Overview

Dataset statistics

Number of variables4
Number of observations172
Missing cells73
Missing cells (%)10.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory33.7 B

Variable types

Numeric1
Text3

Dataset

Description경기도 부천시 관내의 직업소개소에 대한 현황자료로서 업체명, 전화번호, 소재지(도로명) 등의 자료를 제공합니다.
Author경기도 부천시
URLhttps://www.data.go.kr/data/15090516/fileData.do

Alerts

전화번호 has 73 (42.4%) missing valuesMissing
일련번호 has unique valuesUnique

Reproduction

Analysis started2024-04-21 12:35:18.260995
Analysis finished2024-04-21 12:35:19.402924
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

UNIQUE 

Distinct172
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86.5
Minimum1
Maximum172
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-04-21T21:35:19.616165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.55
Q143.75
median86.5
Q3129.25
95-th percentile163.45
Maximum172
Range171
Interquartile range (IQR)85.5

Descriptive statistics

Standard deviation49.796252
Coefficient of variation (CV)0.57567921
Kurtosis-1.2
Mean86.5
Median Absolute Deviation (MAD)43
Skewness0
Sum14878
Variance2479.6667
MonotonicityStrictly increasing
2024-04-21T21:35:20.056573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
120 1
 
0.6%
112 1
 
0.6%
113 1
 
0.6%
114 1
 
0.6%
115 1
 
0.6%
116 1
 
0.6%
117 1
 
0.6%
118 1
 
0.6%
119 1
 
0.6%
Other values (162) 162
94.2%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
172 1
0.6%
171 1
0.6%
170 1
0.6%
169 1
0.6%
168 1
0.6%
167 1
0.6%
166 1
0.6%
165 1
0.6%
164 1
0.6%
163 1
0.6%

업체명
Text

Distinct170
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-21T21:35:20.948103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length6.994186
Min length2

Characters and Unicode

Total characters1203
Distinct characters226
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

Unique168 ?
Unique (%)97.7%

Sample

1st row도원
2nd row희망인력
3rd row주식회사 코리아파트너스
4th row지빈인력
5th row올잡&모든일
ValueCountFrequency (%)
주식회사 5
 
2.4%
직업소개소 5
 
2.4%
희망인력 2
 
1.0%
인력개발 2
 
1.0%
명성인력 2
 
1.0%
부천점 2
 
1.0%
스마일간병협회 1
 
0.5%
국보인력개발 1
 
0.5%
바로바로취업정보 1
 
0.5%
명진인력 1
 
0.5%
Other values (183) 183
89.3%
2024-04-21T21:35:22.294607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 84
 
7.0%
력 72
 
6.0%
소 66
 
5.5%
개 47
 
3.9%
업 45
 
3.7%
33
 
2.7%
직 31
 
2.6%
부 29
 
2.4%
천 19
 
1.6%
파 19
 
1.6%
Other values (216) 758
63.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1148
95.4%
Space Separator 33
 
2.7%
Decimal Number 6
 
0.5%
Close Punctuation 5
 
0.4%
Open Punctuation 5
 
0.4%
Other Punctuation 4
 
0.3%
Uppercase Letter 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 84
 
7.3%
력 72
 
6.3%
소 66
 
5.7%
개 47
 
4.1%
업 45
 
3.9%
직 31
 
2.7%
부 29
 
2.5%
천 19
 
1.7%
파 19
 
1.7%
터 17
 
1.5%
Other values (206) 719
62.6%
Decimal Number
ValueCountFrequency (%)
1 4
66.7%
4 1
 
16.7%
9 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
& 2
50.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1148
95.4%
Common 54
 
4.5%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 84
 
7.3%
력 72
 
6.3%
소 66
 
5.7%
개 47
 
4.1%
업 45
 
3.9%
직 31
 
2.7%
부 29
 
2.5%
천 19
 
1.7%
파 19
 
1.7%
터 17
 
1.5%
Other values (206) 719
62.6%
Common
ValueCountFrequency (%)
33
61.1%
) 5
 
9.3%
( 5
 
9.3%
1 4
 
7.4%
. 2
 
3.7%
& 2
 
3.7%
4 1
 
1.9%
9 1
 
1.9%
+ 1
 
1.9%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1148
95.4%
ASCII 55
 
4.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 84
 
7.3%
력 72
 
6.3%
소 66
 
5.7%
개 47
 
4.1%
업 45
 
3.9%
직 31
 
2.7%
부 29
 
2.5%
천 19
 
1.7%
파 19
 
1.7%
터 17
 
1.5%
Other values (206) 719
62.6%
ASCII
ValueCountFrequency (%)
33
60.0%
) 5
 
9.1%
( 5
 
9.1%
1 4
 
7.3%
. 2
 
3.6%
& 2
 
3.6%
A 1
 
1.8%
4 1
 
1.8%
9 1
 
1.8%
+ 1
 
1.8%

전화번호
Text

MISSING 

Distinct99
Distinct (%)100.0%
Missing73
Missing (%)42.4%
Memory size1.5 KiB
2024-04-21T21:35:23.180391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.959596
Min length9

Characters and Unicode

Total characters1184
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

Unique99 ?
Unique (%)100.0%

Sample

1st row032-612-9297
2nd row032-666-5949
3rd row032-721-6176
4th row032-655-7707
5th row032-323-9948
ValueCountFrequency (%)
032 5
 
4.6%
032-341-3579 1
 
0.9%
032-655-0911 1
 
0.9%
032-655-0003 1
 
0.9%
032-612-3545 1
 
0.9%
032-344-8784 1
 
0.9%
032-652-9313 1
 
0.9%
032-666-4888 1
 
0.9%
032-611-9782 1
 
0.9%
611-2000 1
 
0.9%
Other values (94) 94
87.0%
2024-04-21T21:35:24.511591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 187
15.8%
3 176
14.9%
2 158
13.3%
0 153
12.9%
6 101
8.5%
1 89
7.5%
4 70
 
5.9%
5 70
 
5.9%
7 61
 
5.2%
9 55
 
4.6%
Other values (2) 64
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 988
83.4%
Dash Punctuation 187
 
15.8%
Space Separator 9
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 176
17.8%
2 158
16.0%
0 153
15.5%
6 101
10.2%
1 89
9.0%
4 70
 
7.1%
5 70
 
7.1%
7 61
 
6.2%
9 55
 
5.6%
8 55
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 187
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1184
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 187
15.8%
3 176
14.9%
2 158
13.3%
0 153
12.9%
6 101
8.5%
1 89
7.5%
4 70
 
5.9%
5 70
 
5.9%
7 61
 
5.2%
9 55
 
4.6%
Other values (2) 64
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1184
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 187
15.8%
3 176
14.9%
2 158
13.3%
0 153
12.9%
6 101
8.5%
1 89
7.5%
4 70
 
5.9%
5 70
 
5.9%
7 61
 
5.2%
9 55
 
4.6%
Other values (2) 64
 
5.4%

소재지(도로명)
Text

Distinct171
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-04-21T21:35:25.777078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length38
Mean length29.627907
Min length19

Characters and Unicode

Total characters5096
Distinct characters174
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

Unique170 ?
Unique (%)98.8%

Sample

1st row경기도 부천시 소향로13번길 14-22. 금호프라자 802-9호 (상동)
2nd row경기도 부천시 부일로 326. 205호 (중동)
3rd row경기도 부천시 중동로248번길 23. VIVANT 801호 (중동)
4th row경기도 부천시 부천로245번길 55. 1층 (춘의동)
5th row경기도 부천시 부일로205번길 46. 윌타운 2층 204호 R209호 (상동)
ValueCountFrequency (%)
경기도 171
 
15.5%
부천시 171
 
15.5%
2층 40
 
3.6%
심곡동 34
 
3.1%
부일로 30
 
2.7%
3층 24
 
2.2%
중동 22
 
2.0%
심곡본동 21
 
1.9%
상동 17
 
1.5%
소사본동 15
 
1.4%
Other values (346) 556
50.5%
2024-04-21T21:35:27.491048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
929
 
18.2%
부 244
 
4.8%
천 198
 
3.9%
경 194
 
3.8%
2 193
 
3.8%
동 190
 
3.7%
도 180
 
3.5%
시 172
 
3.4%
기 172
 
3.4%
. 171
 
3.4%
Other values (164) 2453
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2676
52.5%
Decimal Number 936
 
18.4%
Space Separator 929
 
18.2%
Other Punctuation 171
 
3.4%
Open Punctuation 171
 
3.4%
Close Punctuation 171
 
3.4%
Dash Punctuation 32
 
0.6%
Uppercase Letter 10
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 244
 
9.1%
천 198
 
7.4%
경 194
 
7.2%
동 190
 
7.1%
도 180
 
6.7%
시 172
 
6.4%
기 172
 
6.4%
로 171
 
6.4%
층 97
 
3.6%
호 77
 
2.9%
Other values (140) 981
36.7%
Decimal Number
ValueCountFrequency (%)
2 193
20.6%
1 162
17.3%
3 128
13.7%
0 112
12.0%
4 88
9.4%
5 67
 
7.2%
6 60
 
6.4%
8 46
 
4.9%
7 42
 
4.5%
9 38
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
V 2
20.0%
S 1
10.0%
J 1
10.0%
B 1
10.0%
R 1
10.0%
T 1
10.0%
N 1
10.0%
A 1
10.0%
I 1
10.0%
Space Separator
ValueCountFrequency (%)
929
100.0%
Other Punctuation
ValueCountFrequency (%)
. 171
100.0%
Open Punctuation
ValueCountFrequency (%)
( 171
100.0%
Close Punctuation
ValueCountFrequency (%)
) 171
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2676
52.5%
Common 2410
47.3%
Latin 10
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 244
 
9.1%
천 198
 
7.4%
경 194
 
7.2%
동 190
 
7.1%
도 180
 
6.7%
시 172
 
6.4%
기 172
 
6.4%
로 171
 
6.4%
층 97
 
3.6%
호 77
 
2.9%
Other values (140) 981
36.7%
Common
ValueCountFrequency (%)
929
38.5%
2 193
 
8.0%
. 171
 
7.1%
( 171
 
7.1%
) 171
 
7.1%
1 162
 
6.7%
3 128
 
5.3%
0 112
 
4.6%
4 88
 
3.7%
5 67
 
2.8%
Other values (5) 218
 
9.0%
Latin
ValueCountFrequency (%)
V 2
20.0%
S 1
10.0%
J 1
10.0%
B 1
10.0%
R 1
10.0%
T 1
10.0%
N 1
10.0%
A 1
10.0%
I 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2676
52.5%
ASCII 2420
47.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
929
38.4%
2 193
 
8.0%
. 171
 
7.1%
( 171
 
7.1%
) 171
 
7.1%
1 162
 
6.7%
3 128
 
5.3%
0 112
 
4.6%
4 88
 
3.6%
5 67
 
2.8%
Other values (14) 228
 
9.4%
Hangul
ValueCountFrequency (%)
부 244
 
9.1%
천 198
 
7.4%
경 194
 
7.2%
동 190
 
7.1%
도 180
 
6.7%
시 172
 
6.4%
기 172
 
6.4%
로 171
 
6.4%
층 97
 
3.6%
호 77
 
2.9%
Other values (140) 981
36.7%

Interactions

2024-04-21T21:35:18.673369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T21:35:27.744066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호전화번호
일련번호1.0001.000
전화번호1.0001.000

Missing values

2024-04-21T21:35:19.010211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T21:35:19.292387image/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

일련번호업체명전화번호소재지(도로명)
01도원<NA>경기도 부천시 소향로13번길 14-22. 금호프라자 802-9호 (상동)
12희망인력032-612-9297경기도 부천시 부일로 326. 205호 (중동)
23주식회사 코리아파트너스<NA>경기도 부천시 중동로248번길 23. VIVANT 801호 (중동)
34지빈인력<NA>경기도 부천시 부천로245번길 55. 1층 (춘의동)
45올잡&모든일<NA>경기도 부천시 부일로205번길 46. 윌타운 2층 204호 R209호 (상동)
56전통직업소개소032-666-5949경기도 부천시 신흥로 8. 1층 (심곡본동)
67정성인력부천오정점<NA>경기도 부천시 삼작로 116. 103호 (내동. 영백주택)
78이루고 직업소개소<NA>경기도 부천시 부일로 448. 프리존 빌딩 1002-5 일부호 (심곡동)
89한걸음인력032-721-6176경기도 부천시 부천로103번길 26. 2층 (심곡동. 라이프타운)
910주식회사 신현대인력032-655-7707경기도 부천시 송내대로 34. 영상빌딩 지하101.102호 (송내동)
일련번호업체명전화번호소재지(도로명)
162163삼성인력032-612-1919경기도 부천시 경인로 315 (심곡본동)
163164유경복지재단032-322-658경기도 부천시 부흥로303번길 50. 202호 (중동. 한양프라자)
164165부천원미지역자활센터032-653-9987경기도 부천시 부흥로303번길 8. 403호 (중동. 청원프라자)
165166지구촌032-662-1604경기도 부천시 부흥로 382 (심곡동)
166167역곡인력<NA>경기도 부천시 부일로 642 (역곡동)
167168경기인력<NA>경기도 부천시 경인로 330 (소사본동)
168169보람취업컨설팅032-344-5050경기도 부천시 부일로 416. 2층 (심곡동)
169170종합직업소개소032-651-4300경기도 부천시 경인로 211-1. 3층 (심곡본동)
170171동성환경개발032-346-7123경기도 부천시 은성로76번길 41. 4층 (소사본동)
171172부천여성인력개발센터무료직업소개소032-326-0221경기도 부천시 석천로 171. 5층 (중동)