Overview

Dataset statistics

Number of variables5
Number of observations200
Missing cells149
Missing cells (%)14.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.1 KiB
Average record size in memory41.7 B

Variable types

Numeric1
Text4

Dataset

Description문경시 관내의 캠핑장(야영장)에 대한 데이터로 글램핑장 또는 펜션의 상호명, 위치 및 연락처 등의 항목을 제공합니다.
Author경상북도 문경시
URLhttps://www.data.go.kr/data/15088400/fileData.do

Alerts

전화번호 has 149 (74.5%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:29:49.670783
Analysis finished2023-12-12 12:29:50.496504
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.5
Minimum1
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T21:29:50.606259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.95
Q150.75
median100.5
Q3150.25
95-th percentile190.05
Maximum200
Range199
Interquartile range (IQR)99.5

Descriptive statistics

Standard deviation57.879185
Coefficient of variation (CV)0.57591228
Kurtosis-1.2
Mean100.5
Median Absolute Deviation (MAD)50
Skewness0
Sum20100
Variance3350
MonotonicityStrictly increasing
2023-12-12T21:29:50.831560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
139 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
Other values (190) 190
95.0%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
200 1
0.5%
199 1
0.5%
198 1
0.5%
197 1
0.5%
196 1
0.5%
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%
Distinct193
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T21:29:51.263757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length5.795
Min length2

Characters and Unicode

Total characters1159
Distinct characters264
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)93.0%

Sample

1st row꿈꾸는새재
2nd row산중모텔펜션
3rd row해가빛
4th row문경새재국민여가캠핑장
5th row이둔펜션
ValueCountFrequency (%)
캠핑장 4
 
1.8%
야영장 4
 
1.8%
더모스트 3
 
1.4%
불정자연휴양림황토펜션 2
 
0.9%
해바라기 2
 
0.9%
민박 2
 
0.9%
새재마당바위 2
 
0.9%
문경가름펜션 2
 
0.9%
가은민박 2
 
0.9%
이둔펜션 2
 
0.9%
Other values (194) 196
88.7%
2023-12-12T21:29:51.848782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
73
 
6.3%
73
 
6.3%
30
 
2.6%
28
 
2.4%
27
 
2.3%
27
 
2.3%
27
 
2.3%
27
 
2.3%
24
 
2.1%
23
 
2.0%
Other values (254) 800
69.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1110
95.8%
Space Separator 21
 
1.8%
Uppercase Letter 17
 
1.5%
Decimal Number 6
 
0.5%
Letter Number 2
 
0.2%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
73
 
6.6%
73
 
6.6%
30
 
2.7%
28
 
2.5%
27
 
2.4%
27
 
2.4%
27
 
2.4%
27
 
2.4%
24
 
2.2%
23
 
2.1%
Other values (233) 751
67.7%
Uppercase Letter
ValueCountFrequency (%)
A 3
17.6%
M 2
11.8%
J 2
11.8%
S 2
11.8%
U 2
11.8%
K 1
 
5.9%
O 1
 
5.9%
L 1
 
5.9%
G 1
 
5.9%
I 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
1 2
33.3%
3 1
16.7%
6 1
16.7%
Letter Number
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1111
95.9%
Common 29
 
2.5%
Latin 19
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
73
 
6.6%
73
 
6.6%
30
 
2.7%
28
 
2.5%
27
 
2.4%
27
 
2.4%
27
 
2.4%
27
 
2.4%
24
 
2.2%
23
 
2.1%
Other values (234) 752
67.7%
Latin
ValueCountFrequency (%)
A 3
15.8%
M 2
10.5%
J 2
10.5%
S 2
10.5%
U 2
10.5%
K 1
 
5.3%
O 1
 
5.3%
L 1
 
5.3%
G 1
 
5.3%
I 1
 
5.3%
Other values (3) 3
15.8%
Common
ValueCountFrequency (%)
21
72.4%
2 2
 
6.9%
1 2
 
6.9%
) 1
 
3.4%
( 1
 
3.4%
3 1
 
3.4%
6 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1110
95.8%
ASCII 46
 
4.0%
Number Forms 2
 
0.2%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
73
 
6.6%
73
 
6.6%
30
 
2.7%
28
 
2.5%
27
 
2.4%
27
 
2.4%
27
 
2.4%
27
 
2.4%
24
 
2.2%
23
 
2.1%
Other values (233) 751
67.7%
ASCII
ValueCountFrequency (%)
21
45.7%
A 3
 
6.5%
2 2
 
4.3%
M 2
 
4.3%
J 2
 
4.3%
1 2
 
4.3%
S 2
 
4.3%
U 2
 
4.3%
K 1
 
2.2%
O 1
 
2.2%
Other values (8) 8
 
17.4%
None
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
50.0%
1
50.0%
Distinct192
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T21:29:52.289667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length13.595
Min length6

Characters and Unicode

Total characters2719
Distinct characters129
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

Unique185 ?
Unique (%)92.5%

Sample

1st row문경시 문경읍 새재2길 18
2nd row문경시 문경읍 새재2길 36
3rd row문경시 농암면 청화로 551-2
4th row문경시 문경읍 새재1길 47
5th row문경시 문경읍 활공장길 115
ValueCountFrequency (%)
문경읍 61
 
9.5%
문경시 51
 
7.9%
가은읍 36
 
5.6%
농암면 35
 
5.4%
마성면 32
 
5.0%
동로면 18
 
2.8%
청화로 17
 
2.6%
여우목로 14
 
2.2%
새재로 13
 
2.0%
문경대로 12
 
1.9%
Other values (257) 356
55.2%
2023-12-12T21:29:52.939263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
449
 
16.5%
1 168
 
6.2%
2 128
 
4.7%
128
 
4.7%
126
 
4.6%
114
 
4.2%
97
 
3.6%
97
 
3.6%
- 95
 
3.5%
92
 
3.4%
Other values (119) 1225
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1405
51.7%
Decimal Number 761
28.0%
Space Separator 449
 
16.5%
Dash Punctuation 95
 
3.5%
Other Punctuation 4
 
0.1%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
128
 
9.1%
126
 
9.0%
114
 
8.1%
97
 
6.9%
97
 
6.9%
92
 
6.5%
51
 
3.6%
41
 
2.9%
38
 
2.7%
37
 
2.6%
Other values (103) 584
41.6%
Decimal Number
ValueCountFrequency (%)
1 168
22.1%
2 128
16.8%
8 71
9.3%
5 66
 
8.7%
3 62
 
8.1%
9 60
 
7.9%
7 56
 
7.4%
4 54
 
7.1%
6 50
 
6.6%
0 46
 
6.0%
Space Separator
ValueCountFrequency (%)
449
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 95
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1405
51.7%
Common 1313
48.3%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
128
 
9.1%
126
 
9.0%
114
 
8.1%
97
 
6.9%
97
 
6.9%
92
 
6.5%
51
 
3.6%
41
 
2.9%
38
 
2.7%
37
 
2.6%
Other values (103) 584
41.6%
Common
ValueCountFrequency (%)
449
34.2%
1 168
 
12.8%
2 128
 
9.7%
- 95
 
7.2%
8 71
 
5.4%
5 66
 
5.0%
3 62
 
4.7%
9 60
 
4.6%
7 56
 
4.3%
4 54
 
4.1%
Other values (5) 104
 
7.9%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1405
51.7%
ASCII 1314
48.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
449
34.2%
1 168
 
12.8%
2 128
 
9.7%
- 95
 
7.2%
8 71
 
5.4%
5 66
 
5.0%
3 62
 
4.7%
9 60
 
4.6%
7 56
 
4.3%
4 54
 
4.1%
Other values (6) 105
 
8.0%
Hangul
ValueCountFrequency (%)
128
 
9.1%
126
 
9.0%
114
 
8.1%
97
 
6.9%
97
 
6.9%
92
 
6.5%
51
 
3.6%
41
 
2.9%
38
 
2.7%
37
 
2.6%
Other values (103) 584
41.6%
Distinct197
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T21:29:53.466364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length13.53
Min length6

Characters and Unicode

Total characters2706
Distinct characters106
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

Unique194 ?
Unique (%)97.0%

Sample

1st row문경시 문경읍 상초리 288-8
2nd row문경시 문경읍 상초리 288-2
3rd row문경시 농암면 내서리 273
4th row문경시 문경읍 하초리 365
5th row문경시 문경읍 고요리 72-1
ValueCountFrequency (%)
문경읍 59
 
9.1%
문경시 57
 
8.8%
가은읍 36
 
5.6%
농암면 35
 
5.4%
마성면 32
 
4.9%
내서리 27
 
4.2%
동로면 18
 
2.8%
신현리 17
 
2.6%
마원리 11
 
1.7%
하초리 11
 
1.7%
Other values (256) 345
53.2%
2023-12-12T21:29:54.218055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
459
 
17.0%
172
 
6.4%
1 141
 
5.2%
- 131
 
4.8%
119
 
4.4%
117
 
4.3%
3 113
 
4.2%
95
 
3.5%
92
 
3.4%
2 75
 
2.8%
Other values (96) 1192
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1351
49.9%
Decimal Number 750
27.7%
Space Separator 459
 
17.0%
Dash Punctuation 131
 
4.8%
Close Punctuation 7
 
0.3%
Open Punctuation 7
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
172
 
12.7%
119
 
8.8%
117
 
8.7%
95
 
7.0%
92
 
6.8%
57
 
4.2%
45
 
3.3%
43
 
3.2%
39
 
2.9%
38
 
2.8%
Other values (81) 534
39.5%
Decimal Number
ValueCountFrequency (%)
1 141
18.8%
3 113
15.1%
2 75
10.0%
4 72
9.6%
8 72
9.6%
5 67
8.9%
9 55
 
7.3%
0 55
 
7.3%
6 51
 
6.8%
7 49
 
6.5%
Space Separator
ValueCountFrequency (%)
459
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 131
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1355
50.1%
Hangul 1351
49.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
172
 
12.7%
119
 
8.8%
117
 
8.7%
95
 
7.0%
92
 
6.8%
57
 
4.2%
45
 
3.3%
43
 
3.2%
39
 
2.9%
38
 
2.8%
Other values (81) 534
39.5%
Common
ValueCountFrequency (%)
459
33.9%
1 141
 
10.4%
- 131
 
9.7%
3 113
 
8.3%
2 75
 
5.5%
4 72
 
5.3%
8 72
 
5.3%
5 67
 
4.9%
9 55
 
4.1%
0 55
 
4.1%
Other values (5) 115
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1355
50.1%
Hangul 1351
49.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
459
33.9%
1 141
 
10.4%
- 131
 
9.7%
3 113
 
8.3%
2 75
 
5.5%
4 72
 
5.3%
8 72
 
5.3%
5 67
 
4.9%
9 55
 
4.1%
0 55
 
4.1%
Other values (5) 115
 
8.5%
Hangul
ValueCountFrequency (%)
172
 
12.7%
119
 
8.8%
117
 
8.7%
95
 
7.0%
92
 
6.8%
57
 
4.2%
45
 
3.3%
43
 
3.2%
39
 
2.9%
38
 
2.8%
Other values (81) 534
39.5%

전화번호
Text

MISSING 

Distinct50
Distinct (%)98.0%
Missing149
Missing (%)74.5%
Memory size1.7 KiB
2023-12-12T21:29:54.547106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.098039
Min length9

Characters and Unicode

Total characters617
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

Unique49 ?
Unique (%)96.1%

Sample

1st row054-571-7776
2nd row054-571-7973
3rd row054-571-8998
4th row054-572-3762
5th row054-572-3340
ValueCountFrequency (%)
054-572-3340 2
 
3.9%
054-571-6542 1
 
2.0%
0507-1498-8863 1
 
2.0%
054-571-7776 1
 
2.0%
054-572-3170 1
 
2.0%
054-553-8886 1
 
2.0%
054-552-0014 1
 
2.0%
054-571-0669 1
 
2.0%
054-553-9267 1
 
2.0%
054-571-6565 1
 
2.0%
Other values (40) 40
78.4%
2023-12-12T21:29:55.002759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 124
20.1%
- 101
16.4%
0 82
13.3%
4 67
10.9%
7 65
10.5%
1 44
 
7.1%
2 37
 
6.0%
3 33
 
5.3%
8 24
 
3.9%
9 20
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 516
83.6%
Dash Punctuation 101
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 124
24.0%
0 82
15.9%
4 67
13.0%
7 65
12.6%
1 44
 
8.5%
2 37
 
7.2%
3 33
 
6.4%
8 24
 
4.7%
9 20
 
3.9%
6 20
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 617
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 124
20.1%
- 101
16.4%
0 82
13.3%
4 67
10.9%
7 65
10.5%
1 44
 
7.1%
2 37
 
6.0%
3 33
 
5.3%
8 24
 
3.9%
9 20
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 617
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 124
20.1%
- 101
16.4%
0 82
13.3%
4 67
10.9%
7 65
10.5%
1 44
 
7.1%
2 37
 
6.0%
3 33
 
5.3%
8 24
 
3.9%
9 20
 
3.2%

Interactions

2023-12-12T21:29:50.108108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:29:55.121332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번전화번호
연번1.0000.780
전화번호0.7801.000

Missing values

2023-12-12T21:29:50.288634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:29:50.437939image/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

연번펜션명도로명 주소지번 주소전화번호
01꿈꾸는새재문경시 문경읍 새재2길 18문경시 문경읍 상초리 288-8054-571-7776
12산중모텔펜션문경시 문경읍 새재2길 36문경시 문경읍 상초리 288-2054-571-7973
23해가빛문경시 농암면 청화로 551-2문경시 농암면 내서리 273054-571-8998
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