Overview

Dataset statistics

Number of variables5
Number of observations254
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.5 KiB
Average record size in memory42.5 B

Variable types

Text2
Numeric2
Categorical1

Dataset

Description부산광역시_축산물가공업체현황_20231226
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3076099

Alerts

위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
업종 is highly imbalanced (82.7%)Imbalance
업소명 has unique valuesUnique

Reproduction

Analysis started2024-03-13 13:15:18.893639
Analysis finished2024-03-13 13:15:19.891766
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct254
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-03-13T22:15:20.099600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length6.5551181
Min length2

Characters and Unicode

Total characters1665
Distinct characters279
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique254 ?
Unique (%)100.0%

Sample

1st row주식회사 다이닝푸드
2nd row(주)미스바
3rd row(주)지강푸드
4th row희성식품(주)
5th row(주)명진푸드 동래지점
ValueCountFrequency (%)
주식회사 58
 
17.9%
농업회사법인 2
 
0.6%
씨에프(cf 1
 
0.3%
경민푸드 1
 
0.3%
제일f&c 1
 
0.3%
조은닭 1
 
0.3%
한울식품 1
 
0.3%
현백 1
 
0.3%
늘찬 1
 
0.3%
신성푸드 1
 
0.3%
Other values (256) 256
79.0%
2024-03-13T22:15:20.547770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 109
 
6.5%
식 99
 
5.9%
드 79
 
4.7%
푸 76
 
4.6%
70
 
4.2%
사 67
 
4.0%
회 61
 
3.7%
( 54
 
3.2%
) 54
 
3.2%
품 41
 
2.5%
Other values (269) 955
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1432
86.0%
Space Separator 70
 
4.2%
Open Punctuation 54
 
3.2%
Close Punctuation 54
 
3.2%
Uppercase Letter 41
 
2.5%
Other Punctuation 7
 
0.4%
Decimal Number 6
 
0.4%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 109
 
7.6%
식 99
 
6.9%
드 79
 
5.5%
푸 76
 
5.3%
사 67
 
4.7%
회 61
 
4.3%
품 41
 
2.9%
산 29
 
2.0%
이 28
 
2.0%
에 23
 
1.6%
Other values (244) 820
57.3%
Uppercase Letter
ValueCountFrequency (%)
F 8
19.5%
C 6
14.6%
A 4
9.8%
E 3
 
7.3%
L 3
 
7.3%
H 3
 
7.3%
I 2
 
4.9%
O 2
 
4.9%
D 2
 
4.9%
M 2
 
4.9%
Other values (4) 6
14.6%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 1
 
16.7%
0 1
 
16.7%
4 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
& 5
71.4%
＆ 1
 
14.3%
/ 1
 
14.3%
Space Separator
ValueCountFrequency (%)
70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Lowercase Letter
ValueCountFrequency (%)
j 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1432
86.0%
Common 191
 
11.5%
Latin 42
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 109
 
7.6%
식 99
 
6.9%
드 79
 
5.5%
푸 76
 
5.3%
사 67
 
4.7%
회 61
 
4.3%
품 41
 
2.9%
산 29
 
2.0%
이 28
 
2.0%
에 23
 
1.6%
Other values (244) 820
57.3%
Latin
ValueCountFrequency (%)
F 8
19.0%
C 6
14.3%
A 4
9.5%
E 3
 
7.1%
L 3
 
7.1%
H 3
 
7.1%
I 2
 
4.8%
O 2
 
4.8%
D 2
 
4.8%
M 2
 
4.8%
Other values (5) 7
16.7%
Common
ValueCountFrequency (%)
70
36.6%
( 54
28.3%
) 54
28.3%
& 5
 
2.6%
2 3
 
1.6%
1 1
 
0.5%
＆ 1
 
0.5%
0 1
 
0.5%
/ 1
 
0.5%
4 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1432
86.0%
ASCII 232
 
13.9%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 109
 
7.6%
식 99
 
6.9%
드 79
 
5.5%
푸 76
 
5.3%
사 67
 
4.7%
회 61
 
4.3%
품 41
 
2.9%
산 29
 
2.0%
이 28
 
2.0%
에 23
 
1.6%
Other values (244) 820
57.3%
ASCII
ValueCountFrequency (%)
70
30.2%
( 54
23.3%
) 54
23.3%
F 8
 
3.4%
C 6
 
2.6%
& 5
 
2.2%
A 4
 
1.7%
E 3
 
1.3%
2 3
 
1.3%
L 3
 
1.3%
Other values (14) 22
 
9.5%
None
ValueCountFrequency (%)
＆ 1
100.0%

업소주소
Text

Distinct253
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2024-03-13T22:15:20.856549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length40
Mean length28.925197
Min length19

Characters and Unicode

Total characters7347
Distinct characters204
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique252 ?
Unique (%)99.2%

Sample

1st row부산광역시 기장군 기장읍 차성로365번길 30
2nd row부산광역시 강서구 대저로155번길 27-2, 2동(대저1동)
3rd row부산광역시 부산진구 성지로 134-1, 17호 (초읍동)
4th row부산광역시 남구 수영로325번길 145, 1층 (대연동)
5th row부산광역시 해운대구 삼어로91번길 68-27, 1층 (반여동)
ValueCountFrequency (%)
부산광역시 254
 
18.2%
강서구 63
 
4.5%
1층 50
 
3.6%
기장군 41
 
2.9%
사상구 38
 
2.7%
금정구 33
 
2.4%
해운대구 25
 
1.8%
대저1동 22
 
1.6%
기장읍 18
 
1.3%
2층 13
 
0.9%
Other values (520) 835
60.0%
2024-03-13T22:15:21.413735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1138
 
15.5%
1 326
 
4.4%
동 302
 
4.1%
산 293
 
4.0%
부 272
 
3.7%
광 262
 
3.6%
시 260
 
3.5%
역 254
 
3.5%
로 233
 
3.2%
구 224
 
3.0%
Other values (194) 3783
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4288
58.4%
Decimal Number 1271
 
17.3%
Space Separator 1138
 
15.5%
Close Punctuation 214
 
2.9%
Open Punctuation 214
 
2.9%
Other Punctuation 150
 
2.0%
Dash Punctuation 59
 
0.8%
Uppercase Letter 9
 
0.1%
Math Symbol 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 302
 
7.0%
산 293
 
6.8%
부 272
 
6.3%
광 262
 
6.1%
시 260
 
6.1%
역 254
 
5.9%
로 233
 
5.4%
구 224
 
5.2%
길 167
 
3.9%
번 149
 
3.5%
Other values (175) 1872
43.7%
Decimal Number
ValueCountFrequency (%)
1 326
25.6%
2 188
14.8%
3 143
11.3%
5 111
 
8.7%
4 100
 
7.9%
7 91
 
7.2%
6 88
 
6.9%
9 84
 
6.6%
0 77
 
6.1%
8 63
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 5
55.6%
C 2
 
22.2%
A 2
 
22.2%
Space Separator
ValueCountFrequency (%)
1138
100.0%
Close Punctuation
ValueCountFrequency (%)
) 214
100.0%
Open Punctuation
ValueCountFrequency (%)
( 214
100.0%
Other Punctuation
ValueCountFrequency (%)
, 150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4288
58.4%
Common 3050
41.5%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 302
 
7.0%
산 293
 
6.8%
부 272
 
6.3%
광 262
 
6.1%
시 260
 
6.1%
역 254
 
5.9%
로 233
 
5.4%
구 224
 
5.2%
길 167
 
3.9%
번 149
 
3.5%
Other values (175) 1872
43.7%
Common
ValueCountFrequency (%)
1138
37.3%
1 326
 
10.7%
) 214
 
7.0%
( 214
 
7.0%
2 188
 
6.2%
, 150
 
4.9%
3 143
 
4.7%
5 111
 
3.6%
4 100
 
3.3%
7 91
 
3.0%
Other values (6) 375
 
12.3%
Latin
ValueCountFrequency (%)
B 5
55.6%
C 2
 
22.2%
A 2
 
22.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4288
58.4%
ASCII 3059
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1138
37.2%
1 326
 
10.7%
) 214
 
7.0%
( 214
 
7.0%
2 188
 
6.1%
, 150
 
4.9%
3 143
 
4.7%
5 111
 
3.6%
4 100
 
3.3%
7 91
 
3.0%
Other values (9) 384
 
12.6%
Hangul
ValueCountFrequency (%)
동 302
 
7.0%
산 293
 
6.8%
부 272
 
6.3%
광 262
 
6.1%
시 260
 
6.1%
역 254
 
5.9%
로 233
 
5.4%
구 224
 
5.2%
길 167
 
3.9%
번 149
 
3.5%
Other values (175) 1872
43.7%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct244
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.200577
Minimum35.055428
Maximum35.360174
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-03-13T22:15:21.690984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.055428
5-th percentile35.090858
Q135.175551
median35.202548
Q335.224489
95-th percentile35.319744
Maximum35.360174
Range0.30474621
Interquartile range (IQR)0.048938077

Descriptive statistics

Standard deviation0.057060626
Coefficient of variation (CV)0.0016210139
Kurtosis0.94290328
Mean35.200577
Median Absolute Deviation (MAD)0.0230925
Skewness0.044283234
Sum8940.9466
Variance0.003255915
MonotonicityNot monotonic
2024-03-13T22:15:21.887159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.23503545 2
 
0.8%
35.18161308 2
 
0.8%
35.2189976 2
 
0.8%
35.19351922 2
 
0.8%
35.22835372 2
 
0.8%
35.14044343 2
 
0.8%
35.20921529 2
 
0.8%
35.31975706 2
 
0.8%
35.28276311 2
 
0.8%
35.19301852 2
 
0.8%
Other values (234) 234
92.1%
ValueCountFrequency (%)
35.05542807 1
0.4%
35.05639329 1
0.4%
35.06644223 1
0.4%
35.07163803 1
0.4%
35.07398863 1
0.4%
35.07684529 1
0.4%
35.07783739 1
0.4%
35.07940901 1
0.4%
35.08004198 1
0.4%
35.08391888 1
0.4%
ValueCountFrequency (%)
35.36017428 1
0.4%
35.35863299 1
0.4%
35.35771303 1
0.4%
35.33492009 1
0.4%
35.33240333 1
0.4%
35.3303637 1
0.4%
35.32799634 1
0.4%
35.32638735 1
0.4%
35.32494338 1
0.4%
35.32050064 1
0.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct244
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.05547
Minimum128.83118
Maximum129.2868
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-03-13T22:15:22.077971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.83118
5-th percentile128.93248
Q1128.97735
median129.02619
Q3129.12456
95-th percentile129.21987
Maximum129.2868
Range0.4556195
Interquartile range (IQR)0.1472145

Descriptive statistics

Standard deviation0.10303193
Coefficient of variation (CV)0.0007983538
Kurtosis-0.94461424
Mean129.05547
Median Absolute Deviation (MAD)0.07899935
Skewness0.27196458
Sum32780.09
Variance0.010615578
MonotonicityNot monotonic
2024-03-13T22:15:22.230018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.2198582 2
 
0.8%
129.1267479 2
 
0.8%
128.9325717 2
 
0.8%
128.9876779 2
 
0.8%
129.1224292 2
 
0.8%
128.9812085 2
 
0.8%
128.9795762 2
 
0.8%
129.2088136 2
 
0.8%
129.2251473 2
 
0.8%
128.9871777 2
 
0.8%
Other values (234) 234
92.1%
ValueCountFrequency (%)
128.8311832 1
0.4%
128.8322736 1
0.4%
128.8500009 1
0.4%
128.8582659 1
0.4%
128.8599251 1
0.4%
128.8655024 1
0.4%
128.8884719 1
0.4%
128.8914472 1
0.4%
128.9080173 1
0.4%
128.912808 1
0.4%
ValueCountFrequency (%)
129.2868027 1
0.4%
129.2719625 1
0.4%
129.2701945 1
0.4%
129.2693384 1
0.4%
129.2593588 1
0.4%
129.2549801 1
0.4%
129.2442199 1
0.4%
129.2388399 1
0.4%
129.2272396 1
0.4%
129.2251473 2
0.8%

업종
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
축산물가공업-식육가공업
244 
축산물가공업-유가공업
 
7
축산물가공업-알가공업
 
3

Length

Max length12
Median length12
Mean length11.96063
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row축산물가공업-식육가공업
2nd row축산물가공업-식육가공업
3rd row축산물가공업-식육가공업
4th row축산물가공업-식육가공업
5th row축산물가공업-식육가공업

Common Values

ValueCountFrequency (%)
축산물가공업-식육가공업 244
96.1%
축산물가공업-유가공업 7
 
2.8%
축산물가공업-알가공업 3
 
1.2%

Length

2024-03-13T22:15:22.385730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:15:22.503086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
축산물가공업-식육가공업 244
96.1%
축산물가공업-유가공업 7
 
2.8%
축산물가공업-알가공업 3
 
1.2%

Interactions

2024-03-13T22:15:19.520565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:19.266542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:19.610205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:19.415884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:15:22.579518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도업종
위도1.0000.8190.000
경도0.8191.0000.000
업종0.0000.0001.000
2024-03-13T22:15:22.662131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도업종
위도1.0000.5280.000
경도0.5281.0000.000
업종0.0000.0001.000

Missing values

2024-03-13T22:15:19.730572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:15:19.847167image/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

업소명업소주소위도경도업종
0주식회사 다이닝푸드부산광역시 기장군 기장읍 차성로365번길 3035.25225129.21282축산물가공업-식육가공업
1(주)미스바부산광역시 강서구 대저로155번길 27-2, 2동(대저1동)35.216482128.969306축산물가공업-식육가공업
2(주)지강푸드부산광역시 부산진구 성지로 134-1, 17호 (초읍동)35.181341129.049836축산물가공업-식육가공업
3희성식품(주)부산광역시 남구 수영로325번길 145, 1층 (대연동)35.143968129.097652축산물가공업-식육가공업
4(주)명진푸드 동래지점부산광역시 해운대구 삼어로91번길 68-27, 1층 (반여동)35.208239129.117078축산물가공업-식육가공업
5주식회사 올닥푸드부산광역시 강서구 공항로 1165, 2층 (대저1동)35.205964128.976967축산물가공업-식육가공업
6(주)에이치앤컴퍼니부산광역시 기장군 일광면 화용길 78, 4층35.282763129.225147축산물가공업-식육가공업
7(주)에이젯푸드서비스지점부산광역시 북구 사상로583번길 635.196437128.990173축산물가공업-식육가공업
8거성미트앤푸드부산광역시 강서구 평강로187번길 23, 1층 (대저1동)35.202797128.93992축산물가공업-식육가공업
9(주)MGH부산광역시 수영구 망미로 4 (망미동)35.172088129.105023축산물가공업-식육가공업
업소명업소주소위도경도업종
244영원아이스부산광역시 해운대구 달맞이길117번나길 117, 임페리얼빌딩 지하1층(중동)35.161953129.183487축산물가공업-유가공업
245훼미리식품(주)부산공장부산광역시 사하구 하신중앙로 14035.091652128.965302축산물가공업-유가공업
246(주)일성냉동부산광역시 사하구 다대로320번길 10, 1호 (장림동)35.073989128.974885축산물가공업-유가공업
247주식회사 릴요거트부산광역시 강서구 공항로1309번길 95-11 (대저1동)35.214979128.983567축산물가공업-유가공업
248오아시송부산광역시 동래구 여고북로 102, 3층(사직동)35.200871129.070744축산물가공업-유가공업
249신앙촌식품(주)부산광역시 기장군 기장읍 죽성로 197, 126동 1,2층 2097호 (시온주택)35.247164129.23884축산물가공업-유가공업
250HADA부산광역시 기장군 기장읍 배산로68번길 16-4, 2층35.248475129.211797축산물가공업-유가공업
251세진유통부산광역시 기장군 기장읍 대청로36번길 6635.234809129.213736축산물가공업-알가공업
252경남유통부산광역시 동래구 온천천로319번길 33, 1층 (수안동)35.196324129.088375축산물가공업-알가공업
253해성넷 주식회사부산광역시 서구 원양로 1, B동 3층 307호 (암남동,수산가공선진화단지)35.055428129.011223축산물가공업-알가공업