Overview

Dataset statistics

Number of variables6
Number of observations40
Missing cells70
Missing cells (%)29.2%
Duplicate rows1
Duplicate rows (%)2.5%
Total size in memory2.0 KiB
Average record size in memory52.3 B

Variable types

Numeric1
Text4
Categorical1

Dataset

Description충청남도 홍성군의 모범음식점 현황으로, 연번, 업소명, 소재지, 연락처, 주메뉴, 데이터기준일자 정보를 포함하고 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=450&beforeMenuCd=DOM_000000201001001000&publicdatapk=3073574

Alerts

Dataset has 1 (2.5%) duplicate rowsDuplicates
연번 is highly overall correlated with 데이터기준일자High correlation
데이터기준일자 is highly overall correlated with 연번High correlation
연번 has 14 (35.0%) missing valuesMissing
업소명 has 14 (35.0%) missing valuesMissing
소재지 has 14 (35.0%) missing valuesMissing
연락처 has 14 (35.0%) missing valuesMissing
주메뉴 has 14 (35.0%) missing valuesMissing

Reproduction

Analysis started2024-01-09 22:57:06.285142
Analysis finished2024-01-09 22:57:06.891888
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct26
Distinct (%)100.0%
Missing14
Missing (%)35.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-01-10T07:57:06.950940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2024-01-10T07:57:07.057020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
15 1
 
2.5%
26 1
 
2.5%
25 1
 
2.5%
24 1
 
2.5%
23 1
 
2.5%
22 1
 
2.5%
21 1
 
2.5%
20 1
 
2.5%
19 1
 
2.5%
18 1
 
2.5%
Other values (16) 16
40.0%
(Missing) 14
35.0%
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 (%)
26 1
2.5%
25 1
2.5%
24 1
2.5%
23 1
2.5%
22 1
2.5%
21 1
2.5%
20 1
2.5%
19 1
2.5%
18 1
2.5%
17 1
2.5%

업소명
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing14
Missing (%)35.0%
Memory size452.0 B
2024-01-10T07:57:07.233088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length5.4615385
Min length3

Characters and Unicode

Total characters142
Distinct characters88
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row한올채
2nd row한우本
3rd row㈜케이알산업홍성 (상)휴게소
4th row코리아식당
5th row예당큰집
ValueCountFrequency (%)
㈜케이알산업홍성 2
 
6.9%
한우本 1
 
3.4%
달평석갈비 1
 
3.4%
남해횟집수산 1
 
3.4%
일미옥불고기 1
 
3.4%
대어횟집 1
 
3.4%
조양아구찜 1
 
3.4%
등나무 1
 
3.4%
삽다리곱창전문집 1
 
3.4%
갯마을횟집 1
 
3.4%
Other values (18) 18
62.1%
2024-01-10T07:57:07.532165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 5
 
3.5%
집 5
 
3.5%
당 5
 
3.5%
4
 
2.8%
가 4
 
2.8%
리 3
 
2.1%
한 3
 
2.1%
횟 3
 
2.1%
이 3
 
2.1%
식 3
 
2.1%
Other values (78) 104
73.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 132
93.0%
Space Separator 4
 
2.8%
Open Punctuation 2
 
1.4%
Close Punctuation 2
 
1.4%
Other Symbol 2
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 5
 
3.8%
집 5
 
3.8%
당 5
 
3.8%
가 4
 
3.0%
리 3
 
2.3%
한 3
 
2.3%
횟 3
 
2.3%
이 3
 
2.3%
식 3
 
2.3%
네 2
 
1.5%
Other values (74) 96
72.7%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133
93.7%
Common 8
 
5.6%
Han 1
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 5
 
3.8%
집 5
 
3.8%
당 5
 
3.8%
가 4
 
3.0%
리 3
 
2.3%
한 3
 
2.3%
횟 3
 
2.3%
이 3
 
2.3%
식 3
 
2.3%
네 2
 
1.5%
Other values (74) 97
72.9%
Common
ValueCountFrequency (%)
4
50.0%
( 2
25.0%
) 2
25.0%
Han
ValueCountFrequency (%)
本 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 131
92.3%
ASCII 8
 
5.6%
None 2
 
1.4%
CJK 1
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 5
 
3.8%
집 5
 
3.8%
당 5
 
3.8%
가 4
 
3.1%
리 3
 
2.3%
한 3
 
2.3%
횟 3
 
2.3%
이 3
 
2.3%
식 3
 
2.3%
네 2
 
1.5%
Other values (73) 95
72.5%
ASCII
ValueCountFrequency (%)
4
50.0%
( 2
25.0%
) 2
25.0%
None
ValueCountFrequency (%)
㈜ 2
100.0%
CJK
ValueCountFrequency (%)
本 1
100.0%

소재지
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing14
Missing (%)35.0%
Memory size452.0 B
2024-01-10T07:57:07.743097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length24.384615
Min length20

Characters and Unicode

Total characters634
Distinct characters67
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

Unique26 ?
Unique (%)100.0%

Sample

1st row 충청남도 홍성군 금마면 광금북로 419
2nd row 충청남도 홍성군 홍성읍 문화로72번길 29
3rd row 충청남도 홍성군 은하면 서해안고속도로 220
4th row 충청남도 홍성군 홍성읍 홍성천길 136
5th row 충청남도 홍성군 장곡면 무한로 957-18
ValueCountFrequency (%)
충청남도 26
20.0%
홍성군 26
20.0%
홍성읍 16
 
12.3%
10 2
 
1.5%
홍북읍 2
 
1.5%
서부면 2
 
1.5%
홍덕서로 2
 
1.5%
남당항로 2
 
1.5%
서해안고속도로 2
 
1.5%
은하면 2
 
1.5%
Other values (48) 48
36.9%
2024-01-10T07:57:08.089061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
172
27.1%
홍 47
 
7.4%
성 43
 
6.8%
도 30
 
4.7%
청 28
 
4.4%
남 28
 
4.4%
충 27
 
4.3%
군 26
 
4.1%
로 21
 
3.3%
읍 19
 
3.0%
Other values (57) 193
30.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 371
58.5%
Space Separator 172
27.1%
Decimal Number 86
 
13.6%
Dash Punctuation 5
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
홍 47
12.7%
성 43
11.6%
도 30
 
8.1%
청 28
 
7.5%
남 28
 
7.5%
충 27
 
7.3%
군 26
 
7.0%
로 21
 
5.7%
읍 19
 
5.1%
길 12
 
3.2%
Other values (45) 90
24.3%
Decimal Number
ValueCountFrequency (%)
2 15
17.4%
1 13
15.1%
8 11
12.8%
6 10
11.6%
9 7
8.1%
5 7
8.1%
3 7
8.1%
0 7
8.1%
7 5
 
5.8%
4 4
 
4.7%
Space Separator
ValueCountFrequency (%)
172
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 371
58.5%
Common 263
41.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
홍 47
12.7%
성 43
11.6%
도 30
 
8.1%
청 28
 
7.5%
남 28
 
7.5%
충 27
 
7.3%
군 26
 
7.0%
로 21
 
5.7%
읍 19
 
5.1%
길 12
 
3.2%
Other values (45) 90
24.3%
Common
ValueCountFrequency (%)
172
65.4%
2 15
 
5.7%
1 13
 
4.9%
8 11
 
4.2%
6 10
 
3.8%
9 7
 
2.7%
5 7
 
2.7%
3 7
 
2.7%
0 7
 
2.7%
7 5
 
1.9%
Other values (2) 9
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 371
58.5%
ASCII 263
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
172
65.4%
2 15
 
5.7%
1 13
 
4.9%
8 11
 
4.2%
6 10
 
3.8%
9 7
 
2.7%
5 7
 
2.7%
3 7
 
2.7%
0 7
 
2.7%
7 5
 
1.9%
Other values (2) 9
 
3.4%
Hangul
ValueCountFrequency (%)
홍 47
12.7%
성 43
11.6%
도 30
 
8.1%
청 28
 
7.5%
남 28
 
7.5%
충 27
 
7.3%
군 26
 
7.0%
로 21
 
5.7%
읍 19
 
5.1%
길 12
 
3.2%
Other values (45) 90
24.3%

연락처
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing14
Missing (%)35.0%
Memory size452.0 B
2024-01-10T07:57:08.270979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters312
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

Unique26 ?
Unique (%)100.0%

Sample

1st row041-634-6292
2nd row041-634-2292
3rd row041-642-1151
4th row041-631-7600
5th row041-642-3833
ValueCountFrequency (%)
041-634-2292 1
 
3.8%
041-642-1151 1
 
3.8%
041-631-6944 1
 
3.8%
041-631-9555 1
 
3.8%
041-632-3319 1
 
3.8%
041-634-2990 1
 
3.8%
041-632-6686 1
 
3.8%
041-631-3399 1
 
3.8%
041-634-0362 1
 
3.8%
041-631-3969 1
 
3.8%
Other values (16) 16
61.5%
2024-01-10T07:57:08.554803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 52
16.7%
1 50
16.0%
0 41
13.1%
6 40
12.8%
4 38
12.2%
3 35
11.2%
2 21
6.7%
9 15
 
4.8%
5 10
 
3.2%
7 6
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 260
83.3%
Dash Punctuation 52
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 50
19.2%
0 41
15.8%
6 40
15.4%
4 38
14.6%
3 35
13.5%
2 21
8.1%
9 15
 
5.8%
5 10
 
3.8%
7 6
 
2.3%
8 4
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 52
16.7%
1 50
16.0%
0 41
13.1%
6 40
12.8%
4 38
12.2%
3 35
11.2%
2 21
6.7%
9 15
 
4.8%
5 10
 
3.2%
7 6
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 52
16.7%
1 50
16.0%
0 41
13.1%
6 40
12.8%
4 38
12.2%
3 35
11.2%
2 21
6.7%
9 15
 
4.8%
5 10
 
3.2%
7 6
 
1.9%

주메뉴
Text

MISSING 

Distinct19
Distinct (%)73.1%
Missing14
Missing (%)35.0%
Memory size452.0 B
2024-01-10T07:57:08.714326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length4.5769231
Min length2

Characters and Unicode

Total characters119
Distinct characters49
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)57.7%

Sample

1st row오리백숙
2nd row한정식
3rd row한식, 면류
4th row아나고탕
5th row한정식
ValueCountFrequency (%)
한정식 4
 
12.9%
생선회 3
 
9.7%
삼계탕 3
 
9.7%
한식 3
 
9.7%
면류 2
 
6.5%
한우생갈비 2
 
6.5%
오리백숙 1
 
3.2%
굴밥 1
 
3.2%
돼지석갈비 1
 
3.2%
불고기,시래기밥 1
 
3.2%
Other values (10) 10
32.3%
2024-01-10T07:57:09.018981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
한 9
 
7.6%
식 8
 
6.7%
, 7
 
5.9%
탕 6
 
5.0%
생 5
 
4.2%
정 5
 
4.2%
5
 
4.2%
갈 4
 
3.4%
삼 4
 
3.4%
비 4
 
3.4%
Other values (39) 62
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107
89.9%
Other Punctuation 7
 
5.9%
Space Separator 5
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 9
 
8.4%
식 8
 
7.5%
탕 6
 
5.6%
생 5
 
4.7%
정 5
 
4.7%
갈 4
 
3.7%
삼 4
 
3.7%
비 4
 
3.7%
구 4
 
3.7%
오 3
 
2.8%
Other values (37) 55
51.4%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 107
89.9%
Common 12
 
10.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 9
 
8.4%
식 8
 
7.5%
탕 6
 
5.6%
생 5
 
4.7%
정 5
 
4.7%
갈 4
 
3.7%
삼 4
 
3.7%
비 4
 
3.7%
구 4
 
3.7%
오 3
 
2.8%
Other values (37) 55
51.4%
Common
ValueCountFrequency (%)
, 7
58.3%
5
41.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 107
89.9%
ASCII 12
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
한 9
 
8.4%
식 8
 
7.5%
탕 6
 
5.6%
생 5
 
4.7%
정 5
 
4.7%
갈 4
 
3.7%
삼 4
 
3.7%
비 4
 
3.7%
구 4
 
3.7%
오 3
 
2.8%
Other values (37) 55
51.4%
ASCII
ValueCountFrequency (%)
, 7
58.3%
5
41.7%

데이터기준일자
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-09-27
26 
<NA>
14 

Length

Max length10
Median length10
Mean length7.9
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-27
2nd row2023-09-27
3rd row2023-09-27
4th row2023-09-27
5th row2023-09-27

Common Values

ValueCountFrequency (%)
2023-09-27 26
65.0%
<NA> 14
35.0%

Length

2024-01-10T07:57:09.137219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:57:09.230422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-27 26
65.0%
na 14
35.0%

Interactions

2024-01-10T07:57:06.519673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:57:09.289976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명소재지연락처주메뉴
연번1.0001.0001.0001.0000.665
업소명1.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.000
주메뉴0.6651.0001.0001.0001.000
2024-01-10T07:57:09.376031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번데이터기준일자
연번1.0001.000
데이터기준일자1.0001.000

Missing values

2024-01-10T07:57:06.622262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:57:06.719446image/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.
2024-01-10T07:57:06.819831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번업소명소재지연락처주메뉴데이터기준일자
01한올채충청남도 홍성군 금마면 광금북로 419041-634-6292오리백숙2023-09-27
12한우本충청남도 홍성군 홍성읍 문화로72번길 29041-634-2292한정식2023-09-27
23㈜케이알산업홍성 (상)휴게소충청남도 홍성군 은하면 서해안고속도로 220041-642-1151한식, 면류2023-09-27
34코리아식당충청남도 홍성군 홍성읍 홍성천길 136041-631-7600아나고탕2023-09-27
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