Overview

Dataset statistics

Number of variables6
Number of observations109
Missing cells110
Missing cells (%)16.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory52.2 B

Variable types

Unsupported1
Numeric2
Text3

Dataset

Description당진시 모범 숙박업소 현황입니다.(평가구분, 업종, 업소명, 소새지(도로명))
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=450&beforeMenuCd=DOM_000000201001001000&publicdatapk=15052875

Alerts

일련 번호 is highly overall correlated with 객실수High correlation
객실수 is highly overall correlated with 일련 번호High correlation
Unnamed: 0 has 109 (100.0%) missing valuesMissing
일련 번호 has unique valuesUnique
업소명 has unique valuesUnique
업소소재지(도로명) has unique valuesUnique
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-01-09 20:11:50.284219
Analysis finished2024-01-09 20:11:51.235083
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing109
Missing (%)100.0%
Memory size1.1 KiB

일련 번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55
Minimum1
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-01-10T05:11:51.326421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.4
Q128
median55
Q382
95-th percentile103.6
Maximum109
Range108
Interquartile range (IQR)54

Descriptive statistics

Standard deviation31.609598
Coefficient of variation (CV)0.57471996
Kurtosis-1.2
Mean55
Median Absolute Deviation (MAD)27
Skewness0
Sum5995
Variance999.16667
MonotonicityStrictly increasing
2024-01-10T05:11:51.522067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
70 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
Other values (99) 99
90.8%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%

업소명
Text

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2024-01-10T05:11:51.878657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.9357798
Min length1

Characters and Unicode

Total characters538
Distinct characters152
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)100.0%

Sample

1st row난지파크
2nd row신흥여인숙
3rd row제일여인숙
4th row금호여인숙
5th row동궁장여관
ValueCountFrequency (%)
여관 3
 
2.6%
호텔 2
 
1.7%
난지파크 1
 
0.9%
그린월드장 1
 
0.9%
부웅모텔 1
 
0.9%
로얄모텔 1
 
0.9%
워커힐 1
 
0.9%
힐하우스모텔 1
 
0.9%
신흥모텔 1
 
0.9%
하이힐모텔 1
 
0.9%
Other values (102) 102
88.7%
2024-01-10T05:11:52.422997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
53
 
9.9%
46
 
8.6%
44
 
8.2%
32
 
5.9%
32
 
5.9%
16
 
3.0%
16
 
3.0%
15
 
2.8%
13
 
2.4%
8
 
1.5%
Other values (142) 263
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 525
97.6%
Space Separator 6
 
1.1%
Uppercase Letter 4
 
0.7%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
53
 
10.1%
46
 
8.8%
44
 
8.4%
32
 
6.1%
32
 
6.1%
16
 
3.0%
16
 
3.0%
15
 
2.9%
13
 
2.5%
8
 
1.5%
Other values (135) 250
47.6%
Uppercase Letter
ValueCountFrequency (%)
S 2
50.0%
M 1
25.0%
Q 1
25.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 525
97.6%
Common 8
 
1.5%
Latin 5
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
53
 
10.1%
46
 
8.8%
44
 
8.4%
32
 
6.1%
32
 
6.1%
16
 
3.0%
16
 
3.0%
15
 
2.9%
13
 
2.5%
8
 
1.5%
Other values (135) 250
47.6%
Latin
ValueCountFrequency (%)
S 2
40.0%
M 1
20.0%
Q 1
20.0%
a 1
20.0%
Common
ValueCountFrequency (%)
6
75.0%
( 1
 
12.5%
) 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 525
97.6%
ASCII 13
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
53
 
10.1%
46
 
8.8%
44
 
8.4%
32
 
6.1%
32
 
6.1%
16
 
3.0%
16
 
3.0%
15
 
2.9%
13
 
2.5%
8
 
1.5%
Other values (135) 250
47.6%
ASCII
ValueCountFrequency (%)
6
46.2%
S 2
 
15.4%
( 1
 
7.7%
) 1
 
7.7%
M 1
 
7.7%
Q 1
 
7.7%
a 1
 
7.7%
Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2024-01-10T05:11:52.854525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length22.954128
Min length18

Characters and Unicode

Total characters2502
Distinct characters105
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

Unique109 ?
Unique (%)100.0%

Sample

1st row충청남도 당진시 석문면 대호만로 2336-1
2nd row충청남도 당진시 합덕읍 합덕교동1길 20
3rd row충청남도 당진시 서문2길 4 (읍내동)
4th row충청남도 당진시 당진시장서길 34 (읍내동)
5th row충청남도 당진시 당진중앙2로 41-9 (읍내동)
ValueCountFrequency (%)
충청남도 109
20.0%
당진시 109
20.0%
읍내동 32
 
5.9%
송악읍 30
 
5.5%
당진중앙2로 15
 
2.7%
석문면 11
 
2.0%
당진중앙3로 11
 
2.0%
신평면 11
 
2.0%
반촌로 8
 
1.5%
합덕읍 6
 
1.1%
Other values (161) 204
37.4%
2024-01-10T05:11:53.461299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
440
17.6%
143
 
5.7%
140
 
5.6%
118
 
4.7%
115
 
4.6%
109
 
4.4%
109
 
4.4%
109
 
4.4%
1 76
 
3.0%
74
 
3.0%
Other values (95) 1069
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1541
61.6%
Space Separator 440
 
17.6%
Decimal Number 385
 
15.4%
Dash Punctuation 51
 
2.0%
Close Punctuation 41
 
1.6%
Open Punctuation 41
 
1.6%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
143
 
9.3%
140
 
9.1%
118
 
7.7%
115
 
7.5%
109
 
7.1%
109
 
7.1%
109
 
7.1%
74
 
4.8%
68
 
4.4%
43
 
2.8%
Other values (79) 513
33.3%
Decimal Number
ValueCountFrequency (%)
1 76
19.7%
2 62
16.1%
3 61
15.8%
6 37
9.6%
8 34
8.8%
5 32
8.3%
7 30
 
7.8%
4 24
 
6.2%
9 16
 
4.2%
0 13
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
440
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1541
61.6%
Common 961
38.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
143
 
9.3%
140
 
9.1%
118
 
7.7%
115
 
7.5%
109
 
7.1%
109
 
7.1%
109
 
7.1%
74
 
4.8%
68
 
4.4%
43
 
2.8%
Other values (79) 513
33.3%
Common
ValueCountFrequency (%)
440
45.8%
1 76
 
7.9%
2 62
 
6.5%
3 61
 
6.3%
- 51
 
5.3%
) 41
 
4.3%
( 41
 
4.3%
6 37
 
3.9%
8 34
 
3.5%
5 32
 
3.3%
Other values (6) 86
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1541
61.6%
ASCII 961
38.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
440
45.8%
1 76
 
7.9%
2 62
 
6.5%
3 61
 
6.3%
- 51
 
5.3%
) 41
 
4.3%
( 41
 
4.3%
6 37
 
3.9%
8 34
 
3.5%
5 32
 
3.3%
Other values (6) 86
 
8.9%
Hangul
ValueCountFrequency (%)
143
 
9.3%
140
 
9.1%
118
 
7.7%
115
 
7.5%
109
 
7.1%
109
 
7.1%
109
 
7.1%
74
 
4.8%
68
 
4.4%
43
 
2.8%
Other values (79) 513
33.3%
Distinct107
Distinct (%)99.1%
Missing1
Missing (%)0.9%
Memory size1004.0 B
2024-01-10T05:11:53.772508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.851852
Min length2

Characters and Unicode

Total characters1496
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique106 ?
Unique (%)98.1%

Sample

1st row 041- 353-0212
2nd row - -
3rd row 041- 355-2336
4th row 041- 356-1396
5th row 041- 355-2870
ValueCountFrequency (%)
041 99
43.6%
8
 
3.5%
357 6
 
2.6%
358 4
 
1.8%
357-5887 1
 
0.4%
356-6220 1
 
0.4%
352-3566 1
 
0.4%
363-4666 1
 
0.4%
355-0798 1
 
0.4%
353-3900 1
 
0.4%
Other values (104) 104
45.8%
2024-01-10T05:11:54.268143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/