Overview

Dataset statistics

Number of variables12
Number of observations345
Missing cells128
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.8 KiB
Average record size in memory100.4 B

Variable types

Numeric4
Categorical5
Text3

Dataset

Description충청남도 당진시 음식물쓰레기 다량배출사업장에대한 공공데이터로 연도별 배출량, 월별 배출량, 일별 배출량 등을 제공하고 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=302&beforeMenuCd=DOM_000000201001001000&publicdatapk=15094904

Alerts

지역 is highly overall correlated with 연번 and 7 other fieldsHigh correlation
시-군-읍 is highly overall correlated with 연번 and 7 other fieldsHigh correlation
위탁처리업체명 is highly overall correlated with 지역 and 2 other fieldsHigh correlation
사업장구분 is highly overall correlated with 지역 and 1 other fieldsHigh correlation
처리방법 is highly overall correlated with 지역 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 지역 and 1 other fieldsHigh correlation
일배출량 is highly overall correlated with 월배출량 and 3 other fieldsHigh correlation
월배출량 is highly overall correlated with 일배출량 and 3 other fieldsHigh correlation
년배출량 is highly overall correlated with 일배출량 and 3 other fieldsHigh correlation
지역 is highly imbalanced (97.1%)Imbalance
시-군-읍 is highly imbalanced (97.1%)Imbalance
사업장구분 is highly imbalanced (62.4%)Imbalance
위탁처리업체명 is highly imbalanced (59.5%)Imbalance
사업장 전화번호 has 123 (35.7%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:20:23.788622
Analysis finished2024-01-09 21:20:25.937561
Duration2.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct345
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean173.01159
Minimum1
Maximum347
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-01-10T06:20:25.994152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18.2
Q187
median173
Q3259
95-th percentile327.8
Maximum347
Range346
Interquartile range (IQR)172

Descriptive statistics

Standard deviation99.757205
Coefficient of variation (CV)0.5765926
Kurtosis-1.199036
Mean173.01159
Median Absolute Deviation (MAD)86
Skewness0.00069495653
Sum59689
Variance9951.4999
MonotonicityStrictly increasing
2024-01-10T06:20:26.323611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
228 1
 
0.3%
236 1
 
0.3%
235 1
 
0.3%
234 1
 
0.3%
233 1
 
0.3%
232 1
 
0.3%
231 1
 
0.3%
230 1
 
0.3%
229 1
 
0.3%
Other values (335) 335
97.1%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
347 1
0.3%
345 1
0.3%
344 1
0.3%
342 1
0.3%
341 1
0.3%
340 1
0.3%
339 1
0.3%
338 1
0.3%
337 1
0.3%
336 1
0.3%

지역
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
충청남도
344 
<NA>
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
충청남도 344
99.7%
<NA> 1
 
0.3%

Length

2024-01-10T06:20:26.438138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:20:26.514922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 344
99.7%
na 1
 
0.3%

시-군-읍
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
당진시
344 
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0028986
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
당진시 344
99.7%
<NA> 1
 
0.3%

Length

2024-01-10T06:20:26.597366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:20:26.676615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
당진시 344
99.7%
na 1
 
0.3%

사업장구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
일반음식점
211 
집단급식소
124 
장례식장
 
2
대규모점포
 
2
일반음식점
 
2
Other values (4)
 
4

Length

Max length12
Median length5
Mean length5.0173913
Min length2

Unique

Unique4 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 211
61.2%
집단급식소 124
35.9%
장례식장 2
 
0.6%
대규모점포 2
 
0.6%
일반음식점 2
 
0.6%
집단급식소- 일반음식점 1
 
0.3%
호텔 1
 
0.3%
<NA> 1
 
0.3%
농수산물도매시장 1
 
0.3%

Length

2024-01-10T06:20:26.762745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:20:26.868467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 214
61.8%
집단급식소 125
36.1%
장례식장 2
 
0.6%
대규모점포 2
 
0.6%
호텔 1
 
0.3%
na 1
 
0.3%
농수산물도매시장 1
 
0.3%

상호
Text

Distinct340
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-01-10T06:20:27.144217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length6.6376812
Min length2

Characters and Unicode

Total characters2290
Distinct characters376
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique335 ?
Unique (%)97.1%

Sample

1st row당진초등학교
2nd row빌텍
3rd row송산초등학교
4th row석문초등학교
5th row계성초등학교
ValueCountFrequency (%)
주식회사 5
 
1.1%
아라마크 4
 
0.9%
횟집 4
 
0.9%
당진점 4
 
0.9%
본우리집밥 3
 
0.7%
제이에스지 3
 
0.7%
아워홈 3
 
0.7%
빌텍 2
 
0.5%
본푸드서비스본우리집밥 2
 
0.5%
항아리 2
 
0.5%
Other values (392) 405
92.7%
2024-01-10T06:20:27.501597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
106
 
4.6%
당 69
 
3.0%
이 52
 
2.3%
교 45
 
2.0%
식 42
 
1.8%
진 42
 
1.8%
학 41
 
1.8%
리 40
 
1.7%
스 36
 
1.6%
등 35
 
1.5%
Other values (366) 1782
77.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2158
94.2%
Space Separator 106
 
4.6%
Decimal Number 10
 
0.4%
Other Symbol 9
 
0.4%
Uppercase Letter 7
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 69
 
3.2%
이 52
 
2.4%
교 45
 
2.1%
식 42
 
1.9%
진 42
 
1.9%
학 41
 
1.9%
리 40
 
1.9%
스 36
 
1.7%
등 35
 
1.6%
한 32
 
1.5%
Other values (354) 1724
79.9%
Decimal Number
ValueCountFrequency (%)
1 3
30.0%
2 2
20.0%
3 2
20.0%
0 1
 
10.0%
5 1
 
10.0%
9 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
S 3
42.9%
F 2
28.6%
P 1
 
14.3%
E 1
 
14.3%
Space Separator
ValueCountFrequency (%)
106
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2167
94.6%
Common 116
 
5.1%
Latin 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 69
 
3.2%
이 52
 
2.4%
교 45
 
2.1%
식 42
 
1.9%
진 42
 
1.9%
학 41
 
1.9%
리 40
 
1.8%
스 36
 
1.7%
등 35
 
1.6%
한 32
 
1.5%
Other values (355) 1733
80.0%
Common
ValueCountFrequency (%)
106
91.4%
1 3
 
2.6%
2 2
 
1.7%
3 2
 
1.7%
0 1
 
0.9%
5 1
 
0.9%
9 1
 
0.9%
Latin
ValueCountFrequency (%)
S 3
42.9%
F 2
28.6%
P 1
 
14.3%
E 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2158
94.2%
ASCII 123
 
5.4%
None 9
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
106
86.2%
1 3
 
2.4%
S 3
 
2.4%
2 2
 
1.6%
F 2
 
1.6%
3 2
 
1.6%
0 1
 
0.8%
5 1
 
0.8%
9 1
 
0.8%
P 1
 
0.8%
Hangul
ValueCountFrequency (%)
당 69
 
3.2%
이 52
 
2.4%
교 45
 
2.1%
식 42
 
1.9%
진 42
 
1.9%
학 41
 
1.9%
리 40
 
1.9%
스 36
 
1.7%
등 35
 
1.6%
한 32
 
1.5%
Other values (354) 1724
79.9%
None
ValueCountFrequency (%)
㈜ 9
100.0%

사업장 전화번호
Text

MISSING 

Distinct215
Distinct (%)96.8%
Missing123
Missing (%)35.7%
Memory size2.8 KiB
2024-01-10T06:20:27.701129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.959459
Min length11

Characters and Unicode

Total characters2655
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

Unique209 ?
Unique (%)94.1%

Sample

1st row041-357-3750
2nd row041-351-8227
3rd row041-352-9681
4th row041-353-9344
5th row041-352-4032
ValueCountFrequency (%)
031-493-5343 3
 
1.4%
041-362-8992 2
 
0.9%
041-350-1578 2
 
0.9%
041-358-2570 2
 
0.9%
041-350-8127 2
 
0.9%
041-363-4446 2
 
0.9%
053-202-5155 1
 
0.5%
041-357-1337 1
 
0.5%
041-359-3801 1
 
0.5%
041-353-4144 1
 
0.5%
Other values (205) 205
92.3%
2024-01-10T06:20:28.026437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 430
16.2%
0 370
13.9%
4 332
12.5%
3 326
12.3%
1 314
11.8%
5 290
10.9%
2 150
 
5.6%
6 135
 
5.1%
8 111
 
4.2%
7 99
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2225
83.8%
Dash Punctuation 430
 
16.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 370
16.6%
4 332
14.9%
3 326
14.7%
1 314
14.1%
5 290
13.0%
2 150
6.7%
6 135
 
6.1%
8 111
 
5.0%
7 99
 
4.4%
9 98
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 430
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2655
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 430
16.2%
0 370
13.9%
4 332
12.5%
3 326
12.3%
1 314
11.8%
5 290
10.9%
2 150
 
5.6%
6 135
 
5.1%
8 111
 
4.2%
7 99
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2655
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 430
16.2%
0 370
13.9%
4 332
12.5%
3 326
12.3%
1 314
11.8%
5 290
10.9%
2 150
 
5.6%
6 135
 
5.1%
8 111
 
4.2%
7 99
 
3.7%

사업장 지번주소
Text

Distinct327
Distinct (%)95.6%
Missing3
Missing (%)0.9%
Memory size2.8 KiB
2024-01-10T06:20:28.273003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length20
Mean length15.353801
Min length9

Characters and Unicode

Total characters5251
Distinct characters154
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique315 ?
Unique (%)92.1%

Sample

1st row당진시 읍내동 교동길 106
2nd row당진시 송악읍 북부산업로 1228
3rd row당진시 송산면 상거리 323
4th row당진시 석문면 통정리 596-1
5th row당진시 읍내리 13
ValueCountFrequency (%)
당진시 339
27.0%
송악읍 54
 
4.3%
신평면 44
 
3.5%
석문면 32
 
2.6%
합덕읍 24
 
1.9%
송산면 23
 
1.8%
순성면 13
 
1.0%
삽교천3길 12
 
1.0%
대호만로 12
 
1.0%
서해로 10
 
0.8%
Other values (486) 691
55.1%
2024-01-10T06:20:28.603729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
921
17.5%
시 364
 
6.9%
당 363
 
6.9%
진 362
 
6.9%
1 280
 
5.3%
2 192
 
3.7%
로 174
 
3.3%
면 153
 
2.9%
3 151
 
2.9%
- 123
 
2.3%
Other values (144) 2168
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2983
56.8%
Decimal Number 1223
23.3%
Space Separator 921
 
17.5%
Dash Punctuation 123
 
2.3%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 364
 
12.2%
당 363
 
12.2%
진 362
 
12.1%
로 174
 
5.8%
면 153
 
5.1%
길 102
 
3.4%
송 97
 
3.3%
읍 91
 
3.1%
리 65
 
2.2%
악 64
 
2.1%
Other values (131) 1148
38.5%
Decimal Number
ValueCountFrequency (%)
1 280
22.9%
2 192
15.7%
3 151
12.3%
5 120
9.8%
7 92
 
7.5%
4 83
 
6.8%
8 83
 
6.8%
0 78
 
6.4%
6 74
 
6.1%
9 70
 
5.7%
Space Separator
ValueCountFrequency (%)
921
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 123
100.0%
Uppercase Letter
ValueCountFrequency (%)
F 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2983
56.8%
Common 2267
43.2%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 364
 
12.2%
당 363
 
12.2%
진 362
 
12.1%
로 174
 
5.8%
면 153
 
5.1%
길 102
 
3.4%
송 97
 
3.3%
읍 91
 
3.1%
리 65
 
2.2%
악 64
 
2.1%
Other values (131) 1148
38.5%
Common
ValueCountFrequency (%)
921
40.6%
1 280
 
12.4%
2 192
 
8.5%
3 151
 
6.7%
- 123
 
5.4%
5 120
 
5.3%
7 92
 
4.1%
4 83
 
3.7%
8 83
 
3.7%
0 78
 
3.4%
Other values (2) 144
 
6.4%
Latin
ValueCountFrequency (%)
F 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2983
56.8%
ASCII 2268
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
921
40.6%
1 280
 
12.3%
2 192
 
8.5%
3 151
 
6.7%
- 123
 
5.4%
5 120
 
5.3%
7 92
 
4.1%
4 83
 
3.7%
8 83
 
3.7%
0 78
 
3.4%
Other values (3) 145
 
6.4%
Hangul
ValueCountFrequency (%)
시 364
 
12.2%
당 363
 
12.2%
진 362
 
12.1%
로 174
 
5.8%
면 153
 
5.1%
길 102
 
3.4%
송 97
 
3.3%
읍 91
 
3.1%
리 65
 
2.2%
악 64
 
2.1%
Other values (131) 1148
38.5%

일배출량
Real number (ℝ)

HIGH CORRELATION 

Distinct94
Distinct (%)27.3%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean41.482558
Minimum1
Maximum425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-01-10T06:20:28.719927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q113
median26.5
Q350
95-th percentile131.4
Maximum425
Range424
Interquartile range (IQR)37

Descriptive statistics

Standard deviation48.538341
Coefficient of variation (CV)1.1700903
Kurtosis16.632824
Mean41.482558
Median Absolute Deviation (MAD)16.5
Skewness3.3522373
Sum14270
Variance2355.9705
MonotonicityNot monotonic
2024-01-10T06:20:28.822472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 15
 
4.3%
40 15
 
4.3%
30 15
 
4.3%
8 14
 
4.1%
17 14
 
4.1%
20 13
 
3.8%
50 13
 
3.8%
13 11
 
3.2%
14 10
 
2.9%
100 9
 
2.6%
Other values (84) 215
62.3%
ValueCountFrequency (%)
1 3
 
0.9%
2 3
 
0.9%
3 5
 
1.4%
4 5
 
1.4%
5 7
2.0%
6 5
 
1.4%
7 8
2.3%
8 14
4.1%
9 1
 
0.3%
10 15
4.3%
ValueCountFrequency (%)
425 1
 
0.3%
307 1
 
0.3%
300 1
 
0.3%
201 1
 
0.3%
200 3
0.9%
197 1
 
0.3%
191 1
 
0.3%
167 4
1.2%
150 2
0.6%
140 1
 
0.3%

월배출량
Real number (ℝ)

HIGH CORRELATION 

Distinct194
Distinct (%)56.4%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean1243.7703
Minimum25
Maximum12750
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-01-10T06:20:28.927855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile150
Q1400
median790
Q31500
95-th percentile3943.5
Maximum12750
Range12725
Interquartile range (IQR)1100

Descriptive statistics

Standard deviation1456.2111
Coefficient of variation (CV)1.1708038
Kurtosis16.620221
Mean1243.7703
Median Absolute Deviation (MAD)487
Skewness3.3503155
Sum427857
Variance2120550.8
MonotonicityNot monotonic
2024-01-10T06:20:29.035634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
900 13
 
3.8%
300 12
 
3.5%
1200 12
 
3.5%
1500 11
 
3.2%
600 10
 
2.9%
500 9
 
2.6%
3000 9
 
2.6%
250 9
 
2.6%
480 7
 
2.0%
400 7
 
2.0%
Other values (184) 245
71.0%
ValueCountFrequency (%)
25 1
0.3%
31 1
0.3%
40 1
0.3%
45 1
0.3%
60 1
0.3%
61 1
0.3%
78 1
0.3%
83 1
0.3%
90 2
0.6%
92 1
0.3%
ValueCountFrequency (%)
12750 1
 
0.3%
9200 1
 
0.3%
9000 1
 
0.3%
6038 1
 
0.3%
6000 3
0.9%
5915 1
 
0.3%
5723 1
 
0.3%
5000 4
1.2%
4500 2
0.6%
4192 1
 
0.3%

년배출량
Real number (ℝ)

HIGH CORRELATION 

Distinct199
Distinct (%)57.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14887.104
Minimum300
Maximum153000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.2 KiB
2024-01-10T06:20:29.138984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum300
5-th percentile1800
Q14800
median9360
Q318000
95-th percentile47256
Maximum153000
Range152700
Interquartile range (IQR)13200

Descriptive statistics

Standard deviation17463.264
Coefficient of variation (CV)1.1730464
Kurtosis16.643244
Mean14887.104
Median Absolute Deviation (MAD)5720
Skewness3.3523376
Sum5136051
Variance3.0496559 × 108
MonotonicityNot monotonic
2024-01-10T06:20:29.247856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10800 13
 
3.8%
14400 12
 
3.5%
3600 12
 
3.5%
18000 11
 
3.2%
7200 10
 
2.9%
36000 9
 
2.6%
6000 9
 
2.6%
3000 9
 
2.6%
4800 7
 
2.0%
5760 7
 
2.0%
Other values (189) 246
71.3%
ValueCountFrequency (%)
300 1
0.3%
370 1
0.3%
480 1
0.3%
540 1
0.3%
720 1
0.3%
735 1
0.3%
930 1
0.3%
1000 1
0.3%
1080 2
0.6%
1100 1
0.3%
ValueCountFrequency (%)
153000 1
 
0.3%
110400 1
 
0.3%
108000 1
 
0.3%
72450 1
 
0.3%
72000 3
0.9%
70980 1
 
0.3%
68680 1
 
0.3%
60000 4
1.2%
54000 2
0.6%
50300 1
 
0.3%

위탁처리업체명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct20
Distinct (%)5.8%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
재활용 처리-대생리클린 수집운반-대생이엔티
243 
재활용 처리-그린아산 수집운반-세움환경
35 
인영호
25 
서해농산
 
10
경희축산
 
10
Other values (15)
 
22

Length

Max length24
Median length24
Mean length19.811594
Min length2

Unique

Unique11 ?
Unique (%)3.2%

Sample

1st row재활용 처리-대생리클린 수집운반-대생이엔티
2nd row재활용 처리-두비원 수집운반-리코
3rd row재활용 처리-대생리클린 수집운반-대생이엔티
4th row재활용 처리-대생리클린 수집운반-대생이엔티
5th row재활용 처리-대생리클린 수집운반-대생이엔티

Common Values

ValueCountFrequency (%)
재활용 처리-대생리클린 수집운반-대생이엔티 243
70.4%
재활용 처리-그린아산 수집운반-세움환경 35
 
10.1%
인영호 25
 
7.2%
서해농산 10
 
2.9%
경희축산 10
 
2.9%
양지농장 4
 
1.2%
원당농장 3
 
0.9%
재활용 처리-두비원 수집운반-리코 2
 
0.6%
신농씨앤피 2
 
0.6%
김선호 1
 
0.3%
Other values (10) 10
 
2.9%

Length

2024-01-10T06:20:29.361638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
재활용 280
30.9%
수집운반-대생이엔티 243
26.9%
처리-대생리클린 243
26.9%
처리-그린아산 35
 
3.9%
수집운반-세움환경 35
 
3.9%
인영호 25
 
2.8%
서해농산 10
 
1.1%
경희축산 10
 
1.1%
양지농장 4
 
0.4%
원당농장 3
 
0.3%
Other values (14) 17
 
1.9%

처리방법
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
퇴비화
246 
사료화
98 
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0028986
Min length3

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
퇴비화 246
71.3%
사료화 98
 
28.4%
<NA> 1
 
0.3%

Length

2024-01-10T06:20:29.455410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:20:29.540823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
퇴비화 246
71.3%
사료화 98
 
28.4%
na 1
 
0.3%

Interactions

2024-01-10T06:20:25.272469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:24.410089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:24.704174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:24.994969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:25.345842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:24.481764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:24.793283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:25.069275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:25.415175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:24.545060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:24.859418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:25.131800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:25.486682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:24.614463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:24.925878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:20:25.197806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:20:29.596182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업장구분일배출량월배출량년배출량위탁처리업체명처리방법
연번1.0000.3900.1880.1800.1800.2420.126
사업장구분0.3901.0000.2000.2060.2040.0000.372
일배출량0.1880.2001.0001.0001.0000.0910.033
월배출량0.1800.2061.0001.0001.0000.1100.053
년배출량0.1800.2041.0001.0001.0000.1600.048
위탁처리업체명0.2420.0000.0910.1100.1601.0001.000
처리방법0.1260.3720.0330.0530.0481.0001.000
2024-01-10T06:20:29.688284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역시-군-읍위탁처리업체명사업장구분처리방법
지역1.0001.0001.0001.0001.000
시-군-읍1.0001.0001.0001.0001.000
위탁처리업체명1.0001.0001.0000.0000.975
사업장구분1.0001.0000.0001.0000.277
처리방법1.0001.0000.9750.2771.000
2024-01-10T06:20:29.770919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번일배출량월배출량년배출량지역시-군-읍사업장구분위탁처리업체명처리방법
연번1.000-0.103-0.103-0.0971.0001.0000.1970.0910.095
일배출량-0.1031.0001.0001.0001.0001.0000.1080.0380.034
월배출량-0.1031.0001.0001.0001.0001.0000.1110.0460.056
년배출량-0.0971.0001.0001.0001.0001.0000.1100.0470.054
지역1.0001.0001.0001.0001.0001.0001.0001.0001.000
시-군-읍1.0001.0001.0001.0001.0001.0001.0001.0001.000
사업장구분0.1970.1080.1110.1101.0001.0001.0000.0000.277
위탁처리업체명0.0910.0380.0460.0471.0001.0000.0001.0000.975
처리방법0.0950.0340.0560.0541.0001.0000.2770.9751.000

Missing values

2024-01-10T06:20:25.593796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:20:25.717474image/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.
2024-01-10T06:20:25.863337image/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

연번지역시-군-읍사업장구분상호사업장 전화번호사업장 지번주소일배출량월배출량년배출량위탁처리업체명처리방법
01충청남도당진시집단급식소당진초등학교041-357-3750당진시 읍내동 교동길 10642125515058재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
12충청남도당진시집단급식소빌텍041-351-8227당진시 송악읍 북부산업로 1228201603872450재활용 처리-두비원 수집운반-리코퇴비화
23충청남도당진시집단급식소송산초등학교041-352-9681당진시 송산면 상거리 32382272720재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
34충청남도당진시집단급식소석문초등학교041-353-9344당진시 석문면 통정리 596-1113173800재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
45충청남도당진시집단급식소계성초등학교041-352-4032당진시 읍내리 1338114313710재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
56충청남도당진시집단급식소상록초등학교041-356-2320당진시 송악면 부곡리 187-8237038430재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
67충청남도당진시집단급식소고대초등학교041-353-8041당진시 고대면 진관리 산 17113323980재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
78충청남도당진시집단급식소면천초등학교041-356-3090당진시 면천면 성상리 772-1123634360재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
89충청남도당진시집단급식소송악초등학교041-358-9445당진시 송악면 중흥리 257154615530재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
910충청남도당진시집단급식소순성초등학교041-353-4140당진시 순성면 봉소리 59216307560재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
연번지역시-군-읍사업장구분상호사업장 전화번호사업장 지번주소일배출량월배출량년배출량위탁처리업체명처리방법
335336충청남도당진시집단급식소당진꿈나래학교041-359-1004당진시 합덕읍 면천로 1590132603120재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
336337충청남도당진시대규모점포대륙마트041-363-3123당진시 우강면 면천로 168551501800인영호사료화
337338충청남도당진시일반음식점가야정기지시점<NA>당진시 송악읍 틀모시로 7133399011880재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
338339충청남도당진시일반음식점로로<NA>당진시 대덕로 237175106120재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
339340충청남도당진시집단급식소삼원푸드<NA>당진시 송악읍 송악로 612216307560재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
340341충청남도당진시집단급식소당진1공장<NA>당진시 합덕읍 면천로 1361-15278209840재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
341342충청남도당진시일반음식점여수동 생고기<NA>당진시 석문면 대호로 1585-12885010200재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
342344충청남도당진시일반음식점백장골<NA>당진시 대덕1로 102-8450150018000재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
343345충청남도당진시농수산물도매시장농업회사법인 두리반팩토리041-356-4700당진시 순성면 남원로 250100300036000재활용 처리-대생리클린 수집운반-대생이엔티퇴비화
344347충청남도당진시집단급식소씨제이프레시웨이 다스코㈜ 당진 1공장<NA>당진시 합덕읍 면천로 1361-15278209840재활용 처리-대생리클린 수집운반-대생이엔티퇴비화