Overview

Dataset statistics

Number of variables7
Number of observations128
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.4 KiB
Average record size in memory59.0 B

Variable types

Numeric1
Text3
Categorical3

Dataset

Description충청북도 단양군 공공데이터 제공 목록으로 단양군 내 헌옷수거함에 대한 연번, 관리번호, 위치, 도로명주소, 비고(색상, 소재 등)으로 목록 구성
Author충청북도 단양군
URLhttps://www.data.go.kr/data/15127282/fileData.do

Alerts

관리상태 has constant value ""Constant
설치년도 is highly overall correlated with 비고High correlation
비고 is highly overall correlated with 설치년도High correlation
설치년도 is highly imbalanced (84.0%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-23 06:04:07.234052
Analysis finished2024-03-23 06:04:09.830484
Duration2.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct128
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.5
Minimum1
Maximum128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-23T06:04:10.124569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.35
Q132.75
median64.5
Q396.25
95-th percentile121.65
Maximum128
Range127
Interquartile range (IQR)63.5

Descriptive statistics

Standard deviation37.094474
Coefficient of variation (CV)0.57510812
Kurtosis-1.2
Mean64.5
Median Absolute Deviation (MAD)32
Skewness0
Sum8256
Variance1376
MonotonicityStrictly increasing
2024-03-23T06:04:10.790156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
66 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%
90 1
 
0.8%
89 1
 
0.8%
Other values (118) 118
92.2%
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 (%)
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%
121 1
0.8%
120 1
0.8%
119 1
0.8%

관리번호
Text

Distinct121
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-23T06:04:11.653672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4.5
Mean length4.453125
Min length3

Characters and Unicode

Total characters570
Distinct characters30
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

Unique117 ?
Unique (%)91.4%

Sample

1st row단양읍1
2nd row단양읍2
3rd row단양읍3
4th row단양읍4
5th row단양읍5
ValueCountFrequency (%)
단성면5 3
 
2.3%
단성면6 3
 
2.3%
단성면7 3
 
2.3%
단성면9 2
 
1.6%
대강면2 1
 
0.8%
단성면1 1
 
0.8%
단성면2 1
 
0.8%
단성면3 1
 
0.8%
단성면4 1
 
0.8%
대강면1 1
 
0.8%
Other values (111) 111
86.7%
2024-03-23T06:04:13.070761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
읍 64
 
11.2%
1 50
 
8.8%
단 48
 
8.4%
면 48
 
8.4%
2 35
 
6.1%
양 33
 
5.8%
포 31
 
5.4%
매 31
 
5.4%
3 21
 
3.7%
대 19
 
3.3%
Other values (20) 190
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 382
67.0%
Decimal Number 188
33.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
읍 64
16.8%
단 48
12.6%
면 48
12.6%
양 33
8.6%
포 31
8.1%
매 31
8.1%
대 19
 
5.0%
강 19
 
5.0%
성 15
 
3.9%
트 13
 
3.4%
Other values (10) 61
16.0%
Decimal Number
ValueCountFrequency (%)
1 50
26.6%
2 35
18.6%
3 21
11.2%
6 14
 
7.4%
7 14
 
7.4%
5 14
 
7.4%
4 12
 
6.4%
9 11
 
5.9%
8 9
 
4.8%
0 8
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 382
67.0%
Common 188
33.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
읍 64
16.8%
단 48
12.6%
면 48
12.6%
양 33
8.6%
포 31
8.1%
매 31
8.1%
대 19
 
5.0%
강 19
 
5.0%
성 15
 
3.9%
트 13
 
3.4%
Other values (10) 61
16.0%
Common
ValueCountFrequency (%)
1 50
26.6%
2 35
18.6%
3 21
11.2%
6 14
 
7.4%
7 14
 
7.4%
5 14
 
7.4%
4 12
 
6.4%
9 11
 
5.9%
8 9
 
4.8%
0 8
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 382
67.0%
ASCII 188
33.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
읍 64
16.8%
단 48
12.6%
면 48
12.6%
양 33
8.6%
포 31
8.1%
매 31
8.1%
대 19
 
5.0%
강 19
 
5.0%
성 15
 
3.9%
트 13
 
3.4%
Other values (10) 61
16.0%
ASCII
ValueCountFrequency (%)
1 50
26.6%
2 35
18.6%
3 21
11.2%
6 14
 
7.4%
7 14
 
7.4%
5 14
 
7.4%
4 12
 
6.4%
9 11
 
5.9%
8 9
 
4.8%
0 8
 
4.3%

설치장소
Text

Distinct120
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-23T06:04:13.883215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length8.4609375
Min length2

Characters and Unicode

Total characters1083
Distinct characters183
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)88.3%

Sample

1st row마운틴뷰 39-6
2nd row삼봉캐슬 39-14
3rd row도담 에코빌
4th row별곡 1길 11
5th row별곡1길 18
ValueCountFrequency (%)
앞 8
 
3.0%
마을회관 7
 
2.6%
평동 6
 
2.2%
두음 5
 
1.9%
군청로 4
 
1.5%
코너 4
 
1.5%
태양드림아파트 3
 
1.1%
옆 3
 
1.1%
놀이터 3
 
1.1%
도전 3
 
1.1%
Other values (188) 222
82.8%
2024-03-23T06:04:15.667978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
141
 
13.0%
1 53
 
4.9%
길 43
 
4.0%
앞 30
 
2.8%
동 22
 
2.0%
평 22
 
2.0%
2 20
 
1.8%
아 20
 
1.8%
상 19
 
1.8%
파 18
 
1.7%
Other values (173) 695
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 759
70.1%
Decimal Number 152
 
14.0%
Space Separator 141
 
13.0%
Close Punctuation 12
 
1.1%
Open Punctuation 12
 
1.1%
Dash Punctuation 6
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 43
 
5.7%
앞 30
 
4.0%
동 22
 
2.9%
평 22
 
2.9%
아 20
 
2.6%
상 19
 
2.5%
파 18
 
2.4%
트 18
 
2.4%
로 17
 
2.2%
리 16
 
2.1%
Other values (158) 534
70.4%
Decimal Number
ValueCountFrequency (%)
1 53
34.9%
2 20
 
13.2%
3 16
 
10.5%
4 15
 
9.9%
6 10
 
6.6%
9 9
 
5.9%
5 8
 
5.3%
7 8
 
5.3%
0 7
 
4.6%
8 6
 
3.9%
Space Separator
ValueCountFrequency (%)
141
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 759
70.1%
Common 324
29.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 43
 
5.7%
앞 30
 
4.0%
동 22
 
2.9%
평 22
 
2.9%
아 20
 
2.6%
상 19
 
2.5%
파 18
 
2.4%
트 18
 
2.4%
로 17
 
2.2%
리 16
 
2.1%
Other values (158) 534
70.4%
Common
ValueCountFrequency (%)
141
43.5%
1 53
 
16.4%
2 20
 
6.2%
3 16
 
4.9%
4 15
 
4.6%
) 12
 
3.7%
( 12
 
3.7%
6 10
 
3.1%
9 9
 
2.8%
5 8
 
2.5%
Other values (5) 28
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 759
70.1%
ASCII 324
29.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
141
43.5%
1 53
 
16.4%
2 20
 
6.2%
3 16
 
4.9%
4 15
 
4.6%
) 12
 
3.7%
( 12
 
3.7%
6 10
 
3.1%
9 9
 
2.8%
5 8
 
2.5%
Other values (5) 28
 
8.6%
Hangul
ValueCountFrequency (%)
길 43
 
5.7%
앞 30
 
4.0%
동 22
 
2.9%
평 22
 
2.9%
아 20
 
2.6%
상 19
 
2.5%
파 18
 
2.4%
트 18
 
2.4%
로 17
 
2.2%
리 16
 
2.1%
Other values (158) 534
70.4%

주소
Text

Distinct119
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-23T06:04:16.628149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length27
Mean length20.882812
Min length6

Characters and Unicode

Total characters2673
Distinct characters130
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)87.5%

Sample

1st row충청북도 단양군 단양읍 별곡3로 39-6
2nd row충청북도 단양군 단양읍 별곡3로 39-10 신성단양미소지움(상가)
3rd row충청북도 단양군 단양읍 별곡리 106-34
4th row충청북도 단양군 단양읍 별곡 1길 11
5th row충청북도 단양군 단양읍 별곡 1길 18
ValueCountFrequency (%)
충청북도 125
19.6%
단양군 125
19.6%
단양읍 41
 
6.4%
매포읍 35
 
5.5%
대강면 19
 
3.0%
단성면 15
 
2.4%
가곡면 7
 
1.1%
상진리 7
 
1.1%
평동리 5
 
0.8%
영춘면 5
 
0.8%
Other values (189) 254
39.8%
2024-03-23T06:04:18.595329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
510
19.1%
단 184
 
6.9%
양 170
 
6.4%
북 132
 
4.9%
도 132
 
4.9%
군 128
 
4.8%
청 128
 
4.8%
충 126
 
4.7%
1 103
 
3.9%
읍 77
 
2.9%
Other values (120) 983
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1746
65.3%
Space Separator 510
 
19.1%
Decimal Number 375
 
14.0%
Dash Punctuation 30
 
1.1%
Close Punctuation 5
 
0.2%
Open Punctuation 5
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
단 184
 
10.5%
양 170
 
9.7%
북 132
 
7.6%
도 132
 
7.6%
군 128
 
7.3%
청 128
 
7.3%
충 126
 
7.2%
읍 77
 
4.4%
길 64
 
3.7%
면 48
 
2.7%
Other values (105) 557
31.9%
Decimal Number
ValueCountFrequency (%)
1 103
27.5%
3 50
13.3%
2 45
12.0%
5 35
 
9.3%
4 29
 
7.7%
6 25
 
6.7%
0 24
 
6.4%
7 24
 
6.4%
9 22
 
5.9%
8 18
 
4.8%
Space Separator
ValueCountFrequency (%)
510
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
? 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1746
65.3%
Common 927
34.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
단 184
 
10.5%
양 170
 
9.7%
북 132
 
7.6%
도 132
 
7.6%
군 128
 
7.3%
청 128
 
7.3%
충 126
 
7.2%
읍 77
 
4.4%
길 64
 
3.7%
면 48
 
2.7%
Other values (105) 557
31.9%
Common
ValueCountFrequency (%)
510
55.0%
1 103
 
11.1%
3 50
 
5.4%
2 45
 
4.9%
5 35
 
3.8%
- 30
 
3.2%
4 29
 
3.1%
6 25
 
2.7%
0 24
 
2.6%
7 24
 
2.6%
Other values (5) 52
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1746
65.3%
ASCII 927
34.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
510
55.0%
1 103
 
11.1%
3 50
 
5.4%
2 45
 
4.9%
5 35
 
3.8%
- 30
 
3.2%
4 29
 
3.1%
6 25
 
2.7%
0 24
 
2.6%
7 24
 
2.6%
Other values (5) 52
 
5.6%
Hangul
ValueCountFrequency (%)
단 184
 
10.5%
양 170
 
9.7%
북 132
 
7.6%
도 132
 
7.6%
군 128
 
7.3%
청 128
 
7.3%
충 126
 
7.2%
읍 77
 
4.4%
길 64
 
3.7%
면 48
 
2.7%
Other values (105) 557
31.9%

설치년도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2007
125 
2012
 
3

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2012
2nd row2012
3rd row2012
4th row2007
5th row2007

Common Values

ValueCountFrequency (%)
2007 125
97.7%
2012 3
 
2.3%

Length

2024-03-23T06:04:19.088641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:04:19.387987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2007 125
97.7%
2012 3
 
2.3%

관리상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
양호
128 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
양호 128
100.0%

Length

2024-03-23T06:04:19.931478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:04:20.215894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양호 128
100.0%

비고
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
검정색
95 
파란색
32 
초록철통
 
1

Length

Max length4
Median length3
Mean length3.0078125
Min length3

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row파란색
2nd row초록철통
3rd row검정색
4th row파란색
5th row검정색

Common Values

ValueCountFrequency (%)
검정색 95
74.2%
파란색 32
 
25.0%
초록철통 1
 
0.8%

Length

2024-03-23T06:04:20.761153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:04:21.198307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검정색 95
74.2%
파란색 32
 
25.0%
초록철통 1
 
0.8%

Interactions

2024-03-23T06:04:08.308495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T06:04:21.445254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치년도비고
연번1.0000.5070.448
설치년도0.5071.0000.355
비고0.4480.3551.000
2024-03-23T06:04:21.815987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도비고
설치년도1.0000.564
비고0.5641.000
2024-03-23T06:04:22.079503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치년도비고
연번1.0000.3780.293
설치년도0.3781.0000.564
비고0.2930.5641.000

Missing values

2024-03-23T06:04:08.857257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T06:04:09.624526image/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

연번관리번호설치장소주소설치년도관리상태비고
01단양읍1마운틴뷰 39-6충청북도 단양군 단양읍 별곡3로 39-62012양호파란색
12단양읍2삼봉캐슬 39-14충청북도 단양군 단양읍 별곡3로 39-10 신성단양미소지움(상가)2012양호초록철통
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