Overview

Dataset statistics

Number of variables10
Number of observations193
Missing cells24
Missing cells (%)1.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.0 KiB
Average record size in memory84.7 B

Variable types

Numeric4
Text3
Categorical3

Dataset

Description대전광역시 동구 음식물류폐기물 다량배출사업장 현황으로, 사업장명(상호), 전화번호, 주소, 사업장구분, 일배출량, 월배출량, 연간처리량, 처리방법 등의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15042951/fileData.do

Alerts

일일배출량(kg) is highly overall correlated with 월배출량(kg) and 1 other fieldsHigh correlation
월배출량(kg) is highly overall correlated with 일일배출량(kg) and 1 other fieldsHigh correlation
연간처리량(kg) is highly overall correlated with 일일배출량(kg) and 1 other fieldsHigh correlation
처리방법 is highly imbalanced (68.8%)Imbalance
위탁재활용방법 is highly imbalanced (68.8%)Imbalance
사업장전화 has 24 (12.4%) missing valuesMissing
연번 has unique valuesUnique
상호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:52:29.099117
Analysis finished2023-12-11 23:52:31.770365
Duration2.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct193
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97
Minimum1
Maximum193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T08:52:31.839611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.6
Q149
median97
Q3145
95-th percentile183.4
Maximum193
Range192
Interquartile range (IQR)96

Descriptive statistics

Standard deviation55.858452
Coefficient of variation (CV)0.57586033
Kurtosis-1.2
Mean97
Median Absolute Deviation (MAD)48
Skewness0
Sum18721
Variance3120.1667
MonotonicityStrictly increasing
2023-12-12T08:52:31.981438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
146 1
 
0.5%
124 1
 
0.5%
125 1
 
0.5%
126 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
Other values (183) 183
94.8%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%
187 1
0.5%
186 1
0.5%
185 1
0.5%
184 1
0.5%

상호
Text

UNIQUE 

Distinct193
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T08:52:32.208378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length8.2020725
Min length2

Characters and Unicode

Total characters1583
Distinct characters313
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

Unique193 ?
Unique (%)100.0%

Sample

1st row한밭식당
2nd row태화장
3rd row현암기사식당
4th row청주식당
5th row중국성
ValueCountFrequency (%)
대전대학교 4
 
1.6%
식당 4
 
1.6%
용전점 3
 
1.2%
가오점 3
 
1.2%
대전 2
 
0.8%
가양점 2
 
0.8%
주식회사 2
 
0.8%
유성갈비 2
 
0.8%
우송대학교 2
 
0.8%
샤브쌈주머니 2
 
0.8%
Other values (217) 218
89.3%
2023-12-12T08:52:32.562262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 85
 
5.4%
전 73
 
4.6%
학 54
 
3.4%
51
 
3.2%
교 50
 
3.2%
점 35
 
2.2%
식 33
 
2.1%
등 31
 
2.0%
당 29
 
1.8%
원 28
 
1.8%
Other values (303) 1114
70.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1469
92.8%
Space Separator 51
 
3.2%
Open Punctuation 15
 
0.9%
Close Punctuation 15
 
0.9%
Lowercase Letter 12
 
0.8%
Decimal Number 10
 
0.6%
Uppercase Letter 8
 
0.5%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 85
 
5.8%
전 73
 
5.0%
학 54
 
3.7%
교 50
 
3.4%
점 35
 
2.4%
식 33
 
2.2%
등 31
 
2.1%
당 29
 
2.0%
원 28
 
1.9%
동 26
 
1.8%
Other values (280) 1025
69.8%
Lowercase Letter
ValueCountFrequency (%)
a 3
25.0%
e 2
16.7%
l 2
16.7%
z 1
 
8.3%
b 1
 
8.3%
h 1
 
8.3%
k 1
 
8.3%
s 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
3 3
30.0%
2 3
30.0%
0 2
20.0%
5 1
 
10.0%
4 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
D 2
25.0%
R 2
25.0%
T 2
25.0%
H 1
12.5%
C 1
12.5%
Other Punctuation
ValueCountFrequency (%)
& 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1469
92.8%
Common 94
 
5.9%
Latin 20
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 85
 
5.8%
전 73
 
5.0%
학 54
 
3.7%
교 50
 
3.4%
점 35
 
2.4%
식 33
 
2.2%
등 31
 
2.1%
당 29
 
2.0%
원 28
 
1.9%
동 26
 
1.8%
Other values (280) 1025
69.8%
Latin
ValueCountFrequency (%)
a 3
15.0%
e 2
10.0%
l 2
10.0%
D 2
10.0%
R 2
10.0%
T 2
10.0%
z 1
 
5.0%
H 1
 
5.0%
C 1
 
5.0%
b 1
 
5.0%
Other values (3) 3
15.0%
Common
ValueCountFrequency (%)
51
54.3%
( 15
 
16.0%
) 15
 
16.0%
3 3
 
3.2%
2 3
 
3.2%
& 2
 
2.1%
0 2
 
2.1%
5 1
 
1.1%
4 1
 
1.1%
. 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1469
92.8%
ASCII 114
 
7.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 85
 
5.8%
전 73
 
5.0%
학 54
 
3.7%
교 50
 
3.4%
점 35
 
2.4%
식 33
 
2.2%
등 31
 
2.1%
당 29
 
2.0%
원 28
 
1.9%
동 26
 
1.8%
Other values (280) 1025
69.8%
ASCII
ValueCountFrequency (%)
51
44.7%
( 15
 
13.2%
) 15
 
13.2%
a 3
 
2.6%
3 3
 
2.6%
2 3
 
2.6%
e 2
 
1.8%
l 2
 
1.8%
& 2
 
1.8%
D 2
 
1.8%
Other values (13) 16
 
14.0%

사업장전화
Text

MISSING 

Distinct169
Distinct (%)100.0%
Missing24
Missing (%)12.4%
Memory size1.6 KiB
2023-12-12T08:52:32.903092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.035503
Min length12

Characters and Unicode

Total characters2034
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

Unique169 ?
Unique (%)100.0%

Sample

1st row042-256-1565
2nd row042-256-2407
3rd row042-672-3683
4th row042-257-1455
5th row042-254-3353
ValueCountFrequency (%)
042-282-8403 1
 
0.6%
042-606-1752 1
 
0.6%
042-622-6426 1
 
0.6%
042-273-0900 1
 
0.6%
042-272-9633 1
 
0.6%
070-4771-7801 1
 
0.6%
042-631-0100 1
 
0.6%
070-7882-6032 1
 
0.6%
070-7605-0024 1
 
0.6%
042-272-8882 1
 
0.6%
Other values (159) 159
94.1%
2023-12-12T08:52:33.244527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 414
20.4%
- 338
16.6%
0 302
14.8%
4 245
12.0%
6 138
 
6.8%
8 128
 
6.3%
3 125
 
6.1%
7 108
 
5.3%
5 88
 
4.3%
1 79
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1696
83.4%
Dash Punctuation 338
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 414
24.4%
0 302
17.8%
4 245
14.4%
6 138
 
8.1%
8 128
 
7.5%
3 125
 
7.4%
7 108
 
6.4%
5 88
 
5.2%
1 79
 
4.7%
9 69
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 338
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2034
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 414
20.4%
- 338
16.6%
0 302
14.8%
4 245
12.0%
6 138
 
6.8%
8 128
 
6.3%
3 125
 
6.1%
7 108
 
5.3%
5 88
 
4.3%
1 79
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2034
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 414
20.4%
- 338
16.6%
0 302
14.8%
4 245
12.0%
6 138
 
6.8%
8 128
 
6.3%
3 125
 
6.1%
7 108
 
5.3%
5 88
 
4.3%
1 79
 
3.9%

사업장도로명주소
Text

Distinct191
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-12-12T08:52:33.504100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length42
Mean length27.803109
Min length15

Characters and Unicode

Total characters5366
Distinct characters171
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

Unique189 ?
Unique (%)97.9%

Sample

1st row대전광역시 동구 태전로 3 (중동)
2nd row대전광역시 동구 중앙로203번길 78 1 2 3층 (정동)
3rd row대전광역시 동구 대전천북로 72 (삼성동)
4th row대전광역시 동구 대전로 833 (정동)
5th row대전광역시 동구 대전로815번길 66 (정동)
ValueCountFrequency (%)
대전광역시 193
 
17.2%
동구 193
 
17.2%
2층 24
 
2.1%
가양동 24
 
2.1%
용전동 21
 
1.9%
가오동 18
 
1.6%
1층 17
 
1.5%
판암동 17
 
1.5%
용운동 14
 
1.2%
대전로 13
 
1.2%
Other values (341) 587
52.4%
2023-12-12T08:52:33.876475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1027
19.1%
동 454
 
8.5%
대 307
 
5.7%
전 273
 
5.1%
1 212
 
4.0%
구 209
 
3.9%
시 197
 
3.7%
광 196
 
3.7%
역 194
 
3.6%
( 193
 
3.6%
Other values (161) 2104
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3032
56.5%
Space Separator 1027
 
19.1%
Decimal Number 863
 
16.1%
Open Punctuation 194
 
3.6%
Close Punctuation 194
 
3.6%
Dash Punctuation 40
 
0.7%
Uppercase Letter 14
 
0.3%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 454
15.0%
대 307
 
10.1%
전 273
 
9.0%
구 209
 
6.9%
시 197
 
6.5%
광 196
 
6.5%
역 194
 
6.4%
로 184
 
6.1%
층 61
 
2.0%
길 54
 
1.8%
Other values (134) 903
29.8%
Decimal Number
ValueCountFrequency (%)
1 212
24.6%
2 129
14.9%
3 95
11.0%
4 78
 
9.0%
6 76
 
8.8%
0 66
 
7.6%
5 65
 
7.5%
7 64
 
7.4%
8 43
 
5.0%
9 35
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
B 4
28.6%
C 3
21.4%
H 1
 
7.1%
R 1
 
7.1%
J 1
 
7.1%
T 1
 
7.1%
O 1
 
7.1%
W 1
 
7.1%
N 1
 
7.1%
Open Punctuation
ValueCountFrequency (%)
( 193
99.5%
[ 1
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 193
99.5%
] 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
* 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
1027
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3032
56.5%
Common 2320
43.2%
Latin 14
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 454
15.0%
대 307
 
10.1%
전 273
 
9.0%
구 209
 
6.9%
시 197
 
6.5%
광 196
 
6.5%
역 194
 
6.4%
로 184
 
6.1%
층 61
 
2.0%
길 54
 
1.8%
Other values (134) 903
29.8%
Common
ValueCountFrequency (%)
1027
44.3%
1 212
 
9.1%
( 193
 
8.3%
) 193
 
8.3%
2 129
 
5.6%
3 95
 
4.1%
4 78
 
3.4%
6 76
 
3.3%
0 66
 
2.8%
5 65
 
2.8%
Other values (8) 186
 
8.0%
Latin
ValueCountFrequency (%)
B 4
28.6%
C 3
21.4%
H 1
 
7.1%
R 1
 
7.1%
J 1
 
7.1%
T 1
 
7.1%
O 1
 
7.1%
W 1
 
7.1%
N 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3032
56.5%
ASCII 2334
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1027
44.0%
1 212
 
9.1%
( 193
 
8.3%
) 193
 
8.3%
2 129
 
5.5%
3 95
 
4.1%
4 78
 
3.3%
6 76
 
3.3%
0 66
 
2.8%
5 65
 
2.8%
Other values (17) 200
 
8.6%
Hangul
ValueCountFrequency (%)
동 454
15.0%
대 307
 
10.1%
전 273
 
9.0%
구 209
 
6.9%
시 197
 
6.5%
광 196
 
6.5%
역 194
 
6.4%
로 184
 
6.1%
층 61
 
2.0%
길 54
 
1.8%
Other values (134) 903
29.8%

사업장구분
Categorical

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
일반음식점
104 
집단급식소
84 
휴게음식점
 
2
관광숙박업
 
2
대규모점포
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 104
53.9%
집단급식소 84
43.5%
휴게음식점 2
 
1.0%
관광숙박업 2
 
1.0%
대규모점포 1
 
0.5%

Length

2023-12-12T08:52:33.993176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:52:34.082450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 104
53.9%
집단급식소 84
43.5%
휴게음식점 2
 
1.0%
관광숙박업 2
 
1.0%
대규모점포 1
 
0.5%

일일배출량(kg)
Real number (ℝ)

HIGH CORRELATION 

Distinct96
Distinct (%)49.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.072539
Minimum3
Maximum348
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T08:52:34.213348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile13.6
Q125
median43
Q370
95-th percentile138.8
Maximum348
Range345
Interquartile range (IQR)45

Descriptive statistics

Standard deviation48.213014
Coefficient of variation (CV)0.84476729
Kurtosis12.138077
Mean57.072539
Median Absolute Deviation (MAD)19
Skewness2.8408789
Sum11015
Variance2324.4947
MonotonicityNot monotonic
2023-12-12T08:52:34.334732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25 8
 
4.1%
50 7
 
3.6%
33 6
 
3.1%
42 6
 
3.1%
23 6
 
3.1%
20 5
 
2.6%
61 5
 
2.6%
56 5
 
2.6%
90 4
 
2.1%
10 4
 
2.1%
Other values (86) 137
71.0%
ValueCountFrequency (%)
3 1
 
0.5%
5 1
 
0.5%
7 1
 
0.5%
9 1
 
0.5%
10 4
2.1%
13 2
1.0%
14 1
 
0.5%
15 1
 
0.5%
16 3
1.6%
17 1
 
0.5%
ValueCountFrequency (%)
348 1
0.5%
332 1
0.5%
222 1
0.5%
207 1
0.5%
189 1
0.5%
173 1
0.5%
160 1
0.5%
153 1
0.5%
141 1
0.5%
140 1
0.5%

월배출량(kg)
Real number (ℝ)

HIGH CORRELATION 

Distinct168
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1711.8705
Minimum93
Maximum10436
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T08:52:34.471035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum93
5-th percentile416.2
Q1754
median1288
Q32103
95-th percentile4159
Maximum10436
Range10343
Interquartile range (IQR)1349

Descriptive statistics

Standard deviation1446.675
Coefficient of variation (CV)0.84508436
Kurtosis12.110299
Mean1711.8705
Median Absolute Deviation (MAD)581
Skewness2.8385362
Sum330391
Variance2092868.4
MonotonicityNot monotonic
2023-12-12T08:52:34.605155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1500 6
 
3.1%
600 4
 
2.1%
750 4
 
2.1%
2700 3
 
1.6%
1667 3
 
1.6%
300 3
 
1.6%
900 3
 
1.6%
1250 3
 
1.6%
2970 2
 
1.0%
850 2
 
1.0%
Other values (158) 160
82.9%
ValueCountFrequency (%)
93 1
 
0.5%
150 1
 
0.5%
200 1
 
0.5%
271 1
 
0.5%
300 3
1.6%
313 1
 
0.5%
378 1
 
0.5%
400 1
 
0.5%
427 1
 
0.5%
450 1
 
0.5%
ValueCountFrequency (%)
10436 1
0.5%
9956 1
0.5%
6664 1
0.5%
6200 1
0.5%
5684 1
0.5%
5193 1
0.5%
4800 1
0.5%
4598 1
0.5%
4243 1
0.5%
4207 1
0.5%

연간처리량(kg)
Real number (ℝ)

HIGH CORRELATION 

Distinct168
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20541.642
Minimum1110
Maximum125230
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-12T08:52:34.732455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1110
5-th percentile4992
Q19045
median15450
Q325235
95-th percentile49906
Maximum125230
Range124120
Interquartile range (IQR)16190

Descriptive statistics

Standard deviation17360.124
Coefficient of variation (CV)0.8451186
Kurtosis12.109644
Mean20541.642
Median Absolute Deviation (MAD)6970
Skewness2.8384251
Sum3964537
Variance3.0137391 × 108
MonotonicityNot monotonic
2023-12-12T08:52:34.868006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18000 6
 
3.1%
7200 4
 
2.1%
9000 4
 
2.1%
32400 3
 
1.6%
20000 3
 
1.6%
3600 3
 
1.6%
10800 3
 
1.6%
15000 3
 
1.6%
35640 2
 
1.0%
10200 2
 
1.0%
Other values (158) 160
82.9%
ValueCountFrequency (%)
1110 1
 
0.5%
1800 1
 
0.5%
2400 1
 
0.5%
3250 1
 
0.5%
3600 3
1.6%
3750 1
 
0.5%
4540 1
 
0.5%
4800 1
 
0.5%
5120 1
 
0.5%
5400 1
 
0.5%
ValueCountFrequency (%)
125230 1
0.5%
119470 1
0.5%
79970 1
0.5%
74400 1
0.5%
68205 1
0.5%
62310 1
0.5%
57600 1
0.5%
55170 1
0.5%
50920 1
0.5%
50485 1
0.5%

처리방법
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
위탁재활용
175 
자가감량처리
 
16
자가감량처리 및 위탁재활용병행
 
2

Length

Max length16
Median length5
Mean length5.1968912
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위탁재활용 175
90.7%
자가감량처리 16
 
8.3%
자가감량처리 및 위탁재활용병행 2
 
1.0%

Length

2023-12-12T08:52:35.005628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:52:35.122781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위탁재활용 175
88.8%
자가감량처리 18
 
9.1%
및 2
 
1.0%
위탁재활용병행 2
 
1.0%

위탁재활용방법
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
사료화
175 
<NA>
 
16
퇴비화
 
2

Length

Max length4
Median length3
Mean length3.0829016
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사료화 175
90.7%
<NA> 16
 
8.3%
퇴비화 2
 
1.0%

Length

2023-12-12T08:52:35.257604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:52:35.380466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사료화 175
90.7%
na 16
 
8.3%
퇴비화 2
 
1.0%

Interactions

2023-12-12T08:52:30.809113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:29.659682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:30.007714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:30.360895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:30.937487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:29.754599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:30.096735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:30.451560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:31.063184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:29.845220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:30.190739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:30.558236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:31.151159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:29.927264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:30.272911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:52:30.677904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:52:35.453877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업장구분일일배출량(kg)월배출량(kg)연간처리량(kg)처리방법위탁재활용방법
연번1.0000.8320.2640.2590.2580.3640.300
사업장구분0.8321.0000.3480.2990.3040.4330.000
일일배출량(kg)0.2640.3481.0001.0001.0000.4980.547
월배출량(kg)0.2590.2991.0001.0001.0000.4680.481
연간처리량(kg)0.2580.3041.0001.0001.0000.4670.481
처리방법0.3640.4330.4980.4680.4671.0000.000
위탁재활용방법0.3000.0000.5470.4810.4810.0001.000
2023-12-12T08:52:35.557056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위탁재활용방법처리방법사업장구분
위탁재활용방법1.0000.0000.000
처리방법0.0001.0000.362
사업장구분0.0000.3621.000
2023-12-12T08:52:35.655359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번일일배출량(kg)월배출량(kg)연간처리량(kg)사업장구분처리방법위탁재활용방법
연번1.0000.2500.2510.2510.4900.2320.210
일일배출량(kg)0.2501.0001.0001.0000.2200.3600.405
월배출량(kg)0.2511.0001.0001.0000.1860.3320.356
연간처리량(kg)0.2511.0001.0001.0000.1860.3320.356
사업장구분0.4900.2200.1860.1861.0000.3620.000
처리방법0.2320.3600.3320.3320.3621.0000.000
위탁재활용방법0.2100.4050.3560.3560.0000.0001.000

Missing values

2023-12-12T08:52:31.558879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:52:31.718912image/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

연번상호사업장전화사업장도로명주소사업장구분일일배출량(kg)월배출량(kg)연간처리량(kg)처리방법위탁재활용방법
01한밭식당042-256-1565대전광역시 동구 태전로 3 (중동)일반음식점33100012000위탁재활용사료화
12태화장042-256-2407대전광역시 동구 중앙로203번길 78 1 2 3층 (정동)일반음식점33100012000위탁재활용사료화
23현암기사식당042-672-3683대전광역시 동구 대전천북로 72 (삼성동)일반음식점3329956119470위탁재활용사료화
34청주식당042-257-1455대전광역시 동구 대전로 833 (정동)일반음식점185436520위탁재활용사료화
45중국성042-254-3353대전광역시 동구 대전로815번길 66 (정동)일반음식점216217450위탁재활용사료화
56별천지042-271-0207대전광역시 동구 산서로1659번길 29 (대별동)일반음식점70211325360위탁재활용사료화
67평양숨두부식당042-284-4141대전광역시 동구 대전로 381 (대성동)일반음식점236858220위탁재활용사료화
78만인산식당042-274-0700대전광역시 동구 산내로 111 (하소동)일반음식점96288234580위탁재활용사료화
89정현육가공식당042-282-8403대전광역시 동구 판암로 17 (판암동)일반음식점44133015960위탁재활용사료화
910오씨칼국수042-627-9972대전광역시 동구 옛신탄진로 13 (삼성동)일반음식점42125015000위탁재활용사료화
연번상호사업장전화사업장도로명주소사업장구분일일배출량(kg)월배출량(kg)연간처리량(kg)처리방법위탁재활용방법
183184씨제이프레시웨이 우송대학교 청운숙점<NA>대전광역시 동구 동대전로183번길 5 지하1층 (자양동)집단급식소56166720000위탁재활용사료화
184185글로벌튼튼병원<NA>대전광역시 동구 계족로 516 지하1층 (용전동)집단급식소42125015000위탁재활용사료화
185186누리엘병원<NA>대전광역시 동구 동서대로 1641 아남빌딩 2층 (용전동)집단급식소236938320위탁재활용사료화
186187보광노인전문병원<NA>대전광역시 동구 산내로560번길 18-11 보광노인전문병원 (상소동)집단급식소41122514700자가감량처리<NA>
187188의료법인 고려의료재단 원동요양병원042-535-9999대전광역시 동구 대전로 742 대전원동건축자재판매시설 4층 (원동)집단급식소42126015120자가감량처리<NA>
188189대전그린의료소비자생활협동조합그린요양병원042-274-9449대전광역시 동구 옥천로176번길 15-4 (판암동 5층)집단급식소99297035640자가감량처리<NA>
189190만인산 푸른학습원042-280-5566대전광역시 동구 산내로 106 (하소동)집단급식소216307560위탁재활용사료화
190191belleza호텔042-622-7800대전광역시 동구 동서대로1683번길 46-8 (용전동)관광숙박업50150218020위탁재활용사료화
191192호텔선샤인042-673-8800대전광역시 동구 동서대로 1700 (가양동)관광숙박업160480057600자가감량처리 및 위탁재활용병행사료화
192193케이알유통(패션아일랜드)042-280-9011대전광역시 동구 은어송로 72 패션아일랜드 2층 사무실대규모점포61182121850위탁재활용사료화