Overview

Dataset statistics

Number of variables4
Number of observations132
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory34.0 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description남원시에서 관리하는 폐의류수거함 설치 현황으로, 소재지, 주소, 관리번호가 제공됨(2024.2.1.기준 데이터)
Author전북특별자치도 남원시
URLhttps://www.data.go.kr/data/15127123/fileData.do

Alerts

연 번 is highly overall correlated with 읍면동High correlation
읍면동 is highly overall correlated with 연 번High correlation
연 번 has unique valuesUnique
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-03-23 03:58:44.853031
Analysis finished2024-03-23 03:58:46.702847
Duration1.85 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연 번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct132
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.5
Minimum1
Maximum132
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-23T03:58:47.245585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.55
Q133.75
median66.5
Q399.25
95-th percentile125.45
Maximum132
Range131
Interquartile range (IQR)65.5

Descriptive statistics

Standard deviation38.249183
Coefficient of variation (CV)0.57517568
Kurtosis-1.2
Mean66.5
Median Absolute Deviation (MAD)33
Skewness0
Sum8778
Variance1463
MonotonicityStrictly increasing
2024-03-23T03:58:48.459585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
85 1
 
0.8%
99 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%
Other values (122) 122
92.4%
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 (%)
132 1
0.8%
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%

읍면동
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
향교동
29 
도통동
17 
죽항동
15 
동충동
12 
왕정동
12 
Other values (13)
47 

Length

Max length3
Median length3
Mean length2.9242424
Min length2

Unique

Unique2 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
향교동 29
22.0%
도통동 17
12.9%
죽항동 15
11.4%
동충동 12
9.1%
왕정동 12
9.1%
금동 10
 
7.6%
노암동 9
 
6.8%
운봉읍 4
 
3.0%
이백면 4
 
3.0%
주생면 4
 
3.0%
Other values (8) 16
12.1%

Length

2024-03-23T03:58:49.192339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
향교동 29
22.0%
도통동 17
12.9%
죽항동 15
11.4%
동충동 12
9.1%
왕정동 12
9.1%
금동 10
 
7.6%
노암동 9
 
6.8%
이백면 4
 
3.0%
주생면 4
 
3.0%
운봉읍 4
 
3.0%
Other values (8) 16
12.1%

주 소
Text

Distinct129
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-23T03:58:50.162904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length10.886364
Min length6

Characters and Unicode

Total characters1437
Distinct characters133
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

Unique126 ?
Unique (%)95.5%

Sample

1st row동충동 486-1
2nd row동충동 396-1
3rd row동충동 486-1
4th row?동충동 251-9
5th row동충동 483
ValueCountFrequency (%)
향교동 21
 
7.3%
도통동 13
 
4.5%
옆 12
 
4.2%
왕정동 9
 
3.1%
동충동 9
 
3.1%
앞 7
 
2.4%
노암동 5
 
1.7%
조산동 5
 
1.7%
쓰레기집하장 4
 
1.4%
집하장 3
 
1.0%
Other values (186) 199
69.3%
2024-03-23T03:58:51.473340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
156
 
10.9%
1 101
 
7.0%
동 96
 
6.7%
- 75
 
5.2%
2 75
 
5.2%
4 44
 
3.1%
3 44
 
3.1%
0 37
 
2.6%
6 37
 
2.6%
5 36
 
2.5%
Other values (123) 736
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 674
46.9%
Decimal Number 463
32.2%
Space Separator 156
 
10.9%
Dash Punctuation 75
 
5.2%
Close Punctuation 34
 
2.4%
Open Punctuation 34
 
2.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 96
 
14.2%
길 35
 
5.2%
마 31
 
4.6%
을 30
 
4.5%
회 25
 
3.7%
관 25
 
3.7%
교 24
 
3.6%
향 23
 
3.4%
정 22
 
3.3%
산 19
 
2.8%
Other values (108) 344
51.0%
Decimal Number
ValueCountFrequency (%)
1 101
21.8%
2 75
16.2%
4 44
9.5%
3 44
9.5%
0 37
 
8.0%
6 37
 
8.0%
5 36
 
7.8%
7 32
 
6.9%
9 31
 
6.7%
8 26
 
5.6%
Space Separator
ValueCountFrequency (%)
156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Other Punctuation
ValueCountFrequency (%)
? 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 763
53.1%
Hangul 674
46.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 96
 
14.2%
길 35
 
5.2%
마 31
 
4.6%
을 30
 
4.5%
회 25
 
3.7%
관 25
 
3.7%
교 24
 
3.6%
향 23
 
3.4%
정 22
 
3.3%
산 19
 
2.8%
Other values (108) 344
51.0%
Common
ValueCountFrequency (%)
156
20.4%
1 101
13.2%
- 75
9.8%
2 75
9.8%
4 44
 
5.8%
3 44
 
5.8%
0 37
 
4.8%
6 37
 
4.8%
5 36
 
4.7%
) 34
 
4.5%
Other values (5) 124
16.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 763
53.1%
Hangul 674
46.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
156
20.4%
1 101
13.2%
- 75
9.8%
2 75
9.8%
4 44
 
5.8%
3 44
 
5.8%
0 37
 
4.8%
6 37
 
4.8%
5 36
 
4.7%
) 34
 
4.5%
Other values (5) 124
16.3%
Hangul
ValueCountFrequency (%)
동 96
 
14.2%
길 35
 
5.2%
마 31
 
4.6%
을 30
 
4.5%
회 25
 
3.7%
관 25
 
3.7%
교 24
 
3.6%
향 23
 
3.4%
정 22
 
3.3%
산 19
 
2.8%
Other values (108) 344
51.0%

관리번호
Text

UNIQUE 

Distinct132
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-03-23T03:58:52.531984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0984848
Min length5

Characters and Unicode

Total characters805
Distinct characters42
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique132 ?
Unique (%)100.0%

Sample

1st row동충-101
2nd row동충-102
3rd row동충-103
4th row동충-104
5th row동충-105
ValueCountFrequency (%)
동충-101 1
 
0.8%
향교-625 1
 
0.8%
도통-711 1
 
0.8%
도통-710 1
 
0.8%
도통-709 1
 
0.8%
도통-708 1
 
0.8%
도통-707 1
 
0.8%
도통-706 1
 
0.8%
도통-705 1
 
0.8%
도통-704 1
 
0.8%
Other values (122) 122
92.4%
2024-03-23T03:58:54.501600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 132
16.4%
0 102
12.7%
1 85
 
10.6%
2 62
 
7.7%
6 42
 
5.2%
교 29
 
3.6%
향 29
 
3.6%
3 27
 
3.4%
7 27
 
3.4%
4 26
 
3.2%
Other values (32) 244
30.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 419
52.0%
Other Letter 254
31.6%
Dash Punctuation 132
 
16.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 29
 
11.4%
향 29
 
11.4%
통 17
 
6.7%
도 17
 
6.7%
동 15
 
5.9%
항 15
 
5.9%
죽 15
 
5.9%
왕 12
 
4.7%
충 12
 
4.7%
정 12
 
4.7%
Other values (21) 81
31.9%
Decimal Number
ValueCountFrequency (%)
0 102
24.3%
1 85
20.3%
2 62
14.8%
6 42
10.0%
3 27
 
6.4%
7 27
 
6.4%
4 26
 
6.2%
5 25
 
6.0%
8 13
 
3.1%
9 10
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 551
68.4%
Hangul 254
31.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 29
 
11.4%
향 29
 
11.4%
통 17
 
6.7%
도 17
 
6.7%
동 15
 
5.9%
항 15
 
5.9%
죽 15
 
5.9%
왕 12
 
4.7%
충 12
 
4.7%
정 12
 
4.7%
Other values (21) 81
31.9%
Common
ValueCountFrequency (%)
- 132
24.0%
0 102
18.5%
1 85
15.4%
2 62
11.3%
6 42
 
7.6%
3 27
 
4.9%
7 27
 
4.9%
4 26
 
4.7%
5 25
 
4.5%
8 13
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 551
68.4%
Hangul 254
31.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 132
24.0%
0 102
18.5%
1 85
15.4%
2 62
11.3%
6 42
 
7.6%
3 27
 
4.9%
7 27
 
4.9%
4 26
 
4.7%
5 25
 
4.5%
8 13
 
2.4%
Hangul
ValueCountFrequency (%)
교 29
 
11.4%
향 29
 
11.4%
통 17
 
6.7%
도 17
 
6.7%
동 15
 
5.9%
항 15
 
5.9%
죽 15
 
5.9%
왕 12
 
4.7%
충 12
 
4.7%
정 12
 
4.7%
Other values (21) 81
31.9%

Interactions

2024-03-23T03:58:45.524497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T03:58:54.855105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연 번읍면동
연 번1.0000.947
읍면동0.9471.000
2024-03-23T03:58:55.268128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연 번읍면동
연 번1.0000.739
읍면동0.7391.000

Missing values

2024-03-23T03:58:46.038184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T03:58:46.603778image/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

연 번읍면동주 소관리번호
01동충동동충동 486-1동충-101
12동충동동충동 396-1동충-102
23동충동동충동 486-1동충-103
34동충동?동충동 251-9동충-104
45동충동동충동 483동충-105
56동충동동충동 70-6동충-106
67동충동동림로 54동충-107
78동충동동충동 14-10동충-108
89동충동동충동 483-11동충-109
910동충동용성로41-4동충-110
연 번읍면동주 소관리번호
122123사매면여의터길40-3(상신마을회관 앞)사매-1602
123124이백면산남길 36(산남마을회관 앞)이백-2001
124125이백면과립리 234-1(입촌마을 승강장 옆)이백-2002
125126이백면안골길 50-6(내동마을회관)이백-2003
126127이백면이백오산길 104-2(오촌마을회관)이백-2004
127128아영면외지2길2(외지마을 집하장)아영-2201
128129아영면봉화산로 1029(일대마을 집하장)아영-2202
129130산내면장항리 807-4(장항마을회관 옆)산내-2301
130131산내면대정리 726-1(대정마을회관 옆)산내-2302
131132산내면중황리 758(하황마을 옆)산내-2303