마크(주)[삼양패키징 진천공장]충청북도 진천군 문백면 문덕1길 92 (주)삼양패키징043-530-7746사료화810.09720
7충북진천군일반음식점장수한식푸드충청북도 진천군 덕산읍 산수산단2로 93개인정보포함퇴비화500.06000
8충북진천군일반음식점원산대반점충청북도 진천군 진천읍 중앙서로 69_ 연빌딩043-533-2503퇴비화1000.012000
9충북진천군일반음식점다님길 박포갈비충청북도 진천군 덕산읍 연미1길 29_ 2층 201호043-535-9592사료화270.03240
지역시군읍사업장구분상호사업장주소연락처처리방법월배출량(kg)연간처리량(kg)
210충북진천군일반음식점한우설렁탕집충청북도 진천군 진천읍 농다리로 1446개인정보포함퇴비화700.08400
211충북진천군일반음식점반값소직영점충청북도 진천군 진천읍 문화로 19개인정보포함퇴비화300.03600
212충북진천군집단급식소청호나이스(주)[마이크로필터2공장 위탁급식]충청북도 진천군 덕산읍 산수산단2로 116 (주)엔하이코리아031-354-1270퇴비화660.07920
213충북진천군집단급식소(주)현대그린푸드(서한산업2공장 급식소)충청북도 진천군 덕산읍 인석로 159-21_ 서한산업(주)제2공장개인정보포함사료화1060.019480
214충북진천군집단급식소(주)현대그린푸드(서한산업1공장 급식소)충청북도 진천군 덕산읍 인석로 95-13_ 서한산업(주)본사/제1공장043-530-3099사료화2000.024000
215충북진천군일반음식점대복칼국수충청북도 진천군 진천읍 원덕로 233043-534-6001퇴비화1000.012000
216충북진천군일반음식점다원제이충청북도 진천군 이월면 진안로 137-1개인정보포함퇴비화1000.012000
217충북진천군집단급식소덕산중학교충청북도 진천군 덕산읍 몽촌2길 19043-536-4280사료화1500.018000
218충북진천군일반음식점진천막국수충청북도 진천군 이월면 진광로 725개인정보포함사료화1215.014580
219충북진천군일반음식점(주)청석한우충청북도 진천군 덕산읍 대월2길 52개인정보포함퇴비화900.010800