Overview

Dataset statistics

Number of variables4
Number of observations203
Missing cells1
Missing cells (%)0.1%
Duplicate rows1
Duplicate rows (%)0.5%
Total size in memory6.7 KiB
Average record size in memory33.7 B

Variable types

Text2
Numeric1
Categorical1

Dataset

Description충청남도 부여군의 대형폐기물 배출(처리) 정보입니다.(품명, 규격, 금액 등 기준에 따른 배출 수수료 안내, 데이터기준일자)
Author충청남도 부여군
URLhttps://www.data.go.kr/data/3046045/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (0.5%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 23:28:47.779184
Analysis finished2023-12-12 23:28:48.309097
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품명
Text

Distinct123
Distinct (%)60.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-13T08:28:48.580608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length3.6157635
Min length2

Characters and Unicode

Total characters734
Distinct characters188
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

Unique68 ?
Unique (%)33.5%

Sample

1st row가스레인지
2nd row가스레인지
3rd row가스오븐렌지
4th row가스오븐렌지
5th row가스히터
ValueCountFrequency (%)
식탁(테이블 5
 
2.4%
타이어 4
 
1.9%
냉장고 4
 
1.9%
온풍기 4
 
1.9%
간판 4
 
1.9%
책상 3
 
1.5%
액자 3
 
1.5%
침대틀 3
 
1.5%
장롱 3
 
1.5%
보드판,칠판 3
 
1.5%
Other values (116) 170
82.5%
2023-12-13T08:28:49.061999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 49
 
6.7%
장 27
 
3.7%
이 21
 
2.9%
판 17
 
2.3%
대 15
 
2.0%
자 15
 
2.0%
스 14
 
1.9%
어 14
 
1.9%
수 13
 
1.8%
침 13
 
1.8%
Other values (178) 536
73.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 704
95.9%
Other Punctuation 11
 
1.5%
Close Punctuation 8
 
1.1%
Open Punctuation 8
 
1.1%
Space Separator 3
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 49
 
7.0%
장 27
 
3.8%
이 21
 
3.0%
판 17
 
2.4%
대 15
 
2.1%
자 15
 
2.1%
스 14
 
2.0%
어 14
 
2.0%
수 13
 
1.8%
침 13
 
1.8%
Other values (174) 506
71.9%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 704
95.9%
Common 30
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 49
 
7.0%
장 27
 
3.8%
이 21
 
3.0%
판 17
 
2.4%
대 15
 
2.1%
자 15
 
2.1%
스 14
 
2.0%
어 14
 
2.0%
수 13
 
1.8%
침 13
 
1.8%
Other values (174) 506
71.9%
Common
ValueCountFrequency (%)
, 11
36.7%
) 8
26.7%
( 8
26.7%
3
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 704
95.9%
ASCII 30
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 49
 
7.0%
장 27
 
3.8%
이 21
 
3.0%
판 17
 
2.4%
대 15
 
2.1%
자 15
 
2.1%
스 14
 
2.0%
어 14
 
2.0%
수 13
 
1.8%
침 13
 
1.8%
Other values (174) 506
71.9%
ASCII
ValueCountFrequency (%)
, 11
36.7%
) 8
26.7%
( 8
26.7%
3
 
10.0%

규격
Text

Distinct90
Distinct (%)44.6%
Missing1
Missing (%)0.5%
Memory size1.7 KiB
2023-12-13T08:28:49.382676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.2821782
Min length2

Characters and Unicode

Total characters865
Distinct characters102
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

Unique70 ?
Unique (%)34.7%

Sample

1st row휴대용
2nd row휴대용외
3rd row높이1m미만
4th row높이1m이상
5th row모든규격
ValueCountFrequency (%)
모든규격 59
27.6%
대형 9
 
4.2%
소형 9
 
4.2%
2인용 7
 
3.3%
가정용 7
 
3.3%
1인용 6
 
2.8%
사업장용 4
 
1.9%
미만 4
 
1.9%
업소용 4
 
1.9%
유아용 3
 
1.4%
Other values (85) 102
47.7%
2023-12-13T08:28:49.820470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
모 59
 
6.8%
규 59
 
6.8%
격 59
 
6.8%
든 59
 
6.8%
용 48
 
5.5%
m 44
 
5.1%
이 41
 
4.7%
1 34
 
3.9%
0 29
 
3.4%
2 29
 
3.4%
Other values (92) 404
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 639
73.9%
Decimal Number 135
 
15.6%
Lowercase Letter 63
 
7.3%
Space Separator 12
 
1.4%
Uppercase Letter 6
 
0.7%
Other Punctuation 5
 
0.6%
Other Symbol 2
 
0.2%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
모 59
 
9.2%
규 59
 
9.2%
격 59
 
9.2%
든 59
 
9.2%
용 48
 
7.5%
이 41
 
6.4%
상 28
 
4.4%
형 24
 
3.8%
인 22
 
3.4%
미 22
 
3.4%
Other values (68) 218
34.1%
Decimal Number
ValueCountFrequency (%)
1 34
25.2%
0 29
21.5%
2 29
21.5%
6 12
 
8.9%
4 10
 
7.4%
9 8
 
5.9%
3 7
 
5.2%
5 4
 
3.0%
8 2
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
E 2
33.3%
V 1
16.7%
P 1
16.7%
R 1
16.7%
J 1
16.7%
Lowercase Letter
ValueCountFrequency (%)
m 44
69.8%
c 15
 
23.8%
k 2
 
3.2%
g 2
 
3.2%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 639
73.9%
Common 157
 
18.2%
Latin 69
 
8.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
모 59
 
9.2%
규 59
 
9.2%
격 59
 
9.2%
든 59
 
9.2%
용 48
 
7.5%
이 41
 
6.4%
상 28
 
4.4%
형 24
 
3.8%
인 22
 
3.4%
미 22
 
3.4%
Other values (68) 218
34.1%
Common
ValueCountFrequency (%)
1 34
21.7%
0 29
18.5%
2 29
18.5%
6 12
 
7.6%
12
 
7.6%
4 10
 
6.4%
9 8
 
5.1%
3 7
 
4.5%
, 5
 
3.2%
5 4
 
2.5%
Other values (5) 7
 
4.5%
Latin
ValueCountFrequency (%)
m 44
63.8%
c 15
 
21.7%
k 2
 
2.9%
g 2
 
2.9%
E 2
 
2.9%
V 1
 
1.4%
P 1
 
1.4%
R 1
 
1.4%
J 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 639
73.9%
ASCII 224
 
25.9%
CJK Compat 2
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
모 59
 
9.2%
규 59
 
9.2%
격 59
 
9.2%
든 59
 
9.2%
용 48
 
7.5%
이 41
 
6.4%
상 28
 
4.4%
형 24
 
3.8%
인 22
 
3.4%
미 22
 
3.4%
Other values (68) 218
34.1%
ASCII
ValueCountFrequency (%)
m 44
19.6%
1 34
15.2%
0 29
12.9%
2 29
12.9%
c 15
 
6.7%
6 12
 
5.4%
12
 
5.4%
4 10
 
4.5%
9 8
 
3.6%
3 7
 
3.1%
Other values (13) 24
10.7%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%

금액(원)
Real number (ℝ)

Distinct7
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4921.1823
Minimum2000
Maximum15000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-13T08:28:49.936802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2000
Q12000
median5000
Q35000
95-th percentile10000
Maximum15000
Range13000
Interquartile range (IQR)3000

Descriptive statistics

Standard deviation3253.8925
Coefficient of variation (CV)0.66120138
Kurtosis1.9140634
Mean4921.1823
Median Absolute Deviation (MAD)3000
Skewness1.4668852
Sum999000
Variance10587816
MonotonicityNot monotonic
2023-12-13T08:28:50.052912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
5000 56
27.6%
2000 55
27.1%
3000 42
20.7%
8000 25
12.3%
10000 14
 
6.9%
15000 9
 
4.4%
4000 2
 
1.0%
ValueCountFrequency (%)
2000 55
27.1%
3000 42
20.7%
4000 2
 
1.0%
5000 56
27.6%
8000 25
12.3%
10000 14
 
6.9%
15000 9
 
4.4%
ValueCountFrequency (%)
15000 9
 
4.4%
10000 14
 
6.9%
8000 25
12.3%
5000 56
27.6%
4000 2
 
1.0%
3000 42
20.7%
2000 55
27.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-09-30
203 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-30
2nd row2023-09-30
3rd row2023-09-30
4th row2023-09-30
5th row2023-09-30

Common Values

ValueCountFrequency (%)
2023-09-30 203
100.0%

Length

2023-12-13T08:28:50.160102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:28:50.242462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-30 203
100.0%

Interactions

2023-12-13T08:28:48.010707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:28:50.295378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규격금액(원)
규격1.0000.579
금액(원)0.5791.000

Missing values

2023-12-13T08:28:48.155102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:28:48.264497image/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

품명규격금액(원)데이터기준일자
0가스레인지휴대용20002023-09-30
1가스레인지휴대용외30002023-09-30
2가스오븐렌지높이1m미만30002023-09-30
3가스오븐렌지높이1m이상50002023-09-30
4가스히터모든규격50002023-09-30
5가습기모든규격20002023-09-30
6간이화장실상단100002023-09-30
7간이화장실하단150002023-09-30
8간판긴면3m이상150002023-09-30
9간판긴면2m이상3m미만100002023-09-30
품명규격금액(원)데이터기준일자
193피아노모든규격150002023-09-30
194올겐모든규격40002023-09-30
195항아리대형30002023-09-30
196항아리소형20002023-09-30
197화장대모든규격50002023-09-30
198화분소형20002023-09-30
199화분대형30002023-09-30
200환풍기모든규격20002023-09-30
201휠체어모든규격20002023-09-30
202가정배출소량폐물40kg 기준40002023-09-30

Duplicate rows

Most frequently occurring

품명규격금액(원)데이터기준일자# duplicates
0쌀통모든규격20002023-09-302