Overview

Dataset statistics

Number of variables6
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory54.3 B

Variable types

Numeric1
Categorical3
Text2

Dataset

Description보문단지 입주 기타상가 리스트
Author경상북도관광공사
URLhttps://www.data.go.kr/data/15044404/fileData.do

Alerts

업종 has constant value ""Constant
우편번호 is highly overall correlated with 전화번호(지역번호 054)High correlation
전화번호(지역번호 054) is highly overall correlated with 우편번호High correlation
연번 has unique valuesUnique
상호 has unique valuesUnique
소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:33:08.134132
Analysis finished2023-12-12 15:33:08.745300
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T00:33:08.829443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q17
median13
Q319
95-th percentile23.8
Maximum25
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.3598007
Coefficient of variation (CV)0.56613852
Kurtosis-1.2
Mean13
Median Absolute Deviation (MAD)6
Skewness0
Sum325
Variance54.166667
MonotonicityStrictly increasing
2023-12-13T00:33:08.994375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 1
 
4.0%
2 1
 
4.0%
25 1
 
4.0%
24 1
 
4.0%
23 1
 
4.0%
22 1
 
4.0%
21 1
 
4.0%
20 1
 
4.0%
19 1
 
4.0%
18 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1 1
4.0%
2 1
4.0%
3 1
4.0%
4 1
4.0%
5 1
4.0%
6 1
4.0%
7 1
4.0%
8 1
4.0%
9 1
4.0%
10 1
4.0%
ValueCountFrequency (%)
25 1
4.0%
24 1
4.0%
23 1
4.0%
22 1
4.0%
21 1
4.0%
20 1
4.0%
19 1
4.0%
18 1
4.0%
17 1
4.0%
16 1
4.0%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
기타상가
25 

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 25
100.0%

Length

2023-12-13T00:33:09.133792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:33:09.247772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타상가 25
100.0%

상호
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-13T00:33:09.453929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.72
Min length3

Characters and Unicode

Total characters143
Distinct characters83
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row아리원
2nd row동화상사
3rd row태국왓포마사지
4th row보문현대상가
5th row에덴파크GS25
ValueCountFrequency (%)
아리원 1
 
4.0%
스핑노래궁 1
 
4.0%
경북광유 1
 
4.0%
수상공연장매점 1
 
4.0%
매실동산매점 1
 
4.0%
서라벌광장매점 1
 
4.0%
보문콜로세움 1
 
4.0%
중국전통마사지 1
 
4.0%
천년가요주점 1
 
4.0%
bhc치킨 1
 
4.0%
Other values (15) 15
60.0%
2023-12-13T00:33:09.896449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 7
 
4.9%
점 6
 
4.2%
가 6
 
4.2%
보 5
 
3.5%
트 4
 
2.8%
매 4
 
2.8%
요 4
 
2.8%
주 4
 
2.8%
문 4
 
2.8%
천 3
 
2.1%
Other values (73) 96
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 136
95.1%
Uppercase Letter 5
 
3.5%
Decimal Number 2
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 7
 
5.1%
점 6
 
4.4%
가 6
 
4.4%
보 5
 
3.7%
트 4
 
2.9%
매 4
 
2.9%
요 4
 
2.9%
주 4
 
2.9%
문 4
 
2.9%
천 3
 
2.2%
Other values (66) 89
65.4%
Uppercase Letter
ValueCountFrequency (%)
B 1
20.0%
H 1
20.0%
C 1
20.0%
S 1
20.0%
G 1
20.0%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
2 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 136
95.1%
Latin 5
 
3.5%
Common 2
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 7
 
5.1%
점 6
 
4.4%
가 6
 
4.4%
보 5
 
3.7%
트 4
 
2.9%
매 4
 
2.9%
요 4
 
2.9%
주 4
 
2.9%
문 4
 
2.9%
천 3
 
2.2%
Other values (66) 89
65.4%
Latin
ValueCountFrequency (%)
B 1
20.0%
H 1
20.0%
C 1
20.0%
S 1
20.0%
G 1
20.0%
Common
ValueCountFrequency (%)
5 1
50.0%
2 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136
95.1%
ASCII 7
 
4.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 7
 
5.1%
점 6
 
4.4%
가 6
 
4.4%
보 5
 
3.7%
트 4
 
2.9%
매 4
 
2.9%
요 4
 
2.9%
주 4
 
2.9%
문 4
 
2.9%
천 3
 
2.2%
Other values (66) 89
65.4%
ASCII
ValueCountFrequency (%)
B 1
14.3%
H 1
14.3%
C 1
14.3%
5 1
14.3%
2 1
14.3%
S 1
14.3%
G 1
14.3%

우편번호
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
780-290
20 
780-270
3 
780-280
 
2

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row780-290
2nd row780-290
3rd row780-290
4th row780-290
5th row780-290

Common Values

ValueCountFrequency (%)
780-290 20
80.0%
780-270 3
 
12.0%
780-280 2
 
8.0%

Length

2023-12-13T00:33:10.047143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:33:10.185079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
780-290 20
80.0%
780-270 3
 
12.0%
780-280 2
 
8.0%

소재지(도로명)
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-13T00:33:10.396091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length28
Mean length18.32
Min length13

Characters and Unicode

Total characters458
Distinct characters43
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

Unique25 ?
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 보문로 409(신평동)
ValueCountFrequency (%)
경주시 25
32.5%
천북남로 11
14.3%
보문로 9
 
11.7%
402-31 2
 
2.6%
경감로 2
 
2.6%
27(서광301호 1
 
1.3%
27(서광112호 1
 
1.3%
27(서광113호 1
 
1.3%
27(서광115호 1
 
1.3%
27(서광203호 1
 
1.3%
Other values (23) 23
29.9%
2023-12-13T00:33:10.819446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
 
11.4%
경 27
 
5.9%
시 25
 
5.5%
주 25
 
5.5%
로 24
 
5.2%
( 22
 
4.8%
) 22
 
4.8%
2 21
 
4.6%
1 20
 
4.4%
0 15
 
3.3%
Other values (33) 205
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 242
52.8%
Decimal Number 111
24.2%
Space Separator 52
 
11.4%
Open Punctuation 22
 
4.8%
Close Punctuation 22
 
4.8%
Dash Punctuation 7
 
1.5%
Other Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 27
11.2%
시 25
 
10.3%
주 25
 
10.3%
로 24
 
9.9%
호 14
 
5.8%
천 14
 
5.8%
보 12
 
5.0%
문 12
 
5.0%
북 12
 
5.0%
광 11
 
4.5%
Other values (18) 66
27.3%
Decimal Number
ValueCountFrequency (%)
2 21
18.9%
1 20
18.0%
0 15
13.5%
7 14
12.6%
3 11
9.9%
5 8
 
7.2%
4 8
 
7.2%
8 6
 
5.4%
6 5
 
4.5%
9 3
 
2.7%
Space Separator
ValueCountFrequency (%)
52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 242
52.8%
Common 216
47.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 27
11.2%
시 25
 
10.3%
주 25
 
10.3%
로 24
 
9.9%
호 14
 
5.8%
천 14
 
5.8%
보 12
 
5.0%
문 12
 
5.0%
북 12
 
5.0%
광 11
 
4.5%
Other values (18) 66
27.3%
Common
ValueCountFrequency (%)
52
24.1%
( 22
10.2%
) 22
10.2%
2 21
9.7%
1 20
 
9.3%
0 15
 
6.9%
7 14
 
6.5%
3 11
 
5.1%
5 8
 
3.7%
4 8
 
3.7%
Other values (5) 23
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 242
52.8%
ASCII 216
47.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
24.1%
( 22
10.2%
) 22
10.2%
2 21
9.7%
1 20
 
9.3%
0 15
 
6.9%
7 14
 
6.5%
3 11
 
5.1%
5 8
 
3.7%
4 8
 
3.7%
Other values (5) 23
10.6%
Hangul
ValueCountFrequency (%)
경 27
11.2%
시 25
 
10.3%
주 25
 
10.3%
로 24
 
9.9%
호 14
 
5.8%
천 14
 
5.8%
보 12
 
5.0%
문 12
 
5.0%
북 12
 
5.0%
광 11
 
4.5%
Other values (18) 66
27.3%

전화번호(지역번호 054)
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
개인휴대폰
14 
748-3332
 
1
774-4222
 
1
745-3439
 
1
748-8107
 
1
Other values (7)
7 

Length

Max length8
Median length5
Mean length6.32
Min length5

Unique

Unique11 ?
Unique (%)44.0%

Sample

1st row748-3332
2nd row개인휴대폰
3rd row774-4222
4th row745-3439
5th row개인휴대폰

Common Values

ValueCountFrequency (%)
개인휴대폰 14
56.0%
748-3332 1
 
4.0%
774-4222 1
 
4.0%
745-3439 1
 
4.0%
748-8107 1
 
4.0%
745-0345 1
 
4.0%
745-0081 1
 
4.0%
745-0025 1
 
4.0%
748-0555 1
 
4.0%
777-7555 1
 
4.0%
Other values (2) 2
 
8.0%

Length

2023-12-13T00:33:11.001332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
개인휴대폰 14
56.0%
748-3332 1
 
4.0%
774-4222 1
 
4.0%
745-3439 1
 
4.0%
748-8107 1
 
4.0%
745-0345 1
 
4.0%
745-0081 1
 
4.0%
745-0025 1
 
4.0%
748-0555 1
 
4.0%
777-7555 1
 
4.0%
Other values (2) 2
 
8.0%

Interactions

2023-12-13T00:33:08.437527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:33:11.100670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호우편번호소재지(도로명)전화번호(지역번호 054)
연번1.0001.0000.3601.0000.000
상호1.0001.0001.0001.0001.000
우편번호0.3601.0001.0001.0000.978
소재지(도로명)1.0001.0001.0001.0001.000
전화번호(지역번호 054)0.0001.0000.9781.0001.000
2023-12-13T00:33:11.221285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전화번호(지역번호 054)우편번호
전화번호(지역번호 054)1.0000.630
우편번호0.6301.000
2023-12-13T00:33:11.327736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호전화번호(지역번호 054)
연번1.0000.1460.000
우편번호0.1461.0000.630
전화번호(지역번호 054)0.0000.6301.000

Missing values

2023-12-13T00:33:08.558830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:33:08.685379image/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)
01기타상가아리원780-290경주시 엑스포로 9(신평동)748-3332
12기타상가동화상사780-290경주시 보문로 402-31, 07호(보문레이크타운)개인휴대폰
23기타상가태국왓포마사지780-290경주시 보문로 402-31, 302호(보문레이크타운)774-4222
34기타상가보문현대상가780-290경주시 보문로 368-5(신평동)745-3439
45기타상가에덴파크GS25780-290경주시 보문로 409(신평동)개인휴대폰
56기타상가수목할인마트780-270경주시 엑스포로64(천군동)748-8107
67기타상가보문마트780-270경주시 보문로 579(보문프라자 105호)개인휴대폰
78기타상가천년마트780-290경주시 보문로 368(신평동)745-0345
89기타상가필가요주점780-290경주시 천북남로 27(서광02호)개인휴대폰
910기타상가짬안마시술소780-290경주시 천북남로 27(서광05호)개인휴대폰
연번업종상호우편번호소재지(도로명)전화번호(지역번호 054)
1516기타상가물레방아노래방780-290경주시 천북남로 27(서광113호)개인휴대폰
1617기타상가BHC치킨780-290경주시 천북남로 27(서광115호)개인휴대폰
1718기타상가천년가요주점780-290경주시 천북남로 27(서광203호)개인휴대폰
1819기타상가중국전통마사지780-290경주시 천북남로 27(서광301호)개인휴대폰
1920기타상가보문콜로세움780-280경주시 보문로 132-16(북군동)777-7555
2021기타상가서라벌광장매점780-290경주시 보문로 280-31개인휴대폰
2122기타상가매실동산매점780-290경주시 보문로 402-24개인휴대폰
2223기타상가수상공연장매점780-290경주시 신평동 485-1개인휴대폰
2324기타상가경북광유780-270경주시 경감로 585(천군동)745-6651
2425기타상가천군주유소780-280경주시 경감로 631(천군동)745-9600