Overview

Dataset statistics

Number of variables5
Number of observations130
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.5 KiB
Average record size in memory43.0 B

Variable types

Numeric2
Text2
Categorical1

Dataset

Description계양구 대형폐기물 처리 비용에 대한 데이터로 폐유리, 폐가구, 폐가전, 폐악기, 기타물품 등의 수거비용 항목을 공개합니다.
Author인천광역시계양구시설관리공단
URLhttps://www.data.go.kr/data/15012342/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 22:16:43.096023
Analysis finished2023-12-12 22:16:43.926315
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct130
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.3
Minimum1
Maximum131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T07:16:44.016754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.45
Q134.25
median66.5
Q398.75
95-th percentile124.55
Maximum131
Range130
Interquartile range (IQR)64.5

Descriptive statistics

Standard deviation37.951142
Coefficient of variation (CV)0.57241541
Kurtosis-1.1924627
Mean66.3
Median Absolute Deviation (MAD)32.5
Skewness-0.015541716
Sum8619
Variance1440.2891
MonotonicityStrictly increasing
2023-12-13T07:16:44.175532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
100 1
 
0.8%
98 1
 
0.8%
97 1
 
0.8%
96 1
 
0.8%
95 1
 
0.8%
94 1
 
0.8%
93 1
 
0.8%
92 1
 
0.8%
91 1
 
0.8%
Other values (120) 120
92.3%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
131 1
0.8%
130 1
0.8%
129 1
0.8%
128 1
0.8%
127 1
0.8%
126 1
0.8%
125 1
0.8%
124 1
0.8%
123 1
0.8%
122 1
0.8%

품 명
Text

Distinct78
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T07:16:44.425507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.7461538
Min length2

Characters and Unicode

Total characters487
Distinct characters136
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)31.5%

Sample

1st row가스레인지
2nd row가스오븐레인지
3rd row가스오븐레인지
4th row거울
5th row거 울
ValueCountFrequency (%)
침대 5
 
3.6%
소파 4
 
2.9%
책상 4
 
2.9%
식탁(돌/유리 3
 
2.2%
의자 3
 
2.2%
장롱(한쪽당 3
 
2.2%
어항(업소용 3
 
2.2%
제외 3
 
2.2%
액자 3
 
2.2%
항아리 3
 
2.2%
Other values (74) 105
75.5%
2023-12-13T07:16:44.850330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 24
 
4.9%
대 20
 
4.1%
) 16
 
3.3%
( 16
 
3.3%
스 14
 
2.9%
자 14
 
2.9%
리 14
 
2.9%
기 11
 
2.3%
침 11
 
2.3%
판 10
 
2.1%
Other values (126) 337
69.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 438
89.9%
Close Punctuation 16
 
3.3%
Open Punctuation 16
 
3.3%
Space Separator 9
 
1.8%
Other Punctuation 6
 
1.2%
Uppercase Letter 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 24
 
5.5%
대 20
 
4.6%
스 14
 
3.2%
자 14
 
3.2%
리 14
 
3.2%
기 11
 
2.5%
침 11
 
2.5%
판 10
 
2.3%
소 9
 
2.1%
상 9
 
2.1%
Other values (120) 302
68.9%
Uppercase Letter
ValueCountFrequency (%)
V 1
50.0%
T 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 438
89.9%
Common 47
 
9.7%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 24
 
5.5%
대 20
 
4.6%
스 14
 
3.2%
자 14
 
3.2%
리 14
 
3.2%
기 11
 
2.5%
침 11
 
2.5%
판 10
 
2.3%
소 9
 
2.1%
상 9
 
2.1%
Other values (120) 302
68.9%
Common
ValueCountFrequency (%)
) 16
34.0%
( 16
34.0%
9
19.1%
/ 6
 
12.8%
Latin
ValueCountFrequency (%)
V 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 438
89.9%
ASCII 49
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 24
 
5.5%
대 20
 
4.6%
스 14
 
3.2%
자 14
 
3.2%
리 14
 
3.2%
기 11
 
2.5%
침 11
 
2.5%
판 10
 
2.3%
소 9
 
2.1%
상 9
 
2.1%
Other values (120) 302
68.9%
ASCII
ValueCountFrequency (%)
) 16
32.7%
( 16
32.7%
9
18.4%
/ 6
 
12.2%
V 1
 
2.0%
T 1
 
2.0%

규 격
Text

Distinct74
Distinct (%)56.9%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-13T07:16:45.168795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length11
Mean length5.6153846
Min length1

Characters and Unicode

Total characters730
Distinct characters105
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

Unique60 ?
Unique (%)46.2%

Sample

1st row모든 규격
2nd row높이1m 이상
3rd row높이1m 미만
4th row모든 규격(전신 외)
5th row전신거울
ValueCountFrequency (%)
모든 37
16.8%
규격 36
16.4%
이상 18
 
8.2%
미만 16
 
7.3%
이하 6
 
2.7%
2인용 6
 
2.7%
초과 4
 
1.8%
1인용 4
 
1.8%
6인용 3
 
1.4%
가정용 3
 
1.4%
Other values (63) 87
39.5%
2023-12-13T07:16:45.607893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90
 
12.3%
모 37
 
5.1%
격 37
 
5.1%
든 37
 
5.1%
규 37
 
5.1%
용 30
 
4.1%
( 30
 
4.1%
) 30
 
4.1%
이 29
 
4.0%
1 24
 
3.3%
Other values (95) 349
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 445
61.0%
Space Separator 90
 
12.3%
Decimal Number 85
 
11.6%
Lowercase Letter 32
 
4.4%
Open Punctuation 30
 
4.1%
Close Punctuation 30
 
4.1%
Other Punctuation 11
 
1.5%
Other Symbol 7
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
모 37
 
8.3%
격 37
 
8.3%
든 37
 
8.3%
규 37
 
8.3%
용 30
 
6.7%
이 29
 
6.5%
상 23
 
5.2%
인 20
 
4.5%
만 16
 
3.6%
미 16
 
3.6%
Other values (77) 163
36.6%
Decimal Number
ValueCountFrequency (%)
1 24
28.2%
2 13
15.3%
0 12
14.1%
5 12
14.1%
3 11
12.9%
9 6
 
7.1%
4 4
 
4.7%
6 3
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
m 23
71.9%
k 3
 
9.4%
g 3
 
9.4%
c 3
 
9.4%
Other Punctuation
ValueCountFrequency (%)
. 8
72.7%
, 3
 
27.3%
Space Separator
ValueCountFrequency (%)
90
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Other Symbol
ValueCountFrequency (%)
㎝ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 445
61.0%
Common 253
34.7%
Latin 32
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
모 37
 
8.3%
격 37
 
8.3%
든 37
 
8.3%
규 37
 
8.3%
용 30
 
6.7%
이 29
 
6.5%
상 23
 
5.2%
인 20
 
4.5%
만 16
 
3.6%
미 16
 
3.6%
Other values (77) 163
36.6%
Common
ValueCountFrequency (%)
90
35.6%
( 30
 
11.9%
) 30
 
11.9%
1 24
 
9.5%
2 13
 
5.1%
0 12
 
4.7%
5 12
 
4.7%
3 11
 
4.3%
. 8
 
3.2%
㎝ 7
 
2.8%
Other values (4) 16
 
6.3%
Latin
ValueCountFrequency (%)
m 23
71.9%
k 3
 
9.4%
g 3
 
9.4%
c 3
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 445
61.0%
ASCII 278
38.1%
CJK Compat 7
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
90
32.4%
( 30
 
10.8%
) 30
 
10.8%
1 24
 
8.6%
m 23
 
8.3%
2 13
 
4.7%
0 12
 
4.3%
5 12
 
4.3%
3 11
 
4.0%
. 8
 
2.9%
Other values (7) 25
 
9.0%
Hangul
ValueCountFrequency (%)
모 37
 
8.3%
격 37
 
8.3%
든 37
 
8.3%
규 37
 
8.3%
용 30
 
6.7%
이 29
 
6.5%
상 23
 
5.2%
인 20
 
4.5%
만 16
 
3.6%
미 16
 
3.6%
Other values (77) 163
36.6%
CJK Compat
ValueCountFrequency (%)
㎝ 7
100.0%

금 액
Real number (ℝ)

Distinct13
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5446.1538
Minimum1000
Maximum20000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T07:16:45.755845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile2000
Q13000
median5000
Q36750
95-th percentile12000
Maximum20000
Range19000
Interquartile range (IQR)3750

Descriptive statistics

Standard deviation3710.5789
Coefficient of variation (CV)0.68132099
Kurtosis4.3800989
Mean5446.1538
Median Absolute Deviation (MAD)2000
Skewness1.9135584
Sum708000
Variance13768396
MonotonicityNot monotonic
2023-12-13T07:16:45.880618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
5000 33
25.4%
3000 23
17.7%
2000 18
13.8%
4000 17
13.1%
10000 13
 
10.0%
7000 8
 
6.2%
1000 3
 
2.3%
6000 3
 
2.3%
20000 3
 
2.3%
15000 3
 
2.3%
Other values (3) 6
 
4.6%
ValueCountFrequency (%)
1000 3
 
2.3%
2000 18
13.8%
3000 23
17.7%
4000 17
13.1%
5000 33
25.4%
6000 3
 
2.3%
7000 8
 
6.2%
8000 2
 
1.5%
9000 2
 
1.5%
10000 13
 
10.0%
ValueCountFrequency (%)
20000 3
 
2.3%
15000 3
 
2.3%
12000 2
 
1.5%
10000 13
 
10.0%
9000 2
 
1.5%
8000 2
 
1.5%
7000 8
 
6.2%
6000 3
 
2.3%
5000 33
25.4%
4000 17
13.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2021-03-01
130 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-03-01
2nd row2021-03-01
3rd row2021-03-01
4th row2021-03-01
5th row2021-03-01

Common Values

ValueCountFrequency (%)
2021-03-01 130
100.0%

Length

2023-12-13T07:16:46.039737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:16:46.176903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-03-01 130
100.0%

Interactions

2023-12-13T07:16:43.558184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:16:43.358137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:16:43.653232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:16:43.465775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:16:46.243690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번품 명규 격금 액
연번1.0000.9990.7540.322
품 명0.9991.0000.0000.000
규 격0.7540.0001.0000.856
금 액0.3220.0000.8561.000
2023-12-13T07:16:46.345800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번금 액
연번1.0000.287
금 액0.2871.000

Missing values

2023-12-13T07:16:43.786592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:16:43.888286image/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

연번품 명규 격금 액데이터기준일자
01가스레인지모든 규격20002021-03-01
12가스오븐레인지높이1m 이상40002021-03-01
23가스오븐레인지높이1m 미만20002021-03-01
34거울모든 규격(전신 외)20002021-03-01
45거 울전신거울50002021-03-01
56거실장앞문3쪽70002021-03-01
67거실장앞문2쪽50002021-03-01
78건조대모든 규격20002021-03-01
89고무통모든 규격20002021-03-01
910고양이 타워모든 규격50002021-03-01
연번품 명규 격금 액데이터기준일자
120122행거모든 규격30002021-03-01
121123헬스기구업소용100002021-03-01
122124헬스기구가정용50002021-03-01
123125협탁모든 규격30002021-03-01
124126화장대가정용50002021-03-01
125127화장대업소용100002021-03-01
126128자석/옥 장판2인용100002021-03-01
127129자석/옥 장판1인용70002021-03-01
128130소화기3.3kg 이하30002021-03-01
129131소화기3.3kg 초과 20kg 이하50002021-03-01