Overview

Dataset statistics

Number of variables6
Number of observations72
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory49.8 B

Variable types

Categorical3
Text3

Dataset

Description매년 공표되는 근로자종합복지관 운영현황으로서
Author고용노동부
URLhttps://www.data.go.kr/data/15068780/fileData.do

Alerts

지원구분 is highly overall correlated with 지원 연도High correlation
지원 연도 is highly overall correlated with 지원구분High correlation
소재지 has unique valuesUnique
명칭 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:51:27.253509
Analysis finished2023-12-12 04:51:27.818457
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지원구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size708.0 B
국고보조 지원
41 
분권교부세 배분
31 

Length

Max length8
Median length7
Mean length7.4305556
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국고보조 지원
2nd row국고보조 지원
3rd row국고보조 지원
4th row국고보조 지원
5th row국고보조 지원

Common Values

ValueCountFrequency (%)
국고보조 지원 41
56.9%
분권교부세 배분 31
43.1%

Length

2023-12-12T13:51:27.877052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:51:27.978732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국고보조 41
28.5%
지원 41
28.5%
분권교부세 31
21.5%
배분 31
21.5%

지원 연도
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size708.0 B
2014
2005
1994
2002
2001
 
4
Other values (19)
45 

Length

Max length9
Median length4
Mean length4.4861111
Min length4

Unique

Unique5 ?
Unique (%)6.9%

Sample

1st row1992
2nd row1992
3rd row1992
4th row1993
5th row1993

Common Values

ValueCountFrequency (%)
2014 7
 
9.7%
2005 6
 
8.3%
1994 5
 
6.9%
2002 5
 
6.9%
2001 4
 
5.6%
2010~2013 4
 
5.6%
2007 4
 
5.6%
1993 4
 
5.6%
2004 4
 
5.6%
1995 3
 
4.2%
Other values (14) 26
36.1%

Length

2023-12-12T13:51:28.086248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2014 7
 
9.7%
2005 6
 
8.3%
1994 5
 
6.9%
2002 5
 
6.9%
2001 4
 
5.6%
2010~2013 4
 
5.6%
2007 4
 
5.6%
1993 4
 
5.6%
2004 4
 
5.6%
1996 3
 
4.2%
Other values (14) 26
36.1%

소재지
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-12T13:51:28.335017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length3
Mean length4.0138889
Min length2

Characters and Unicode

Total characters289
Distinct characters91
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

Unique72 ?
Unique (%)100.0%

Sample

1st row대전(둔산동)
2nd row광 양
3rd row문 막
4th row거 제
5th row성 남
ValueCountFrequency (%)
8
 
6.6%
6
 
4.9%
5
 
4.1%
3
 
2.5%
2
 
1.6%
2
 
1.6%
청주 2
 
1.6%
2
 
1.6%
2
 
1.6%
창원 2
 
1.6%
Other values (84) 88
72.1%
2023-12-12T13:51:28.746267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50
 
17.3%
( 15
 
5.2%
14
 
4.8%
) 14
 
4.8%
13
 
4.5%
12
 
4.2%
7
 
2.4%
7
 
2.4%
7
 
2.4%
6
 
2.1%
Other values (81) 144
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 210
72.7%
Space Separator 50
 
17.3%
Open Punctuation 15
 
5.2%
Close Punctuation 14
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
14
 
6.7%
13
 
6.2%
12
 
5.7%
7
 
3.3%
7
 
3.3%
7
 
3.3%
6
 
2.9%
5
 
2.4%
5
 
2.4%
5
 
2.4%
Other values (78) 129
61.4%
Space Separator
ValueCountFrequency (%)
50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 210
72.7%
Common 79
 
27.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
14
 
6.7%
13
 
6.2%
12
 
5.7%
7
 
3.3%
7
 
3.3%
7
 
3.3%
6
 
2.9%
5
 
2.4%
5
 
2.4%
5
 
2.4%
Other values (78) 129
61.4%
Common
ValueCountFrequency (%)
50
63.3%
( 15
 
19.0%
) 14
 
17.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 210
72.7%
ASCII 79
 
27.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50
63.3%
( 15
 
19.0%
) 14
 
17.7%
Hangul
ValueCountFrequency (%)
14
 
6.7%
13
 
6.2%
12
 
5.7%
7
 
3.3%
7
 
3.3%
7
 
3.3%
6
 
2.9%
5
 
2.4%
5
 
2.4%
5
 
2.4%
Other values (78) 129
61.4%

명칭
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-12T13:51:29.064726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length11.986111
Min length8

Characters and Unicode

Total characters863
Distinct characters110
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)100.0%

Sample

1st row대전광역시둔산동 근로자종합복지회관
2nd row광양시근로자종합복지관
3rd row문막근로자종합복지관
4th row거제시근로자가족복지회관
5th row성남시근로자종합복지관
ValueCountFrequency (%)
근로자종합복지회관 3
 
3.3%
근로자종합복지관 3
 
3.3%
종합복지관 2
 
2.2%
근로자 2
 
2.2%
화성시근로자종합복지관 2
 
2.2%
대전광역시둔산동 1
 
1.1%
당진근로자종합복지관 1
 
1.1%
공주시 1
 
1.1%
노동복지회관 1
 
1.1%
창원시 1
 
1.1%
Other values (75) 75
81.5%
2023-12-12T13:51:29.595882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
75
 
8.7%
74
 
8.6%
73
 
8.5%
66
 
7.6%
66
 
7.6%
66
 
7.6%
60
 
7.0%
60
 
7.0%
50
 
5.8%
20
 
2.3%
Other values (100) 253
29.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 835
96.8%
Space Separator 20
 
2.3%
Open Punctuation 4
 
0.5%
Close Punctuation 3
 
0.3%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
75
 
9.0%
74
 
8.9%
73
 
8.7%
66
 
7.9%
66
 
7.9%
66
 
7.9%
60
 
7.2%
60
 
7.2%
50
 
6.0%
17
 
2.0%
Other values (96) 228
27.3%
Space Separator
ValueCountFrequency (%)
20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 835
96.8%
Common 28
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
75
 
9.0%
74
 
8.9%
73
 
8.7%
66
 
7.9%
66
 
7.9%
66
 
7.9%
60
 
7.2%
60
 
7.2%
50
 
6.0%
17
 
2.0%
Other values (96) 228
27.3%
Common
ValueCountFrequency (%)
20
71.4%
( 4
 
14.3%
) 3
 
10.7%
2 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 835
96.8%
ASCII 28
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
75
 
9.0%
74
 
8.9%
73
 
8.7%
66
 
7.9%
66
 
7.9%
66
 
7.9%
60
 
7.2%
60
 
7.2%
50
 
6.0%
17
 
2.0%
Other values (96) 228
27.3%
ASCII
ValueCountFrequency (%)
20
71.4%
( 4
 
14.3%
) 3
 
10.7%
2 1
 
3.6%

주소
Text

UNIQUE 

Distinct72
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size708.0 B
2023-12-12T13:51:29.971414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length18
Mean length14.138889
Min length8

Characters and Unicode

Total characters1018
Distinct characters166
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)100.0%

Sample

1st row대전 서구 둔산서로 84
2nd row광양시불로로123
3rd row원주시 문막공단로42
4th row거제시탑곡로75
5th row성남시 중원구 순환로166
ValueCountFrequency (%)
창원시 5
 
2.5%
남구 3
 
1.5%
대전 3
 
1.5%
원주시 2
 
1.0%
구미시 2
 
1.0%
수원시 2
 
1.0%
청주시 2
 
1.0%
의창구 2
 
1.0%
완주군 2
 
1.0%
봉동읍 2
 
1.0%
Other values (175) 177
87.6%
2023-12-12T13:51:30.544935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
131
 
12.9%
1 60
 
5.9%
59
 
5.8%
52
 
5.1%
3 30
 
2.9%
29
 
2.8%
29
 
2.8%
4 29
 
2.8%
28
 
2.8%
2 25
 
2.5%
Other values (156) 546
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 626
61.5%
Decimal Number 242
 
23.8%
Space Separator 131
 
12.9%
Dash Punctuation 18
 
1.8%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
59
 
9.4%
52
 
8.3%
29
 
4.6%
29
 
4.6%
28
 
4.5%
16
 
2.6%
16
 
2.6%
16
 
2.6%
13
 
2.1%
13
 
2.1%
Other values (143) 355
56.7%
Decimal Number
ValueCountFrequency (%)
1 60
24.8%
3 30
12.4%
4 29
12.0%
2 25
10.3%
8 23
 
9.5%
0 21
 
8.7%
6 20
 
8.3%
5 14
 
5.8%
9 11
 
4.5%
7 9
 
3.7%
Space Separator
ValueCountFrequency (%)
131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 626
61.5%
Common 392
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
59
 
9.4%
52
 
8.3%
29
 
4.6%
29
 
4.6%
28
 
4.5%
16
 
2.6%
16
 
2.6%
16
 
2.6%
13
 
2.1%
13
 
2.1%
Other values (143) 355
56.7%
Common
ValueCountFrequency (%)
131
33.4%
1 60
15.3%
3 30
 
7.7%
4 29
 
7.4%
2 25
 
6.4%
8 23
 
5.9%
0 21
 
5.4%
6 20
 
5.1%
- 18
 
4.6%
5 14
 
3.6%
Other values (3) 21
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 626
61.5%
ASCII 392
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
131
33.4%
1 60
15.3%
3 30
 
7.7%
4 29
 
7.4%
2 25
 
6.4%
8 23
 
5.9%
0 21
 
5.4%
6 20
 
5.1%
- 18
 
4.6%
5 14
 
3.6%
Other values (3) 21
 
5.4%
Hangul
ValueCountFrequency (%)
59
 
9.4%
52
 
8.3%
29
 
4.6%
29
 
4.6%
28
 
4.5%
16
 
2.6%
16
 
2.6%
16
 
2.6%
13
 
2.1%
13
 
2.1%
Other values (143) 355
56.7%

운영주체
Categorical

Distinct32
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Memory size708.0 B
한국노총
36 
민주노총
완주군
 
2
포항시
 
2
진주YWCA
 
1
Other values (27)
27 

Length

Max length17
Median length4
Mean length5.1527778
Min length3

Unique

Unique28 ?
Unique (%)38.9%

Sample

1st row한국노총
2nd row한국노총
3rd row문막공단 운영협회
4th row거제YWCA
5th row한국노총

Common Values

ValueCountFrequency (%)
한국노총 36
50.0%
민주노총 4
 
5.6%
완주군 2
 
2.8%
포항시 2
 
2.8%
진주YWCA 1
 
1.4%
서산시 1
 
1.4%
원주시 1
 
1.4%
울산 시설공단 1
 
1.4%
순천시 1
 
1.4%
동해시설 관리공단 1
 
1.4%
Other values (22) 22
30.6%

Length

2023-12-12T13:51:30.765364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한국노총 37
44.0%
민주노총 4
 
4.8%
관리공단 3
 
3.6%
포항시 2
 
2.4%
완주군 2
 
2.4%
대구카톡릭사회복지회 1
 
1.2%
서비스센터 1
 
1.2%
칠곡군 1
 
1.2%
하남산업단지 1
 
1.2%
당진군 1
 
1.2%
Other values (31) 31
36.9%

Correlations

2023-12-12T13:51:30.884755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지원구분지원 연도소재지명칭주소운영주체
지원구분1.0001.0001.0001.0001.0000.000
지원 연도1.0001.0001.0001.0001.0000.599
소재지1.0001.0001.0001.0001.0001.000
명칭1.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.000
운영주체0.0000.5991.0001.0001.0001.000
2023-12-12T13:51:31.014049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지원 연도운영주체지원구분
지원 연도1.0000.1330.828
운영주체0.1331.0000.000
지원구분0.8280.0001.000
2023-12-12T13:51:31.113968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지원구분지원 연도운영주체
지원구분1.0000.8280.000
지원 연도0.8281.0000.133
운영주체0.0000.1331.000

Missing values

2023-12-12T13:51:27.682870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:51:27.781795image/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

지원구분지원 연도소재지명칭주소운영주체
0국고보조 지원1992대전(둔산동)대전광역시둔산동 근로자종합복지회관대전 서구 둔산서로 84한국노총
1국고보조 지원1992광 양광양시근로자종합복지관광양시불로로123한국노총
2국고보조 지원1992문 막문막근로자종합복지관원주시 문막공단로42문막공단 운영협회
3국고보조 지원1993거 제거제시근로자가족복지회관거제시탑곡로75거제YWCA
4국고보조 지원1993성 남성남시근로자종합복지관성남시 중원구 순환로166한국노총
5국고보조 지원1993춘 천춘천시근로자종합복지관춘천시 후석로440번길9춘천 도시공사
6국고보조 지원1993완 주 (전북)전라북도근로자종합복지관완주군 봉동읍 과학로850-15완주군
7국고보조 지원1994진 주진주시근로자가족복지회관진주시 동진로263번길14진주YWCA
8국고보조 지원1994포 항 (호동관)포항시근로자종합복지관(호동관)포항시 남구 철강로388포항시
9국고보조 지원1994강 릉강릉시근로자종합복지관강릉시 율곡로3020한국노총
지원구분지원 연도소재지명칭주소운영주체
62분권교부세 배분2013충북 (청주)충청북도근로자종합복지관청주시 서원구 2순환로1818-39한국노총
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