Overview

Dataset statistics

Number of variables9
Number of observations49
Missing cells51
Missing cells (%)11.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory77.7 B

Variable types

Numeric3
Text4
Categorical2

Dataset

Description이 데이터는 충청남도 금산군의 음식물쓰레기 다량배출사업장현황(상호명, 연락처, 소재지, 월배출량, 일배출량, 처리방법) 에 대한 데이터를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=394&beforeMenuCd=DOM_000000201001001000&publicdatapk=15042950

Alerts

데이터 기준일자 has constant value ""Constant
월배출량(kg) is highly overall correlated with 일배출량(kg)High correlation
일배출량(kg) is highly overall correlated with 월배출량(kg)High correlation
연락처 has 2 (4.1%) missing valuesMissing
소재지 도로명주소 has 9 (18.4%) missing valuesMissing
소재지 지번주소 has 40 (81.6%) missing valuesMissing
연번 has unique valuesUnique
상호명 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:19:42.530774
Analysis finished2024-01-09 21:19:43.966224
Duration1.44 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25
Minimum1
Maximum49
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2024-01-10T06:19:44.024079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.4
Q113
median25
Q337
95-th percentile46.6
Maximum49
Range48
Interquartile range (IQR)24

Descriptive statistics

Standard deviation14.28869
Coefficient of variation (CV)0.57154761
Kurtosis-1.2
Mean25
Median Absolute Deviation (MAD)12
Skewness0
Sum1225
Variance204.16667
MonotonicityStrictly increasing
2024-01-10T06:19:44.155835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
1 1
 
2.0%
38 1
 
2.0%
28 1
 
2.0%
29 1
 
2.0%
30 1
 
2.0%
31 1
 
2.0%
32 1
 
2.0%
33 1
 
2.0%
34 1
 
2.0%
35 1
 
2.0%
Other values (39) 39
79.6%
ValueCountFrequency (%)
1 1
2.0%
2 1
2.0%
3 1
2.0%
4 1
2.0%
5 1
2.0%
6 1
2.0%
7 1
2.0%
8 1
2.0%
9 1
2.0%
10 1
2.0%
ValueCountFrequency (%)
49 1
2.0%
48 1
2.0%
47 1
2.0%
46 1
2.0%
45 1
2.0%
44 1
2.0%
43 1
2.0%
42 1
2.0%
41 1
2.0%
40 1
2.0%

상호명
Text

UNIQUE 

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2024-01-10T06:19:44.335056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length8.0408163
Min length2

Characters and Unicode

Total characters394
Distinct characters155
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st row금산초등학교
2nd row중앙초등학교
3rd row금산동초등학교
4th row잔치타운
5th row남경가든
ValueCountFrequency (%)
금산초등학교 1
 
1.8%
중앙초등학교 1
 
1.8%
새금산요양병원 1
 
1.8%
새금산병원장례식장 1
 
1.8%
의료법인예은의료재단 1
 
1.8%
편안요양병원 1
 
1.8%
백합유치원 1
 
1.8%
새금산병원 1
 
1.8%
추어탕잘하는집 1
 
1.8%
금산산업고등학교 1
 
1.8%
Other values (46) 46
82.1%
2024-01-10T06:19:44.599859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 22
 
5.6%
금 19
 
4.8%
교 16
 
4.1%
학 15
 
3.8%
등 11
 
2.8%
원 10
 
2.5%
( 8
 
2.0%
) 8
 
2.0%
장 8
 
2.0%
초 7
 
1.8%
Other values (145) 270
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 366
92.9%
Open Punctuation 8
 
2.0%
Close Punctuation 8
 
2.0%
Space Separator 7
 
1.8%
Uppercase Letter 3
 
0.8%
Other Symbol 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 22
 
6.0%
금 19
 
5.2%
교 16
 
4.4%
학 15
 
4.1%
등 11
 
3.0%
원 10
 
2.7%
장 8
 
2.2%
초 7
 
1.9%
사 6
 
1.6%
고 5
 
1.4%
Other values (139) 247
67.5%
Uppercase Letter
ValueCountFrequency (%)
C 2
66.7%
G 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 368
93.4%
Common 23
 
5.8%
Latin 3
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 22
 
6.0%
금 19
 
5.2%
교 16
 
4.3%
학 15
 
4.1%
등 11
 
3.0%
원 10
 
2.7%
장 8
 
2.2%
초 7
 
1.9%
사 6
 
1.6%
고 5
 
1.4%
Other values (140) 249
67.7%
Common
ValueCountFrequency (%)
( 8
34.8%
) 8
34.8%
7
30.4%
Latin
ValueCountFrequency (%)
C 2
66.7%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 366
92.9%
ASCII 26
 
6.6%
None 2
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 22
 
6.0%
금 19
 
5.2%
교 16
 
4.4%
학 15
 
4.1%
등 11
 
3.0%
원 10
 
2.7%
장 8
 
2.2%
초 7
 
1.9%
사 6
 
1.6%
고 5
 
1.4%
Other values (139) 247
67.5%
ASCII
ValueCountFrequency (%)
( 8
30.8%
) 8
30.8%
7
26.9%
C 2
 
7.7%
G 1
 
3.8%
None
ValueCountFrequency (%)
㈜ 2
100.0%

연락처
Text

MISSING 

Distinct47
Distinct (%)100.0%
Missing2
Missing (%)4.1%
Memory size524.0 B
2024-01-10T06:19:44.810707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.765957
Min length1

Characters and Unicode

Total characters553
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

Unique47 ?
Unique (%)100.0%

Sample

1st row041-753-6231
2nd row041-753-6334
3rd row041-753-6135
4th row041-751-0444
5th row041-754-1133
ValueCountFrequency (%)
041-753-6231 1
 
2.2%
041-751-8878 1
 
2.2%
041-751-4491 1
 
2.2%
041-754-0060 1
 
2.2%
041-754-4474 1
 
2.2%
041-751-0014 1
 
2.2%
041-752-7621 1
 
2.2%
041-754-8272 1
 
2.2%
041-753-0700 1
 
2.2%
041-753-5101 1
 
2.2%
Other values (36) 36
78.3%
2024-01-10T06:19:45.098327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 92
16.6%
1 79
14.3%
0 78
14.1%
4 76
13.7%
7 65
11.8%
5 57
10.3%
3 33
 
6.0%
2 31
 
5.6%
6 18
 
3.3%
8 13
 
2.4%
Other values (2) 11
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 460
83.2%
Dash Punctuation 92
 
16.6%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 79
17.2%
0 78
17.0%
4 76
16.5%
7 65
14.1%
5 57
12.4%
3 33
7.2%
2 31
 
6.7%
6 18
 
3.9%
8 13
 
2.8%
9 10
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 553
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 92
16.6%
1 79
14.3%
0 78
14.1%
4 76
13.7%
7 65
11.8%
5 57
10.3%
3 33
 
6.0%
2 31
 
5.6%
6 18
 
3.3%
8 13
 
2.4%
Other values (2) 11
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 553
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 92
16.6%
1 79
14.3%
0 78
14.1%
4 76
13.7%
7 65
11.8%
5 57
10.3%
3 33
 
6.0%
2 31
 
5.6%
6 18
 
3.3%
8 13
 
2.4%
Other values (2) 11
 
2.0%

소재지 도로명주소
Text

MISSING 

Distinct39
Distinct (%)97.5%
Missing9
Missing (%)18.4%
Memory size524.0 B
2024-01-10T06:19:45.307197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length36
Mean length22.225
Min length18

Characters and Unicode

Total characters889
Distinct characters116
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)95.0%

Sample

1st row충청남도 금산군 금산읍 인삼로 69
2nd row충청남도 금산군 금산읍 금산로 1427
3rd row충청남도 금산군 금산읍 후곤천길 145
4th row충청남도 금산군 추부면 하마전로 23
5th row충청남도 금산군 진산면 대둔산로 412
ValueCountFrequency (%)
충청남도 40
19.2%
금산군 40
19.2%
금산읍 17
 
8.2%
추부면 10
 
4.8%
금산로 4
 
1.9%
인삼로 4
 
1.9%
비단로 3
 
1.4%
21 3
 
1.4%
군북면 3
 
1.4%
남일면 3
 
1.4%
Other values (74) 81
38.9%
2024-01-10T06:19:45.623236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
168
18.9%
산 66
 
7.4%
금 64
 
7.2%
군 44
 
4.9%
남 43
 
4.8%
충 40
 
4.5%
도 40
 
4.5%
청 40
 
4.5%
로 28
 
3.1%
1 28
 
3.1%
Other values (106) 328
36.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 587
66.0%
Space Separator 168
 
18.9%
Decimal Number 113
 
12.7%
Close Punctuation 8
 
0.9%
Open Punctuation 8
 
0.9%
Dash Punctuation 3
 
0.3%
Connector Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 66
 
11.2%
금 64
 
10.9%
군 44
 
7.5%
남 43
 
7.3%
충 40
 
6.8%
도 40
 
6.8%
청 40
 
6.8%
로 28
 
4.8%
면 23
 
3.9%
읍 17
 
2.9%
Other values (91) 182
31.0%
Decimal Number
ValueCountFrequency (%)
1 28
24.8%
2 16
14.2%
3 12
10.6%
5 12
10.6%
8 11
 
9.7%
7 10
 
8.8%
0 7
 
6.2%
4 7
 
6.2%
6 5
 
4.4%
9 5
 
4.4%
Space Separator
ValueCountFrequency (%)
168
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 587
66.0%
Common 302
34.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 66
 
11.2%
금 64
 
10.9%
군 44
 
7.5%
남 43
 
7.3%
충 40
 
6.8%
도 40
 
6.8%
청 40
 
6.8%
로 28
 
4.8%
면 23
 
3.9%
읍 17
 
2.9%
Other values (91) 182
31.0%
Common
ValueCountFrequency (%)
168
55.6%
1 28
 
9.3%
2 16
 
5.3%
3 12
 
4.0%
5 12
 
4.0%
8 11
 
3.6%
7 10
 
3.3%
) 8
 
2.6%
( 8
 
2.6%
0 7
 
2.3%
Other values (5) 22
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 587
66.0%
ASCII 302
34.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
168
55.6%
1 28
 
9.3%
2 16
 
5.3%
3 12
 
4.0%
5 12
 
4.0%
8 11
 
3.6%
7 10
 
3.3%
) 8
 
2.6%
( 8
 
2.6%
0 7
 
2.3%
Other values (5) 22
 
7.3%
Hangul
ValueCountFrequency (%)
산 66
 
11.2%
금 64
 
10.9%
군 44
 
7.5%
남 43
 
7.3%
충 40
 
6.8%
도 40
 
6.8%
청 40
 
6.8%
로 28
 
4.8%
면 23
 
3.9%
읍 17
 
2.9%
Other values (91) 182
31.0%

소재지 지번주소
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing40
Missing (%)81.6%
Memory size524.0 B
2024-01-10T06:19:45.773527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length23.444444
Min length21

Characters and Unicode

Total characters211
Distinct characters40
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

Unique9 ?
Unique (%)100.0%

Sample

1st row충청남도 금산군 금산읍 중도리 224번지
2nd row충청남도 금산군 금산읍 상옥리 8-2번지
3rd row충청남도 금산군 금성면 상가리 152-2번지
4th row충청남도 금산군 진산면 읍내리 531번지
5th row충청남도 금산군 남일면 마장리 1062-44번지
ValueCountFrequency (%)
충청남도 9
20.0%
금산군 9
20.0%
금산읍 4
 
8.9%
중도리 2
 
4.4%
마장리 1
 
2.2%
340-3 1
 
2.2%
상리 1
 
2.2%
1004-1번지 1
 
2.2%
신평리 1
 
2.2%
추부면 1
 
2.2%
Other values (15) 15
33.3%
2024-01-10T06:19:46.076170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
19.9%
금 14
 
6.6%
산 14
 
6.6%
도 11
 
5.2%
남 10
 
4.7%
충 9
 
4.3%
군 9
 
4.3%
청 9
 
4.3%
리 9
 
4.3%
1 7
 
3.3%
Other values (30) 77
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130
61.6%
Space Separator 42
 
19.9%
Decimal Number 33
 
15.6%
Dash Punctuation 6
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
금 14
10.8%
산 14
10.8%
도 11
 
8.5%
남 10
 
7.7%
충 9
 
6.9%
군 9
 
6.9%
청 9
 
6.9%
리 9
 
6.9%
번 7
 
5.4%
지 7
 
5.4%
Other values (20) 31
23.8%
Decimal Number
ValueCountFrequency (%)
1 7
21.2%
2 7
21.2%
4 7
21.2%
3 4
12.1%
0 4
12.1%
5 2
 
6.1%
6 1
 
3.0%
8 1
 
3.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130
61.6%
Common 81
38.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
금 14
10.8%
산 14
10.8%
도 11
 
8.5%
남 10
 
7.7%
충 9
 
6.9%
군 9
 
6.9%
청 9
 
6.9%
리 9
 
6.9%
번 7
 
5.4%
지 7
 
5.4%
Other values (20) 31
23.8%
Common
ValueCountFrequency (%)
42
51.9%
1 7
 
8.6%
2 7
 
8.6%
4 7
 
8.6%
- 6
 
7.4%
3 4
 
4.9%
0 4
 
4.9%
5 2
 
2.5%
6 1
 
1.2%
8 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130
61.6%
ASCII 81
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
51.9%
1 7
 
8.6%
2 7
 
8.6%
4 7
 
8.6%
- 6
 
7.4%
3 4
 
4.9%
0 4
 
4.9%
5 2
 
2.5%
6 1
 
1.2%
8 1
 
1.2%
Hangul
ValueCountFrequency (%)
금 14
10.8%
산 14
10.8%
도 11
 
8.5%
남 10
 
7.7%
충 9
 
6.9%
군 9
 
6.9%
청 9
 
6.9%
리 9
 
6.9%
번 7
 
5.4%
지 7
 
5.4%
Other values (20) 31
23.8%

월배출량(kg)
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean929.16327
Minimum30
Maximum5820
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2024-01-10T06:19:46.192446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile62.4
Q1240
median655
Q31284
95-th percentile2206.4
Maximum5820
Range5790
Interquartile range (IQR)1044

Descriptive statistics

Standard deviation992.94
Coefficient of variation (CV)1.0686389
Kurtosis11.340946
Mean929.16327
Median Absolute Deviation (MAD)552
Skewness2.7095752
Sum45529
Variance985929.85
MonotonicityNot monotonic
2024-01-10T06:19:46.305106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
600 2
 
4.1%
480 2
 
4.1%
800 2
 
4.1%
1550 1
 
2.0%
1423 1
 
2.0%
140 1
 
2.0%
1284 1
 
2.0%
80 1
 
2.0%
1474 1
 
2.0%
113 1
 
2.0%
Other values (36) 36
73.5%
ValueCountFrequency (%)
30 1
2.0%
43 1
2.0%
62 1
2.0%
63 1
2.0%
77 1
2.0%
80 1
2.0%
86 1
2.0%
103 1
2.0%
104 1
2.0%
113 1
2.0%
ValueCountFrequency (%)
5820 1
2.0%
2724 1
2.0%
2330 1
2.0%
2021 1
2.0%
1975 1
2.0%
1916 1
2.0%
1800 1
2.0%
1742 1
2.0%
1550 1
2.0%
1532 1
2.0%

일배출량(kg)
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.330612
Minimum1
Maximum194
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2024-01-10T06:19:46.412323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median24.2
Q349.1
95-th percentile73
Maximum194
Range193
Interquartile range (IQR)41.1

Descriptive statistics

Standard deviation33.451515
Coefficient of variation (CV)1.03467
Kurtosis10.297741
Mean32.330612
Median Absolute Deviation (MAD)20.3
Skewness2.5166889
Sum1584.2
Variance1119.0038
MonotonicityNot monotonic
2024-01-10T06:19:46.539216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
20.0 2
 
4.1%
16.0 2
 
4.1%
2.0 2
 
4.1%
3.4 2
 
4.1%
42.0 2
 
4.1%
26.6 2
 
4.1%
51.6 1
 
2.0%
8.0 1
 
2.0%
49.1 1
 
2.0%
3.7 1
 
2.0%
Other values (33) 33
67.3%
ValueCountFrequency (%)
1.0 1
2.0%
1.4 1
2.0%
2.0 2
4.1%
2.5 1
2.0%
2.6 1
2.0%
2.8 1
2.0%
3.4 2
4.1%
3.7 1
2.0%
3.9 1
2.0%
4.6 1
2.0%
ValueCountFrequency (%)
194.0 1
2.0%
91.0 1
2.0%
77.0 1
2.0%
67.0 1
2.0%
65.8 1
2.0%
63.8 1
2.0%
61.0 1
2.0%
60.0 1
2.0%
58.0 1
2.0%
53.0 1
2.0%

처리방법
Categorical

Distinct2
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size524.0 B
위탁 재활용
43 
자가 재활용
6 

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 43
87.8%
자가 재활용 6
 
12.2%

Length

2024-01-10T06:19:46.651567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:19:46.728389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재활용 49
50.0%
위탁 43
43.9%
자가 6
 
6.1%

데이터 기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
2020-02-14
49 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-02-14
2nd row2020-02-14
3rd row2020-02-14
4th row2020-02-14
5th row2020-02-14

Common Values

ValueCountFrequency (%)
2020-02-14 49
100.0%

Length

2024-01-10T06:19:46.807587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:19:46.875579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-02-14 49
100.0%

Interactions

2024-01-10T06:19:43.497079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:42.884972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:43.300083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:43.566679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:43.168240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:43.362127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:43.638117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:43.230477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:43.426503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:19:46.924520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명연락처소재지 도로명주소소재지 지번주소월배출량(kg)일배출량(kg)처리방법
연번1.0001.0001.0000.9561.0000.0000.0000.000
상호명1.0001.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.0001.000
소재지 도로명주소0.9561.0001.0001.000NaN1.0001.0001.000
소재지 지번주소1.0001.0001.000NaN1.0001.0001.0001.000
월배출량(kg)0.0001.0001.0001.0001.0001.0000.9990.386
일배출량(kg)0.0001.0001.0001.0001.0000.9991.0000.386
처리방법0.0001.0001.0001.0001.0000.3860.3861.000
2024-01-10T06:19:47.029526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번월배출량(kg)일배출량(kg)처리방법
연번1.0000.2200.2530.232
월배출량(kg)0.2201.0000.9710.262
일배출량(kg)0.2530.9711.0000.262
처리방법0.2320.2620.2621.000

Missing values

2024-01-10T06:19:43.735866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:19:43.838464image/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.
2024-01-10T06:19:43.922467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번상호명연락처소재지 도로명주소소재지 지번주소월배출량(kg)일배출량(kg)처리방법데이터 기준일자
01금산초등학교041-753-6231충청남도 금산군 금산읍 인삼로 69<NA>155051.6위탁 재활용2020-02-14
12중앙초등학교041-753-6334충청남도 금산군 금산읍 금산로 1427<NA>79026.0위탁 재활용2020-02-14
23금산동초등학교041-753-6135충청남도 금산군 금산읍 후곤천길 145<NA>2939.7위탁 재활용2020-02-14
34잔치타운041-751-0444<NA>충청남도 금산군 금산읍 중도리 224번지60020.0위탁 재활용2020-02-14
45남경가든041-754-1133<NA>충청남도 금산군 금산읍 상옥리 8-2번지48016.0위탁 재활용2020-02-14
56금성초등학교041-752-3010<NA>충청남도 금산군 금성면 상가리 152-2번지431.4위탁 재활용2020-02-14
67진산초등학교041-752-4020<NA>충청남도 금산군 진산면 읍내리 531번지622.0자가 재활용2020-02-14
78추부초등학교041-753-7908충청남도 금산군 추부면 하마전로 23<NA>1043.4위탁 재활용2020-02-14
89금산하이텍고등학교041-752-4376충청남도 금산군 진산면 대둔산로 412<NA>1033.4위탁 재활용2020-02-14
910금산동중학교041-753-7106충청남도 금산군 금산읍 용머리길 25<NA>94731.5위탁 재활용2020-02-14
연번상호명연락처소재지 도로명주소소재지 지번주소월배출량(kg)일배출량(kg)처리방법데이터 기준일자
3940삼성웰스토리(주)한국타이어금산아카데미<NA>충청남도 금산군 부리면 적벽강로 378 (한국타이어아카데미하우스)<NA>180060.0위탁 재활용2020-02-14
4041삼성웰스토리(주)한국타이어금산생활관041-753-7641충청남도 금산군 제원면 금강로 1 (한국타이어)<NA>63353.0위탁 재활용2020-02-14
4142들녘<NA>충청남도 금산군 금산읍 금산로 1377_ 2층 (새동네슈퍼)<NA>80026.6위탁 재활용2020-02-14
4243(주)에스피씨지에프에스 사조오양금산공장식당041-753-6513충청남도 금산군 추부면 군북로 1294 ((주)사조오양)<NA>123441.1위탁 재활용2020-02-14
4344머들령041-751-7713충청남도 금산군 추부면 검한1길 156 (하늘물빛정원_장산관광농원)<NA>272491.0위탁 재활용2020-02-14
4445(주)세종푸드캠프042-255-0706<NA>충청남도 금산군 추부면 신평리 1004-1번지128142.7위탁 재활용2020-02-14
4546GCC웨딩041-751-8822충청남도 금산군 금성면 금산로 1665<NA>60020.0위탁 재활용2020-02-14
4647이본가041-752-9255<NA>충청남도 금산군 금산읍 상리 340-380026.6위탁 재활용2020-02-14
4748금산원조김정시삼계탕041-752-2678<NA>충청남도 금산군 금산읍 중도리 34-148016.0위탁 재활용2020-02-14
4849두리화장품㈜041-754-5421충청남도 금산군 추부면 다복로 588<NA>2739.1위탁 재활용2020-02-14