Overview

Dataset statistics

Number of variables8
Number of observations215
Missing cells34
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.0 KiB
Average record size in memory66.6 B

Variable types

Numeric2
Categorical1
DateTime1
Text4

Dataset

Description익산시 관내 읍면동의 유흥단란주점에 대한 업종명, 인허가일자, 업소명, 도로명주소, 지번주소, 면적, 전화번호 등의 자료를 제공합니다.
Author전북특별자치도 익산시
URLhttps://www.data.go.kr/data/3079817/fileData.do

Alerts

번호 is highly overall correlated with 업종명High correlation
영업장면적 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
소재지전화 has 34 (15.8%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 13:54:55.126220
Analysis finished2024-03-14 13:54:57.288884
Duration2.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct215
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108
Minimum1
Maximum215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-14T22:54:57.500424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.7
Q154.5
median108
Q3161.5
95-th percentile204.3
Maximum215
Range214
Interquartile range (IQR)107

Descriptive statistics

Standard deviation62.209324
Coefficient of variation (CV)0.57601226
Kurtosis-1.2
Mean108
Median Absolute Deviation (MAD)54
Skewness0
Sum23220
Variance3870
MonotonicityStrictly increasing
2024-03-14T22:54:57.947740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
149 1
 
0.5%
138 1
 
0.5%
139 1
 
0.5%
140 1
 
0.5%
141 1
 
0.5%
142 1
 
0.5%
143 1
 
0.5%
144 1
 
0.5%
145 1
 
0.5%
Other values (205) 205
95.3%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
215 1
0.5%
214 1
0.5%
213 1
0.5%
212 1
0.5%
211 1
0.5%
210 1
0.5%
209 1
0.5%
208 1
0.5%
207 1
0.5%
206 1
0.5%

업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
유흥주점영업
109 
단란주점
106 

Length

Max length6
Median length6
Mean length5.0139535
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유흥주점영업 109
50.7%
단란주점 106
49.3%

Length

2024-03-14T22:54:58.386614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:54:58.732976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유흥주점영업 109
50.7%
단란주점 106
49.3%

인허가일자
Date

Distinct195
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum1976-07-07 00:00:00
Maximum2020-10-28 00:00:00
2024-03-14T22:54:59.066687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:54:59.494140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소명
Text

Distinct213
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-14T22:55:00.454335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length5.0093023
Min length1

Characters and Unicode

Total characters1077
Distinct characters283
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique212 ?
Unique (%)98.6%

Sample

1st row일프로노래타운
2nd row사랑방
3rd row신사동
4th row별천지
5th row녹원
ValueCountFrequency (%)
황진이 3
 
1.4%
꽃나비단란주점 1
 
0.5%
부송단란주점 1
 
0.5%
오로라단란주점 1
 
0.5%
케쉬단란주점 1
 
0.5%
육각수 1
 
0.5%
금상첨화단란주점 1
 
0.5%
미가단란주점 1
 
0.5%
와와단란주점 1
 
0.5%
앙코르 1
 
0.5%
Other values (203) 203
94.4%
2024-03-14T22:55:01.834732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 87
 
8.1%
점 85
 
7.9%
단 76
 
7.1%
란 75
 
7.0%
이 22
 
2.0%
래 20
 
1.9%
스 20
 
1.9%
노 19
 
1.8%
0 18
 
1.7%
타 16
 
1.5%
Other values (273) 639
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1015
94.2%
Decimal Number 36
 
3.3%
Uppercase Letter 16
 
1.5%
Open Punctuation 3
 
0.3%
Close Punctuation 3
 
0.3%
Other Punctuation 2
 
0.2%
Lowercase Letter 1
 
0.1%
Letter Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 87
 
8.6%
점 85
 
8.4%
단 76
 
7.5%
란 75
 
7.4%
이 22
 
2.2%
래 20
 
2.0%
스 20
 
2.0%
노 19
 
1.9%
타 16
 
1.6%
리 15
 
1.5%
Other values (253) 580
57.1%
Uppercase Letter
ValueCountFrequency (%)
S 2
12.5%
P 2
12.5%
A 2
12.5%
B 2
12.5%
I 1
6.2%
V 1
6.2%
C 1
6.2%
M 1
6.2%
W 1
6.2%
H 1
6.2%
Other values (2) 2
12.5%
Decimal Number
ValueCountFrequency (%)
0 18
50.0%
7 9
25.0%
8 9
25.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
j 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1015
94.2%
Common 44
 
4.1%
Latin 18
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 87
 
8.6%
점 85
 
8.4%
단 76
 
7.5%
란 75
 
7.4%
이 22
 
2.2%
래 20
 
2.0%
스 20
 
2.0%
노 19
 
1.9%
타 16
 
1.6%
리 15
 
1.5%
Other values (253) 580
57.1%
Latin
ValueCountFrequency (%)
S 2
11.1%
P 2
11.1%
A 2
11.1%
B 2
11.1%
I 1
 
5.6%
V 1
 
5.6%
C 1
 
5.6%
j 1
 
5.6%
M 1
 
5.6%
W 1
 
5.6%
Other values (4) 4
22.2%
Common
ValueCountFrequency (%)
0 18
40.9%
7 9
20.5%
8 9
20.5%
( 3
 
6.8%
) 3
 
6.8%
. 2
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1015
94.2%
ASCII 61
 
5.7%
Number Forms 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 87
 
8.6%
점 85
 
8.4%
단 76
 
7.5%
란 75
 
7.4%
이 22
 
2.2%
래 20
 
2.0%
스 20
 
2.0%
노 19
 
1.9%
타 16
 
1.6%
리 15
 
1.5%
Other values (253) 580
57.1%
ASCII
ValueCountFrequency (%)
0 18
29.5%
7 9
14.8%
8 9
14.8%
( 3
 
4.9%
) 3
 
4.9%
S 2
 
3.3%
. 2
 
3.3%
P 2
 
3.3%
A 2
 
3.3%
B 2
 
3.3%
Other values (9) 9
14.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지(도로명)
Text

Distinct208
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-14T22:55:02.645603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length24.47907
Min length17

Characters and Unicode

Total characters5263
Distinct characters94
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique202 ?
Unique (%)94.0%

Sample

1st row전북특별자치도익산시인북로2길47(인화동2가)
2nd row전북특별자치도익산시익산대로108-1(평화동)
3rd row전북특별자치도익산시익산대로8길10(평화동)
4th row전북특별자치도익산시함열읍함열로73
5th row전북특별자치도익산시중앙로22-167(중앙동3가)
ValueCountFrequency (%)
전북특별자치도익산시인북로1길13(인화동1가 3
 
1.4%
전북특별자치도익산시목천로3길7-1(인화동1가 2
 
0.9%
전북특별자치도익산시고봉로306(영등동 2
 
0.9%
전북특별자치도익산시목천로13길11(인화동2가 2
 
0.9%
전북특별자치도익산시인북로2길47(인화동2가 2
 
0.9%
전북특별자치도익산시인북로4길30(인화동2가 2
 
0.9%
전북특별자치도익산시부송로6(부송동 1
 
0.5%
전북특별자치도익산시인북로318(남중동 1
 
0.5%
전북특별자치도익산시인북로365(신동 1
 
0.5%
전북특별자치도익산시인북로4길37(인화동2가 1
 
0.5%
Other values (198) 198
92.1%
2024-03-14T22:55:03.679708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
북 268
 
5.1%
산 262
 
5.0%
1 245
 
4.7%
동 244
 
4.6%
익 243
 
4.6%
( 227
 
4.3%
) 227
 
4.3%
시 216
 
4.1%
도 215
 
4.1%
치 215
 
4.1%
Other values (84) 2901
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3762
71.5%
Decimal Number 916
 
17.4%
Open Punctuation 227
 
4.3%
Close Punctuation 227
 
4.3%
Dash Punctuation 70
 
1.3%
Other Punctuation 57
 
1.1%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
북 268
 
7.1%
산 262
 
7.0%
동 244
 
6.5%
익 243
 
6.5%
시 216
 
5.7%
도 215
 
5.7%
치 215
 
5.7%
자 215
 
5.7%
별 215
 
5.7%
특 215
 
5.7%
Other values (65) 1454
38.6%
Decimal Number
ValueCountFrequency (%)
1 245
26.7%
2 169
18.4%
3 132
14.4%
4 91
 
9.9%
7 58
 
6.3%
5 55
 
6.0%
6 48
 
5.2%
0 44
 
4.8%
8 39
 
4.3%
9 35
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
B 1
25.0%
L 1
25.0%
G 1
25.0%
J 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 56
98.2%
& 1
 
1.8%
Open Punctuation
ValueCountFrequency (%)
( 227
100.0%
Close Punctuation
ValueCountFrequency (%)
) 227
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3762
71.5%
Common 1497
 
28.4%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
북 268
 
7.1%
산 262
 
7.0%
동 244
 
6.5%
익 243
 
6.5%
시 216
 
5.7%
도 215
 
5.7%
치 215
 
5.7%
자 215
 
5.7%
별 215
 
5.7%
특 215
 
5.7%
Other values (65) 1454
38.6%
Common
ValueCountFrequency (%)
1 245
16.4%
( 227
15.2%
) 227
15.2%
2 169
11.3%
3 132
8.8%
4 91
 
6.1%
- 70
 
4.7%
7 58
 
3.9%
, 56
 
3.7%
5 55
 
3.7%
Other values (5) 167
11.2%
Latin
ValueCountFrequency (%)
B 1
25.0%
L 1
25.0%
G 1
25.0%
J 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3762
71.5%
ASCII 1501
 
28.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
북 268
 
7.1%
산 262
 
7.0%
동 244
 
6.5%
익 243
 
6.5%
시 216
 
5.7%
도 215
 
5.7%
치 215
 
5.7%
자 215
 
5.7%
별 215
 
5.7%
특 215
 
5.7%
Other values (65) 1454
38.6%
ASCII
ValueCountFrequency (%)
1 245
16.3%
( 227
15.1%
) 227
15.1%
2 169
11.3%
3 132
8.8%
4 91
 
6.1%
- 70
 
4.7%
7 58
 
3.9%
, 56
 
3.7%
5 55
 
3.7%
Other values (9) 171
11.4%

소재지(지번)
Text

Distinct210
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-14T22:55:04.469736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length20.12093
Min length15

Characters and Unicode

Total characters4326
Distinct characters78
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique205 ?
Unique (%)95.3%

Sample

1st row전북특별자치도익산시인화동2가98-11
2nd row전북특별자치도익산시평화동14-5
3rd row전북특별자치도익산시평화동17-2
4th row전북특별자치도익산시함열읍와리545-122
5th row전북특별자치도익산시중앙동3가118-25
ValueCountFrequency (%)
전북특별자치도익산시인화동2가98-11 2
 
0.9%
전북특별자치도익산시인화동1가173-4 2
 
0.9%
전북특별자치도익산시인화동2가93-8 2
 
0.9%
전북특별자치도익산시영등동829-2 2
 
0.9%
전북특별자치도익산시인화동1가175-1 2
 
0.9%
전북특별자치도익산시모현동1가261-2 1
 
0.5%
전북특별자치도익산시송학동3-32-17 1
 
0.5%
전북특별자치도익산시부송동1097-1 1
 
0.5%
전북특별자치도익산시영등동755-7 1
 
0.5%
전북특별자치도익산시모현동1가262-7270-3 1
 
0.5%
Other values (200) 200
93.0%
2024-03-14T22:55:05.496909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 268
 
6.2%
산 232
 
5.4%
도 222
 
5.1%
동 221
 
5.1%
시 216
 
5.0%
전 215
 
5.0%
특 215
 
5.0%
별 215
 
5.0%
자 215
 
5.0%
치 215
 
5.0%
Other values (68) 2092
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2998
69.3%
Decimal Number 1052
 
24.3%
Dash Punctuation 214
 
4.9%
Close Punctuation 25
 
0.6%
Open Punctuation 25
 
0.6%
Other Punctuation 8
 
0.2%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 232
 
7.7%
도 222
 
7.4%
동 221
 
7.4%
시 216
 
7.2%
전 215
 
7.2%
특 215
 
7.2%
별 215
 
7.2%
자 215
 
7.2%
치 215
 
7.2%
익 215
 
7.2%
Other values (49) 817
27.3%
Decimal Number
ValueCountFrequency (%)
1 268
25.5%
2 152
14.4%
3 112
10.6%
7 92
 
8.7%
8 84
 
8.0%
5 77
 
7.3%
4 69
 
6.6%
9 68
 
6.5%
6 66
 
6.3%
0 64
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
G 1
25.0%
L 1
25.0%
B 1
25.0%
J 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 7
87.5%
& 1
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 214
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2998
69.3%
Common 1324
30.6%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 232
 
7.7%
도 222
 
7.4%
동 221
 
7.4%
시 216
 
7.2%
전 215
 
7.2%
특 215
 
7.2%
별 215
 
7.2%
자 215
 
7.2%
치 215
 
7.2%
익 215
 
7.2%
Other values (49) 817
27.3%
Common
ValueCountFrequency (%)
1 268
20.2%
- 214
16.2%
2 152
11.5%
3 112
8.5%
7 92
 
6.9%
8 84
 
6.3%
5 77
 
5.8%
4 69
 
5.2%
9 68
 
5.1%
6 66
 
5.0%
Other values (5) 122
9.2%
Latin
ValueCountFrequency (%)
G 1
25.0%
L 1
25.0%
B 1
25.0%
J 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2998
69.3%
ASCII 1328
30.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 268
20.2%
- 214
16.1%
2 152
11.4%
3 112
8.4%
7 92
 
6.9%
8 84
 
6.3%
5 77
 
5.8%
4 69
 
5.2%
9 68
 
5.1%
6 66
 
5.0%
Other values (9) 126
9.5%
Hangul
ValueCountFrequency (%)
산 232
 
7.7%
도 222
 
7.4%
동 221
 
7.4%
시 216
 
7.2%
전 215
 
7.2%
특 215
 
7.2%
별 215
 
7.2%
자 215
 
7.2%
치 215
 
7.2%
익 215
 
7.2%
Other values (49) 817
27.3%

영업장면적
Real number (ℝ)

HIGH CORRELATION 

Distinct211
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean141.9167
Minimum0
Maximum660.73
Zeros1
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-14T22:55:05.903625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile46.882
Q193.15
median117.13
Q3161.76
95-th percentile308.7
Maximum660.73
Range660.73
Interquartile range (IQR)68.61

Descriptive statistics

Standard deviation89.692593
Coefficient of variation (CV)0.63200874
Kurtosis8.3279835
Mean141.9167
Median Absolute Deviation (MAD)29.67
Skewness2.3732184
Sum30512.09
Variance8044.7613
MonotonicityNot monotonic
2024-03-14T22:55:06.342741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84.0 2
 
0.9%
137.55 2
 
0.9%
80.25 2
 
0.9%
143.29 2
 
0.9%
101.14 1
 
0.5%
151.96 1
 
0.5%
92.38 1
 
0.5%
48.0 1
 
0.5%
110.35 1
 
0.5%
78.79 1
 
0.5%
Other values (201) 201
93.5%
ValueCountFrequency (%)
0.0 1
0.5%
22.08 1
0.5%
28.0 1
0.5%
32.0 1
0.5%
35.77 1
0.5%
36.45 1
0.5%
38.78 1
0.5%
39.0 1
0.5%
39.92 1
0.5%
43.87 1
0.5%
ValueCountFrequency (%)
660.73 1
0.5%
531.18 1
0.5%
516.09 1
0.5%
512.78 1
0.5%
379.04 1
0.5%
359.1 1
0.5%
353.46 1
0.5%
344.2 1
0.5%
315.1 1
0.5%
314.08 1
0.5%

소재지전화
Text

MISSING 

Distinct181
Distinct (%)100.0%
Missing34
Missing (%)15.8%
Memory size1.8 KiB
2024-03-14T22:55:07.347275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.016575
Min length12

Characters and Unicode

Total characters2175
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

Unique181 ?
Unique (%)100.0%

Sample

1st row063-842-7782
2nd row063-857-1864
3rd row063-842-0324
4th row063-841-9418
5th row063-855-2398
ValueCountFrequency (%)
063-852-2437 1
 
0.6%
063-836-7707 1
 
0.6%
063-854-2740 1
 
0.6%
063-856-8300 1
 
0.6%
063-854-6026 1
 
0.6%
063-852-6405 1
 
0.6%
063-856-2357 1
 
0.6%
063-832-2287 1
 
0.6%
063-832-2339 1
 
0.6%
063-857-0316 1
 
0.6%
Other values (171) 171
94.5%
2024-03-14T22:55:08.831517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 362
16.6%
3 303
13.9%
0 293
13.5%
6 265
12.2%
8 264
12.1%
5 189
8.7%
2 128
 
5.9%
4 127
 
5.8%
1 92
 
4.2%
7 90
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1813
83.4%
Dash Punctuation 362
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 303
16.7%
0 293
16.2%
6 265
14.6%
8 264
14.6%
5 189
10.4%
2 128
7.1%
4 127
7.0%
1 92
 
5.1%
7 90
 
5.0%
9 62
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 362
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2175
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 362
16.6%
3 303
13.9%
0 293
13.5%
6 265
12.2%
8 264
12.1%
5 189
8.7%
2 128
 
5.9%
4 127
 
5.8%
1 92
 
4.2%
7 90
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2175
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 362
16.6%
3 303
13.9%
0 293
13.5%
6 265
12.2%
8 264
12.1%
5 189
8.7%
2 128
 
5.9%
4 127
 
5.8%
1 92
 
4.2%
7 90
 
4.1%

Interactions

2024-03-14T22:54:56.116764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:54:55.643260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:54:56.353331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T22:54:55.871738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T22:55:09.093972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업종명영업장면적
번호1.0001.0000.479
업종명1.0001.0000.530
영업장면적0.4790.5301.000
2024-03-14T22:55:09.333302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호영업장면적업종명
번호1.000-0.2100.972
영업장면적-0.2101.0000.523
업종명0.9720.5231.000

Missing values

2024-03-14T22:54:56.708838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:54:57.127194image/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

번호업종명인허가일자업소명소재지(도로명)소재지(지번)영업장면적소재지전화
01유흥주점영업1976-07-07일프로노래타운전북특별자치도익산시인북로2길47(인화동2가)전북특별자치도익산시인화동2가98-11101.14063-842-7782
12유흥주점영업1978-06-22사랑방전북특별자치도익산시익산대로108-1(평화동)전북특별자치도익산시평화동14-50.0063-857-1864
23유흥주점영업1980-08-13신사동전북특별자치도익산시익산대로8길10(평화동)전북특별자치도익산시평화동17-228.0063-842-0324
34유흥주점영업1981-12-28별천지전북특별자치도익산시함열읍함열로73전북특별자치도익산시함열읍와리545-12256.95<NA>
45유흥주점영업1981-10-19녹원전북특별자치도익산시중앙로22-167(중앙동3가)전북특별자치도익산시중앙동3가118-2555.6063-841-9418
56유흥주점영업1982-06-05자매전북특별자치도익산시익산대로142-21(중앙동1가)전북특별자치도익산시중앙동1가42-839.0063-855-2398
67유흥주점영업1983-09-06탱크나이트클럽전북특별자치도익산시익산대로173(창인동1가)전북특별자치도익산시창인동1가9-3315.1063-855-8442
78유흥주점영업1983-02-10계곡음악홀전북특별자치도익산시동서로18길7-3(남중동)전북특별자치도익산시남중동375-262118.3063-852-7704
89유흥주점영업1984-11-23그린전북특별자치도익산시중앙로5(중앙동1가)전북특별자치도익산시중앙동1가16-1266.3063-852-8383
910유흥주점영업1984-12-11소나기전북특별자치도익산시인북로4길15(인화동1가)전북특별자치도익산시인화동1가186-11119.94063-851-3681
번호업종명인허가일자업소명소재지(도로명)소재지(지번)영업장면적소재지전화
205206단란주점2009-09-15휴단란주점전북특별자치도익산시하나로10길69(부송동,,제1동(3층))전북특별자치도익산시부송동1096-2,제1동(3층)38.78<NA>
206207단란주점2009-09-30럭셔리단란주점전북특별자치도익산시하나로10길70-1(부송동,(3층))전북특별자치도익산시부송동1097-3(3층)100.95<NA>
207208단란주점2010-06-08술한잔인생한입전북특별자치도익산시중앙로22-82(중앙동1가,(1층))전북특별자치도익산시중앙동1가45-1(1층)69.89<NA>
208209단란주점2010-10-13도쿄단란주점전북특별자치도익산시하나로10길76-4(부송동,(2층))전북특별자치도익산시부송동1097-4(2층)97.98063-834-5656
209210단란주점2012-07-09해와달단란주점전북특별자치도익산시금마면미륵사지로1길42전북특별자치도익산시금마면동고도리816-5105.05<NA>
210211단란주점2013-05-02크리스탈전북특별자치도익산시하나로10길68,3층(부송동)전북특별자치도익산시부송동1097-193.77063-833-0090
211212단란주점2017-03-17VIP단란주점전북특별자치도익산시하나로10길75-3,2층(부송동,우즈빌딩)전북특별자치도익산시부송동1096-4우주빌딩98.08<NA>
212213단란주점2018-10-12정드림단란주점전북특별자치도익산시중앙로15-4(중앙동1가)전북특별자치도익산시중앙동1가61344.2<NA>
213214단란주점2020-01-15한밤라이브단란주점전북특별자치도익산시무왕로23길32,4층401호(부송동)전북특별자치도익산시부송동1090-24층401호115.21<NA>
214215단란주점2020-10-28무쏘단란주점전북특별자치도익산시선화로10길75,무쏘단란주점(지하)(모현동1가)전북특별자치도익산시모현동1가239-27무쏘단란주점(지하)165.64<NA>