Overview

Dataset statistics

Number of variables10
Number of observations107
Missing cells6
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.8 KiB
Average record size in memory84.2 B

Variable types

Categorical2
Text5
Numeric3

Dataset

Description취업지원기관 목록
Author경기도일자리재단
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=BQXSSSQUK2A3291XDJ5H32192146&infSeq=1

Alerts

정제우편번호 is highly overall correlated with 정제WGS84위도 and 1 other fieldsHigh correlation
정제WGS84위도 is highly overall correlated with 정제우편번호 and 1 other fieldsHigh correlation
정제WGS84경도 is highly overall correlated with 지역High correlation
지역 is highly overall correlated with 정제우편번호 and 2 other fieldsHigh correlation
정제도로명주소 has 3 (2.8%) missing valuesMissing
기관명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:36:54.272223
Analysis finished2023-12-10 22:36:55.717166
Duration1.44 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct6
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size988.0 B
여성 일자리
29 
고용센터
27 
노인일자리
24 
대학생 일자리
23 
제대군인 일자리
 
2

Length

Max length8
Median length7
Mean length5.5420561
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여성 일자리
2nd row여성 일자리
3rd row여성 일자리
4th row여성 일자리
5th row여성 일자리

Common Values

ValueCountFrequency (%)
여성 일자리 29
27.1%
고용센터 27
25.2%
노인일자리 24
22.4%
대학생 일자리 23
21.5%
제대군인 일자리 2
 
1.9%
중장년 일자리 2
 
1.9%

Length

2023-12-11T07:36:55.974705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:36:56.064162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일자리 56
34.4%
여성 29
17.8%
고용센터 27
16.6%
노인일자리 24
14.7%
대학생 23
14.1%
제대군인 2
 
1.2%
중장년 2
 
1.2%

지역
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size988.0 B
용인시
8 
수원시
8 
의정부시
 
6
성남시
 
6
화성시
 
6
Other values (23)
73 

Length

Max length4
Median length3
Mean length3.1028037
Min length3

Unique

Unique4 ?
Unique (%)3.7%

Sample

1st row오산시
2nd row용인시
3rd row의왕시
4th row의정부시
5th row이천시

Common Values

ValueCountFrequency (%)
용인시 8
 
7.5%
수원시 8
 
7.5%
의정부시 6
 
5.6%
성남시 6
 
5.6%
화성시 6
 
5.6%
오산시 5
 
4.7%
부천시 5
 
4.7%
안양시 5
 
4.7%
고양시 5
 
4.7%
시흥시 5
 
4.7%
Other values (18) 48
44.9%

Length

2023-12-11T07:36:56.163460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용인시 8
 
7.5%
수원시 8
 
7.5%
의정부시 6
 
5.6%
성남시 6
 
5.6%
화성시 6
 
5.6%
오산시 5
 
4.7%
부천시 5
 
4.7%
안양시 5
 
4.7%
고양시 5
 
4.7%
시흥시 5
 
4.7%
Other values (18) 48
44.9%

기관명
Text

UNIQUE 

Distinct107
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-11T07:36:56.372233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length9.4672897
Min length6

Characters and Unicode

Total characters1013
Distinct characters106
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)100.0%

Sample

1st row오산새일센터
2nd row용인새일센터
3rd row의왕새일센터
4th row의정부YWCA새일센터
5th row이천새일센터
ValueCountFrequency (%)
대학일자리플러스센터 23
 
17.6%
오산새일센터 1
 
0.8%
광주고용복지+센터 1
 
0.8%
아주대 1
 
0.8%
성결대 1
 
0.8%
단국대 1
 
0.8%
가천대 1
 
0.8%
여주고용복지센터 1
 
0.8%
의정부고용복지+센터 1
 
0.8%
수원고용복지+센터 1
 
0.8%
Other values (99) 99
75.6%
2023-12-11T07:36:56.701598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
센 83
 
8.2%
터 83
 
8.2%
일 54
 
5.3%
대 48
 
4.7%
용 31
 
3.1%
고 31
 
3.1%
새 29
 
2.9%
지 29
 
2.9%
시 29
 
2.9%
복 28
 
2.8%
Other values (96) 568
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 950
93.8%
Space Separator 24
 
2.4%
Math Symbol 23
 
2.3%
Uppercase Letter 10
 
1.0%
Open Punctuation 3
 
0.3%
Close Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
센 83
 
8.7%
터 83
 
8.7%
일 54
 
5.7%
대 48
 
5.1%
용 31
 
3.3%
고 31
 
3.3%
새 29
 
3.1%
지 29
 
3.1%
시 29
 
3.1%
복 28
 
2.9%
Other values (84) 505
53.2%
Uppercase Letter
ValueCountFrequency (%)
I 2
20.0%
C 2
20.0%
M 1
10.0%
T 1
10.0%
A 1
10.0%
W 1
10.0%
Y 1
10.0%
E 1
10.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Math Symbol
ValueCountFrequency (%)
+ 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 950
93.8%
Common 53
 
5.2%
Latin 10
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
센 83
 
8.7%
터 83
 
8.7%
일 54
 
5.7%
대 48
 
5.1%
용 31
 
3.3%
고 31
 
3.3%
새 29
 
3.1%
지 29
 
3.1%
시 29
 
3.1%
복 28
 
2.9%
Other values (84) 505
53.2%
Latin
ValueCountFrequency (%)
I 2
20.0%
C 2
20.0%
M 1
10.0%
T 1
10.0%
A 1
10.0%
W 1
10.0%
Y 1
10.0%
E 1
10.0%
Common
ValueCountFrequency (%)
24
45.3%
+ 23
43.4%
( 3
 
5.7%
) 3
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 950
93.8%
ASCII 63
 
6.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
센 83
 
8.7%
터 83
 
8.7%
일 54
 
5.7%
대 48
 
5.1%
용 31
 
3.3%
고 31
 
3.3%
새 29
 
3.1%
지 29
 
3.1%
시 29
 
3.1%
복 28
 
2.9%
Other values (84) 505
53.2%
ASCII
ValueCountFrequency (%)
24
38.1%
+ 23
36.5%
( 3
 
4.8%
) 3
 
4.8%
I 2
 
3.2%
C 2
 
3.2%
M 1
 
1.6%
T 1
 
1.6%
A 1
 
1.6%
W 1
 
1.6%
Other values (2) 2
 
3.2%

연락처
Text

Distinct105
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-11T07:36:56.914683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length9

Characters and Unicode

Total characters1284
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

Unique103 ?
Unique (%)96.3%

Sample

1st row031-8024-9861
2nd row031-324-8997
3rd row031-345-2681
4th row031-853-6333
5th row031-632-1982
ValueCountFrequency (%)
031-270-9900 2
 
1.9%
1666-9279 2
 
1.9%
031-670-5066 1
 
0.9%
031-560-5800 1
 
0.9%
031-219-2041 1
 
0.9%
031-467-8237 1
 
0.9%
031-8005-2514 1
 
0.9%
031-750-4787 1
 
0.9%
031-740-6790 1
 
0.9%
031-828-0900 1
 
0.9%
Other values (95) 95
88.8%
2023-12-11T07:36:57.221920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 233
18.1%
- 212
16.5%
3 163
12.7%
1 156
12.1%
2 95
7.4%
6 84
 
6.5%
9 81
 
6.3%
8 69
 
5.4%
7 67
 
5.2%
4 66
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1072
83.5%
Dash Punctuation 212
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 233
21.7%
3 163
15.2%
1 156
14.6%
2 95
8.9%
6 84
 
7.8%
9 81
 
7.6%
8 69
 
6.4%
7 67
 
6.2%
4 66
 
6.2%
5 58
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 212
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1284
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 233
18.1%
- 212
16.5%
3 163
12.7%
1 156
12.1%
2 95
7.4%
6 84
 
6.5%
9 81
 
6.3%
8 69
 
5.4%
7 67
 
5.2%
4 66
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1284
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 233
18.1%
- 212
16.5%
3 163
12.7%
1 156
12.1%
2 95
7.4%
6 84
 
6.5%
9 81
 
6.3%
8 69
 
5.4%
7 67
 
5.2%
4 66
 
5.1%

홈페이지
Text

Distinct102
Distinct (%)96.2%
Missing1
Missing (%)0.9%
Memory size988.0 B
2023-12-11T07:36:57.438737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length103
Median length41
Mean length32.716981
Min length16

Characters and Unicode

Total characters3468
Distinct characters46
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)93.4%

Sample

1st rowhttps://www.osan.go.kr/main.do
2nd rowhttp://www.yongin.go.kr/index.do
3rd rowhttp://www.uiwang.go.kr/index
4th rowhttp://www.ujbywca.or.kr/user/main/index.hpc
5th rowhttp://www.2000saeil.com/
ValueCountFrequency (%)
https://www.gjf.or.kr/web/gjf/main 3
 
2.8%
https://www.kycenter.or.kr/index.aspx 2
 
1.9%
https://www.vnet.go.kr/hm/infobbs.do 2
 
1.9%
https://career.kangnam.ac.kr 1
 
0.9%
https://job.dankook.ac.kr 1
 
0.9%
https://www.work.go.kr/yeoju/main.do 1
 
0.9%
https://www.work.go.kr/uijeongbu/main.do 1
 
0.9%
https://www.work.go.kr/suwon/main.do 1
 
0.9%
https://www.work.go.kr/seongnam/main.do 1
 
0.9%
https://www.work.go.kr/pocheon/main.do 1
 
0.9%
Other values (92) 92
86.8%
2023-12-11T07:36:57.784205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 383
 
11.0%
. 342
 
9.9%
w 294
 
8.5%
o 239
 
6.9%
t 236
 
6.8%
r 196
 
5.7%
n 166
 
4.8%
s 151
 
4.4%
k 145
 
4.2%
p 140
 
4.0%
Other values (36) 1176
33.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2583
74.5%
Other Punctuation 835
 
24.1%
Decimal Number 34
 
1.0%
Uppercase Letter 10
 
0.3%
Dash Punctuation 4
 
0.1%
Connector Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 294
 
11.4%
o 239
 
9.3%
t 236
 
9.1%
r 196
 
7.6%
n 166
 
6.4%
s 151
 
5.8%
k 145
 
5.6%
p 140
 
5.4%
h 134
 
5.2%
a 131
 
5.1%
Other values (15) 751
29.1%
Decimal Number
ValueCountFrequency (%)
2 6
17.6%
0 6
17.6%
1 5
14.7%
4 5
14.7%
8 4
11.8%
6 3
8.8%
3 2
 
5.9%
9 1
 
2.9%
7 1
 
2.9%
5 1
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/ 383
45.9%
. 342
41.0%
: 107
 
12.8%
# 2
 
0.2%
? 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
I 6
60.0%
M 2
 
20.0%
B 2
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2593
74.8%
Common 875
 
25.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 294
 
11.3%
o 239
 
9.2%
t 236
 
9.1%
r 196
 
7.6%
n 166
 
6.4%
s 151
 
5.8%
k 145
 
5.6%
p 140
 
5.4%
h 134
 
5.2%
a 131
 
5.1%
Other values (18) 761
29.3%
Common
ValueCountFrequency (%)
/ 383
43.8%
. 342
39.1%
: 107
 
12.2%
2 6
 
0.7%
0 6
 
0.7%
1 5
 
0.6%
4 5
 
0.6%
- 4
 
0.5%
8 4
 
0.5%
6 3
 
0.3%
Other values (8) 10
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3468
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 383
 
11.0%
. 342
 
9.9%
w 294
 
8.5%
o 239
 
6.9%
t 236
 
6.8%
r 196
 
5.7%
n 166
 
4.8%
s 151
 
4.4%
k 145
 
4.2%
p 140
 
4.0%
Other values (36) 1176
33.9%

정제도로명주소
Text

MISSING 

Distinct95
Distinct (%)91.3%
Missing3
Missing (%)2.8%
Memory size988.0 B
2023-12-11T07:36:58.013381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length22
Mean length18.192308
Min length14

Characters and Unicode

Total characters1892
Distinct characters141
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

Unique86 ?
Unique (%)82.7%

Sample

1st row경기도 오산시 경기동로 51
2nd row경기도 용인시 수지구 문정로7번길 15
3rd row경기도 의왕시 안양판교로 82
4th row경기도 의정부시 장곡로 606
5th row경기도 이천시 아리역로 1
ValueCountFrequency (%)
경기도 103
 
22.3%
수원시 8
 
1.7%
성남시 7
 
1.5%
용인시 7
 
1.5%
화성시 6
 
1.3%
고양시 6
 
1.3%
수정구 5
 
1.1%
의정부시 5
 
1.1%
안양시 5
 
1.1%
오산시 5
 
1.1%
Other values (210) 304
65.9%
2023-12-11T07:36:58.381030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
357
18.9%
기 112
 
5.9%
경 111
 
5.9%
시 107
 
5.7%
도 103
 
5.4%
로 95
 
5.0%
1 70
 
3.7%
3 43
 
2.3%
구 42
 
2.2%
2 39
 
2.1%
Other values (131) 813
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1194
63.1%
Space Separator 357
 
18.9%
Decimal Number 329
 
17.4%
Dash Punctuation 12
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 112
 
9.4%
경 111
 
9.3%
시 107
 
9.0%
도 103
 
8.6%
로 95
 
8.0%
구 42
 
3.5%
길 30
 
2.5%
안 25
 
2.1%
성 24
 
2.0%
양 24
 
2.0%
Other values (119) 521
43.6%
Decimal Number
ValueCountFrequency (%)
1 70
21.3%
3 43
13.1%
2 39
11.9%
4 38
11.6%
5 29
8.8%
6 27
 
8.2%
8 25
 
7.6%
7 21
 
6.4%
9 21
 
6.4%
0 16
 
4.9%
Space Separator
ValueCountFrequency (%)
357
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1194
63.1%
Common 698
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 112
 
9.4%
경 111
 
9.3%
시 107
 
9.0%
도 103
 
8.6%
로 95
 
8.0%
구 42
 
3.5%
길 30
 
2.5%
안 25
 
2.1%
성 24
 
2.0%
양 24
 
2.0%
Other values (119) 521
43.6%
Common
ValueCountFrequency (%)
357
51.1%
1 70
 
10.0%
3 43
 
6.2%
2 39
 
5.6%
4 38
 
5.4%
5 29
 
4.2%
6 27
 
3.9%
8 25
 
3.6%
7 21
 
3.0%
9 21
 
3.0%
Other values (2) 28
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1194
63.1%
ASCII 698
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
357
51.1%
1 70
 
10.0%
3 43
 
6.2%
2 39
 
5.6%
4 38
 
5.4%
5 29
 
4.2%
6 27
 
3.9%
8 25
 
3.6%
7 21
 
3.0%
9 21
 
3.0%
Other values (2) 28
 
4.0%
Hangul
ValueCountFrequency (%)
기 112
 
9.4%
경 111
 
9.3%
시 107
 
9.0%
도 103
 
8.6%
로 95
 
8.0%
구 42
 
3.5%
길 30
 
2.5%
안 25
 
2.1%
성 24
 
2.0%
양 24
 
2.0%
Other values (119) 521
43.6%

정제지번주소
Text

Distinct104
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size988.0 B
2023-12-11T07:36:58.618252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length35
Mean length25.915888
Min length17

Characters and Unicode

Total characters2773
Distinct characters198
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

Unique101 ?
Unique (%)94.4%

Sample

1st row경기도 오산시 오산동 34-5번지 3층
2nd row경기도 용인시 수지구 풍덕천동 1086번지 (용인시 평생학습관 1층)
3rd row경기도 의왕시 포일동 686번지 포일어울림센터 4층
4th row경기도 의정부시 신곡동 762-2번지
5th row경기도 이천시 창전동 440-3번지
ValueCountFrequency (%)
경기도 105
 
17.6%
1층 14
 
2.3%
2층 11
 
1.8%
용인시 8
 
1.3%
3층 8
 
1.3%
수원시 8
 
1.3%
성남시 7
 
1.2%
고양시 6
 
1.0%
화성시 6
 
1.0%
의정부시 6
 
1.0%
Other values (293) 419
70.1%
2023-12-11T07:36:58.930957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
491
 
17.7%
기 114
 
4.1%
지 113
 
4.1%
시 112
 
4.0%
경 109
 
3.9%
1 107
 
3.9%
도 107
 
3.9%
동 106
 
3.8%
번 105
 
3.8%
- 74
 
2.7%
Other values (188) 1335
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1689
60.9%
Decimal Number 494
 
17.8%
Space Separator 491
 
17.7%
Dash Punctuation 74
 
2.7%
Uppercase Letter 13
 
0.5%
Other Punctuation 4
 
0.1%
Math Symbol 4
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 114
 
6.7%
지 113
 
6.7%
시 112
 
6.6%
경 109
 
6.5%
도 107
 
6.3%
동 106
 
6.3%
번 105
 
6.2%
층 49
 
2.9%
구 46
 
2.7%
양 28
 
1.7%
Other values (164) 800
47.4%
Decimal Number
ValueCountFrequency (%)
1 107
21.7%
2 58
11.7%
4 56
11.3%
3 51
10.3%
6 49
9.9%
0 46
9.3%
5 44
8.9%
9 31
 
6.3%
7 27
 
5.5%
8 25
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
B 5
38.5%
K 2
 
15.4%
C 2
 
15.4%
D 1
 
7.7%
U 1
 
7.7%
G 1
 
7.7%
T 1
 
7.7%
Math Symbol
ValueCountFrequency (%)
~ 3
75.0%
+ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
491
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1689
60.9%
Common 1071
38.6%
Latin 13
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 114
 
6.7%
지 113
 
6.7%
시 112
 
6.6%
경 109
 
6.5%
도 107
 
6.3%
동 106
 
6.3%
번 105
 
6.2%
층 49
 
2.9%
구 46
 
2.7%
양 28
 
1.7%
Other values (164) 800
47.4%
Common
ValueCountFrequency (%)
491
45.8%
1 107
 
10.0%
- 74
 
6.9%
2 58
 
5.4%
4 56
 
5.2%
3 51
 
4.8%
6 49
 
4.6%
0 46
 
4.3%
5 44
 
4.1%
9 31
 
2.9%
Other values (7) 64
 
6.0%
Latin
ValueCountFrequency (%)
B 5
38.5%
K 2
 
15.4%
C 2
 
15.4%
D 1
 
7.7%
U 1
 
7.7%
G 1
 
7.7%
T 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1689
60.9%
ASCII 1084
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
491
45.3%
1 107
 
9.9%
- 74
 
6.8%
2 58
 
5.4%
4 56
 
5.2%
3 51
 
4.7%
6 49
 
4.5%
0 46
 
4.2%
5 44
 
4.1%
9 31
 
2.9%
Other values (14) 77
 
7.1%
Hangul
ValueCountFrequency (%)
기 114
 
6.7%
지 113
 
6.7%
시 112
 
6.6%
경 109
 
6.5%
도 107
 
6.3%
동 106
 
6.3%
번 105
 
6.2%
층 49
 
2.9%
구 46
 
2.7%
양 28
 
1.7%
Other values (164) 800
47.4%

정제우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct95
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14949.047
Minimum10020
Maximum61240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:36:59.051517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10020
5-th percentile10369.1
Q112002.5
median14628
Q316922
95-th percentile18306.9
Maximum61240
Range51220
Interquartile range (IQR)4919.5

Descriptive statistics

Standard deviation5218.496
Coefficient of variation (CV)0.34908554
Kurtosis58.857394
Mean14949.047
Median Absolute Deviation (MAD)2391
Skewness6.6262331
Sum1599548
Variance27232700
MonotonicityNot monotonic
2023-12-11T07:36:59.160105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18131 2
 
1.9%
11650 2
 
1.9%
10930 2
 
1.9%
13120 2
 
1.9%
15829 2
 
1.9%
11498 2
 
1.9%
12237 2
 
1.9%
10083 2
 
1.9%
16922 2
 
1.9%
11149 2
 
1.9%
Other values (85) 87
81.3%
ValueCountFrequency (%)
10020 1
0.9%
10083 2
1.9%
10111 1
0.9%
10222 1
0.9%
10364 1
0.9%
10381 1
0.9%
10497 1
0.9%
10540 2
1.9%
10923 1
0.9%
10930 2
1.9%
ValueCountFrequency (%)
61240 1
0.9%
18372 1
0.9%
18331 1
0.9%
18330 1
0.9%
18323 1
0.9%
18309 1
0.9%
18302 1
0.9%
18131 2
1.9%
18119 1
0.9%
18112 1
0.9%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)91.5%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean37.40275
Minimum35.155392
Maximum37.898815
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:36:59.262556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.155392
5-th percentile37.056052
Q137.278781
median37.379191
Q337.603535
95-th percentile37.765393
Maximum37.898815
Range2.7434223
Interquartile range (IQR)0.32475481

Descriptive statistics

Standard deviation0.30745094
Coefficient of variation (CV)0.008220009
Kurtosis26.339941
Mean37.40275
Median Absolute Deviation (MAD)0.12479255
Skewness-3.5966225
Sum3964.6915
Variance0.09452608
MonotonicityNot monotonic
2023-12-11T07:36:59.365368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.1588864144 2
 
1.9%
37.3617955681 2
 
1.9%
37.2933822755 2
 
1.9%
37.6336759654 2
 
1.9%
37.7361993437 2
 
1.9%
37.7862395519 2
 
1.9%
37.6446988777 2
 
1.9%
37.4496437867 2
 
1.9%
37.5990111999 2
 
1.9%
37.892615025 1
 
0.9%
Other values (87) 87
81.3%
ValueCountFrequency (%)
35.1553923885 1
0.9%
36.9912208605 1
0.9%
37.0012481351 1
0.9%
37.0064435119 1
0.9%
37.0124058703 1
0.9%
37.0532690732 1
0.9%
37.0644002135 1
0.9%
37.1535710263 1
0.9%
37.1588864144 2
1.9%
37.1792651749 1
0.9%
ValueCountFrequency (%)
37.8988146838 1
0.9%
37.892615025 1
0.9%
37.8904660485 1
0.9%
37.7862395519 2
1.9%
37.765559326 1
0.9%
37.7648959643 1
0.9%
37.7577233671 1
0.9%
37.7499767569 1
0.9%
37.7451070911 1
0.9%
37.7387069086 1
0.9%

정제WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)91.5%
Missing1
Missing (%)0.9%
Infinite0
Infinite (%)0.0%
Mean127.02037
Minimum126.5466
Maximum127.6369
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:36:59.482836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5466
5-th percentile126.74252
Q1126.90206
median127.03237
Q3127.127
95-th percentile127.41966
Maximum127.6369
Range1.090298
Interquartile range (IQR)0.22493414

Descriptive statistics

Standard deviation0.19803707
Coefficient of variation (CV)0.0015590969
Kurtosis1.0547224
Mean127.02037
Median Absolute Deviation (MAD)0.098729562
Skewness0.57852948
Sum13464.16
Variance0.039218681
MonotonicityNot monotonic
2023-12-11T07:36:59.614502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0773098833 2
 
1.9%
126.9358413859 2
 
1.9%
127.1080702932 2
 
1.9%
127.2078056477 2
 
1.9%
127.0400241431 2
 
1.9%
127.0467327194 2
 
1.9%
126.6671052236 2
 
1.9%
127.1269964861 2
 
1.9%
126.8641707819 2
 
1.9%
127.199790646 1
 
0.9%
Other values (87) 87
81.3%
ValueCountFrequency (%)
126.54660312 1
0.9%
126.6671052236 2
1.9%
126.7226202082 1
0.9%
126.7365612783 1
0.9%
126.7423886716 1
0.9%
126.7429250165 1
0.9%
126.7493880065 1
0.9%
126.7625175247 1
0.9%
126.7659366331 1
0.9%
126.7739395836 1
0.9%
ValueCountFrequency (%)
127.636901133 1
0.9%
127.6358927578 1
0.9%
127.501425427 1
0.9%
127.4496058904 1
0.9%
127.4480946748 1
0.9%
127.4407183633 1
0.9%
127.3564940083 1
0.9%
127.2694243638 1
0.9%
127.267844096 1
0.9%
127.262234737 1
0.9%

Interactions

2023-12-11T07:36:55.193803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:54.749634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:54.978448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:55.265790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:54.818688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:55.052305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:55.343263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:54.888114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:36:55.124799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:36:59.688261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분지역정제도로명주소정제우편번호정제WGS84위도정제WGS84경도
구분1.0000.0000.9740.0000.0000.000
지역0.0001.0000.9970.9920.9890.944
정제도로명주소0.9740.9971.0001.0001.0001.000
정제우편번호0.0000.9921.0001.0000.8560.567
정제WGS84위도0.0000.9891.0000.8561.0000.561
정제WGS84경도0.0000.9441.0000.5670.5611.000
2023-12-11T07:36:59.785288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분지역
구분1.0000.000
지역0.0001.000
2023-12-11T07:36:59.867082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정제우편번호정제WGS84위도정제WGS84경도구분지역
정제우편번호1.000-0.9260.2520.0000.853
정제WGS84위도-0.9261.000-0.2780.0000.839
정제WGS84경도0.252-0.2781.0000.0000.653
구분0.0000.0000.0001.0000.000
지역0.8530.8390.6530.0001.000

Missing values

2023-12-11T07:36:55.444894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:36:55.567350image/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.
2023-12-11T07:36:55.664819image/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

구분지역기관명연락처홈페이지정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
0여성 일자리오산시오산새일센터031-8024-9861https://www.osan.go.kr/main.do경기도 오산시 경기동로 51경기도 오산시 오산동 34-5번지 3층1813137.158886127.07731
1여성 일자리용인시용인새일센터031-324-8997http://www.yongin.go.kr/index.do경기도 용인시 수지구 문정로7번길 15경기도 용인시 수지구 풍덕천동 1086번지 (용인시 평생학습관 1층)1684137.320544127.095413
2여성 일자리의왕시의왕새일센터031-345-2681http://www.uiwang.go.kr/index경기도 의왕시 안양판교로 82경기도 의왕시 포일동 686번지 포일어울림센터 4층1601437.396208126.982673
3여성 일자리의정부시의정부YWCA새일센터031-853-6333http://www.ujbywca.or.kr/user/main/index.hpc경기도 의정부시 장곡로 606경기도 의정부시 신곡동 762-2번지1177537.749977127.070054
4여성 일자리이천시이천새일센터031-632-1982http://www.2000saeil.com/경기도 이천시 아리역로 1경기도 이천시 창전동 440-3번지1735637.285664127.448095
5여성 일자리파주시파주새일센터031-942-0281https://blog.naver.com/pjwoman경기도 파주시 금정로 28경기도 파주시 금촌동 773-7번지 2층1092337.757723126.776287
6여성 일자리평택시평택새일센터031-8024-7411https://www.pyeongtaek.go.kr/newjob/main.do경기도 평택시 이충로 84-6경기도 평택시 이충동 591번지 평생학습센터 2층1773237.0644127.067464
7여성 일자리화성시화성새일센터031-267-8714https://www.hswf.or.kr/womanjob/212경기도 화성시 태안로 145경기도 화성시 병점동 734번지 유앤아이센터 4층1837237.202962127.033262
8제대군인 일자리수원시경기남부제대군인지원센터1666-9279https://www.vnet.go.kr/hm/InfoBbs.do경기도 수원시 장안구 조원로 8경기도 수원시 장안구 영화동 15-5번지 경기남부보훈지청 별관 2층1627537.295863127.022636
9중장년 일자리부천시경기도신중년일자리센터031-270-6660https://www.gjf.or.kr/web/newmiddle/main#경기도 부천시 부천로 139경기도 부천시 심곡동 87-4번지 퍼스트뷰 2층1457637.496717126.785227
구분지역기관명연락처홈페이지정제도로명주소정제지번주소정제우편번호정제WGS84위도정제WGS84경도
97여성 일자리시흥시시흥새일센터(산단형)031-310-6021<NA>경기도 군포시 청백리길 6경기도 군포시 금정동 844번지 여성비전센터 1층1582937.361796126.935841
98여성 일자리안양시안양새일센터031-453-4360https://www.anyangcenter.or.kr/경기도 안양시 동안구 경수대로 594경기도 안양시 동안구 호계동 985-19번지1410937.375658126.956926
99여성 일자리수원시영통새일센터031-206-1919https://vocationplus.com/경기도 수원시 영통구 반달로7번길 40경기도 수원시 영통구 영통동 998-1번지 평익빌딩 10층1670437.253544127.075214
100여성 일자리고양시고양MICE새일센터(경력개발형)031-912-8668https://www.kycenter.or.kr/index.aspx경기도 고양시 일산서구 강성로 247경기도 고양시 일산서구 대화동 2202-1번지 명진프라자빌딩 8~9층1038137.676112126.749388
101여성 일자리구리시구리새일센터031-550-8391https://www.guri.go.kr/www/index.do경기도 구리시 아차산로 453경기도 구리시 교문동 390번지 여성행복센터 구리여성새로일하기센터 행복동 1층1195437.595547127.12986
102여성 일자리김포시김포새일센터031-996-7607https://www.gimpo.go.kr/portal/index.do경기도 김포시 김포한강4로 125경기도 김포시 장기동 1604번지 4층1008337.644699126.667105
103여성 일자리부천시부천새일센터032-326-3004http://www.ilwoman.or.kr/경기도 부천시 석천로 171경기도 부천시 중동 1162-5번지 중동프라자 5층1454637.502995126.762518
104여성 일자리시흥시시흥새일센터031-313-8219http://www.shwomen.or.kr/경기도 시흥시 비둘기공원7길 51경기도 시흥시 대야동 546-1번지 대명프라자 7층1491237.44163126.791901
105여성 일자리안산시안산새일센터031-439-2069http://www.ansanwomen.or.kr/경기도 안산시 단원구 광덕대로 271경기도 안산시 단원구 고잔동 523-8번지 3층1535337.320898126.829987
106여성 일자리양주시양주새일센터031-849-2350http://www.yangju.go.kr/vision/index.do경기도 양주시 부흥로 1533경기도 양주시 남방동 1-1번지 양주고용복지플러스센터 내1149837.78624127.046733