Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory957.0 KiB
Average record size in memory98.0 B

Variable types

Categorical3
Text5
Numeric2
DateTime1

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실)
Author지방자치단체
URLhttps://www.data.go.kr/data/15114146/standard.do

Alerts

제공기관코드 is highly overall correlated with 시도명High correlation
시도명 is highly overall correlated with 제공기관코드High correlation
유무료여부 is highly imbalanced (83.3%)Imbalance
수수료 has 254 (2.5%) zerosZeros

Reproduction

Analysis started2024-05-11 10:30:43.150428
Analysis finished2024-05-11 10:30:49.050676
Duration5.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도
1734 
서울특별시
1409 
부산광역시
895 
경상북도
752 
강원특별자치도
605 
Other values (14)
4605 

Length

Max length7
Median length5
Mean length4.501
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row서울특별시
3rd row경상남도
4th row대구광역시
5th row부산광역시

Common Values

ValueCountFrequency (%)
경기도 1734
17.3%
서울특별시 1409
14.1%
부산광역시 895
8.9%
경상북도 752
 
7.5%
강원특별자치도 605
 
6.0%
대구광역시 563
 
5.6%
충청남도 484
 
4.8%
전라남도 474
 
4.7%
인천광역시 472
 
4.7%
경상남도 455
 
4.5%
Other values (9) 2157
21.6%

Length

2024-05-11T10:30:49.362355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 1734
17.3%
서울특별시 1409
14.1%
부산광역시 895
8.9%
경상북도 752
 
7.5%
강원특별자치도 605
 
6.0%
대구광역시 563
 
5.6%
충청남도 484
 
4.8%
전라남도 474
 
4.7%
인천광역시 472
 
4.7%
경상남도 455
 
4.5%
Other values (9) 2157
21.6%

시군구명
Text

Distinct111
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:30:50.145027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9437
Min length2

Characters and Unicode

Total characters29437
Distinct characters95
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row성북구
2nd row용산구
3rd row거창군
4th row북구
5th row사상구
ValueCountFrequency (%)
서구 302
 
3.0%
중구 268
 
2.7%
홍천군 217
 
2.2%
성북구 190
 
1.9%
용산구 187
 
1.9%
북구 183
 
1.8%
남구 182
 
1.8%
동구 179
 
1.8%
서귀포시 173
 
1.7%
중랑구 152
 
1.5%
Other values (101) 7967
79.7%
2024-05-11T10:30:51.475627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 3901
 
13.3%
시 3620
 
12.3%
군 2634
 
8.9%
천 1151
 
3.9%
산 1038
 
3.5%
주 1025
 
3.5%
성 968
 
3.3%
서 952
 
3.2%
양 843
 
2.9%
남 542
 
1.8%
Other values (85) 12763
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29437
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3901
 
13.3%
시 3620
 
12.3%
군 2634
 
8.9%
천 1151
 
3.9%
산 1038
 
3.5%
주 1025
 
3.5%
성 968
 
3.3%
서 952
 
3.2%
양 843
 
2.9%
남 542
 
1.8%
Other values (85) 12763
43.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29437
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3901
 
13.3%
시 3620
 
12.3%
군 2634
 
8.9%
천 1151
 
3.9%
산 1038
 
3.5%
주 1025
 
3.5%
성 968
 
3.3%
서 952
 
3.2%
양 843
 
2.9%
남 542
 
1.8%
Other values (85) 12763
43.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29437
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 3901
 
13.3%
시 3620
 
12.3%
군 2634
 
8.9%
천 1151
 
3.9%
산 1038
 
3.5%
주 1025
 
3.5%
성 968
 
3.3%
서 952
 
3.2%
양 843
 
2.9%
남 542
 
1.8%
Other values (85) 12763
43.4%

대형폐기물명
Text

Distinct1932
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:30:52.457347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length46
Mean length4.3301
Min length1

Characters and Unicode

Total characters43301
Distinct characters498
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique990 ?
Unique (%)9.9%

Sample

1st row침대
2nd row책상
3rd row쌀통
4th row벽시계
5th row소파　
ValueCountFrequency (%)
침대 260
 
2.3%
책상 183
 
1.6%
냉장고 168
 
1.5%
피아노 153
 
1.3%
의자 141
 
1.2%
장롱 135
 
1.2%
식탁 132
 
1.2%
소파 130
 
1.1%
서랍장 129
 
1.1%
자전거 120
 
1.1%
Other values (1859) 9858
86.4%
2024-05-11T10:30:53.959858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 2195
 
5.1%
장 1735
 
4.0%
1409
 
3.3%
대 1108
 
2.6%
( 1105
 
2.6%
) 1104
 
2.5%
자 911
 
2.1%
스 774
 
1.8%
전 681
 
1.6%
리 623
 
1.4%
Other values (488) 31656
73.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 38217
88.3%
Space Separator 1423
 
3.3%
Open Punctuation 1105
 
2.6%
Close Punctuation 1104
 
2.5%
Other Punctuation 572
 
1.3%
Math Symbol 383
 
0.9%
Uppercase Letter 353
 
0.8%
Decimal Number 94
 
0.2%
Lowercase Letter 35
 
0.1%
Connector Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 2195
 
5.7%
장 1735
 
4.5%
대 1108
 
2.9%
자 911
 
2.4%
스 774
 
2.0%
전 681
 
1.8%
리 623
 
1.6%
이 622
 
1.6%
트 605
 
1.6%
침 574
 
1.5%
Other values (446) 28389
74.3%
Uppercase Letter
ValueCountFrequency (%)
V 93
26.3%
T 79
22.4%
P 45
12.7%
R 39
11.0%
F 38
10.8%
D 33
 
9.3%
C 10
 
2.8%
E 6
 
1.7%
L 5
 
1.4%
B 2
 
0.6%
Other values (3) 3
 
0.8%
Decimal Number
ValueCountFrequency (%)
1 37
39.4%
2 17
18.1%
0 11
 
11.7%
3 8
 
8.5%
5 8
 
8.5%
8 6
 
6.4%
4 3
 
3.2%
6 3
 
3.2%
7 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 373
65.2%
· 110
 
19.2%
/ 47
 
8.2%
. 24
 
4.2%
* 16
 
2.8%
? 2
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
m 18
51.4%
c 9
25.7%
v 3
 
8.6%
t 3
 
8.6%
g 1
 
2.9%
k 1
 
2.9%
Space Separator
ValueCountFrequency (%)
1409
99.0%
　 14
 
1.0%
Math Symbol
ValueCountFrequency (%)
+ 380
99.2%
~ 3
 
0.8%
Open Punctuation
ValueCountFrequency (%)
( 1105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1104
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 38215
88.3%
Common 4696
 
10.8%
Latin 388
 
0.9%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 2195
 
5.7%
장 1735
 
4.5%
대 1108
 
2.9%
자 911
 
2.4%
스 774
 
2.0%
전 681
 
1.8%
리 623
 
1.6%
이 622
 
1.6%
트 605
 
1.6%
침 574
 
1.5%
Other values (444) 28387
74.3%
Common
ValueCountFrequency (%)
1409
30.0%
( 1105
23.5%
) 1104
23.5%
+ 380
 
8.1%
, 373
 
7.9%
· 110
 
2.3%
/ 47
 
1.0%
1 37
 
0.8%
. 24
 
0.5%
2 17
 
0.4%
Other values (13) 90
 
1.9%
Latin
ValueCountFrequency (%)
V 93
24.0%
T 79
20.4%
P 45
11.6%
R 39
10.1%
F 38
9.8%
D 33
 
8.5%
m 18
 
4.6%
C 10
 
2.6%
c 9
 
2.3%
E 6
 
1.5%
Other values (9) 18
 
4.6%
Han
ValueCountFrequency (%)
沮 1
50.0%
劉 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 38208
88.2%
ASCII 4960
 
11.5%
None 124
 
0.3%
Compat Jamo 7
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 2195
 
5.7%
장 1735
 
4.5%
대 1108
 
2.9%
자 911
 
2.4%
스 774
 
2.0%
전 681
 
1.8%
리 623
 
1.6%
이 622
 
1.6%
트 605
 
1.6%
침 574
 
1.5%
Other values (443) 28380
74.3%
ASCII
ValueCountFrequency (%)
1409
28.4%
( 1105
22.3%
) 1104
22.3%
+ 380
 
7.7%
, 373
 
7.5%
V 93
 
1.9%
T 79
 
1.6%
/ 47
 
0.9%
P 45
 
0.9%
R 39
 
0.8%
Other values (30) 286
 
5.8%
None
ValueCountFrequency (%)
· 110
88.7%
　 14
 
11.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 7
100.0%
CJK
ValueCountFrequency (%)
沮 1
50.0%
劉 1
50.0%

대형폐기물구분명
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
가구류
2995 
기타
2692 
가전제품류
2194 
생활용품류
2119 

Length

Max length5
Median length3
Mean length3.5934
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가구류
2nd row가구류
3rd row생활용품류
4th row생활용품류
5th row가구류

Common Values

ValueCountFrequency (%)
가구류 2995
29.9%
기타 2692
26.9%
가전제품류 2194
21.9%
생활용품류 2119
21.2%

Length

2024-05-11T10:30:54.405300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:30:54.732836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가구류 2995
29.9%
기타 2692
26.9%
가전제품류 2194
21.9%
생활용품류 2119
21.2%

대형폐기물규격
Text

Distinct3711
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:30:55.623548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length41
Mean length6.7364
Min length1

Characters and Unicode

Total characters67364
Distinct characters525
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2762 ?
Unique (%)27.6%

Sample

1st row침대 2층침대 사다리
2nd rowh형 책상+책상상판+책장+서랍 포함된 책상
3rd row용량 80킬로그램 미만
4th row소형(높이0.5m미만)
5th row리클라이너(추가)
ValueCountFrequency (%)
이상 1378
 
8.0%
모든규격 1215
 
7.0%
미만 1115
 
6.5%
규격 879
 
5.1%
모든 875
 
5.1%
1m 457
 
2.7%
높이 439
 
2.5%
1인용 299
 
1.7%
2인용 241
 
1.4%
이하 222
 
1.3%
Other values (2945) 10124
58.7%
2024-05-11T10:30:57.342704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7258
 
10.8%
이 3684
 
5.5%
1 3166
 
4.7%
0 3035
 
4.5%
m 2383
 
3.5%
상 2262
 
3.4%
모 2187
 
3.2%
격 2156
 
3.2%
규 2156
 
3.2%
든 2145
 
3.2%
Other values (515) 36932
54.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39766
59.0%
Decimal Number 10872
 
16.1%
Space Separator 7276
 
10.8%
Lowercase Letter 4262
 
6.3%
Close Punctuation 1347
 
2.0%
Open Punctuation 1347
 
2.0%
Other Punctuation 831
 
1.2%
Other Symbol 793
 
1.2%
Math Symbol 482
 
0.7%
Uppercase Letter 342
 
0.5%
Other values (3) 46
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 3684
 
9.3%
상 2262
 
5.7%
모 2187
 
5.5%
격 2156
 
5.4%
규 2156
 
5.4%
든 2145
 
5.4%
미 1970
 
5.0%
용 1797
 
4.5%
만 1677
 
4.2%
인 1511
 
3.8%
Other values (436) 18221
45.8%
Lowercase Letter
ValueCountFrequency (%)
m 2383
55.9%
c 1017
23.9%
g 252
 
5.9%
k 251
 
5.9%
ℓ 196
 
4.6%
x 76
 
1.8%
h 26
 
0.6%
l 19
 
0.4%
a 14
 
0.3%
e 5
 
0.1%
Other values (9) 23
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
L 126
36.8%
C 60
17.5%
M 35
 
10.2%
X 34
 
9.9%
R 13
 
3.8%
P 12
 
3.5%
K 10
 
2.9%
V 10
 
2.9%
D 10
 
2.9%
T 9
 
2.6%
Other values (8) 23
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 3166
29.1%
0 3035
27.9%
2 1325
12.2%
5 908
 
8.4%
6 703
 
6.5%
3 596
 
5.5%
4 491
 
4.5%
9 343
 
3.2%
8 223
 
2.1%
7 82
 
0.8%
Other Symbol
ValueCountFrequency (%)
㎝ 321
40.5%
㎡ 316
39.8%
㎏ 84
 
10.6%
㎥ 62
 
7.8%
㎉ 4
 
0.5%
㎘ 2
 
0.3%
㎜ 2
 
0.3%
㎈ 1
 
0.1%
㎠ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
× 217
45.0%
+ 143
29.7%
~ 110
22.8%
∼ 4
 
0.8%
> 3
 
0.6%
～ 3
 
0.6%
= 1
 
0.2%
| 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
. 446
53.7%
, 269
32.4%
* 56
 
6.7%
/ 37
 
4.5%
· 22
 
2.6%
: 1
 
0.1%
Space Separator
ValueCountFrequency (%)
7258
99.8%
　 18
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 1342
99.6%
] 5
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 1342
99.6%
[ 5
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 13
100.0%
Other Number
ValueCountFrequency (%)
² 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39762
59.0%
Common 23190
34.4%
Latin 4408
 
6.5%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 3684
 
9.3%
상 2262
 
5.7%
모 2187
 
5.5%
격 2156
 
5.4%
규 2156
 
5.4%
든 2145
 
5.4%
미 1970
 
5.0%
용 1797
 
4.5%
만 1677
 
4.2%
인 1511
 
3.8%
Other values (434) 18217
45.8%
Common
ValueCountFrequency (%)
7258
31.3%
1 3166
13.7%
0 3035
13.1%
) 1342
 
5.8%
( 1342
 
5.8%
2 1325
 
5.7%
5 908
 
3.9%
6 703
 
3.0%
3 596
 
2.6%
4 491
 
2.1%
Other values (33) 3024
13.0%
Latin
ValueCountFrequency (%)
m 2383
54.1%
c 1017
23.1%
g 252
 
5.7%
k 251
 
5.7%
L 126
 
2.9%
x 76
 
1.7%
C 60
 
1.4%
M 35
 
0.8%
X 34
 
0.8%
h 26
 
0.6%
Other values (26) 148
 
3.4%
Han
ValueCountFrequency (%)
小 2
50.0%
大 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39757
59.0%
ASCII 26333
39.1%
CJK Compat 793
 
1.2%
None 272
 
0.4%
Letterlike Symbols 196
 
0.3%
Compat Jamo 5
 
< 0.1%
Math Operators 4
 
< 0.1%
CJK 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7258
27.6%
1 3166
12.0%
0 3035
11.5%
m 2383
 
9.0%
) 1342
 
5.1%
( 1342
 
5.1%
2 1325
 
5.0%
c 1017
 
3.9%
5 908
 
3.4%
6 703
 
2.7%
Other values (53) 3854
14.6%
Hangul
ValueCountFrequency (%)
이 3684
 
9.3%
상 2262
 
5.7%
모 2187
 
5.5%
격 2156
 
5.4%
규 2156
 
5.4%
든 2145
 
5.4%
미 1970
 
5.0%
용 1797
 
4.5%
만 1677
 
4.2%
인 1511
 
3.8%
Other values (433) 18212
45.8%
CJK Compat
ValueCountFrequency (%)
㎝ 321
40.5%
㎡ 316
39.8%
㎏ 84
 
10.6%
㎥ 62
 
7.8%
㎉ 4
 
0.5%
㎘ 2
 
0.3%
㎜ 2
 
0.3%
㎈ 1
 
0.1%
㎠ 1
 
0.1%
None
ValueCountFrequency (%)
× 217
79.8%
· 22
 
8.1%
　 18
 
6.6%
² 12
 
4.4%
～ 3
 
1.1%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 196
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 5
100.0%
Math Operators
ValueCountFrequency (%)
∼ 4
100.0%
CJK
ValueCountFrequency (%)
小 2
50.0%
大 2
50.0%

유무료여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
유료
9753 
무료
 
247

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유료 9753
97.5%
무료 247
 
2.5%

Length

2024-05-11T10:30:57.908935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:30:58.337212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 9753
97.5%
무료 247
 
2.5%

수수료
Real number (ℝ)

ZEROS 

Distinct97
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5343.73
Minimum0
Maximum300000
Zeros254
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:30:58.801257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1000
Q12000
median4000
Q36000
95-th percentile15000
Maximum300000
Range300000
Interquartile range (IQR)4000

Descriptive statistics

Standard deviation7424.5726
Coefficient of variation (CV)1.3893989
Kurtosis528.46227
Mean5343.73
Median Absolute Deviation (MAD)2000
Skewness17.376252
Sum53437300
Variance55124278
MonotonicityNot monotonic
2024-05-11T10:30:59.288856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 1851
18.5%
3000 1842
18.4%
5000 1300
13.0%
4000 1042
10.4%
1000 612
 
6.1%
6000 507
 
5.1%
10000 502
 
5.0%
8000 428
 
4.3%
7000 334
 
3.3%
0 254
 
2.5%
Other values (87) 1328
13.3%
ValueCountFrequency (%)
0 254
2.5%
100 3
 
< 0.1%
120 1
 
< 0.1%
280 1
 
< 0.1%
300 1
 
< 0.1%
500 17
 
0.2%
1000 612
6.1%
1200 5
 
0.1%
1300 4
 
< 0.1%
1500 21
 
0.2%
ValueCountFrequency (%)
300000 1
 
< 0.1%
250000 1
 
< 0.1%
240000 1
 
< 0.1%
170000 1
 
< 0.1%
150000 1
 
< 0.1%
123000 1
 
< 0.1%
100000 6
0.1%
80000 1
 
< 0.1%
75000 1
 
< 0.1%
60000 1
 
< 0.1%

관리기관명
Text

Distinct125
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:31:00.153717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length9.8589
Min length3

Characters and Unicode

Total characters98589
Distinct characters115
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row서울특별시 성북구청
2nd row서울특별시 용산구청 청소행정과
3rd row경상남도 거창군청
4th row대구광역시 북구청
5th row부산광역시 사상구
ValueCountFrequency (%)
경기도 1537
 
7.5%
서울특별시 1409
 
6.9%
자원순환과 928
 
4.5%
강원특별자치도 877
 
4.3%
부산광역시 580
 
2.8%
경상북도 499
 
2.4%
충청남도 484
 
2.4%
전라남도 474
 
2.3%
경상남도 455
 
2.2%
청소행정과 437
 
2.1%
Other values (128) 12872
62.6%
2024-05-11T10:31:01.251903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10552
 
10.7%
청 8831
 
9.0%
시 6900
 
7.0%
도 5348
 
5.4%
구 3861
 
3.9%
경 3381
 
3.4%
특 2694
 
2.7%
별 2694
 
2.7%
군 2634
 
2.7%
원 2494
 
2.5%
Other values (105) 49200
49.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 88037
89.3%
Space Separator 10552
 
10.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 8831
 
10.0%
시 6900
 
7.8%
도 5348
 
6.1%
구 3861
 
4.4%
경 3381
 
3.8%
특 2694
 
3.1%
별 2694
 
3.1%
군 2634
 
3.0%
원 2494
 
2.8%
자 2459
 
2.8%
Other values (104) 46741
53.1%
Space Separator
ValueCountFrequency (%)
10552
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 88037
89.3%
Common 10552
 
10.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 8831
 
10.0%
시 6900
 
7.8%
도 5348
 
6.1%
구 3861
 
4.4%
경 3381
 
3.8%
특 2694
 
3.1%
별 2694
 
3.1%
군 2634
 
3.0%
원 2494
 
2.8%
자 2459
 
2.8%
Other values (104) 46741
53.1%
Common
ValueCountFrequency (%)
10552
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 88037
89.3%
ASCII 10552
 
10.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10552
100.0%
Hangul
ValueCountFrequency (%)
청 8831
 
10.0%
시 6900
 
7.8%
도 5348
 
6.1%
구 3861
 
4.4%
경 3381
 
3.8%
특 2694
 
3.1%
별 2694
 
3.1%
군 2634
 
3.0%
원 2494
 
2.8%
자 2459
 
2.8%
Other values (104) 46741
53.1%

데이터기준일자
Date

Distinct61
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-06-01 00:00:00
Maximum2024-04-25 00:00:00
2024-05-11T10:31:01.658652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:31:02.140640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

제공기관코드
Real number (ℝ)

HIGH CORRELATION 

Distinct131
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4152828.8
Minimum3000000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:31:02.637506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3060000
Q13450000
median4060000
Q34731000
95-th percentile5670000
Maximum6520000
Range3520000
Interquartile range (IQR)1281000

Descriptive statistics

Standard deviation834345.89
Coefficient of variation (CV)0.20091026
Kurtosis-0.39584596
Mean4152828.8
Median Absolute Deviation (MAD)640000
Skewness0.59056291
Sum4.1528288 × 1010
Variance6.9613307 × 1011
MonotonicityNot monotonic
2024-05-11T10:31:03.187198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3070000 190
 
1.9%
3020000 187
 
1.9%
6520000 173
 
1.7%
3060000 152
 
1.5%
5530000 144
 
1.4%
3210000 141
 
1.4%
3100000 138
 
1.4%
4820000 134
 
1.3%
3010000 129
 
1.3%
4390000 129
 
1.3%
Other values (121) 8483
84.8%
ValueCountFrequency (%)
3000000 74
 
0.7%
3010000 129
1.3%
3020000 187
1.9%
3060000 152
1.5%
3070000 190
1.9%
3100000 138
1.4%
3140000 122
1.2%
3150000 93
0.9%
3200000 102
1.0%
3210000 141
1.4%
ValueCountFrequency (%)
6520000 173
1.7%
5710000 70
0.7%
5700000 85
0.9%
5690000 98
1.0%
5670000 87
0.9%
5590000 98
1.0%
5530000 144
1.4%
5480000 36
 
0.4%
5470000 41
 
0.4%
5460000 76
0.8%

제공기관명
Text

Distinct131
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:31:03.964960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.5124
Min length7

Characters and Unicode

Total characters85124
Distinct characters103
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row서울특별시 성북구
2nd row서울특별시 용산구
3rd row경상남도 거창군
4th row대구광역시 북구
5th row부산광역시 사상구
ValueCountFrequency (%)
경기도 1734
 
8.7%
서울특별시 1409
 
7.1%
부산광역시 895
 
4.5%
강원특별자치도 772
 
3.9%
경상북도 752
 
3.8%
대구광역시 563
 
2.8%
충청남도 484
 
2.4%
전라남도 474
 
2.4%
인천광역시 472
 
2.4%
경상남도 455
 
2.3%
Other values (119) 11892
59.8%
2024-05-11T10:31:05.052444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9902
 
11.6%
시 7747
 
9.1%
도 5990
 
7.0%
구 4464
 
5.2%
경 2989
 
3.5%
광 2974
 
3.5%
특 2690
 
3.2%
별 2690
 
3.2%
군 2634
 
3.1%
역 2620
 
3.1%
Other values (93) 40424
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 75222
88.4%
Space Separator 9902
 
11.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 7747
 
10.3%
도 5990
 
8.0%
구 4464
 
5.9%
경 2989
 
4.0%
광 2974
 
4.0%
특 2690
 
3.6%
별 2690
 
3.6%
군 2634
 
3.5%
역 2620
 
3.5%
서 2361
 
3.1%
Other values (92) 38063
50.6%
Space Separator
ValueCountFrequency (%)
9902
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 75222
88.4%
Common 9902
 
11.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 7747
 
10.3%
도 5990
 
8.0%
구 4464
 
5.9%
경 2989
 
4.0%
광 2974
 
4.0%
특 2690
 
3.6%
별 2690
 
3.6%
군 2634
 
3.5%
역 2620
 
3.5%
서 2361
 
3.1%
Other values (92) 38063
50.6%
Common
ValueCountFrequency (%)
9902
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 75222
88.4%
ASCII 9902
 
11.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9902
100.0%
Hangul
ValueCountFrequency (%)
시 7747
 
10.3%
도 5990
 
8.0%
구 4464
 
5.9%
경 2989
 
4.0%
광 2974
 
4.0%
특 2690
 
3.6%
별 2690
 
3.6%
군 2634
 
3.5%
역 2620
 
3.5%
서 2361
 
3.1%
Other values (92) 38063
50.6%

Interactions

2024-05-11T10:30:47.025612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:30:46.330091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:30:47.468620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:30:46.644670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T10:31:05.350621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명대형폐기물구분명유무료여부수수료데이터기준일자제공기관코드
시도명1.0000.3130.2160.0730.9760.966
대형폐기물구분명0.3131.0000.3830.0340.4690.200
유무료여부0.2160.3831.0000.0000.3400.099
수수료0.0730.0340.0001.0000.0000.000
데이터기준일자0.9760.4690.3400.0001.0000.954
제공기관코드0.9660.2000.0990.0000.9541.000
2024-05-11T10:31:05.659261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유무료여부시도명대형폐기물구분명
유무료여부1.0000.1910.257
시도명0.1911.0000.176
대형폐기물구분명0.2570.1761.000
2024-05-11T10:31:06.177081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수수료제공기관코드시도명대형폐기물구분명유무료여부
수수료1.000-0.0160.0290.0220.000
제공기관코드-0.0161.0000.8340.1250.105
시도명0.0290.8341.0000.1760.191
대형폐기물구분명0.0220.1250.1761.0000.257
유무료여부0.0000.1050.1910.2571.000

Missing values

2024-05-11T10:30:48.007370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T10:30:48.728223image/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

시도명시군구명대형폐기물명대형폐기물구분명대형폐기물규격유무료여부수수료관리기관명데이터기준일자제공기관코드제공기관명
999서울특별시성북구침대가구류침대 2층침대 사다리유료2000서울특별시 성북구청2023-07-013070000서울특별시 성북구
790서울특별시용산구책상가구류h형 책상+책상상판+책장+서랍 포함된 책상유료10000서울특별시 용산구청 청소행정과2023-07-133020000서울특별시 용산구
5857경상남도거창군쌀통생활용품류용량 80킬로그램 미만유료3000경상남도 거창군청2023-06-305470000경상남도 거창군
5209대구광역시북구벽시계생활용품류소형(높이0.5m미만)유료1000대구광역시 북구청2023-07-073450000대구광역시 북구
7692부산광역시사상구소파가구류리클라이너(추가)유료5000부산광역시 사상구2023-07-033390000부산광역시 사상구
17910인천광역시미추홀구오락기생활용품류일반유료10000인천광역시 미추홀구청2024-01-043510500인천광역시 미추홀구
11290경상북도영주시에어컨(난방기)가전제품류벽걸이형유료3000환경보호과2023-07-205090000경상북도 영주시
16164대전광역시동구광고판기타3㎡이상유료7000대전광역시 동구청2023-08-253640000대전광역시 동구
3126경상남도창원시소형가전가전제품류카세트라디오유료2000경상남도 창원시청2023-07-105670000경상남도 창원시
2609경상남도함양군식기건조기가전제품류모든 규격유료3000경상남도 함양군청2023-07-105460000경상남도 함양군
시도명시군구명대형폐기물명대형폐기물구분명대형폐기물규격유무료여부수수료관리기관명데이터기준일자제공기관코드제공기관명
12317충청북도옥천군냉온수기가전제품류1m 미만유료3000충청북도 옥천군청 환경과2023-06-284430000충청북도 옥천군
13308울산광역시울주군에어콘가전제품류264㎡형 이상무료0울산광역시 울주군청2023-07-143730000울산광역시 울주군
8079경상북도영덕군비키니옷장기타모든 규격유료2000경상북도 영덕군청2023-06-285180000경상북도 영덕군
15800제주특별자치도서귀포시물탱크기타1000~2000L유료15000제주특별자치도 서귀포시청 생활환경과2023-07-276520000제주특별자치도 서귀포시
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