Overview

Dataset statistics

Number of variables5
Number of observations45
Missing cells2
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory43.9 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description국내에 체류하고 있는 고용허가제 외국인근로자(E-9, H-2)에게 체류지원서비스를 제공하기 위한 외국인노동자지원센터 현황입니다.
URLhttps://www.data.go.kr/data/3038226/fileData.do

Alerts

순번 is highly overall correlated with 유형High correlation
유형 is highly overall correlated with 순번High correlation
소재지 has 1 (2.2%) missing valuesMissing
연락처 has 1 (2.2%) missing valuesMissing
순번 has unique valuesUnique
기관명(거점센터 운영기관) has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:39:12.495721
Analysis finished2023-12-12 12:39:13.180536
Duration0.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23
Minimum1
Maximum45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T21:39:13.270993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.2
Q112
median23
Q334
95-th percentile42.8
Maximum45
Range44
Interquartile range (IQR)22

Descriptive statistics

Standard deviation13.133926
Coefficient of variation (CV)0.57104024
Kurtosis-1.2
Mean23
Median Absolute Deviation (MAD)11
Skewness0
Sum1035
Variance172.5
MonotonicityStrictly increasing
2023-12-12T21:39:13.466089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
1 1
 
2.2%
35 1
 
2.2%
26 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%
36 1
2.2%

유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
소지역
36 
거점
9 

Length

Max length3
Median length3
Mean length2.8
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소지역 36
80.0%
거점 9
 
20.0%

Length

2023-12-12T21:39:13.672612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:39:13.809424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소지역 36
80.0%
거점 9
 
20.0%

기관명(거점센터 운영기관)
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T21:39:14.044909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length27
Mean length15.4
Min length6

Characters and Unicode

Total characters693
Distinct characters127
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row한국 외국인노동자지원센터((사)지구촌사랑나눔)
2nd row의정부 외국인노동자지원센터(신한대학교 산학협력단)
3rd row김해 외국인노동자지원센터(인제대학교)
4th row창원 외국인노동자지원센터(사회복지법인 통도사자비원)
5th row인천 외국인노동자지원센터(인천경총 및 한국노총 공동수급체)
ValueCountFrequency (%)
공동수급체 3
 
4.2%
및 3
 
4.2%
사)외국인근로자문화센터 2
 
2.8%
한국노총 2
 
2.8%
한국 1
 
1.4%
사)외국인과동행 1
 
1.4%
대전다문화센터 1
 
1.4%
대전이주외국인종합복지관 1
 
1.4%
사)홍성이주민센터 1
 
1.4%
아산이주근로자센터 1
 
1.4%
Other values (55) 55
77.5%
2023-12-12T21:39:14.466233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 33
 
4.8%
인 32
 
4.6%
터 32
 
4.6%
센 32
 
4.6%
( 30
 
4.3%
) 30
 
4.3%
지 27
 
3.9%
외 26
 
3.8%
26
 
3.8%
자 22
 
3.2%
Other values (117) 403
58.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 601
86.7%
Open Punctuation 30
 
4.3%
Close Punctuation 30
 
4.3%
Space Separator 26
 
3.8%
Uppercase Letter 6
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 33
 
5.5%
인 32
 
5.3%
터 32
 
5.3%
센 32
 
5.3%
지 27
 
4.5%
외 26
 
4.3%
자 22
 
3.7%
주 22
 
3.7%
사 21
 
3.5%
원 20
 
3.3%
Other values (108) 334
55.6%
Uppercase Letter
ValueCountFrequency (%)
E 1
16.7%
X 1
16.7%
O 1
16.7%
D 1
16.7%
U 1
16.7%
S 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 601
86.7%
Common 86
 
12.4%
Latin 6
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 33
 
5.5%
인 32
 
5.3%
터 32
 
5.3%
센 32
 
5.3%
지 27
 
4.5%
외 26
 
4.3%
자 22
 
3.7%
주 22
 
3.7%
사 21
 
3.5%
원 20
 
3.3%
Other values (108) 334
55.6%
Latin
ValueCountFrequency (%)
E 1
16.7%
X 1
16.7%
O 1
16.7%
D 1
16.7%
U 1
16.7%
S 1
16.7%
Common
ValueCountFrequency (%)
( 30
34.9%
) 30
34.9%
26
30.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 601
86.7%
ASCII 92
 
13.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 33
 
5.5%
인 32
 
5.3%
터 32
 
5.3%
센 32
 
5.3%
지 27
 
4.5%
외 26
 
4.3%
자 22
 
3.7%
주 22
 
3.7%
사 21
 
3.5%
원 20
 
3.3%
Other values (108) 334
55.6%
ASCII
ValueCountFrequency (%)
( 30
32.6%
) 30
32.6%
26
28.3%
E 1
 
1.1%
X 1
 
1.1%
O 1
 
1.1%
D 1
 
1.1%
U 1
 
1.1%
S 1
 
1.1%

소재지
Text

MISSING 

Distinct39
Distinct (%)88.6%
Missing1
Missing (%)2.2%
Memory size492.0 B
2023-12-12T21:39:14.709160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.1590909
Min length5

Characters and Unicode

Total characters271
Distinct characters56
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

Unique36 ?
Unique (%)81.8%

Sample

1st row서울 구로구
2nd row경기 의정부시
3rd row경남 김해시
4th row경남 창원시
5th row인천 남동구
ValueCountFrequency (%)
경기 12
 
13.6%
경남 5
 
5.7%
전남 4
 
4.5%
광산구 4
 
4.5%
광주 4
 
4.5%
충남 3
 
3.4%
경북 3
 
3.4%
대전 2
 
2.3%
의정부시 2
 
2.3%
안산시 2
 
2.3%
Other values (42) 47
53.4%
2023-12-12T21:39:15.096352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50
18.5%
시 30
 
11.1%
경 21
 
7.7%
남 14
 
5.2%
구 13
 
4.8%
기 12
 
4.4%
주 12
 
4.4%
산 11
 
4.1%
광 9
 
3.3%
전 9
 
3.3%
Other values (46) 90
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 221
81.5%
Space Separator 50
 
18.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 30
 
13.6%
경 21
 
9.5%
남 14
 
6.3%
구 13
 
5.9%
기 12
 
5.4%
주 12
 
5.4%
산 11
 
5.0%
광 9
 
4.1%
전 9
 
4.1%
북 7
 
3.2%
Other values (45) 83
37.6%
Space Separator
ValueCountFrequency (%)
50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 221
81.5%
Common 50
 
18.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 30
 
13.6%
경 21
 
9.5%
남 14
 
6.3%
구 13
 
5.9%
기 12
 
5.4%
주 12
 
5.4%
산 11
 
5.0%
광 9
 
4.1%
전 9
 
4.1%
북 7
 
3.2%
Other values (45) 83
37.6%
Common
ValueCountFrequency (%)
50
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 221
81.5%
ASCII 50
 
18.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50
100.0%
Hangul
ValueCountFrequency (%)
시 30
 
13.6%
경 21
 
9.5%
남 14
 
6.3%
구 13
 
5.9%
기 12
 
5.4%
주 12
 
5.4%
산 11
 
5.0%
광 9
 
4.1%
전 9
 
4.1%
북 7
 
3.2%
Other values (45) 83
37.6%

연락처
Text

MISSING 

Distinct44
Distinct (%)100.0%
Missing1
Missing (%)2.2%
Memory size492.0 B
2023-12-12T21:39:15.387756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.977273
Min length9

Characters and Unicode

Total characters527
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

Unique44 ?
Unique (%)100.0%

Sample

1st row02-6900-8000
2nd row031-838-9111
3rd row055-338-2727
4th row055-253-5270
5th row032-431-5757
ValueCountFrequency (%)
02-6900-8000 1
 
2.3%
031-838-9111 1
 
2.3%
041-631-2310 1
 
2.3%
042-631-6242 1
 
2.3%
042-543-1191 1
 
2.3%
054-291-0191 1
 
2.3%
054-705-1828 1
 
2.3%
054-458-0755 1
 
2.3%
055-275-8203 1
 
2.3%
055-763-0707 1
 
2.3%
Other values (34) 34
77.3%
2023-12-12T21:39:15.826516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 87
16.5%
0 79
15.0%
1 62
11.8%
5 49
9.3%
2 48
9.1%
3 42
8.0%
4 38
7.2%
7 33
 
6.3%
6 31
 
5.9%
9 29
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 440
83.5%
Dash Punctuation 87
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 79
18.0%
1 62
14.1%
5 49
11.1%
2 48
10.9%
3 42
9.5%
4 38
8.6%
7 33
7.5%
6 31
 
7.0%
9 29
 
6.6%
8 29
 
6.6%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 527
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 87
16.5%
0 79
15.0%
1 62
11.8%
5 49
9.3%
2 48
9.1%
3 42
8.0%
4 38
7.2%
7 33
 
6.3%
6 31
 
5.9%
9 29
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 527
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 87
16.5%
0 79
15.0%
1 62
11.8%
5 49
9.3%
2 48
9.1%
3 42
8.0%
4 38
7.2%
7 33
 
6.3%
6 31
 
5.9%
9 29
 
5.5%

Interactions

2023-12-12T21:39:12.792014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:39:15.945044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번유형기관명(거점센터 운영기관)소재지연락처
순번1.0001.0001.0000.9491.000
유형1.0001.0001.0000.5681.000
기관명(거점센터 운영기관)1.0001.0001.0001.0001.000
소재지0.9490.5681.0001.0001.000
연락처1.0001.0001.0001.0001.000
2023-12-12T21:39:16.044374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번유형
순번1.0000.902
유형0.9021.000

Missing values

2023-12-12T21:39:12.925647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:39:13.041496image/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.
2023-12-12T21:39:13.136693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

순번유형기관명(거점센터 운영기관)소재지연락처
01거점한국 외국인노동자지원센터((사)지구촌사랑나눔)서울 구로구02-6900-8000
12거점의정부 외국인노동자지원센터(신한대학교 산학협력단)경기 의정부시031-838-9111
23거점김해 외국인노동자지원센터(인제대학교)경남 김해시055-338-2727
34거점창원 외국인노동자지원센터(사회복지법인 통도사자비원)경남 창원시055-253-5270
45거점인천 외국인노동자지원센터(인천경총 및 한국노총 공동수급체)인천 남동구032-431-5757
56거점대구 외국인노동자지원센터(대구경총 및 한국노총 공동수급체)대구 달성군053-654-9700
67거점천안 외국인노동자지원센터((재)기독교대한감리회유지재단)충남 천안시041-411-7000
78거점광주 외국인노동자지원센터((재)한국능력개발원 및 광주외국인복지센터 공동수급체)광주 광산구062-946-1199
89거점양산 외국인노동자지원센터((사)희망웅상)경남 양산시055-912-0255
910소지역(사)한국이주근로자복지회서울 관악02-858-4118
순번유형기관명(거점센터 운영기관)소재지연락처
3536소지역전주시다문화가족지원센터광주 광산구062-943-8930
3637소지역(사)외국인근로자문화센터광주 광산구062-224-7448
3738소지역아시아인권문화재단광주 광산구062-959-9335
3839소지역광주이주민지원센터전남 순천시061-724-1127
3940소지역로드월드비젼전남 여수시061-644-3927
4041소지역여수외국인근로자문화센터전남 영암군061-462-8389
4142소지역전남목포영암외국인근로자문화센터전남 목포시061-272-1560
4243소지역(사)전남이주민통합지원센터강원 원주시070-7521-8097
4344소지역(사)함께하는공동체제주 제주시064-712-1141
4445소지역(사)제주외국인평화공동체<NA><NA>