Overview

Dataset statistics

Number of variables10
Number of observations184
Missing cells110
Missing cells (%)6.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.7 KiB
Average record size in memory81.7 B

Variable types

Text6
DateTime1
Categorical2
Numeric1

Dataset

Description산림사업법인나무병원포함등록현황2019년
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202182

Alerts

팩스번호 has 109 (59.2%) missing valuesMissing
등록번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:28:44.881632
Analysis finished2024-03-14 01:28:45.575497
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

등록번호
Text

UNIQUE 

Distinct184
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-14T10:28:45.719238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length13.076087
Min length10

Characters and Unicode

Total characters2406
Distinct characters23
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

Unique184 ?
Unique (%)100.0%

Sample

1st row전북2017-006(0)
2nd row전북2017-004(0)
3rd row전북2016-013(0)
4th row전북2009-015(1)
5th row전북2016-003(0)
ValueCountFrequency (%)
전북2017-006(0 1
 
0.5%
경북2018-017(0 1
 
0.5%
경북2012-028(6 1
 
0.5%
전북2013-007(0 1
 
0.5%
전북2013-016(2 1
 
0.5%
전북2015-027(0 1
 
0.5%
t-전북2019-002 1
 
0.5%
전북2017-007(0 1
 
0.5%
전북2016-015(0 1
 
0.5%
전북2017-018(0 1
 
0.5%
Other values (174) 174
94.6%
2024-03-14T10:28:46.113197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 597
24.8%
1 278
11.6%
2 268
11.1%
- 222
 
9.2%
( 175
 
7.3%
) 175
 
7.3%
전 157
 
6.5%
북 142
 
5.9%
8 71
 
3.0%
3 55
 
2.3%
Other values (13) 266
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1467
61.0%
Other Letter 332
 
13.8%
Dash Punctuation 222
 
9.2%
Open Punctuation 175
 
7.3%
Close Punctuation 175
 
7.3%
Uppercase Letter 35
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 597
40.7%
1 278
19.0%
2 268
18.3%
8 71
 
4.8%
3 55
 
3.7%
5 45
 
3.1%
4 45
 
3.1%
6 41
 
2.8%
7 37
 
2.5%
9 30
 
2.0%
Other Letter
ValueCountFrequency (%)
전 157
47.3%
북 142
42.8%
남 21
 
6.3%
충 3
 
0.9%
경 3
 
0.9%
강 2
 
0.6%
원 2
 
0.6%
광 1
 
0.3%
주 1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 222
100.0%
Open Punctuation
ValueCountFrequency (%)
( 175
100.0%
Close Punctuation
ValueCountFrequency (%)
) 175
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2039
84.7%
Hangul 332
 
13.8%
Latin 35
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 597
29.3%
1 278
13.6%
2 268
13.1%
- 222
 
10.9%
( 175
 
8.6%
) 175
 
8.6%
8 71
 
3.5%
3 55
 
2.7%
5 45
 
2.2%
4 45
 
2.2%
Other values (3) 108
 
5.3%
Hangul
ValueCountFrequency (%)
전 157
47.3%
북 142
42.8%
남 21
 
6.3%
충 3
 
0.9%
경 3
 
0.9%
강 2
 
0.6%
원 2
 
0.6%
광 1
 
0.3%
주 1
 
0.3%
Latin
ValueCountFrequency (%)
T 35
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2074
86.2%
Hangul 332
 
13.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 597
28.8%
1 278
13.4%
2 268
12.9%
- 222
 
10.7%
( 175
 
8.4%
) 175
 
8.4%
8 71
 
3.4%
3 55
 
2.7%
5 45
 
2.2%
4 45
 
2.2%
Other values (4) 143
 
6.9%
Hangul
ValueCountFrequency (%)
전 157
47.3%
북 142
42.8%
남 21
 
6.3%
충 3
 
0.9%
경 3
 
0.9%
강 2
 
0.6%
원 2
 
0.6%
광 1
 
0.3%
주 1
 
0.3%

등록일자
Date

Distinct124
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2002-12-11 00:00:00
Maximum2019-03-13 00:00:00
2024-03-14T10:28:46.253641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:28:46.361821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

법인명
Text

Distinct135
Distinct (%)73.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-14T10:28:46.576103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length7.7282609
Min length2

Characters and Unicode

Total characters1422
Distinct characters164
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)50.5%

Sample

1st row백제조경주식회사
2nd row주식회사 영웅
3rd row(유)미소조경
4th row(유)성민종합개발
5th row(유)이안조경
ValueCountFrequency (%)
유한회사 35
 
14.0%
주식회사 28
 
11.2%
유한회사늘푸른산림개발 5
 
2.0%
주)신림조경건설 3
 
1.2%
대원산림개발(유 3
 
1.2%
유)삼성종합건설 3
 
1.2%
유)태산임업 3
 
1.2%
유)산울림 2
 
0.8%
유)포레시스 2
 
0.8%
미산 2
 
0.8%
Other values (129) 164
65.6%
2024-03-14T10:28:46.918542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 115
 
8.1%
( 105
 
7.4%
) 105
 
7.4%
사 78
 
5.5%
회 74
 
5.2%
68
 
4.8%
주 65
 
4.6%
한 46
 
3.2%
산 42
 
3.0%
림 41
 
2.9%
Other values (154) 683
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1140
80.2%
Open Punctuation 105
 
7.4%
Close Punctuation 105
 
7.4%
Space Separator 68
 
4.8%
Other Symbol 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 115
 
10.1%
사 78
 
6.8%
회 74
 
6.5%
주 65
 
5.7%
한 46
 
4.0%
산 42
 
3.7%
림 41
 
3.6%
건 34
 
3.0%
식 32
 
2.8%
경 32
 
2.8%
Other values (150) 581
51.0%
Open Punctuation
ValueCountFrequency (%)
( 105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 105
100.0%
Space Separator
ValueCountFrequency (%)
68
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1144
80.5%
Common 278
 
19.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 115
 
10.1%
사 78
 
6.8%
회 74
 
6.5%
주 65
 
5.7%
한 46
 
4.0%
산 42
 
3.7%
림 41
 
3.6%
건 34
 
3.0%
식 32
 
2.8%
경 32
 
2.8%
Other values (151) 585
51.1%
Common
ValueCountFrequency (%)
( 105
37.8%
) 105
37.8%
68
24.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1140
80.2%
ASCII 278
 
19.5%
None 4
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 115
 
10.1%
사 78
 
6.8%
회 74
 
6.5%
주 65
 
5.7%
한 46
 
4.0%
산 42
 
3.7%
림 41
 
3.6%
건 34
 
3.0%
식 32
 
2.8%
경 32
 
2.8%
Other values (150) 581
51.0%
ASCII
ValueCountFrequency (%)
( 105
37.8%
) 105
37.8%
68
24.5%
None
ValueCountFrequency (%)
㈜ 4
100.0%

대표자
Text

Distinct129
Distinct (%)70.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-14T10:28:47.219522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.0706522
Min length2

Characters and Unicode

Total characters565
Distinct characters110
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

Unique87 ?
Unique (%)47.3%

Sample

1st row지애란
2nd row서범석
3rd row이희원
4th row조남영
5th row한상돈
ValueCountFrequency (%)
최현옥 5
 
2.6%
김동욱 4
 
2.1%
최성관 4
 
2.1%
황은정 3
 
1.6%
차상기 3
 
1.6%
한웅진 3
 
1.6%
이세진 3
 
1.6%
송기창 3
 
1.6%
서범석 3
 
1.6%
오미영 2
 
1.0%
Other values (125) 159
82.8%
2024-03-14T10:28:47.610680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 42
 
7.4%
최 22
 
3.9%
현 19
 
3.4%
이 18
 
3.2%
영 17
 
3.0%
정 17
 
3.0%
기 12
 
2.1%
미 11
 
1.9%
한 10
 
1.8%
우 10
 
1.8%
Other values (100) 387
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 555
98.2%
Space Separator 9
 
1.6%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 42
 
7.6%
최 22
 
4.0%
현 19
 
3.4%
이 18
 
3.2%
영 17
 
3.1%
정 17
 
3.1%
기 12
 
2.2%
미 11
 
2.0%
한 10
 
1.8%
우 10
 
1.8%
Other values (98) 377
67.9%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 555
98.2%
Common 10
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 42
 
7.6%
최 22
 
4.0%
현 19
 
3.4%
이 18
 
3.2%
영 17
 
3.1%
정 17
 
3.1%
기 12
 
2.2%
미 11
 
2.0%
한 10
 
1.8%
우 10
 
1.8%
Other values (98) 377
67.9%
Common
ValueCountFrequency (%)
9
90.0%
, 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 555
98.2%
ASCII 10
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 42
 
7.6%
최 22
 
4.0%
현 19
 
3.4%
이 18
 
3.2%
영 17
 
3.1%
정 17
 
3.1%
기 12
 
2.2%
미 11
 
2.0%
한 10
 
1.8%
우 10
 
1.8%
Other values (98) 377
67.9%
ASCII
ValueCountFrequency (%)
9
90.0%
, 1
 
10.0%

사업의 종류
Categorical

Distinct10
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
도시림등 조성
59 
숲가꾸기 및 병해충방제
43 
산림토목
40 
1종 나무병원
24 
2종 나무병원
11 
Other values (5)
7 

Length

Max length13
Median length7
Mean length7.5597826
Min length3

Unique

Unique3 ?
Unique (%)1.6%

Sample

1st row도시림등 조성
2nd row도시림등 조성
3rd row도시림등 조성
4th row도시림등 조성
5th row도시림등 조성

Common Values

ValueCountFrequency (%)
도시림등 조성 59
32.1%
숲가꾸기 및 병해충방제 43
23.4%
산림토목 40
21.7%
1종 나무병원 24
13.0%
2종 나무병원 11
 
6.0%
산림경영계획 및 산림조사 2
 
1.1%
자연휴양림 등 조성 2
 
1.1%
도시림 1
 
0.5%
숲가꾸기 1
 
0.5%
나무병원 1
 
0.5%

Length

2024-03-14T10:28:47.724230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:28:47.816722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
조성 61
16.4%
도시림등 59
15.9%
및 45
12.1%
숲가꾸기 44
11.8%
병해충방제 43
11.6%
산림토목 40
10.8%
나무병원 36
9.7%
1종 24
 
6.5%
2종 11
 
3.0%
산림경영계획 2
 
0.5%
Other values (4) 7
 
1.9%

우편번호
Real number (ℝ)

Distinct112
Distinct (%)60.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean160903.55
Minimum54029
Maximum597842
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-03-14T10:28:47.945307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54029
5-th percentile54352.4
Q155428
median55734
Q356194.5
95-th percentile590210
Maximum597842
Range543813
Interquartile range (IQR)766.5

Descriptive statistics

Standard deviation210677.81
Coefficient of variation (CV)1.3093422
Kurtosis0.27489266
Mean160903.55
Median Absolute Deviation (MAD)378
Skewness1.5060611
Sum29606253
Variance4.4385138 × 1010
MonotonicityNot monotonic
2024-03-14T10:28:48.057569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55772 6
 
3.3%
568804 5
 
2.7%
55622 5
 
2.7%
55630 5
 
2.7%
55631 4
 
2.2%
55602 4
 
2.2%
55548 4
 
2.2%
55632 4
 
2.2%
55365 4
 
2.2%
55925 3
 
1.6%
Other values (102) 140
76.1%
ValueCountFrequency (%)
54029 1
0.5%
54055 1
0.5%
54068 1
0.5%
54078 2
1.1%
54103 1
0.5%
54104 1
0.5%
54168 1
0.5%
54338 1
0.5%
54350 1
0.5%
54366 1
0.5%
ValueCountFrequency (%)
597842 1
 
0.5%
595805 2
1.1%
590986 1
 
0.5%
590984 3
1.6%
590823 1
 
0.5%
590210 3
1.6%
590130 2
1.1%
590050 1
 
0.5%
580924 1
 
0.5%
580921 2
1.1%

주사무소위치
Text

Distinct144
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-03-14T10:28:48.380810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length20.184783
Min length11

Characters and Unicode

Total characters3714
Distinct characters176
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

Unique114 ?
Unique (%)62.0%

Sample

1st row전주시 완산구 메너머2길 19-11(중화산동2가)
2nd row전주시 완산구 메너머2길 19-11, 2층 (중화산동2가) 2층
3rd row전주시 완산구 반촌로 6-1, 1층 (서노송동)
4th row전주시 완산구 소대배기로 26-16, 프라임빌딩 403호(평화동2가)
5th row전주시 완산구 쑥고개로 218(삼천동3가) 2층
ValueCountFrequency (%)
장수군 31
 
3.7%
남원시 30
 
3.6%
2층 27
 
3.2%
전주시 26
 
3.1%
임실군 20
 
2.4%
정읍시 18
 
2.1%
무주군 18
 
2.1%
1층 17
 
2.0%
장수읍 15
 
1.8%
완산구 15
 
1.8%
Other values (312) 628
74.3%
2024-03-14T10:28:48.777341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
785
 
21.1%
1 187
 
5.0%
2 130
 
3.5%
로 115
 
3.1%
군 104
 
2.8%
시 98
 
2.6%
3 92
 
2.5%
동 83
 
2.2%
읍 77
 
2.1%
장 75
 
2.0%
Other values (166) 1968
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1930
52.0%
Space Separator 785
21.1%
Decimal Number 749
 
20.2%
Dash Punctuation 71
 
1.9%
Close Punctuation 66
 
1.8%
Open Punctuation 66
 
1.8%
Other Punctuation 44
 
1.2%
Uppercase Letter 2
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 115
 
6.0%
군 104
 
5.4%
시 98
 
5.1%
동 83
 
4.3%
읍 77
 
4.0%
장 75
 
3.9%
주 68
 
3.5%
길 59
 
3.1%
층 56
 
2.9%
수 51
 
2.6%
Other values (148) 1144
59.3%
Decimal Number
ValueCountFrequency (%)
1 187
25.0%
2 130
17.4%
3 92
12.3%
4 68
 
9.1%
0 66
 
8.8%
8 49
 
6.5%
7 46
 
6.1%
5 44
 
5.9%
9 41
 
5.5%
6 26
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 43
97.7%
. 1
 
2.3%
Space Separator
ValueCountFrequency (%)
785
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1930
52.0%
Common 1781
48.0%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 115
 
6.0%
군 104
 
5.4%
시 98
 
5.1%
동 83
 
4.3%
읍 77
 
4.0%
장 75
 
3.9%
주 68
 
3.5%
길 59
 
3.1%
층 56
 
2.9%
수 51
 
2.6%
Other values (148) 1144
59.3%
Common
ValueCountFrequency (%)
785
44.1%
1 187
 
10.5%
2 130
 
7.3%
3 92
 
5.2%
- 71
 
4.0%
4 68
 
3.8%
) 66
 
3.7%
( 66
 
3.7%
0 66
 
3.7%
8 49
 
2.8%
Other values (6) 201
 
11.3%
Latin
ValueCountFrequency (%)
A 2
66.7%
b 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1930
52.0%
ASCII 1784
48.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
785
44.0%
1 187
 
10.5%
2 130
 
7.3%
3 92
 
5.2%
- 71
 
4.0%
4 68
 
3.8%
) 66
 
3.7%
( 66
 
3.7%
0 66
 
3.7%
8 49
 
2.7%
Other values (8) 204
 
11.4%
Hangul
ValueCountFrequency (%)
로 115
 
6.0%
군 104
 
5.4%
시 98
 
5.1%
동 83
 
4.3%
읍 77
 
4.0%
장 75
 
3.9%
주 68
 
3.5%
길 59
 
3.1%
층 56
 
2.9%
수 51
 
2.6%
Other values (148) 1144
59.3%

전화번호
Text

Distinct149
Distinct (%)81.4%
Missing1
Missing (%)0.5%
Memory size1.6 KiB
2024-03-14T10:28:48.979084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length12
Mean length15.775956
Min length12

Characters and Unicode

Total characters2887
Distinct characters17
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)67.8%

Sample

1st row010-3661-6690
2nd row063-222-4955
3rd row063-271-4361
4th row063-231-0089
5th row063-221-4647
ValueCountFrequency (%)
063-351-1117 5
 
2.6%
063-322-1326 4
 
2.1%
063-243-4011 3
 
1.5%
063-636-0371 3
 
1.5%
063-246-6100 3
 
1.5%
063-534-4256 3
 
1.5%
011-683-7822 2
 
1.0%
063-644-5658(010-4895-8580 2
 
1.0%
063-642-6064 2
 
1.0%
063-351-2631 2
 
1.0%
Other values (145) 166
85.1%
2024-03-14T10:28:49.292053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 454
15.7%
0 401
13.9%
3 392
13.6%
6 349
12.1%
1 241
8.3%
2 237
8.2%
5 196
6.8%
4 176
 
6.1%
7 150
 
5.2%
8 109
 
3.8%
Other values (7) 182
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2346
81.3%
Dash Punctuation 454
 
15.7%
Close Punctuation 28
 
1.0%
Open Punctuation 27
 
0.9%
Other Punctuation 19
 
0.7%
Space Separator 13
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 401
17.1%
3 392
16.7%
6 349
14.9%
1 241
10.3%
2 237
10.1%
5 196
8.4%
4 176
7.5%
7 150
 
6.4%
8 109
 
4.6%
9 95
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 16
84.2%
/ 2
 
10.5%
. 1
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 454
100.0%
Close Punctuation
ValueCountFrequency (%)
) 28
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2887
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 454
15.7%
0 401
13.9%
3 392
13.6%
6 349
12.1%
1 241
8.3%
2 237
8.2%
5 196
6.8%
4 176
 
6.1%
7 150
 
5.2%
8 109
 
3.8%
Other values (7) 182
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2887
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 454
15.7%
0 401
13.9%
3 392
13.6%
6 349
12.1%
1 241
8.3%
2 237
8.2%
5 196
6.8%
4 176
 
6.1%
7 150
 
5.2%
8 109
 
3.8%
Other values (7) 182
6.3%

팩스번호
Text

MISSING 

Distinct57
Distinct (%)76.0%
Missing109
Missing (%)59.2%
Memory size1.6 KiB
2024-03-14T10:28:49.487609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.813333
Min length8

Characters and Unicode

Total characters886
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

Unique44 ?
Unique (%)58.7%

Sample

1st row063-231-0083
2nd row063-226-8409
3rd row063-285-5194
4th row063-232-2241
5th row063-903-0852
ValueCountFrequency (%)
063-571-0543 4
 
5.3%
063-626-7091 4
 
5.3%
063-231-0083 3
 
4.0%
063-443-1127 2
 
2.7%
063-324-6778 2
 
2.7%
063-283-2028 2
 
2.7%
063-643-5657 2
 
2.7%
063-644-2744 2
 
2.7%
063-534-4254 2
 
2.7%
063-626-2016 2
 
2.7%
Other values (47) 50
66.7%
2024-03-14T10:28:49.787777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 146
16.5%
3 128
14.4%
6 118
13.3%
0 114
12.9%
2 91
10.3%
4 63
7.1%
5 59
6.7%
7 54
 
6.1%
1 49
 
5.5%
9 36
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 740
83.5%
Dash Punctuation 146
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 128
17.3%
6 118
15.9%
0 114
15.4%
2 91
12.3%
4 63
8.5%
5 59
8.0%
7 54
7.3%
1 49
 
6.6%
9 36
 
4.9%
8 28
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 146
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 886
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 146
16.5%
3 128
14.4%
6 118
13.3%
0 114
12.9%
2 91
10.3%
4 63
7.1%
5 59
6.7%
7 54
 
6.1%
1 49
 
5.5%
9 36
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 146
16.5%
3 128
14.4%
6 118
13.3%
0 114
12.9%
2 91
10.3%
4 63
7.1%
5 59
6.7%
7 54
 
6.1%
1 49
 
5.5%
9 36
 
4.1%

시군구(우편번호)
Categorical

Distinct15
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
장수군
31 
남원시
30 
정읍시
18 
무주군
18 
임실군
18 
Other values (10)
69 

Length

Max length7
Median length3
Mean length3.5652174
Min length3

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row전주시 완산구
2nd row전주시 완산구
3rd row전주시 완산구
4th row전주시 완산구
5th row전주시 완산구

Common Values

ValueCountFrequency (%)
장수군 31
16.8%
남원시 30
16.3%
정읍시 18
9.8%
무주군 18
9.8%
임실군 18
9.8%
전주시 완산구 14
7.6%
전주시 덕진구 12
 
6.5%
완주군 12
 
6.5%
군산시 8
 
4.3%
순창군 8
 
4.3%
Other values (5) 15
8.2%

Length

2024-03-14T10:28:49.913818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
장수군 31
14.8%
남원시 30
14.3%
전주시 26
12.4%
정읍시 18
8.6%
무주군 18
8.6%
임실군 18
8.6%
완산구 14
6.7%
덕진구 12
 
5.7%
완주군 12
 
5.7%
군산시 8
 
3.8%
Other values (6) 23
11.0%

Interactions

2024-03-14T10:28:45.243096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T10:28:49.995625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업의 종류우편번호팩스번호시군구(우편번호)
사업의 종류1.0000.2300.0000.319
우편번호0.2301.0000.8690.330
팩스번호0.0000.8691.0000.993
시군구(우편번호)0.3190.3300.9931.000
2024-03-14T10:28:50.075577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업의 종류시군구(우편번호)
사업의 종류1.0000.121
시군구(우편번호)0.1211.000
2024-03-14T10:28:50.142091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호사업의 종류시군구(우편번호)
우편번호1.0000.1700.292
사업의 종류0.1701.0000.121
시군구(우편번호)0.2920.1211.000

Missing values

2024-03-14T10:28:45.341315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:28:45.459484image/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.
2024-03-14T10:28:45.539375image/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

등록번호등록일자법인명대표자사업의 종류우편번호주사무소위치전화번호팩스번호시군구(우편번호)
0전북2017-006(0)2017-02-23백제조경주식회사지애란도시림등 조성54972전주시 완산구 메너머2길 19-11(중화산동2가)010-3661-6690<NA>전주시 완산구
1전북2017-004(0)2017-02-23주식회사 영웅서범석도시림등 조성54972전주시 완산구 메너머2길 19-11, 2층 (중화산동2가) 2층063-222-4955<NA>전주시 완산구
2전북2016-013(0)2016-08-04(유)미소조경이희원도시림등 조성55005전주시 완산구 반촌로 6-1, 1층 (서노송동)063-271-4361<NA>전주시 완산구
3전북2009-015(1)2009-02-19(유)성민종합개발조남영도시림등 조성560871전주시 완산구 소대배기로 26-16, 프라임빌딩 403호(평화동2가)063-231-0089063-231-0083전주시 완산구
4전북2016-003(0)2016-02-23(유)이안조경한상돈도시림등 조성55075전주시 완산구 쑥고개로 218(삼천동3가) 2층063-221-4647<NA>전주시 완산구
5전북2012-016(0)2012-05-09(주)창대건설엔지니어링임정연도시림등 조성55080전주시 완산구 용머리로 36, 824호 (효자동1가) 824호063-222-8409(010-4650-8409)063-226-8409전주시 완산구
6전북2009-013(0)2009-02-10(유)삼송개발강지형도시림등 조성55000전주시 완산구 현무3길 80(서노송동) 2층063-221-5191063-285-5194전주시 완산구
72007-039(1)2007-05-31(주)신성건설고상범산림토목560924전주시 완산구 기린대로 192, 2층(서노송동)063-232-2244063-232-2241전주시 완산구
8T-전북2018-016(0)2018-06-28유한회사 지에스코리아양금순1종 나무병원54966전주시 완산구 바우배기2길 14, 5층 비호 (효자동2가)063-237-5248<NA>전주시 완산구
9T-전북2018-013(0)2018-06-28(유)개미환경위생송혜자1종 나무병원54951전주시 완산구 서신천변15길 15-9 (서신동)063-253-0762<NA>전주시 완산구
등록번호등록일자법인명대표자사업의 종류우편번호주사무소위치전화번호팩스번호시군구(우편번호)
174전북2014-023(0)2014-11-12천지주식회사최순자도시림등 조성56038순창군 순창읍 장류로 300, 상가동 1층 101호 상가동 1층 101호063-652-2238(010-5300-5127)<NA>순창군
175T-전북2018-001(0)2018-06-28주식회사 푸른잎사귀변현정1종 나무병원56013순창군 구림면 강천로 876-2062-955-1732<NA>순창군
176T-전남2018-030(0)2018-06-28(유)재안산림양승복1종 나무병원56046순창군 순창읍 순창5길 3063-652-0964<NA>순창군
177T-전북2018-006(0)2018-06-28(유)드림조경김우관1종 나무병원56040순창군 순창읍 순창로 213063-652-7085<NA>순창군
178전북2013-017(0)2013-08-12유한회사 정도김수현, 황희정산림토목56433고창군 고창읍 성산로 36063-561-2975063-229-2977고창군
179전북2012-032(1)2012-12-12(유)청신김광우산림토목56433고창군 고창읍 성산로 36, 4층 8호 4층 8호063-538-4990063-227-4880고창군
180T-충남2018-007(0)2018-06-28신한나무종합병원(주)지철1종 나무병원56439고창군 고창읍 보릿골로 56063-564-4080<NA>고창군
181T-전북2018-010(0)2018-06-28(주)전국나무병원박지두1종 나무병원56430고창군 고창읍 월곡공원1길 44070-7663-0706<NA>고창군
182T-전북2018-014(0)2018-06-28(주)유한조경윤영예1종 나무병원56418고창군 부안면 인촌로 686-9063-561-2052<NA>고창군
183T-전북2018-029(0)2018-09-10주식회사 예원홍범철2종 나무병원56304부안군 부안읍 선은1길 4063-582-3738<NA>부안군