Overview

Dataset statistics

Number of variables6
Number of observations262
Missing cells46
Missing cells (%)2.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.7 KiB
Average record size in memory49.5 B

Variable types

Numeric1
Text5

Dataset

Description담배 소매업소 상호, 주소, 전화번호 등
Author전라북도 고창군
URLhttps://www.data.go.kr/data/15021280/fileData.do

Alerts

업소전화번호 has 46 (17.6%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-13 00:51:53.414358
Analysis finished2023-12-13 00:51:53.942191
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct262
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.5
Minimum1
Maximum262
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-13T09:51:54.211626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.05
Q166.25
median131.5
Q3196.75
95-th percentile248.95
Maximum262
Range261
Interquartile range (IQR)130.5

Descriptive statistics

Standard deviation75.777085
Coefficient of variation (CV)0.5762516
Kurtosis-1.2
Mean131.5
Median Absolute Deviation (MAD)65.5
Skewness0
Sum34453
Variance5742.1667
MonotonicityStrictly increasing
2023-12-13T09:51:54.315667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
166 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
172 1
 
0.4%
173 1
 
0.4%
174 1
 
0.4%
175 1
 
0.4%
Other values (252) 252
96.2%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
262 1
0.4%
261 1
0.4%
260 1
0.4%
259 1
0.4%
258 1
0.4%
257 1
0.4%
256 1
0.4%
255 1
0.4%
254 1
0.4%
253 1
0.4%

대표자명
Text

Distinct250
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T09:51:54.599260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length3
Mean length3.370229
Min length2

Characters and Unicode

Total characters883
Distinct characters176
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

Unique239 ?
Unique (%)91.2%

Sample

1st row김현주
2nd row김화영
3rd row김영례
4th row이막동
5th row조옥순
ValueCountFrequency (%)
선운산농협 3
 
1.1%
국군복지단 2
 
0.8%
유청자 2
 
0.8%
박래현 2
 
0.8%
김진갑 2
 
0.8%
광주지원본부 2
 
0.8%
오양환 2
 
0.8%
오종남 2
 
0.8%
고창농업협동조합 2
 
0.8%
이동헌 2
 
0.8%
Other values (242) 244
92.1%
2023-12-13T09:51:54.974647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 66
 
7.5%
이 39
 
4.4%
순 32
 
3.6%
영 24
 
2.7%
정 23
 
2.6%
조 18
 
2.0%
수 17
 
1.9%
성 17
 
1.9%
박 16
 
1.8%
자 16
 
1.8%
Other values (166) 615
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 877
99.3%
Space Separator 3
 
0.3%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 66
 
7.5%
이 39
 
4.4%
순 32
 
3.6%
영 24
 
2.7%
정 23
 
2.6%
조 18
 
2.1%
수 17
 
1.9%
성 17
 
1.9%
박 16
 
1.8%
자 16
 
1.8%
Other values (162) 609
69.4%
Space Separator
ValueCountFrequency (%)
3
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 878
99.4%
Common 5
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 66
 
7.5%
이 39
 
4.4%
순 32
 
3.6%
영 24
 
2.7%
정 23
 
2.6%
조 18
 
2.1%
수 17
 
1.9%
성 17
 
1.9%
박 16
 
1.8%
자 16
 
1.8%
Other values (163) 610
69.5%
Common
ValueCountFrequency (%)
3
60.0%
( 1
 
20.0%
) 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 877
99.3%
ASCII 5
 
0.6%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 66
 
7.5%
이 39
 
4.4%
순 32
 
3.6%
영 24
 
2.7%
정 23
 
2.6%
조 18
 
2.1%
수 17
 
1.9%
성 17
 
1.9%
박 16
 
1.8%
자 16
 
1.8%
Other values (162) 609
69.4%
ASCII
ValueCountFrequency (%)
3
60.0%
( 1
 
20.0%
) 1
 
20.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

업소명
Text

Distinct207
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T09:51:55.162995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length5.2709924
Min length1

Characters and Unicode

Total characters1381
Distinct characters246
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

Unique202 ?
Unique (%)77.1%

Sample

1st row롤로 코리아 고창점
2nd row씨유고창월곡점
3rd row혜성슈퍼
4th row고창특산품
5th row씨유고창상하점
ValueCountFrequency (%)
하나로마트 4
 
1.6%
씨유 3
 
1.2%
세븐일레븐 3
 
1.2%
gs25 3
 
1.2%
대성할인마트 2
 
0.8%
고수슈퍼 2
 
0.8%
미니스톱 2
 
0.8%
마트 2
 
0.8%
고창농협 2
 
0.8%
화신슈퍼 2
 
0.8%
Other values (221) 221
89.8%
2023-12-13T09:51:55.442879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
88
 
6.4%
고 54
 
3.9%
마 45
 
3.3%
퍼 44
 
3.2%
창 43
 
3.1%
트 43
 
3.1%
점 42
 
3.0%
슈 40
 
2.9%
회 27
 
2.0%
농 26
 
1.9%
Other values (236) 929
67.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1229
89.0%
Space Separator 88
 
6.4%
Uppercase Letter 22
 
1.6%
Decimal Number 18
 
1.3%
Close Punctuation 10
 
0.7%
Open Punctuation 10
 
0.7%
Lowercase Letter 2
 
0.1%
Dash Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 54
 
4.4%
마 45
 
3.7%
퍼 44
 
3.6%
창 43
 
3.5%
트 43
 
3.5%
점 42
 
3.4%
슈 40
 
3.3%
회 27
 
2.2%
농 26
 
2.1%
상 26
 
2.1%
Other values (213) 839
68.3%
Uppercase Letter
ValueCountFrequency (%)
G 6
27.3%
S 4
18.2%
N 2
 
9.1%
C 2
 
9.1%
U 2
 
9.1%
D 1
 
4.5%
E 1
 
4.5%
T 1
 
4.5%
A 1
 
4.5%
P 1
 
4.5%
Decimal Number
ValueCountFrequency (%)
2 8
44.4%
5 4
22.2%
4 3
 
16.7%
1 2
 
11.1%
9 1
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
o 1
50.0%
Space Separator
ValueCountFrequency (%)
88
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1229
89.0%
Common 128
 
9.3%
Latin 24
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 54
 
4.4%
마 45
 
3.7%
퍼 44
 
3.6%
창 43
 
3.5%
트 43
 
3.5%
점 42
 
3.4%
슈 40
 
3.3%
회 27
 
2.2%
농 26
 
2.1%
상 26
 
2.1%
Other values (213) 839
68.3%
Latin
ValueCountFrequency (%)
G 6
25.0%
S 4
16.7%
N 2
 
8.3%
C 2
 
8.3%
U 2
 
8.3%
k 1
 
4.2%
o 1
 
4.2%
D 1
 
4.2%
E 1
 
4.2%
T 1
 
4.2%
Other values (3) 3
12.5%
Common
ValueCountFrequency (%)
88
68.8%
) 10
 
7.8%
( 10
 
7.8%
2 8
 
6.2%
5 4
 
3.1%
4 3
 
2.3%
1 2
 
1.6%
- 1
 
0.8%
+ 1
 
0.8%
9 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1229
89.0%
ASCII 152
 
11.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
88
57.9%
) 10
 
6.6%
( 10
 
6.6%
2 8
 
5.3%
G 6
 
3.9%
S 4
 
2.6%
5 4
 
2.6%
4 3
 
2.0%
1 2
 
1.3%
N 2
 
1.3%
Other values (13) 15
 
9.9%
Hangul
ValueCountFrequency (%)
고 54
 
4.4%
마 45
 
3.7%
퍼 44
 
3.6%
창 43
 
3.5%
트 43
 
3.5%
점 42
 
3.4%
슈 40
 
3.3%
회 27
 
2.2%
농 26
 
2.1%
상 26
 
2.1%
Other values (213) 839
68.3%

업소도로명주소
Text

Distinct184
Distinct (%)70.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T09:51:55.734015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length32
Mean length15.396947
Min length1

Characters and Unicode

Total characters4034
Distinct characters149
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

Unique181 ?
Unique (%)69.1%

Sample

1st row전라북도 고창군 고창읍 중앙로 210
2nd row전라북도 고창군 고창읍 중앙로 321
3rd row전라북도 고창군 해리면 동호로 346 (혜성슈퍼.혜성약방)
4th row전라북도 고창군 고창읍 중거리당산로 155
5th row전라북도 고창군 상하면 진암구시포로 15
ValueCountFrequency (%)
전라북도 185
19.7%
고창군 185
19.7%
고창읍 78
 
8.3%
중앙로 18
 
1.9%
해리면 15
 
1.6%
대산면 14
 
1.5%
상하면 13
 
1.4%
흥덕면 11
 
1.2%
부안면 9
 
1.0%
아산면 8
 
0.9%
Other values (266) 403
42.9%
2023-12-13T09:51:56.145179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
831
20.6%
고 272
 
6.7%
창 263
 
6.5%
전 191
 
4.7%
도 186
 
4.6%
북 186
 
4.6%
라 185
 
4.6%
군 185
 
4.6%
로 122
 
3.0%
1 113
 
2.8%
Other values (139) 1500
37.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2612
64.7%
Space Separator 831
 
20.6%
Decimal Number 530
 
13.1%
Dash Punctuation 36
 
0.9%
Close Punctuation 11
 
0.3%
Open Punctuation 11
 
0.3%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 272
 
10.4%
창 263
 
10.1%
전 191
 
7.3%
도 186
 
7.1%
북 186
 
7.1%
라 185
 
7.1%
군 185
 
7.1%
로 122
 
4.7%
면 107
 
4.1%
읍 80
 
3.1%
Other values (124) 835
32.0%
Decimal Number
ValueCountFrequency (%)
1 113
21.3%
2 95
17.9%
3 60
11.3%
7 42
 
7.9%
4 41
 
7.7%
6 40
 
7.5%
5 39
 
7.4%
9 35
 
6.6%
8 34
 
6.4%
0 31
 
5.8%
Space Separator
ValueCountFrequency (%)
831
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2612
64.7%
Common 1422
35.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 272
 
10.4%
창 263
 
10.1%
전 191
 
7.3%
도 186
 
7.1%
북 186
 
7.1%
라 185
 
7.1%
군 185
 
7.1%
로 122
 
4.7%
면 107
 
4.1%
읍 80
 
3.1%
Other values (124) 835
32.0%
Common
ValueCountFrequency (%)
831
58.4%
1 113
 
7.9%
2 95
 
6.7%
3 60
 
4.2%
7 42
 
3.0%
4 41
 
2.9%
6 40
 
2.8%
5 39
 
2.7%
- 36
 
2.5%
9 35
 
2.5%
Other values (5) 90
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2612
64.7%
ASCII 1422
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
831
58.4%
1 113
 
7.9%
2 95
 
6.7%
3 60
 
4.2%
7 42
 
3.0%
4 41
 
2.9%
6 40
 
2.8%
5 39
 
2.7%
- 36
 
2.5%
9 35
 
2.5%
Other values (5) 90
 
6.3%
Hangul
ValueCountFrequency (%)
고 272
 
10.4%
창 263
 
10.1%
전 191
 
7.3%
도 186
 
7.1%
북 186
 
7.1%
라 185
 
7.1%
군 185
 
7.1%
로 122
 
4.7%
면 107
 
4.1%
읍 80
 
3.1%
Other values (124) 835
32.0%

업소전화번호
Text

MISSING 

Distinct169
Distinct (%)78.2%
Missing46
Missing (%)17.6%
Memory size2.2 KiB
2023-12-13T09:51:56.354745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length9.8611111
Min length1

Characters and Unicode

Total characters2130
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique162 ?
Unique (%)75.0%

Sample

1st row063-563-6512
2nd row063-562-3021
3rd row063-563-1220
4th row063-563-6031
5th row063-561-0031
ValueCountFrequency (%)
063-563-6512 2
 
1.1%
061-390-4901 2
 
1.1%
063-564-6754 2
 
1.1%
063-561-6323 2
 
1.1%
063-564-3969 2
 
1.1%
063-562-5166 2
 
1.1%
063-562-1542 1
 
0.6%
063-561-3377 1
 
0.6%
063-564-5398 1
 
0.6%
063-562-1759 1
 
0.6%
Other values (158) 158
90.8%
2023-12-13T09:51:56.668405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 413
19.4%
- 348
16.3%
3 288
13.5%
0 261
12.3%
5 244
11.5%
2 118
 
5.5%
1 110
 
5.2%
4 103
 
4.8%
9 73
 
3.4%
8 68
 
3.2%
Other values (2) 104
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1740
81.7%
Dash Punctuation 348
 
16.3%
Space Separator 42
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 413
23.7%
3 288
16.6%
0 261
15.0%
5 244
14.0%
2 118
 
6.8%
1 110
 
6.3%
4 103
 
5.9%
9 73
 
4.2%
8 68
 
3.9%
7 62
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 348
100.0%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2130
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 413
19.4%
- 348
16.3%
3 288
13.5%
0 261
12.3%
5 244
11.5%
2 118
 
5.5%
1 110
 
5.2%
4 103
 
4.8%
9 73
 
3.4%
8 68
 
3.2%
Other values (2) 104
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 413
19.4%
- 348
16.3%
3 288
13.5%
0 261
12.3%
5 244
11.5%
2 118
 
5.5%
1 110
 
5.2%
4 103
 
4.8%
9 73
 
3.4%
8 68
 
3.2%
Other values (2) 104
 
4.9%

지정일자
Text

Distinct235
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-13T09:51:56.891856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters2620
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

Unique212 ?
Unique (%)80.9%

Sample

1st row2017-11-21
2nd row2017-11-15
3rd row2017-10-17
4th row2017-09-28
5th row2017-09-28
ValueCountFrequency (%)
1974-07-01 5
 
1.9%
1980-12-20 3
 
1.1%
2006-11-30 2
 
0.8%
2002-05-21 2
 
0.8%
2007-03-14 2
 
0.8%
2014-09-19 2
 
0.8%
1998-11-20 2
 
0.8%
1998-11-28 2
 
0.8%
2011-04-06 2
 
0.8%
2011-03-31 2
 
0.8%
Other values (225) 238
90.8%
2023-12-13T09:51:57.206364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 635
24.2%
- 524
20.0%
1 424
16.2%
2 365
13.9%
9 173
 
6.6%
8 98
 
3.7%
7 88
 
3.4%
5 81
 
3.1%
6 79
 
3.0%
3 79
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2096
80.0%
Dash Punctuation 524
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 635
30.3%
1 424
20.2%
2 365
17.4%
9 173
 
8.3%
8 98
 
4.7%
7 88
 
4.2%
5 81
 
3.9%
6 79
 
3.8%
3 79
 
3.8%
4 74
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 524
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2620
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 635
24.2%
- 524
20.0%
1 424
16.2%
2 365
13.9%
9 173
 
6.6%
8 98
 
3.7%
7 88
 
3.4%
5 81
 
3.1%
6 79
 
3.0%
3 79
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2620
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 635
24.2%
- 524
20.0%
1 424
16.2%
2 365
13.9%
9 173
 
6.6%
8 98
 
3.7%
7 88
 
3.4%
5 81
 
3.1%
6 79
 
3.0%
3 79
 
3.0%

Interactions

2023-12-13T09:51:53.756024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T09:51:53.836930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:51:53.911386image/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

번호대표자명업소명업소도로명주소업소전화번호지정일자
01김현주롤로 코리아 고창점전라북도 고창군 고창읍 중앙로 210<NA>2017-11-21
12김화영씨유고창월곡점전라북도 고창군 고창읍 중앙로 321<NA>2017-11-15
23김영례혜성슈퍼전라북도 고창군 해리면 동호로 346 (혜성슈퍼.혜성약방)063-563-65122017-10-17
34이막동고창특산품전라북도 고창군 고창읍 중거리당산로 155<NA>2017-09-28
45조옥순씨유고창상하점전라북도 고창군 상하면 진암구시포로 15<NA>2017-09-28
56유길임대농휴게실전라북도 고창군 흥덕면 부안로 269-7<NA>2017-08-25
67김백수성내마트전라북도 고창군 성내면 시기1길 49063-562-30212017-07-13
78김경태풀하우스편의점전라북도 고창군 상하면 구시포안길 29-3<NA>2017-07-05
89김다유월곡슈퍼전라북도 고창군 고창읍 월곡6길 10<NA>2017-04-10
910최순자복흥슈퍼전라북도 고창군 성송면 학천로 801063-563-12202017-02-24
번호대표자명업소명업소도로명주소업소전화번호지정일자
252253윤옥중063-561-08482000-07-06
253254강두만1975-05-22
254255손정성1975-03-20
255256설금순1975-05-12
256257이금례1975-05-15
257258유순님학원문구사063-564-32051975-02-07
258259윤향자1974-07-01
259260황학영1974-07-01
260261김형진063-562-90481974-07-01
261262김수훈1974-07-01