Overview

Dataset statistics

Number of variables13
Number of observations94
Missing cells157
Missing cells (%)12.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.9 KiB
Average record size in memory107.4 B

Variable types

Numeric2
Categorical5
Text4
Boolean1
DateTime1

Dataset

Description전북특별자치도 시군별 유원시설 현황 데이터입니다.(시군명, 시설명, 도로명주소, 대표자, 전화번호, 검사기구수, 비검기구수 등)우리 기관에서는 더 이상 생성 불가 데이터입니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055597/fileData.do

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
검사기구수 is highly overall correlated with 비검기구수 and 1 other fieldsHigh correlation
비검기구수 is highly overall correlated with 검사기구수 and 1 other fieldsHigh correlation
비고 is highly overall correlated with 검사기구수 and 1 other fieldsHigh correlation
전화번호 has 81 (86.2%) missing valuesMissing
검사기구수 has 76 (80.9%) missing valuesMissing
순번 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-03-15 02:03:45.343622
Analysis finished2024-03-15 02:03:49.612806
Duration4.27 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.5
Minimum1
Maximum94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size974.0 B
2024-03-15T11:03:49.861208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.65
Q124.25
median47.5
Q370.75
95-th percentile89.35
Maximum94
Range93
Interquartile range (IQR)46.5

Descriptive statistics

Standard deviation27.279418
Coefficient of variation (CV)0.57430354
Kurtosis-1.2
Mean47.5
Median Absolute Deviation (MAD)23.5
Skewness0
Sum4465
Variance744.16667
MonotonicityStrictly increasing
2024-03-15T11:03:50.324567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
61 1
 
1.1%
70 1
 
1.1%
69 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
Other values (84) 84
89.4%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
94 1
1.1%
93 1
1.1%
92 1
1.1%
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%

시군명
Categorical

Distinct14
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size880.0 B
전주시
41 
군산시
10 
정읍시
9 
익산시
8 
무주군
5 
Other values (9)
21 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique3 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 41
43.6%
군산시 10
 
10.6%
정읍시 9
 
9.6%
익산시 8
 
8.5%
무주군 5
 
5.3%
부안군 5
 
5.3%
고창군 4
 
4.3%
남원시 3
 
3.2%
김제시 2
 
2.1%
완주군 2
 
2.1%
Other values (4) 5
 
5.3%

Length

2024-03-15T11:03:50.769087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 41
43.6%
군산시 10
 
10.6%
정읍시 9
 
9.6%
익산시 8
 
8.5%
무주군 5
 
5.3%
부안군 5
 
5.3%
고창군 4
 
4.3%
남원시 3
 
3.2%
김제시 2
 
2.1%
완주군 2
 
2.1%
Other values (4) 5
 
5.3%

시설명
Text

Distinct92
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size880.0 B
2024-03-15T11:03:51.793709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length12
Mean length7.0212766
Min length2

Characters and Unicode

Total characters660
Distinct characters206
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)95.7%

Sample

1st row전주 노리존
2nd row전주 드림랜드
3rd row전주한옥레일바이크
4th row금강랜드
5th row군산 야외수영장
ValueCountFrequency (%)
야사노 4
 
3.1%
킹콩점프 3
 
2.3%
키즈카페 3
 
2.3%
월드킹 2
 
1.6%
익산점 2
 
1.6%
전주 2
 
1.6%
차타타 2
 
1.6%
상상노리 2
 
1.6%
노리존 1
 
0.8%
해피키즈팡팡 1
 
0.8%
Other values (107) 107
82.9%
2024-03-15T11:03:53.020327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
5.3%
점 23
 
3.5%
드 20
 
3.0%
리 18
 
2.7%
이 17
 
2.6%
방 16
 
2.4%
키 16
 
2.4%
즈 16
 
2.4%
랜 13
 
2.0%
아 11
 
1.7%
Other values (196) 475
72.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 593
89.8%
Space Separator 35
 
5.3%
Uppercase Letter 13
 
2.0%
Lowercase Letter 7
 
1.1%
Decimal Number 5
 
0.8%
Close Punctuation 3
 
0.5%
Open Punctuation 3
 
0.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 23
 
3.9%
드 20
 
3.4%
리 18
 
3.0%
이 17
 
2.9%
방 16
 
2.7%
키 16
 
2.7%
즈 16
 
2.7%
랜 13
 
2.2%
아 11
 
1.9%
주 11
 
1.9%
Other values (177) 432
72.8%
Uppercase Letter
ValueCountFrequency (%)
V 4
30.8%
R 4
30.8%
P 2
15.4%
H 1
 
7.7%
T 1
 
7.7%
B 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
o 2
28.6%
l 2
28.6%
c 1
14.3%
e 1
14.3%
i 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
1 1
20.0%
5 1
20.0%
0 1
20.0%
Space Separator
ValueCountFrequency (%)
35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 593
89.8%
Common 47
 
7.1%
Latin 20
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 23
 
3.9%
드 20
 
3.4%
리 18
 
3.0%
이 17
 
2.9%
방 16
 
2.7%
키 16
 
2.7%
즈 16
 
2.7%
랜 13
 
2.2%
아 11
 
1.9%
주 11
 
1.9%
Other values (177) 432
72.8%
Latin
ValueCountFrequency (%)
V 4
20.0%
R 4
20.0%
P 2
10.0%
o 2
10.0%
l 2
10.0%
H 1
 
5.0%
c 1
 
5.0%
T 1
 
5.0%
B 1
 
5.0%
e 1
 
5.0%
Common
ValueCountFrequency (%)
35
74.5%
) 3
 
6.4%
( 3
 
6.4%
2 2
 
4.3%
1 1
 
2.1%
5 1
 
2.1%
0 1
 
2.1%
& 1
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 593
89.8%
ASCII 67
 
10.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
52.2%
V 4
 
6.0%
R 4
 
6.0%
) 3
 
4.5%
( 3
 
4.5%
2 2
 
3.0%
P 2
 
3.0%
o 2
 
3.0%
l 2
 
3.0%
1 1
 
1.5%
Other values (9) 9
 
13.4%
Hangul
ValueCountFrequency (%)
점 23
 
3.9%
드 20
 
3.4%
리 18
 
3.0%
이 17
 
2.9%
방 16
 
2.7%
키 16
 
2.7%
즈 16
 
2.7%
랜 13
 
2.2%
아 11
 
1.9%
주 11
 
1.9%
Other values (177) 432
72.8%

도로명주소
Text

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size880.0 B
2024-03-15T11:03:54.128549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length18.191489
Min length10

Characters and Unicode

Total characters1710
Distinct characters162
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)100.0%

Sample

1st row전주시 완산구 전주객사3길 34
2nd row전주시 덕진구 덕진동1가 산 36-8
3rd row전주시 덕진구 동부대로 420, 아중역
4th row군산시 성산면 철새로 53
5th row군산시 해망로 546-10
ValueCountFrequency (%)
전주시 41
 
10.0%
완산구 26
 
6.3%
덕진구 15
 
3.6%
2층 13
 
3.2%
군산시 10
 
2.4%
정읍시 9
 
2.2%
3층 9
 
2.2%
4층 8
 
1.9%
익산시 8
 
1.9%
무주군 5
 
1.2%
Other values (216) 268
65.0%
2024-03-15T11:03:55.691635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
325
 
19.0%
시 75
 
4.4%
1 69
 
4.0%
산 63
 
3.7%
로 55
 
3.2%
3 54
 
3.2%
주 54
 
3.2%
, 51
 
3.0%
2 49
 
2.9%
전 46
 
2.7%
Other values (152) 869
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 952
55.7%
Decimal Number 343
 
20.1%
Space Separator 325
 
19.0%
Other Punctuation 51
 
3.0%
Dash Punctuation 22
 
1.3%
Close Punctuation 8
 
0.5%
Open Punctuation 8
 
0.5%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 75
 
7.9%
산 63
 
6.6%
로 55
 
5.8%
주 54
 
5.7%
전 46
 
4.8%
층 42
 
4.4%
구 42
 
4.4%
군 32
 
3.4%
완 28
 
2.9%
길 25
 
2.6%
Other values (136) 490
51.5%
Decimal Number
ValueCountFrequency (%)
1 69
20.1%
3 54
15.7%
2 49
14.3%
4 42
12.2%
5 26
 
7.6%
0 24
 
7.0%
8 23
 
6.7%
6 21
 
6.1%
7 21
 
6.1%
9 14
 
4.1%
Space Separator
ValueCountFrequency (%)
325
100.0%
Other Punctuation
ValueCountFrequency (%)
, 51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 952
55.7%
Common 757
44.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 75
 
7.9%
산 63
 
6.6%
로 55
 
5.8%
주 54
 
5.7%
전 46
 
4.8%
층 42
 
4.4%
구 42
 
4.4%
군 32
 
3.4%
완 28
 
2.9%
길 25
 
2.6%
Other values (136) 490
51.5%
Common
ValueCountFrequency (%)
325
42.9%
1 69
 
9.1%
3 54
 
7.1%
, 51
 
6.7%
2 49
 
6.5%
4 42
 
5.5%
5 26
 
3.4%
0 24
 
3.2%
8 23
 
3.0%
- 22
 
2.9%
Other values (5) 72
 
9.5%
Latin
ValueCountFrequency (%)
b 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 952
55.7%
ASCII 758
44.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
325
42.9%
1 69
 
9.1%
3 54
 
7.1%
, 51
 
6.7%
2 49
 
6.5%
4 42
 
5.5%
5 26
 
3.4%
0 24
 
3.2%
8 23
 
3.0%
- 22
 
2.9%
Other values (6) 73
 
9.6%
Hangul
ValueCountFrequency (%)
시 75
 
7.9%
산 63
 
6.6%
로 55
 
5.8%
주 54
 
5.7%
전 46
 
4.8%
층 42
 
4.4%
구 42
 
4.4%
군 32
 
3.4%
완 28
 
2.9%
길 25
 
2.6%
Other values (136) 490
51.5%

대표자
Text

Distinct87
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size880.0 B
2024-03-15T11:03:56.693608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length3
Mean length3.3085106
Min length2

Characters and Unicode

Total characters311
Distinct characters102
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

Unique80 ?
Unique (%)85.1%

Sample

1st row시*진
2nd row김*종
3rd row권*현, 권*기
4th row소*숙
5th row군산시장
ValueCountFrequency (%)
김*선 2
 
2.1%
최*이 2
 
2.1%
김*수 2
 
2.1%
이*희 2
 
2.1%
김*성 2
 
2.1%
김*숙 2
 
2.1%
김*종 2
 
2.1%
오*순 1
 
1.1%
강*수 1
 
1.1%
명*율 1
 
1.1%
Other values (78) 78
82.1%
2024-03-15T11:03:58.002461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 89
28.6%
김 24
 
7.7%
이 15
 
4.8%
수 6
 
1.9%
고 6
 
1.9%
최 5
 
1.6%
장 5
 
1.6%
환 5
 
1.6%
순 5
 
1.6%
박 4
 
1.3%
Other values (92) 147
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 216
69.5%
Other Punctuation 90
28.9%
Open Punctuation 2
 
0.6%
Close Punctuation 2
 
0.6%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 24
 
11.1%
이 15
 
6.9%
수 6
 
2.8%
고 6
 
2.8%
최 5
 
2.3%
장 5
 
2.3%
환 5
 
2.3%
순 5
 
2.3%
박 4
 
1.9%
정 4
 
1.9%
Other values (87) 137
63.4%
Other Punctuation
ValueCountFrequency (%)
* 89
98.9%
, 1
 
1.1%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 216
69.5%
Common 95
30.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 24
 
11.1%
이 15
 
6.9%
수 6
 
2.8%
고 6
 
2.8%
최 5
 
2.3%
장 5
 
2.3%
환 5
 
2.3%
순 5
 
2.3%
박 4
 
1.9%
정 4
 
1.9%
Other values (87) 137
63.4%
Common
ValueCountFrequency (%)
* 89
93.7%
( 2
 
2.1%
) 2
 
2.1%
, 1
 
1.1%
1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 216
69.5%
ASCII 95
30.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 89
93.7%
( 2
 
2.1%
) 2
 
2.1%
, 1
 
1.1%
1
 
1.1%
Hangul
ValueCountFrequency (%)
김 24
 
11.1%
이 15
 
6.9%
수 6
 
2.8%
고 6
 
2.8%
최 5
 
2.3%
장 5
 
2.3%
환 5
 
2.3%
순 5
 
2.3%
박 4
 
1.9%
정 4
 
1.9%
Other values (87) 137
63.4%

전화번호
Text

MISSING 

Distinct13
Distinct (%)100.0%
Missing81
Missing (%)86.2%
Memory size880.0 B
2024-03-15T11:03:58.740044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.769231
Min length9

Characters and Unicode

Total characters153
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

Unique13 ?
Unique (%)100.0%

Sample

1st row063-275-4900
2nd row063-453-1525
3rd row063-632-6070
4th row063-548-4401
5th row1800-5266
ValueCountFrequency (%)
063-275-4900 1
 
7.7%
063-453-1525 1
 
7.7%
063-632-6070 1
 
7.7%
063-548-4401 1
 
7.7%
1800-5266 1
 
7.7%
063-263-7343 1
 
7.7%
063-322-9000 1
 
7.7%
063-322-7752 1
 
7.7%
063-560-8663 1
 
7.7%
063-560-7500 1
 
7.7%
Other values (3) 3
23.1%
2024-03-15T11:03:59.840966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33
21.6%
- 25
16.3%
6 21
13.7%
3 20
13.1%
5 12
 
7.8%
2 11
 
7.2%
7 11
 
7.2%
4 6
 
3.9%
8 6
 
3.9%
9 4
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 128
83.7%
Dash Punctuation 25
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 33
25.8%
6 21
16.4%
3 20
15.6%
5 12
 
9.4%
2 11
 
8.6%
7 11
 
8.6%
4 6
 
4.7%
8 6
 
4.7%
9 4
 
3.1%
1 4
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 153
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 33
21.6%
- 25
16.3%
6 21
13.7%
3 20
13.1%
5 12
 
7.8%
2 11
 
7.2%
7 11
 
7.2%
4 6
 
3.9%
8 6
 
3.9%
9 4
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 153
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33
21.6%
- 25
16.3%
6 21
13.7%
3 20
13.1%
5 12
 
7.8%
2 11
 
7.2%
7 11
 
7.2%
4 6
 
3.9%
8 6
 
3.9%
9 4
 
2.6%

검사기구수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)50.0%
Missing76
Missing (%)80.9%
Infinite0
Infinite (%)0.0%
Mean13.222222
Minimum1
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size974.0 B
2024-03-15T11:04:00.067387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q38
95-th percentile64.5
Maximum90
Range89
Interquartile range (IQR)7

Descriptive statistics

Standard deviation24.419268
Coefficient of variation (CV)1.8468354
Kurtosis5.8010656
Mean13.222222
Median Absolute Deviation (MAD)2
Skewness2.4802986
Sum238
Variance596.30065
MonotonicityNot monotonic
2024-03-15T11:04:00.397307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 7
 
7.4%
3 3
 
3.2%
4 2
 
2.1%
34 1
 
1.1%
60 1
 
1.1%
16 1
 
1.1%
90 1
 
1.1%
9 1
 
1.1%
5 1
 
1.1%
(Missing) 76
80.9%
ValueCountFrequency (%)
1 7
7.4%
3 3
3.2%
4 2
 
2.1%
5 1
 
1.1%
9 1
 
1.1%
16 1
 
1.1%
34 1
 
1.1%
60 1
 
1.1%
90 1
 
1.1%
ValueCountFrequency (%)
90 1
 
1.1%
60 1
 
1.1%
34 1
 
1.1%
16 1
 
1.1%
9 1
 
1.1%
5 1
 
1.1%
4 2
 
2.1%
3 3
3.2%
1 7
7.4%

비검기구수
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size880.0 B
2
23 
1
20 
13 
3
6 
7
5 
Other values (15)
27 

Length

Max length4
Median length1
Mean length1.2340426
Min length1

Unique

Unique8 ?
Unique (%)8.5%

Sample

1st row
2nd row13
3rd row
4th row38
5th row

Common Values

ValueCountFrequency (%)
2 23
24.5%
1 20
21.3%
13
13.8%
3 6
 
6.4%
7 5
 
5.3%
4 4
 
4.3%
<NA> 4
 
4.3%
8 3
 
3.2%
5 2
 
2.1%
6 2
 
2.1%
Other values (10) 12
12.8%

Length

2024-03-15T11:04:00.878124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 23
28.4%
1 20
24.7%
3 6
 
7.4%
7 5
 
6.2%
4 4
 
4.9%
na 4
 
4.9%
8 3
 
3.7%
10 2
 
2.5%
9 2
 
2.5%
6 2
 
2.5%
Other values (9) 10
12.3%

비고
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size880.0 B
<NA>
74 
19 
휴업중
 
1

Length

Max length4
Median length4
Mean length3.3829787
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 74
78.7%
19
 
20.2%
휴업중 1
 
1.1%

Length

2024-03-15T11:04:01.288391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:04:01.643921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 74
98.7%
휴업중 1
 
1.3%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size880.0 B
관광총괄과
94 

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 94
100.0%

Length

2024-03-15T11:04:02.124913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:04:02.385516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광총괄과 94
100.0%

공개여부
Boolean

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size222.0 B
True
94 
ValueCountFrequency (%)
True 94
100.0%
2024-03-15T11:04:02.576231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

작성일
Date

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size880.0 B
Minimum2018-12-31 00:00:00
Maximum2018-12-31 00:00:00
2024-03-15T11:04:02.891434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:04:03.287194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size880.0 B
1년
94 

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 94
100.0%

Length

2024-03-15T11:04:03.676119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:04:04.013088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 94
100.0%

Interactions

2024-03-15T11:03:47.535753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:03:47.048419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:03:47.806613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:03:47.286448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T11:04:04.215347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명시설명도로명주소대표자전화번호검사기구수비검기구수비고
순번1.0000.8040.8621.0000.9381.0000.0740.6570.000
시군명0.8041.0000.9841.0000.8041.0000.4520.0000.271
시설명0.8620.9841.0001.0000.9881.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
대표자0.9380.8040.9881.0001.0001.0001.0000.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
검사기구수0.0740.4521.0001.0001.0001.0001.0000.8821.000
비검기구수0.6570.0001.0001.0000.0001.0000.8821.0001.000
비고0.0000.2711.0001.0001.0001.0001.0001.0001.000
2024-03-15T11:04:04.755157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고시군명비검기구수
비고1.0000.0000.850
시군명0.0001.0000.000
비검기구수0.8500.0001.000
2024-03-15T11:04:05.076932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번검사기구수시군명비검기구수비고
순번1.000-0.2720.4770.2910.000
검사기구수-0.2721.0000.0000.7740.961
시군명0.4770.0001.0000.0000.000
비검기구수0.2910.7740.0001.0000.850
비고0.0000.9610.0000.8501.000

Missing values

2024-03-15T11:03:48.334195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T11:03:48.991783image/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.
2024-03-15T11:03:49.430843image/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

순번시군명시설명도로명주소대표자전화번호검사기구수비검기구수비고자료출처공개여부작성일갱신주기
01전주시전주 노리존전주시 완산구 전주객사3길 34시*진<NA>1관광총괄과Y2018-12-311년
12전주시전주 드림랜드전주시 덕진구 덕진동1가 산 36-8김*종063-275-49003413<NA>관광총괄과Y2018-12-311년
23전주시전주한옥레일바이크전주시 덕진구 동부대로 420, 아중역권*현, 권*기<NA>60<NA>관광총괄과Y2018-12-311년
34군산시금강랜드군산시 성산면 철새로 53소*숙063-453-15251638휴업중관광총괄과Y2018-12-311년
45군산시군산 야외수영장군산시 해망로 546-10군산시장<NA>3관광총괄과Y2018-12-311년
56익산시익산 놀리터 디스코팡팡익산시 무왕로9길 3윤*순<NA>1관광총괄과Y2018-12-311년
67정읍시칠보물테마유원지정읍시 칠보면 칠보산로 1555정읍시장<NA>1관광총괄과Y2018-12-311년
78남원시남원랜드남원시 양림길 53-13(어현동)오*태063-632-60709011관광총괄과Y2018-12-311년
89김제시모악랜드김제시 금산면 금산리 79-10최*환063-548-44019관광총괄과Y2018-12-311년
910김제시오투아일랜드김제시 화동길 112이*범1800-52664관광총괄과Y2018-12-311년
순번시군명시설명도로명주소대표자전화번호검사기구수비검기구수비고자료출처공개여부작성일갱신주기
8485무주군야구연습장무주군 설천면 만선로 186임*구<NA><NA>1<NA>관광총괄과Y2018-12-311년
8586무주군태권슬라이딩무주군 설천면 무설로 1482장*훈<NA><NA><NA><NA>관광총괄과Y2018-12-311년
8687장수군장수방화동 캠핑장장수군 번암면 사암리 64-1번지김*남<NA><NA>2<NA>관광총괄과Y2018-12-311년
8788장수군강마루펜션장수군 장수읍 송천리 1808-1번지이*새<NA><NA>3<NA>관광총괄과Y2018-12-311년
8889임실군버블방방임실군 임실읍 운수로 19이*희<NA><NA>2<NA>관광총괄과Y2018-12-311년
8990순창군순창군장류사업소순창군 순창읍 민속마을길 61-59김*건<NA><NA>1<NA>관광총괄과Y2018-12-311년
9091고창군점프노리 키즈카페 고창점고창군 고창읍 월곡6길 12, 1층조*영<NA><NA>2<NA>관광총괄과Y2018-12-311년
9192고창군플레이방&블록고창군 고창읍 중앙로 232, 5층오*순<NA><NA>3<NA>관광총괄과Y2018-12-311년
9293부안군줄포만갯벌 생태공원부안군 줄포면 생태공원로 38부안군수<NA><NA>2<NA>관광총괄과Y2018-12-311년
9394부안군돌개영농조합법인부안군 진서면 구룡댐길 65박*우<NA><NA>1<NA>관광총괄과Y2018-12-311년