Overview

Dataset statistics

Number of variables12
Number of observations33
Missing cells10
Missing cells (%)2.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory100.0 B

Variable types

Categorical6
Text6

Dataset

Description낚시산업 정보 입니다
Author해양수산부
URLhttps://www.data.go.kr/data/15070721/fileData.do

Alerts

미디어 is highly overall correlated with 조구업체 and 1 other fieldsHigh correlation
판매점 is highly overall correlated with 조구업체 and 3 other fieldsHigh correlation
낚시정보제공 is highly overall correlated with 조구업체 and 2 other fieldsHigh correlation
조구업체 is highly overall correlated with 미디어 and 3 other fieldsHigh correlation
출조점 is highly overall correlated with 조구업체 and 2 other fieldsHigh correlation
일반전화 has 7 (21.2%) missing valuesMissing
사업영역 has 3 (9.1%) missing valuesMissing
상호명 has unique valuesUnique
대표자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:24:38.045152
Analysis finished2023-12-12 16:24:39.020695
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

협회/기관/단체
Categorical

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
24 
협회/기관/단체
9 

Length

Max length8
Median length4
Mean length5.0909091
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 24
72.7%
협회/기관/단체 9
 
27.3%

Length

2023-12-13T01:24:39.081511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:24:39.209155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 24
72.7%
협회/기관/단체 9
 
27.3%

조구업체
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
20 
조구업체
13 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row조구업체
4th row조구업체
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 20
60.6%
조구업체 13
39.4%

Length

2023-12-13T01:24:39.315465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:24:39.399819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
60.6%
조구업체 13
39.4%

미디어
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
29 
미디어
4 

Length

Max length4
Median length4
Mean length3.8787879
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미디어
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 29
87.9%
미디어 4
 
12.1%

Length

2023-12-13T01:24:39.492367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:24:39.594395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
87.9%
미디어 4
 
12.1%

판매점
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
23 
판매점
10 

Length

Max length4
Median length4
Mean length3.6969697
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row판매점
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 23
69.7%
판매점 10
30.3%

Length

2023-12-13T01:24:39.700226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:24:39.785419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 23
69.7%
판매점 10
30.3%

출조점
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
28 
출조점
5 

Length

Max length4
Median length4
Mean length3.8484848
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row출조점
3rd row<NA>
4th row<NA>
5th row출조점

Common Values

ValueCountFrequency (%)
<NA> 28
84.8%
출조점 5
 
15.2%

Length

2023-12-13T01:24:39.873026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:24:40.210970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 28
84.8%
출조점 5
 
15.2%

낚시정보제공
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size396.0 B
<NA>
29 
낚시정보제공
4 

Length

Max length6
Median length4
Mean length4.2424242
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row낚시정보제공
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 29
87.9%
낚시정보제공 4
 
12.1%

Length

2023-12-13T01:24:40.314004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:24:40.409327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
87.9%
낚시정보제공 4
 
12.1%

상호명
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T01:24:40.608121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length6.2424242
Min length2

Characters and Unicode

Total characters206
Distinct characters92
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row(주)한국낚시채널
2nd row만남낚시점
3rd row유승조구산업
4th row아오맥스
5th row코리아나피싱
ValueCountFrequency (%)
주)한국낚시채널 1
 
2.9%
사)한국프로낚시연맹 1
 
2.9%
통영아라피싱 1
 
2.9%
군산낚시일번지 1
 
2.9%
여수만물상낚시 1
 
2.9%
사)한국낚시협회 1
 
2.9%
사)한국스포츠피싱협회 1
 
2.9%
한국쏘가리협회 1
 
2.9%
사)한국낚시업중앙회 1
 
2.9%
코러낚시 1
 
2.9%
Other values (25) 25
71.4%
2023-12-13T01:24:40.953306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 17
 
8.3%
낚 16
 
7.8%
한 10
 
4.9%
국 10
 
4.9%
( 7
 
3.4%
) 7
 
3.4%
회 7
 
3.4%
사 6
 
2.9%
협 6
 
2.9%
스 5
 
2.4%
Other values (82) 115
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 187
90.8%
Open Punctuation 7
 
3.4%
Close Punctuation 7
 
3.4%
Decimal Number 3
 
1.5%
Space Separator 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 17
 
9.1%
낚 16
 
8.6%
한 10
 
5.3%
국 10
 
5.3%
회 7
 
3.7%
사 6
 
3.2%
협 6
 
3.2%
스 5
 
2.7%
피 5
 
2.7%
아 4
 
2.1%
Other values (76) 101
54.0%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
6 1
33.3%
5 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 187
90.8%
Common 19
 
9.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 17
 
9.1%
낚 16
 
8.6%
한 10
 
5.3%
국 10
 
5.3%
회 7
 
3.7%
사 6
 
3.2%
협 6
 
3.2%
스 5
 
2.7%
피 5
 
2.7%
아 4
 
2.1%
Other values (76) 101
54.0%
Common
ValueCountFrequency (%)
( 7
36.8%
) 7
36.8%
2
 
10.5%
3 1
 
5.3%
6 1
 
5.3%
5 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 187
90.8%
ASCII 19
 
9.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 17
 
9.1%
낚 16
 
8.6%
한 10
 
5.3%
국 10
 
5.3%
회 7
 
3.7%
사 6
 
3.2%
협 6
 
3.2%
스 5
 
2.7%
피 5
 
2.7%
아 4
 
2.1%
Other values (76) 101
54.0%
ASCII
ValueCountFrequency (%)
( 7
36.8%
) 7
36.8%
2
 
10.5%
3 1
 
5.3%
6 1
 
5.3%
5 1
 
5.3%

대표자
Text

UNIQUE 

Distinct33
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T01:24:41.188922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length3
Mean length4.0909091
Min length3

Characters and Unicode

Total characters135
Distinct characters67
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row나채재
2nd row이막래
3rd row이기용
4th row권택규
5th row이춘석
ValueCountFrequency (%)
회장 8
 
18.6%
나채재 1
 
2.3%
이막래 1
 
2.3%
임혁진 1
 
2.3%
배상준 1
 
2.3%
정연화 1
 
2.3%
김정구 1
 
2.3%
공동회장 1
 
2.3%
김선규 1
 
2.3%
장재학 1
 
2.3%
Other values (26) 26
60.5%
2023-12-13T01:24:41.703009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
 
7.4%
장 10
 
7.4%
회 9
 
6.7%
김 8
 
5.9%
이 6
 
4.4%
현 4
 
3.0%
종 3
 
2.2%
기 3
 
2.2%
재 3
 
2.2%
권 3
 
2.2%
Other values (57) 76
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 124
91.9%
Space Separator 10
 
7.4%
Other Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 10
 
8.1%
회 9
 
7.3%
김 8
 
6.5%
이 6
 
4.8%
현 4
 
3.2%
종 3
 
2.4%
기 3
 
2.4%
재 3
 
2.4%
권 3
 
2.4%
임 3
 
2.4%
Other values (55) 72
58.1%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 124
91.9%
Common 11
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 10
 
8.1%
회 9
 
7.3%
김 8
 
6.5%
이 6
 
4.8%
현 4
 
3.2%
종 3
 
2.4%
기 3
 
2.4%
재 3
 
2.4%
권 3
 
2.4%
임 3
 
2.4%
Other values (55) 72
58.1%
Common
ValueCountFrequency (%)
10
90.9%
, 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 124
91.9%
ASCII 11
 
8.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
90.9%
, 1
 
9.1%
Hangul
ValueCountFrequency (%)
장 10
 
8.1%
회 9
 
7.3%
김 8
 
6.5%
이 6
 
4.8%
현 4
 
3.2%
종 3
 
2.4%
기 3
 
2.4%
재 3
 
2.4%
권 3
 
2.4%
임 3
 
2.4%
Other values (55) 72
58.1%

일반전화
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing7
Missing (%)21.2%
Memory size396.0 B
2023-12-13T01:24:41.949528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.730769
Min length9

Characters and Unicode

Total characters305
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

Unique26 ?
Unique (%)100.0%

Sample

1st row031-663-7898
2nd row051-624-5040
3rd row053-812-2775
4th row032-811-1880
5th row055-295-3655
ValueCountFrequency (%)
031-663-7898 1
 
3.8%
051-624-5040 1
 
3.8%
02-2671-3790 1
 
3.8%
031-564-2733 1
 
3.8%
02-957-1811 1
 
3.8%
02-334-7330 1
 
3.8%
070-7517-9701 1
 
3.8%
031-227-0744 1
 
3.8%
055-645-3987 1
 
3.8%
043-423-3438 1
 
3.8%
Other values (16) 16
61.5%
2023-12-13T01:24:42.379668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 51
16.7%
0 43
14.1%
2 32
10.5%
1 29
9.5%
7 29
9.5%
5 29
9.5%
3 27
8.9%
8 24
7.9%
4 15
 
4.9%
6 14
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 254
83.3%
Dash Punctuation 51
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 43
16.9%
2 32
12.6%
1 29
11.4%
7 29
11.4%
5 29
11.4%
3 27
10.6%
8 24
9.4%
4 15
 
5.9%
6 14
 
5.5%
9 12
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 305
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 51
16.7%
0 43
14.1%
2 32
10.5%
1 29
9.5%
7 29
9.5%
5 29
9.5%
3 27
8.9%
8 24
7.9%
4 15
 
4.9%
6 14
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 305
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 51
16.7%
0 43
14.1%
2 32
10.5%
1 29
9.5%
7 29
9.5%
5 29
9.5%
3 27
8.9%
8 24
7.9%
4 15
 
4.9%
6 14
 
4.6%

사업영역
Text

MISSING 

Distinct29
Distinct (%)96.7%
Missing3
Missing (%)9.1%
Memory size396.0 B
2023-12-13T01:24:42.684746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length31
Mean length16.333333
Min length5

Characters and Unicode

Total characters490
Distinct characters129
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)93.3%

Sample

1st row낚시방송, 낚시용품판매, 광고
2nd row낚시용품,미끼/마트제품 일체 판매,낚시정보제공,출조선박대기
3rd row낚시바늘 제조
4th row낚시대 개발,제조,판매
5th row먼바다출조.내만권 참돔.볼락
ValueCountFrequency (%)
제조 6
 
6.5%
낚시 5
 
5.4%
판매 4
 
4.3%
및 4
 
4.3%
사단법인 4
 
4.3%
낚시대 3
 
3.2%
낚시방송 2
 
2.2%
광고 2
 
2.2%
낚시용품판매 2
 
2.2%
제작 2
 
2.2%
Other values (58) 59
63.4%
2023-12-13T01:24:43.106611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
12.9%
시 43
 
8.8%
낚 42
 
8.6%
, 23
 
4.7%
제 15
 
3.1%
조 15
 
3.1%
품 10
 
2.0%
매 10
 
2.0%
. 9
 
1.8%
판 9
 
1.8%
Other values (119) 251
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 390
79.6%
Space Separator 63
 
12.9%
Other Punctuation 35
 
7.1%
Uppercase Letter 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 43
 
11.0%
낚 42
 
10.8%
제 15
 
3.8%
조 15
 
3.8%
품 10
 
2.6%
매 10
 
2.6%
판 9
 
2.3%
수 8
 
2.1%
한 8
 
2.1%
국 8
 
2.1%
Other values (113) 222
56.9%
Other Punctuation
ValueCountFrequency (%)
, 23
65.7%
. 9
 
25.7%
/ 3
 
8.6%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 390
79.6%
Common 98
 
20.0%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 43
 
11.0%
낚 42
 
10.8%
제 15
 
3.8%
조 15
 
3.8%
품 10
 
2.6%
매 10
 
2.6%
판 9
 
2.3%
수 8
 
2.1%
한 8
 
2.1%
국 8
 
2.1%
Other values (113) 222
56.9%
Common
ValueCountFrequency (%)
63
64.3%
, 23
 
23.5%
. 9
 
9.2%
/ 3
 
3.1%
Latin
ValueCountFrequency (%)
S 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 390
79.6%
ASCII 100
 
20.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
63.0%
, 23
 
23.0%
. 9
 
9.0%
/ 3
 
3.0%
S 1
 
1.0%
A 1
 
1.0%
Hangul
ValueCountFrequency (%)
시 43
 
11.0%
낚 42
 
10.8%
제 15
 
3.8%
조 15
 
3.8%
품 10
 
2.6%
매 10
 
2.6%
판 9
 
2.3%
수 8
 
2.1%
한 8
 
2.1%
국 8
 
2.1%
Other values (113) 222
56.9%

홈페이지
Text

Distinct32
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T01:24:43.333390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length21.212121
Min length7

Characters and Unicode

Total characters700
Distinct characters38
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)93.9%

Sample

1st rowhttp://eftv.co.kr
2nd rowhttp://
3rd rowhttp://youseunghook.com
4th rowhttp://www.aomex.co.kr
5th rowhttp://
ValueCountFrequency (%)
http 2
 
6.1%
http://eftv.co.kr 1
 
3.0%
http://www.fishingtv.kr 1
 
3.0%
http://www.kff.or.kr 1
 
3.0%
http://www.gyeonji.net 1
 
3.0%
http://www.seoulfishing.or.kr 1
 
3.0%
http://www.lfa.or.kr 1
 
3.0%
http://www.koreafca.or.kr 1
 
3.0%
http://www.kpfa.co.kr 1
 
3.0%
http://www.kssa.co.kr 1
 
3.0%
Other values (22) 22
66.7%
2023-12-13T01:24:43.730768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 73
 
10.4%
/ 71
 
10.1%
. 70
 
10.0%
w 66
 
9.4%
o 44
 
6.3%
h 40
 
5.7%
p 36
 
5.1%
k 35
 
5.0%
: 33
 
4.7%
r 31
 
4.4%
Other values (28) 201
28.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 508
72.6%
Other Punctuation 174
 
24.9%
Other Letter 9
 
1.3%
Decimal Number 7
 
1.0%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 73
14.4%
w 66
13.0%
o 44
 
8.7%
h 40
 
7.9%
p 36
 
7.1%
k 35
 
6.9%
r 31
 
6.1%
c 24
 
4.7%
a 21
 
4.1%
s 20
 
3.9%
Other values (14) 118
23.2%
Other Letter
ValueCountFrequency (%)
시 2
22.2%
낚 2
22.2%
군 1
11.1%
산 1
11.1%
만 1
11.1%
물 1
11.1%
상 1
11.1%
Other Punctuation
ValueCountFrequency (%)
/ 71
40.8%
. 70
40.2%
: 33
19.0%
Decimal Number
ValueCountFrequency (%)
1 4
57.1%
7 2
28.6%
4 1
 
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 508
72.6%
Common 183
 
26.1%
Hangul 9
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 73
14.4%
w 66
13.0%
o 44
 
8.7%
h 40
 
7.9%
p 36
 
7.1%
k 35
 
6.9%
r 31
 
6.1%
c 24
 
4.7%
a 21
 
4.1%
s 20
 
3.9%
Other values (14) 118
23.2%
Common
ValueCountFrequency (%)
/ 71
38.8%
. 70
38.3%
: 33
18.0%
1 4
 
2.2%
- 2
 
1.1%
7 2
 
1.1%
4 1
 
0.5%
Hangul
ValueCountFrequency (%)
시 2
22.2%
낚 2
22.2%
군 1
11.1%
산 1
11.1%
만 1
11.1%
물 1
11.1%
상 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 691
98.7%
Hangul 9
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 73
 
10.6%
/ 71
 
10.3%
. 70
 
10.1%
w 66
 
9.6%
o 44
 
6.4%
h 40
 
5.8%
p 36
 
5.2%
k 35
 
5.1%
: 33
 
4.8%
r 31
 
4.5%
Other values (21) 192
27.8%
Hangul
ValueCountFrequency (%)
시 2
22.2%
낚 2
22.2%
군 1
11.1%
산 1
11.1%
만 1
11.1%
물 1
11.1%
상 1
11.1%

사업장주소
Text

Distinct32
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size396.0 B
2023-12-13T01:24:44.054831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length34
Mean length30.272727
Min length15

Characters and Unicode

Total characters999
Distinct characters181
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

Unique31 ?
Unique (%)93.9%

Sample

1st row경기 성남시 분당구 판교로 242 (삼평동)판교디지털센터 A동 1001호
2nd row경남 거제시 장목면 거제북로 2598 (송진포리)송진포리61-1
3rd row부산 사하구 보덕포1길 85-6 (장림동)유승산업
4th row경기 평택시 청북읍 청북중앙로 9-39 (후사리)아오맥스
5th row경남 통영시 미우지해안로 121 (미수동, 우성수산)우성수산 맞은편
ValueCountFrequency (%)
경기 8
 
4.0%
서울 5
 
2.5%
경남 5
 
2.5%
부산 4
 
2.0%
대구 3
 
1.5%
통영시 3
 
1.5%
동구 3
 
1.5%
성남시 2
 
1.0%
분당구 2
 
1.0%
사하구 2
 
1.0%
Other values (157) 161
81.3%
2023-12-13T01:24:44.561698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
166
 
16.6%
동 44
 
4.4%
) 33
 
3.3%
( 33
 
3.3%
1 33
 
3.3%
구 31
 
3.1%
로 28
 
2.8%
2 23
 
2.3%
0 22
 
2.2%
산 20
 
2.0%
Other values (171) 566
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 580
58.1%
Space Separator 166
 
16.6%
Decimal Number 155
 
15.5%
Close Punctuation 33
 
3.3%
Open Punctuation 33
 
3.3%
Other Punctuation 15
 
1.5%
Dash Punctuation 9
 
0.9%
Uppercase Letter 7
 
0.7%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 44
 
7.6%
구 31
 
5.3%
로 28
 
4.8%
산 20
 
3.4%
시 20
 
3.4%
경 15
 
2.6%
남 15
 
2.6%
호 12
 
2.1%
기 10
 
1.7%
대 9
 
1.6%
Other values (149) 376
64.8%
Decimal Number
ValueCountFrequency (%)
1 33
21.3%
2 23
14.8%
0 22
14.2%
3 16
10.3%
5 15
9.7%
6 13
 
8.4%
4 11
 
7.1%
9 10
 
6.5%
7 7
 
4.5%
8 5
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 2
28.6%
K 2
28.6%
A 1
14.3%
D 1
14.3%
F 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 14
93.3%
. 1
 
6.7%
Space Separator
ValueCountFrequency (%)
166
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 580
58.1%
Common 411
41.1%
Latin 8
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 44
 
7.6%
구 31
 
5.3%
로 28
 
4.8%
산 20
 
3.4%
시 20
 
3.4%
경 15
 
2.6%
남 15
 
2.6%
호 12
 
2.1%
기 10
 
1.7%
대 9
 
1.6%
Other values (149) 376
64.8%
Common
ValueCountFrequency (%)
166
40.4%
) 33
 
8.0%
( 33
 
8.0%
1 33
 
8.0%
2 23
 
5.6%
0 22
 
5.4%
3 16
 
3.9%
5 15
 
3.6%
, 14
 
3.4%
6 13
 
3.2%
Other values (6) 43
 
10.5%
Latin
ValueCountFrequency (%)
B 2
25.0%
K 2
25.0%
n 1
12.5%
A 1
12.5%
D 1
12.5%
F 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 580
58.1%
ASCII 419
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
166
39.6%
) 33
 
7.9%
( 33
 
7.9%
1 33
 
7.9%
2 23
 
5.5%
0 22
 
5.3%
3 16
 
3.8%
5 15
 
3.6%
, 14
 
3.3%
6 13
 
3.1%
Other values (12) 51
 
12.2%
Hangul
ValueCountFrequency (%)
동 44
 
7.6%
구 31
 
5.3%
로 28
 
4.8%
산 20
 
3.4%
시 20
 
3.4%
경 15
 
2.6%
남 15
 
2.6%
호 12
 
2.1%
기 10
 
1.7%
대 9
 
1.6%
Other values (149) 376
64.8%

Correlations

2023-12-13T01:24:44.669804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호명대표자일반전화사업영역홈페이지사업장주소
상호명1.0001.0001.0001.0001.0001.000
대표자1.0001.0001.0001.0001.0001.000
일반전화1.0001.0001.0001.0001.0001.000
사업영역1.0001.0001.0001.0000.9900.990
홈페이지1.0001.0001.0000.9901.0000.992
사업장주소1.0001.0001.0000.9900.9921.000
2023-12-13T01:24:44.789203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
미디어판매점낚시정보제공조구업체협회/기관/단체출조점
미디어1.0001.000NaN1.000NaNNaN
판매점1.0001.0001.0001.000NaN1.000
낚시정보제공NaN1.0001.0001.000NaN1.000
조구업체1.0001.0001.0001.000NaN1.000
협회/기관/단체NaNNaNNaNNaN1.000NaN
출조점NaN1.0001.0001.000NaN1.000
2023-12-13T01:24:44.912886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
협회/기관/단체조구업체미디어판매점출조점낚시정보제공
협회/기관/단체1.0000.0000.0000.0000.0000.000
조구업체0.0001.0001.0001.0001.0001.000
미디어0.0001.0001.0001.0000.000NaN
판매점0.0001.0001.0001.0001.0001.000
출조점0.0001.0000.0001.0001.0001.000
낚시정보제공0.0001.000NaN1.0001.0001.000

Missing values

2023-12-13T01:24:38.665611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:24:38.806083image/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.
2023-12-13T01:24:38.937227image/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

협회/기관/단체조구업체미디어판매점출조점낚시정보제공상호명대표자일반전화사업영역홈페이지사업장주소
0<NA><NA>미디어<NA><NA><NA>(주)한국낚시채널나채재<NA>낚시방송, 낚시용품판매, 광고http://eftv.co.kr경기 성남시 분당구 판교로 242 (삼평동)판교디지털센터 A동 1001호
1<NA><NA><NA>판매점출조점낚시정보제공만남낚시점이막래<NA>낚시용품,미끼/마트제품 일체 판매,낚시정보제공,출조선박대기http://경남 거제시 장목면 거제북로 2598 (송진포리)송진포리61-1
2<NA>조구업체<NA><NA><NA><NA>유승조구산업이기용<NA>낚시바늘 제조http://youseunghook.com부산 사하구 보덕포1길 85-6 (장림동)유승산업
3<NA>조구업체<NA><NA><NA><NA>아오맥스권택규031-663-7898낚시대 개발,제조,판매http://www.aomex.co.kr경기 평택시 청북읍 청북중앙로 9-39 (후사리)아오맥스
4<NA><NA><NA><NA>출조점<NA>코리아나피싱이춘석<NA>먼바다출조.내만권 참돔.볼락http://경남 통영시 미우지해안로 121 (미수동, 우성수산)우성수산 맞은편
5<NA>조구업체미디어판매점<NA>낚시정보제공긱스이성규051-624-5040낚시 장비 제조, 낚시찌 제조, 낚시 소품 제조, 유튜브 낚시 교육 컨텐츠 제작http://gigskorea.com부산 수영구 망미로27번길 42 (광안동)3층 긱스
6<NA>조구업체<NA><NA><NA><NA>현대상사권용현053-812-2775낚시 가방,의자 및 특수 봉제http://www.assokorea.com경북 경산시 백천서로 102 (옥곡동)
7<NA>조구업체<NA><NA><NA><NA>피싱조이김중태032-811-1880낚시용품제조, 전동릴배터리, 낚시용배터리http://www.fishingjoy.co.kr인천 남동구 선수촌공원로 1 (구월동, 구월테크노밸리(자족1-4))구월테크노밸리 D동 402호
8<NA><NA><NA>판매점<NA><NA>365낚시마트임명숙055-295-3655낚시용품, 낚시대 제조 및 판매http://samyuko.kr경남 창원시 마산회원구 3.15대로 601 (석전동, 365낚시마트)1층
9<NA><NA><NA>판매점<NA><NA>가자낚시서경옥052-287-8990낚시장비/용품 판매, 출조정보http://www.ok1717.com울산 중구 염포로 96 (반구동)
협회/기관/단체조구업체미디어판매점출조점낚시정보제공상호명대표자일반전화사업영역홈페이지사업장주소
23협회/기관/단체<NA><NA><NA><NA><NA>(사)한국스포츠피싱협회김선규 회장02-777-3885사단법인 한국스포츠피싱협회http://sportfishing.co.kr/서울 종로구 와룡동 74201호
24협회/기관/단체<NA><NA><NA><NA><NA>한국쏘가리협회장재학 회장043-423-3438한국쏘가리협회http://www.kssa.co.kr충북 단양군 단양읍 별곡리 15-6(공설운동장내 1층)
25협회/기관/단체<NA><NA><NA><NA><NA>(사)한국프로낚시연맹박재홍 회장055-645-3987사단법인 한국프로낚시연맹http://www.kpfa.co.kr경남 통영시 중앙로 258 (북신동, 우정사진관)
26협회/기관/단체<NA><NA><NA><NA><NA>(사)한국낚시업중앙회성기억 회장031-227-0744사단법인 한국낚시업중앙회http://www.koreafca.or.kr경기 안성시 일죽면 송천길 71 (송천리)
27협회/기관/단체<NA><NA><NA><NA><NA>한국루어낚시협회이찬구 회장070-7517-9701한국루어낚시협회http://www.lfa.or.kr경기 성남시 분당구 구미로 60 (구미동, 관보쇼핑)209호
28협회/기관/단체<NA><NA><NA><NA><NA>서울시 낚시협회이춘근 회장02-334-7330서울시 낚시협회http://www.seoulfishing.or.kr/서울 마포구 서강로 61 (창전동)1층
29협회/기관/단체<NA><NA><NA><NA><NA>한국견지낚시협회류권현 회장02-957-1811한국견지낚시협회http://www.gyeonji.net/서울 동대문구 고산자로 459 (제기동)부림빌딩 403호
30협회/기관/단체<NA><NA><NA><NA><NA>한국낚시연합김동현 회장031-564-2733한국낚시연합http://www.kff.or.kr경기 구리시 교문동 307-9302호
31<NA><NA>미디어<NA><NA><NA>한국낚시방송김영준02-2671-3790낚시방송, 낚시용품판매, 광고http://www.fishingtv.kr/서울 영등포구 영신로 220 (영등포동8가, KnK디지털타워)201호
32<NA><NA><NA><NA><NA>낚시정보제공바다사랑바다사랑팀1800-7290바다선상낚시, 바다낚시터, 출조점 예약 및 조황정보 제공http://www.naksi.co.kr대전 서구 갈마역로 14 (둔산동, 하이스트빌)203호