Overview

Dataset statistics

Number of variables10
Number of observations263
Missing cells12
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.2 KiB
Average record size in memory82.5 B

Variable types

Categorical1
Text6
Numeric2
DateTime1

Dataset

Description경기도 여주시의 사업장 폐기물 배출신고 현황 데이터입니다. 상호명, 소재지도로명주소, 소재지지번주소, 위도, 경도, 인허가관리번호, 인허가등록일자, 배출폐기물코드, 배출폐기물종류 등의 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15100729/fileData.do

Alerts

시군명 has constant value ""Constant
배출폐기물코드 has 10 (3.8%) missing valuesMissing
인허가관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:22:57.306847
Analysis finished2023-12-12 15:22:58.435031
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
여주시
263 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여주시 263
100.0%

Length

2023-12-13T00:22:58.492369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:22:58.580673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여주시 263
100.0%

상호명
Text

Distinct254
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T00:22:59.021966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length20
Mean length9.0722433
Min length2

Characters and Unicode

Total characters2386
Distinct characters288
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique247 ?
Unique (%)93.9%

Sample

1st row(주)벽산여주공장
2nd row강남건영(주) 제1공장
3rd row남광토건(주)
4th row(주)금강
5th row유정산업(주)
ValueCountFrequency (%)
주식회사 13
 
4.3%
천지산업(주 4
 
1.3%
주)수리산업 3
 
1.0%
농업회사법인 3
 
1.0%
여주공장 2
 
0.7%
주)남문기공 2
 
0.7%
여주지점 2
 
0.7%
여주점 2
 
0.7%
주)농우바이오 2
 
0.7%
주)영천씰테크 2
 
0.7%
Other values (264) 268
88.4%
2023-12-13T00:22:59.320698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 229
 
9.6%
( 189
 
7.9%
) 188
 
7.9%
업 54
 
2.3%
이 54
 
2.3%
사 47
 
2.0%
산 45
 
1.9%
리 42
 
1.8%
40
 
1.7%
여 39
 
1.6%
Other values (278) 1459
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1935
81.1%
Open Punctuation 189
 
7.9%
Close Punctuation 188
 
7.9%
Space Separator 40
 
1.7%
Other Symbol 20
 
0.8%
Uppercase Letter 8
 
0.3%
Decimal Number 5
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 229
 
11.8%
업 54
 
2.8%
이 54
 
2.8%
사 47
 
2.4%
산 45
 
2.3%
리 42
 
2.2%
여 39
 
2.0%
스 36
 
1.9%
지 32
 
1.7%
회 29
 
1.5%
Other values (265) 1328
68.6%
Decimal Number
ValueCountFrequency (%)
0 1
20.0%
6 1
20.0%
3 1
20.0%
1 1
20.0%
2 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
C 6
75.0%
T 1
 
12.5%
K 1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
( 189
100.0%
Close Punctuation
ValueCountFrequency (%)
) 188
100.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 20
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1955
81.9%
Common 423
 
17.7%
Latin 8
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 229
 
11.7%
업 54
 
2.8%
이 54
 
2.8%
사 47
 
2.4%
산 45
 
2.3%
리 42
 
2.1%
여 39
 
2.0%
스 36
 
1.8%
지 32
 
1.6%
회 29
 
1.5%
Other values (266) 1348
69.0%
Common
ValueCountFrequency (%)
( 189
44.7%
) 188
44.4%
40
 
9.5%
. 1
 
0.2%
0 1
 
0.2%
6 1
 
0.2%
3 1
 
0.2%
1 1
 
0.2%
2 1
 
0.2%
Latin
ValueCountFrequency (%)
C 6
75.0%
T 1
 
12.5%
K 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1935
81.1%
ASCII 431
 
18.1%
None 20
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 229
 
11.8%
업 54
 
2.8%
이 54
 
2.8%
사 47
 
2.4%
산 45
 
2.3%
리 42
 
2.2%
여 39
 
2.0%
스 36
 
1.9%
지 32
 
1.7%
회 29
 
1.5%
Other values (265) 1328
68.6%
ASCII
ValueCountFrequency (%)
( 189
43.9%
) 188
43.6%
40
 
9.3%
C 6
 
1.4%
. 1
 
0.2%
T 1
 
0.2%
0 1
 
0.2%
6 1
 
0.2%
3 1
 
0.2%
K 1
 
0.2%
Other values (2) 2
 
0.5%
None
ValueCountFrequency (%)
㈜ 20
100.0%

소재지도로명주소
Text

Distinct231
Distinct (%)88.5%
Missing2
Missing (%)0.8%
Memory size2.2 KiB
2023-12-13T00:22:59.676005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length24
Mean length19.494253
Min length13

Characters and Unicode

Total characters5088
Distinct characters148
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

Unique206 ?
Unique (%)78.9%

Sample

1st row경기도 여주시 가남읍 경충대로 1418
2nd row경기도 여주시 도예로 268
3rd row경기도 여주시 가남읍 경충대로 1054
4th row경기도 여주시 가남읍 여주남로 541
5th row경기도 여주시 금사면 이여로 1195
ValueCountFrequency (%)
경기도 261
20.9%
여주시 261
20.9%
가남읍 87
 
7.0%
점동면 22
 
1.8%
여주남로 20
 
1.6%
세종대왕면 17
 
1.4%
흥천면 17
 
1.4%
강천면 15
 
1.2%
북내면 15
 
1.2%
대신면 14
 
1.1%
Other values (311) 520
41.6%
2023-12-13T00:23:00.196705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
988
19.4%
여 317
 
6.2%
주 290
 
5.7%
경 276
 
5.4%
도 266
 
5.2%
기 264
 
5.2%
시 261
 
5.1%
로 200
 
3.9%
1 198
 
3.9%
남 117
 
2.3%
Other values (138) 1911
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3106
61.0%
Space Separator 988
 
19.4%
Decimal Number 905
 
17.8%
Dash Punctuation 81
 
1.6%
Open Punctuation 3
 
0.1%
Close Punctuation 3
 
0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
여 317
 
10.2%
주 290
 
9.3%
경 276
 
8.9%
도 266
 
8.6%
기 264
 
8.5%
시 261
 
8.4%
로 200
 
6.4%
남 117
 
3.8%
면 112
 
3.6%
가 102
 
3.3%
Other values (123) 901
29.0%
Decimal Number
ValueCountFrequency (%)
1 198
21.9%
4 94
10.4%
6 87
9.6%
5 85
9.4%
3 82
9.1%
2 82
9.1%
8 79
 
8.7%
7 74
 
8.2%
0 63
 
7.0%
9 61
 
6.7%
Space Separator
ValueCountFrequency (%)
988
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3106
61.0%
Common 1982
39.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
여 317
 
10.2%
주 290
 
9.3%
경 276
 
8.9%
도 266
 
8.6%
기 264
 
8.5%
시 261
 
8.4%
로 200
 
6.4%
남 117
 
3.8%
면 112
 
3.6%
가 102
 
3.3%
Other values (123) 901
29.0%
Common
ValueCountFrequency (%)
988
49.8%
1 198
 
10.0%
4 94
 
4.7%
6 87
 
4.4%
5 85
 
4.3%
3 82
 
4.1%
2 82
 
4.1%
- 81
 
4.1%
8 79
 
4.0%
7 74
 
3.7%
Other values (5) 132
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3106
61.0%
ASCII 1982
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
988
49.8%
1 198
 
10.0%
4 94
 
4.7%
6 87
 
4.4%
5 85
 
4.3%
3 82
 
4.1%
2 82
 
4.1%
- 81
 
4.1%
8 79
 
4.0%
7 74
 
3.7%
Other values (5) 132
 
6.7%
Hangul
ValueCountFrequency (%)
여 317
 
10.2%
주 290
 
9.3%
경 276
 
8.9%
도 266
 
8.6%
기 264
 
8.5%
시 261
 
8.4%
로 200
 
6.4%
남 117
 
3.8%
면 112
 
3.6%
가 102
 
3.3%
Other values (123) 901
29.0%

소재지지번주소
Text

Distinct234
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T00:23:00.447704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length21.387833
Min length15

Characters and Unicode

Total characters5625
Distinct characters124
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

Unique210 ?
Unique (%)79.8%

Sample

1st row경기도 여주시 가남읍 태평리 260번지
2nd row경기도 여주시 오학동 1-1번지
3rd row경기도 여주시 가남읍 심석리 67-1번지
4th row경기도 여주시 가남읍 본두리 1-2번지
5th row경기도 여주시 금사면 궁리 135번지
ValueCountFrequency (%)
경기도 263
21.0%
여주시 263
21.0%
가남읍 87
 
6.9%
점동면 22
 
1.8%
세종대왕면 17
 
1.4%
흥천면 17
 
1.4%
강천면 15
 
1.2%
북내면 15
 
1.2%
대신면 14
 
1.1%
본두리 13
 
1.0%
Other values (316) 526
42.0%
2023-12-13T00:23:00.814472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
999
17.8%
주 268
 
4.8%
도 267
 
4.7%
여 264
 
4.7%
경 263
 
4.7%
시 263
 
4.7%
기 263
 
4.7%
지 258
 
4.6%
번 255
 
4.5%
리 200
 
3.6%
Other values (114) 2325
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3506
62.3%
Space Separator 999
 
17.8%
Decimal Number 929
 
16.5%
Dash Punctuation 191
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 268
 
7.6%
도 267
 
7.6%
여 264
 
7.5%
경 263
 
7.5%
시 263
 
7.5%
기 263
 
7.5%
지 258
 
7.4%
번 255
 
7.3%
리 200
 
5.7%
면 112
 
3.2%
Other values (102) 1093
31.2%
Decimal Number
ValueCountFrequency (%)
1 182
19.6%
2 122
13.1%
4 105
11.3%
3 104
11.2%
6 91
9.8%
5 91
9.8%
7 72
 
7.8%
8 68
 
7.3%
0 49
 
5.3%
9 45
 
4.8%
Space Separator
ValueCountFrequency (%)
999
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 191
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3506
62.3%
Common 2119
37.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 268
 
7.6%
도 267
 
7.6%
여 264
 
7.5%
경 263
 
7.5%
시 263
 
7.5%
기 263
 
7.5%
지 258
 
7.4%
번 255
 
7.3%
리 200
 
5.7%
면 112
 
3.2%
Other values (102) 1093
31.2%
Common
ValueCountFrequency (%)
999
47.1%
- 191
 
9.0%
1 182
 
8.6%
2 122
 
5.8%
4 105
 
5.0%
3 104
 
4.9%
6 91
 
4.3%
5 91
 
4.3%
7 72
 
3.4%
8 68
 
3.2%
Other values (2) 94
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3506
62.3%
ASCII 2119
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
999
47.1%
- 191
 
9.0%
1 182
 
8.6%
2 122
 
5.8%
4 105
 
5.0%
3 104
 
4.9%
6 91
 
4.3%
5 91
 
4.3%
7 72
 
3.4%
8 68
 
3.2%
Other values (2) 94
 
4.4%
Hangul
ValueCountFrequency (%)
주 268
 
7.6%
도 267
 
7.6%
여 264
 
7.5%
경 263
 
7.5%
시 263
 
7.5%
기 263
 
7.5%
지 258
 
7.4%
번 255
 
7.3%
리 200
 
5.7%
면 112
 
3.2%
Other values (102) 1093
31.2%

위도
Real number (ℝ)

Distinct237
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.268109
Minimum37.153906
Maximum37.413138
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-13T00:23:00.969512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.153906
5-th percentile37.182257
Q137.220503
median37.252821
Q337.317443
95-th percentile37.385144
Maximum37.413138
Range0.25923153
Interquartile range (IQR)0.096939885

Descriptive statistics

Standard deviation0.064990542
Coefficient of variation (CV)0.0017438647
Kurtosis-0.80033805
Mean37.268109
Median Absolute Deviation (MAD)0.04688116
Skewness0.48409087
Sum9801.5128
Variance0.0042237705
MonotonicityNot monotonic
2023-12-13T00:23:01.138779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.18624155 4
 
1.5%
37.36556019 3
 
1.1%
37.24300223 3
 
1.1%
37.22217027 3
 
1.1%
37.20000452 2
 
0.8%
37.25992085 2
 
0.8%
37.23765791 2
 
0.8%
37.17259096 2
 
0.8%
37.34320572 2
 
0.8%
37.25282114 2
 
0.8%
Other values (227) 238
90.5%
ValueCountFrequency (%)
37.15390598 1
0.4%
37.16840913 1
0.4%
37.17176432 1
0.4%
37.17186857 1
0.4%
37.17259096 2
0.8%
37.17542324 1
0.4%
37.17570387 1
0.4%
37.17591825 1
0.4%
37.17665813 1
0.4%
37.18092615 2
0.8%
ValueCountFrequency (%)
37.41313751 1
0.4%
37.4113735 1
0.4%
37.40654576 1
0.4%
37.40629098 1
0.4%
37.40603911 1
0.4%
37.40574998 1
0.4%
37.40559706 1
0.4%
37.39888802 1
0.4%
37.3945957 1
0.4%
37.39248104 1
0.4%

경도
Real number (ℝ)

Distinct237
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.60591
Minimum127.4314
Maximum127.74341
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-13T00:23:01.304573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.4314
5-th percentile127.51541
Q1127.56143
median127.60263
Q3127.65601
95-th percentile127.70817
Maximum127.74341
Range0.3120154
Interquartile range (IQR)0.0945795

Descriptive statistics

Standard deviation0.063557305
Coefficient of variation (CV)0.00049807493
Kurtosis0.04511317
Mean127.60591
Median Absolute Deviation (MAD)0.0464902
Skewness-0.2704589
Sum33560.355
Variance0.004039531
MonotonicityNot monotonic
2023-12-13T00:23:01.451936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.5643656 4
 
1.5%
127.6573491 3
 
1.1%
127.5931537 3
 
1.1%
127.5671578 3
 
1.1%
127.5937882 2
 
0.8%
127.639728 2
 
0.8%
127.5450516 2
 
0.8%
127.5699412 2
 
0.8%
127.6355468 2
 
0.8%
127.6009578 2
 
0.8%
Other values (227) 238
90.5%
ValueCountFrequency (%)
127.4313969 1
0.4%
127.4357522 1
0.4%
127.4360681 1
0.4%
127.4363399 1
0.4%
127.4370401 1
0.4%
127.4406555 1
0.4%
127.445227 1
0.4%
127.4453647 1
0.4%
127.4468531 1
0.4%
127.4921084 1
0.4%
ValueCountFrequency (%)
127.7434123 1
0.4%
127.7393867 1
0.4%
127.739319 1
0.4%
127.7339648 1
0.4%
127.726593 1
0.4%
127.7248665 1
0.4%
127.7194552 1
0.4%
127.7180235 1
0.4%
127.7168979 1
0.4%
127.7168442 1
0.4%

인허가관리번호
Text

UNIQUE 

Distinct263
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T00:23:01.659118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters5523
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

Unique263 ?
Unique (%)100.0%

Sample

1st row5700000-31-1995-00001
2nd row5700000-31-1995-00002
3rd row5700000-31-1997-00001
4th row5700000-31-1998-00001
5th row5700000-31-1999-00014
ValueCountFrequency (%)
5700000-31-1995-00001 1
 
0.4%
5700000-31-2018-00016 1
 
0.4%
5700000-31-2016-00004 1
 
0.4%
5700000-31-2016-00006 1
 
0.4%
5700000-31-2016-00007 1
 
0.4%
5700000-31-2016-00008 1
 
0.4%
5700000-31-2016-00009 1
 
0.4%
5700000-31-2016-00010 1
 
0.4%
5700000-31-2016-00011 1
 
0.4%
5700000-31-2016-00012 1
 
0.4%
Other values (253) 253
96.2%
2023-12-13T00:23:02.010268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2593
46.9%
- 789
 
14.3%
1 541
 
9.8%
2 393
 
7.1%
3 330
 
6.0%
7 313
 
5.7%
5 311
 
5.6%
9 81
 
1.5%
4 60
 
1.1%
6 59
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4734
85.7%
Dash Punctuation 789
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2593
54.8%
1 541
 
11.4%
2 393
 
8.3%
3 330
 
7.0%
7 313
 
6.6%
5 311
 
6.6%
9 81
 
1.7%
4 60
 
1.3%
6 59
 
1.2%
8 53
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 789
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5523
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2593
46.9%
- 789
 
14.3%
1 541
 
9.8%
2 393
 
7.1%
3 330
 
6.0%
7 313
 
5.7%
5 311
 
5.6%
9 81
 
1.5%
4 60
 
1.1%
6 59
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5523
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2593
46.9%
- 789
 
14.3%
1 541
 
9.8%
2 393
 
7.1%
3 330
 
6.0%
7 313
 
5.7%
5 311
 
5.6%
9 81
 
1.5%
4 60
 
1.1%
6 59
 
1.1%

인허가등록일자
Date

Distinct248
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum1998-03-23 00:00:00
Maximum2023-06-20 00:00:00
2023-12-13T00:23:02.233411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:23:02.536574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

배출폐기물코드
Text

MISSING 

Distinct132
Distinct (%)52.2%
Missing10
Missing (%)3.8%
Memory size2.2 KiB
2023-12-13T00:23:02.842618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length125
Median length116
Mean length18.407115
Min length5

Characters and Unicode

Total characters4657
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 (%)43.5%

Sample

1st row51-30-04+51-03-01+91-07-02+03-04-01+51-07-01+51-30-01
2nd row51-03-01+51-22-01+51-02-99+51-05-99
3rd row03-02-00
4th row03-02-00
5th row51-05-02+51-22-01+51-03-01
ValueCountFrequency (%)
1951-03-01 45
 
17.8%
51-22-01 30
 
11.9%
51-99-00 7
 
2.8%
51-17-29 7
 
2.8%
51-14-02 6
 
2.4%
51-14-02+51-02-99 4
 
1.6%
51-05-99 4
 
1.6%
51-38-01 4
 
1.6%
03-02-00 4
 
1.6%
51-02-99+51-22-01 3
 
1.2%
Other values (122) 139
54.9%
2023-12-13T00:23:03.272724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1064
22.8%
1 982
21.1%
0 837
18.0%
5 508
10.9%
2 307
 
6.6%
+ 282
 
6.1%
9 274
 
5.9%
3 215
 
4.6%
7 71
 
1.5%
4 56
 
1.2%
Other values (2) 61
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3311
71.1%
Dash Punctuation 1064
 
22.8%
Math Symbol 282
 
6.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 982
29.7%
0 837
25.3%
5 508
15.3%
2 307
 
9.3%
9 274
 
8.3%
3 215
 
6.5%
7 71
 
2.1%
4 56
 
1.7%
8 40
 
1.2%
6 21
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
- 1064
100.0%
Math Symbol
ValueCountFrequency (%)
+ 282
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4657
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1064
22.8%
1 982
21.1%
0 837
18.0%
5 508
10.9%
2 307
 
6.6%
+ 282
 
6.1%
9 274
 
5.9%
3 215
 
4.6%
7 71
 
1.5%
4 56
 
1.2%
Other values (2) 61
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4657
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1064
22.8%
1 982
21.1%
0 837
18.0%
5 508
10.9%
2 307
 
6.6%
+ 282
 
6.1%
9 274
 
5.9%
3 215
 
4.6%
7 71
 
1.5%
4 56
 
1.2%
Other values (2) 61
 
1.3%

배출폐기물종류
Text

Distinct155
Distinct (%)58.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T00:23:03.646401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length202
Median length106
Mean length29.250951
Min length3

Characters and Unicode

Total characters7693
Distinct characters204
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique129 ?
Unique (%)49.0%

Sample

1st row폐유리섬유+폐합성수지류(폐염화비닐수지류는 제외한다)+폐유리+폐내화물
2nd row폐합성수지류(폐염화비닐수지류는 제외한다)+폐콘크리트+그 밖의 무기성오니+그 밖의 분진
3rd row폐흡착제 및 폐흡수제+사업장외생활폐기물+분진+광재
4th row소각잔재물+폐합성수지류+분진+사업장외생활폐기물+기타+공정오니+음식물쓰레기
5th row시멘트제조공정분진+폐콘크리트+폐합성수지류(폐염화비닐수지류는 제외한다)
ValueCountFrequency (%)
밖의 125
 
12.2%
폐합성수지류(폐염화비닐수지류는 66
 
6.5%
제외한다 58
 
5.7%
그 51
 
5.0%
폐콘크리트 27
 
2.6%
제외한다)+그 21
 
2.1%
과정에서 20
 
2.0%
발생한 16
 
1.6%
폐기물 15
 
1.5%
및 12
 
1.2%
Other values (287) 611
59.8%
2023-12-13T00:23:04.303641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
759
 
9.9%
폐 598
 
7.8%
류 335
 
4.4%
수 313
 
4.1%
+ 302
 
3.9%
지 281
 
3.7%
성 209
 
2.7%
한 193
 
2.5%
물 183
 
2.4%
합 164
 
2.1%
Other values (194) 4356
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6247
81.2%
Space Separator 759
 
9.9%
Math Symbol 302
 
3.9%
Open Punctuation 162
 
2.1%
Close Punctuation 162
 
2.1%
Other Punctuation 48
 
0.6%
Decimal Number 13
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 598
 
9.6%
류 335
 
5.4%
수 313
 
5.0%
지 281
 
4.5%
성 209
 
3.3%
한 193
 
3.1%
물 183
 
2.9%
합 164
 
2.6%
다 157
 
2.5%
제 151
 
2.4%
Other values (180) 3663
58.6%
Decimal Number
ValueCountFrequency (%)
1 7
53.8%
8 3
23.1%
3 1
 
7.7%
7 1
 
7.7%
2 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 45
93.8%
· 2
 
4.2%
. 1
 
2.1%
Open Punctuation
ValueCountFrequency (%)
( 159
98.1%
「 3
 
1.9%
Close Punctuation
ValueCountFrequency (%)
) 159
98.1%
」 3
 
1.9%
Space Separator
ValueCountFrequency (%)
759
100.0%
Math Symbol
ValueCountFrequency (%)
+ 302
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6247
81.2%
Common 1446
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 598
 
9.6%
류 335
 
5.4%
수 313
 
5.0%
지 281
 
4.5%
성 209
 
3.3%
한 193
 
3.1%
물 183
 
2.9%
합 164
 
2.6%
다 157
 
2.5%
제 151
 
2.4%
Other values (180) 3663
58.6%
Common
ValueCountFrequency (%)
759
52.5%
+ 302
 
20.9%
( 159
 
11.0%
) 159
 
11.0%
, 45
 
3.1%
1 7
 
0.5%
「 3
 
0.2%
8 3
 
0.2%
」 3
 
0.2%
· 2
 
0.1%
Other values (4) 4
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6220
80.9%
ASCII 1438
 
18.7%
Compat Jamo 27
 
0.4%
None 8
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
759
52.8%
+ 302
 
21.0%
( 159
 
11.1%
) 159
 
11.1%
, 45
 
3.1%
1 7
 
0.5%
8 3
 
0.2%
3 1
 
0.1%
. 1
 
0.1%
7 1
 
0.1%
Hangul
ValueCountFrequency (%)
폐 598
 
9.6%
류 335
 
5.4%
수 313
 
5.0%
지 281
 
4.5%
성 209
 
3.4%
한 193
 
3.1%
물 183
 
2.9%
합 164
 
2.6%
다 157
 
2.5%
제 151
 
2.4%
Other values (179) 3636
58.5%
Compat Jamo
ValueCountFrequency (%)
ㆍ 27
100.0%
None
ValueCountFrequency (%)
「 3
37.5%
」 3
37.5%
· 2
25.0%

Interactions

2023-12-13T00:22:57.978717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:57.818565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:58.062486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:22:57.900238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:23:04.439736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.741
경도0.7411.000
2023-12-13T00:23:04.559074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.021
경도0.0211.000

Missing values

2023-12-13T00:22:58.174606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:22:58.294845image/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.
2023-12-13T00:22:58.390017image/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

시군명상호명소재지도로명주소소재지지번주소위도경도인허가관리번호인허가등록일자배출폐기물코드배출폐기물종류
0여주시(주)벽산여주공장경기도 여주시 가남읍 경충대로 1418경기도 여주시 가남읍 태평리 260번지37.216034127.5417255700000-31-1995-000012002-03-3051-30-04+51-03-01+91-07-02+03-04-01+51-07-01+51-30-01폐유리섬유+폐합성수지류(폐염화비닐수지류는 제외한다)+폐유리+폐내화물
1여주시강남건영(주) 제1공장경기도 여주시 도예로 268경기도 여주시 오학동 1-1번지37.317162127.6593475700000-31-1995-000022007-05-0751-03-01+51-22-01+51-02-99+51-05-99폐합성수지류(폐염화비닐수지류는 제외한다)+폐콘크리트+그 밖의 무기성오니+그 밖의 분진
2여주시남광토건(주)경기도 여주시 가남읍 경충대로 1054경기도 여주시 가남읍 심석리 67-1번지37.188884127.562615700000-31-1997-000012007-04-1703-02-00폐흡착제 및 폐흡수제+사업장외생활폐기물+분진+광재
3여주시(주)금강경기도 여주시 가남읍 여주남로 541경기도 여주시 가남읍 본두리 1-2번지37.243002127.5931545700000-31-1998-000011998-03-2303-02-00소각잔재물+폐합성수지류+분진+사업장외생활폐기물+기타+공정오니+음식물쓰레기
4여주시유정산업(주)경기도 여주시 금사면 이여로 1195경기도 여주시 금사면 궁리 135번지37.385456127.5257225700000-31-1999-000141999-03-0451-05-02+51-22-01+51-03-01시멘트제조공정분진+폐콘크리트+폐합성수지류(폐염화비닐수지류는 제외한다)
5여주시(주)수리산업경기도 여주시 가남읍 여주남로 554경기도 여주시 가남읍 본두리 12-1번지37.246619127.5908695700000-31-1999-000152007-03-0951-14-02+51-02-99폐석재+그 밖의 무기성오니
6여주시중앙산업(주)경기도 여주시 여양로 461경기도 여주시 현암동 22-1번지37.320573127.6498635700000-31-1999-000162002-03-1951-38-01+51-05-99+51-03-01+51-22-01음식물류폐기물+그 밖의 분진+폐합성수지류(폐염화비닐수지류는 제외한다)+폐콘크리트
7여주시극동도기(주)경기도 여주시 학동1길 16경기도 여주시 오학동 366-1번지37.304085127.6436585700000-31-1999-000202003-03-1951-07-01+03-04-01+51-02-01+01-02-01+51-99-00폐내화물+폐수처리오니+그 밖의 폐기물
8여주시삼광산업(주)경기도 여주시 강천면 강천로 32경기도 여주시 강천면 간매리 502-9번지37.262294127.7158585700000-31-1999-000221999-06-2251-22-01폐콘크리트
9여주시일신산업(주)테라조공장경기도 여주시 대신면 상구5길 58경기도 여주시 대신면 상구리 148-3번지37.3873127.6372425700000-31-1999-000251999-07-0251-22-01폐콘크리트
시군명상호명소재지도로명주소소재지지번주소위도경도인허가관리번호인허가등록일자배출폐기물코드배출폐기물종류
253여주시(주)코어피씨경기도 여주시 북내면 외재로 170_ 에이동 1층경기도 여주시 북내면 외룡리 383-1037.358739127.656215700000-31-2022-000082022-08-1651-22-01폐콘크리트
254여주시(주)덕성정공경기도 여주시 세종대왕면 북성산로 104경기도 여주시 세종대왕면 신지리 72-637.293684127.5895665700000-31-2022-000092022-11-041951-11-03폐활성탄
255여주시다임러트럭코리아(주)경기도 여주시 세종대왕면 북성산로 104경기도 여주시 세종대왕면 신지리 72-637.293684127.5895665700000-31-2022-000102022-12-061951-03-01폐합성수지류(폐염화비닐수지류는 제외한다)
256여주시일신산업(주)경기도 여주시 신단1길 33-27 (연양동)경기도 여주시 연양동 159-137.279371127.6715685700000-31-2023-000012023-03-131951-01-06그 밖의 공정오니
257여주시태강건설(주)경기도 여주시 세종대왕면 월평로 480경기도 여주시 세종대왕면 광대리 266-237.260698127.5706195700000-31-2023-000022023-03-3051-05-99그 밖의 분진
258여주시(주)케이티 동부물류센터경기도 여주시 장여로 1610 (삼교동)경기도 여주시 삼교동 45937.241651127.6544685700000-31-2023-000032023-04-1451-18-02산업용폐전기전자제품
259여주시(주)성우패널시스템경기도 여주시 세종대왕면 중부대로 2678경기도 여주시 세종대왕면 번도리 887-5237.297219127.6011715700000-31-2023-000042023-04-1951-30-04폐유리섬유
260여주시하이네켄코리아(주)경기도 여주시 대신면 대신로 894-10경기도 여주시 대신면 장풍리 46237.377821127.607565700000-31-2023-000052023-05-1151-38-01음식물류폐기물
261여주시(주)다성레미콘 여주지점경기도 여주시 흥천면 흥천로 308-85경기도 여주시 흥천면 효지리 45337.33165127.5581985700000-31-2023-000062023-06-071951-02-06석재ㆍ골재폐수처리오니(석재ㆍ골재 생산 시 발생한 폐수를 처리하는 과정에서 발생한 오니로 한정한다)
262여주시(주)골든블루인터내셔널경기도 여주시 대신면 대신로 894-10경기도 여주시 대신면 장풍리 46237.377821127.607565700000-31-2023-000072023-06-2051-38-01음식물류폐기물