Overview

Dataset statistics

Number of variables6
Number of observations119
Missing cells58
Missing cells (%)8.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory50.1 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description인천광역시 서구 직업소개소 현황에 대한 데이터셋입니다. 이 데이터셋에는 인천광역시 서구 직업소개소의 유무료구분, 업소명, 소재지, 전화번호의 정보를 포함하고 있습니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15038855&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
유무료구분 is highly imbalanced (83.0%)Imbalance
전화번호 has 58 (48.7%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 05:30:33.993475
Analysis finished2024-01-28 05:30:34.555835
Duration0.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct119
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60
Minimum1
Maximum119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-01-28T14:30:34.615868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.9
Q130.5
median60
Q389.5
95-th percentile113.1
Maximum119
Range118
Interquartile range (IQR)59

Descriptive statistics

Standard deviation34.496377
Coefficient of variation (CV)0.57493961
Kurtosis-1.2
Mean60
Median Absolute Deviation (MAD)30
Skewness0
Sum7140
Variance1190
MonotonicityStrictly increasing
2024-01-28T14:30:34.739397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
2 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
82 1
 
0.8%
Other values (109) 109
91.6%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%
112 1
0.8%
111 1
0.8%
110 1
0.8%

유무료구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
유료
116 
무료
 
3

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 116
97.5%
무료 3
 
2.5%

Length

2024-01-28T14:30:34.867177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:30:34.949260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 116
97.5%
무료 3
 
2.5%

업소명
Text

Distinct117
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-28T14:30:35.109774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length13
Mean length6.3613445
Min length2

Characters and Unicode

Total characters757
Distinct characters204
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

Unique115 ?
Unique (%)96.6%

Sample

1st row대성종합직업소개소
2nd row우주인력
3rd row럭키인력
4th row청라파출
5th row보솔BOSOL직업소개소
ValueCountFrequency (%)
인력 4
 
2.8%
믿음인력 2
 
1.4%
우리인력 2
 
1.4%
인천 2
 
1.4%
직업소개소 2
 
1.4%
a))해피케어 1
 
0.7%
녹색인력 1
 
0.7%
뉴월드인력 1
 
0.7%
파파인력 1
 
0.7%
이레인력 1
 
0.7%
Other values (124) 124
87.9%
2024-01-28T14:30:35.421926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 74
 
9.8%
력 64
 
8.5%
소 37
 
4.9%
개 29
 
3.8%
22
 
2.9%
사 16
 
2.1%
업 15
 
2.0%
직 14
 
1.8%
( 13
 
1.7%
이 13
 
1.7%
Other values (194) 460
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 691
91.3%
Space Separator 22
 
2.9%
Open Punctuation 13
 
1.7%
Close Punctuation 13
 
1.7%
Uppercase Letter 9
 
1.2%
Decimal Number 7
 
0.9%
Math Symbol 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 74
 
10.7%
력 64
 
9.3%
소 37
 
5.4%
개 29
 
4.2%
사 16
 
2.3%
업 15
 
2.2%
직 14
 
2.0%
이 13
 
1.9%
발 12
 
1.7%
파 11
 
1.6%
Other values (177) 406
58.8%
Uppercase Letter
ValueCountFrequency (%)
A 2
22.2%
O 2
22.2%
R 1
11.1%
H 1
11.1%
L 1
11.1%
S 1
11.1%
B 1
11.1%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
5 1
 
14.3%
6 1
 
14.3%
3 1
 
14.3%
4 1
 
14.3%
Space Separator
ValueCountFrequency (%)
22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 691
91.3%
Common 57
 
7.5%
Latin 9
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 74
 
10.7%
력 64
 
9.3%
소 37
 
5.4%
개 29
 
4.2%
사 16
 
2.3%
업 15
 
2.2%
직 14
 
2.0%
이 13
 
1.9%
발 12
 
1.7%
파 11
 
1.6%
Other values (177) 406
58.8%
Common
ValueCountFrequency (%)
22
38.6%
( 13
22.8%
) 13
22.8%
1 3
 
5.3%
5 1
 
1.8%
6 1
 
1.8%
3 1
 
1.8%
+ 1
 
1.8%
4 1
 
1.8%
& 1
 
1.8%
Latin
ValueCountFrequency (%)
A 2
22.2%
O 2
22.2%
R 1
11.1%
H 1
11.1%
L 1
11.1%
S 1
11.1%
B 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 691
91.3%
ASCII 66
 
8.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 74
 
10.7%
력 64
 
9.3%
소 37
 
5.4%
개 29
 
4.2%
사 16
 
2.3%
업 15
 
2.2%
직 14
 
2.0%
이 13
 
1.9%
발 12
 
1.7%
파 11
 
1.6%
Other values (177) 406
58.8%
ASCII
ValueCountFrequency (%)
22
33.3%
( 13
19.7%
) 13
19.7%
1 3
 
4.5%
A 2
 
3.0%
O 2
 
3.0%
5 1
 
1.5%
6 1
 
1.5%
3 1
 
1.5%
R 1
 
1.5%
Other values (7) 7
 
10.6%

소재지(도로명)
Text

Distinct118
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-01-28T14:30:35.633397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length42
Mean length33.092437
Min length22

Characters and Unicode

Total characters3938
Distinct characters186
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

Unique117 ?
Unique (%)98.3%

Sample

1st row인천광역시 서구 서곶로 345. 서광빌딩 306호 (연희동)
2nd row인천광역시 서구 검단로 492. 3층 (마전동)
3rd row인천광역시 서구 완정로 146. 208호 (마전동. 리더스빌)
4th row인천광역시 서구 청라에메랄드로149번길 13. 103호 (청라동)
5th row인천광역시 서구 석남로 124. 3층 5호 (석남동)
ValueCountFrequency (%)
인천광역시 119
 
14.8%
서구 119
 
14.8%
석남동 28
 
3.5%
마전동 26
 
3.2%
3층 24
 
3.0%
가정로 20
 
2.5%
2층 15
 
1.9%
완정로 13
 
1.6%
가정동 10
 
1.2%
청라동 9
 
1.1%
Other values (282) 423
52.5%
2024-01-28T14:30:35.984634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
688
 
17.5%
1 138
 
3.5%
서 129
 
3.3%
동 129
 
3.3%
로 124
 
3.1%
. 122
 
3.1%
인 121
 
3.1%
시 121
 
3.1%
광 120
 
3.0%
천 120
 
3.0%
Other values (176) 2126
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2165
55.0%
Decimal Number 699
 
17.8%
Space Separator 688
 
17.5%
Other Punctuation 122
 
3.1%
Close Punctuation 119
 
3.0%
Open Punctuation 119
 
3.0%
Dash Punctuation 21
 
0.5%
Uppercase Letter 4
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 129
 
6.0%
동 129
 
6.0%
로 124
 
5.7%
인 121
 
5.6%
시 121
 
5.6%
광 120
 
5.5%
천 120
 
5.5%
구 119
 
5.5%
역 119
 
5.5%
호 73
 
3.4%
Other values (156) 990
45.7%
Decimal Number
ValueCountFrequency (%)
1 138
19.7%
2 98
14.0%
3 98
14.0%
0 97
13.9%
4 63
9.0%
6 46
 
6.6%
5 45
 
6.4%
9 42
 
6.0%
8 36
 
5.2%
7 36
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
B 1
25.0%
G 1
25.0%
L 1
25.0%
A 1
25.0%
Space Separator
ValueCountFrequency (%)
688
100.0%
Other Punctuation
ValueCountFrequency (%)
. 122
100.0%
Close Punctuation
ValueCountFrequency (%)
) 119
100.0%
Open Punctuation
ValueCountFrequency (%)
( 119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2165
55.0%
Common 1768
44.9%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 129
 
6.0%
동 129
 
6.0%
로 124
 
5.7%
인 121
 
5.6%
시 121
 
5.6%
광 120
 
5.5%
천 120
 
5.5%
구 119
 
5.5%
역 119
 
5.5%
호 73
 
3.4%
Other values (156) 990
45.7%
Common
ValueCountFrequency (%)
688
38.9%
1 138
 
7.8%
. 122
 
6.9%
) 119
 
6.7%
( 119
 
6.7%
2 98
 
5.5%
3 98
 
5.5%
0 97
 
5.5%
4 63
 
3.6%
6 46
 
2.6%
Other values (5) 180
 
10.2%
Latin
ValueCountFrequency (%)
B 1
20.0%
e 1
20.0%
G 1
20.0%
L 1
20.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2165
55.0%
ASCII 1773
45.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
688
38.8%
1 138
 
7.8%
. 122
 
6.9%
) 119
 
6.7%
( 119
 
6.7%
2 98
 
5.5%
3 98
 
5.5%
0 97
 
5.5%
4 63
 
3.6%
6 46
 
2.6%
Other values (10) 185
 
10.4%
Hangul
ValueCountFrequency (%)
서 129
 
6.0%
동 129
 
6.0%
로 124
 
5.7%
인 121
 
5.6%
시 121
 
5.6%
광 120
 
5.5%
천 120
 
5.5%
구 119
 
5.5%
역 119
 
5.5%
호 73
 
3.4%
Other values (156) 990
45.7%

전화번호
Text

MISSING 

Distinct61
Distinct (%)100.0%
Missing58
Missing (%)48.7%
Memory size1.1 KiB
2024-01-28T14:30:36.225087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length9

Characters and Unicode

Total characters732
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)100.0%

Sample

1st row032-563-0085
2nd row032-578-1666
3rd row032-217-0101
4th row032-563-0360
5th row032-577-2553
ValueCountFrequency (%)
032-568-1997 1
 
1.5%
032-568-4380 1
 
1.5%
032-573-9117 1
 
1.5%
032-561-3551 1
 
1.5%
070-7601-2143 1
 
1.5%
032-548-3579 1
 
1.5%
032-746-4499 1
 
1.5%
032-567-9447 1
 
1.5%
032-881-1173 1
 
1.5%
032-562-8858 1
 
1.5%
Other values (55) 55
84.6%
2024-01-28T14:30:36.568045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 117
16.0%
0 101
13.8%
2 96
13.1%
3 90
12.3%
5 74
10.1%
6 58
7.9%
8 47
6.4%
1 45
 
6.1%
7 45
 
6.1%
4 31
 
4.2%
Other values (2) 28
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 611
83.5%
Dash Punctuation 117
 
16.0%
Space Separator 4
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 101
16.5%
2 96
15.7%
3 90
14.7%
5 74
12.1%
6 58
9.5%
8 47
7.7%
1 45
7.4%
7 45
7.4%
4 31
 
5.1%
9 24
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 117
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 732
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 117
16.0%
0 101
13.8%
2 96
13.1%
3 90
12.3%
5 74
10.1%
6 58
7.9%
8 47
6.4%
1 45
 
6.1%
7 45
 
6.1%
4 31
 
4.2%
Other values (2) 28
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 732
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 117
16.0%
0 101
13.8%
2 96
13.1%
3 90
12.3%
5 74
10.1%
6 58
7.9%
8 47
6.4%
1 45
 
6.1%
7 45
 
6.1%
4 31
 
4.2%
Other values (2) 28
 
3.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-07-31
119 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-31
2nd row2023-07-31
3rd row2023-07-31
4th row2023-07-31
5th row2023-07-31

Common Values

ValueCountFrequency (%)
2023-07-31 119
100.0%

Length

2024-01-28T14:30:36.693384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:30:36.766121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-31 119
100.0%

Interactions

2024-01-28T14:30:34.298902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T14:30:36.814756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번유무료구분전화번호
순번1.0000.0001.000
유무료구분0.0001.0001.000
전화번호1.0001.0001.000
2024-01-28T14:30:36.884620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번유무료구분
순번1.0000.000
유무료구분0.0001.000

Missing values

2024-01-28T14:30:34.421254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T14:30:34.519866image/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

순번유무료구분업소명소재지(도로명)전화번호데이터기준일자
01유료대성종합직업소개소인천광역시 서구 서곶로 345. 서광빌딩 306호 (연희동)<NA>2023-07-31
12유료우주인력인천광역시 서구 검단로 492. 3층 (마전동)<NA>2023-07-31
23유료럭키인력인천광역시 서구 완정로 146. 208호 (마전동. 리더스빌)<NA>2023-07-31
34유료청라파출인천광역시 서구 청라에메랄드로149번길 13. 103호 (청라동)032-563-00852023-07-31
45유료보솔BOSOL직업소개소인천광역시 서구 석남로 124. 3층 5호 (석남동)<NA>2023-07-31
56유료믿음인력인천광역시 서구 가정로 340. 3층 (가정동)<NA>2023-07-31
67유료새빛인력인천광역시 서구 원당대로840번길 5. 장원프라자 5층 507-2호 (당하동)<NA>2023-07-31
78유료선주인천광역시 서구 가정로 209. 3층 (석남동)<NA>2023-07-31
89유료한빛인력개발인천광역시 서구 가정로 193. 3층 (석남동)032-578-16662023-07-31
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112113유료덕성직업소개소인천광역시 서구 가정로 415 (신현동)032-582-12932023-07-31
113114무료인천서구여성인력개발센터인천광역시 서구 가정로 350 (가정동)032-577-60912023-07-31
114115유료월드인력공사인천광역시 서구 원창로 196. 3층 301호 (신현동)032-561-88672023-07-31
115116유료국도인력공사인천광역시 서구 가정로 340 (가정동)032-574-02882023-07-31
116117유료참사랑간병인협회인천광역시 서구 가정로 384. 3층 301호 (가정동. 가정뉴타운상가조합)032-583-10032023-07-31
117118유료삼우인력개발인천광역시 서구 가정로 194-2 (석남동)032-576-55552023-07-31
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