Overview

Dataset statistics

Number of variables6
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory55.7 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description보문단지 기타상가 현황(숙박업체, 요식업체, 유원시설을 제외한 시설)
Author경상북도관광공사
URLhttps://www.data.go.kr/data/15044403/fileData.do

Alerts

업종 has constant value ""Constant
연번 has unique valuesUnique
상호 has unique valuesUnique
소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:02:03.713907
Analysis finished2023-12-12 23:02:04.135988
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-13T08:02:04.189046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2023-12-13T08:02:04.287357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
23 1
 
4.3%
22 1
 
4.3%
21 1
 
4.3%
20 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
16 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
6 1
4.3%
7 1
4.3%
8 1
4.3%
9 1
4.3%
10 1
4.3%
ValueCountFrequency (%)
23 1
4.3%
22 1
4.3%
21 1
4.3%
20 1
4.3%
19 1
4.3%
18 1
4.3%
17 1
4.3%
16 1
4.3%
15 1
4.3%
14 1
4.3%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
기타상가
23 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기타상가 23
100.0%

Length

2023-12-13T08:02:04.382568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:02:04.731220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타상가 23
100.0%

상호
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T08:02:04.874753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.7826087
Min length4

Characters and Unicode

Total characters133
Distinct characters75
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row한국대중음악박물관
2nd row동화상사
3rd row태국왓포마사지
4th row보문현대상가
5th row수목할인마트
ValueCountFrequency (%)
한국대중음악박물관 1
 
4.3%
부킹가요궁 1
 
4.3%
경북광유 1
 
4.3%
수상공연장매점 1
 
4.3%
매실동산매점 1
 
4.3%
서라벌광장매점 1
 
4.3%
보문콜로세움 1
 
4.3%
골프샷존 1
 
4.3%
중국전통마사지 1
 
4.3%
천년가요주점 1
 
4.3%
Other values (13) 13
56.5%
2023-12-13T08:02:05.155914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 7
 
5.3%
보 5
 
3.8%
점 5
 
3.8%
가 5
 
3.8%
트 4
 
3.0%
문 4
 
3.0%
매 4
 
3.0%
사 3
 
2.3%
방 3
 
2.3%
주 3
 
2.3%
Other values (65) 90
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 7
 
5.3%
보 5
 
3.8%
점 5
 
3.8%
가 5
 
3.8%
트 4
 
3.0%
문 4
 
3.0%
매 4
 
3.0%
사 3
 
2.3%
방 3
 
2.3%
주 3
 
2.3%
Other values (65) 90
67.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 7
 
5.3%
보 5
 
3.8%
점 5
 
3.8%
가 5
 
3.8%
트 4
 
3.0%
문 4
 
3.0%
매 4
 
3.0%
사 3
 
2.3%
방 3
 
2.3%
주 3
 
2.3%
Other values (65) 90
67.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 7
 
5.3%
보 5
 
3.8%
점 5
 
3.8%
가 5
 
3.8%
트 4
 
3.0%
문 4
 
3.0%
매 4
 
3.0%
사 3
 
2.3%
방 3
 
2.3%
주 3
 
2.3%
Other values (65) 90
67.7%

우편번호
Categorical

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
38116
17 
38118
3 
38117
3 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
38116 17
73.9%
38118 3
 
13.0%
38117 3
 
13.0%

Length

2023-12-13T08:02:05.260870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:02:05.339616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
38116 17
73.9%
38118 3
 
13.0%
38117 3
 
13.0%

소재지(도로명)
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T08:02:05.482451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length28
Mean length18.434783
Min length13

Characters and Unicode

Total characters424
Distinct characters44
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

Unique23 ?
Unique (%)100.0%

Sample

1st row경주시 엑스포로 9(신평동)
2nd row경주시 보문로 402-31, 07호(보문레이크타운)
3rd row경주시 보문로 402-31, 302호(보문레이크타운)
4th row경주시 보문로 368-5(신평동)
5th row경주시 엑스포로64(천군동)
ValueCountFrequency (%)
경주시 23
32.4%
천북남로 10
14.1%
보문로 8
 
11.3%
402-31 2
 
2.8%
경감로 2
 
2.8%
132-16(북군동 1
 
1.4%
27(서광113호 1
 
1.4%
27(서광203호 1
 
1.4%
27(서광301호 1
 
1.4%
27(서광b01호 1
 
1.4%
Other values (21) 21
29.6%
2023-12-13T08:02:05.837603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
 
11.3%
경 25
 
5.9%
시 23
 
5.4%
주 23
 
5.4%
로 22
 
5.2%
( 20
 
4.7%
2 20
 
4.7%
) 20
 
4.7%
1 19
 
4.5%
0 14
 
3.3%
Other values (34) 190
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 223
52.6%
Decimal Number 103
24.3%
Space Separator 48
 
11.3%
Open Punctuation 20
 
4.7%
Close Punctuation 20
 
4.7%
Dash Punctuation 7
 
1.7%
Other Punctuation 2
 
0.5%
Uppercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 25
11.2%
시 23
 
10.3%
주 23
 
10.3%
로 22
 
9.9%
천 13
 
5.8%
호 13
 
5.8%
문 11
 
4.9%
보 11
 
4.9%
북 11
 
4.9%
남 10
 
4.5%
Other values (18) 61
27.4%
Decimal Number
ValueCountFrequency (%)
2 20
19.4%
1 19
18.4%
0 14
13.6%
7 13
12.6%
3 11
10.7%
4 7
 
6.8%
5 7
 
6.8%
6 5
 
4.9%
8 5
 
4.9%
9 2
 
1.9%
Space Separator
ValueCountFrequency (%)
48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 223
52.6%
Common 200
47.2%
Latin 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 25
11.2%
시 23
 
10.3%
주 23
 
10.3%
로 22
 
9.9%
천 13
 
5.8%
호 13
 
5.8%
문 11
 
4.9%
보 11
 
4.9%
북 11
 
4.9%
남 10
 
4.5%
Other values (18) 61
27.4%
Common
ValueCountFrequency (%)
48
24.0%
( 20
10.0%
2 20
10.0%
) 20
10.0%
1 19
 
9.5%
0 14
 
7.0%
7 13
 
6.5%
3 11
 
5.5%
4 7
 
3.5%
- 7
 
3.5%
Other values (5) 21
10.5%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 223
52.6%
ASCII 201
47.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48
23.9%
( 20
10.0%
2 20
10.0%
) 20
10.0%
1 19
 
9.5%
0 14
 
7.0%
7 13
 
6.5%
3 11
 
5.5%
4 7
 
3.5%
- 7
 
3.5%
Other values (6) 22
10.9%
Hangul
ValueCountFrequency (%)
경 25
11.2%
시 23
 
10.3%
주 23
 
10.3%
로 22
 
9.9%
천 13
 
5.8%
호 13
 
5.8%
문 11
 
4.9%
보 11
 
4.9%
북 11
 
4.9%
남 10
 
4.5%
Other values (18) 61
27.4%

전화번호(지역번호 054)
Text

Distinct12
Distinct (%)52.2%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-13T08:02:05.974237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length5
Mean length6.4347826
Min length5

Characters and Unicode

Total characters148
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)47.8%

Sample

1st row776-5502
2nd row개인휴대폰
3rd row774-4222
4th row745-3439
5th row748-8107
ValueCountFrequency (%)
개인휴대폰 12
52.2%
776-5502 1
 
4.3%
774-4222 1
 
4.3%
745-3439 1
 
4.3%
748-8107 1
 
4.3%
745-0345 1
 
4.3%
745-0025 1
 
4.3%
748-0555 1
 
4.3%
772-8100 1
 
4.3%
777-7555 1
 
4.3%
Other values (2) 2
 
8.7%
2023-12-13T08:02:06.233103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 18
12.2%
5 16
10.8%
개 12
8.1%
인 12
8.1%
휴 12
8.1%
대 12
8.1%
폰 12
8.1%
- 11
7.4%
4 11
7.4%
0 10
6.8%
Other values (6) 22
14.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
52.0%
Other Letter 60
40.5%
Dash Punctuation 11
 
7.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 18
23.4%
5 16
20.8%
4 11
14.3%
0 10
13.0%
2 6
 
7.8%
6 4
 
5.2%
8 4
 
5.2%
3 3
 
3.9%
1 3
 
3.9%
9 2
 
2.6%
Other Letter
ValueCountFrequency (%)
개 12
20.0%
인 12
20.0%
휴 12
20.0%
대 12
20.0%
폰 12
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88
59.5%
Hangul 60
40.5%

Most frequent character per script

Common
ValueCountFrequency (%)
7 18
20.5%
5 16
18.2%
- 11
12.5%
4 11
12.5%
0 10
11.4%
2 6
 
6.8%
6 4
 
4.5%
8 4
 
4.5%
3 3
 
3.4%
1 3
 
3.4%
Hangul
ValueCountFrequency (%)
개 12
20.0%
인 12
20.0%
휴 12
20.0%
대 12
20.0%
폰 12
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
59.5%
Hangul 60
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 18
20.5%
5 16
18.2%
- 11
12.5%
4 11
12.5%
0 10
11.4%
2 6
 
6.8%
6 4
 
4.5%
8 4
 
4.5%
3 3
 
3.4%
1 3
 
3.4%
Hangul
ValueCountFrequency (%)
개 12
20.0%
인 12
20.0%
휴 12
20.0%
대 12
20.0%
폰 12
20.0%

Interactions

2023-12-13T08:02:03.894612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:02:06.328991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호우편번호소재지(도로명)전화번호(지역번호 054)
연번1.0001.0000.5461.0000.573
상호1.0001.0001.0001.0001.000
우편번호0.5461.0001.0001.0000.435
소재지(도로명)1.0001.0001.0001.0001.000
전화번호(지역번호 054)0.5731.0000.4351.0001.000
2023-12-13T08:02:06.422167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호
연번1.0000.286
우편번호0.2861.000

Missing values

2023-12-13T08:02:03.993302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:02:04.097783image/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)
01기타상가한국대중음악박물관38116경주시 엑스포로 9(신평동)776-5502
12기타상가동화상사38116경주시 보문로 402-31, 07호(보문레이크타운)개인휴대폰
23기타상가태국왓포마사지38116경주시 보문로 402-31, 302호(보문레이크타운)774-4222
34기타상가보문현대상가38116경주시 보문로 368-5(신평동)745-3439
45기타상가수목할인마트38116경주시 엑스포로64(천군동)748-8107
56기타상가보문마트38118경주시 보문로 579(보문프라자 105호)개인휴대폰
67기타상가천년마트38116경주시 보문로 368(신평동)745-0345
78기타상가필가요주점38116경주시 천북남로 27(서광02호)개인휴대폰
89기타상가짬안마시술소38116경주시 천북남로 27(서광05호)개인휴대폰
910기타상가물레방아마트38116경주시 천북남로 27(서광104호)745-0025
연번업종상호우편번호소재지(도로명)전화번호(지역번호 054)
1314기타상가물레방아노래방38116경주시 천북남로 27(서광113호)개인휴대폰
1415기타상가천년가요주점38116경주시 천북남로 27(서광203호)개인휴대폰
1516기타상가중국전통마사지38116경주시 천북남로 27(서광301호)개인휴대폰
1617기타상가골프샷존38116경주시 천북남로 27(서광B01호)772-8100
1718기타상가보문콜로세움38117경주시 보문로 132-16(북군동)777-7555
1819기타상가서라벌광장매점38117경주시 보문로 280-31개인휴대폰
1920기타상가매실동산매점38116경주시 보문로 402-24개인휴대폰
2021기타상가수상공연장매점38117경주시 신평동 485-1개인휴대폰
2122기타상가경북광유38118경주시 경감로 585(천군동)745-6651
2223기타상가천군주유소38118경주시 경감로 631(천군동)745-9600