Overview

Dataset statistics

Number of variables5
Number of observations40
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory44.3 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description충청남도 보령시_보령사랑상품권판매대행점현황 자료에 대한 연번, 지점명, 주소, 전화번호 항목에 대한 공개데이터
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=330&beforeMenuCd=DOM_000000201001001000&publicdatapk=15089540

Alerts

데이터 기준일 has constant value ""Constant
연번 has unique valuesUnique
지점명 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:50:11.944333
Analysis finished2024-01-09 22:50:12.329184
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-01-10T07:50:12.391800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q110.75
median20.5
Q330.25
95-th percentile38.05
Maximum40
Range39
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2024-01-10T07:50:12.510864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
22 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%

지점명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-01-10T07:50:12.691245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length8.875
Min length5

Characters and Unicode

Total characters355
Distinct characters67
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st rowNH농협은행 보령시지부
2nd rowNH농협은행 보령시청 출장소
3rd rowNH농협은행 대천지점
4th row대천농협 본점
5th row대천농협 한내지점
ValueCountFrequency (%)
대천농협 10
 
13.5%
본점 7
 
9.5%
보령수협 4
 
5.4%
보령축협 4
 
5.4%
웅천농협 4
 
5.4%
대천신협 3
 
4.1%
nh농협은행 3
 
4.1%
대천지점 3
 
4.1%
보령우체국 2
 
2.7%
오천농협 2
 
2.7%
Other values (31) 32
43.2%
2024-01-10T07:50:12.967451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
 
11.8%
협 35
 
9.9%
점 30
 
8.5%
천 29
 
8.2%
지 24
 
6.8%
농 24
 
6.8%
대 22
 
6.2%
보 13
 
3.7%
령 13
 
3.7%
본 7
 
2.0%
Other values (57) 116
32.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 307
86.5%
Space Separator 42
 
11.8%
Uppercase Letter 6
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
협 35
 
11.4%
점 30
 
9.8%
천 29
 
9.4%
지 24
 
7.8%
농 24
 
7.8%
대 22
 
7.2%
보 13
 
4.2%
령 13
 
4.2%
본 7
 
2.3%
동 6
 
2.0%
Other values (54) 104
33.9%
Uppercase Letter
ValueCountFrequency (%)
N 3
50.0%
H 3
50.0%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 307
86.5%
Common 42
 
11.8%
Latin 6
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
협 35
 
11.4%
점 30
 
9.8%
천 29
 
9.4%
지 24
 
7.8%
농 24
 
7.8%
대 22
 
7.2%
보 13
 
4.2%
령 13
 
4.2%
본 7
 
2.3%
동 6
 
2.0%
Other values (54) 104
33.9%
Latin
ValueCountFrequency (%)
N 3
50.0%
H 3
50.0%
Common
ValueCountFrequency (%)
42
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 307
86.5%
ASCII 48
 
13.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
87.5%
N 3
 
6.2%
H 3
 
6.2%
Hangul
ValueCountFrequency (%)
협 35
 
11.4%
점 30
 
9.8%
천 29
 
9.4%
지 24
 
7.8%
농 24
 
7.8%
대 22
 
7.2%
보 13
 
4.2%
령 13
 
4.2%
본 7
 
2.3%
동 6
 
2.0%
Other values (54) 104
33.9%

주소
Text

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-01-10T07:50:13.179948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length18.025
Min length15

Characters and Unicode

Total characters721
Distinct characters76
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

Unique38 ?
Unique (%)95.0%

Sample

1st row충청남도 보령시 대천로 22
2nd row충청남도 보령시 성주산로 77
3rd row충청남도 보령시 희망1길 18
4th row충청남도 보령시 남대천로 50
5th row충청남도 보령시 중앙로 57
ValueCountFrequency (%)
충청남도 40
22.7%
보령시 40
22.7%
한내로 4
 
2.3%
남대천로 3
 
1.7%
오천면 3
 
1.7%
웅천읍 2
 
1.1%
장터중앙길 2
 
1.1%
29 2
 
1.1%
11 2
 
1.1%
머드로 2
 
1.1%
Other values (69) 76
43.2%
2024-01-10T07:50:13.500489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
137
19.0%
청 45
 
6.2%
남 44
 
6.1%
충 43
 
6.0%
도 41
 
5.7%
시 41
 
5.7%
보 40
 
5.5%
령 40
 
5.5%
로 24
 
3.3%
1 23
 
3.2%
Other values (66) 243
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 478
66.3%
Space Separator 137
 
19.0%
Decimal Number 101
 
14.0%
Dash Punctuation 5
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 45
 
9.4%
남 44
 
9.2%
충 43
 
9.0%
도 41
 
8.6%
시 41
 
8.6%
보 40
 
8.4%
령 40
 
8.4%
로 24
 
5.0%
길 16
 
3.3%
면 14
 
2.9%
Other values (54) 130
27.2%
Decimal Number
ValueCountFrequency (%)
1 23
22.8%
8 14
13.9%
4 12
11.9%
2 11
10.9%
7 11
10.9%
3 8
 
7.9%
9 7
 
6.9%
0 6
 
5.9%
5 5
 
5.0%
6 4
 
4.0%
Space Separator
ValueCountFrequency (%)
137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 478
66.3%
Common 243
33.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 45
 
9.4%
남 44
 
9.2%
충 43
 
9.0%
도 41
 
8.6%
시 41
 
8.6%
보 40
 
8.4%
령 40
 
8.4%
로 24
 
5.0%
길 16
 
3.3%
면 14
 
2.9%
Other values (54) 130
27.2%
Common
ValueCountFrequency (%)
137
56.4%
1 23
 
9.5%
8 14
 
5.8%
4 12
 
4.9%
2 11
 
4.5%
7 11
 
4.5%
3 8
 
3.3%
9 7
 
2.9%
0 6
 
2.5%
- 5
 
2.1%
Other values (2) 9
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 478
66.3%
ASCII 243
33.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
137
56.4%
1 23
 
9.5%
8 14
 
5.8%
4 12
 
4.9%
2 11
 
4.5%
7 11
 
4.5%
3 8
 
3.3%
9 7
 
2.9%
0 6
 
2.5%
- 5
 
2.1%
Other values (2) 9
 
3.7%
Hangul
ValueCountFrequency (%)
청 45
 
9.4%
남 44
 
9.2%
충 43
 
9.0%
도 41
 
8.6%
시 41
 
8.6%
보 40
 
8.4%
령 40
 
8.4%
로 24
 
5.0%
길 16
 
3.3%
면 14
 
2.9%
Other values (54) 130
27.2%

전화번호
Text

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-01-10T07:50:13.687002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.25
Min length12

Characters and Unicode

Total characters490
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

Unique38 ?
Unique (%)95.0%

Sample

1st row041-939-9241
2nd row041-932-6141
3rd row041-934-6970
4th row041-935-0144
5th row041-935-0141
ValueCountFrequency (%)
041-935-0134 2
 
5.0%
041-931-4059 1
 
2.5%
041-933-9767 1
 
2.5%
041-933-6600 1
 
2.5%
041-933-6161 1
 
2.5%
041-933-2130 1
 
2.5%
041-934-1559 1
 
2.5%
041-931-3350 1
 
2.5%
041-931-0241 1
 
2.5%
041-931-2010 1
 
2.5%
Other values (29) 29
72.5%
2024-01-10T07:50:13.969661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 80
16.3%
0 79
16.1%
1 79
16.1%
4 66
13.5%
3 59
12.0%
9 49
10.0%
5 22
 
4.5%
6 16
 
3.3%
2 14
 
2.9%
10
 
2.0%
Other values (2) 16
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 400
81.6%
Dash Punctuation 80
 
16.3%
Space Separator 10
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 79
19.8%
1 79
19.8%
4 66
16.5%
3 59
14.8%
9 49
12.2%
5 22
 
5.5%
6 16
 
4.0%
2 14
 
3.5%
7 9
 
2.2%
8 7
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 490
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 80
16.3%
0 79
16.1%
1 79
16.1%
4 66
13.5%
3 59
12.0%
9 49
10.0%
5 22
 
4.5%
6 16
 
3.3%
2 14
 
2.9%
10
 
2.0%
Other values (2) 16
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 80
16.3%
0 79
16.1%
1 79
16.1%
4 66
13.5%
3 59
12.0%
9 49
10.0%
5 22
 
4.5%
6 16
 
3.3%
2 14
 
2.9%
10
 
2.0%
Other values (2) 16
 
3.3%

데이터 기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-02-27
40 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-02-27
2nd row2023-02-27
3rd row2023-02-27
4th row2023-02-27
5th row2023-02-27

Common Values

ValueCountFrequency (%)
2023-02-27 40
100.0%

Length

2024-01-10T07:50:14.086900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:50:14.183298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-02-27 40
100.0%

Interactions

2024-01-10T07:50:12.123996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:50:14.235640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지점명주소전화번호
연번1.0001.0001.0001.000
지점명1.0001.0001.0001.000
주소1.0001.0001.0001.000
전화번호1.0001.0001.0001.000

Missing values

2024-01-10T07:50:12.221803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:50:12.296093image/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

연번지점명주소전화번호데이터 기준일
01NH농협은행 보령시지부충청남도 보령시 대천로 22041-939-92412023-02-27
12NH농협은행 보령시청 출장소충청남도 보령시 성주산로 77041-932-61412023-02-27
23NH농협은행 대천지점충청남도 보령시 희망1길 18041-934-69702023-02-27
34대천농협 본점충청남도 보령시 남대천로 50041-935-01442023-02-27
45대천농협 한내지점충청남도 보령시 중앙로 57041-935-01412023-02-27
56대천농협 해수욕장지점충청남도 보령시 머드로 11041-934-00832023-02-27
67대천농협 명천지점충청남도 보령시 한내로 82041-935-01342023-02-27
78대천농협 동대지점충청남도 보령시 한내로 82041-935-01342023-02-27
89대천농협 주교지점충청남도 보령시 주교면 올계큰길 388041-931-13412023-02-27
910대천농협 주포지점충청남도 보령시 주포면 질재로 47-61041-931-13482023-02-27
연번지점명주소전화번호데이터 기준일
3031보령수협 대천항지점충청남도 보령시 대천항중앙길 72041-933-97672023-02-27
3132보령수협 오천지점충청남도 보령시 오천면 오천해안로 781-15041-931-40592023-02-27
3233대천신협 본점충청남도 보령시 한내로 11041-930-70002023-02-27
3334대천신협 대천지점충청남도 보령시 원동2길 47041-934-43512023-02-27
3435대천신협 신흑지점충청남도 보령시 해수욕장6길 104041-931-12412023-02-27
3536보령시새마을금고충청남도 보령시 한내시장길 27041-931-32002023-02-27
3637웅천새마을금고충청남도 보령시 웅천읍 장터중앙길 130041-934-25602023-02-27
3738보령우체국 본점충청남도 보령시 터미널길 29041-930-77182023-02-27
3839보령우체국 대천동우체국충청남도 보령시 중앙로 78041-931-20102023-02-27
3940하나은행 대천지점충청남도 보령시 남대천로 40041-935-11112023-02-27