Overview

Dataset statistics

Number of variables8
Number of observations103
Missing cells59
Missing cells (%)7.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.7 KiB
Average record size in memory66.3 B

Variable types

Numeric1
Categorical2
Text4
DateTime1

Alerts

데이터기준일자 has constant value ""Constant
순서 is highly overall correlated with 지역 and 1 other fieldsHigh correlation
지역 is highly overall correlated with 순서 and 1 other fieldsHigh correlation
업종 is highly overall correlated with 순서 and 1 other fieldsHigh correlation
전화번호 has 58 (56.3%) missing valuesMissing
순서 has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:54:21.855238
Analysis finished2024-03-14 00:54:22.476643
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순서
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct103
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52
Minimum1
Maximum103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-14T09:54:22.542790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.1
Q126.5
median52
Q377.5
95-th percentile97.9
Maximum103
Range102
Interquartile range (IQR)51

Descriptive statistics

Standard deviation29.877528
Coefficient of variation (CV)0.57456784
Kurtosis-1.2
Mean52
Median Absolute Deviation (MAD)26
Skewness0
Sum5356
Variance892.66667
MonotonicityStrictly increasing
2024-03-14T09:54:22.674564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
2 1
 
1.0%
77 1
 
1.0%
76 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
Other values (93) 93
90.3%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
103 1
1.0%
102 1
1.0%
101 1
1.0%
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%

지역
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Memory size956.0 B
완주군
54 
익산시
12 
장수군
전주시
 
4
정읍시
 
4
Other values (8)
23 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)1.9%

Sample

1st row전주시
2nd row전주시
3rd row전주시
4th row전주시
5th row군산시

Common Values

ValueCountFrequency (%)
완주군 54
52.4%
익산시 12
 
11.7%
장수군 6
 
5.8%
전주시 4
 
3.9%
정읍시 4
 
3.9%
진안군 4
 
3.9%
임실군 4
 
3.9%
고창군 4
 
3.9%
부안군 4
 
3.9%
군산시 3
 
2.9%
Other values (3) 4
 
3.9%

Length

2024-03-14T09:54:22.802442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
완주군 54
52.4%
익산시 12
 
11.7%
장수군 6
 
5.8%
전주시 4
 
3.9%
정읍시 4
 
3.9%
진안군 4
 
3.9%
임실군 4
 
3.9%
고창군 4
 
3.9%
부안군 4
 
3.9%
군산시 3
 
2.9%
Other values (3) 4
 
3.9%

업종
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size956.0 B
식품제조가공업
39 
기타김치
38 
배추김치
11 
식품제조
즉석섭취식품
Other values (3)

Length

Max length23
Median length4
Mean length5.7378641
Min length3

Unique

Unique2 ?
Unique (%)1.9%

Sample

1st row식품제조가공업
2nd row식품제조가공업
3rd row식품제조가공업
4th row식품제조가공업
5th row식품제조가공업

Common Values

ValueCountFrequency (%)
식품제조가공업 39
37.9%
기타김치 38
36.9%
배추김치 11
 
10.7%
식품제조 6
 
5.8%
즉석섭취식품 4
 
3.9%
과실 및 채소 절임식품 제조업 3
 
2.9%
조미김 1
 
1.0%
수산동물 건조 및 염장품 제조업 외 1 종 1
 
1.0%

Length

2024-03-14T09:54:22.954765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:54:23.105442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품제조가공업 39
32.0%
기타김치 38
31.1%
배추김치 11
 
9.0%
식품제조 6
 
4.9%
즉석섭취식품 4
 
3.3%
제조업 4
 
3.3%
4
 
3.3%
절임식품 3
 
2.5%
채소 3
 
2.5%
과실 3
 
2.5%
Other values (7) 7
 
5.7%
Distinct63
Distinct (%)61.2%
Missing0
Missing (%)0.0%
Memory size956.0 B
2024-03-14T09:54:23.328379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16
Mean length8.1067961
Min length3

Characters and Unicode

Total characters835
Distinct characters150
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)52.4%

Sample

1st row농업회사법인(유)새만금식품
2nd row농업회사법인 유한회사 오성식품외갓집김치
3rd row유한회사맛디자인
4th row대중식품
5th row(주) 김장독
ValueCountFrequency (%)
도계정보화두부김치마을 10
 
7.9%
행복한집 8
 
6.3%
산야식품 7
 
5.5%
온신정식품 7
 
5.5%
둔지메반찬가게영농조합법인 5
 
3.9%
농업회사법인 5
 
3.9%
검태골식품 4
 
3.1%
주식회사 4
 
3.1%
농가의 3
 
2.4%
부엌 3
 
2.4%
Other values (66) 71
55.9%
2024-03-14T09:54:23.685203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
 
5.7%
42
 
5.0%
31
 
3.7%
25
 
3.0%
24
 
2.9%
23
 
2.8%
22
 
2.6%
21
 
2.5%
20
 
2.4%
) 18
 
2.2%
Other values (140) 561
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 777
93.1%
Space Separator 24
 
2.9%
Close Punctuation 18
 
2.2%
Open Punctuation 14
 
1.7%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
48
 
6.2%
42
 
5.4%
31
 
4.0%
25
 
3.2%
23
 
3.0%
22
 
2.8%
21
 
2.7%
20
 
2.6%
17
 
2.2%
17
 
2.2%
Other values (135) 511
65.8%
Uppercase Letter
ValueCountFrequency (%)
M 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 777
93.1%
Common 56
 
6.7%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
48
 
6.2%
42
 
5.4%
31
 
4.0%
25
 
3.2%
23
 
3.0%
22
 
2.8%
21
 
2.7%
20
 
2.6%
17
 
2.2%
17
 
2.2%
Other values (135) 511
65.8%
Common
ValueCountFrequency (%)
24
42.9%
) 18
32.1%
( 14
25.0%
Latin
ValueCountFrequency (%)
M 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 777
93.1%
ASCII 58
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
48
 
6.2%
42
 
5.4%
31
 
4.0%
25
 
3.2%
23
 
3.0%
22
 
2.8%
21
 
2.7%
20
 
2.6%
17
 
2.2%
17
 
2.2%
Other values (135) 511
65.8%
ASCII
ValueCountFrequency (%)
24
41.4%
) 18
31.0%
( 14
24.1%
M 1
 
1.7%
G 1
 
1.7%
Distinct65
Distinct (%)63.7%
Missing1
Missing (%)1.0%
Memory size956.0 B
2024-03-14T09:54:23.856169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length85
Median length39
Mean length9.254902
Min length2

Characters and Unicode

Total characters944
Distinct characters124
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)51.0%

Sample

1st row배추김치,기타김치,절임류
2nd row배추김치,기타김치
3rd row배추김치,기타김치
4th row김치류
5th row김치
ValueCountFrequency (%)
김치류 14
 
13.7%
배추김치 4
 
3.9%
열무김치 4
 
3.9%
김치 4
 
3.9%
고들빼기김치 3
 
2.9%
파김치 3
 
2.9%
기타김치 3
 
2.9%
배추김치,기타김치 3
 
2.9%
깻잎김치 3
 
2.9%
맛김치 3
 
2.9%
Other values (55) 58
56.9%
2024-03-14T09:54:24.150566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
 
12.7%
118
 
12.5%
, 82
 
8.7%
55
 
5.8%
34
 
3.6%
33
 
3.5%
28
 
3.0%
19
 
2.0%
17
 
1.8%
17
 
1.8%
Other values (114) 421
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 858
90.9%
Other Punctuation 82
 
8.7%
Uppercase Letter 2
 
0.2%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
120
 
14.0%
118
 
13.8%
55
 
6.4%
34
 
4.0%
33
 
3.8%
28
 
3.3%
19
 
2.2%
17
 
2.0%
17
 
2.0%
17
 
2.0%
Other values (111) 400
46.6%
Other Punctuation
ValueCountFrequency (%)
, 82
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 858
90.9%
Common 84
 
8.9%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
120
 
14.0%
118
 
13.8%
55
 
6.4%
34
 
4.0%
33
 
3.8%
28
 
3.3%
19
 
2.2%
17
 
2.0%
17
 
2.0%
17
 
2.0%
Other values (111) 400
46.6%
Common
ValueCountFrequency (%)
, 82
97.6%
- 2
 
2.4%
Latin
ValueCountFrequency (%)
A 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 858
90.9%
ASCII 86
 
9.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
120
 
14.0%
118
 
13.8%
55
 
6.4%
34
 
4.0%
33
 
3.8%
28
 
3.3%
19
 
2.2%
17
 
2.0%
17
 
2.0%
17
 
2.0%
Other values (111) 400
46.6%
ASCII
ValueCountFrequency (%)
, 82
95.3%
A 2
 
2.3%
- 2
 
2.3%

주소
Text

Distinct63
Distinct (%)61.2%
Missing0
Missing (%)0.0%
Memory size956.0 B
2024-03-14T09:54:24.615989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/