Overview

Dataset statistics

Number of variables4
Number of observations1043
Missing cells0
Missing cells (%)0.0%
Duplicate rows33
Duplicate rows (%)3.2%
Total size in memory32.7 KiB
Average record size in memory32.1 B

Variable types

Text1
Categorical2
DateTime1

Dataset

Description경기도 안양시 출판사를 경영하고자 하는 자의 신청을 받아 출판사로 신고된 현황(안양시 출판사 상호명, 안양시 출판사 소재지, 안양시 출판사 신고일자,영업상태) 데이터 정보입니다.
Author경기도 안양시
URLhttps://www.data.go.kr/data/3079530/fileData.do

Alerts

영업상태 has constant value ""Constant
Dataset has 33 (3.2%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 11:12:01.777020
Analysis finished2023-12-12 11:12:02.428410
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호명
Text

Distinct977
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
2023-12-12T20:12:02.651597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length6.9932886
Min length2

Characters and Unicode

Total characters7294
Distinct characters603
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique916 ?
Unique (%)87.8%

Sample

1st row예성출판사
2nd row화신문화사
3rd row도서출판 예진
4th row송암문화
5th row한국노총 경기중부
ValueCountFrequency (%)
도서출판 105
 
7.2%
주식회사 103
 
7.0%
출판사 13
 
0.9%
디자인 8
 
0.5%
주 7
 
0.5%
사단법인 6
 
0.4%
스튜디오 5
 
0.3%
하늘기획 4
 
0.3%
은학사 4
 
0.3%
미디어 4
 
0.3%
Other values (1108) 1205
82.3%
2023-12-12T20:12:03.171299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
428
 
5.9%
사 269
 
3.7%
주 241
 
3.3%
판 187
 
2.6%
출 186
 
2.6%
) 164
 
2.2%
( 161
 
2.2%
스 152
 
2.1%
도 148
 
2.0%
서 145
 
2.0%
Other values (593) 5213
71.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5961
81.7%
Space Separator 428
 
5.9%
Uppercase Letter 268
 
3.7%
Lowercase Letter 253
 
3.5%
Close Punctuation 164
 
2.2%
Open Punctuation 161
 
2.2%
Other Punctuation 37
 
0.5%
Decimal Number 18
 
0.2%
Dash Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 269
 
4.5%
주 241
 
4.0%
판 187
 
3.1%
출 186
 
3.1%
스 152
 
2.5%
도 148
 
2.5%
서 145
 
2.4%
이 140
 
2.3%
회 126
 
2.1%
인 121
 
2.0%
Other values (530) 4246
71.2%
Uppercase Letter
ValueCountFrequency (%)
S 22
 
8.2%
O 22
 
8.2%
I 21
 
7.8%
C 20
 
7.5%
A 20
 
7.5%
P 19
 
7.1%
N 17
 
6.3%
E 15
 
5.6%
L 13
 
4.9%
K 13
 
4.9%
Other values (15) 86
32.1%
Lowercase Letter
ValueCountFrequency (%)
o 39
15.4%
e 31
12.3%
i 23
9.1%
n 22
 
8.7%
a 17
 
6.7%
l 16
 
6.3%
t 14
 
5.5%
s 12
 
4.7%
d 12
 
4.7%
c 10
 
4.0%
Other values (13) 57
22.5%
Decimal Number
ValueCountFrequency (%)
1 7
38.9%
2 4
22.2%
0 4
22.2%
4 1
 
5.6%
8 1
 
5.6%
9 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 19
51.4%
& 12
32.4%
, 3
 
8.1%
* 2
 
5.4%
/ 1
 
2.7%
Space Separator
ValueCountFrequency (%)
428
100.0%
Close Punctuation
ValueCountFrequency (%)
) 164
100.0%
Open Punctuation
ValueCountFrequency (%)
( 161
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5958
81.7%
Common 812
 
11.1%
Latin 521
 
7.1%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 269
 
4.5%
주 241
 
4.0%
판 187
 
3.1%
출 186
 
3.1%
스 152
 
2.6%
도 148
 
2.5%
서 145
 
2.4%
이 140
 
2.3%
회 126
 
2.1%
인 121
 
2.0%
Other values (527) 4243
71.2%
Latin
ValueCountFrequency (%)
o 39
 
7.5%
e 31
 
6.0%
i 23
 
4.4%
n 22
 
4.2%
S 22
 
4.2%
O 22
 
4.2%
I 21
 
4.0%
C 20
 
3.8%
A 20
 
3.8%
P 19
 
3.6%
Other values (38) 282
54.1%
Common
ValueCountFrequency (%)
428
52.7%
) 164
 
20.2%
( 161
 
19.8%
. 19
 
2.3%
& 12
 
1.5%
1 7
 
0.9%
- 4
 
0.5%
2 4
 
0.5%
0 4
 
0.5%
, 3
 
0.4%
Other values (5) 6
 
0.7%
Han
ValueCountFrequency (%)
社 1
33.3%
門 1
33.3%
畢 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5958
81.7%
ASCII 1333
 
18.3%
CJK 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
428
32.1%
) 164
 
12.3%
( 161
 
12.1%
o 39
 
2.9%
e 31
 
2.3%
i 23
 
1.7%
n 22
 
1.7%
S 22
 
1.7%
O 22
 
1.7%
I 21
 
1.6%
Other values (53) 400
30.0%
Hangul
ValueCountFrequency (%)
사 269
 
4.5%
주 241
 
4.0%
판 187
 
3.1%
출 186
 
3.1%
스 152
 
2.6%
도 148
 
2.5%
서 145
 
2.4%
이 140
 
2.3%
회 126
 
2.1%
인 121
 
2.0%
Other values (527) 4243
71.2%
CJK
ValueCountFrequency (%)
社 1
33.3%
門 1
33.3%
畢 1
33.3%

소재지(읍면동)
Categorical

Distinct7
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
관양동
373 
안양동
264 
호계동
181 
비산동
91 
평촌동
61 
Other values (2)
73 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관양동 373
35.8%
안양동 264
25.3%
호계동 181
17.4%
비산동 91
 
8.7%
평촌동 61
 
5.8%
석수동 58
 
5.6%
박달동 15
 
1.4%

Length

2023-12-12T20:12:03.372424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:12:03.543463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관양동 373
35.8%
안양동 264
25.3%
호계동 181
17.4%
비산동 91
 
8.7%
평촌동 61
 
5.8%
석수동 58
 
5.6%
박달동 15
 
1.4%

신고일자
Date

Distinct903
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
Minimum1965-03-02 00:00:00
Maximum2023-07-24 00:00:00
2023-12-12T20:12:03.742599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:12:03.975831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
영업중
1043 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 1043
100.0%

Length

2023-12-12T20:12:04.188678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:12:04.358171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 1043
100.0%

Missing values

2023-12-12T20:12:02.230188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:12:02.369570image/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

상호명소재지(읍면동)신고일자영업상태
0예성출판사안양동1989-12-26영업중
1화신문화사안양동1992-08-14영업중
2도서출판 예진안양동1994-03-05영업중
3송암문화안양동1995-10-07영업중
4한국노총 경기중부안양동1995-03-27영업중
5예진기획안양동1996-10-28영업중
6도서출판 열린안양동1996-03-09영업중
7아침미디어석수동1996-05-29영업중
8하나교육안양동1996-11-08영업중
9원차일드안양동1997-05-06영업중
상호명소재지(읍면동)신고일자영업상태
1033동양비지니스폼(주)안양지점호계동2013-01-08영업중
1034주식회사 지피호계동2013-02-26영업중
1035토탈피앤씨호계동2013-08-06영업중
1036미래문화사호계동2015-10-22영업중
1037세한피엔씨(주)호계동2018-04-27영업중
1038샛별기획인쇄호계동2019-01-28영업중
1039페이지스호계동2019-12-03영업중
1040(주)일루비즈호계동2020-05-06영업중
1041주식회사 엘큐브호계동2020-11-04영업중
1042디프린팅호계동2023-05-22영업중

Duplicate rows

Most frequently occurring

상호명소재지(읍면동)신고일자영업상태# duplicates
0(사)인희선도 태백원관양동1999-06-14영업중2
1(주)나우맵소프트평촌동2013-03-06영업중2
2(주)지앤피월드관양동2009-01-13영업중2
3(주)채움광고기획안양동2014-12-31영업중2
4(주)플레이앤북스안양동2009-06-29영업중2
5경기마을교육공동체사회적협동조합안양동2017-01-17영업중2
6고흥기획관양동2006-02-28영업중2
7과천인쇄관양동2004-08-18영업중2
8그랙션관양동2015-04-21영업중2
9기쁘다노정문화사관양동2012-07-13영업중2