Overview

Dataset statistics

Number of variables6
Number of observations496
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.9 KiB
Average record size in memory49.3 B

Variable types

Numeric1
Text2
Categorical3

Dataset

Description경상남도 사천시 의류수거함 위치 데이터입니다. 의류수거함이 있는 주소, 관리단체, 관리번호 등이 포함되어 있습니다.
Author경상남도 사천시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15127257

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 행정동High correlation
관리단체 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-03-23 07:18:21.086338
Analysis finished2024-03-23 07:18:22.864122
Duration1.78 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct496
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean248.5
Minimum1
Maximum496
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2024-03-23T07:18:23.150964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25.75
Q1124.75
median248.5
Q3372.25
95-th percentile471.25
Maximum496
Range495
Interquartile range (IQR)247.5

Descriptive statistics

Standard deviation143.32713
Coefficient of variation (CV)0.57676914
Kurtosis-1.2
Mean248.5
Median Absolute Deviation (MAD)124
Skewness0
Sum123256
Variance20542.667
MonotonicityStrictly increasing
2024-03-23T07:18:23.673728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
328 1
 
0.2%
341 1
 
0.2%
340 1
 
0.2%
339 1
 
0.2%
338 1
 
0.2%
337 1
 
0.2%
336 1
 
0.2%
335 1
 
0.2%
334 1
 
0.2%
Other values (486) 486
98.0%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
496 1
0.2%
495 1
0.2%
494 1
0.2%
493 1
0.2%
492 1
0.2%
491 1
0.2%
490 1
0.2%
489 1
0.2%
488 1
0.2%
487 1
0.2%

관리번호
Text

UNIQUE 

Distinct496
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-03-23T07:18:24.665719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.2762097
Min length2

Characters and Unicode

Total characters2121
Distinct characters16
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

Unique496 ?
Unique (%)100.0%

Sample

1st row단-2
2nd row단-5
3rd row단-6
4th row단-7
5th row단-9
ValueCountFrequency (%)
단-2 1
 
0.2%
쓰-220 1
 
0.2%
삼-15 1
 
0.2%
삼-9 1
 
0.2%
삼-8 1
 
0.2%
삼-1 1
 
0.2%
추77 1
 
0.2%
쓰-231 1
 
0.2%
쓰-230 1
 
0.2%
쓰-229 1
 
0.2%
Other values (486) 486
98.0%
2024-03-23T07:18:26.262871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 432
20.4%
1 277
13.1%
쓰 195
9.2%
삼 193
9.1%
2 162
 
7.6%
5 106
 
5.0%
4 103
 
4.9%
3 101
 
4.8%
6 100
 
4.7%
7 92
 
4.3%
Other values (6) 360
17.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1193
56.2%
Other Letter 496
23.4%
Dash Punctuation 432
 
20.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 277
23.2%
2 162
13.6%
5 106
 
8.9%
4 103
 
8.6%
3 101
 
8.5%
6 100
 
8.4%
7 92
 
7.7%
8 87
 
7.3%
9 83
 
7.0%
0 82
 
6.9%
Other Letter
ValueCountFrequency (%)
쓰 195
39.3%
삼 193
38.9%
추 64
 
12.9%
일 33
 
6.7%
단 11
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 432
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1625
76.6%
Hangul 496
 
23.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 432
26.6%
1 277
17.0%
2 162
 
10.0%
5 106
 
6.5%
4 103
 
6.3%
3 101
 
6.2%
6 100
 
6.2%
7 92
 
5.7%
8 87
 
5.4%
9 83
 
5.1%
Hangul
ValueCountFrequency (%)
쓰 195
39.3%
삼 193
38.9%
추 64
 
12.9%
일 33
 
6.7%
단 11
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1625
76.6%
Hangul 496
 
23.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 432
26.6%
1 277
17.0%
2 162
 
10.0%
5 106
 
6.5%
4 103
 
6.3%
3 101
 
6.2%
6 100
 
6.2%
7 92
 
5.7%
8 87
 
5.4%
9 83
 
5.1%
Hangul
ValueCountFrequency (%)
쓰 195
39.3%
삼 193
38.9%
추 64
 
12.9%
일 33
 
6.7%
단 11
 
2.2%

관리단체
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
삼성자원
230 
쓰임업
216 
일어서기자원
39 
단비자원
 
11

Length

Max length6
Median length4
Mean length3.7217742
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
삼성자원 230
46.4%
쓰임업 216
43.5%
일어서기자원 39
 
7.9%
단비자원 11
 
2.2%

Length

2024-03-23T07:18:26.725013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:18:27.067535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
삼성자원 230
46.4%
쓰임업 216
43.5%
일어서기자원 39
 
7.9%
단비자원 11
 
2.2%

행정동
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
벌용동
86 
사천읍
72 
향촌동
70 
동서동
49 
동서금
48 
Other values (9)
171 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
벌용동 86
17.3%
사천읍 72
14.5%
향촌동 70
14.1%
동서동 49
9.9%
동서금 48
9.7%
선구동 44
8.9%
사남면 36
7.3%
남양동 22
 
4.4%
정동면 21
 
4.2%
용현면 19
 
3.8%
Other values (4) 29
 
5.8%

Length

2024-03-23T07:18:27.586700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
벌용동 86
17.3%
사천읍 72
14.5%
향촌동 70
14.1%
동서동 49
9.9%
동서금 48
9.7%
선구동 44
8.9%
사남면 36
7.3%
남양동 22
 
4.4%
정동면 21
 
4.2%
용현면 19
 
3.8%
Other values (4) 29
 
5.8%

설치장소
Text

Distinct413
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-03-23T07:18:28.966284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length10.377016
Min length6

Characters and Unicode

Total characters5147
Distinct characters119
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique375 ?
Unique (%)75.6%

Sample

1st row곤명면 정곡리 1011
2nd row곤명면 정곡리 851
3rd row곤명면 정곡리 863
4th row곤명면 정곡리 862
5th row곤명면 정곡리 838-8
ValueCountFrequency (%)
사천읍 70
 
6.0%
향촌동 69
 
5.9%
벌리동 64
 
5.4%
동금동 43
 
3.7%
사남면 32
 
2.7%
선구동 30
 
2.6%
선인리 28
 
2.4%
동동 22
 
1.9%
504 21
 
1.8%
용강동 20
 
1.7%
Other values (490) 777
66.1%
2024-03-23T07:18:30.469119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
680
 
13.2%
동 434
 
8.4%
1 392
 
7.6%
- 343
 
6.7%
리 246
 
4.8%
4 240
 
4.7%
2 235
 
4.6%
3 219
 
4.3%
5 198
 
3.8%
7 157
 
3.1%
Other values (109) 2003
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2069
40.2%
Decimal Number 1986
38.6%
Space Separator 680
 
13.2%
Dash Punctuation 343
 
6.7%
Close Punctuation 33
 
0.6%
Open Punctuation 33
 
0.6%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 434
21.0%
리 246
 
11.9%
사 105
 
5.1%
면 94
 
4.5%
천 82
 
4.0%
읍 81
 
3.9%
촌 73
 
3.5%
향 70
 
3.4%
벌 67
 
3.2%
선 67
 
3.2%
Other values (92) 750
36.2%
Decimal Number
ValueCountFrequency (%)
1 392
19.7%
4 240
12.1%
2 235
11.8%
3 219
11.0%
5 198
10.0%
7 157
7.9%
0 156
 
7.9%
6 141
 
7.1%
9 126
 
6.3%
8 122
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
S 1
33.3%
I 1
33.3%
G 1
33.3%
Space Separator
ValueCountFrequency (%)
680
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 343
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3075
59.7%
Hangul 2069
40.2%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 434
21.0%
리 246
 
11.9%
사 105
 
5.1%
면 94
 
4.5%
천 82
 
4.0%
읍 81
 
3.9%
촌 73
 
3.5%
향 70
 
3.4%
벌 67
 
3.2%
선 67
 
3.2%
Other values (92) 750
36.2%
Common
ValueCountFrequency (%)
680
22.1%
1 392
12.7%
- 343
11.2%
4 240
 
7.8%
2 235
 
7.6%
3 219
 
7.1%
5 198
 
6.4%
7 157
 
5.1%
0 156
 
5.1%
6 141
 
4.6%
Other values (4) 314
10.2%
Latin
ValueCountFrequency (%)
S 1
33.3%
I 1
33.3%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3078
59.8%
Hangul 2069
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
680
22.1%
1 392
12.7%
- 343
11.1%
4 240
 
7.8%
2 235
 
7.6%
3 219
 
7.1%
5 198
 
6.4%
7 157
 
5.1%
0 156
 
5.1%
6 141
 
4.6%
Other values (7) 317
10.3%
Hangul
ValueCountFrequency (%)
동 434
21.0%
리 246
 
11.9%
사 105
 
5.1%
면 94
 
4.5%
천 82
 
4.0%
읍 81
 
3.9%
촌 73
 
3.5%
향 70
 
3.4%
벌 67
 
3.2%
선 67
 
3.2%
Other values (92) 750
36.2%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2024-02-01
496 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-01
2nd row2024-02-01
3rd row2024-02-01
4th row2024-02-01
5th row2024-02-01

Common Values

ValueCountFrequency (%)
2024-02-01 496
100.0%

Length

2024-03-23T07:18:31.190473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:18:31.535633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-01 496
100.0%

Interactions

2024-03-23T07:18:21.597187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:18:31.750705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관리단체행정동
연번1.0000.4690.938
관리단체0.4691.0000.772
행정동0.9380.7721.000
2024-03-23T07:18:32.083587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동관리단체
행정동1.0000.556
관리단체0.5561.000
2024-03-23T07:18:32.485072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번관리단체행정동
연번1.0000.2950.754
관리단체0.2951.0000.556
행정동0.7540.5561.000

Missing values

2024-03-23T07:18:22.137552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:18:22.657019image/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

연번관리번호관리단체행정동설치장소데이터기준일자
01단-2단비자원곤명면곤명면 정곡리 10112024-02-01
12단-5단비자원곤명면곤명면 정곡리 8512024-02-01
23단-6단비자원곤명면곤명면 정곡리 8632024-02-01
34단-7단비자원곤명면곤명면 정곡리 8622024-02-01
45단-9단비자원곤명면곤명면 정곡리 838-82024-02-01
56단-10단비자원곤명면곤명면 정곡리 8502024-02-01
67단-13단비자원곤명면곤명면 봉계리 8752024-02-01
78단-14단비자원곤명면곤명면 본촌리 142-12024-02-01
89쓰-141쓰임업곤양면곤양면 남문외리 147-12024-02-01
910쓰-142쓰임업곤양면곤양면 서정리 373-22024-02-01
연번관리번호관리단체행정동설치장소데이터기준일자
486487추17쓰임업향촌동향촌동 10052024-02-01
487488추25삼성자원향촌동향촌동 1124-42024-02-01
488489추26삼성자원향촌동향촌동 1142-62024-02-01
489490추27삼성자원향촌동향촌동 1137-72024-02-01
490491추28삼성자원향촌동향촌동 977-32024-02-01
491492추29삼성자원향촌동향촌동 10052024-02-01
492493추47삼성자원향촌동향촌동 815-102024-02-01
493494추48삼성자원향촌동향촌동 824-22024-02-01
494495추49삼성자원향촌동향촌동 825-72024-02-01
495496추50일어서기자원향촌동사등동 2402024-02-01