Overview

Dataset statistics

Number of variables6
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory52.9 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description보문단지 요식업체 현황
Author경상북도관광공사
URLhttps://www.data.go.kr/data/15044401/fileData.do

Alerts

업종 has constant value ""Constant
연번 has unique valuesUnique
상호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:40:37.305239
Analysis finished2023-12-12 11:40:38.386543
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.5
Minimum1
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-12T20:40:38.534213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.25
Q112.25
median23.5
Q334.75
95-th percentile43.75
Maximum46
Range45
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation13.422618
Coefficient of variation (CV)0.57117522
Kurtosis-1.2
Mean23.5
Median Absolute Deviation (MAD)11.5
Skewness0
Sum1081
Variance180.16667
MonotonicityStrictly increasing
2023-12-12T20:40:38.789744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 1
 
2.2%
36 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
34 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
46 1
2.2%
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
요식업
46 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
요식업 46
100.0%

Length

2023-12-12T20:40:39.020449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:40:39.174396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
요식업 46
100.0%

상호
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-12T20:40:39.520655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length5.5217391
Min length2

Characters and Unicode

Total characters254
Distinct characters138
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row맥도날드보문점
2nd row미래상가
3rd row에디슨소리역사관
4th row롯데리아
5th row운수대통가든
ValueCountFrequency (%)
맥도날드보문점 1
 
2.1%
솔미가 1
 
2.1%
경주보문호수점 1
 
2.1%
맛있는밥상 1
 
2.1%
부산원조왕돈까스 1
 
2.1%
도미노피자보문점 1
 
2.1%
장우동 1
 
2.1%
김밥천국 1
 
2.1%
카페베네 1
 
2.1%
전통손칼국수 1
 
2.1%
Other values (37) 37
78.7%
2023-12-12T20:40:40.137848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
문 11
 
4.3%
보 10
 
3.9%
점 8
 
3.1%
가 7
 
2.8%
스 7
 
2.8%
미 5
 
2.0%
수 5
 
2.0%
아 4
 
1.6%
타 4
 
1.6%
주 4
 
1.6%
Other values (128) 189
74.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 253
99.6%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
문 11
 
4.3%
보 10
 
4.0%
점 8
 
3.2%
가 7
 
2.8%
스 7
 
2.8%
미 5
 
2.0%
수 5
 
2.0%
아 4
 
1.6%
타 4
 
1.6%
주 4
 
1.6%
Other values (127) 188
74.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 253
99.6%
Common 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
문 11
 
4.3%
보 10
 
4.0%
점 8
 
3.2%
가 7
 
2.8%
스 7
 
2.8%
미 5
 
2.0%
수 5
 
2.0%
아 4
 
1.6%
타 4
 
1.6%
주 4
 
1.6%
Other values (127) 188
74.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 253
99.6%
ASCII 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
문 11
 
4.3%
보 10
 
4.0%
점 8
 
3.2%
가 7
 
2.8%
스 7
 
2.8%
미 5
 
2.0%
수 5
 
2.0%
아 4
 
1.6%
타 4
 
1.6%
주 4
 
1.6%
Other values (127) 188
74.3%
ASCII
ValueCountFrequency (%)
1
100.0%

우편번호
Categorical

Distinct3
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size500.0 B
38116
22 
38118
19 
38117
5 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row38116
2nd row38116
3rd row38118
4th row38118
5th row38117

Common Values

ValueCountFrequency (%)
38116 22
47.8%
38118 19
41.3%
38117 5
 
10.9%

Length

2023-12-12T20:40:40.375573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:40:40.566570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
38116 22
47.8%
38118 19
41.3%
38117 5
 
10.9%

소재지(도로명)
Text

Distinct45
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-12T20:40:40.888701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length23
Mean length20.173913
Min length13

Characters and Unicode

Total characters928
Distinct characters47
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

Unique44 ?
Unique (%)95.7%

Sample

1st row경주시 보문로 441(신평동)
2nd row경주시 보문로 424-11(신평동)
3rd row경주시 보문로 529(천군동)
4th row경주시 보문로 535(천군동)
5th row경주시 보문로 132-5(북군동)
ValueCountFrequency (%)
경주시 46
30.1%
보문로 31
20.3%
402-31 8
 
5.2%
579(보문프라자 8
 
5.2%
천북남로 6
 
3.9%
경감로 3
 
2.0%
엑스포로 3
 
2.0%
엑스포로64(천군동 2
 
1.3%
545-9(천군동 1
 
0.7%
29-5(신평동 1
 
0.7%
Other values (44) 44
28.8%
2023-12-12T20:40:41.537199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
107
 
11.5%
경 49
 
5.3%
보 47
 
5.1%
문 47
 
5.1%
주 46
 
5.0%
시 46
 
5.0%
로 45
 
4.8%
) 45
 
4.8%
( 45
 
4.8%
1 38
 
4.1%
Other values (37) 413
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 491
52.9%
Decimal Number 214
23.1%
Space Separator 107
 
11.5%
Close Punctuation 45
 
4.8%
Open Punctuation 45
 
4.8%
Dash Punctuation 18
 
1.9%
Other Punctuation 8
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 49
 
10.0%
보 47
 
9.6%
문 47
 
9.6%
주 46
 
9.4%
시 46
 
9.4%
로 45
 
9.2%
동 26
 
5.3%
호 21
 
4.3%
천 20
 
4.1%
군 19
 
3.9%
Other values (22) 125
25.5%
Decimal Number
ValueCountFrequency (%)
1 38
17.8%
0 31
14.5%
2 30
14.0%
5 27
12.6%
4 21
9.8%
3 20
9.3%
7 16
7.5%
9 13
 
6.1%
6 12
 
5.6%
8 6
 
2.8%
Space Separator
ValueCountFrequency (%)
107
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 491
52.9%
Common 437
47.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 49
 
10.0%
보 47
 
9.6%
문 47
 
9.6%
주 46
 
9.4%
시 46
 
9.4%
로 45
 
9.2%
동 26
 
5.3%
호 21
 
4.3%
천 20
 
4.1%
군 19
 
3.9%
Other values (22) 125
25.5%
Common
ValueCountFrequency (%)
107
24.5%
) 45
10.3%
( 45
10.3%
1 38
 
8.7%
0 31
 
7.1%
2 30
 
6.9%
5 27
 
6.2%
4 21
 
4.8%
3 20
 
4.6%
- 18
 
4.1%
Other values (5) 55
12.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 491
52.9%
ASCII 437
47.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
107
24.5%
) 45
10.3%
( 45
10.3%
1 38
 
8.7%
0 31
 
7.1%
2 30
 
6.9%
5 27
 
6.2%
4 21
 
4.8%
3 20
 
4.6%
- 18
 
4.1%
Other values (5) 55
12.6%
Hangul
ValueCountFrequency (%)
경 49
 
10.0%
보 47
 
9.6%
문 47
 
9.6%
주 46
 
9.4%
시 46
 
9.4%
로 45
 
9.2%
동 26
 
5.3%
호 21
 
4.3%
천 20
 
4.1%
군 19
 
3.9%
Other values (22) 125
25.5%

전화번호(지역번호 054)
Text

Distinct45
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-12T20:40:41.934652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length8.1086957
Min length8

Characters and Unicode

Total characters373
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

Unique44 ?
Unique (%)95.7%

Sample

1st row070-7209-0605
2nd row745-9498
3rd row748-8880
4th row745-8866
5th row745-6202
ValueCountFrequency (%)
777-2524 2
 
4.3%
070-7209-0605 1
 
2.2%
749-0039 1
 
2.2%
748-2005 1
 
2.2%
775-3082 1
 
2.2%
745-6918 1
 
2.2%
746-3554 1
 
2.2%
773-3920 1
 
2.2%
745-3010 1
 
2.2%
745-3078 1
 
2.2%
Other values (35) 35
76.1%
2023-12-12T20:40:42.515930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 76
20.4%
4 56
15.0%
- 47
12.6%
0 40
10.7%
8 40
10.7%
5 30
 
8.0%
3 20
 
5.4%
2 19
 
5.1%
6 17
 
4.6%
1 15
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 326
87.4%
Dash Punctuation 47
 
12.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 76
23.3%
4 56
17.2%
0 40
12.3%
8 40
12.3%
5 30
 
9.2%
3 20
 
6.1%
2 19
 
5.8%
6 17
 
5.2%
1 15
 
4.6%
9 13
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 373
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 76
20.4%
4 56
15.0%
- 47
12.6%
0 40
10.7%
8 40
10.7%
5 30
 
8.0%
3 20
 
5.4%
2 19
 
5.1%
6 17
 
4.6%
1 15
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 373
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 76
20.4%
4 56
15.0%
- 47
12.6%
0 40
10.7%
8 40
10.7%
5 30
 
8.0%
3 20
 
5.4%
2 19
 
5.1%
6 17
 
4.6%
1 15
 
4.0%

Interactions

2023-12-12T20:40:37.890614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:40:42.685903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호우편번호소재지(도로명)전화번호(지역번호 054)
연번1.0001.0000.4860.9311.000
상호1.0001.0001.0001.0001.000
우편번호0.4861.0001.0001.0001.000
소재지(도로명)0.9311.0001.0001.0000.996
전화번호(지역번호 054)1.0001.0001.0000.9961.000
2023-12-12T20:40:42.853130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호
연번1.0000.206
우편번호0.2061.000

Missing values

2023-12-12T20:40:38.090907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:40:38.302115image/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

연번업종상호우편번호소재지(도로명)전화번호(지역번호 054)
01요식업맥도날드보문점38116경주시 보문로 441(신평동)070-7209-0605
12요식업미래상가38116경주시 보문로 424-11(신평동)745-9498
23요식업에디슨소리역사관38118경주시 보문로 529(천군동)748-8880
34요식업롯데리아38118경주시 보문로 535(천군동)745-8866
45요식업운수대통가든38117경주시 보문로 132-5(북군동)745-6202
56요식업경주국밥38118경주시 경감로 627(천군동)748-8544
67요식업명수짬뽕짜장전문점38118경주시 경감로 633(천군동)744-9800
78요식업라몽38117경주시 보문로 132-24(북군동)745-8818
89요식업타이타닉38116경주시 보문로 368-5(신평동)748-3555
910요식업로즈가든38116경주시 보문로 402-31, 01호(보문레이크타운)742-8787
연번업종상호우편번호소재지(도로명)전화번호(지역번호 054)
3637요식업보문민속식당38116경주시 천북남로 27(서광108호)748-3200
3738요식업들안길숯불갈비38116경주시 천북남로 27(서광201호)748-7766
3839요식업아사가38116경주시 천북남로 27(신평동) 별관1호741-1218
3940요식업엄마곰탕38118경주시 보문로 545-14(천군동)774-5500
4041요식업보문한우38116경주시 신평동 220번지776-9200
4142요식업아미랑38118경주시 보문로 555(천군동)746-8818
4243요식업디쵸콜렛커피점38118경주시 경감로 579(천군동)748-3456
4344요식업경주천년한우보문점38118경주시 보문로 545-9(천군동)777-1735
4445요식업스타벅스 경주보문호수점38117경주시 보문로 132-6(북군동)741-0040
4546요식업미탐시티38118경주시 엑스포로 80(천군동)777-5701