Overview

Dataset statistics

Number of variables5
Number of observations227
Missing cells5
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.2 KiB
Average record size in memory41.6 B

Variable types

Numeric1
Text3
DateTime1

Dataset

Description전북특별자치도 전주시의 나들가게를 제공하며 매장명, 도로명주소, 지번주소, 위도, 경도, 연락처 등을 제공합니다.
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=12&menuCd=DOM_000000103007001000&pListTypeStr=&pId=15020605

Alerts

데이터기준일자 has constant value ""Constant
소재지연락번호 has 5 (2.2%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-20 22:51:00.896423
Analysis finished2024-04-20 22:51:01.706920
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct227
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114
Minimum1
Maximum227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-21T07:51:01.839840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.3
Q157.5
median114
Q3170.5
95-th percentile215.7
Maximum227
Range226
Interquartile range (IQR)113

Descriptive statistics

Standard deviation65.673435
Coefficient of variation (CV)0.57608276
Kurtosis-1.2
Mean114
Median Absolute Deviation (MAD)57
Skewness0
Sum25878
Variance4313
MonotonicityStrictly increasing
2024-04-21T07:51:02.081621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
144 1
 
0.4%
146 1
 
0.4%
147 1
 
0.4%
148 1
 
0.4%
149 1
 
0.4%
150 1
 
0.4%
151 1
 
0.4%
152 1
 
0.4%
153 1
 
0.4%
Other values (217) 217
95.6%
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 (%)
227 1
0.4%
226 1
0.4%
225 1
0.4%
224 1
0.4%
223 1
0.4%
222 1
0.4%
221 1
0.4%
220 1
0.4%
219 1
0.4%
218 1
0.4%

매장명
Text

Distinct216
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-21T07:51:02.992091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length5.0176211
Min length3

Characters and Unicode

Total characters1139
Distinct characters229
Distinct categories5 ?
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 (%)90.3%

Sample

1st rowe편한마트
2nd rowK마트
3rd row거성복지매장
4th row거시기마트
5th row경기전슈퍼
ValueCountFrequency (%)
코사마트 9
 
3.7%
정마트 4
 
1.6%
애플마트 3
 
1.2%
굿모닝마트 3
 
1.2%
명성마트 2
 
0.8%
현대마트 2
 
0.8%
레드마트25 2
 
0.8%
더조은슈퍼 2
 
0.8%
프랜드마트 2
 
0.8%
다마트 2
 
0.8%
Other values (208) 214
87.3%
2024-04-21T07:51:04.356792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 151
 
13.3%
트 147
 
12.9%
퍼 51
 
4.5%
슈 48
 
4.2%
34
 
3.0%
점 29
 
2.5%
우 16
 
1.4%
성 16
 
1.4%
이 15
 
1.3%
동 13
 
1.1%
Other values (219) 619
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1094
96.0%
Space Separator 34
 
3.0%
Decimal Number 7
 
0.6%
Uppercase Letter 3
 
0.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 151
 
13.8%
트 147
 
13.4%
퍼 51
 
4.7%
슈 48
 
4.4%
점 29
 
2.7%
우 16
 
1.5%
성 16
 
1.5%
이 15
 
1.4%
동 13
 
1.2%
의 13
 
1.2%
Other values (211) 595
54.4%
Decimal Number
ValueCountFrequency (%)
2 4
57.1%
5 2
28.6%
4 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
V 1
33.3%
I 1
33.3%
K 1
33.3%
Space Separator
ValueCountFrequency (%)
34
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1094
96.0%
Common 41
 
3.6%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 151
 
13.8%
트 147
 
13.4%
퍼 51
 
4.7%
슈 48
 
4.4%
점 29
 
2.7%
우 16
 
1.5%
성 16
 
1.5%
이 15
 
1.4%
동 13
 
1.2%
의 13
 
1.2%
Other values (211) 595
54.4%
Common
ValueCountFrequency (%)
34
82.9%
2 4
 
9.8%
5 2
 
4.9%
4 1
 
2.4%
Latin
ValueCountFrequency (%)
e 1
25.0%
V 1
25.0%
I 1
25.0%
K 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1094
96.0%
ASCII 45
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 151
 
13.8%
트 147
 
13.4%
퍼 51
 
4.7%
슈 48
 
4.4%
점 29
 
2.7%
우 16
 
1.5%
성 16
 
1.5%
이 15
 
1.4%
동 13
 
1.2%
의 13
 
1.2%
Other values (211) 595
54.4%
ASCII
ValueCountFrequency (%)
34
75.6%
2 4
 
8.9%
5 2
 
4.4%
e 1
 
2.2%
4 1
 
2.2%
V 1
 
2.2%
I 1
 
2.2%
K 1
 
2.2%

소재지도로명주소
Text

Distinct224
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-21T07:51:05.754011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length32
Mean length28.629956
Min length23

Characters and Unicode

Total characters6499
Distinct characters169
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique221 ?
Unique (%)97.4%

Sample

1st row전라북도 전주시 완산구 효동2길 33-138 (효자동1가)
2nd row전라북도 전주시 덕진구 한배미3길 17 (인후동1가)
3rd row전라북도 전주시 완산구 선너머로 40 (중화산동2가)
4th row전라북도 전주시 완산구 선너머4길 9-2 (중화산동1가)
5th row전라북도 전주시 완산구 태조로 45 (교동)
ValueCountFrequency (%)
전라북도 227
 
16.7%
전주시 226
 
16.6%
완산구 120
 
8.8%
덕진구 107
 
7.9%
삼천동1가 20
 
1.5%
금암동 20
 
1.5%
인후동1가 18
 
1.3%
효자동1가 16
 
1.2%
서신동 12
 
0.9%
효자동3가 10
 
0.7%
Other values (340) 585
43.0%
2024-04-21T07:51:07.547258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1285
19.8%
전 466
 
7.2%
1 241
 
3.7%
동 238
 
3.7%
북 236
 
3.6%
구 231
 
3.6%
라 230
 
3.5%
주 230
 
3.5%
도 228
 
3.5%
시 226
 
3.5%
Other values (159) 2888
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3925
60.4%
Space Separator 1285
 
19.8%
Decimal Number 802
 
12.3%
Open Punctuation 226
 
3.5%
Close Punctuation 225
 
3.5%
Dash Punctuation 36
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 466
 
11.9%
동 238
 
6.1%
북 236
 
6.0%
구 231
 
5.9%
라 230
 
5.9%
주 230
 
5.9%
도 228
 
5.8%
시 226
 
5.8%
가 160
 
4.1%
산 148
 
3.8%
Other values (145) 1532
39.0%
Decimal Number
ValueCountFrequency (%)
1 241
30.0%
2 142
17.7%
3 94
 
11.7%
4 68
 
8.5%
5 49
 
6.1%
7 47
 
5.9%
9 44
 
5.5%
6 43
 
5.4%
0 42
 
5.2%
8 32
 
4.0%
Space Separator
ValueCountFrequency (%)
1285
100.0%
Open Punctuation
ValueCountFrequency (%)
( 226
100.0%
Close Punctuation
ValueCountFrequency (%)
) 225
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3925
60.4%
Common 2574
39.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 466
 
11.9%
동 238
 
6.1%
북 236
 
6.0%
구 231
 
5.9%
라 230
 
5.9%
주 230
 
5.9%
도 228
 
5.8%
시 226
 
5.8%
가 160
 
4.1%
산 148
 
3.8%
Other values (145) 1532
39.0%
Common
ValueCountFrequency (%)
1285
49.9%
1 241
 
9.4%
( 226
 
8.8%
) 225
 
8.7%
2 142
 
5.5%
3 94
 
3.7%
4 68
 
2.6%
5 49
 
1.9%
7 47
 
1.8%
9 44
 
1.7%
Other values (4) 153
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3925
60.4%
ASCII 2574
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1285
49.9%
1 241
 
9.4%
( 226
 
8.8%
) 225
 
8.7%
2 142
 
5.5%
3 94
 
3.7%
4 68
 
2.6%
5 49
 
1.9%
7 47
 
1.8%
9 44
 
1.7%
Other values (4) 153
 
5.9%
Hangul
ValueCountFrequency (%)
전 466
 
11.9%
동 238
 
6.1%
북 236
 
6.0%
구 231
 
5.9%
라 230
 
5.9%
주 230
 
5.9%
도 228
 
5.8%
시 226
 
5.8%
가 160
 
4.1%
산 148
 
3.8%
Other values (145) 1532
39.0%

소재지연락번호
Text

MISSING 

Distinct222
Distinct (%)100.0%
Missing5
Missing (%)2.2%
Memory size1.9 KiB
2024-04-21T07:51:08.638928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.022523
Min length12

Characters and Unicode

Total characters2669
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

Unique222 ?
Unique (%)100.0%

Sample

1st row063-229-7755
2nd row063-245-6584
3rd row063-225-1566
4th row063-288-9153
5th row063-288-2425
ValueCountFrequency (%)
063-245-7088 1
 
0.5%
063-242-7078 1
 
0.5%
063-278-2500 1
 
0.5%
063-227-0072 1
 
0.5%
063-228-3630 1
 
0.5%
063-246-3360 1
 
0.5%
063-274-4890 1
 
0.5%
063-225-1518 1
 
0.5%
063-276-1550 1
 
0.5%
063-226-1758 1
 
0.5%
Other values (212) 212
95.5%
2024-04-21T07:51:09.904121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 444
16.6%
2 382
14.3%
3 342
12.8%
0 331
12.4%
6 307
11.5%
5 186
7.0%
4 167
 
6.3%
7 157
 
5.9%
1 135
 
5.1%
8 133
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2225
83.4%
Dash Punctuation 444
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 382
17.2%
3 342
15.4%
0 331
14.9%
6 307
13.8%
5 186
8.4%
4 167
7.5%
7 157
7.1%
1 135
 
6.1%
8 133
 
6.0%
9 85
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 444
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2669
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 444
16.6%
2 382
14.3%
3 342
12.8%
0 331
12.4%
6 307
11.5%
5 186
7.0%
4 167
 
6.3%
7 157
 
5.9%
1 135
 
5.1%
8 133
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2669
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 444
16.6%
2 382
14.3%
3 342
12.8%
0 331
12.4%
6 307
11.5%
5 186
7.0%
4 167
 
6.3%
7 157
 
5.9%
1 135
 
5.1%
8 133
 
5.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2019-08-30 00:00:00
Maximum2019-08-30 00:00:00
2024-04-21T07:51:10.249811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T07:51:10.543428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-21T07:51:01.302648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-04-21T07:51:01.475107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T07:51:01.641018image/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

연번매장명소재지도로명주소소재지연락번호데이터기준일자
01e편한마트전라북도 전주시 완산구 효동2길 33-138 (효자동1가)063-229-77552019-08-30
12K마트전라북도 전주시 덕진구 한배미3길 17 (인후동1가)063-245-65842019-08-30
23거성복지매장전라북도 전주시 완산구 선너머로 40 (중화산동2가)063-225-15662019-08-30
34거시기마트전라북도 전주시 완산구 선너머4길 9-2 (중화산동1가)063-288-91532019-08-30
45경기전슈퍼전라북도 전주시 완산구 태조로 45 (교동)063-288-24252019-08-30
56골드마트전라북도 전주시 완산구 안터3길 18 (서신동)063-908-78152019-08-30
67광명슈퍼전라북도 전주시 덕진구 모래내3길 14-4 (인후동2가)063-252-37852019-08-30
78광진하이퍼마트전라북도 전주시 완산구 선너머로 16 (중화산동2가)063-224-35012019-08-30
89국민청과슈퍼전라북도 전주시 덕진구 매봉5길 28 (금암동)063-251-90822019-08-30
910굴다리상회전라북도 전주시 완산구 최명희길 7 (풍남동3가)063-286-48002019-08-30
연번매장명소재지도로명주소소재지연락번호데이터기준일자
217218호반슈퍼전라북도 전주시 덕진구 호반6길 12 (덕진동2가)063-252-87002019-08-30
218219홈마트전라북도 전주시 완산구 안터2길 28 (서신동)063-221-75312019-08-30
219220환영슈퍼전라북도 전주시 완산구 전라감영로 27 (다가동1가)063-231-51112019-08-30
220221황궁슈퍼마트전라북도 전주시 완산구 장승배기로 398 (동서학동)063-285-78342019-08-30
221222황금편의점전라북도 전주시 덕진구 산정2길 8 (산정동)063-245-46182019-08-30
222223황방쇼핑전라북도 전주시 완산구 서신천변4길 2 (서신동)063-252-82242019-08-30
223224황소마트전라북도 전주시 덕진구 도당산로 8 (우아동3가)063-211-81162019-08-30
224225황제마트전라북도 전주시 완산구 백제대로 159 (효자동1가)063-221-14042019-08-30
225226효궁농수산물슈퍼전라북도 전주시 덕진구 매봉로 17-1 (금암동)063-254-56322019-08-30
226227효문알뜰쇼핑전라북도 전주시 완산구 고사평로 21 (삼천동1가)063-225-61802019-08-30