Overview

Dataset statistics

Number of variables3
Number of observations117
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory26.1 B

Variable types

Text2
Numeric1

Dataset

Description부산광역시사상구_대형폐기물처리수수료정보_20221031
Author부산광역시 사상구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15093872

Alerts

수수료 has 19 (16.2%) zerosZeros

Reproduction

Analysis started2023-12-10 16:23:50.501681
Analysis finished2023-12-10 16:23:51.169245
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

폐기물 명
Text

Distinct74
Distinct (%)63.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-11T01:23:51.480227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length4.4188034
Min length1

Characters and Unicode

Total characters517
Distinct characters147
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)35.9%

Sample

1st row냉장고(자판기)
2nd row냉장고(자판기)
3rd row냉장고(자판기)
4th row냉장고(자판기)
5th row텔레비전
ValueCountFrequency (%)
냉장고(자판기 4
 
2.7%
물탱크 4
 
2.7%
정화조(frp 4
 
2.7%
일반침대 4
 
2.7%
에어컨(온풍기 3
 
2.0%
기 3
 
2.0%
1쪽당 3
 
2.0%
장롱(장식장 3
 
2.0%
전기요 3
 
2.0%
의자 3
 
2.0%
Other values (83) 113
76.9%
2023-12-11T01:23:52.117348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 34
 
6.6%
30
 
5.8%
장 21
 
4.1%
( 20
 
3.9%
) 18
 
3.5%
자 14
 
2.7%
전 13
 
2.5%
대 10
 
1.9%
, 9
 
1.7%
식 8
 
1.5%
Other values (137) 340
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 418
80.9%
Space Separator 30
 
5.8%
Open Punctuation 20
 
3.9%
Close Punctuation 18
 
3.5%
Uppercase Letter 18
 
3.5%
Other Punctuation 9
 
1.7%
Decimal Number 4
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 34
 
8.1%
장 21
 
5.0%
자 14
 
3.3%
전 13
 
3.1%
대 10
 
2.4%
식 8
 
1.9%
크 8
 
1.9%
정 7
 
1.7%
판 7
 
1.7%
탱 6
 
1.4%
Other values (126) 290
69.4%
Uppercase Letter
ValueCountFrequency (%)
P 6
33.3%
R 4
22.2%
F 4
22.2%
C 2
 
11.1%
T 1
 
5.6%
V 1
 
5.6%
Space Separator
ValueCountFrequency (%)
30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Decimal Number
ValueCountFrequency (%)
1 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 418
80.9%
Common 81
 
15.7%
Latin 18
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 34
 
8.1%
장 21
 
5.0%
자 14
 
3.3%
전 13
 
3.1%
대 10
 
2.4%
식 8
 
1.9%
크 8
 
1.9%
정 7
 
1.7%
판 7
 
1.7%
탱 6
 
1.4%
Other values (126) 290
69.4%
Latin
ValueCountFrequency (%)
P 6
33.3%
R 4
22.2%
F 4
22.2%
C 2
 
11.1%
T 1
 
5.6%
V 1
 
5.6%
Common
ValueCountFrequency (%)
30
37.0%
( 20
24.7%
) 18
22.2%
, 9
 
11.1%
1 4
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 418
80.9%
ASCII 99
 
19.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 34
 
8.1%
장 21
 
5.0%
자 14
 
3.3%
전 13
 
3.1%
대 10
 
2.4%
식 8
 
1.9%
크 8
 
1.9%
정 7
 
1.7%
판 7
 
1.7%
탱 6
 
1.4%
Other values (126) 290
69.4%
ASCII
ValueCountFrequency (%)
30
30.3%
( 20
20.2%
) 18
18.2%
, 9
 
9.1%
P 6
 
6.1%
1 4
 
4.0%
R 4
 
4.0%
F 4
 
4.0%
C 2
 
2.0%
T 1
 
1.0%

폐기물 규격
Text

Distinct72
Distinct (%)61.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-11T01:23:52.488067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length9
Mean length4.7692308
Min length2

Characters and Unicode

Total characters558
Distinct characters101
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)51.3%

Sample

1st row1000ℓ이상
2nd row500ℓ이상
3rd row300ℓ이상
4th row300ℓ미만
5th row42인치이상
ValueCountFrequency (%)
개당 16
 
12.4%
대당 15
 
11.6%
1㎡이상 4
 
3.1%
높이1m이상 3
 
2.3%
가로120cm당 3
 
2.3%
1인용 3
 
2.3%
높이1m미만 3
 
2.3%
1㎡미만 2
 
1.6%
폭 2
 
1.6%
2인용 2
 
1.6%
Other values (72) 76
58.9%
2023-12-11T01:23:53.035374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 40
 
7.2%
당 36
 
6.5%
1 35
 
6.3%
0 30
 
5.4%
상 29
 
5.2%
미 21
 
3.8%
2 21
 
3.8%
만 21
 
3.8%
대 19
 
3.4%
m 18
 
3.2%
Other values (91) 288
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 356
63.8%
Decimal Number 112
 
20.1%
Lowercase Letter 37
 
6.6%
Other Symbol 20
 
3.6%
Space Separator 12
 
2.2%
Open Punctuation 8
 
1.4%
Close Punctuation 8
 
1.4%
Other Punctuation 5
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 40
 
11.2%
당 36
 
10.1%
상 29
 
8.1%
미 21
 
5.9%
만 21
 
5.9%
대 19
 
5.3%
용 17
 
4.8%
인 16
 
4.5%
개 16
 
4.5%
로 9
 
2.5%
Other values (72) 132
37.1%
Decimal Number
ValueCountFrequency (%)
1 35
31.2%
0 30
26.8%
2 21
18.8%
6 9
 
8.0%
5 5
 
4.5%
3 4
 
3.6%
9 4
 
3.6%
4 2
 
1.8%
7 2
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
m 18
48.6%
c 10
27.0%
ℓ 9
24.3%
Other Symbol
ValueCountFrequency (%)
㎡ 13
65.0%
㎘ 4
 
20.0%
㎏ 3
 
15.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 356
63.8%
Common 174
31.2%
Latin 28
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 40
 
11.2%
당 36
 
10.1%
상 29
 
8.1%
미 21
 
5.9%
만 21
 
5.9%
대 19
 
5.3%
용 17
 
4.8%
인 16
 
4.5%
개 16
 
4.5%
로 9
 
2.5%
Other values (72) 132
37.1%
Common
ValueCountFrequency (%)
1 35
20.1%
0 30
17.2%
2 21
12.1%
㎡ 13
 
7.5%
12
 
6.9%
ℓ 9
 
5.2%
6 9
 
5.2%
( 8
 
4.6%
) 8
 
4.6%
, 5
 
2.9%
Other values (7) 24
13.8%
Latin
ValueCountFrequency (%)
m 18
64.3%
c 10
35.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 356
63.8%
ASCII 173
31.0%
CJK Compat 20
 
3.6%
Letterlike Symbols 9
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 40
 
11.2%
당 36
 
10.1%
상 29
 
8.1%
미 21
 
5.9%
만 21
 
5.9%
대 19
 
5.3%
용 17
 
4.8%
인 16
 
4.5%
개 16
 
4.5%
로 9
 
2.5%
Other values (72) 132
37.1%
ASCII
ValueCountFrequency (%)
1 35
20.2%
0 30
17.3%
2 21
12.1%
m 18
10.4%
12
 
6.9%
c 10
 
5.8%
6 9
 
5.2%
( 8
 
4.6%
) 8
 
4.6%
, 5
 
2.9%
Other values (5) 17
9.8%
CJK Compat
ValueCountFrequency (%)
㎡ 13
65.0%
㎘ 4
 
20.0%
㎏ 3
 
15.0%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 9
100.0%

수수료
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6987.1795
Minimum0
Maximum80000
Zeros19
Zeros (%)16.2%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T01:23:53.164142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12000
median5000
Q37000
95-th percentile21000
Maximum80000
Range80000
Interquartile range (IQR)5000

Descriptive statistics

Standard deviation10783.221
Coefficient of variation (CV)1.5432867
Kurtosis22.874689
Mean6987.1795
Median Absolute Deviation (MAD)3000
Skewness4.2796244
Sum817500
Variance1.1627785 × 108
MonotonicityNot monotonic
2023-12-11T01:23:53.293438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 19
16.2%
5000 18
15.4%
3000 12
10.3%
2000 12
10.3%
7000 11
9.4%
4000 8
6.8%
10000 6
 
5.1%
15000 6
 
5.1%
1000 5
 
4.3%
6000 4
 
3.4%
Other values (11) 16
13.7%
ValueCountFrequency (%)
0 19
16.2%
1000 5
 
4.3%
1500 1
 
0.9%
2000 12
10.3%
3000 12
10.3%
4000 8
6.8%
5000 18
15.4%
6000 4
 
3.4%
7000 11
9.4%
8000 1
 
0.9%
ValueCountFrequency (%)
80000 1
 
0.9%
60000 1
 
0.9%
40000 1
 
0.9%
35000 1
 
0.9%
30000 1
 
0.9%
25000 1
 
0.9%
20000 2
 
1.7%
15000 6
5.1%
12000 2
 
1.7%
10000 6
5.1%

Interactions

2023-12-11T01:23:50.807127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:23:53.403404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물 명폐기물 규격수수료
폐기물 명1.0000.0000.000
폐기물 규격0.0001.0000.986
수수료0.0000.9861.000

Missing values

2023-12-11T01:23:51.010177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:23:51.125877image/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

폐기물 명폐기물 규격수수료
0냉장고(자판기)1000ℓ이상30000
1냉장고(자판기)500ℓ이상15000
2냉장고(자판기)300ℓ이상10000
3냉장고(자판기)300ℓ미만6000
4텔레비전42인치이상5000
5텔레비전29인치이상4000
6텔레비전29인치미만3000
7세탁기10㎏이상7000
8세탁기10㎏미만5000
9에어컨(온풍기)264㎡이상12000
폐기물 명폐기물 규격수수료
107이불, 담요, 카페트10㎏당5000
108스티로폼1마대(100ℓ)2000
109천막,장판(합성수지100ℓ마대5000
110드럼통개당4000
111기름탱크2드럼이상6000
112기름탱크2드럼미만4000
113창틀1㎡이상2000
114창틀1㎡미만1000
115자전거성인용2000
116자전거아동용1000