Overview

Dataset statistics

Number of variables5
Number of observations158
Missing cells87
Missing cells (%)11.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory40.8 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description충청남도 공주시 출판사 및 인쇄사 현황에 대한 데이터로 (구분, 사업체명칭, 전화번호, 데이터기준일) 등의 항목을 제공합니다
Author충청남도 공주시
URLhttps://www.data.go.kr/data/3084531/fileData.do

Alerts

데이터기준일 has constant value ""Constant
전화번호 has 86 (54.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 10:40:57.323482
Analysis finished2023-12-12 10:40:57.989145
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
출판사
84 
인쇄사
74 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
출판사 84
53.2%
인쇄사 74
46.8%

Length

2023-12-12T19:40:58.066904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:40:58.193822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
출판사 84
53.2%
인쇄사 74
46.8%

사업체명칭
Text

Distinct137
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-12T19:40:58.515361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length15.5
Mean length6.9177215
Min length2

Characters and Unicode

Total characters1093
Distinct characters255
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)73.4%

Sample

1st row공주대학교출판사
2nd row공주합동출판인쇄공사
3rd row시사논평사
4th row순리세계사
5th row공명출판사
ValueCountFrequency (%)
도서출판 3
 
1.6%
주식회사 3
 
1.6%
밝문화 2
 
1.1%
특급뉴스 2
 
1.1%
미디어 2
 
1.1%
출판사 2
 
1.1%
사거리 2
 
1.1%
문화인쇄사 2
 
1.1%
대한복사인쇄 2
 
1.1%
충남디자인연구소 2
 
1.1%
Other values (150) 166
88.3%
2023-12-12T19:40:59.046725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
인 64
 
5.9%
사 57
 
5.2%
쇄 44
 
4.0%
30
 
2.7%
판 27
 
2.5%
출 27
 
2.5%
주 23
 
2.1%
디 21
 
1.9%
공 20
 
1.8%
화 19
 
1.7%
Other values (245) 761
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 919
84.1%
Lowercase Letter 66
 
6.0%
Uppercase Letter 43
 
3.9%
Space Separator 30
 
2.7%
Close Punctuation 16
 
1.5%
Open Punctuation 16
 
1.5%
Dash Punctuation 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 64
 
7.0%
사 57
 
6.2%
쇄 44
 
4.8%
판 27
 
2.9%
출 27
 
2.9%
주 23
 
2.5%
디 21
 
2.3%
공 20
 
2.2%
화 19
 
2.1%
문 18
 
2.0%
Other values (203) 599
65.2%
Uppercase Letter
ValueCountFrequency (%)
U 4
 
9.3%
E 3
 
7.0%
R 3
 
7.0%
N 3
 
7.0%
H 3
 
7.0%
P 3
 
7.0%
Y 3
 
7.0%
G 3
 
7.0%
S 2
 
4.7%
L 2
 
4.7%
Other values (10) 14
32.6%
Lowercase Letter
ValueCountFrequency (%)
a 9
13.6%
s 6
 
9.1%
o 6
 
9.1%
e 5
 
7.6%
n 5
 
7.6%
u 4
 
6.1%
i 4
 
6.1%
g 4
 
6.1%
k 4
 
6.1%
m 3
 
4.5%
Other values (8) 16
24.2%
Space Separator
ValueCountFrequency (%)
30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 919
84.1%
Latin 109
 
10.0%
Common 65
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 64
 
7.0%
사 57
 
6.2%
쇄 44
 
4.8%
판 27
 
2.9%
출 27
 
2.9%
주 23
 
2.5%
디 21
 
2.3%
공 20
 
2.2%
화 19
 
2.1%
문 18
 
2.0%
Other values (203) 599
65.2%
Latin
ValueCountFrequency (%)
a 9
 
8.3%
s 6
 
5.5%
o 6
 
5.5%
e 5
 
4.6%
n 5
 
4.6%
u 4
 
3.7%
i 4
 
3.7%
U 4
 
3.7%
g 4
 
3.7%
k 4
 
3.7%
Other values (28) 58
53.2%
Common
ValueCountFrequency (%)
30
46.2%
) 16
24.6%
( 16
24.6%
- 3
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 919
84.1%
ASCII 174
 
15.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
인 64
 
7.0%
사 57
 
6.2%
쇄 44
 
4.8%
판 27
 
2.9%
출 27
 
2.9%
주 23
 
2.5%
디 21
 
2.3%
공 20
 
2.2%
화 19
 
2.1%
문 18
 
2.0%
Other values (203) 599
65.2%
ASCII
ValueCountFrequency (%)
30
17.2%
) 16
 
9.2%
( 16
 
9.2%
a 9
 
5.2%
s 6
 
3.4%
o 6
 
3.4%
e 5
 
2.9%
n 5
 
2.9%
u 4
 
2.3%
i 4
 
2.3%
Other values (32) 73
42.0%

사업체소재지(도로명)
Text

Distinct136
Distinct (%)86.6%
Missing1
Missing (%)0.6%
Memory size1.4 KiB
2023-12-12T19:40:59.379553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length41
Mean length25.414013
Min length17

Characters and Unicode

Total characters3990
Distinct characters172
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

Unique116 ?
Unique (%)73.9%

Sample

1st row충청남도 공주시 공주대학로 56 (신관동)
2nd row충청남도 공주시 웅진로 156-1 (중동)
3rd row충청남도 공주시 월성산2길 19-1 (옥룡동)
4th row충청남도 공주시 반포면 밀목재길 31
5th row충청남도 공주시 산성찬호길 19-10 (산성동)
ValueCountFrequency (%)
충청남도 156
 
18.5%
공주시 156
 
18.5%
신관동 30
 
3.6%
옥룡동 19
 
2.3%
반죽동 19
 
2.3%
봉황로 14
 
1.7%
중동 13
 
1.5%
우금티로 10
 
1.2%
무령로 10
 
1.2%
교동 9
 
1.1%
Other values (245) 408
48.3%
2023-12-12T19:40:59.879197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
749
18.8%
공 170
 
4.3%
주 170
 
4.3%
남 163
 
4.1%
도 160
 
4.0%
시 159
 
4.0%
충 157
 
3.9%
청 157
 
3.9%
동 143
 
3.6%
1 140
 
3.5%
Other values (162) 1822
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2300
57.6%
Space Separator 749
 
18.8%
Decimal Number 576
 
14.4%
Open Punctuation 126
 
3.2%
Close Punctuation 126
 
3.2%
Dash Punctuation 64
 
1.6%
Other Punctuation 45
 
1.1%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 170
 
7.4%
주 170
 
7.4%
남 163
 
7.1%
도 160
 
7.0%
시 159
 
6.9%
충 157
 
6.8%
청 157
 
6.8%
동 143
 
6.2%
길 82
 
3.6%
로 70
 
3.0%
Other values (146) 869
37.8%
Decimal Number
ValueCountFrequency (%)
1 140
24.3%
2 83
14.4%
3 62
10.8%
5 52
 
9.0%
4 52
 
9.0%
0 42
 
7.3%
7 41
 
7.1%
9 40
 
6.9%
8 33
 
5.7%
6 31
 
5.4%
Space Separator
ValueCountFrequency (%)
749
100.0%
Open Punctuation
ValueCountFrequency (%)
( 126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 126
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 64
100.0%
Other Punctuation
ValueCountFrequency (%)
, 45
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2300
57.6%
Common 1686
42.3%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 170
 
7.4%
주 170
 
7.4%
남 163
 
7.1%
도 160
 
7.0%
시 159
 
6.9%
충 157
 
6.8%
청 157
 
6.8%
동 143
 
6.2%
길 82
 
3.6%
로 70
 
3.0%
Other values (146) 869
37.8%
Common
ValueCountFrequency (%)
749
44.4%
1 140
 
8.3%
( 126
 
7.5%
) 126
 
7.5%
2 83
 
4.9%
- 64
 
3.8%
3 62
 
3.7%
5 52
 
3.1%
4 52
 
3.1%
, 45
 
2.7%
Other values (5) 187
 
11.1%
Latin
ValueCountFrequency (%)
A 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2300
57.6%
ASCII 1690
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
749
44.3%
1 140
 
8.3%
( 126
 
7.5%
) 126
 
7.5%
2 83
 
4.9%
- 64
 
3.8%
3 62
 
3.7%
5 52
 
3.1%
4 52
 
3.1%
, 45
 
2.7%
Other values (6) 191
 
11.3%
Hangul
ValueCountFrequency (%)
공 170
 
7.4%
주 170
 
7.4%
남 163
 
7.1%
도 160
 
7.0%
시 159
 
6.9%
충 157
 
6.8%
청 157
 
6.8%
동 143
 
6.2%
길 82
 
3.6%
로 70
 
3.0%
Other values (146) 869
37.8%

전화번호
Text

MISSING 

Distinct60
Distinct (%)83.3%
Missing86
Missing (%)54.4%
Memory size1.4 KiB
2023-12-12T19:41:00.180523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.041667
Min length12

Characters and Unicode

Total characters867
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

Unique51 ?
Unique (%)70.8%

Sample

1st row041-855-5717
2nd row041-850-6224
3rd row041-857-0776
4th row041-855-4921
5th row041-857-9253
ValueCountFrequency (%)
041-853-0126 5
 
6.9%
041-881-3183 2
 
2.8%
041-856-3191 2
 
2.8%
041-853-0365 2
 
2.8%
041-854-8992 2
 
2.8%
041-856-9633 2
 
2.8%
041-960-2305 2
 
2.8%
041-858-0033 2
 
2.8%
042-824-4055 2
 
2.8%
041-841-3964 1
 
1.4%
Other values (50) 50
69.4%
2023-12-12T19:41:00.667554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 144
16.6%
0 120
13.8%
8 107
12.3%
1 106
12.2%
4 104
12.0%
5 100
11.5%
6 46
 
5.3%
3 45
 
5.2%
7 36
 
4.2%
2 34
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 723
83.4%
Dash Punctuation 144
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 120
16.6%
8 107
14.8%
1 106
14.7%
4 104
14.4%
5 100
13.8%
6 46
 
6.4%
3 45
 
6.2%
7 36
 
5.0%
2 34
 
4.7%
9 25
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 867
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 144
16.6%
0 120
13.8%
8 107
12.3%
1 106
12.2%
4 104
12.0%
5 100
11.5%
6 46
 
5.3%
3 45
 
5.2%
7 36
 
4.2%
2 34
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 867
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 144
16.6%
0 120
13.8%
8 107
12.3%
1 106
12.2%
4 104
12.0%
5 100
11.5%
6 46
 
5.3%
3 45
 
5.2%
7 36
 
4.2%
2 34
 
3.9%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2017-05-15 00:00:00
Maximum2017-05-15 00:00:00
2023-12-12T19:41:00.865647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:41:01.007363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T19:41:01.111156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분전화번호
구분1.0000.000
전화번호0.0001.000

Missing values

2023-12-12T19:40:57.703528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:40:57.827801image/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.
2023-12-12T19:40:57.929862image/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

구분사업체명칭사업체소재지(도로명)전화번호데이터기준일
0출판사공주대학교출판사충청남도 공주시 공주대학로 56 (신관동)<NA>2017-05-15
1출판사공주합동출판인쇄공사충청남도 공주시 웅진로 156-1 (중동)<NA>2017-05-15
2출판사시사논평사충청남도 공주시 월성산2길 19-1 (옥룡동)<NA>2017-05-15
3출판사순리세계사충청남도 공주시 반포면 밀목재길 31<NA>2017-05-15
4출판사공명출판사충청남도 공주시 산성찬호길 19-10 (산성동)<NA>2017-05-15
5출판사공주종합인쇄출판사충청남도 공주시 무령로 195 (교동)041-855-57172017-05-15
6출판사공주민속극박물관출판부충청남도 공주시 의당면 돌모루2길 17-15<NA>2017-05-15
7출판사도서출판디지털만화사충청남도 공주시 우금티로 753, 320호 (옥룡동,영상보건대문화관)041-850-62242017-05-15
8출판사도움디자인충청남도 공주시 번영3로 53 (신관동)<NA>2017-05-15
9출판사(주)공주신문출판국충청남도 공주시 봉황로 125 (교동)041-857-07762017-05-15
구분사업체명칭사업체소재지(도로명)전화번호데이터기준일
148인쇄사사거리인쇄광고기획충청남도 공주시 버드나무1길 공중 13-1 (옥룡동)041-853-01262017-05-15
149인쇄사대성상사충청남도 공주시 봉황로 22 (봉황동)041-856-25952017-05-15
150인쇄사일신인쇄문화사충청남도 공주시 장기로 117 (금흥동)<NA>2017-05-15
151인쇄사광고인충청남도 공주시 전막2길 32-9 (신관동)041-852-98872017-05-15
152인쇄사주식회사 파워뉴스충청남도 공주시 먹자2길 13 (중동)<NA>2017-05-15
153인쇄사미래광고충청남도 공주시 감영길 11 (반죽동)041-852-58812017-05-15
154인쇄사신양문화사충청남도 공주시 정자방1길 26-4 (금성동)<NA>2017-05-15
155인쇄사kongkam(공감투데이)충청남도 공주시 우금티로 746 (옥룡동)<NA>2017-05-15
156인쇄사우신안전광고공사충청남도 공주시 전막3길 4-3 (신관동)041-854-32012017-05-15
157인쇄사그린건설광고기획충청남도 공주시 연수원길 5 (금흥동)041-854-83002017-05-15