Overview

Dataset statistics

Number of variables5
Number of observations80
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory43.6 B

Variable types

Numeric2
Text2
Categorical1

Dataset

Description- 근로복지공단이 근로자 및 그 가족들의 여가 욕구 충족을 위해 지원하는 휴양시설(콘도)현황입니다. - 근로자 휴양콘도: 근로자 및 그 가족들의 여가 욕구 충족을 위해 휴양시설(콘도)을 저렴한 비용으로 이용할 수 있도록 지원하는 사업 ※ 근로복지넷: https://welfare.comwel.or.kr
URLhttps://www.data.go.kr/data/15122181/fileData.do

Alerts

객실타입2 is highly overall correlated with 객실타입1High correlation
객실타입1 is highly overall correlated with 객실타입2High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:12:15.867652
Analysis finished2023-12-12 16:12:17.031645
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.5
Minimum1
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-13T01:12:17.131441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.95
Q120.75
median40.5
Q360.25
95-th percentile76.05
Maximum80
Range79
Interquartile range (IQR)39.5

Descriptive statistics

Standard deviation23.2379
Coefficient of variation (CV)0.57377531
Kurtosis-1.2
Mean40.5
Median Absolute Deviation (MAD)20
Skewness0
Sum3240
Variance540
MonotonicityStrictly increasing
2023-12-13T01:12:17.334457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
42 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
54 1
 
1.2%
53 1
 
1.2%
Other values (70) 70
87.5%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%
73 1
1.2%
72 1
1.2%
71 1
1.2%

콘도명
Text

Distinct48
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-13T01:12:17.593529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.6125
Min length5

Characters and Unicode

Total characters529
Distinct characters77
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

Unique19 ?
Unique (%)23.8%

Sample

1st row금강산 고성(화진포)
2nd row금강산 고성(화진포)
3rd row금강산 제주
4th row금호 설악
5th row금호 제주
ValueCountFrequency (%)
대명 18
 
11.2%
한화 13
 
8.1%
일성 12
 
7.5%
리솜 11
 
6.8%
켄싱턴 9
 
5.6%
제주 8
 
5.0%
토비스 8
 
5.0%
경주 8
 
5.0%
설악 7
 
4.3%
금호 6
 
3.7%
Other values (33) 61
37.9%
2023-12-13T01:12:18.005284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
 
15.3%
주 24
 
4.5%
대 20
 
3.8%
명 18
 
3.4%
화 17
 
3.2%
비 16
 
3.0%
) 14
 
2.6%
리 14
 
2.6%
도 14
 
2.6%
성 14
 
2.6%
Other values (67) 297
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 418
79.0%
Space Separator 81
 
15.3%
Close Punctuation 14
 
2.6%
Open Punctuation 14
 
2.6%
Uppercase Letter 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 24
 
5.7%
대 20
 
4.8%
명 18
 
4.3%
화 17
 
4.1%
비 16
 
3.8%
리 14
 
3.3%
도 14
 
3.3%
성 14
 
3.3%
산 14
 
3.3%
한 14
 
3.3%
Other values (63) 253
60.5%
Space Separator
ValueCountFrequency (%)
81
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 418
79.0%
Common 109
 
20.6%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 24
 
5.7%
대 20
 
4.8%
명 18
 
4.3%
화 17
 
4.1%
비 16
 
3.8%
리 14
 
3.3%
도 14
 
3.3%
성 14
 
3.3%
산 14
 
3.3%
한 14
 
3.3%
Other values (63) 253
60.5%
Common
ValueCountFrequency (%)
81
74.3%
) 14
 
12.8%
( 14
 
12.8%
Latin
ValueCountFrequency (%)
A 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 418
79.0%
ASCII 111
 
21.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
81
73.0%
) 14
 
12.6%
( 14
 
12.6%
A 2
 
1.8%
Hangul
ValueCountFrequency (%)
주 24
 
5.7%
대 20
 
4.8%
명 18
 
4.3%
화 17
 
4.1%
비 16
 
3.8%
리 14
 
3.3%
도 14
 
3.3%
성 14
 
3.3%
산 14
 
3.3%
한 14
 
3.3%
Other values (63) 253
60.5%

객실타입1
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)28.7%
Missing0
Missing (%)0.0%
Memory size772.0 B
스위트
12 
패밀리
12 
패밀리(일반)
9 
17평
5 
28평
4 
Other values (18)
38 

Length

Max length10
Median length3
Mean length4
Min length3

Unique

Unique9 ?
Unique (%)11.2%

Sample

1st row16평
2nd row30평
3rd row27평
4th row스위트
5th row패밀리

Common Values

ValueCountFrequency (%)
스위트 12
15.0%
패밀리 12
15.0%
패밀리(일반) 9
11.2%
17평 5
 
6.2%
28평 4
 
5.0%
25평 4
 
5.0%
노블(21) 4
 
5.0%
23평 4
 
5.0%
27평 4
 
5.0%
26평 3
 
3.8%
Other values (13) 19
23.8%

Length

2023-12-13T01:12:18.169733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
스위트 12
15.0%
패밀리 12
15.0%
패밀리(일반 9
11.2%
17평 5
 
6.2%
28평 4
 
5.0%
25평 4
 
5.0%
노블(21 4
 
5.0%
23평 4
 
5.0%
27평 4
 
5.0%
젠트리(16 3
 
3.8%
Other values (13) 19
23.8%

객실타입2
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)41.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.26875
Minimum49.5
Maximum125
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-13T01:12:18.326610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum49.5
5-th percentile52.8
Q162.775
median75.95
Q386
95-th percentile102.015
Maximum125
Range75.5
Interquartile range (IQR)23.225

Descriptive statistics

Standard deviation15.951077
Coefficient of variation (CV)0.20914302
Kurtosis-0.20784133
Mean76.26875
Median Absolute Deviation (MAD)13.15
Skewness0.21004865
Sum6101.5
Variance254.43686
MonotonicityNot monotonic
2023-12-13T01:12:18.474300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
75.9 7
 
8.8%
52.8 5
 
6.2%
89.1 5
 
6.2%
56.0 4
 
5.0%
56.1 4
 
5.0%
69.3 4
 
5.0%
85.8 4
 
5.0%
92.4 4
 
5.0%
85.9 4
 
5.0%
76.0 4
 
5.0%
Other values (23) 35
43.8%
ValueCountFrequency (%)
49.5 2
 
2.5%
52.8 5
6.2%
53.0 1
 
1.2%
56.0 4
5.0%
56.1 4
5.0%
59.0 2
 
2.5%
59.4 1
 
1.2%
62.7 1
 
1.2%
62.8 2
 
2.5%
66.0 1
 
1.2%
ValueCountFrequency (%)
125.0 1
 
1.2%
105.7 2
 
2.5%
102.3 1
 
1.2%
102.0 1
 
1.2%
99.0 2
 
2.5%
92.5 1
 
1.2%
92.4 4
5.0%
92.0 1
 
1.2%
89.2 1
 
1.2%
89.1 5
6.2%

주소
Text

Distinct46
Distinct (%)57.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-13T01:12:18.790344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20.5
Mean length19.1625
Min length12

Characters and Unicode

Total characters1533
Distinct characters125
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)25.0%

Sample

1st row강원 고성군 현내면 금강산로 416
2nd row강원 고성군 현내면 금강산로 416
3rd row제주 북제주군 한림읍 협재리 929-1
4th row강원 속초시 사당골길 43
5th row제주 서귀포시 남원읍 태위로 522-12
ValueCountFrequency (%)
강원 16
 
4.1%
충남 14
 
3.6%
제주 11
 
2.8%
경북 9
 
2.3%
전북 9
 
2.3%
경주시 8
 
2.1%
고성군 8
 
2.1%
보문로 7
 
1.8%
경기 7
 
1.8%
북제주군 6
 
1.6%
Other values (145) 291
75.4%
2023-12-13T01:12:19.265770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
306
 
20.0%
군 53
 
3.5%
면 52
 
3.4%
로 50
 
3.3%
2 48
 
3.1%
1 44
 
2.9%
5 42
 
2.7%
북 36
 
2.3%
주 36
 
2.3%
시 35
 
2.3%
Other values (115) 831
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 913
59.6%
Space Separator 306
 
20.0%
Decimal Number 283
 
18.5%
Dash Punctuation 31
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 53
 
5.8%
면 52
 
5.7%
로 50
 
5.5%
북 36
 
3.9%
주 36
 
3.9%
시 35
 
3.8%
산 33
 
3.6%
경 30
 
3.3%
남 27
 
3.0%
제 26
 
2.8%
Other values (103) 535
58.6%
Decimal Number
ValueCountFrequency (%)
2 48
17.0%
1 44
15.5%
5 42
14.8%
3 33
11.7%
4 31
11.0%
7 26
9.2%
6 18
 
6.4%
0 18
 
6.4%
8 12
 
4.2%
9 11
 
3.9%
Space Separator
ValueCountFrequency (%)
306
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 913
59.6%
Common 620
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 53
 
5.8%
면 52
 
5.7%
로 50
 
5.5%
북 36
 
3.9%
주 36
 
3.9%
시 35
 
3.8%
산 33
 
3.6%
경 30
 
3.3%
남 27
 
3.0%
제 26
 
2.8%
Other values (103) 535
58.6%
Common
ValueCountFrequency (%)
306
49.4%
2 48
 
7.7%
1 44
 
7.1%
5 42
 
6.8%
3 33
 
5.3%
- 31
 
5.0%
4 31
 
5.0%
7 26
 
4.2%
6 18
 
2.9%
0 18
 
2.9%
Other values (2) 23
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 913
59.6%
ASCII 620
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
306
49.4%
2 48
 
7.7%
1 44
 
7.1%
5 42
 
6.8%
3 33
 
5.3%
- 31
 
5.0%
4 31
 
5.0%
7 26
 
4.2%
6 18
 
2.9%
0 18
 
2.9%
Other values (2) 23
 
3.7%
Hangul
ValueCountFrequency (%)
군 53
 
5.8%
면 52
 
5.7%
로 50
 
5.5%
북 36
 
3.9%
주 36
 
3.9%
시 35
 
3.8%
산 33
 
3.6%
경 30
 
3.3%
남 27
 
3.0%
제 26
 
2.8%
Other values (103) 535
58.6%

Interactions

2023-12-13T01:12:16.518768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:16.243757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:16.659707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:12:16.385230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:12:19.369856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번콘도명객실타입1객실타입2주소
연번1.0000.9910.8350.3890.991
콘도명0.9911.0000.0000.5091.000
객실타입10.8350.0001.0000.9320.761
객실타입20.3890.5090.9321.0000.596
주소0.9911.0000.7610.5961.000
2023-12-13T01:12:19.484168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번객실타입2객실타입1
연번1.0000.0020.448
객실타입20.0021.0000.642
객실타입10.4480.6421.000

Missing values

2023-12-13T01:12:16.814422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:12:16.967797image/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

연번콘도명객실타입1객실타입2주소
01금강산 고성(화진포)16평52.8강원 고성군 현내면 금강산로 416
12금강산 고성(화진포)30평99.0강원 고성군 현내면 금강산로 416
23금강산 제주27평89.1제주 북제주군 한림읍 협재리 929-1
34금호 설악스위트89.1강원 속초시 사당골길 43
45금호 제주패밀리53.0제주 서귀포시 남원읍 태위로 522-12
56금호 통영패밀리52.8경남 통영시 큰발개1길 33
67금호 통영스위트89.1경남 통영시 큰발개1길 33
78금호 화순패밀리56.1전남 화순군 북면 옥리
89금호 화순스위트89.1전남 화순군 북면 옥리
910대명 거제패밀리69.4경남 거제시 일운면 거제대로 2660
연번콘도명객실타입1객실타입2주소
7071한화 백암패밀리(일반)75.9경북 울진군 온정면 온천로 129-13
7172한화 산정호수패밀리(일반)85.8경기 포천시 영북면 산정호수로 402
7273한화 설악패밀리(일반)75.9강원 속초시 미시령로2983번길 111
7374한화 설악패밀리(쏘라노)76.0강원 속초시 미시령로2983번길 111
7475한화 수안보패밀리(일반)85.8충북 충주시 상모면 온천리 748-2
7576한화 양평패밀리(일반)75.9경기 양평군 옥천면 신복리 164-1
7677한화 용인패밀리(일반)75.9경기 용인군 남사면 봉무리 257-1
7778한화 제주패밀리(일반)82.5제주 제주시 명림로 575-107
7879한화 평창패밀리스위트(38)125.0강원 평창군 봉평면 태기로 228-33
7980한화 해운대패밀리(일반)86.0부산 해운대구 마린시티3로 52