Overview

Dataset statistics

Number of variables15
Number of observations23
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory127.7 B

Variable types

Numeric1
Categorical8
Text6

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 순번High correlation
업체명 has 1 (4.3%) missing valuesMissing
순번 has unique valuesUnique
시설명 has unique valuesUnique
대표자 has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:31:20.827676
Analysis finished2024-03-14 00:31:21.639518
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-03-14T09:31:21.692444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2024-03-14T09:31:21.818606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
23 1
 
4.3%
22 1
 
4.3%
21 1
 
4.3%
20 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
16 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
6 1
4.3%
7 1
4.3%
8 1
4.3%
9 1
4.3%
10 1
4.3%
ValueCountFrequency (%)
23 1
4.3%
22 1
4.3%
21 1
4.3%
20 1
4.3%
19 1
4.3%
18 1
4.3%
17 1
4.3%
16 1
4.3%
15 1
4.3%
14 1
4.3%

시군명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)39.1%
Missing0
Missing (%)0.0%
Memory size316.0 B
전주시
7 
무주군
3 
김제시
3 
부안군
2 
군산시
2 
Other values (4)
6 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)8.7%

Sample

1st row부안군
2nd row부안군
3rd row무주군
4th row무주군
5th row무주군

Common Values

ValueCountFrequency (%)
전주시 7
30.4%
무주군 3
13.0%
김제시 3
13.0%
부안군 2
 
8.7%
군산시 2
 
8.7%
고창군 2
 
8.7%
임실군 2
 
8.7%
남원시 1
 
4.3%
정읍시 1
 
4.3%

Length

2024-03-14T09:31:21.920122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:31:22.009506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전주시 7
30.4%
무주군 3
13.0%
김제시 3
13.0%
부안군 2
 
8.7%
군산시 2
 
8.7%
고창군 2
 
8.7%
임실군 2
 
8.7%
남원시 1
 
4.3%
정읍시 1
 
4.3%

시설명
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-14T09:31:22.187247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length6.5652174
Min length4

Characters and Unicode

Total characters151
Distinct characters87
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

Unique23 ?
Unique (%)100.0%

Sample

1st row모항해나루가족호텔
2nd row아쿠아월드
3rd row무주놀이랜드
4th row무주덕유산 리조트
5th row뉴 잉글랜드
ValueCountFrequency (%)
전주 2
 
5.7%
모항해나루가족호텔 1
 
2.9%
방방월드 1
 
2.9%
키즈야 1
 
2.9%
드림랜드 1
 
2.9%
퍼니팡팡 1
 
2.9%
그로잉 1
 
2.9%
실내방방 1
 
2.9%
금강랜드 1
 
2.9%
키즈카페 1
 
2.9%
Other values (24) 24
68.6%
2024-03-14T09:31:22.554568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
7.9%
드 11
 
7.3%
방 10
 
6.6%
랜 8
 
5.3%
아 4
 
2.6%
주 4
 
2.6%
스 3
 
2.0%
고 2
 
1.3%
잉 2
 
1.3%
즈 2
 
1.3%
Other values (77) 93
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 136
90.1%
Space Separator 12
 
7.9%
Open Punctuation 1
 
0.7%
Close Punctuation 1
 
0.7%
Other Symbol 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
드 11
 
8.1%
방 10
 
7.4%
랜 8
 
5.9%
아 4
 
2.9%
주 4
 
2.9%
스 3
 
2.2%
고 2
 
1.5%
잉 2
 
1.5%
즈 2
 
1.5%
야 2
 
1.5%
Other values (73) 88
64.7%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 137
90.7%
Common 14
 
9.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
드 11
 
8.0%
방 10
 
7.3%
랜 8
 
5.8%
아 4
 
2.9%
주 4
 
2.9%
스 3
 
2.2%
고 2
 
1.5%
잉 2
 
1.5%
즈 2
 
1.5%
야 2
 
1.5%
Other values (74) 89
65.0%
Common
ValueCountFrequency (%)
12
85.7%
( 1
 
7.1%
) 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136
90.1%
ASCII 14
 
9.3%
None 1
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
85.7%
( 1
 
7.1%
) 1
 
7.1%
Hangul
ValueCountFrequency (%)
드 11
 
8.1%
방 10
 
7.4%
랜 8
 
5.9%
아 4
 
2.9%
주 4
 
2.9%
스 3
 
2.2%
고 2
 
1.5%
잉 2
 
1.5%
즈 2
 
1.5%
야 2
 
1.5%
Other values (73) 88
64.7%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명주소
Text

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-14T09:31:22.757334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length14.608696
Min length10

Characters and Unicode

Total characters336
Distinct characters78
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

Unique21 ?
Unique (%)91.3%

Sample

1st row부안군 변산면 모항해변길 73
2nd row부안군 변산면 변산해변로 51
3rd row무주군 무주읍 괴목로 1330
4th row무주군 설천면 만선로 185
5th row무주군 설천면 만선로 185
ValueCountFrequency (%)
전주시 7
 
8.0%
완산구 6
 
6.9%
무주군 3
 
3.4%
김제시 3
 
3.4%
부안군 2
 
2.3%
임실군 2
 
2.3%
설천면 2
 
2.3%
173 2
 
2.3%
군산시 2
 
2.3%
만선로 2
 
2.3%
Other values (52) 56
64.4%
2024-03-14T09:31:23.066077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64
 
19.0%
3 16
 
4.8%
로 15
 
4.5%
시 14
 
4.2%
산 13
 
3.9%
1 12
 
3.6%
주 12
 
3.6%
군 11
 
3.3%
길 8
 
2.4%
전 8
 
2.4%
Other values (68) 163
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 203
60.4%
Decimal Number 66
 
19.6%
Space Separator 64
 
19.0%
Dash Punctuation 3
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 15
 
7.4%
시 14
 
6.9%
산 13
 
6.4%
주 12
 
5.9%
군 11
 
5.4%
길 8
 
3.9%
전 8
 
3.9%
면 7
 
3.4%
구 7
 
3.4%
완 6
 
3.0%
Other values (56) 102
50.2%
Decimal Number
ValueCountFrequency (%)
3 16
24.2%
1 12
18.2%
4 7
10.6%
5 7
10.6%
7 7
10.6%
8 6
 
9.1%
2 4
 
6.1%
0 3
 
4.5%
9 2
 
3.0%
6 2
 
3.0%
Space Separator
ValueCountFrequency (%)
64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 203
60.4%
Common 133
39.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 15
 
7.4%
시 14
 
6.9%
산 13
 
6.4%
주 12
 
5.9%
군 11
 
5.4%
길 8
 
3.9%
전 8
 
3.9%
면 7
 
3.4%
구 7
 
3.4%
완 6
 
3.0%
Other values (56) 102
50.2%
Common
ValueCountFrequency (%)
64
48.1%
3 16
 
12.0%
1 12
 
9.0%
4 7
 
5.3%
5 7
 
5.3%
7 7
 
5.3%
8 6
 
4.5%
2 4
 
3.0%
0 3
 
2.3%
- 3
 
2.3%
Other values (2) 4
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 203
60.4%
ASCII 133
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64
48.1%
3 16
 
12.0%
1 12
 
9.0%
4 7
 
5.3%
5 7
 
5.3%
7 7
 
5.3%
8 6
 
4.5%
2 4
 
3.0%
0 3
 
2.3%
- 3
 
2.3%
Other values (2) 4
 
3.0%
Hangul
ValueCountFrequency (%)
로 15
 
7.4%
시 14
 
6.9%
산 13
 
6.4%
주 12
 
5.9%
군 11
 
5.4%
길 8
 
3.9%
전 8
 
3.9%
면 7
 
3.4%
구 7
 
3.4%
완 6
 
3.0%
Other values (56) 102
50.2%

지번주소
Text

Distinct22
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-14T09:31:23.259032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length16.652174
Min length11

Characters and Unicode

Total characters383
Distinct characters68
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

Unique21 ?
Unique (%)91.3%

Sample

1st row부안군 변산면 도청리 203-6
2nd row부안군 변산면 격포리 257
3rd row무주군 무주읍 당산리 343
4th row무주군 설천면 심곡리 산43-15
5th row무주군 설천면 심곡리 산43-15
ValueCountFrequency (%)
전주시 7
 
8.0%
완산구 6
 
6.9%
무주군 3
 
3.4%
김제시 3
 
3.4%
부안군 2
 
2.3%
고창읍 2
 
2.3%
삼천동1가 2
 
2.3%
설천면 2
 
2.3%
군산시 2
 
2.3%
심곡리 2
 
2.3%
Other values (52) 56
64.4%
2024-03-14T09:31:23.541116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64
 
16.7%
1 22
 
5.7%
산 20
 
5.2%
- 17
 
4.4%
3 16
 
4.2%
시 14
 
3.7%
7 13
 
3.4%
동 12
 
3.1%
2 12
 
3.1%
군 11
 
2.9%
Other values (58) 182
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 202
52.7%
Decimal Number 100
26.1%
Space Separator 64
 
16.7%
Dash Punctuation 17
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 20
 
9.9%
시 14
 
6.9%
동 12
 
5.9%
군 11
 
5.4%
주 11
 
5.4%
리 11
 
5.4%
구 7
 
3.5%
전 7
 
3.5%
면 7
 
3.5%
가 6
 
3.0%
Other values (46) 96
47.5%
Decimal Number
ValueCountFrequency (%)
1 22
22.0%
3 16
16.0%
7 13
13.0%
2 12
12.0%
4 10
10.0%
0 9
9.0%
5 6
 
6.0%
9 5
 
5.0%
6 4
 
4.0%
8 3
 
3.0%
Space Separator
ValueCountFrequency (%)
64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 202
52.7%
Common 181
47.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 20
 
9.9%
시 14
 
6.9%
동 12
 
5.9%
군 11
 
5.4%
주 11
 
5.4%
리 11
 
5.4%
구 7
 
3.5%
전 7
 
3.5%
면 7
 
3.5%
가 6
 
3.0%
Other values (46) 96
47.5%
Common
ValueCountFrequency (%)
64
35.4%
1 22
 
12.2%
- 17
 
9.4%
3 16
 
8.8%
7 13
 
7.2%
2 12
 
6.6%
4 10
 
5.5%
0 9
 
5.0%
5 6
 
3.3%
9 5
 
2.8%
Other values (2) 7
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 202
52.7%
ASCII 181
47.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64
35.4%
1 22
 
12.2%
- 17
 
9.4%
3 16
 
8.8%
7 13
 
7.2%
2 12
 
6.6%
4 10
 
5.5%
0 9
 
5.0%
5 6
 
3.3%
9 5
 
2.8%
Other values (2) 7
 
3.9%
Hangul
ValueCountFrequency (%)
산 20
 
9.9%
시 14
 
6.9%
동 12
 
5.9%
군 11
 
5.4%
주 11
 
5.4%
리 11
 
5.4%
구 7
 
3.5%
전 7
 
3.5%
면 7
 
3.5%
가 6
 
3.0%
Other values (46) 96
47.5%

업체명
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing1
Missing (%)4.3%
Memory size316.0 B
2024-03-14T09:31:23.701921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.2272727
Min length3

Characters and Unicode

Total characters137
Distinct characters82
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 row모항해나루 가족호텔
2nd row㈜대명레저산업
3rd row무주놀이랜드
4th row㈜부영
5th row뉴 잉글랜드
ValueCountFrequency (%)
전주 2
 
5.9%
모항해나루 1
 
2.9%
그로잉 1
 
2.9%
키즈카페 1
 
2.9%
방방클럽 1
 
2.9%
키즈야 1
 
2.9%
드림랜드 1
 
2.9%
퍼니팡팡 1
 
2.9%
실내방방 1
 
2.9%
㈜스파라쿠아 1
 
2.9%
Other values (23) 23
67.6%
2024-03-14T09:31:24.007829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
8.8%
방 10
 
7.3%
드 9
 
6.6%
랜 7
 
5.1%
주 3
 
2.2%
㈜ 3
 
2.2%
스 3
 
2.2%
키 2
 
1.5%
즈 2
 
1.5%
카 2
 
1.5%
Other values (72) 84
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120
87.6%
Space Separator 12
 
8.8%
Other Symbol 3
 
2.2%
Open Punctuation 1
 
0.7%
Close Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
방 10
 
8.3%
드 9
 
7.5%
랜 7
 
5.8%
주 3
 
2.5%
스 3
 
2.5%
키 2
 
1.7%
즈 2
 
1.7%
카 2
 
1.7%
파 2
 
1.7%
전 2
 
1.7%
Other values (68) 78
65.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 123
89.8%
Common 14
 
10.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
방 10
 
8.1%
드 9
 
7.3%
랜 7
 
5.7%
주 3
 
2.4%
㈜ 3
 
2.4%
스 3
 
2.4%
키 2
 
1.6%
즈 2
 
1.6%
카 2
 
1.6%
파 2
 
1.6%
Other values (69) 80
65.0%
Common
ValueCountFrequency (%)
12
85.7%
( 1
 
7.1%
) 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 120
87.6%
ASCII 14
 
10.2%
None 3
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
85.7%
( 1
 
7.1%
) 1
 
7.1%
Hangul
ValueCountFrequency (%)
방 10
 
8.3%
드 9
 
7.5%
랜 7
 
5.8%
주 3
 
2.5%
스 3
 
2.5%
키 2
 
1.7%
즈 2
 
1.7%
카 2
 
1.7%
파 2
 
1.7%
전 2
 
1.7%
Other values (68) 78
65.0%
None
ValueCountFrequency (%)
㈜ 3
100.0%

대표자
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-14T09:31:24.178983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0434783
Min length3

Characters and Unicode

Total characters70
Distinct characters52
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

Unique23 ?
Unique (%)100.0%

Sample

1st row홍성춘
2nd row조현철
3rd row이장호
4th row이중근
5th row오주연
ValueCountFrequency (%)
홍성춘 1
 
4.3%
문진혁 1
 
4.3%
이주희 1
 
4.3%
이종균 1
 
4.3%
고창군수 1
 
4.3%
이준국 1
 
4.3%
송미옥 1
 
4.3%
손성섭 1
 
4.3%
최금이 1
 
4.3%
김일권 1
 
4.3%
Other values (13) 13
56.5%
2024-03-14T09:31:24.472566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 6
 
8.6%
진 4
 
5.7%
성 4
 
5.7%
오 3
 
4.3%
김 2
 
2.9%
정 2
 
2.9%
최 2
 
2.9%
두 2
 
2.9%
주 2
 
2.9%
미 1
 
1.4%
Other values (42) 42
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 70
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 6
 
8.6%
진 4
 
5.7%
성 4
 
5.7%
오 3
 
4.3%
김 2
 
2.9%
정 2
 
2.9%
최 2
 
2.9%
두 2
 
2.9%
주 2
 
2.9%
미 1
 
1.4%
Other values (42) 42
60.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 70
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 6
 
8.6%
진 4
 
5.7%
성 4
 
5.7%
오 3
 
4.3%
김 2
 
2.9%
정 2
 
2.9%
최 2
 
2.9%
두 2
 
2.9%
주 2
 
2.9%
미 1
 
1.4%
Other values (42) 42
60.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 70
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 6
 
8.6%
진 4
 
5.7%
성 4
 
5.7%
오 3
 
4.3%
김 2
 
2.9%
정 2
 
2.9%
최 2
 
2.9%
두 2
 
2.9%
주 2
 
2.9%
미 1
 
1.4%
Other values (42) 42
60.0%

전화번호
Text

Distinct19
Distinct (%)82.6%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-03-14T09:31:24.659028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length9.5652174
Min length1

Characters and Unicode

Total characters220
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

Unique18 ?
Unique (%)78.3%

Sample

1st row063-580-0700
2nd row063-580-8702
3rd row063-322-7752
4th row063-320-9000
5th row063-322-0702
ValueCountFrequency (%)
5
21.7%
063-580-0700 1
 
4.3%
063-223-0020 1
 
4.3%
070-4799-0007 1
 
4.3%
063-560-7500 1
 
4.3%
063-560-8663 1
 
4.3%
063-453-1525 1
 
4.3%
063-275-4900 1
 
4.3%
070-8174-5446 1
 
4.3%
063-229-0407 1
 
4.3%
Other values (9) 9
39.1%
2024-03-14T09:31:24.920383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 52
23.6%
- 40
18.2%
6 26
11.8%
3 24
10.9%
2 17
 
7.7%
7 15
 
6.8%
5 14
 
6.4%
4 13
 
5.9%
8 9
 
4.1%
1 5
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 180
81.8%
Dash Punctuation 40
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 52
28.9%
6 26
14.4%
3 24
13.3%
2 17
 
9.4%
7 15
 
8.3%
5 14
 
7.8%
4 13
 
7.2%
8 9
 
5.0%
1 5
 
2.8%
9 5
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 220
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 52
23.6%
- 40
18.2%
6 26
11.8%
3 24
10.9%
2 17
 
7.7%
7 15
 
6.8%
5 14
 
6.4%
4 13
 
5.9%
8 9
 
4.1%
1 5
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 52
23.6%
- 40
18.2%
6 26
11.8%
3 24
10.9%
2 17
 
7.7%
7 15
 
6.8%
5 14
 
6.4%
4 13
 
5.9%
8 9
 
4.1%
1 5
 
2.3%

검사기구수
Categorical

Distinct10
Distinct (%)43.5%
Missing0
Missing (%)0.0%
Memory size316.0 B
-
9 
3
4 
1
3 
5
1 
10
1 
Other values (5)
5 

Length

Max length2
Median length1
Mean length1.1304348
Min length1

Unique

Unique7 ?
Unique (%)30.4%

Sample

1st row1
2nd row5
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
- 9
39.1%
3 4
17.4%
1 3
 
13.0%
5 1
 
4.3%
10 1
 
4.3%
8 1
 
4.3%
2 1
 
4.3%
11 1
 
4.3%
16 1
 
4.3%
4 1
 
4.3%

Length

2024-03-14T09:31:25.027449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:31:25.121032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
9
39.1%
3 4
17.4%
1 3
 
13.0%
5 1
 
4.3%
10 1
 
4.3%
8 1
 
4.3%
2 1
 
4.3%
11 1
 
4.3%
16 1
 
4.3%
4 1
 
4.3%

비검기구수
Categorical

Distinct10
Distinct (%)43.5%
Missing0
Missing (%)0.0%
Memory size316.0 B
-
8 
2
5 
5
2 
4
2 
1
1 
Other values (5)
5 

Length

Max length2
Median length1
Mean length1.1304348
Min length1

Unique

Unique6 ?
Unique (%)26.1%

Sample

1st row1
2nd row2
3rd row-
4th row-
5th row-

Common Values

ValueCountFrequency (%)
- 8
34.8%
2 5
21.7%
5 2
 
8.7%
4 2
 
8.7%
1 1
 
4.3%
12 1
 
4.3%
13 1
 
4.3%
3 1
 
4.3%
38 1
 
4.3%
6 1
 
4.3%

Length

2024-03-14T09:31:25.243640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:31:25.355592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8
34.8%
2 5
21.7%
5 2
 
8.7%
4 2
 
8.7%
1 1
 
4.3%
12 1
 
4.3%
13 1
 
4.3%
3 1
 
4.3%
38 1
 
4.3%
6 1
 
4.3%

비고
Categorical

Distinct10
Distinct (%)43.5%
Missing0
Missing (%)0.0%
Memory size316.0 B
전주시
5 
물놀이(년1회)
4 
년1회
4 
년2회
4 
년1회(휴업)
1 
Other values (5)
5 

Length

Max length14
Median length3
Mean length4.5217391
Min length3

Unique

Unique6 ?
Unique (%)26.1%

Sample

1st row물놀이(년1회)
2nd row물놀이(년1회)
3rd row년1회(휴업)
4th row년1회
5th row년1회

Common Values

ValueCountFrequency (%)
전주시 5
21.7%
물놀이(년1회) 4
17.4%
년1회 4
17.4%
년2회 4
17.4%
년1회(휴업) 1
 
4.3%
정읍시 1
 
4.3%
김제시 1
 
4.3%
년2회(9), 년1회(2) 1
 
4.3%
군산시 1
 
4.3%
임실군 1
 
4.3%

Length

2024-03-14T09:31:25.456388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:31:25.552521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전주시 5
20.8%
물놀이(년1회 4
16.7%
년1회 4
16.7%
년2회 4
16.7%
년1회(휴업 1
 
4.2%
정읍시 1
 
4.2%
김제시 1
 
4.2%
년2회(9 1
 
4.2%
년1회(2 1
 
4.2%
군산시 1
 
4.2%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
관광총괄과
23 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광총괄과 23
100.0%

Length

2024-03-14T09:31:25.653427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:31:25.725198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광총괄과 23
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
공개
23 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 23
100.0%

Length

2024-03-14T09:31:25.816470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:31:25.885391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 23
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2015.1
23 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015.1
2nd row2015.1
3rd row2015.1
4th row2015.1
5th row2015.1

Common Values

ValueCountFrequency (%)
2015.1 23
100.0%

Length

2024-03-14T09:31:25.960405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:31:26.047843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 23
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
1년
23 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 23
100.0%

Length

2024-03-14T09:31:26.117483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:31:26.189209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 23
100.0%

Interactions

2024-03-14T09:31:21.309850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:31:26.479911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명시설명도로명주소지번주소업체명대표자전화번호검사기구수비검기구수비고
순번1.0000.8291.0001.0001.0001.0001.0000.6150.7330.0790.791
시군명0.8291.0001.0001.0001.0001.0001.0000.7910.7560.7200.772
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0000.9321.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.0000.9321.0001.0001.000
업체명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대표자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호0.6150.7911.0000.9320.9321.0001.0001.0000.9840.8040.000
검사기구수0.7330.7561.0001.0001.0001.0001.0000.9841.0000.7010.000
비검기구수0.0790.7201.0001.0001.0001.0001.0000.8040.7011.0000.861
비고0.7910.7721.0001.0001.0001.0001.0000.0000.0000.8611.000
2024-03-14T09:31:26.578975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명비검기구수비고검사기구수
시군명1.0000.3880.4510.432
비검기구수0.3881.0000.4080.229
비고0.4510.4081.0000.000
검사기구수0.4320.2290.0001.000
2024-03-14T09:31:26.686988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명검사기구수비검기구수비고
순번1.0000.5180.1050.0000.245
시군명0.5181.0000.4320.3880.451
검사기구수0.1050.4321.0000.2290.000
비검기구수0.0000.3880.2291.0000.408
비고0.2450.4510.0000.4081.000

Missing values

2024-03-14T09:31:21.404538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:31:21.559604image/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

순번시군명시설명도로명주소지번주소업체명대표자전화번호검사기구수비검기구수비고자료출처공개여부작성일갱신주기
01부안군모항해나루가족호텔부안군 변산면 모항해변길 73부안군 변산면 도청리 203-6모항해나루 가족호텔홍성춘063-580-070011물놀이(년1회)관광총괄과공개2015.11년
12부안군아쿠아월드부안군 변산면 변산해변로 51부안군 변산면 격포리 257㈜대명레저산업조현철063-580-870252물놀이(년1회)관광총괄과공개2015.11년
23무주군무주놀이랜드무주군 무주읍 괴목로 1330무주군 무주읍 당산리 343무주놀이랜드이장호063-322-77523-년1회(휴업)관광총괄과공개2015.11년
34무주군무주덕유산 리조트무주군 설천면 만선로 185무주군 설천면 심곡리 산43-15㈜부영이중근063-320-90003-년1회관광총괄과공개2015.11년
45무주군뉴 잉글랜드무주군 설천면 만선로 185무주군 설천면 심곡리 산43-15뉴 잉글랜드오주연063-322-07023-년1회관광총괄과공개2015.11년
56남원시남원랜드남원시 양림길 58-13남원시 어현동 37-140<NA>오경태063-632-6070105년2회관광총괄과공개2015.11년
67정읍시진영 야구 연습장정읍시 수성로 33정읍시 수성동 932-8진영 야구 연습장김찬식--12정읍시관광총괄과공개2015.11년
78김제시모악랜드김제시 금산면 모악로 476-39김제시 금산면 금산리 79-10모악랜드최두환063-548-44018-년2회관광총괄과공개2015.11년
89김제시하우스방방김제시 금성8길 17김제시 신풍동 610-5하우스 방방박성규063-547-4063-5김제시관광총괄과공개2015.11년
910김제시오투아일랜드김제시 승암길 13김제시 검산동 912-43오투 아일랜드양천두1800-52662-물놀이(년1회)관광총괄과공개2015.11년
순번시군명시설명도로명주소지번주소업체명대표자전화번호검사기구수비검기구수비고자료출처공개여부작성일갱신주기
1314전주시방방클럽 키즈야전주시 완산구 거마평로 57전주시 완산구 삼천동1가 287-14방방클럽 키즈야정은진070-8174-5446-2전주시관광총괄과공개2015.11년
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