Overview

Dataset statistics

Number of variables12
Number of observations22
Missing cells34
Missing cells (%)12.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory103.8 B

Variable types

Numeric1
Categorical3
Text6
DateTime2

Dataset

Description전북특별자치도 해양수상레저사업장 현황(지방청/광역지자체, 등록관청, 사업장명, 대표자, 연락처, 사업장위치, 영업구역 등)
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=9&menuCd=DOM_000000103007001000&pListTypeStr=&pId=15055804

Alerts

연락처 has constant value ""Constant
비상구조선 (대) is highly overall correlated with 영업구역 (00강_00천 등)High correlation
영업구역 (00강_00천 등) is highly overall correlated with 지방청_광역지자체 and 1 other fieldsHigh correlation
지방청_광역지자체 is highly overall correlated with 영업구역 (00강_00천 등)High correlation
지방청_광역지자체 is highly imbalanced (56.1%)Imbalance
연락처 has 21 (95.5%) missing valuesMissing
사업등록기간(시작) has 5 (22.7%) missing valuesMissing
사업등록기간(만료) has 4 (18.2%) missing valuesMissing
종사자(인명구조요원) has 4 (18.2%) missing valuesMissing
순번 has unique valuesUnique
사업장명 has unique valuesUnique
사업장위치 has unique valuesUnique

Reproduction

Analysis started2024-04-21 16:03:33.126329
Analysis finished2024-04-21 16:03:34.700324
Duration1.57 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size326.0 B
2024-04-22T01:03:34.809881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.05
Q16.25
median11.5
Q316.75
95-th percentile20.95
Maximum22
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.5646597
Kurtosis-1.2
Mean11.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum253
Variance42.166667
MonotonicityStrictly increasing
2024-04-22T01:03:35.013864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 1
 
4.5%
13 1
 
4.5%
22 1
 
4.5%
21 1
 
4.5%
20 1
 
4.5%
19 1
 
4.5%
18 1
 
4.5%
17 1
 
4.5%
16 1
 
4.5%
15 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1 1
4.5%
2 1
4.5%
3 1
4.5%
4 1
4.5%
5 1
4.5%
6 1
4.5%
7 1
4.5%
8 1
4.5%
9 1
4.5%
10 1
4.5%
ValueCountFrequency (%)
22 1
4.5%
21 1
4.5%
20 1
4.5%
19 1
4.5%
18 1
4.5%
17 1
4.5%
16 1
4.5%
15 1
4.5%
14 1
4.5%
13 1
4.5%

지방청_광역지자체
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size304.0 B
전북특별자치도
20 
서해청
 
2

Length

Max length7
Median length7
Mean length6.6363636
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전북특별자치도
2nd row서해청
3rd row전북특별자치도
4th row전북특별자치도
5th row전북특별자치도

Common Values

ValueCountFrequency (%)
전북특별자치도 20
90.9%
서해청 2
 
9.1%

Length

2024-04-22T01:03:35.236925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T01:03:35.431151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북특별자치도 20
90.9%
서해청 2
 
9.1%

등록관청
Text

Distinct11
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size304.0 B
2024-04-22T01:03:35.786638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters66
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)45.5%

Sample

1st row전주시
2nd row군산시
3rd row익산시
4th row김제시
5th row완주군
ValueCountFrequency (%)
무주군 12
54.5%
전주시 1
 
4.5%
군산시 1
 
4.5%
익산시 1
 
4.5%
김제시 1
 
4.5%
완주군 1
 
4.5%
진안군 1
 
4.5%
장수군 1
 
4.5%
임실군 1
 
4.5%
순창군 1
 
4.5%
2024-04-22T01:03:36.358089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 19
28.8%
주 14
21.2%
무 12
18.2%
시 4
 
6.1%
산 2
 
3.0%
안 2
 
3.0%
장 1
 
1.5%
창 1
 
1.5%
순 1
 
1.5%
실 1
 
1.5%
Other values (9) 9
13.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 19
28.8%
주 14
21.2%
무 12
18.2%
시 4
 
6.1%
산 2
 
3.0%
안 2
 
3.0%
장 1
 
1.5%
창 1
 
1.5%
순 1
 
1.5%
실 1
 
1.5%
Other values (9) 9
13.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 19
28.8%
주 14
21.2%
무 12
18.2%
시 4
 
6.1%
산 2
 
3.0%
안 2
 
3.0%
장 1
 
1.5%
창 1
 
1.5%
순 1
 
1.5%
실 1
 
1.5%
Other values (9) 9
13.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 19
28.8%
주 14
21.2%
무 12
18.2%
시 4
 
6.1%
산 2
 
3.0%
안 2
 
3.0%
장 1
 
1.5%
창 1
 
1.5%
순 1
 
1.5%
실 1
 
1.5%
Other values (9) 9
13.6%

사업장명
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size304.0 B
2024-04-22T01:03:36.903562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length10
Mean length8.1363636
Min length5

Characters and Unicode

Total characters179
Distinct characters85
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

Unique22 ?
Unique (%)100.0%

Sample

1st row한국레저스포츠협동조합
2nd row이지스레포츠
3rd row(유)금강관광개발
4th row㈜김제지평선마린리조트
5th row청정테마힐링센터(청정인성수련원)
ValueCountFrequency (%)
무주 4
 
12.9%
한국레저스포츠협동조합 1
 
3.2%
무주레저스쿨 1
 
3.2%
갯벌 1
 
3.2%
줄포만 1
 
3.2%
체험교실 1
 
3.2%
해양레저 1
 
3.2%
해피랜드 1
 
3.2%
유)사선대 1
 
3.2%
장수논개수상레저 1
 
3.2%
Other values (18) 18
58.1%
2024-04-22T01:03:37.692258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
레 14
 
7.8%
저 12
 
6.7%
9
 
5.0%
무 7
 
3.9%
주 7
 
3.9%
포 5
 
2.8%
스 5
 
2.8%
강 5
 
2.8%
츠 4
 
2.2%
수 4
 
2.2%
Other values (75) 107
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 163
91.1%
Space Separator 9
 
5.0%
Open Punctuation 3
 
1.7%
Close Punctuation 3
 
1.7%
Other Symbol 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
레 14
 
8.6%
저 12
 
7.4%
무 7
 
4.3%
주 7
 
4.3%
포 5
 
3.1%
스 5
 
3.1%
강 5
 
3.1%
츠 4
 
2.5%
수 4
 
2.5%
금 4
 
2.5%
Other values (71) 96
58.9%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 164
91.6%
Common 15
 
8.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
레 14
 
8.5%
저 12
 
7.3%
무 7
 
4.3%
주 7
 
4.3%
포 5
 
3.0%
스 5
 
3.0%
강 5
 
3.0%
츠 4
 
2.4%
수 4
 
2.4%
금 4
 
2.4%
Other values (72) 97
59.1%
Common
ValueCountFrequency (%)
9
60.0%
( 3
 
20.0%
) 3
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 163
91.1%
ASCII 15
 
8.4%
None 1
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
레 14
 
8.6%
저 12
 
7.4%
무 7
 
4.3%
주 7
 
4.3%
포 5
 
3.1%
스 5
 
3.1%
강 5
 
3.1%
츠 4
 
2.5%
수 4
 
2.5%
금 4
 
2.5%
Other values (71) 96
58.9%
ASCII
ValueCountFrequency (%)
9
60.0%
( 3
 
20.0%
) 3
 
20.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

대표자
Text

Distinct12
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Memory size304.0 B
2024-04-22T01:03:38.168935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length3
Mean length3.4545455
Min length3

Characters and Unicode

Total characters76
Distinct characters23
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

Unique9 ?
Unique (%)40.9%

Sample

1st row김**
2nd row김**
3rd row이**
4th row방**
5th row이**
ValueCountFrequency (%)
이 7
30.4%
김 3
13.0%
최 3
13.0%
방 1
 
4.3%
구 1
 
4.3%
유 1
 
4.3%
음 1
 
4.3%
노 1
 
4.3%
박 1
 
4.3%
임 1
 
4.3%
Other values (3) 3
13.0%
2024-04-22T01:03:38.993060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 44
57.9%
이 7
 
9.2%
김 3
 
3.9%
최 3
 
3.9%
강 1
 
1.3%
서 1
 
1.3%
1
 
1.3%
맹 1
 
1.3%
연 1
 
1.3%
저 1
 
1.3%
Other values (13) 13
 
17.1%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 44
57.9%
Other Letter 31
40.8%
Space Separator 1
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 7
22.6%
김 3
 
9.7%
최 3
 
9.7%
강 1
 
3.2%
서 1
 
3.2%
맹 1
 
3.2%
연 1
 
3.2%
저 1
 
3.2%
레 1
 
3.2%
상 1
 
3.2%
Other values (11) 11
35.5%
Other Punctuation
ValueCountFrequency (%)
* 44
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 45
59.2%
Hangul 31
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 7
22.6%
김 3
 
9.7%
최 3
 
9.7%
강 1
 
3.2%
서 1
 
3.2%
맹 1
 
3.2%
연 1
 
3.2%
저 1
 
3.2%
레 1
 
3.2%
상 1
 
3.2%
Other values (11) 11
35.5%
Common
ValueCountFrequency (%)
* 44
97.8%
1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
59.2%
Hangul 31
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 44
97.8%
1
 
2.2%
Hangul
ValueCountFrequency (%)
이 7
22.6%
김 3
 
9.7%
최 3
 
9.7%
강 1
 
3.2%
서 1
 
3.2%
맹 1
 
3.2%
연 1
 
3.2%
저 1
 
3.2%
레 1
 
3.2%
상 1
 
3.2%
Other values (11) 11
35.5%

연락처
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing21
Missing (%)95.5%
Memory size304.0 B
2024-04-22T01:03:39.412061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters12
Distinct characters8
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

Unique1 ?
Unique (%)100.0%

Sample

1st row063-222-7754
ValueCountFrequency (%)
063-222-7754 1
100.0%
2024-04-22T01:03:40.014074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3
25.0%
- 2
16.7%
7 2
16.7%
0 1
 
8.3%
6 1
 
8.3%
3 1
 
8.3%
5 1
 
8.3%
4 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
83.3%
Dash Punctuation 2
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3
30.0%
7 2
20.0%
0 1
 
10.0%
6 1
 
10.0%
3 1
 
10.0%
5 1
 
10.0%
4 1
 
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3
25.0%
- 2
16.7%
7 2
16.7%
0 1
 
8.3%
6 1
 
8.3%
3 1
 
8.3%
5 1
 
8.3%
4 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3
25.0%
- 2
16.7%
7 2
16.7%
0 1
 
8.3%
6 1
 
8.3%
3 1
 
8.3%
5 1
 
8.3%
4 1
 
8.3%

사업장위치
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size304.0 B
2024-04-22T01:03:40.623660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length12.318182
Min length10

Characters and Unicode

Total characters271
Distinct characters71
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row전주시 덕진구 동부대로375
2nd row옥도면 장자도 2길1
3rd row웅포면 웅포리 723-2하천
4th row만경읍 만경리 100
5th row완주군 구이면 안덕저수지
ValueCountFrequency (%)
무주군 12
 
18.2%
무금로 3
 
4.5%
잠두강변길 3
 
4.5%
굴암리 2
 
3.0%
721 1
 
1.5%
85번지 1
 
1.5%
211 1
 
1.5%
312 1
 
1.5%
213 1
 
1.5%
689 1
 
1.5%
Other values (40) 40
60.6%
2024-04-22T01:03:41.661956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44
 
16.2%
군 15
 
5.5%
무 15
 
5.5%
주 14
 
5.2%
1 11
 
4.1%
2 10
 
3.7%
리 8
 
3.0%
로 8
 
3.0%
3 8
 
3.0%
면 7
 
2.6%
Other values (61) 131
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 163
60.1%
Decimal Number 61
 
22.5%
Space Separator 44
 
16.2%
Dash Punctuation 3
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 15
 
9.2%
무 15
 
9.2%
주 14
 
8.6%
리 8
 
4.9%
로 8
 
4.9%
면 7
 
4.3%
길 6
 
3.7%
잠 4
 
2.5%
두 4
 
2.5%
암 4
 
2.5%
Other values (49) 78
47.9%
Decimal Number
ValueCountFrequency (%)
1 11
18.0%
2 10
16.4%
3 8
13.1%
6 7
11.5%
7 7
11.5%
5 6
9.8%
8 5
8.2%
4 3
 
4.9%
0 2
 
3.3%
9 2
 
3.3%
Space Separator
ValueCountFrequency (%)
44
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 163
60.1%
Common 108
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 15
 
9.2%
무 15
 
9.2%
주 14
 
8.6%
리 8
 
4.9%
로 8
 
4.9%
면 7
 
4.3%
길 6
 
3.7%
잠 4
 
2.5%
두 4
 
2.5%
암 4
 
2.5%
Other values (49) 78
47.9%
Common
ValueCountFrequency (%)
44
40.7%
1 11
 
10.2%
2 10
 
9.3%
3 8
 
7.4%
6 7
 
6.5%
7 7
 
6.5%
5 6
 
5.6%
8 5
 
4.6%
4 3
 
2.8%
- 3
 
2.8%
Other values (2) 4
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 163
60.1%
ASCII 108
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
40.7%
1 11
 
10.2%
2 10
 
9.3%
3 8
 
7.4%
6 7
 
6.5%
7 7
 
6.5%
5 6
 
5.6%
8 5
 
4.6%
4 3
 
2.8%
- 3
 
2.8%
Other values (2) 4
 
3.7%
Hangul
ValueCountFrequency (%)
군 15
 
9.2%
무 15
 
9.2%
주 14
 
8.6%
리 8
 
4.9%
로 8
 
4.9%
면 7
 
4.3%
길 6
 
3.7%
잠 4
 
2.5%
두 4
 
2.5%
암 4
 
2.5%
Other values (49) 78
47.9%

영업구역 (00강_00천 등)
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size304.0 B
금강
12 
<NA>
 
1
장자도1회 순회
 
1
능저수지
 
1
안덕저수지
 
1
Other values (6)
6 

Length

Max length11
Median length2
Mean length3.6363636
Min length2

Unique

Unique10 ?
Unique (%)45.5%

Sample

1st row<NA>
2nd row장자도1회 순회
3rd row금강
4th row능저수지
5th row안덕저수지

Common Values

ValueCountFrequency (%)
금강 12
54.5%
<NA> 1
 
4.5%
장자도1회 순회 1
 
4.5%
능저수지 1
 
4.5%
안덕저수지 1
 
4.5%
남부마이산 탐영제 내 1
 
4.5%
남대천 1
 
4.5%
대곡저수지 1
 
4.5%
섬진강 1
 
4.5%
순창군 섬진강 1
 
4.5%

Length

2024-04-22T01:03:41.887529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
금강 12
44.4%
섬진강 2
 
7.4%
na 1
 
3.7%
장자도1회 1
 
3.7%
순회 1
 
3.7%
능저수지 1
 
3.7%
안덕저수지 1
 
3.7%
남부마이산 1
 
3.7%
탐영제 1
 
3.7%
내 1
 
3.7%
Other values (5) 5
18.5%

사업등록기간(시작)
Date

MISSING 

Distinct14
Distinct (%)82.4%
Missing5
Missing (%)22.7%
Memory size304.0 B
Minimum2015-09-25 00:00:00
Maximum2020-07-18 00:00:00
2024-04-22T01:03:42.064692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:03:42.264491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)

사업등록기간(만료)
Date

MISSING 

Distinct16
Distinct (%)88.9%
Missing4
Missing (%)18.2%
Memory size304.0 B
Minimum1930-12-31 00:00:00
Maximum2029-11-14 00:00:00
2024-04-22T01:03:42.463072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:03:42.653404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

종사자(인명구조요원)
Text

MISSING 

Distinct13
Distinct (%)72.2%
Missing4
Missing (%)18.2%
Memory size304.0 B
2024-04-22T01:03:43.175294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length9.1666667
Min length1

Characters and Unicode

Total characters165
Distinct characters29
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)61.1%

Sample

1st row0
2nd row종사자3명(인명구조요원2명)
3rd row휴업중
4th row종사자3명(인명구조요원4명)
5th row종사자1명(안전요원1명)
ValueCountFrequency (%)
종사자3명 4
20.0%
종사자5명 3
15.0%
0 1
 
5.0%
종사자3명(인명구조요원2명 1
 
5.0%
휴업중 1
 
5.0%
종사자3명(인명구조요원4명 1
 
5.0%
종사자1명(안전요원1명 1
 
5.0%
종사자 1
 
5.0%
1명(안전요원 1
 
5.0%
2명 1
 
5.0%
Other values (5) 5
25.0%
2024-04-22T01:03:43.916613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
명 27
16.4%
종 15
 
9.1%
자 15
 
9.1%
사 15
 
9.1%
3 9
 
5.5%
( 8
 
4.8%
) 8
 
4.8%
1 7
 
4.2%
요 7
 
4.2%
원 7
 
4.2%
Other values (19) 47
28.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 113
68.5%
Decimal Number 31
 
18.8%
Open Punctuation 8
 
4.8%
Close Punctuation 8
 
4.8%
Space Separator 2
 
1.2%
Dash Punctuation 2
 
1.2%
Math Symbol 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
명 27
23.9%
종 15
13.3%
자 15
13.3%
사 15
13.3%
요 7
 
6.2%
원 7
 
6.2%
구 5
 
4.4%
조 5
 
4.4%
인 5
 
4.4%
전 2
 
1.8%
Other values (6) 10
 
8.8%
Decimal Number
ValueCountFrequency (%)
3 9
29.0%
1 7
22.6%
2 5
16.1%
0 3
 
9.7%
5 3
 
9.7%
7 2
 
6.5%
4 1
 
3.2%
6 1
 
3.2%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 113
68.5%
Common 52
31.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
명 27
23.9%
종 15
13.3%
자 15
13.3%
사 15
13.3%
요 7
 
6.2%
원 7
 
6.2%
구 5
 
4.4%
조 5
 
4.4%
인 5
 
4.4%
전 2
 
1.8%
Other values (6) 10
 
8.8%
Common
ValueCountFrequency (%)
3 9
17.3%
( 8
15.4%
) 8
15.4%
1 7
13.5%
2 5
9.6%
0 3
 
5.8%
5 3
 
5.8%
2
 
3.8%
- 2
 
3.8%
7 2
 
3.8%
Other values (3) 3
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 113
68.5%
ASCII 52
31.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
명 27
23.9%
종 15
13.3%
자 15
13.3%
사 15
13.3%
요 7
 
6.2%
원 7
 
6.2%
구 5
 
4.4%
조 5
 
4.4%
인 5
 
4.4%
전 2
 
1.8%
Other values (6) 10
 
8.8%
ASCII
ValueCountFrequency (%)
3 9
17.3%
( 8
15.4%
) 8
15.4%
1 7
13.5%
2 5
9.6%
0 3
 
5.8%
5 3
 
5.8%
2
 
3.8%
- 2
 
3.8%
7 2
 
3.8%
Other values (3) 3
 
5.8%

비상구조선 (대)
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size304.0 B
<NA>
14 
1
7 
0
 
1

Length

Max length4
Median length4
Mean length2.9090909
Min length1

Unique

Unique1 ?
Unique (%)4.5%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 14
63.6%
1 7
31.8%
0 1
 
4.5%

Length

2024-04-22T01:03:44.149376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T01:03:44.342137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 14
63.6%
1 7
31.8%
0 1
 
4.5%

Interactions

2024-04-22T01:03:33.843150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-22T01:03:44.482685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번지방청_광역지자체등록관청사업장명대표자사업장위치영업구역 (00강_00천 등)사업등록기간(시작)사업등록기간(만료)종사자(인명구조요원)비상구조선 (대)
순번1.0000.0000.0001.0000.4831.0000.3330.3620.0000.0000.000
지방청_광역지자체0.0001.0001.0001.0000.6561.0001.0001.0001.0001.0000.000
등록관청0.0001.0001.0001.0000.4281.0000.9971.0001.0001.0001.000
사업장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대표자0.4830.6560.4281.0001.0001.0000.5500.8100.8680.2450.000
사업장위치1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
영업구역 (00강_00천 등)0.3331.0000.9971.0000.5501.0001.0001.0001.0001.000NaN
사업등록기간(시작)0.3621.0001.0001.0000.8101.0001.0001.0001.0000.9241.000
사업등록기간(만료)0.0001.0001.0001.0000.8681.0001.0001.0001.0000.9301.000
종사자(인명구조요원)0.0001.0001.0001.0000.2451.0001.0000.9240.9301.0001.000
비상구조선 (대)0.0000.0001.0001.0000.0001.000NaN1.0001.0001.0001.000
2024-04-22T01:03:44.715315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지방청_광역지자체비상구조선 (대)영업구역 (00강_00천 등)
지방청_광역지자체1.0000.0000.761
비상구조선 (대)0.0001.0001.000
영업구역 (00강_00천 등)0.7611.0001.000
2024-04-22T01:03:44.867501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번지방청_광역지자체영업구역 (00강_00천 등)비상구조선 (대)
순번1.0000.0000.0000.000
지방청_광역지자체0.0001.0000.7610.000
영업구역 (00강_00천 등)0.0000.7611.0001.000
비상구조선 (대)0.0000.0001.0001.000

Missing values

2024-04-22T01:03:34.032506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-22T01:03:34.327623image/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.
2024-04-22T01:03:34.556227image/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

순번지방청_광역지자체등록관청사업장명대표자연락처사업장위치영업구역 (00강_00천 등)사업등록기간(시작)사업등록기간(만료)종사자(인명구조요원)비상구조선 (대)
01전북특별자치도전주시한국레저스포츠협동조합김**<NA>전주시 덕진구 동부대로375<NA>2019-07-032028-07-0300
12서해청군산시이지스레포츠김**<NA>옥도면 장자도 2길1장자도1회 순회2020-07-182020-12-31종사자3명(인명구조요원2명)1
23전북특별자치도익산시(유)금강관광개발이**<NA>웅포면 웅포리 723-2하천금강2019-01-012021-12-31휴업중1
34전북특별자치도김제시㈜김제지평선마린리조트방**<NA>만경읍 만경리 100능저수지2020-02-032024-12-29종사자3명(인명구조요원4명)1
45전북특별자치도완주군청정테마힐링센터(청정인성수련원)이**063-222-7754완주군 구이면 안덕저수지안덕저수지2019-11-152029-11-14종사자1명(안전요원1명)<NA>
56서해청진안군하라 레포츠구**<NA>진안군 마령면 동촌리남부마이산 탐영제 내2018-01-302027-01-29종사자 1명(안전요원 2명)1
67전북특별자치도무주군금강래프팅유**<NA>무주군 부남로 854금강2020-06-122021-06-12종사자5명<NA>
78전북특별자치도무주군무주스피드레저이**<NA>무주군 잠두강변길 215금강2020-06-192021-06-19종사자5명<NA>
89전북특별자치도무주군무주래프팅음**<NA>무주군 잠두길 5번지금강2020-06-112021-06-11종사자3명<NA>
910전북특별자치도무주군금강파워레저노**<NA>무주군 무금로 721금강2020-06-192020-08-31종사자3명<NA>
순번지방청_광역지자체등록관청사업장명대표자연락처사업장위치영업구역 (00강_00천 등)사업등록기간(시작)사업등록기간(만료)종사자(인명구조요원)비상구조선 (대)
1213전북특별자치도무주군김태홍스포츠아카데미김**<NA>무주군 무금로 312금강2020-06-042021-06-05종사자3명<NA>
1314전북특별자치도무주군무주레저스쿨박**<NA>무주군 잠두강변길 213금강2020-06-202021-06-20종사자3명<NA>
1415전북특별자치도무주군금강레저클럽최**<NA>무주군 무금로 689금강<NA><NA><NA><NA>
1516전북특별자치도무주군무주 코리아레저이**<NA>무주군 굴암리 18금강<NA><NA><NA><NA>
1617전북특별자치도무주군무주 레저클럽임**<NA>무주군 굴암리 367금강<NA><NA><NA><NA>
1718전북특별자치도무주군마린수상레저이**<NA>무주군 당산리 1765남대천<NA><NA><NA><NA>
1819전북특별자치도장수군장수논개수상레저최**<NA>장계면 의암로 632-77대곡저수지2019-04-122023-12-13종사자3명(인명구조요원3명)1
1920전북특별자치도임실군(유)사선대 해피랜드이**<NA>관촌면 춘향로 3441-26섬진강<NA>2015-05-31장기휴업중(2013-07-11~)<NA>
2021전북특별자치도순창군해양레저 체험교실섬진강수상레저연맹 서**<NA>적성면 고원리 966순창군 섬진강2020-06-252020-11-15종사자7명(인명구조요원6명)1
2122전북특별자치도부안군줄포만 갯벌 생태공원권**<NA>부안군 줄포리 생태공원로38줄포면 습지2015-09-251930-12-31종사자2명(인명구조요원2명)1