Overview

Dataset statistics

Number of variables8
Number of observations110
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 KiB
Average record size in memory66.2 B

Variable types

Categorical5
Text2
Numeric1

Dataset

Description인천광역시 내 준회의시설 보유 컨벤션호텔의 시설명, 소재지, 컨벤션시설현황(구분 호텔명 컨벤션시설명 면적(제곱미터) 연회(명) 극장식(명) 칵테일(명) 강의실(명) 등)의 정보를 제공합니다.
URLhttps://www.data.go.kr/data/15048956/fileData.do

Alerts

호텔명 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 호텔명High correlation
칵테일(명) is highly overall correlated with 연회(명) and 2 other fieldsHigh correlation
연회(명) is highly overall correlated with 칵테일(명) and 2 other fieldsHigh correlation
극장식(명) is highly overall correlated with 칵테일(명) and 2 other fieldsHigh correlation
강의실(명) is highly overall correlated with 칵테일(명) and 2 other fieldsHigh correlation
칵테일(명) has 55 (50.0%) zerosZeros

Reproduction

Analysis started2023-12-12 08:09:07.553434
Analysis finished2023-12-12 08:09:08.507017
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1012.0 B
중구(영종)
49 
연수구(송도)
37 
중구
10 
강화군
8 
남동구
6 

Length

Max length7
Median length6
Mean length5.5909091
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row연수구(송도)
2nd row연수구(송도)
3rd row연수구(송도)
4th row연수구(송도)
5th row연수구(송도)

Common Values

ValueCountFrequency (%)
중구(영종) 49
44.5%
연수구(송도) 37
33.6%
중구 10
 
9.1%
강화군 8
 
7.3%
남동구 6
 
5.5%

Length

2023-12-12T17:09:08.567634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:09:08.667873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구(영종 49
44.5%
연수구(송도 37
33.6%
중구 10
 
9.1%
강화군 8
 
7.3%
남동구 6
 
5.5%

호텔명
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Memory size1012.0 B
네스트호텔
12 
파라다이스시티
11 
하버파크호텔
10 
오크우드 프리미어 인천
7 
쉐라톤 그랜드 인천
 
6
Other values (18)
64 

Length

Max length20
Median length16
Mean length9.7272727
Min length5

Unique

Unique2 ?
Unique (%)1.8%

Sample

1st row경원재 앰배서더 인천
2nd row경원재 앰배서더 인천
3rd row쉐라톤 그랜드 인천
4th row쉐라톤 그랜드 인천
5th row쉐라톤 그랜드 인천

Common Values

ValueCountFrequency (%)
네스트호텔 12
 
10.9%
파라다이스시티 11
 
10.0%
하버파크호텔 10
 
9.1%
오크우드 프리미어 인천 7
 
6.4%
쉐라톤 그랜드 인천 6
 
5.5%
라르고빌 리조트 6
 
5.5%
더위크앤 리조트 6
 
5.5%
라마다 송도호텔 6
 
5.5%
그랜드하얏트인천 6
 
5.5%
호텔 스카이파크 인천 송도 5
 
4.5%
Other values (13) 35
31.8%

Length

2023-12-12T17:09:08.776507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인천 28
 
11.5%
호텔 18
 
7.4%
리조트 13
 
5.3%
네스트호텔 12
 
4.9%
송도 12
 
4.9%
프리미어 12
 
4.9%
파라다이스시티 11
 
4.5%
하버파크호텔 10
 
4.1%
라마다 8
 
3.3%
송도호텔 7
 
2.9%
Other values (31) 112
46.1%

컨벤션시설명
Text

Distinct103
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2023-12-12T17:09:09.033663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length5.2
Min length2

Characters and Unicode

Total characters572
Distinct characters120
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

Unique97 ?
Unique (%)88.2%

Sample

1st row영빈관
2nd row아리랑
3rd row그랜드볼룸(1+2)
4th row그랜드볼룸1
5th row그랜드볼룸2
ValueCountFrequency (%)
볼룸 8
 
4.9%
그랜드 7
 
4.3%
b 6
 
3.7%
미팅룸 6
 
3.7%
스테인 6
 
3.7%
a 6
 
3.7%
사파이어 4
 
2.5%
에메랄드 4
 
2.5%
a+b 4
 
2.5%
c 3
 
1.8%
Other values (89) 109
66.9%
2023-12-12T17:09:09.397928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56
 
9.8%
룸 32
 
5.6%
드 25
 
4.4%
I 25
 
4.4%
스 21
 
3.7%
홀 18
 
3.1%
B 17
 
3.0%
A 16
 
2.8%
이 16
 
2.8%
+ 14
 
2.4%
Other values (110) 332
58.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 393
68.7%
Uppercase Letter 78
 
13.6%
Space Separator 56
 
9.8%
Other Punctuation 17
 
3.0%
Math Symbol 14
 
2.4%
Decimal Number 10
 
1.7%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
룸 32
 
8.1%
드 25
 
6.4%
스 21
 
5.3%
홀 18
 
4.6%
이 16
 
4.1%
볼 13
 
3.3%
랜 13
 
3.3%
그 13
 
3.3%
아 11
 
2.8%
파 9
 
2.3%
Other values (91) 222
56.5%
Uppercase Letter
ValueCountFrequency (%)
I 25
32.1%
B 17
21.8%
A 16
20.5%
C 10
 
12.8%
D 4
 
5.1%
E 2
 
2.6%
P 1
 
1.3%
F 1
 
1.3%
L 1
 
1.3%
V 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
, 10
58.8%
/ 6
35.3%
& 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
1 5
50.0%
2 5
50.0%
Space Separator
ValueCountFrequency (%)
56
100.0%
Math Symbol
ValueCountFrequency (%)
+ 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 393
68.7%
Common 101
 
17.7%
Latin 78
 
13.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
룸 32
 
8.1%
드 25
 
6.4%
스 21
 
5.3%
홀 18
 
4.6%
이 16
 
4.1%
볼 13
 
3.3%
랜 13
 
3.3%
그 13
 
3.3%
아 11
 
2.8%
파 9
 
2.3%
Other values (91) 222
56.5%
Latin
ValueCountFrequency (%)
I 25
32.1%
B 17
21.8%
A 16
20.5%
C 10
 
12.8%
D 4
 
5.1%
E 2
 
2.6%
P 1
 
1.3%
F 1
 
1.3%
L 1
 
1.3%
V 1
 
1.3%
Common
ValueCountFrequency (%)
56
55.4%
+ 14
 
13.9%
, 10
 
9.9%
/ 6
 
5.9%
1 5
 
5.0%
2 5
 
5.0%
) 2
 
2.0%
( 2
 
2.0%
& 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 393
68.7%
ASCII 179
31.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
56
31.3%
I 25
14.0%
B 17
 
9.5%
A 16
 
8.9%
+ 14
 
7.8%
C 10
 
5.6%
, 10
 
5.6%
/ 6
 
3.4%
1 5
 
2.8%
2 5
 
2.8%
Other values (9) 15
 
8.4%
Hangul
ValueCountFrequency (%)
룸 32
 
8.1%
드 25
 
6.4%
스 21
 
5.3%
홀 18
 
4.6%
이 16
 
4.1%
볼 13
 
3.3%
랜 13
 
3.3%
그 13
 
3.3%
아 11
 
2.8%
파 9
 
2.3%
Other values (91) 222
56.5%

면적(제곱미터)
Text

Distinct92
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Memory size1012.0 B
2023-12-12T17:09:09.622549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length2.7545455
Min length1

Characters and Unicode

Total characters303
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)71.8%

Sample

1st row135
2nd row448
3rd row500
4th row250
5th row250
ValueCountFrequency (%)
60 4
 
3.6%
39 3
 
2.7%
350 3
 
2.7%
33 3
 
2.7%
331 2
 
1.8%
155 2
 
1.8%
82 2
 
1.8%
124 2
 
1.8%
0 2
 
1.8%
105 2
 
1.8%
Other values (82) 85
77.3%
2023-12-12T17:09:10.255738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 41
13.5%
1 41
13.5%
3 38
12.5%
2 38
12.5%
5 33
10.9%
4 28
9.2%
6 24
7.9%
8 24
7.9%
7 17
5.6%
9 15
 
5.0%
Other values (3) 4
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 299
98.7%
Space Separator 2
 
0.7%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41
13.7%
1 41
13.7%
3 38
12.7%
2 38
12.7%
5 33
11.0%
4 28
9.4%
6 24
8.0%
8 24
8.0%
7 17
5.7%
9 15
 
5.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 303
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 41
13.5%
1 41
13.5%
3 38
12.5%
2 38
12.5%
5 33
10.9%
4 28
9.2%
6 24
7.9%
8 24
7.9%
7 17
5.6%
9 15
 
5.0%
Other values (3) 4
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 303
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 41
13.5%
1 41
13.5%
3 38
12.5%
2 38
12.5%
5 33
10.9%
4 28
9.2%
6 24
7.9%
8 24
7.9%
7 17
5.6%
9 15
 
5.0%
Other values (3) 4
 
1.3%

연회(명)
Categorical

HIGH CORRELATION 

Distinct40
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Memory size1012.0 B
60
11 
0
11 
30
10 
120
9 
50
7 
Other values (35)
62 

Length

Max length8
Median length3
Mean length2.4090909
Min length1

Unique

Unique22 ?
Unique (%)20.0%

Sample

1st row60
2nd row220
3rd row300
4th row140
5th row140

Common Values

ValueCountFrequency (%)
60 11
 
10.0%
0 11
 
10.0%
30 10
 
9.1%
120 9
 
8.2%
50 7
 
6.4%
100 5
 
4.5%
20 5
 
4.5%
40 4
 
3.6%
150 4
 
3.6%
80 3
 
2.7%
Other values (30) 41
37.3%

Length

2023-12-12T17:09:10.429468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
60 11
 
10.0%
0 11
 
10.0%
30 10
 
9.1%
120 9
 
8.2%
50 7
 
6.4%
100 5
 
4.5%
20 5
 
4.5%
40 4
 
3.6%
150 4
 
3.6%
80 3
 
2.7%
Other values (30) 41
37.3%

극장식(명)
Categorical

HIGH CORRELATION 

Distinct48
Distinct (%)43.6%
Missing0
Missing (%)0.0%
Memory size1012.0 B
0
17 
60
 
7
50
 
6
250
 
5
100
 
5
Other values (43)
70 

Length

Max length8
Median length3
Mean length2.4909091
Min length1

Unique

Unique29 ?
Unique (%)26.4%

Sample

1st row60
2nd row200
3rd row500
4th row250
5th row250

Common Values

ValueCountFrequency (%)
0 17
 
15.5%
60 7
 
6.4%
50 6
 
5.5%
250 5
 
4.5%
100 5
 
4.5%
30 5
 
4.5%
200 5
 
4.5%
120 4
 
3.6%
80 4
 
3.6%
500 3
 
2.7%
Other values (38) 49
44.5%

Length

2023-12-12T17:09:10.613365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 17
 
15.5%
60 7
 
6.4%
50 6
 
5.5%
250 5
 
4.5%
100 5
 
4.5%
30 5
 
4.5%
200 5
 
4.5%
120 4
 
3.6%
80 4
 
3.6%
500 3
 
2.7%
Other values (38) 49
44.5%

칵테일(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct34
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean134.72727
Minimum0
Maximum1400
Zeros55
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T17:09:10.763232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10
Q3150
95-th percentile660
Maximum1400
Range1400
Interquartile range (IQR)150

Descriptive statistics

Standard deviation255.29605
Coefficient of variation (CV)1.8949099
Kurtosis9.5180834
Mean134.72727
Median Absolute Deviation (MAD)10
Skewness2.9440787
Sum14820
Variance65176.072
MonotonicityNot monotonic
2023-12-12T17:09:10.928426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 55
50.0%
250 5
 
4.5%
80 5
 
4.5%
60 3
 
2.7%
200 3
 
2.7%
100 3
 
2.7%
500 3
 
2.7%
120 2
 
1.8%
35 2
 
1.8%
150 2
 
1.8%
Other values (24) 27
24.5%
ValueCountFrequency (%)
0 55
50.0%
20 1
 
0.9%
30 1
 
0.9%
35 2
 
1.8%
40 1
 
0.9%
45 1
 
0.9%
55 1
 
0.9%
60 3
 
2.7%
70 2
 
1.8%
80 5
 
4.5%
ValueCountFrequency (%)
1400 1
 
0.9%
1250 1
 
0.9%
1000 1
 
0.9%
890 1
 
0.9%
850 1
 
0.9%
750 1
 
0.9%
550 1
 
0.9%
500 3
2.7%
450 1
 
0.9%
400 1
 
0.9%

강의실(명)
Categorical

HIGH CORRELATION 

Distinct48
Distinct (%)43.6%
Missing0
Missing (%)0.0%
Memory size1012.0 B
0
14 
200
 
6
30
 
6
180
 
5
60
 
5
Other values (43)
74 

Length

Max length8
Median length3
Mean length2.3363636
Min length1

Unique

Unique28 ?
Unique (%)25.5%

Sample

1st row60
2nd row200
3rd row300
4th row150
5th row150

Common Values

ValueCountFrequency (%)
0 14
 
12.7%
200 6
 
5.5%
30 6
 
5.5%
180 5
 
4.5%
60 5
 
4.5%
40 4
 
3.6%
80 4
 
3.6%
100 4
 
3.6%
150 4
 
3.6%
50 4
 
3.6%
Other values (38) 54
49.1%

Length

2023-12-12T17:09:11.102669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 14
 
12.7%
30 6
 
5.5%
200 6
 
5.5%
180 5
 
4.5%
60 5
 
4.5%
50 4
 
3.6%
70 4
 
3.6%
150 4
 
3.6%
100 4
 
3.6%
80 4
 
3.6%
Other values (38) 54
49.1%

Interactions

2023-12-12T17:09:08.234571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:09:11.244772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분호텔명면적(제곱미터)연회(명)극장식(명)칵테일(명)강의실(명)
구분1.0001.0000.8660.0000.3100.1450.000
호텔명1.0001.0000.9830.7420.3290.6570.000
면적(제곱미터)0.8660.9831.0000.9810.9790.9990.950
연회(명)0.0000.7420.9811.0000.9780.9700.980
극장식(명)0.3100.3290.9790.9781.0000.9800.994
칵테일(명)0.1450.6570.9990.9700.9801.0000.979
강의실(명)0.0000.0000.9500.9800.9940.9791.000
2023-12-12T17:09:11.415651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
극장식(명)강의실(명)연회(명)호텔명구분
극장식(명)1.0000.6320.5650.0000.095
강의실(명)0.6321.0000.5800.0000.000
연회(명)0.5650.5801.0000.2250.000
호텔명0.0000.0000.2251.0000.910
구분0.0950.0000.0000.9101.000
2023-12-12T17:09:11.584053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
칵테일(명)구분호텔명연회(명)극장식(명)강의실(명)
칵테일(명)1.0000.0780.2960.6820.6670.662
구분0.0781.0000.9100.0000.0950.000
호텔명0.2960.9101.0000.2250.0000.000
연회(명)0.6820.0000.2251.0000.5650.580
극장식(명)0.6670.0950.0000.5651.0000.632
강의실(명)0.6620.0000.0000.5800.6321.000

Missing values

2023-12-12T17:09:08.353616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:09:08.464851image/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

구분호텔명컨벤션시설명면적(제곱미터)연회(명)극장식(명)칵테일(명)강의실(명)
0연수구(송도)경원재 앰배서더 인천영빈관13560606060
1연수구(송도)경원재 앰배서더 인천아리랑448220200150200
2연수구(송도)쉐라톤 그랜드 인천그랜드볼룸(1+2)500300500250300
3연수구(송도)쉐라톤 그랜드 인천그랜드볼룸1250140250100150
4연수구(송도)쉐라톤 그랜드 인천그랜드볼룸2250140250100150
5연수구(송도)쉐라톤 그랜드 인천로터스(1+2)160801008060
6연수구(송도)쉐라톤 그랜드 인천로터스110050704045
7연수구(송도)쉐라톤 그랜드 인천로터스26030302024
8연수구(송도)오크우드 프리미어 인천프리미어룸213150280150160
9연수구(송도)오크우드 프리미어 인천아스테리아148701007070
구분호텔명컨벤션시설명면적(제곱미터)연회(명)극장식(명)칵테일(명)강의실(명)
100강화군라르고빌 리조트심포니홀175100200250150
101강화군라르고빌 리조트오페라홀162100200250150
102강화군라르고빌 리조트하모니홀10550150180100
103강화군라르고빌 리조트아레나홀825010012080
104남동구라마다 인천호텔글로리 홀11060100080
105남동구라마다 인천호텔EFL 라운지373030040
106남동구파크마린 호텔연회홀33110012000
107남동구파크마린 호텔컨퍼런스 룸46101500
108남동구파크마린 호텔점프 시티37450000
109남동구파크마린 호텔문그루브32680000