Overview

Dataset statistics

Number of variables9
Number of observations136
Missing cells8
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.1 KiB
Average record size in memory76.0 B

Variable types

Text3
Categorical3
Numeric3

Dataset

Description충청남도 예산군 음식물쓰레기 다량배출사업장 현황입니다.(사업장 주소, 연락처, 사업장 구분, 규모, 배출량, 처리방법 등 제공)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=307&beforeMenuCd=DOM_000000201001001000&publicdatapk=15094263

Alerts

처리방법 has constant value ""Constant
규모 is highly overall correlated with 사업장구분 and 1 other fieldsHigh correlation
월배출예상 is highly overall correlated with 년배출예상High correlation
년배출예상 is highly overall correlated with 월배출예상High correlation
사업장구분 is highly overall correlated with 규모 and 1 other fieldsHigh correlation
사업장규모 is highly overall correlated with 규모 and 1 other fieldsHigh correlation
사업장전화번호 has 8 (5.9%) missing valuesMissing
상호 has unique valuesUnique

Reproduction

Analysis started2024-03-13 11:47:17.718860
Analysis finished2024-03-13 11:47:19.698508
Duration1.98 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

UNIQUE 

Distinct136
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-13T20:47:19.938063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length19
Mean length7.8676471
Min length2

Characters and Unicode

Total characters1070
Distinct characters265
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

Unique136 ?
Unique (%)100.0%

Sample

1st row덕산초등학교
2nd row내포 남도밥상
3rd row광시길한우타운식당
4th row한백당한식뷔페
5th row(주)고려비엔피
ValueCountFrequency (%)
내포신도시점 2
 
1.2%
주)녹수 2
 
1.2%
예산공장 2
 
1.2%
심원개발 2
 
1.2%
주)푸디스트 2
 
1.2%
예산명지병원 2
 
1.2%
구내식당 2
 
1.2%
예산점 2
 
1.2%
동흥루 1
 
0.6%
쿡케이 1
 
0.6%
Other values (153) 153
89.5%
2024-03-13T20:47:20.422151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 44
 
4.1%
예 37
 
3.5%
35
 
3.3%
교 27
 
2.5%
( 26
 
2.4%
학 26
 
2.4%
장 26
 
2.4%
) 26
 
2.4%
주 25
 
2.3%
식 24
 
2.2%
Other values (255) 774
72.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 972
90.8%
Space Separator 35
 
3.3%
Open Punctuation 26
 
2.4%
Close Punctuation 26
 
2.4%
Dash Punctuation 5
 
0.5%
Decimal Number 3
 
0.3%
Uppercase Letter 2
 
0.2%
Connector Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 44
 
4.5%
예 37
 
3.8%
교 27
 
2.8%
학 26
 
2.7%
장 26
 
2.7%
주 25
 
2.6%
식 24
 
2.5%
한 22
 
2.3%
원 19
 
2.0%
등 18
 
1.9%
Other values (245) 704
72.4%
Decimal Number
ValueCountFrequency (%)
2 1
33.3%
3 1
33.3%
1 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
J 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 972
90.8%
Common 96
 
9.0%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 44
 
4.5%
예 37
 
3.8%
교 27
 
2.8%
학 26
 
2.7%
장 26
 
2.7%
주 25
 
2.6%
식 24
 
2.5%
한 22
 
2.3%
원 19
 
2.0%
등 18
 
1.9%
Other values (245) 704
72.4%
Common
ValueCountFrequency (%)
35
36.5%
( 26
27.1%
) 26
27.1%
- 5
 
5.2%
2 1
 
1.0%
3 1
 
1.0%
_ 1
 
1.0%
1 1
 
1.0%
Latin
ValueCountFrequency (%)
J 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 972
90.8%
ASCII 98
 
9.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 44
 
4.5%
예 37
 
3.8%
교 27
 
2.8%
학 26
 
2.7%
장 26
 
2.7%
주 25
 
2.6%
식 24
 
2.5%
한 22
 
2.3%
원 19
 
2.0%
등 18
 
1.9%
Other values (245) 704
72.4%
ASCII
ValueCountFrequency (%)
35
35.7%
( 26
26.5%
) 26
26.5%
- 5
 
5.1%
J 1
 
1.0%
C 1
 
1.0%
2 1
 
1.0%
3 1
 
1.0%
_ 1
 
1.0%
1 1
 
1.0%

사업장전화번호
Text

MISSING 

Distinct113
Distinct (%)88.3%
Missing8
Missing (%)5.9%
Memory size1.2 KiB
2024-03-13T20:47:20.792595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length8.3046875
Min length1

Characters and Unicode

Total characters1063
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

Unique110 ?
Unique (%)85.9%

Sample

1st row413370204
2nd row3310092
3rd row041-332-0017
4th row 041 3310213
5th row3373839
ValueCountFrequency (%)
041-337-1730 2
 
1.7%
041 2
 
1.7%
041-584-8891 2
 
1.7%
330-1692 1
 
0.9%
041-338-1937 1
 
0.9%
3348300 1
 
0.9%
3328206 1
 
0.9%
3320013 1
 
0.9%
3323714 1
 
0.9%
3345520 1
 
0.9%
Other values (103) 103
88.8%
2024-03-13T20:47:21.330076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 269
25.3%
0 121
11.4%
1 115
10.8%
- 112
10.5%
4 106
 
10.0%
2 77
 
7.2%
8 57
 
5.4%
7 50
 
4.7%
9 50
 
4.7%
5 47
 
4.4%
Other values (2) 59
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 934
87.9%
Dash Punctuation 112
 
10.5%
Space Separator 17
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 269
28.8%
0 121
13.0%
1 115
12.3%
4 106
 
11.3%
2 77
 
8.2%
8 57
 
6.1%
7 50
 
5.4%
9 50
 
5.4%
5 47
 
5.0%
6 42
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1063
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 269
25.3%
0 121
11.4%
1 115
10.8%
- 112
10.5%
4 106
 
10.0%
2 77
 
7.2%
8 57
 
5.4%
7 50
 
4.7%
9 50
 
4.7%
5 47
 
4.4%
Other values (2) 59
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1063
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 269
25.3%
0 121
11.4%
1 115
10.8%
- 112
10.5%
4 106
 
10.0%
2 77
 
7.2%
8 57
 
5.4%
7 50
 
4.7%
9 50
 
4.7%
5 47
 
4.4%
Other values (2) 59
 
5.6%

사업장도로명주소
Text

Distinct134
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-13T20:47:21.797156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length45
Mean length23.830882
Min length18

Characters and Unicode

Total characters3241
Distinct characters162
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique132 ?
Unique (%)97.1%

Sample

1st row충청남도 예산군 덕산면 봉운로 38
2nd row충청남도 예산군 삽교읍 예학로 93_ 2층층 203(4)호
3rd row충청남도 예산군 광시면 예당로 156
4th row충청남도 예산군 오가면 충서로 381
5th row충청남도 예산군 신암면 추사로 235-9
ValueCountFrequency (%)
충청남도 136
18.7%
예산군 136
18.7%
예산읍 49
 
6.7%
삽교읍 36
 
5.0%
덕산면 11
 
1.5%
고덕면 9
 
1.2%
광시면 6
 
0.8%
벚꽃로 6
 
0.8%
금오대로 6
 
0.8%
오가면 6
 
0.8%
Other values (227) 326
44.8%
2024-03-13T20:47:22.401727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
591
18.2%
산 237
 
7.3%
예 215
 
6.6%
청 153
 
4.7%
충 144
 
4.4%
도 141
 
4.4%
군 139
 
4.3%
남 137
 
4.2%
로 109
 
3.4%
1 108
 
3.3%
Other values (152) 1267
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2082
64.2%
Space Separator 591
 
18.2%
Decimal Number 486
 
15.0%
Connector Punctuation 31
 
1.0%
Dash Punctuation 29
 
0.9%
Open Punctuation 10
 
0.3%
Close Punctuation 10
 
0.3%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 237
 
11.4%
예 215
 
10.3%
청 153
 
7.3%
충 144
 
6.9%
도 141
 
6.8%
군 139
 
6.7%
남 137
 
6.6%
로 109
 
5.2%
읍 85
 
4.1%
교 52
 
2.5%
Other values (136) 670
32.2%
Decimal Number
ValueCountFrequency (%)
1 108
22.2%
2 80
16.5%
0 51
10.5%
3 49
10.1%
4 40
 
8.2%
9 39
 
8.0%
8 35
 
7.2%
5 31
 
6.4%
6 27
 
5.6%
7 26
 
5.3%
Space Separator
ValueCountFrequency (%)
591
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2082
64.2%
Common 1159
35.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 237
 
11.4%
예 215
 
10.3%
청 153
 
7.3%
충 144
 
6.9%
도 141
 
6.8%
군 139
 
6.7%
남 137
 
6.6%
로 109
 
5.2%
읍 85
 
4.1%
교 52
 
2.5%
Other values (136) 670
32.2%
Common
ValueCountFrequency (%)
591
51.0%
1 108
 
9.3%
2 80
 
6.9%
0 51
 
4.4%
3 49
 
4.2%
4 40
 
3.5%
9 39
 
3.4%
8 35
 
3.0%
_ 31
 
2.7%
5 31
 
2.7%
Other values (6) 104
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2082
64.2%
ASCII 1159
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
591
51.0%
1 108
 
9.3%
2 80
 
6.9%
0 51
 
4.4%
3 49
 
4.2%
4 40
 
3.5%
9 39
 
3.4%
8 35
 
3.0%
_ 31
 
2.7%
5 31
 
2.7%
Other values (6) 104
 
9.0%
Hangul
ValueCountFrequency (%)
산 237
 
11.4%
예 215
 
10.3%
청 153
 
7.3%
충 144
 
6.9%
도 141
 
6.8%
군 139
 
6.7%
남 137
 
6.6%
로 109
 
5.2%
읍 85
 
4.1%
교 52
 
2.5%
Other values (136) 670
32.2%

사업장구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
일반음식점
77 
집단급식소
54 
기타
 
3
농수산물시장
 
1
관광숙박시설
 
1

Length

Max length6
Median length5
Mean length4.9485294
Min length2

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 77
56.6%
집단급식소 54
39.7%
기타 3
 
2.2%
농수산물시장 1
 
0.7%
관광숙박시설 1
 
0.7%

Length

2024-03-13T20:47:22.563747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:47:22.715777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 77
56.6%
집단급식소 54
39.7%
기타 3
 
2.2%
농수산물시장 1
 
0.7%
관광숙박시설 1
 
0.7%

사업장규모
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
166_330㎡(51_100평)
47 
100_300인
28 
331_660㎡(101_200평)
18 
301_500인
13 
200㎡이상
9 
Other values (6)
21 

Length

Max length18
Median length17
Mean length12.955882
Min length6

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row301_500인
2nd row166_330㎡(51_100평)
3rd row166_330㎡(51_100평)
4th row166_330㎡(51_100평)
5th row100_300인

Common Values

ValueCountFrequency (%)
166_330㎡(51_100평) 47
34.6%
100_300인 28
20.6%
331_660㎡(101_200평) 18
 
13.2%
301_500인 13
 
9.6%
200㎡이상 9
 
6.6%
661_990㎡(201_300평) 7
 
5.1%
501_1000인 5
 
3.7%
100인 이상 4
 
2.9%
1001_2000인 2
 
1.5%
991㎡이상(301평이상) 2
 
1.5%

Length

2024-03-13T20:47:22.873244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
166_330㎡(51_100평 47
33.6%
100_300인 28
20.0%
331_660㎡(101_200평 18
 
12.9%
301_500인 13
 
9.3%
200㎡이상 9
 
6.4%
661_990㎡(201_300평 7
 
5.0%
501_1000인 5
 
3.6%
100인 4
 
2.9%
이상 4
 
2.9%
1001_2000인 2
 
1.4%
Other values (2) 3
 
2.1%

규모
Real number (ℝ)

HIGH CORRELATION 

Distinct108
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean483.50221
Minimum10
Maximum20000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-13T20:47:23.025367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile100
Q1206.09
median264.23
Q3370.8475
95-th percentile850.43
Maximum20000
Range19990
Interquartile range (IQR)164.7575

Descriptive statistics

Standard deviation1712.6553
Coefficient of variation (CV)3.5421872
Kurtosis127.53547
Mean483.50221
Median Absolute Deviation (MAD)69.715
Skewness11.138202
Sum65756.3
Variance2933188.3
MonotonicityNot monotonic
2024-03-13T20:47:23.200676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 10
 
7.4%
200.0 7
 
5.1%
150.0 4
 
2.9%
130.0 3
 
2.2%
450.0 3
 
2.2%
350.0 3
 
2.2%
300.0 3
 
2.2%
500.0 2
 
1.5%
210.0 2
 
1.5%
243.9 1
 
0.7%
Other values (98) 98
72.1%
ValueCountFrequency (%)
10.0 1
 
0.7%
100.0 10
7.4%
105.0 1
 
0.7%
126.0 1
 
0.7%
130.0 3
 
2.2%
132.0 1
 
0.7%
135.0 1
 
0.7%
140.0 1
 
0.7%
141.0 1
 
0.7%
150.0 4
 
2.9%
ValueCountFrequency (%)
20000.0 1
0.7%
2402.0 1
0.7%
1918.0 1
0.7%
1200.0 1
0.7%
1107.5 1
0.7%
1100.0 1
0.7%
956.0 1
0.7%
815.24 1
0.7%
790.0 1
0.7%
750.0 1
0.7%

월배출예상
Real number (ℝ)

HIGH CORRELATION 

Distinct64
Distinct (%)47.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1376.9963
Minimum10
Maximum12410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-13T20:47:23.400255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile75
Q1300
median750
Q32000
95-th percentile4500
Maximum12410
Range12400
Interquartile range (IQR)1700

Descriptive statistics

Standard deviation1648.013
Coefficient of variation (CV)1.1968173
Kurtosis14.564986
Mean1376.9963
Median Absolute Deviation (MAD)590
Skewness2.9790061
Sum187271.5
Variance2715946.7
MonotonicityNot monotonic
2024-03-13T20:47:23.613504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000.0 12
 
8.8%
600.0 12
 
8.8%
300.0 9
 
6.6%
1000.0 7
 
5.1%
1500.0 7
 
5.1%
2000.0 5
 
3.7%
180.0 4
 
2.9%
700.0 4
 
2.9%
60.0 4
 
2.9%
2100.0 3
 
2.2%
Other values (54) 69
50.7%
ValueCountFrequency (%)
10.0 1
 
0.7%
20.0 1
 
0.7%
30.0 1
 
0.7%
60.0 4
2.9%
80.0 2
1.5%
100.0 2
1.5%
104.0 1
 
0.7%
110.0 1
 
0.7%
120.0 1
 
0.7%
130.0 1
 
0.7%
ValueCountFrequency (%)
12410.0 1
 
0.7%
6000.0 2
 
1.5%
5400.0 1
 
0.7%
5000.0 1
 
0.7%
4600.0 1
 
0.7%
4500.0 2
 
1.5%
4000.0 2
 
1.5%
3900.0 1
 
0.7%
3000.0 12
8.8%
2700.0 2
 
1.5%

년배출예상
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)49.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17396.654
Minimum120
Maximum284700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-13T20:47:23.788239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum120
5-th percentile720
Q13600
median8400
Q324000
95-th percentile54000
Maximum284700
Range284580
Interquartile range (IQR)20400

Descriptive statistics

Standard deviation28155.981
Coefficient of variation (CV)1.618471
Kurtosis60.314245
Mean17396.654
Median Absolute Deviation (MAD)6660
Skewness6.6469213
Sum2365945
Variance7.9275925 × 108
MonotonicityNot monotonic
2024-03-13T20:47:23.945614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7200 12
 
8.8%
36000 9
 
6.6%
3600 9
 
6.6%
24000 6
 
4.4%
12000 6
 
4.4%
18000 5
 
3.7%
720 4
 
2.9%
2160 4
 
2.9%
8400 4
 
2.9%
4800 3
 
2.2%
Other values (57) 74
54.4%
ValueCountFrequency (%)
120 1
 
0.7%
240 2
1.5%
360 1
 
0.7%
720 4
2.9%
960 2
1.5%
1200 2
1.5%
1248 1
 
0.7%
1320 1
 
0.7%
1440 1
 
0.7%
1560 1
 
0.7%
ValueCountFrequency (%)
284700 1
 
0.7%
72000 2
 
1.5%
64800 1
 
0.7%
60000 1
 
0.7%
55200 1
 
0.7%
54000 2
 
1.5%
48000 2
 
1.5%
46800 1
 
0.7%
36500 1
 
0.7%
36000 9
6.6%

처리방법
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
위탁 재활용
136 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row위탁 재활용
2nd row위탁 재활용
3rd row위탁 재활용
4th row위탁 재활용
5th row위탁 재활용

Common Values

ValueCountFrequency (%)
위탁 재활용 136
100.0%

Length

2024-03-13T20:47:24.128938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:47:24.268097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁 136
50.0%
재활용 136
50.0%

Interactions

2024-03-13T20:47:18.984206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:47:18.204902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:47:18.595040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:47:19.094189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:47:18.344222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:47:18.739706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:47:19.240493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:47:18.474956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:47:18.871993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T20:47:24.355962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장구분사업장규모규모월배출예상년배출예상
사업장구분1.0000.8410.6040.0820.000
사업장규모0.8411.0000.8360.4790.395
규모0.6040.8361.0000.0000.000
월배출예상0.0820.4790.0001.0000.904
년배출예상0.0000.3950.0000.9041.000
2024-03-13T20:47:24.466798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장구분사업장규모
사업장구분1.0000.649
사업장규모0.6491.000
2024-03-13T20:47:24.894643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규모월배출예상년배출예상사업장구분사업장규모
규모1.0000.2690.2520.5530.708
월배출예상0.2691.0000.9740.0520.264
년배출예상0.2520.9741.0000.0000.241
사업장구분0.5530.0520.0001.0000.649
사업장규모0.7080.2640.2410.6491.000

Missing values

2024-03-13T20:47:19.405751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:47:19.617328image/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

상호사업장전화번호사업장도로명주소사업장구분사업장규모규모월배출예상년배출예상처리방법
0덕산초등학교413370204충청남도 예산군 덕산면 봉운로 38집단급식소301_500인315.0170.02040위탁 재활용
1내포 남도밥상<NA>충청남도 예산군 삽교읍 예학로 93_ 2층층 203(4)호일반음식점166_330㎡(51_100평)208.121500.018000위탁 재활용
2광시길한우타운식당3310092충청남도 예산군 광시면 예당로 156일반음식점166_330㎡(51_100평)330.881000.012000위탁 재활용
3한백당한식뷔페041-332-0017충청남도 예산군 오가면 충서로 381일반음식점166_330㎡(51_100평)300.0500.06000위탁 재활용
4(주)고려비엔피041 3310213충청남도 예산군 신암면 추사로 235-9집단급식소100_300인105.080.0960위탁 재활용
5장춘한식3373839충청남도 예산군 삽교읍 수암산로 253일반음식점166_330㎡(51_100평)281.94500.06000위탁 재활용
6예산명지병원3346033충청남도 예산군 예산읍 신례원로 26_ 예산명지병원집단급식소301_500인450.060.0720위탁 재활용
7청수가든3373682충청남도 예산군 고덕면 고덕중앙로 45-9일반음식점166_330㎡(51_100평)225.5100.01200위탁 재활용
8대장금337-7971충청남도 예산군 덕산면 온천단지3로 40일반음식점166_330㎡(51_100평)318.651200.014400위탁 재활용
9옛날한식뷔페041 3340181충청남도 예산군 예산읍 충서로 1170일반음식점166_330㎡(51_100평)247.5260.03120위탁 재활용
상호사업장전화번호사업장도로명주소사업장구분사업장규모규모월배출예상년배출예상처리방법
126마중3311998충청남도 예산군 예산읍 역전로140번길 32일반음식점331_660㎡(101_200평)100.01000.012000위탁 재활용
127예산냉면갈비335-9941충청남도 예산군 예산읍 산성공원2길 19일반음식점166_330㎡(51_100평)100.01000.012000위탁 재활용
128지돈가3349003충청남도 예산군 예산읍 주안길 34일반음식점166_330㎡(51_100평)100.02000.024000위탁 재활용
129양지한우타운3331202충청남도 예산군 광시면 광시소길 11일반음식점166_330㎡(51_100평)331.62000.024000위탁 재활용
130더센트럴웨딩331-3000충청남도 예산군 예산읍 예산로 320 (더센트럴웨딩홀)기타661_990㎡(201_300평)300.03900.046800위탁 재활용
131한정식예산041-334-1331충청남도 예산군 예산읍 산성공원1길 24일반음식점166_330㎡(51_100평)250.0530.06360위탁 재활용
132충남경찰청 구내식당336-2621충청남도 예산군 삽교읍 청사로 201 (충청남도지방경찰청)집단급식소100_300인150.0120.01440위탁 재활용
133더스타웨딩컨벤션334-3331충청남도 예산군 예산읍 벚꽃로155번길 52-11기타2001_3000인20000.0600.07200위탁 재활용
134(주)유진엠-동양플랜트예산컴플랙스점3392012충청남도 예산군 고덕면 호음덕령길 60집단급식소100_300인130.0190.02280위탁 재활용
135그린플러스3326421충청남도 예산군 응봉면 응봉로 50-42집단급식소100_300인200.080.0960위탁 재활용