Overview

Dataset statistics

Number of variables9
Number of observations813
Missing cells0
Missing cells (%)0.0%
Duplicate rows11
Duplicate rows (%)1.4%
Total size in memory58.1 KiB
Average record size in memory73.2 B

Variable types

DateTime1
Text4
Numeric1
Categorical3

Dataset

Description경상남도 밀양시 대형폐기물 수거 현황입니다
Author경상남도 밀양시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15093344

Alerts

관리기관 has constant value ""Constant
전화번호 has constant value ""Constant
Dataset has 11 (1.4%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-11 01:04:17.365154
Analysis finished2023-12-11 01:04:18.301207
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수거일자
Date

Distinct128
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
Minimum2021-05-04 00:00:00
Maximum2021-10-20 00:00:00
2023-12-11T10:04:18.363148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T10:04:18.492656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

폐기물 구분
Text

Distinct73
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-12-11T10:04:18.846754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.5448954
Min length2

Characters and Unicode

Total characters2882
Distinct characters125
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)2.1%

Sample

1st row식탁유리
2nd row보통의자
3rd row장판
4th row침대
5th row거울 액자
ValueCountFrequency (%)
침대 86
 
8.8%
서랍장 73
 
7.4%
소파 71
 
7.2%
보통의자 68
 
6.9%
책장 45
 
4.6%
책꽂이 45
 
4.6%
책상 32
 
3.3%
장롱 25
 
2.5%
유모차 25
 
2.5%
밥상 24
 
2.4%
Other values (74) 487
49.6%
2023-12-11T10:04:19.264106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 235
 
8.2%
168
 
5.8%
책 122
 
4.2%
대 120
 
4.2%
자 114
 
4.0%
침 86
 
3.0%
기 85
 
2.9%
소 85
 
2.9%
보 81
 
2.8%
통 76
 
2.6%
Other values (115) 1710
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2599
90.2%
Space Separator 168
 
5.8%
Open Punctuation 57
 
2.0%
Close Punctuation 57
 
2.0%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 235
 
9.0%
책 122
 
4.7%
대 120
 
4.6%
자 114
 
4.4%
침 86
 
3.3%
기 85
 
3.3%
소 85
 
3.3%
보 81
 
3.1%
통 76
 
2.9%
서 74
 
2.8%
Other values (111) 1521
58.5%
Space Separator
ValueCountFrequency (%)
168
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2599
90.2%
Common 283
 
9.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 235
 
9.0%
책 122
 
4.7%
대 120
 
4.6%
자 114
 
4.4%
침 86
 
3.3%
기 85
 
3.3%
소 85
 
3.3%
보 81
 
3.1%
통 76
 
2.9%
서 74
 
2.8%
Other values (111) 1521
58.5%
Common
ValueCountFrequency (%)
168
59.4%
( 57
 
20.1%
) 57
 
20.1%
, 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2599
90.2%
ASCII 283
 
9.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 235
 
9.0%
책 122
 
4.7%
대 120
 
4.6%
자 114
 
4.4%
침 86
 
3.3%
기 85
 
3.3%
소 85
 
3.3%
보 81
 
3.1%
통 76
 
2.9%
서 74
 
2.8%
Other values (111) 1521
58.5%
ASCII
ValueCountFrequency (%)
168
59.4%
( 57
 
20.1%
) 57
 
20.1%
, 1
 
0.4%

폐기물 명
Text

Distinct73
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-12-11T10:04:19.503573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.5448954
Min length2

Characters and Unicode

Total characters2882
Distinct characters125
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)2.1%

Sample

1st row식탁유리
2nd row보통의자
3rd row장판
4th row침대
5th row거울 액자
ValueCountFrequency (%)
침대 86
 
8.8%
서랍장 73
 
7.4%
소파 71
 
7.2%
보통의자 68
 
6.9%
책장 45
 
4.6%
책꽂이 45
 
4.6%
책상 32
 
3.3%
장롱 25
 
2.5%
유모차 25
 
2.5%
밥상 24
 
2.4%
Other values (74) 487
49.6%
2023-12-11T10:04:19.914025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 235
 
8.2%
168
 
5.8%
책 122
 
4.2%
대 120
 
4.2%
자 114
 
4.0%
침 86
 
3.0%
기 85
 
2.9%
소 85
 
2.9%
보 81
 
2.8%
통 76
 
2.6%
Other values (115) 1710
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2599
90.2%
Space Separator 168
 
5.8%
Open Punctuation 57
 
2.0%
Close Punctuation 57
 
2.0%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 235
 
9.0%
책 122
 
4.7%
대 120
 
4.6%
자 114
 
4.4%
침 86
 
3.3%
기 85
 
3.3%
소 85
 
3.3%
보 81
 
3.1%
통 76
 
2.9%
서 74
 
2.8%
Other values (111) 1521
58.5%
Space Separator
ValueCountFrequency (%)
168
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2599
90.2%
Common 283
 
9.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 235
 
9.0%
책 122
 
4.7%
대 120
 
4.6%
자 114
 
4.4%
침 86
 
3.3%
기 85
 
3.3%
소 85
 
3.3%
보 81
 
3.1%
통 76
 
2.9%
서 74
 
2.8%
Other values (111) 1521
58.5%
Common
ValueCountFrequency (%)
168
59.4%
( 57
 
20.1%
) 57
 
20.1%
, 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2599
90.2%
ASCII 283
 
9.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 235
 
9.0%
책 122
 
4.7%
대 120
 
4.6%
자 114
 
4.4%
침 86
 
3.3%
기 85
 
3.3%
소 85
 
3.3%
보 81
 
3.1%
통 76
 
2.9%
서 74
 
2.8%
Other values (111) 1521
58.5%
ASCII
ValueCountFrequency (%)
168
59.4%
( 57
 
20.1%
) 57
 
20.1%
, 1
 
0.4%

폐기물 규격
Text

Distinct62
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-12-11T10:04:20.138441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length6.0270603
Min length2

Characters and Unicode

Total characters4900
Distinct characters87
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.7%

Sample

1st row모든규격
2nd row학생용 의자
3rd row평당
4th row2인용 매트리스
5th rowm2당
ValueCountFrequency (%)
모든규격 201
 
14.4%
미만 135
 
9.6%
의자 71
 
5.1%
이상 71
 
5.1%
2인용 64
 
4.6%
1인용 62
 
4.4%
학생용 58
 
4.1%
폭 56
 
4.0%
매트리스 51
 
3.6%
5단 45
 
3.2%
Other values (50) 585
41.8%
2023-12-11T10:04:20.556259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
586
 
12.0%
1 309
 
6.3%
용 270
 
5.5%
모 204
 
4.2%
든 201
 
4.1%
격 201
 
4.1%
규 201
 
4.1%
인 197
 
4.0%
이 160
 
3.3%
m 160
 
3.3%
Other values (77) 2411
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3171
64.7%
Decimal Number 748
 
15.3%
Space Separator 586
 
12.0%
Lowercase Letter 168
 
3.4%
Other Punctuation 134
 
2.7%
Other Symbol 40
 
0.8%
Math Symbol 25
 
0.5%
Open Punctuation 13
 
0.3%
Close Punctuation 13
 
0.3%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
용 270
 
8.5%
모 204
 
6.4%
든 201
 
6.3%
격 201
 
6.3%
규 201
 
6.3%
인 197
 
6.2%
이 160
 
5.0%
만 151
 
4.8%
미 151
 
4.8%
단 118
 
3.7%
Other values (56) 1317
41.5%
Decimal Number
ValueCountFrequency (%)
1 309
41.3%
2 116
 
15.5%
0 108
 
14.4%
5 66
 
8.8%
3 44
 
5.9%
4 42
 
5.6%
8 33
 
4.4%
9 20
 
2.7%
6 10
 
1.3%
Lowercase Letter
ValueCountFrequency (%)
m 160
95.2%
k 4
 
2.4%
g 4
 
2.4%
Other Punctuation
ValueCountFrequency (%)
. 109
81.3%
, 25
 
18.7%
Other Symbol
ValueCountFrequency (%)
㎝ 38
95.0%
㎏ 2
 
5.0%
Space Separator
ValueCountFrequency (%)
586
100.0%
Math Symbol
ValueCountFrequency (%)
× 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3171
64.7%
Common 1559
31.8%
Latin 170
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
용 270
 
8.5%
모 204
 
6.4%
든 201
 
6.3%
격 201
 
6.3%
규 201
 
6.3%
인 197
 
6.2%
이 160
 
5.0%
만 151
 
4.8%
미 151
 
4.8%
단 118
 
3.7%
Other values (56) 1317
41.5%
Common
ValueCountFrequency (%)
586
37.6%
1 309
19.8%
2 116
 
7.4%
. 109
 
7.0%
0 108
 
6.9%
5 66
 
4.2%
3 44
 
2.8%
4 42
 
2.7%
㎝ 38
 
2.4%
8 33
 
2.1%
Other values (7) 108
 
6.9%
Latin
ValueCountFrequency (%)
m 160
94.1%
k 4
 
2.4%
g 4
 
2.4%
L 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3171
64.7%
ASCII 1664
34.0%
CJK Compat 40
 
0.8%
None 25
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
586
35.2%
1 309
18.6%
m 160
 
9.6%
2 116
 
7.0%
. 109
 
6.6%
0 108
 
6.5%
5 66
 
4.0%
3 44
 
2.6%
4 42
 
2.5%
8 33
 
2.0%
Other values (8) 91
 
5.5%
Hangul
ValueCountFrequency (%)
용 270
 
8.5%
모 204
 
6.4%
든 201
 
6.3%
격 201
 
6.3%
규 201
 
6.3%
인 197
 
6.2%
이 160
 
5.0%
만 151
 
4.8%
미 151
 
4.8%
단 118
 
3.7%
Other values (56) 1317
41.5%
CJK Compat
ValueCountFrequency (%)
㎝ 38
95.0%
㎏ 2
 
5.0%
None
ValueCountFrequency (%)
× 25
100.0%

개수
Real number (ℝ)

Distinct9
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4206642
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-11T10:04:20.693454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile3
Maximum36
Range35
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.5663223
Coefficient of variation (CV)1.1025282
Kurtosis298.06979
Mean1.4206642
Median Absolute Deviation (MAD)0
Skewness14.499375
Sum1155
Variance2.4533656
MonotonicityNot monotonic
2023-12-11T10:04:20.797143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 638
78.5%
2 109
 
13.4%
3 32
 
3.9%
4 19
 
2.3%
5 7
 
0.9%
6 4
 
0.5%
12 2
 
0.2%
8 1
 
0.1%
36 1
 
0.1%
ValueCountFrequency (%)
1 638
78.5%
2 109
 
13.4%
3 32
 
3.9%
4 19
 
2.3%
5 7
 
0.9%
6 4
 
0.5%
8 1
 
0.1%
12 2
 
0.2%
36 1
 
0.1%
ValueCountFrequency (%)
36 1
 
0.1%
12 2
 
0.2%
8 1
 
0.1%
6 4
 
0.5%
5 7
 
0.9%
4 19
 
2.3%
3 32
 
3.9%
2 109
 
13.4%
1 638
78.5%

수거장소_도로명주소
Text

Distinct358
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-12-11T10:04:21.148084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length59
Mean length38.067651
Min length22

Characters and Unicode

Total characters30949
Distinct characters310
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique198 ?
Unique (%)24.4%

Sample

1st row경상남도 밀양시 시청서2길 20-1 601호 (내이동)
2nd row경상남도 밀양시 시청서2길 20-1 601호 (내이동)
3rd row경상남도 밀양시 역앞광장로 15 밀양강푸르지오 103동 2504호 (가곡동)
4th row경상남도 밀양시 시청로2길 6 103동206호 (내이동)
5th row경상남도 밀양시 상남면 평촌길 42-19 옥수가든주택 (상남면)
ValueCountFrequency (%)
경상남도 813
 
12.0%
밀양시 813
 
12.0%
삼문동 440
 
6.5%
244
 
3.6%
내이동 230
 
3.4%
지역 223
 
3.3%
관할 221
 
3.3%
그 208
 
3.1%
외 208
 
3.1%
상남면 114
 
1.7%
Other values (660) 3266
48.2%
2023-12-11T10:04:21.679914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5996
 
19.4%
동 1207
 
3.9%
1 1144
 
3.7%
( 1059
 
3.4%
) 1059
 
3.4%
남 1025
 
3.3%
상 958
 
3.1%
밀 877
 
2.8%
도 859
 
2.8%
시 856
 
2.8%
Other values (300) 15909
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16915
54.7%
Space Separator 5996
 
19.4%
Decimal Number 5265
 
17.0%
Open Punctuation 1059
 
3.4%
Close Punctuation 1059
 
3.4%
Dash Punctuation 340
 
1.1%
Other Punctuation 263
 
0.8%
Math Symbol 30
 
0.1%
Uppercase Letter 17
 
0.1%
Lowercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1207
 
7.1%
남 1025
 
6.1%
상 958
 
5.7%
밀 877
 
5.2%
도 859
 
5.1%
시 856
 
5.1%
양 843
 
5.0%
경 821
 
4.9%
삼 539
 
3.2%
로 525
 
3.1%
Other values (271) 8405
49.7%
Decimal Number
ValueCountFrequency (%)
1 1144
21.7%
0 813
15.4%
2 760
14.4%
3 726
13.8%
4 452
 
8.6%
5 388
 
7.4%
7 319
 
6.1%
6 313
 
5.9%
8 222
 
4.2%
9 128
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
A 5
29.4%
B 5
29.4%
S 2
 
11.8%
G 2
 
11.8%
U 1
 
5.9%
P 1
 
5.9%
C 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
: 221
84.0%
, 25
 
9.5%
. 16
 
6.1%
@ 1
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
e 3
60.0%
c 1
 
20.0%
b 1
 
20.0%
Space Separator
ValueCountFrequency (%)
5996
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1059
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1059
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 340
100.0%
Math Symbol
ValueCountFrequency (%)
~ 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16915
54.7%
Common 14012
45.3%
Latin 22
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1207
 
7.1%
남 1025
 
6.1%
상 958
 
5.7%
밀 877
 
5.2%
도 859
 
5.1%
시 856
 
5.1%
양 843
 
5.0%
경 821
 
4.9%
삼 539
 
3.2%
로 525
 
3.1%
Other values (271) 8405
49.7%
Common
ValueCountFrequency (%)
5996
42.8%
1 1144
 
8.2%
( 1059
 
7.6%
) 1059
 
7.6%
0 813
 
5.8%
2 760
 
5.4%
3 726
 
5.2%
4 452
 
3.2%
5 388
 
2.8%
- 340
 
2.4%
Other values (9) 1275
 
9.1%
Latin
ValueCountFrequency (%)
A 5
22.7%
B 5
22.7%
e 3
13.6%
S 2
 
9.1%
G 2
 
9.1%
c 1
 
4.5%
U 1
 
4.5%
b 1
 
4.5%
P 1
 
4.5%
C 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16873
54.5%
ASCII 14034
45.3%
Compat Jamo 42
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5996
42.7%
1 1144
 
8.2%
( 1059
 
7.5%
) 1059
 
7.5%
0 813
 
5.8%
2 760
 
5.4%
3 726
 
5.2%
4 452
 
3.2%
5 388
 
2.8%
- 340
 
2.4%
Other values (19) 1297
 
9.2%
Hangul
ValueCountFrequency (%)
동 1207
 
7.2%
남 1025
 
6.1%
상 958
 
5.7%
밀 877
 
5.2%
도 859
 
5.1%
시 856
 
5.1%
양 843
 
5.0%
경 821
 
4.9%
삼 539
 
3.2%
로 525
 
3.1%
Other values (267) 8363
49.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 17
40.5%
ㅇ 11
26.2%
ㄷ 11
26.2%
ㅡ 3
 
7.1%

행정동
Categorical

Distinct19
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
내이동
216 
삼문동 (삼문동 관할) : 그 외 지역
208 
상남면
59 
가곡동
50 
교동
41 
Other values (14)
239 

Length

Max length31
Median length3
Mean length8.3776138
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row내이동
2nd row내이동
3rd row가곡동
4th row내이동
5th row상남면

Common Values

ValueCountFrequency (%)
내이동 216
26.6%
삼문동 (삼문동 관할) : 그 외 지역 208
25.6%
상남면 59
 
7.3%
가곡동 50
 
6.2%
교동 41
 
5.0%
하남읍 38
 
4.7%
부북면 34
 
4.2%
삼랑진읍 28
 
3.4%
무안면 26
 
3.2%
단장면 25
 
3.1%
Other values (9) 88
10.8%

Length

2023-12-11T10:04:21.869447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
삼문동 438
20.4%
내이동 229
10.7%
지역 223
10.4%
관할 221
10.3%
221
10.3%
그 208
9.7%
외 208
9.7%
상남면 59
 
2.8%
가곡동 50
 
2.3%
교동 41
 
1.9%
Other values (13) 245
11.4%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
환경관리과
813 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
환경관리과 813
100.0%

Length

2023-12-11T10:04:22.014258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T10:04:22.103626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경관리과 813
100.0%

전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
055-359-5321
813 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row055-359-5321
2nd row055-359-5321
3rd row055-359-5321
4th row055-359-5321
5th row055-359-5321

Common Values

ValueCountFrequency (%)
055-359-5321 813
100.0%

Length

2023-12-11T10:04:22.208210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T10:04:22.313681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
055-359-5321 813
100.0%

Interactions

2023-12-11T10:04:17.982703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T10:04:22.418421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물 구분폐기물 명폐기물 규격개수행정동
폐기물 구분1.0001.0000.9950.0000.000
폐기물 명1.0001.0000.9950.0000.000
폐기물 규격0.9950.9951.0000.0000.000
개수0.0000.0000.0001.0000.348
행정동0.0000.0000.0000.3481.000
2023-12-11T10:04:22.516604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개수행정동
개수1.0000.124
행정동0.1241.000

Missing values

2023-12-11T10:04:18.116923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T10:04:18.247360image/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

수거일자폐기물 구분폐기물 명폐기물 규격개수수거장소_도로명주소행정동관리기관전화번호
02021-10-20식탁유리식탁유리모든규격1경상남도 밀양시 시청서2길 20-1 601호 (내이동)내이동환경관리과055-359-5321
12021-10-20보통의자보통의자학생용 의자1경상남도 밀양시 시청서2길 20-1 601호 (내이동)내이동환경관리과055-359-5321
22021-10-20장판장판평당2경상남도 밀양시 역앞광장로 15 밀양강푸르지오 103동 2504호 (가곡동)가곡동환경관리과055-359-5321
32021-10-19침대침대2인용 매트리스1경상남도 밀양시 시청로2길 6 103동206호 (내이동)내이동환경관리과055-359-5321
42021-10-19거울 액자거울 액자m2당2경상남도 밀양시 상남면 평촌길 42-19 옥수가든주택 (상남면)상남면환경관리과055-359-5321
52021-10-19빨래 건조대빨래 건조대모든규격2경상남도 밀양시 상남면 평촌길 42-19 옥수가든주택 (상남면)상남면환경관리과055-359-5321
62021-10-19가스 오븐렌지가스 오븐렌지높이 1m 미만2경상남도 밀양시 상남면 평촌길 42-19 옥수가든주택 (상남면)상남면환경관리과055-359-5321
72021-10-19여행용 가방여행용 가방모든규격1경상남도 밀양시 상남면 평촌길 42-19 옥수가든주택 (상남면)상남면환경관리과055-359-5321
82021-10-19침대침대1인용 매트리스1경상남도 밀양시 상남면 평촌길 42-19 옥수가든주택 (상남면)상남면환경관리과055-359-5321
92021-10-19서랍장서랍장1단기준2경상남도 밀양시 상남면 평촌길 42-19 옥수가든주택 (상남면)상남면환경관리과055-359-5321
수거일자폐기물 구분폐기물 명폐기물 규격개수수거장소_도로명주소행정동관리기관전화번호
8032021-05-10여행용 가방여행용 가방모든규격1경상남도 밀양시 미리벌로3길 11 203동 305호 (삼문동)삼문동환경관리과055-359-5321
8042021-05-10침대침대2인용 매트리스1경상남도 밀양시 시청로2길 6 101동1001호 (내이동)내이동환경관리과055-359-5321
8052021-05-10책상책상폭 1.5m 미만2경상남도 밀양시 점필재로 45-25 105-203 (삼문동)삼문동환경관리과055-359-5321
8062021-05-10문짝문짝0.9m×1.8m 미만1경상남도 밀양시 점필재로 45-25 105-203 (삼문동)삼문동환경관리과055-359-5321
8072021-05-10소파소파3인용1경상남도 밀양시 상남면 상남로 564 . (상남면)상남면환경관리과055-359-5321
8082021-05-07자전거자전거모든규격1경상남도 밀양시 미리벌중앙로3길 46 101동 1003호 (삼문동)삼문동환경관리과055-359-5321
8092021-05-07선풍기선풍기높이 1m이상1경상남도 밀양시 미리벌중앙로3길 46 101동 1003호 (삼문동)삼문동환경관리과055-359-5321
8102021-05-07유모차유모차모든규격1경상남도 밀양시 밀양향교2길 12 향교2길12 (교동)교동환경관리과055-359-5321
8112021-05-04여행용 가방여행용 가방모든규격1경상남도 밀양시 밀성로3길 16-14 프라하캐슬 (내이동)내이동환경관리과055-359-5321
8122021-05-04보통의자보통의자업소용 의자1경상남도 밀양시 백민로8길 21-5 장관청실303 (내이동)내이동환경관리과055-359-5321

Duplicate rows

Most frequently occurring

수거일자폐기물 구분폐기물 명폐기물 규격개수수거장소_도로명주소행정동관리기관전화번호# duplicates
52021-08-02책장 (책꽂이)책장 (책꽂이)5단 이상1경상남도 밀양시 중앙로 234-22 일성아파트 2동 208호 (삼문동 (삼문동 관할) : 그 외 지역)삼문동 (삼문동 관할) : 그 외 지역환경관리과055-359-53214
32021-08-02서랍장서랍장1단기준1경상남도 밀양시 중앙로 234-22 일성아파트 2동 208호 (삼문동 (삼문동 관할) : 그 외 지역)삼문동 (삼문동 관할) : 그 외 지역환경관리과055-359-53213
02021-06-30보통의자보통의자학생용 의자1경상남도 밀양시 시청로2길 13 피란체 B동 301호 (내이동)내이동환경관리과055-359-53212
12021-06-30신발장신발장폭0.6m,높이1.0m이상1경상남도 밀양시 교동로 93 1501호 (교동)교동환경관리과055-359-53212
22021-07-29침대침대1인용 매트리스1경상남도 밀양시 미리벌중앙로3길 47 삼문푸르지오 아파트 101동 703호 (삼문동 (삼문동 관할) : 그 외 지역)삼문동 (삼문동 관할) : 그 외 지역환경관리과055-359-53212
42021-08-02책장 (책꽂이)책장 (책꽂이)5단 미만1경상남도 밀양시 중앙로 234-22 일성아파트 2동 208호 (삼문동 (삼문동 관할) : 그 외 지역)삼문동 (삼문동 관할) : 그 외 지역환경관리과055-359-53212
62021-08-16서랍장서랍장1단 추가시3경상남도 밀양시 점필재로 45 105-203 (삼문동 (내이동 관할) : 373~432번지,도뮤토아파트)삼문동 (내이동 관할) : 373~432번지,도뮤토아파트환경관리과055-359-53212
72021-08-16서랍장서랍장1단기준1경상남도 밀양시 점필재로 45 105-203 (삼문동 (내이동 관할) : 373~432번지,도뮤토아파트)삼문동 (내이동 관할) : 373~432번지,도뮤토아파트환경관리과055-359-53212
82021-08-26책장 (책꽂이)책장 (책꽂이)5단 미만1경상남도 밀양시 상남면 상남로 1187-15 101동706호 (상남면)상남면환경관리과055-359-53212
92021-09-18세발 자전거세발 자전거모든규격1경상남도 밀양시 창밀로 3530 102동 2202호 (내이동)내이동환경관리과055-359-53212