Overview

Dataset statistics

Number of variables6
Number of observations57
Missing cells2
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory51.3 B

Variable types

Categorical2
Text3
Numeric1

Dataset

Description경기도 안산시 소재 단체현황입니다.관련부서,단체명,소재지,연락처,회원수(명),데이터기준일자를 제공합니다.
Author경기도 안산시
URLhttps://www.data.go.kr/data/15068620/fileData.do

Alerts

회원수(명) is highly overall correlated with 관련부서High correlation
관련부서 is highly overall correlated with 회원수(명) and 1 other fieldsHigh correlation
데이터기준일자 is highly overall correlated with 관련부서High correlation
데이터기준일자 is highly imbalanced (87.3%)Imbalance
회원수(명) has 2 (3.5%) missing valuesMissing
단체명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:06:23.887085
Analysis finished2023-12-12 15:06:24.540592
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관련부서
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Memory size588.0 B
경제일자리과
20 
장애인복지과
11 
자치행정과
8 
농업기술지원과
5 
체육진흥과
 
2
Other values (7)
11 

Length

Max length7
Median length6
Mean length5.6491228
Min length3

Unique

Unique3 ?
Unique (%)5.3%

Sample

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

Common Values

ValueCountFrequency (%)
경제일자리과 20
35.1%
장애인복지과 11
19.3%
자치행정과 8
 
14.0%
농업기술지원과 5
 
8.8%
체육진흥과 2
 
3.5%
아동권리과 2
 
3.5%
보육정책과 2
 
3.5%
노인복지과 2
 
3.5%
관광과 2
 
3.5%
노동정책과 1
 
1.8%
Other values (2) 2
 
3.5%

Length

2023-12-13T00:06:24.610796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경제일자리과 20
35.1%
장애인복지과 11
19.3%
자치행정과 8
 
14.0%
농업기술지원과 5
 
8.8%
체육진흥과 2
 
3.5%
아동권리과 2
 
3.5%
보육정책과 2
 
3.5%
노인복지과 2
 
3.5%
관광과 2
 
3.5%
노동정책과 1
 
1.8%
Other values (2) 2
 
3.5%

단체명
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-13T00:06:24.802849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length18
Mean length11.54386
Min length4

Characters and Unicode

Total characters658
Distinct characters137
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

Unique57 ?
Unique (%)100.0%

Sample

1st row안산시 자원봉사센터
2nd row자율방범대 연합회
3rd row로보캅순찰대
4th row민주평화통일자문회의 안산시협의회
5th row사)안산시 새마을회
ValueCountFrequency (%)
안산시지회 7
 
7.5%
안산시 5
 
5.4%
상점가 4
 
4.3%
안산시지부 3
 
3.2%
안산시협의회 2
 
2.2%
사)대한노인회 2
 
2.2%
안산지부 2
 
2.2%
지회 2
 
2.2%
상록구 1
 
1.1%
소상공인연합회 1
 
1.1%
Other values (64) 64
68.8%
2023-12-13T00:06:25.149838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
안 45
 
6.8%
산 43
 
6.5%
회 42
 
6.4%
시 38
 
5.8%
37
 
5.6%
지 25
 
3.8%
인 18
 
2.7%
사 17
 
2.6%
자 16
 
2.4%
장 15
 
2.3%
Other values (127) 362
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 588
89.4%
Space Separator 37
 
5.6%
Close Punctuation 13
 
2.0%
Open Punctuation 10
 
1.5%
Uppercase Letter 6
 
0.9%
Decimal Number 2
 
0.3%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 45
 
7.7%
산 43
 
7.3%
회 42
 
7.1%
시 38
 
6.5%
지 25
 
4.3%
인 18
 
3.1%
사 17
 
2.9%
자 16
 
2.7%
장 15
 
2.6%
연 14
 
2.4%
Other values (117) 315
53.6%
Uppercase Letter
ValueCountFrequency (%)
H 2
33.3%
A 1
16.7%
M 1
16.7%
Y 1
16.7%
C 1
16.7%
Space Separator
ValueCountFrequency (%)
37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Decimal Number
ValueCountFrequency (%)
4 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 588
89.4%
Common 64
 
9.7%
Latin 6
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 45
 
7.7%
산 43
 
7.3%
회 42
 
7.1%
시 38
 
6.5%
지 25
 
4.3%
인 18
 
3.1%
사 17
 
2.9%
자 16
 
2.7%
장 15
 
2.6%
연 14
 
2.4%
Other values (117) 315
53.6%
Common
ValueCountFrequency (%)
37
57.8%
) 13
 
20.3%
( 10
 
15.6%
4 2
 
3.1%
- 2
 
3.1%
Latin
ValueCountFrequency (%)
H 2
33.3%
A 1
16.7%
M 1
16.7%
Y 1
16.7%
C 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 588
89.4%
ASCII 70
 
10.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
안 45
 
7.7%
산 43
 
7.3%
회 42
 
7.1%
시 38
 
6.5%
지 25
 
4.3%
인 18
 
3.1%
사 17
 
2.9%
자 16
 
2.7%
장 15
 
2.6%
연 14
 
2.4%
Other values (117) 315
53.6%
ASCII
ValueCountFrequency (%)
37
52.9%
) 13
 
18.6%
( 10
 
14.3%
4 2
 
2.9%
- 2
 
2.9%
H 2
 
2.9%
A 1
 
1.4%
M 1
 
1.4%
Y 1
 
1.4%
C 1
 
1.4%

소재지
Text

Distinct55
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-13T00:06:25.373609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length35
Mean length28.140351
Min length18

Characters and Unicode

Total characters1604
Distinct characters121
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)93.0%

Sample

1st row경기도 안산시 단원구 화랑로 260 (초지동666-1) 와스타디움 1층
2nd row경기도 안산시 상록구 부곡동 719-1(시낭운동장내)
3rd row경기도 안산시 상록구 항가울로 200 (도시정보센터 내)
4th row경기도 안산시 단원구 고잔로 27 , 4층(상하수도사업소 내)
5th row경기도 안산시 상록구 용신로 348
ValueCountFrequency (%)
안산시 57
16.5%
경기도 54
 
15.6%
상록구 32
 
9.2%
단원구 25
 
7.2%
화랑로 8
 
2.3%
차돌배기로24-3 7
 
2.0%
장애인지원센터 7
 
2.0%
항가울로 6
 
1.7%
농업기술센터 5
 
1.4%
260 5
 
1.4%
Other values (116) 140
40.5%
2023-12-13T00:06:25.768336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
291
 
18.1%
기 69
 
4.3%
산 62
 
3.9%
안 61
 
3.8%
시 59
 
3.7%
구 59
 
3.7%
로 56
 
3.5%
도 56
 
3.5%
경 54
 
3.4%
1 47
 
2.9%
Other values (111) 790
49.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1000
62.3%
Space Separator 291
 
18.1%
Decimal Number 229
 
14.3%
Open Punctuation 24
 
1.5%
Close Punctuation 24
 
1.5%
Other Punctuation 20
 
1.2%
Dash Punctuation 11
 
0.7%
Math Symbol 3
 
0.2%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 69
 
6.9%
산 62
 
6.2%
안 61
 
6.1%
시 59
 
5.9%
구 59
 
5.9%
로 56
 
5.6%
도 56
 
5.6%
경 54
 
5.4%
원 36
 
3.6%
상 34
 
3.4%
Other values (93) 454
45.4%
Decimal Number
ValueCountFrequency (%)
1 47
20.5%
2 41
17.9%
0 32
14.0%
3 27
11.8%
4 24
10.5%
5 20
8.7%
6 16
 
7.0%
7 10
 
4.4%
8 7
 
3.1%
9 5
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
291
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1000
62.3%
Common 602
37.5%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 69
 
6.9%
산 62
 
6.2%
안 61
 
6.1%
시 59
 
5.9%
구 59
 
5.9%
로 56
 
5.6%
도 56
 
5.6%
경 54
 
5.4%
원 36
 
3.6%
상 34
 
3.4%
Other values (93) 454
45.4%
Common
ValueCountFrequency (%)
291
48.3%
1 47
 
7.8%
2 41
 
6.8%
0 32
 
5.3%
3 27
 
4.5%
( 24
 
4.0%
4 24
 
4.0%
) 24
 
4.0%
, 20
 
3.3%
5 20
 
3.3%
Other values (6) 52
 
8.6%
Latin
ValueCountFrequency (%)
C 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1000
62.3%
ASCII 604
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
291
48.2%
1 47
 
7.8%
2 41
 
6.8%
0 32
 
5.3%
3 27
 
4.5%
( 24
 
4.0%
4 24
 
4.0%
) 24
 
4.0%
, 20
 
3.3%
5 20
 
3.3%
Other values (8) 54
 
8.9%
Hangul
ValueCountFrequency (%)
기 69
 
6.9%
산 62
 
6.2%
안 61
 
6.1%
시 59
 
5.9%
구 59
 
5.9%
로 56
 
5.6%
도 56
 
5.6%
경 54
 
5.4%
원 36
 
3.6%
상 34
 
3.4%
Other values (93) 454
45.4%

연락처
Text

Distinct52
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-13T00:06:25.980299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.754386
Min length9

Characters and Unicode

Total characters670
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)87.7%

Sample

1st row031-411-1365
2nd row031-403-0112
3rd row031-481-3327
4th row031-482-5910
5th row031-482-2543
ValueCountFrequency (%)
1666-1234 5
 
8.8%
031-418-6766 2
 
3.5%
031-410-0140 1
 
1.8%
031-411-1365 1
 
1.8%
031-486-5955 1
 
1.8%
031-482-5067 1
 
1.8%
031-406-2105 1
 
1.8%
031-407-0951 1
 
1.8%
031-437-4000 1
 
1.8%
031-485-1887 1
 
1.8%
Other values (42) 42
73.7%
2023-12-13T00:06:26.314119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 115
17.2%
- 109
16.3%
0 103
15.4%
3 79
11.8%
4 79
11.8%
8 49
7.3%
6 40
 
6.0%
2 36
 
5.4%
5 24
 
3.6%
7 20
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 561
83.7%
Dash Punctuation 109
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 115
20.5%
0 103
18.4%
3 79
14.1%
4 79
14.1%
8 49
8.7%
6 40
 
7.1%
2 36
 
6.4%
5 24
 
4.3%
7 20
 
3.6%
9 16
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 670
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 115
17.2%
- 109
16.3%
0 103
15.4%
3 79
11.8%
4 79
11.8%
8 49
7.3%
6 40
 
6.0%
2 36
 
5.4%
5 24
 
3.6%
7 20
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 670
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 115
17.2%
- 109
16.3%
0 103
15.4%
3 79
11.8%
4 79
11.8%
8 49
7.3%
6 40
 
6.0%
2 36
 
5.4%
5 24
 
3.6%
7 20
 
3.0%

회원수(명)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct50
Distinct (%)90.9%
Missing2
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean1250.0727
Minimum9
Maximum29766
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-13T00:06:26.460409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile33.5
Q1111
median239
Q3531.5
95-th percentile5673
Maximum29766
Range29757
Interquartile range (IQR)420.5

Descriptive statistics

Standard deviation4190.2895
Coefficient of variation (CV)3.3520366
Kurtosis41.391694
Mean1250.0727
Median Absolute Deviation (MAD)142
Skewness6.1627827
Sum68754
Variance17558526
MonotonicityNot monotonic
2023-12-13T00:06:26.582261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
250 3
 
5.3%
800 2
 
3.5%
700 2
 
3.5%
289 2
 
3.5%
150 1
 
1.8%
194 1
 
1.8%
255 1
 
1.8%
251 1
 
1.8%
119 1
 
1.8%
112 1
 
1.8%
Other values (40) 40
70.2%
(Missing) 2
 
3.5%
ValueCountFrequency (%)
9 1
1.8%
29 1
1.8%
30 1
1.8%
35 1
1.8%
59 1
1.8%
79 1
1.8%
80 1
1.8%
87 1
1.8%
90 1
1.8%
96 1
1.8%
ValueCountFrequency (%)
29766 1
1.8%
7787 1
1.8%
5743 1
1.8%
5643 1
1.8%
2867 1
1.8%
2000 1
1.8%
1836 1
1.8%
1448 1
1.8%
800 2
3.5%
710 1
1.8%

데이터기준일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-08-07
56 
2023-08-22
 
1

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st row2023-08-07
2nd row2023-08-07
3rd row2023-08-07
4th row2023-08-07
5th row2023-08-07

Common Values

ValueCountFrequency (%)
2023-08-07 56
98.2%
2023-08-22 1
 
1.8%

Length

2023-12-13T00:06:26.714259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:06:26.815032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-07 56
98.2%
2023-08-22 1
 
1.8%

Interactions

2023-12-13T00:06:24.308917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:06:26.878218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관련부서단체명소재지연락처회원수(명)데이터기준일자
관련부서1.0001.0001.0001.0000.9930.762
단체명1.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0000.9700.0001.000
연락처1.0001.0000.9701.0001.0001.000
회원수(명)0.9931.0000.0001.0001.0000.000
데이터기준일자0.7621.0001.0001.0000.0001.000
2023-12-13T00:06:26.968676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
데이터기준일자관련부서
데이터기준일자1.0000.548
관련부서0.5481.000
2023-12-13T00:06:27.040926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회원수(명)관련부서데이터기준일자
회원수(명)1.0000.8140.000
관련부서0.8141.0000.548
데이터기준일자0.0000.5481.000

Missing values

2023-12-13T00:06:24.409570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:06:24.501718image/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

관련부서단체명소재지연락처회원수(명)데이터기준일자
0자치행정과안산시 자원봉사센터경기도 안산시 단원구 화랑로 260 (초지동666-1) 와스타디움 1층031-411-1365352023-08-07
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