Overview

Dataset statistics

Number of variables5
Number of observations40
Missing cells4
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory44.3 B

Variable types

Numeric1
DateTime1
Text2
Categorical1

Dataset

Description인천광역시 서구 관내에 위치한 인쇄사 현황(업체명, 신고일자, 사업체명칭, 사업체소재지(도로명))에 관하여 입력된 데이터입니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15067833&srcSe=7661IVAWM27C61E190

Alerts

연번 is highly overall correlated with 데이터기준일자High correlation
데이터기준일자 is highly overall correlated with 연번High correlation
데이터기준일자 is highly imbalanced (83.1%)Imbalance
연번 has 1 (2.5%) missing valuesMissing
신고일자 has 1 (2.5%) missing valuesMissing
사업체명칭 has 1 (2.5%) missing valuesMissing
사업체소재지(도로명) has 1 (2.5%) missing valuesMissing

Reproduction

Analysis started2024-01-28 09:09:53.662992
Analysis finished2024-01-28 09:09:54.185114
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct39
Distinct (%)100.0%
Missing1
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean20
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-01-28T18:09:54.242028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.9
Q110.5
median20
Q329.5
95-th percentile37.1
Maximum39
Range38
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.401754
Coefficient of variation (CV)0.57008771
Kurtosis-1.2
Mean20
Median Absolute Deviation (MAD)10
Skewness0
Sum780
Variance130
MonotonicityStrictly increasing
2024-01-28T18:09:54.348352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 1
 
2.5%
2 1
 
2.5%
23 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
Other values (29) 29
72.5%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%
30 1
2.5%

신고일자
Date

MISSING 

Distinct39
Distinct (%)100.0%
Missing1
Missing (%)2.5%
Memory size452.0 B
Minimum1991-03-29 00:00:00
Maximum2022-05-09 00:00:00
2024-01-28T18:09:54.452094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T18:09:54.551095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)

사업체명칭
Text

MISSING 

Distinct39
Distinct (%)100.0%
Missing1
Missing (%)2.5%
Memory size452.0 B
2024-01-28T18:09:54.717793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length9
Mean length5.8461538
Min length1

Characters and Unicode

Total characters228
Distinct characters110
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

Unique39 ?
Unique (%)100.0%

Sample

1st row하이씨닷컴
2nd row고려문화사
3rd row승진인쇄소
4th row네오프린트
5th row드림프린트피아
ValueCountFrequency (%)
주식회사 3
 
6.5%
도서출판 2
 
4.3%
하이씨닷컴 1
 
2.2%
광고방 1
 
2.2%
주)광성공사 1
 
2.2%
희성디자인 1
 
2.2%
주)스톰앤 1
 
2.2%
오성프린팅 1
 
2.2%
피엔씨 1
 
2.2%
언프레임 1
 
2.2%
Other values (33) 33
71.7%
2024-01-28T18:09:55.012712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 12
 
5.3%
주 9
 
3.9%
7
 
3.1%
( 6
 
2.6%
) 6
 
2.6%
사 6
 
2.6%
성 6
 
2.6%
프 6
 
2.6%
쇄 6
 
2.6%
자 5
 
2.2%
Other values (100) 159
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 192
84.2%
Lowercase Letter 15
 
6.6%
Space Separator 7
 
3.1%
Open Punctuation 6
 
2.6%
Close Punctuation 6
 
2.6%
Uppercase Letter 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 12
 
6.2%
주 9
 
4.7%
사 6
 
3.1%
성 6
 
3.1%
프 6
 
3.1%
쇄 6
 
3.1%
자 5
 
2.6%
디 5
 
2.6%
서 4
 
2.1%
아 4
 
2.1%
Other values (83) 129
67.2%
Lowercase Letter
ValueCountFrequency (%)
o 3
20.0%
n 2
13.3%
a 1
 
6.7%
e 1
 
6.7%
w 1
 
6.7%
m 1
 
6.7%
s 1
 
6.7%
u 1
 
6.7%
l 1
 
6.7%
t 1
 
6.7%
Other values (2) 2
13.3%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 192
84.2%
Common 19
 
8.3%
Latin 17
 
7.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 12
 
6.2%
주 9
 
4.7%
사 6
 
3.1%
성 6
 
3.1%
프 6
 
3.1%
쇄 6
 
3.1%
자 5
 
2.6%
디 5
 
2.6%
서 4
 
2.1%
아 4
 
2.1%
Other values (83) 129
67.2%
Latin
ValueCountFrequency (%)
o 3
17.6%
n 2
11.8%
S 1
 
5.9%
a 1
 
5.9%
e 1
 
5.9%
w 1
 
5.9%
m 1
 
5.9%
C 1
 
5.9%
s 1
 
5.9%
u 1
 
5.9%
Other values (4) 4
23.5%
Common
ValueCountFrequency (%)
7
36.8%
( 6
31.6%
) 6
31.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 192
84.2%
ASCII 36
 
15.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 12
 
6.2%
주 9
 
4.7%
사 6
 
3.1%
성 6
 
3.1%
프 6
 
3.1%
쇄 6
 
3.1%
자 5
 
2.6%
디 5
 
2.6%
서 4
 
2.1%
아 4
 
2.1%
Other values (83) 129
67.2%
ASCII
ValueCountFrequency (%)
7
19.4%
( 6
16.7%
) 6
16.7%
o 3
8.3%
n 2
 
5.6%
S 1
 
2.8%
a 1
 
2.8%
e 1
 
2.8%
w 1
 
2.8%
m 1
 
2.8%
Other values (7) 7
19.4%

사업체소재지(도로명)
Text

MISSING 

Distinct39
Distinct (%)100.0%
Missing1
Missing (%)2.5%
Memory size452.0 B
2024-01-28T18:09:55.234674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length37
Mean length31.307692
Min length21

Characters and Unicode

Total characters1221
Distinct characters137
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

Unique39 ?
Unique (%)100.0%

Sample

1st row인천광역시 서구 가정로189번길 9-7 (석남동)
2nd row인천광역시 서구 검단로 540 (오류동)
3rd row인천광역시 서구 서곶로 833 (당하동)
4th row인천광역시 서구 거북로 17, 가동 607호 (석남동, 테크피아)
5th row인천광역시 서구 심곡로56번길 1 (심곡동)
ValueCountFrequency (%)
인천광역시 39
 
15.8%
서구 39
 
15.8%
심곡동 8
 
3.2%
가좌동 7
 
2.8%
석남동 6
 
2.4%
서곶로 6
 
2.4%
오류동 4
 
1.6%
연희동 4
 
1.6%
10 4
 
1.6%
1층 3
 
1.2%
Other values (102) 127
51.4%
2024-01-28T18:09:55.578785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
208
 
17.0%
서 49
 
4.0%
광 43
 
3.5%
동 43
 
3.5%
인 42
 
3.4%
천 42
 
3.4%
1 41
 
3.4%
( 40
 
3.3%
) 40
 
3.3%
역 39
 
3.2%
Other values (127) 634
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 692
56.7%
Space Separator 208
 
17.0%
Decimal Number 192
 
15.7%
Open Punctuation 40
 
3.3%
Close Punctuation 40
 
3.3%
Other Punctuation 36
 
2.9%
Dash Punctuation 6
 
0.5%
Uppercase Letter 6
 
0.5%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 49
 
7.1%
광 43
 
6.2%
동 43
 
6.2%
인 42
 
6.1%
천 42
 
6.1%
역 39
 
5.6%
시 39
 
5.6%
구 39
 
5.6%
로 39
 
5.6%
호 20
 
2.9%
Other values (106) 297
42.9%
Decimal Number
ValueCountFrequency (%)
1 41
21.4%
0 30
15.6%
3 25
13.0%
2 22
11.5%
8 16
 
8.3%
4 15
 
7.8%
6 14
 
7.3%
5 13
 
6.8%
7 10
 
5.2%
9 6
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 2
33.3%
G 1
16.7%
J 1
16.7%
K 1
16.7%
M 1
16.7%
Space Separator
ValueCountFrequency (%)
208
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Other Punctuation
ValueCountFrequency (%)
, 36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 692
56.7%
Common 523
42.8%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 49
 
7.1%
광 43
 
6.2%
동 43
 
6.2%
인 42
 
6.1%
천 42
 
6.1%
역 39
 
5.6%
시 39
 
5.6%
구 39
 
5.6%
로 39
 
5.6%
호 20
 
2.9%
Other values (106) 297
42.9%
Common
ValueCountFrequency (%)
208
39.8%
1 41
 
7.8%
( 40
 
7.6%
) 40
 
7.6%
, 36
 
6.9%
0 30
 
5.7%
3 25
 
4.8%
2 22
 
4.2%
8 16
 
3.1%
4 15
 
2.9%
Other values (6) 50
 
9.6%
Latin
ValueCountFrequency (%)
B 2
33.3%
G 1
16.7%
J 1
16.7%
K 1
16.7%
M 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 692
56.7%
ASCII 529
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
208
39.3%
1 41
 
7.8%
( 40
 
7.6%
) 40
 
7.6%
, 36
 
6.8%
0 30
 
5.7%
3 25
 
4.7%
2 22
 
4.2%
8 16
 
3.0%
4 15
 
2.8%
Other values (11) 56
 
10.6%
Hangul
ValueCountFrequency (%)
서 49
 
7.1%
광 43
 
6.2%
동 43
 
6.2%
인 42
 
6.1%
천 42
 
6.1%
역 39
 
5.6%
시 39
 
5.6%
구 39
 
5.6%
로 39
 
5.6%
호 20
 
2.9%
Other values (106) 297
42.9%

데이터기준일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2022-08-31
39 
<NA>
 
1

Length

Max length10
Median length10
Mean length9.85
Min length4

Unique

Unique1 ?
Unique (%)2.5%

Sample

1st row2022-08-31
2nd row2022-08-31
3rd row2022-08-31
4th row2022-08-31
5th row2022-08-31

Common Values

ValueCountFrequency (%)
2022-08-31 39
97.5%
<NA> 1
 
2.5%

Length

2024-01-28T18:09:55.692713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:09:55.774604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-31 39
97.5%
na 1
 
2.5%

Interactions

2024-01-28T18:09:53.864491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T18:09:55.825907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번신고일자사업체명칭사업체소재지(도로명)
연번1.0001.0001.0001.000
신고일자1.0001.0001.0001.000
사업체명칭1.0001.0001.0001.000
사업체소재지(도로명)1.0001.0001.0001.000
2024-01-28T18:09:55.902008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번데이터기준일자
연번1.0001.000
데이터기준일자1.0001.000

Missing values

2024-01-28T18:09:53.961764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T18:09:54.033952image/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.
2024-01-28T18:09:54.118388image/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

연번신고일자사업체명칭사업체소재지(도로명)데이터기준일자
011991-03-29하이씨닷컴인천광역시 서구 가정로189번길 9-7 (석남동)2022-08-31
121998-01-30고려문화사인천광역시 서구 검단로 540 (오류동)2022-08-31
231998-03-30승진인쇄소인천광역시 서구 서곶로 833 (당하동)2022-08-31
341998-12-26네오프린트인천광역시 서구 거북로 17, 가동 607호 (석남동, 테크피아)2022-08-31
452000-01-18드림프린트피아인천광역시 서구 심곡로56번길 1 (심곡동)2022-08-31
562006-05-11보아스넷인천광역시 서구 거북로 17, 가동 504호 (석남동, 인천테크피아)2022-08-31
672007-10-24서해인쇄문화인천광역시 서구 원적로47번길 38 (가좌동)2022-08-31
782008-02-28도서출판 천마인천광역시 서구 서곶로315번길 13 (심곡동)2022-08-31
892008-07-24성림광고인쇄인천광역시 서구 탁옥로51번길 13-8 (심곡동)2022-08-31
9102008-11-05태성테크인천광역시 서구 율도로 19 (석남동)2022-08-31
연번신고일자사업체명칭사업체소재지(도로명)데이터기준일자
30312020-09-01미소디자인인천광역시 서구 고산후로 103, 페라리움 205호 (당하동)2022-08-31
31322021-01-11유브이그래픽에이치에스인천광역시 서구 보듬로 158, 블루텍 공존동 B-101호 (오류동)2022-08-31
32332021-02-04루돌프패키지인천광역시 서구 가석로 30, 광양프런티어밸리3차 B102호 (가좌동)2022-08-31
33342014-08-11연인천광역시 서구 원적로47번길 38, 102호 (가좌동)2022-08-31
34352021-05-11(주)새롬컴퍼니인천광역시 서구 보듬로 158, 블루텍 미플존동 208호 (오류동)2022-08-31
35362020-11-25(주)으랏차인천광역시 서구 백범로630번길 16, GJ가좌타워 지식산업센터 301~2호 (가좌동)2022-08-31
36371999-08-19태양인쇄공사인천광역시 서구 봉수대로 268, 106호 (석남동)2022-08-31
37382022-05-09싸인팩토리인천광역시 서구 가람로 14, 인천표면처리센터 요진코아텍 158호 (오류동)2022-08-31
38392007-07-31한림인천광역시 서구 가석로 30, 광양프런티어밸리3차 918호 (가좌동)2022-08-31
39<NA><NA><NA><NA><NA>