Overview

Dataset statistics

Number of variables6
Number of observations64
Missing cells18
Missing cells (%)4.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory51.1 B

Variable types

Numeric1
Text4
Categorical1

Dataset

Description인천광역시 계양구 관내 직업소개소 현황에 대한 데이터로, 연번, 기관명, 대표자명, 전화번호, 소재지 주소, 비용(유료/무료) 등을 제공합니다.
Author인천광역시 계양구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15039186&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 비용High correlation
비용 is highly overall correlated with 연번High correlation
비용 is highly imbalanced (66.3%)Imbalance
전화번호 has 17 (26.6%) missing valuesMissing
소재지 has 1 (1.6%) missing valuesMissing
연번 has unique valuesUnique
기관명 has unique valuesUnique

Reproduction

Analysis started2024-01-28 10:34:33.716544
Analysis finished2024-01-28 10:34:34.269720
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct64
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.5
Minimum1
Maximum64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2024-01-28T19:34:34.322013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.15
Q116.75
median32.5
Q348.25
95-th percentile60.85
Maximum64
Range63
Interquartile range (IQR)31.5

Descriptive statistics

Standard deviation18.618987
Coefficient of variation (CV)0.5728919
Kurtosis-1.2
Mean32.5
Median Absolute Deviation (MAD)16
Skewness0
Sum2080
Variance346.66667
MonotonicityStrictly increasing
2024-01-28T19:34:34.423512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.6%
34 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
42 1
 
1.6%
43 1
 
1.6%
Other values (54) 54
84.4%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
64 1
1.6%
63 1
1.6%
62 1
1.6%
61 1
1.6%
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%

기관명
Text

UNIQUE 

Distinct64
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-01-28T19:34:34.616159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length7.625
Min length4

Characters and Unicode

Total characters488
Distinct characters166
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)100.0%

Sample

1st row제일인력개발
2nd row통일인력개발
3rd row소망여성인력
4th row한마음인력개발직업소개소
5th row삼천리인력직업소개소
ValueCountFrequency (%)
직업소개소 2
 
2.5%
제일인력개발 1
 
1.3%
주)한팀 1
 
1.3%
새마을인력 1
 
1.3%
믿음건설인력 1
 
1.3%
계양인력개발 1
 
1.3%
팔도인력 1
 
1.3%
english(김치잉글리쉬 1
 
1.3%
kimchi 1
 
1.3%
인력 1
 
1.3%
Other values (68) 68
86.1%
2024-01-28T19:34:34.916819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 47
 
9.6%
력 37
 
7.6%
소 29
 
5.9%
개 28
 
5.7%
업 16
 
3.3%
15
 
3.1%
발 13
 
2.7%
직 13
 
2.7%
사 8
 
1.6%
리 7
 
1.4%
Other values (156) 275
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 442
90.6%
Space Separator 15
 
3.1%
Lowercase Letter 10
 
2.0%
Uppercase Letter 7
 
1.4%
Open Punctuation 5
 
1.0%
Close Punctuation 5
 
1.0%
Decimal Number 3
 
0.6%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 47
 
10.6%
력 37
 
8.4%
소 29
 
6.6%
개 28
 
6.3%
업 16
 
3.6%
발 13
 
2.9%
직 13
 
2.9%
사 8
 
1.8%
리 7
 
1.6%
파 6
 
1.4%
Other values (136) 238
53.8%
Lowercase Letter
ValueCountFrequency (%)
i 3
30.0%
h 2
20.0%
l 1
 
10.0%
g 1
 
10.0%
n 1
 
10.0%
s 1
 
10.0%
m 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
K 2
28.6%
C 1
14.3%
E 1
14.3%
R 1
14.3%
H 1
14.3%
O 1
14.3%
Decimal Number
ValueCountFrequency (%)
7 1
33.3%
3 1
33.3%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 442
90.6%
Common 29
 
5.9%
Latin 17
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 47
 
10.6%
력 37
 
8.4%
소 29
 
6.6%
개 28
 
6.3%
업 16
 
3.6%
발 13
 
2.9%
직 13
 
2.9%
사 8
 
1.8%
리 7
 
1.6%
파 6
 
1.4%
Other values (136) 238
53.8%
Latin
ValueCountFrequency (%)
i 3
17.6%
K 2
11.8%
h 2
11.8%
l 1
 
5.9%
g 1
 
5.9%
C 1
 
5.9%
E 1
 
5.9%
n 1
 
5.9%
s 1
 
5.9%
m 1
 
5.9%
Other values (3) 3
17.6%
Common
ValueCountFrequency (%)
15
51.7%
( 5
 
17.2%
) 5
 
17.2%
7 1
 
3.4%
. 1
 
3.4%
3 1
 
3.4%
2 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 442
90.6%
ASCII 46
 
9.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 47
 
10.6%
력 37
 
8.4%
소 29
 
6.6%
개 28
 
6.3%
업 16
 
3.6%
발 13
 
2.9%
직 13
 
2.9%
사 8
 
1.8%
리 7
 
1.6%
파 6
 
1.4%
Other values (136) 238
53.8%
ASCII
ValueCountFrequency (%)
15
32.6%
( 5
 
10.9%
) 5
 
10.9%
i 3
 
6.5%
K 2
 
4.3%
h 2
 
4.3%
l 1
 
2.2%
g 1
 
2.2%
C 1
 
2.2%
E 1
 
2.2%
Other values (10) 10
21.7%

대표자명
Text

Distinct63
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size644.0 B
2024-01-28T19:34:35.114201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters192
Distinct characters88
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)96.9%

Sample

1st row임중재
2nd row황복연
3rd row서미경
4th row서현정
5th row박홍주
ValueCountFrequency (%)
김정원 2
 
3.1%
문용대 1
 
1.6%
정현수 1
 
1.6%
김동훈 1
 
1.6%
조재천 1
 
1.6%
이덕주 1
 
1.6%
박경자 1
 
1.6%
박상욱 1
 
1.6%
권도형 1
 
1.6%
박예선 1
 
1.6%
Other values (53) 53
82.8%
2024-01-28T19:34:35.403138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 14
 
7.3%
이 10
 
5.2%
정 8
 
4.2%
경 6
 
3.1%
희 6
 
3.1%
박 6
 
3.1%
조 4
 
2.1%
호 4
 
2.1%
현 4
 
2.1%
원 4
 
2.1%
Other values (78) 126
65.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 192
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 14
 
7.3%
이 10
 
5.2%
정 8
 
4.2%
경 6
 
3.1%
희 6
 
3.1%
박 6
 
3.1%
조 4
 
2.1%
호 4
 
2.1%
현 4
 
2.1%
원 4
 
2.1%
Other values (78) 126
65.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 192
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 14
 
7.3%
이 10
 
5.2%
정 8
 
4.2%
경 6
 
3.1%
희 6
 
3.1%
박 6
 
3.1%
조 4
 
2.1%
호 4
 
2.1%
현 4
 
2.1%
원 4
 
2.1%
Other values (78) 126
65.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 192
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 14
 
7.3%
이 10
 
5.2%
정 8
 
4.2%
경 6
 
3.1%
희 6
 
3.1%
박 6
 
3.1%
조 4
 
2.1%
호 4
 
2.1%
현 4
 
2.1%
원 4
 
2.1%
Other values (78) 126
65.6%

전화번호
Text

MISSING 

Distinct47
Distinct (%)100.0%
Missing17
Missing (%)26.6%
Memory size644.0 B
2024-01-28T19:34:35.594137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.042553
Min length9

Characters and Unicode

Total characters566
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

Unique47 ?
Unique (%)100.0%

Sample

1st row032-543-0124
2nd row032-554-5400
3rd row032-556-4554
4th row031-551-1616
5th row032-556-4541
ValueCountFrequency (%)
032-543-0124 1
 
2.1%
032-554-6002 1
 
2.1%
032-547-9955 1
 
2.1%
032-545-1685 1
 
2.1%
032-241-8300 1
 
2.1%
032-547-1187 1
 
2.1%
032-554-1900 1
 
2.1%
032-542-0223 1
 
2.1%
032-288-7640 1
 
2.1%
070-7398-4629 1
 
2.1%
Other values (37) 37
78.7%
2024-01-28T19:34:36.091034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 93
16.4%
0 85
15.0%
5 84
14.8%
3 66
11.7%
2 66
11.7%
4 42
7.4%
1 38
6.7%
8 28
 
4.9%
7 23
 
4.1%
6 23
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 473
83.6%
Dash Punctuation 93
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 85
18.0%
5 84
17.8%
3 66
14.0%
2 66
14.0%
4 42
8.9%
1 38
8.0%
8 28
 
5.9%
7 23
 
4.9%
6 23
 
4.9%
9 18
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 566
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 93
16.4%
0 85
15.0%
5 84
14.8%
3 66
11.7%
2 66
11.7%
4 42
7.4%
1 38
6.7%
8 28
 
4.9%
7 23
 
4.1%
6 23
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 566
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 93
16.4%
0 85
15.0%
5 84
14.8%
3 66
11.7%
2 66
11.7%
4 42
7.4%
1 38
6.7%
8 28
 
4.9%
7 23
 
4.1%
6 23
 
4.1%

소재지
Text

MISSING 

Distinct63
Distinct (%)100.0%
Missing1
Missing (%)1.6%
Memory size644.0 B
2024-01-28T19:34:36.334159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length41
Mean length30.349206
Min length23

Characters and Unicode

Total characters1912
Distinct characters90
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)100.0%

Sample

1st row인천광역시 계양구 장제로 847 (임학동)
2nd row인천광역시 계양구 계양대로 148 (계산동)
3rd row인천광역시 계양구 경명대로 1133-1 (계산동)
4th row인천광역시 계양구 효서로 233 (작전동)
5th row인천광역시 계양구 계산천동로 47 (계산동)
ValueCountFrequency (%)
인천광역시 63
16.4%
계양구 63
16.4%
계산동 30
 
7.8%
계양대로 19
 
5.0%
작전동 19
 
5.0%
경명대로 11
 
2.9%
임학동 8
 
2.1%
2층 8
 
2.1%
3층 6
 
1.6%
장제로 6
 
1.6%
Other values (119) 150
39.2%
2024-01-28T19:34:36.674151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
320
 
16.7%
계 121
 
6.3%
양 87
 
4.6%
1 83
 
4.3%
동 69
 
3.6%
인 68
 
3.6%
천 65
 
3.4%
시 64
 
3.3%
역 63
 
3.3%
구 63
 
3.3%
Other values (80) 909
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1104
57.7%
Space Separator 320
 
16.7%
Decimal Number 318
 
16.6%
Open Punctuation 63
 
3.3%
Close Punctuation 63
 
3.3%
Other Punctuation 38
 
2.0%
Dash Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 121
 
11.0%
양 87
 
7.9%
동 69
 
6.2%
인 68
 
6.2%
천 65
 
5.9%
시 64
 
5.8%
역 63
 
5.7%
구 63
 
5.7%
광 63
 
5.7%
로 63
 
5.7%
Other values (64) 378
34.2%
Decimal Number
ValueCountFrequency (%)
1 83
26.1%
2 48
15.1%
0 40
12.6%
3 33
 
10.4%
5 28
 
8.8%
8 19
 
6.0%
4 19
 
6.0%
6 18
 
5.7%
9 15
 
4.7%
7 15
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 37
97.4%
. 1
 
2.6%
Space Separator
ValueCountFrequency (%)
320
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1104
57.7%
Common 808
42.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 121
 
11.0%
양 87
 
7.9%
동 69
 
6.2%
인 68
 
6.2%
천 65
 
5.9%
시 64
 
5.8%
역 63
 
5.7%
구 63
 
5.7%
광 63
 
5.7%
로 63
 
5.7%
Other values (64) 378
34.2%
Common
ValueCountFrequency (%)
320
39.6%
1 83
 
10.3%
( 63
 
7.8%
) 63
 
7.8%
2 48
 
5.9%
0 40
 
5.0%
, 37
 
4.6%
3 33
 
4.1%
5 28
 
3.5%
8 19
 
2.4%
Other values (6) 74
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1104
57.7%
ASCII 808
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
320
39.6%
1 83
 
10.3%
( 63
 
7.8%
) 63
 
7.8%
2 48
 
5.9%
0 40
 
5.0%
, 37
 
4.6%
3 33
 
4.1%
5 28
 
3.5%
8 19
 
2.4%
Other values (6) 74
 
9.2%
Hangul
ValueCountFrequency (%)
계 121
 
11.0%
양 87
 
7.9%
동 69
 
6.2%
인 68
 
6.2%
천 65
 
5.9%
시 64
 
5.8%
역 63
 
5.7%
구 63
 
5.7%
광 63
 
5.7%
로 63
 
5.7%
Other values (64) 378
34.2%

비용
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size644.0 B
유료
60 
무료
 
4

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유료 60
93.8%
무료 4
 
6.2%

Length

2024-01-28T19:34:36.785975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T19:34:36.855361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 60
93.8%
무료 4
 
6.2%

Interactions

2024-01-28T19:34:33.993360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T19:34:36.902616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번기관명대표자명전화번호소재지비용
연번1.0001.0001.0001.0001.0000.851
기관명1.0001.0001.0001.0001.0001.000
대표자명1.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.000
비용0.8511.0001.0001.0001.0001.000
2024-01-28T19:34:36.978252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번비용
연번1.0000.638
비용0.6381.000

Missing values

2024-01-28T19:34:34.075574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T19:34:34.160384image/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.
2024-01-28T19:34:34.235331image/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

연번기관명대표자명전화번호소재지비용
01제일인력개발임중재032-543-0124인천광역시 계양구 장제로 847 (임학동)유료
12통일인력개발황복연032-554-5400인천광역시 계양구 계양대로 148 (계산동)유료
23소망여성인력서미경032-556-4554인천광역시 계양구 경명대로 1133-1 (계산동)유료
34한마음인력개발직업소개소서현정031-551-1616인천광역시 계양구 효서로 233 (작전동)유료
45삼천리인력직업소개소박홍주<NA>인천광역시 계양구 계산천동로 47 (계산동)유료
56유명직업소개소김천순032-556-4541인천광역시 계양구 장제로863번길 15 (임학동, 씨티2000 오피스텔 301호)유료
67우정여성인력김은희032-543-6888인천광역시 계양구 계양대로 134 (작전동)유료
78신창인력개발구자섭032-555-4003인천광역시 계양구 계양대로 115 (작전동)유료
89대호인력개발직업소개소이상철032-548-1797인천광역시 계양구 경명대로 1058, 3층 302-3호 (계산동)유료
910거성인력개발이경래032-555-8171인천광역시 계양구 계양대로 184 (계산동)유료
연번기관명대표자명전화번호소재지비용
5455계양인력정찬복032-551-2500인천광역시 계양구 병방로 11, 3층 (병방동)유료
5556자유롭게 일하는 사람들강혜숙032-551-0007인천광역시 계양구 경명대로1079번길 6-1(계산동)유료
5657삼일인력조영현0507-1408-6932인천광역시 계양구 계양대로 171, 2층 (계산동)유료
5758사임당 홈케어박희원<NA>인천광역시 계양구 경명대로 1115, 인평프라자 505호 (계산동)유료
5859휴머니튜드 간병인협회임선경<NA>인천광역시 계양구 경명대로 1115, 인평프라자 203호 (계산동)유료
5960대신맨인력이영호<NA>인천광역시 계양구 주부토로 463, 302호 (작전동)유료
6061계양구노인인력개발센터김소망032-546-9662인천광역시 계양구 장제로 799, 동성프라자 5층 (계산동)무료
6162(사)한국요양보호사교육기관협회 인천지부손종관032-508-1010인천광역시 계양구 계양대로 101, 삼성프라자 303호 (작전동)무료
6263희망고용지원센터이준모<NA>인천광역시 계양구 계양산로 91 (계산동)무료
6364섬나장애인무료취업소개소이한덕032-555-4138인천광역시 계양구 장제로875번길 1 (임학동)무료