Overview

Dataset statistics

Number of variables6
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory55.3 B

Variable types

Numeric1
Categorical2
Text3

Dataset

Description보문단지 입주 숙박업체 리스트
Author경상북도관광공사
URLhttps://www.data.go.kr/data/15044406/fileData.do

Alerts

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

Reproduction

Analysis started2023-12-12 21:58:35.747163
Analysis finished2023-12-12 21:58:36.321487
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-13T06:58:36.394980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q316
95-th percentile20
Maximum21
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.56407607
Kurtosis-1.2
Mean11
Median Absolute Deviation (MAD)5
Skewness0
Sum231
Variance38.5
MonotonicityStrictly increasing
2023-12-13T06:58:36.564671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
14 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
ValueCountFrequency (%)
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%
12 1
4.8%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
숙박업
21 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
숙박업 21
100.0%

Length

2023-12-13T06:58:36.711581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:58:36.810159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업 21
100.0%

상호
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T06:58:36.986212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.8571429
Min length4

Characters and Unicode

Total characters123
Distinct characters55
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

Unique21 ?
Unique (%)100.0%

Sample

1st row현대호텔
2nd row힐튼호텔
3rd row더케이 경주호텔
4th row콩코드호텔
5th row코모도호텔
ValueCountFrequency (%)
현대호텔 1
 
4.5%
힐튼호텔 1
 
4.5%
올레모텔 1
 
4.5%
발렌타인호텔 1
 
4.5%
이사금유스타운 1
 
4.5%
자라모텔 1
 
4.5%
한솔모텔 1
 
4.5%
그랜드유스타운 1
 
4.5%
스위스로젠관광호텔 1
 
4.5%
스위트호텔경주 1
 
4.5%
Other values (12) 12
54.5%
2023-12-13T06:58:37.350009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 13
 
10.6%
호 10
 
8.1%
경 9
 
7.3%
주 9
 
7.3%
스 6
 
4.9%
도 5
 
4.1%
콘 4
 
3.3%
모 4
 
3.3%
타 3
 
2.4%
한 3
 
2.4%
Other values (45) 57
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 122
99.2%
Space Separator 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 13
 
10.7%
호 10
 
8.2%
경 9
 
7.4%
주 9
 
7.4%
스 6
 
4.9%
도 5
 
4.1%
콘 4
 
3.3%
모 4
 
3.3%
타 3
 
2.5%
한 3
 
2.5%
Other values (44) 56
45.9%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 122
99.2%
Common 1
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 13
 
10.7%
호 10
 
8.2%
경 9
 
7.4%
주 9
 
7.4%
스 6
 
4.9%
도 5
 
4.1%
콘 4
 
3.3%
모 4
 
3.3%
타 3
 
2.5%
한 3
 
2.5%
Other values (44) 56
45.9%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 122
99.2%
ASCII 1
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 13
 
10.7%
호 10
 
8.2%
경 9
 
7.4%
주 9
 
7.4%
스 6
 
4.9%
도 5
 
4.1%
콘 4
 
3.3%
모 4
 
3.3%
타 3
 
2.5%
한 3
 
2.5%
Other values (44) 56
45.9%
ASCII
ValueCountFrequency (%)
1
100.0%

우편번호
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
780-290
18 
780-280
3 

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 18
85.7%
780-280 3
 
14.3%

Length

2023-12-13T06:58:37.473144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:58:37.563909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
780-290 18
85.7%
780-280 3
 
14.3%

소재지(도로명)
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T06:58:37.718664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length17.666667
Min length16

Characters and Unicode

Total characters371
Distinct characters28
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

Unique21 ?
Unique (%)100.0%

Sample

1st row경주시 보문로 338(신평동)
2nd row경주시 보문로 484-7(신평동)
3rd row경주시 엑스포로 45(신평동)
4th row경주시 보문로 404(신평동)
5th row경주시 보문로 422(신평동)
ValueCountFrequency (%)
경주시 21
33.3%
보문로 19
30.2%
엑스포로 2
 
3.2%
353(신평동 1
 
1.6%
465-40(신평동 1
 
1.6%
465-28(신평동 1
 
1.6%
465-24(신평동 1
 
1.6%
465-20(신평동 1
 
1.6%
465-47(신평동 1
 
1.6%
465-43(신평동 1
 
1.6%
Other values (14) 14
22.2%
2023-12-13T06:58:38.095863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
 
11.3%
경 21
 
5.7%
( 21
 
5.7%
시 21
 
5.7%
주 21
 
5.7%
) 21
 
5.7%
로 21
 
5.7%
동 21
 
5.7%
4 19
 
5.1%
문 19
 
5.1%
Other values (18) 144
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 191
51.5%
Decimal Number 84
22.6%
Space Separator 42
 
11.3%
Open Punctuation 21
 
5.7%
Close Punctuation 21
 
5.7%
Dash Punctuation 12
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 21
11.0%
시 21
11.0%
주 21
11.0%
로 21
11.0%
동 21
11.0%
문 19
9.9%
보 19
9.9%
평 18
9.4%
신 18
9.4%
북 3
 
1.6%
Other values (4) 9
4.7%
Decimal Number
ValueCountFrequency (%)
4 19
22.6%
2 13
15.5%
5 10
11.9%
3 10
11.9%
6 8
9.5%
0 7
 
8.3%
8 7
 
8.3%
7 5
 
6.0%
1 4
 
4.8%
9 1
 
1.2%
Space Separator
ValueCountFrequency (%)
42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 191
51.5%
Common 180
48.5%

Most frequent character per script

Common
ValueCountFrequency (%)
42
23.3%
( 21
11.7%
) 21
11.7%
4 19
10.6%
2 13
 
7.2%
- 12
 
6.7%
5 10
 
5.6%
3 10
 
5.6%
6 8
 
4.4%
0 7
 
3.9%
Other values (4) 17
9.4%
Hangul
ValueCountFrequency (%)
경 21
11.0%
시 21
11.0%
주 21
11.0%
로 21
11.0%
동 21
11.0%
문 19
9.9%
보 19
9.9%
평 18
9.4%
신 18
9.4%
북 3
 
1.6%
Other values (4) 9
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 191
51.5%
ASCII 180
48.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
23.3%
( 21
11.7%
) 21
11.7%
4 19
10.6%
2 13
 
7.2%
- 12
 
6.7%
5 10
 
5.6%
3 10
 
5.6%
6 8
 
4.4%
0 7
 
3.9%
Other values (4) 17
9.4%
Hangul
ValueCountFrequency (%)
경 21
11.0%
시 21
11.0%
주 21
11.0%
로 21
11.0%
동 21
11.0%
문 19
9.9%
보 19
9.9%
평 18
9.4%
신 18
9.4%
북 3
 
1.6%
Other values (4) 9
4.7%

전화번호(지역번호 054)
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-13T06:58:38.290421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters168
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

Unique21 ?
Unique (%)100.0%

Sample

1st row779-7627
2nd row740-1303
3rd row770-9124
4th row740-6011
5th row740-8355
ValueCountFrequency (%)
779-7627 1
 
4.8%
778-8306 1
 
4.8%
745-1214 1
 
4.8%
748-3232 1
 
4.8%
745-1695 1
 
4.8%
745-0404 1
 
4.8%
748-3800 1
 
4.8%
745-2777 1
 
4.8%
748-4848 1
 
4.8%
778-5300 1
 
4.8%
Other values (11) 11
52.4%
2023-12-13T06:58:38.602053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 37
22.0%
4 23
13.7%
0 22
13.1%
- 21
12.5%
8 14
 
8.3%
3 12
 
7.1%
1 10
 
6.0%
5 10
 
6.0%
2 8
 
4.8%
9 6
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147
87.5%
Dash Punctuation 21
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 37
25.2%
4 23
15.6%
0 22
15.0%
8 14
 
9.5%
3 12
 
8.2%
1 10
 
6.8%
5 10
 
6.8%
2 8
 
5.4%
9 6
 
4.1%
6 5
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 168
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 37
22.0%
4 23
13.7%
0 22
13.1%
- 21
12.5%
8 14
 
8.3%
3 12
 
7.1%
1 10
 
6.0%
5 10
 
6.0%
2 8
 
4.8%
9 6
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 168
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 37
22.0%
4 23
13.7%
0 22
13.1%
- 21
12.5%
8 14
 
8.3%
3 12
 
7.1%
1 10
 
6.0%
5 10
 
6.0%
2 8
 
4.8%
9 6
 
3.6%

Interactions

2023-12-13T06:58:35.999238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:58:38.717779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호우편번호소재지(도로명)전화번호(지역번호 054)
연번1.0001.0000.0001.0001.000
상호1.0001.0001.0001.0001.000
우편번호0.0001.0001.0001.0001.000
소재지(도로명)1.0001.0001.0001.0001.000
전화번호(지역번호 054)1.0001.0001.0001.0001.000
2023-12-13T06:58:38.837611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호
연번1.0000.612
우편번호0.6121.000

Missing values

2023-12-13T06:58:36.139380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:58:36.267974image/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)
01숙박업현대호텔780-290경주시 보문로 338(신평동)779-7627
12숙박업힐튼호텔780-290경주시 보문로 484-7(신평동)740-1303
23숙박업더케이 경주호텔780-290경주시 엑스포로 45(신평동)770-9124
34숙박업콩코드호텔780-290경주시 보문로 404(신평동)740-6011
45숙박업코모도호텔780-290경주시 보문로 422(신평동)740-8355
56숙박업조선호텔780-290경주시 보문로 407(신평동)740-9503
67숙박업경주관광호텔780-290경주시 보문로 383(신평동)745-7123
78숙박업켄싱턴리조트경주780-280경주시 보문로 182-29(북군동)748-8400
89숙박업경주한화콘도780-280경주시 보문로 182-27(북군동)777-8346
910숙박업경주일성콘도780-290경주시 보문로 365(신평동)744-1199
연번업종상호우편번호소재지(도로명)전화번호(지역번호 054)
1112숙박업경주대명콘도780-290경주시 보문로 402-12(신평동)778-8306
1213숙박업스위트호텔경주780-280경주시 보문로 280-12(북군동)778-5300
1314숙박업스위스로젠관광호텔780-290경주시 보문로 465-37(신평동)748-4848
1415숙박업그랜드유스타운780-290경주시 보문로 465-43(신평동)745-2777
1516숙박업한솔모텔780-290경주시 보문로 465-47(신평동)748-3800
1617숙박업자라모텔780-290경주시 보문로 465-20(신평동)745-0404
1718숙박업이사금유스타운780-290경주시 보문로 465-24(신평동)745-1695
1819숙박업발렌타인호텔780-290경주시 보문로 465-28(신평동)748-3232
1920숙박업올레모텔780-290경주시 보문로 465-40(신평동)745-1214
2021숙박업코웰스경주센터780-290경주시 엑스포로 30(신평동)770-0300