Overview

Dataset statistics

Number of variables5
Number of observations277
Missing cells73
Missing cells (%)5.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.5 KiB
Average record size in memory42.5 B

Variable types

Numeric2
Text3

Dataset

Description대구광역시_축산가공업체 현황_20200306
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15042998&dataSetDetailId=150429981a10b1048a5b0&provdMethod=FILE

Alerts

업소전화번호 has 73 (26.4%) missing valuesMissing
연번 has unique valuesUnique
인허가번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:22:49.208734
Analysis finished2023-12-10 17:22:53.018582
Duration3.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct277
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139
Minimum1
Maximum277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T02:22:53.184902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.8
Q170
median139
Q3208
95-th percentile263.2
Maximum277
Range276
Interquartile range (IQR)138

Descriptive statistics

Standard deviation80.10722
Coefficient of variation (CV)0.57631093
Kurtosis-1.2
Mean139
Median Absolute Deviation (MAD)69
Skewness0
Sum38503
Variance6417.1667
MonotonicityStrictly increasing
2023-12-11T02:22:53.540434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
184 1
 
0.4%
190 1
 
0.4%
189 1
 
0.4%
188 1
 
0.4%
187 1
 
0.4%
186 1
 
0.4%
185 1
 
0.4%
183 1
 
0.4%
175 1
 
0.4%
Other values (267) 267
96.4%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
277 1
0.4%
276 1
0.4%
275 1
0.4%
274 1
0.4%
273 1
0.4%
272 1
0.4%
271 1
0.4%
270 1
0.4%
269 1
0.4%
268 1
0.4%

인허가번호
Real number (ℝ)

UNIQUE 

Distinct277
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0129112 × 1010
Minimum1.9850157 × 1010
Maximum2.0200158 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T02:22:53.944894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9850157 × 1010
5-th percentile2.0038157 × 1010
Q12.0110157 × 1010
median2.0130157 × 1010
Q32.0160157 × 1010
95-th percentile2.0190158 × 1010
Maximum2.0200158 × 1010
Range3.50001 × 108
Interquartile range (IQR)50000007

Descriptive statistics

Standard deviation51317385
Coefficient of variation (CV)0.0025494113
Kurtosis5.5747954
Mean2.0129112 × 1010
Median Absolute Deviation (MAD)29999939
Skewness-1.7934336
Sum5.575764 × 1012
Variance2.633474 × 1015
MonotonicityNot monotonic
2023-12-11T02:22:54.318582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180158003 1
 
0.4%
20180158008 1
 
0.4%
20160157014 1
 
0.4%
20170157015 1
 
0.4%
20130157076 1
 
0.4%
20130157024 1
 
0.4%
20050157001 1
 
0.4%
20130157040 1
 
0.4%
20090157004 1
 
0.4%
20120157011 1
 
0.4%
Other values (267) 267
96.4%
ValueCountFrequency (%)
19850157002 1
0.4%
19870157001 1
0.4%
19940157001 1
0.4%
19970157001 1
0.4%
19970157002 1
0.4%
19980157001 1
0.4%
20000157001 1
0.4%
20000157005 1
0.4%
20020157001 1
0.4%
20030157001 1
0.4%
ValueCountFrequency (%)
20200158005 1
0.4%
20200158004 1
0.4%
20200158003 1
0.4%
20200158002 1
0.4%
20200158001 1
0.4%
20190158022 1
0.4%
20190158021 1
0.4%
20190158019 1
0.4%
20190158018 1
0.4%
20190158017 1
0.4%

업소명
Text

Distinct274
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-11T02:22:54.941201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length5.8267148
Min length2

Characters and Unicode

Total characters1614
Distinct characters272
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

Unique271 ?
Unique (%)97.8%

Sample

1st row(주)가온푸드
2nd row(주)거인축산
3rd row(주)국보푸드시스템
4th row(주)기영
5th row(주)다담
ValueCountFrequency (%)
주식회사 10
 
3.2%
농업회사법인 5
 
1.6%
에이스식품 2
 
0.6%
풀토래(주 2
 
0.6%
은성유통 2
 
0.6%
주)진우식품 2
 
0.6%
food 2
 
0.6%
옥이네식품 1
 
0.3%
에이원 1
 
0.3%
여물게 1
 
0.3%
Other values (282) 282
91.0%
2023-12-11T02:22:55.953522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
푸 90
 
5.6%
드 86
 
5.3%
식 84
 
5.2%
주 75
 
4.6%
품 72
 
4.5%
( 67
 
4.2%
) 67
 
4.2%
33
 
2.0%
유 28
 
1.7%
스 26
 
1.6%
Other values (262) 986
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1388
86.0%
Open Punctuation 67
 
4.2%
Close Punctuation 67
 
4.2%
Uppercase Letter 53
 
3.3%
Space Separator 33
 
2.0%
Other Punctuation 3
 
0.2%
Lowercase Letter 2
 
0.1%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
푸 90
 
6.5%
드 86
 
6.2%
식 84
 
6.1%
주 75
 
5.4%
품 72
 
5.2%
유 28
 
2.0%
스 26
 
1.9%
통 26
 
1.9%
사 25
 
1.8%
성 24
 
1.7%
Other values (237) 852
61.4%
Uppercase Letter
ValueCountFrequency (%)
S 9
17.0%
D 7
13.2%
F 6
11.3%
O 4
 
7.5%
J 4
 
7.5%
G 3
 
5.7%
C 3
 
5.7%
B 3
 
5.7%
E 2
 
3.8%
Y 2
 
3.8%
Other values (8) 10
18.9%
Lowercase Letter
ValueCountFrequency (%)
f 1
50.0%
c 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 67
100.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Other Punctuation
ValueCountFrequency (%)
& 3
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1388
86.0%
Common 171
 
10.6%
Latin 55
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
푸 90
 
6.5%
드 86
 
6.2%
식 84
 
6.1%
주 75
 
5.4%
품 72
 
5.2%
유 28
 
2.0%
스 26
 
1.9%
통 26
 
1.9%
사 25
 
1.8%
성 24
 
1.7%
Other values (237) 852
61.4%
Latin
ValueCountFrequency (%)
S 9
16.4%
D 7
12.7%
F 6
10.9%
O 4
 
7.3%
J 4
 
7.3%
G 3
 
5.5%
C 3
 
5.5%
B 3
 
5.5%
E 2
 
3.6%
Y 2
 
3.6%
Other values (10) 12
21.8%
Common
ValueCountFrequency (%)
( 67
39.2%
) 67
39.2%
33
19.3%
& 3
 
1.8%
1 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1388
86.0%
ASCII 226
 
14.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
푸 90
 
6.5%
드 86
 
6.2%
식 84
 
6.1%
주 75
 
5.4%
품 72
 
5.2%
유 28
 
2.0%
스 26
 
1.9%
통 26
 
1.9%
사 25
 
1.8%
성 24
 
1.7%
Other values (237) 852
61.4%
ASCII
ValueCountFrequency (%)
( 67
29.6%
) 67
29.6%
33
14.6%
S 9
 
4.0%
D 7
 
3.1%
F 6
 
2.7%
O 4
 
1.8%
J 4
 
1.8%
G 3
 
1.3%
& 3
 
1.3%
Other values (15) 23
 
10.2%

업소주소
Text

Distinct275
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-11T02:22:56.625753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length37
Mean length25.191336
Min length19

Characters and Unicode

Total characters6978
Distinct characters180
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

Unique273 ?
Unique (%)98.6%

Sample

1st row대구광역시 북구 노원로47길 17 (침산동)
2nd row대구광역시 서구 서대구로6길 6 (내당동)
3rd row대구광역시 북구 연암로42길 5 (산격동)
4th row대구광역시 달서구 앞산순환로 249 (송현동)
5th row대구광역시 달서구 성서동로 154 (월암동)
ValueCountFrequency (%)
대구광역시 277
 
19.6%
북구 90
 
6.4%
달성군 55
 
3.9%
서구 37
 
2.6%
동구 36
 
2.5%
달서구 32
 
2.3%
다사읍 15
 
1.1%
수성구 15
 
1.1%
노원동3가 15
 
1.1%
논공읍 12
 
0.8%
Other values (524) 830
58.7%
2023-12-11T02:22:57.608927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1137
 
16.3%
구 513
 
7.4%
대 307
 
4.4%
동 290
 
4.2%
역 281
 
4.0%
시 281
 
4.0%
광 277
 
4.0%
1 277
 
4.0%
로 243
 
3.5%
( 219
 
3.1%
Other values (170) 3153
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4112
58.9%
Space Separator 1137
 
16.3%
Decimal Number 1132
 
16.2%
Open Punctuation 219
 
3.1%
Close Punctuation 219
 
3.1%
Dash Punctuation 121
 
1.7%
Other Punctuation 36
 
0.5%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 513
 
12.5%
대 307
 
7.5%
동 290
 
7.1%
역 281
 
6.8%
시 281
 
6.8%
광 277
 
6.7%
로 243
 
5.9%
길 192
 
4.7%
북 112
 
2.7%
달 108
 
2.6%
Other values (152) 1508
36.7%
Decimal Number
ValueCountFrequency (%)
1 277
24.5%
2 154
13.6%
3 135
11.9%
4 113
10.0%
5 93
 
8.2%
6 92
 
8.1%
7 87
 
7.7%
0 67
 
5.9%
9 62
 
5.5%
8 52
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 35
97.2%
/ 1
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
1137
100.0%
Open Punctuation
ValueCountFrequency (%)
( 219
100.0%
Close Punctuation
ValueCountFrequency (%)
) 219
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4112
58.9%
Common 2864
41.0%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 513
 
12.5%
대 307
 
7.5%
동 290
 
7.1%
역 281
 
6.8%
시 281
 
6.8%
광 277
 
6.7%
로 243
 
5.9%
길 192
 
4.7%
북 112
 
2.7%
달 108
 
2.6%
Other values (152) 1508
36.7%
Common
ValueCountFrequency (%)
1137
39.7%
1 277
 
9.7%
( 219
 
7.6%
) 219
 
7.6%
2 154
 
5.4%
3 135
 
4.7%
- 121
 
4.2%
4 113
 
3.9%
5 93
 
3.2%
6 92
 
3.2%
Other values (6) 304
 
10.6%
Latin
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4112
58.9%
ASCII 2866
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1137
39.7%
1 277
 
9.7%
( 219
 
7.6%
) 219
 
7.6%
2 154
 
5.4%
3 135
 
4.7%
- 121
 
4.2%
4 113
 
3.9%
5 93
 
3.2%
6 92
 
3.2%
Other values (8) 306
 
10.7%
Hangul
ValueCountFrequency (%)
구 513
 
12.5%
대 307
 
7.5%
동 290
 
7.1%
역 281
 
6.8%
시 281
 
6.8%
광 277
 
6.7%
로 243
 
5.9%
길 192
 
4.7%
북 112
 
2.7%
달 108
 
2.6%
Other values (152) 1508
36.7%

업소전화번호
Text

MISSING 

Distinct203
Distinct (%)99.5%
Missing73
Missing (%)26.4%
Memory size2.3 KiB
2023-12-11T02:22:58.037881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.058824
Min length12

Characters and Unicode

Total characters2460
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

Unique202 ?
Unique (%)99.0%

Sample

1st row053-351-9200
2nd row053-527-4355
3rd row053-525-9326
4th row053-657-3050
5th row053-526-0811
ValueCountFrequency (%)
053-746-0092 2
 
1.0%
053-583-9926 1
 
0.5%
053-354-6286 1
 
0.5%
053-351-9200 1
 
0.5%
070-4388-4449 1
 
0.5%
053-793-1007 1
 
0.5%
053-567-6328 1
 
0.5%
053-961-5522 1
 
0.5%
053-321-6386 1
 
0.5%
053-423-4041 1
 
0.5%
Other values (193) 193
94.6%
2023-12-11T02:22:58.701929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 430
17.5%
- 408
16.6%
3 377
15.3%
0 345
14.0%
1 147
 
6.0%
6 145
 
5.9%
2 143
 
5.8%
8 138
 
5.6%
9 128
 
5.2%
7 109
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2052
83.4%
Dash Punctuation 408
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 430
21.0%
3 377
18.4%
0 345
16.8%
1 147
 
7.2%
6 145
 
7.1%
2 143
 
7.0%
8 138
 
6.7%
9 128
 
6.2%
7 109
 
5.3%
4 90
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 408
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2460
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 430
17.5%
- 408
16.6%
3 377
15.3%
0 345
14.0%
1 147
 
6.0%
6 145
 
5.9%
2 143
 
5.8%
8 138
 
5.6%
9 128
 
5.2%
7 109
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 430
17.5%
- 408
16.6%
3 377
15.3%
0 345
14.0%
1 147
 
6.0%
6 145
 
5.9%
2 143
 
5.8%
8 138
 
5.6%
9 128
 
5.2%
7 109
 
4.4%

Interactions

2023-12-11T02:22:51.994089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:22:51.459026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:22:52.219601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:22:51.733749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:22:58.867913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번인허가번호
연번1.0000.000
인허가번호0.0001.000
2023-12-11T02:22:59.041290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번인허가번호
연번1.000-0.050
인허가번호-0.0501.000

Missing values

2023-12-11T02:22:52.607450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:22:52.929119image/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

연번인허가번호업소명업소주소업소전화번호
0120180158003(주)가온푸드대구광역시 북구 노원로47길 17 (침산동)053-351-9200
1220140157019(주)거인축산대구광역시 서구 서대구로6길 6 (내당동)053-527-4355
2320170157005(주)국보푸드시스템대구광역시 북구 연암로42길 5 (산격동)053-525-9326
3420180158023(주)기영대구광역시 달서구 앞산순환로 249 (송현동)053-657-3050
4520140157030(주)다담대구광역시 달서구 성서동로 154 (월암동)053-526-0811
5620140157039(주)달구지푸드대구광역시 달성군 논공읍 농공공단길 10053-593-5910
6720050157006(주)대영냉장대구광역시 달성군 논공읍 비슬로264길 46053-631-0805
7820110157017(주)대원미트대구광역시 동구 신덕로6길 26 (신평동)070-8201-3210
8920080157009(주)대홍 농업회사법인대구광역시 서구 와룡로73길 11 (중리동)053-526-9998
91020130157023(주)더푸드대구광역시 북구 노원로10길 74, 1층 (노원동2가)<NA>
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