Overview

Dataset statistics

Number of variables4
Number of observations120
Missing cells72
Missing cells (%)15.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.0 KiB
Average record size in memory34.1 B

Variable types

Text3
Numeric1

Dataset

Description경상북도 경산시에 있는 식품유통판매업체 현황에 대한 데이터로 소재지주소, 우편번호, 소재지 전화번호를 제공합니다.
Author경상북도 경산시
URLhttps://www.data.go.kr/data/15030750/fileData.do

Alerts

소재지전화 has 72 (60.0%) missing valuesMissing
업소명 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:10:08.526292
Analysis finished2024-04-06 08:10:09.525588
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-06T17:10:09.918023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length7.225
Min length2

Characters and Unicode

Total characters867
Distinct characters234
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique120 ?
Unique (%)100.0%

Sample

1st row매일유업(주)경산공장
2nd row(주)도들샘
3rd row무림농산
4th row뚝배기식품
5th row대구한의대학교
ValueCountFrequency (%)
주식회사 19
 
12.2%
농업회사법인 6
 
3.8%
농원 2
 
1.3%
jw트레이더스 1
 
0.6%
마을관리 1
 
0.6%
사회적협동조합 1
 
0.6%
오러스코리아 1
 
0.6%
우인 1
 
0.6%
주)한림농원 1
 
0.6%
봉자푸드 1
 
0.6%
Other values (122) 122
78.2%
2024-04-06T17:10:10.808164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 50
 
5.8%
36
 
4.2%
( 33
 
3.8%
) 33
 
3.8%
농 28
 
3.2%
사 28
 
3.2%
회 27
 
3.1%
식 26
 
3.0%
이 23
 
2.7%
스 18
 
2.1%
Other values (224) 565
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 743
85.7%
Space Separator 36
 
4.2%
Open Punctuation 33
 
3.8%
Close Punctuation 33
 
3.8%
Uppercase Letter 18
 
2.1%
Decimal Number 3
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 50
 
6.7%
농 28
 
3.8%
사 28
 
3.8%
회 27
 
3.6%
식 26
 
3.5%
이 23
 
3.1%
스 18
 
2.4%
드 15
 
2.0%
인 14
 
1.9%
에 12
 
1.6%
Other values (206) 502
67.6%
Uppercase Letter
ValueCountFrequency (%)
A 3
16.7%
H 2
11.1%
P 2
11.1%
N 2
11.1%
G 2
11.1%
D 2
11.1%
M 1
 
5.6%
J 1
 
5.6%
W 1
 
5.6%
E 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
5 1
33.3%
6 1
33.3%
3 1
33.3%
Space Separator
ValueCountFrequency (%)
36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 743
85.7%
Common 106
 
12.2%
Latin 18
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 50
 
6.7%
농 28
 
3.8%
사 28
 
3.8%
회 27
 
3.6%
식 26
 
3.5%
이 23
 
3.1%
스 18
 
2.4%
드 15
 
2.0%
인 14
 
1.9%
에 12
 
1.6%
Other values (206) 502
67.6%
Latin
ValueCountFrequency (%)
A 3
16.7%
H 2
11.1%
P 2
11.1%
N 2
11.1%
G 2
11.1%
D 2
11.1%
M 1
 
5.6%
J 1
 
5.6%
W 1
 
5.6%
E 1
 
5.6%
Common
ValueCountFrequency (%)
36
34.0%
( 33
31.1%
) 33
31.1%
/ 1
 
0.9%
5 1
 
0.9%
6 1
 
0.9%
3 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 743
85.7%
ASCII 124
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 50
 
6.7%
농 28
 
3.8%
사 28
 
3.8%
회 27
 
3.6%
식 26
 
3.5%
이 23
 
3.1%
스 18
 
2.4%
드 15
 
2.0%
인 14
 
1.9%
에 12
 
1.6%
Other values (206) 502
67.6%
ASCII
ValueCountFrequency (%)
36
29.0%
( 33
26.6%
) 33
26.6%
A 3
 
2.4%
H 2
 
1.6%
P 2
 
1.6%
N 2
 
1.6%
G 2
 
1.6%
D 2
 
1.6%
M 1
 
0.8%
Other values (8) 8
 
6.5%

소재지(도로명)
Text

Distinct118
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-04-06T17:10:11.624719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length46
Mean length30.091667
Min length19

Characters and Unicode

Total characters3611
Distinct characters210
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

Unique116 ?
Unique (%)96.7%

Sample

1st row경상북도 경산시 진량읍 대학로 1090
2nd row경상북도 경산시 진량읍 대학로 1423-10
3rd row경상북도 경산시 압량읍 해오름길 118
4th row경상북도 경산시 와촌면 불굴사길 55
5th row경상북도 경산시 한의대로 1 (유곡동)
ValueCountFrequency (%)
경상북도 120
 
15.8%
경산시 120
 
15.8%
진량읍 19
 
2.5%
2층 15
 
2.0%
압량읍 13
 
1.7%
하양읍 11
 
1.4%
용성면 10
 
1.3%
대구대로 9
 
1.2%
자인면 8
 
1.1%
1층 7
 
0.9%
Other values (292) 429
56.4%
2024-04-06T17:10:12.671624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
641
 
17.8%
경 265
 
7.3%
1 146
 
4.0%
산 145
 
4.0%
북 129
 
3.6%
상 122
 
3.4%
도 122
 
3.4%
시 120
 
3.3%
2 119
 
3.3%
0 88
 
2.4%
Other values (200) 1714
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2113
58.5%
Space Separator 641
 
17.8%
Decimal Number 616
 
17.1%
Other Punctuation 85
 
2.4%
Close Punctuation 49
 
1.4%
Open Punctuation 49
 
1.4%
Dash Punctuation 44
 
1.2%
Uppercase Letter 14
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 265
 
12.5%
산 145
 
6.9%
북 129
 
6.1%
상 122
 
5.8%
도 122
 
5.8%
시 120
 
5.7%
로 82
 
3.9%
길 74
 
3.5%
동 73
 
3.5%
대 63
 
3.0%
Other values (179) 918
43.4%
Decimal Number
ValueCountFrequency (%)
1 146
23.7%
2 119
19.3%
0 88
14.3%
3 67
10.9%
5 48
 
7.8%
4 39
 
6.3%
8 32
 
5.2%
7 32
 
5.2%
6 25
 
4.1%
9 20
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 5
35.7%
D 4
28.6%
R 2
 
14.3%
A 2
 
14.3%
F 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 83
97.6%
& 2
 
2.4%
Space Separator
ValueCountFrequency (%)
641
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2113
58.5%
Common 1484
41.1%
Latin 14
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 265
 
12.5%
산 145
 
6.9%
북 129
 
6.1%
상 122
 
5.8%
도 122
 
5.8%
시 120
 
5.7%
로 82
 
3.9%
길 74
 
3.5%
동 73
 
3.5%
대 63
 
3.0%
Other values (179) 918
43.4%
Common
ValueCountFrequency (%)
641
43.2%
1 146
 
9.8%
2 119
 
8.0%
0 88
 
5.9%
, 83
 
5.6%
3 67
 
4.5%
) 49
 
3.3%
( 49
 
3.3%
5 48
 
3.2%
- 44
 
3.0%
Other values (6) 150
 
10.1%
Latin
ValueCountFrequency (%)
B 5
35.7%
D 4
28.6%
R 2
 
14.3%
A 2
 
14.3%
F 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2113
58.5%
ASCII 1498
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
641
42.8%
1 146
 
9.7%
2 119
 
7.9%
0 88
 
5.9%
, 83
 
5.5%
3 67
 
4.5%
) 49
 
3.3%
( 49
 
3.3%
5 48
 
3.2%
- 44
 
2.9%
Other values (11) 164
 
10.9%
Hangul
ValueCountFrequency (%)
경 265
 
12.5%
산 145
 
6.9%
북 129
 
6.1%
상 122
 
5.8%
도 122
 
5.8%
시 120
 
5.7%
로 82
 
3.9%
길 74
 
3.5%
동 73
 
3.5%
대 63
 
3.0%
Other values (179) 918
43.4%

소재지전화
Text

MISSING 

Distinct48
Distinct (%)100.0%
Missing72
Missing (%)60.0%
Memory size1.1 KiB
2024-04-06T17:10:13.136638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.166667
Min length12

Characters and Unicode

Total characters584
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

Unique48 ?
Unique (%)100.0%

Sample

1st row053-853-5666
2nd row053-852-4351
3rd row053-818-8157
4th row053-853-8487
5th row053-819-1111
ValueCountFrequency (%)
053-856-8855 1
 
2.0%
053-813-1238 1
 
2.0%
053-811-5890 1
 
2.0%
053-527-7878 1
 
2.0%
0507-1310-5439 1
 
2.0%
0507-1855-2161 1
 
2.0%
053-857-1234 1
 
2.0%
053-754-1792 1
 
2.0%
053-813-0997 1
 
2.0%
053-852-8051 1
 
2.0%
Other values (39) 39
79.6%
2024-04-06T17:10:13.905292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 96
16.4%
5 90
15.4%
0 84
14.4%
3 74
12.7%
8 63
10.8%
1 57
9.8%
7 35
 
6.0%
2 23
 
3.9%
6 21
 
3.6%
4 21
 
3.6%
Other values (2) 20
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 487
83.4%
Dash Punctuation 96
 
16.4%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 90
18.5%
0 84
17.2%
3 74
15.2%
8 63
12.9%
1 57
11.7%
7 35
 
7.2%
2 23
 
4.7%
6 21
 
4.3%
4 21
 
4.3%
9 19
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 96
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 584
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 96
16.4%
5 90
15.4%
0 84
14.4%
3 74
12.7%
8 63
10.8%
1 57
9.8%
7 35
 
6.0%
2 23
 
3.9%
6 21
 
3.6%
4 21
 
3.6%
Other values (2) 20
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 584
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 96
16.4%
5 90
15.4%
0 84
14.4%
3 74
12.7%
8 63
10.8%
1 57
9.8%
7 35
 
6.0%
2 23
 
3.9%
6 21
 
3.6%
4 21
 
3.6%
Other values (2) 20
 
3.4%

우편번호(도로명)
Real number (ℝ)

Distinct79
Distinct (%)65.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38547.992
Minimum38400
Maximum38699
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2024-04-06T17:10:14.180533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38400
5-th percentile38422
Q138470.5
median38551.5
Q338602
95-th percentile38695
Maximum38699
Range299
Interquartile range (IQR)131.5

Descriptive statistics

Standard deviation84.099031
Coefficient of variation (CV)0.0021816709
Kurtosis-0.9011815
Mean38547.992
Median Absolute Deviation (MAD)64.5
Skewness0.091726691
Sum4625759
Variance7072.647
MonotonicityNot monotonic
2024-04-06T17:10:14.434112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38695 7
 
5.8%
38578 6
 
5.0%
38453 5
 
4.2%
38569 5
 
4.2%
38542 5
 
4.2%
38428 4
 
3.3%
38454 3
 
2.5%
38541 2
 
1.7%
38422 2
 
1.7%
38539 2
 
1.7%
Other values (69) 79
65.8%
ValueCountFrequency (%)
38400 1
 
0.8%
38405 1
 
0.8%
38409 1
 
0.8%
38413 1
 
0.8%
38418 1
 
0.8%
38422 2
1.7%
38426 1
 
0.8%
38428 4
3.3%
38430 2
1.7%
38440 1
 
0.8%
ValueCountFrequency (%)
38699 1
 
0.8%
38695 7
5.8%
38688 2
 
1.7%
38687 1
 
0.8%
38678 1
 
0.8%
38677 1
 
0.8%
38673 1
 
0.8%
38671 1
 
0.8%
38668 1
 
0.8%
38658 1
 
0.8%

Interactions

2024-04-06T17:10:08.982430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:10:14.597156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지전화우편번호(도로명)
소재지전화1.0001.000
우편번호(도로명)1.0001.000

Missing values

2024-04-06T17:10:09.222124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:10:09.457663image/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

업소명소재지(도로명)소재지전화우편번호(도로명)
0매일유업(주)경산공장경상북도 경산시 진량읍 대학로 1090053-853-566638451
1(주)도들샘경상북도 경산시 진량읍 대학로 1423-10053-852-435138440
2무림농산경상북도 경산시 압량읍 해오름길 118053-818-815738540
3뚝배기식품경상북도 경산시 와촌면 불굴사길 55053-853-848738405
4대구한의대학교경상북도 경산시 한의대로 1 (유곡동)053-819-111138610
5(주)초록원경상북도 경산시 진량읍 평사1길 45-15053-852-300038455
6정화식품경상북도 경산시 대학로13길 90 (정평동)<NA>38653
7에스엠푸드(주)경상북도 경산시 남천면 협석1길 24-1053-811-933938695
8압량농업협동조합경상북도 경산시 압량읍 대학로75길 1, 2층053-817-857538511
9(주)고추나라경상북도 경산시 용성면 서원천로 288-13053-851-074038569
업소명소재지(도로명)소재지전화우편번호(도로명)
110밤가시농원경상북도 경산시 용성면 운용로 792<NA>38569
111주식회사 케이앤피푸드경상북도 경산시 남산면 인흥2길 16-15, 3층<NA>38577
112(주)오상인터내셔널경상북도 경산시 남천면 삼성길 21-8, 2층<NA>38695
113윤스팜경상북도 경산시 하양읍 환상길 31-26<NA>38483
114자연올림경상북도 경산시 남산면 하남로 229-3, 1층<NA>38572
115드빅경상북도 경산시 삼성현로91길 10, 2011동 604호 (사동, 팰리스부영2단지)<NA>38602
116주식회사 슬찬바이오경상북도 경산시 원효로 9, 4층 (중방동)<NA>38618
117까미팜경상북도 경산시 용성면 용전길 20-5<NA>38568
118달달보네하우스경상북도 경산시 용성면 곡란2길 18, 주1동<NA>38569
119허밍컴퍼니경상북도 경산시 하양읍 사열길 20-1<NA>38426