Overview

Dataset statistics

Number of variables6
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory51.2 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description경상남도 의령군의 쓰레기분리수거장의 정보를 제공하는 데이터 입니다.
Author경상남도 의령군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15099961

Alerts

데이터기준일 has constant value ""Constant
구분 is highly overall correlated with 읍_면High correlation
읍_면 is highly overall correlated with 구분High correlation
구분 has unique valuesUnique
설치장소 has unique valuesUnique
세부위치 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:04:00.188458
Analysis finished2024-04-06 08:04:01.438050
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.5
Minimum1
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2024-04-06T17:04:01.664592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.95
Q115.75
median30.5
Q345.25
95-th percentile57.05
Maximum60
Range59
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation17.464249
Coefficient of variation (CV)0.57259833
Kurtosis-1.2
Mean30.5
Median Absolute Deviation (MAD)15
Skewness0
Sum1830
Variance305
MonotonicityStrictly increasing
2024-04-06T17:04:01.938378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.7%
32 1
 
1.7%
34 1
 
1.7%
35 1
 
1.7%
36 1
 
1.7%
37 1
 
1.7%
38 1
 
1.7%
39 1
 
1.7%
40 1
 
1.7%
41 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
1 1
1.7%
2 1
1.7%
3 1
1.7%
4 1
1.7%
5 1
1.7%
6 1
1.7%
7 1
1.7%
8 1
1.7%
9 1
1.7%
10 1
1.7%
ValueCountFrequency (%)
60 1
1.7%
59 1
1.7%
58 1
1.7%
57 1
1.7%
56 1
1.7%
55 1
1.7%
54 1
1.7%
53 1
1.7%
52 1
1.7%
51 1
1.7%

읍_면
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
의령읍
14 
지정면
7 
대의면
5 
부림면
5 
용덕면
5 
Other values (8)
24 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)1.7%

Sample

1st row가례면
2nd row가례면
3rd row가례면
4th row가례면
5th row궁류면

Common Values

ValueCountFrequency (%)
의령읍 14
23.3%
지정면 7
11.7%
대의면 5
 
8.3%
부림면 5
 
8.3%
용덕면 5
 
8.3%
가례면 4
 
6.7%
궁류면 4
 
6.7%
봉수면 4
 
6.7%
정곡면 4
 
6.7%
칠곡면 3
 
5.0%
Other values (3) 5
 
8.3%

Length

2024-04-06T17:04:02.201713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
의령읍 14
23.3%
지정면 7
11.7%
대의면 5
 
8.3%
부림면 5
 
8.3%
용덕면 5
 
8.3%
가례면 4
 
6.7%
궁류면 4
 
6.7%
봉수면 4
 
6.7%
정곡면 4
 
6.7%
칠곡면 3
 
5.0%
Other values (3) 5
 
8.3%

마을명
Text

Distinct54
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-04-06T17:04:02.608770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.05
Min length2

Characters and Unicode

Total characters123
Distinct characters66
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

Unique48 ?
Unique (%)80.0%

Sample

1st row갑을
2nd row가례
3rd row양성
4th row평촌
5th row토곡
ValueCountFrequency (%)
서본 2
 
3.3%
행복 2
 
3.3%
신기 2
 
3.3%
중촌 2
 
3.3%
평촌 2
 
3.3%
서신 2
 
3.3%
문곡 1
 
1.7%
갑을 1
 
1.7%
무곡 1
 
1.7%
무중 1
 
1.7%
Other values (44) 44
73.3%
2024-04-06T17:04:03.299030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
신 9
 
7.3%
촌 6
 
4.9%
서 5
 
4.1%
구 4
 
3.3%
암 4
 
3.3%
곡 4
 
3.3%
산 4
 
3.3%
성 4
 
3.3%
중 4
 
3.3%
무 4
 
3.3%
Other values (56) 75
61.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 122
99.2%
Decimal Number 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
신 9
 
7.4%
촌 6
 
4.9%
서 5
 
4.1%
구 4
 
3.3%
암 4
 
3.3%
곡 4
 
3.3%
산 4
 
3.3%
성 4
 
3.3%
중 4
 
3.3%
무 4
 
3.3%
Other values (55) 74
60.7%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 122
99.2%
Common 1
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
신 9
 
7.4%
촌 6
 
4.9%
서 5
 
4.1%
구 4
 
3.3%
암 4
 
3.3%
곡 4
 
3.3%
산 4
 
3.3%
성 4
 
3.3%
중 4
 
3.3%
무 4
 
3.3%
Other values (55) 74
60.7%
Common
ValueCountFrequency (%)
1 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 122
99.2%
ASCII 1
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
신 9
 
7.4%
촌 6
 
4.9%
서 5
 
4.1%
구 4
 
3.3%
암 4
 
3.3%
곡 4
 
3.3%
산 4
 
3.3%
성 4
 
3.3%
중 4
 
3.3%
무 4
 
3.3%
Other values (55) 74
60.7%
ASCII
ValueCountFrequency (%)
1 1
100.0%

설치장소
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-04-06T17:04:03.895086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14.5
Mean length12.433333
Min length9

Characters and Unicode

Total characters746
Distinct characters93
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row가례면 갑을리 243-2
2nd row가례면 가례리 443
3rd row가례면 양성리 619-8
4th row가례면 운암리 200-27
5th row궁류면 토곡리 823
ValueCountFrequency (%)
의령읍 12
 
6.8%
지정면 7
 
4.0%
용덕면 5
 
2.8%
부림면 5
 
2.8%
대의면 5
 
2.8%
가례면 4
 
2.3%
궁류면 4
 
2.3%
봉수면 4
 
2.3%
정곡면 4
 
2.3%
칠곡면 3
 
1.7%
Other values (109) 123
69.9%
2024-04-06T17:04:04.650180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116
 
15.5%
리 50
 
6.7%
1 47
 
6.3%
면 46
 
6.2%
- 44
 
5.9%
2 27
 
3.6%
4 26
 
3.5%
5 25
 
3.4%
의 23
 
3.1%
7 22
 
2.9%
Other values (83) 320
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 359
48.1%
Decimal Number 227
30.4%
Space Separator 116
 
15.5%
Dash Punctuation 44
 
5.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 50
 
13.9%
면 46
 
12.8%
의 23
 
6.4%
곡 15
 
4.2%
정 13
 
3.6%
령 12
 
3.3%
읍 12
 
3.3%
로 9
 
2.5%
지 9
 
2.5%
산 7
 
1.9%
Other values (71) 163
45.4%
Decimal Number
ValueCountFrequency (%)
1 47
20.7%
2 27
11.9%
4 26
11.5%
5 25
11.0%
7 22
9.7%
3 19
8.4%
9 18
 
7.9%
6 17
 
7.5%
0 14
 
6.2%
8 12
 
5.3%
Space Separator
ValueCountFrequency (%)
116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 387
51.9%
Hangul 359
48.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 50
 
13.9%
면 46
 
12.8%
의 23
 
6.4%
곡 15
 
4.2%
정 13
 
3.6%
령 12
 
3.3%
읍 12
 
3.3%
로 9
 
2.5%
지 9
 
2.5%
산 7
 
1.9%
Other values (71) 163
45.4%
Common
ValueCountFrequency (%)
116
30.0%
1 47
12.1%
- 44
 
11.4%
2 27
 
7.0%
4 26
 
6.7%
5 25
 
6.5%
7 22
 
5.7%
3 19
 
4.9%
9 18
 
4.7%
6 17
 
4.4%
Other values (2) 26
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 387
51.9%
Hangul 359
48.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
116
30.0%
1 47
12.1%
- 44
 
11.4%
2 27
 
7.0%
4 26
 
6.7%
5 25
 
6.5%
7 22
 
5.7%
3 19
 
4.9%
9 18
 
4.7%
6 17
 
4.4%
Other values (2) 26
 
6.7%
Hangul
ValueCountFrequency (%)
리 50
 
13.9%
면 46
 
12.8%
의 23
 
6.4%
곡 15
 
4.2%
정 13
 
3.6%
령 12
 
3.3%
읍 12
 
3.3%
로 9
 
2.5%
지 9
 
2.5%
산 7
 
1.9%
Other values (71) 163
45.4%

세부위치
Text

UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size612.0 B
2024-04-06T17:04:05.246725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10.5
Mean length8
Min length4

Characters and Unicode

Total characters480
Distinct characters115
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)100.0%

Sample

1st row갑을마을 주차장
2nd row가례마을 공터
3rd row양성마을 버스승강장 근처
4th row평촌마을 주차장
5th row토곡마을회관
ValueCountFrequency (%)
근처 13
 
12.7%
도로변 9
 
8.8%
주차장 9
 
8.8%
버스승강장 3
 
2.9%
입구 2
 
2.0%
의령동동엘에이치 1
 
1.0%
무하마을 1
 
1.0%
농공단지사무국협의회 1
 
1.0%
수암마을회관 1
 
1.0%
무중마을 1
 
1.0%
Other values (61) 61
59.8%
2024-04-06T17:04:06.130082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
을 43
 
9.0%
마 42
 
8.8%
42
 
8.8%
회 24
 
5.0%
관 24
 
5.0%
장 13
 
2.7%
처 13
 
2.7%
로 13
 
2.7%
근 13
 
2.7%
주 11
 
2.3%
Other values (105) 242
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 436
90.8%
Space Separator 42
 
8.8%
Decimal Number 1
 
0.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
을 43
 
9.9%
마 42
 
9.6%
회 24
 
5.5%
관 24
 
5.5%
장 13
 
3.0%
처 13
 
3.0%
로 13
 
3.0%
근 13
 
3.0%
주 11
 
2.5%
차 10
 
2.3%
Other values (102) 230
52.8%
Space Separator
ValueCountFrequency (%)
42
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 436
90.8%
Common 44
 
9.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
을 43
 
9.9%
마 42
 
9.6%
회 24
 
5.5%
관 24
 
5.5%
장 13
 
3.0%
처 13
 
3.0%
로 13
 
3.0%
근 13
 
3.0%
주 11
 
2.5%
차 10
 
2.3%
Other values (102) 230
52.8%
Common
ValueCountFrequency (%)
42
95.5%
1 1
 
2.3%
- 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 436
90.8%
ASCII 44
 
9.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
을 43
 
9.9%
마 42
 
9.6%
회 24
 
5.5%
관 24
 
5.5%
장 13
 
3.0%
처 13
 
3.0%
로 13
 
3.0%
근 13
 
3.0%
주 11
 
2.5%
차 10
 
2.3%
Other values (102) 230
52.8%
ASCII
ValueCountFrequency (%)
42
95.5%
1 1
 
2.3%
- 1
 
2.3%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size612.0 B
2022-04-25
60 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-04-25
2nd row2022-04-25
3rd row2022-04-25
4th row2022-04-25
5th row2022-04-25

Common Values

ValueCountFrequency (%)
2022-04-25 60
100.0%

Length

2024-04-06T17:04:06.419566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:04:06.599468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-04-25 60
100.0%

Interactions

2024-04-06T17:04:00.919569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:04:07.079082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분읍_면마을명설치장소세부위치
구분1.0000.9230.9521.0001.000
읍_면0.9231.0000.9331.0001.000
마을명0.9520.9331.0001.0001.000
설치장소1.0001.0001.0001.0001.000
세부위치1.0001.0001.0001.0001.000
2024-04-06T17:04:07.255127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분읍_면
구분1.0000.705
읍_면0.7051.000

Missing values

2024-04-06T17:04:01.175261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:04:01.363741image/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

구분읍_면마을명설치장소세부위치데이터기준일
01가례면갑을가례면 갑을리 243-2갑을마을 주차장2022-04-25
12가례면가례가례면 가례리 443가례마을 공터2022-04-25
23가례면양성가례면 양성리 619-8양성마을 버스승강장 근처2022-04-25
34가례면평촌가례면 운암리 200-27평촌마을 주차장2022-04-25
45궁류면토곡궁류면 토곡리 823토곡마을회관2022-04-25
56궁류면계현1구궁류면 계현리 274-9계현1리마을회관2022-04-25
67궁류면석정궁류면 토곡리 591-27석정마을회관2022-04-25
78궁류면평촌궁류면 평촌리 491평촌경로당2022-04-25
89낙서면신기낙서면 정곡리 141-1신기마을 주차장2022-04-25
910낙서면율산낙서면 율산리 464-1율산마을회관2022-04-25
구분읍_면마을명설치장소세부위치데이터기준일
5051지정면태부지정면 태부리 843-1태부마을회관2022-04-25
5152지정면백산지정면 유곡리 280백산농기계창고 근처2022-04-25
5253지정면성당지정면 성당리 586-2성당보건진료소 근처2022-04-25
5354지정면신암지정면 함의로10길 7신정마을 공영주차장2022-04-25
5455지정면나림지정면 봉곡리763-1나림마을회관 근처2022-04-25
5556지정면포외지정면 마산리574-5포외경로당2022-04-25
5657칠곡면입암칠곡면 신포리 739-2마을입구 주차장 쪽2022-04-25
5758칠곡면죽공칠곡면 산북리 549-1죽공마을복지회관2022-04-25
5859칠곡면중촌칠곡면 외조리 206-1중촌마을회관2022-04-25
5960화정면유수화정면 진의4길 139유수마을회관2022-04-25