Overview

Dataset statistics

Number of variables6
Number of observations1010
Missing cells330
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory48.5 KiB
Average record size in memory49.1 B

Variable types

Numeric1
Categorical1
Text3
DateTime1

Dataset

Description식품을 소분하여 판매하는 업체(식품소분업, 유동전문판매업, 집단급식소식품판매업,기타식품판매업) 등에 관한 현황에 대한 데이터로 업종명,업소명,소재지,전화번호 항목으로 구성되어 있습니다.
URLhttps://www.data.go.kr/data/15054246/fileData.do

Alerts

데이터 기준일자 has constant value ""Constant
연번 is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 연번High correlation
소재지전화번호 has 330 (32.7%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:56:16.378519
Analysis finished2023-12-12 18:56:17.932034
Duration1.55 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1010
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean505.5
Minimum1
Maximum1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.0 KiB
2023-12-13T03:56:18.065692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile51.45
Q1253.25
median505.5
Q3757.75
95-th percentile959.55
Maximum1010
Range1009
Interquartile range (IQR)504.5

Descriptive statistics

Standard deviation291.70619
Coefficient of variation (CV)0.57706466
Kurtosis-1.2
Mean505.5
Median Absolute Deviation (MAD)252.5
Skewness0
Sum510555
Variance85092.5
MonotonicityStrictly increasing
2023-12-13T03:56:18.261371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
680 1
 
0.1%
667 1
 
0.1%
668 1
 
0.1%
669 1
 
0.1%
670 1
 
0.1%
671 1
 
0.1%
672 1
 
0.1%
673 1
 
0.1%
674 1
 
0.1%
Other values (1000) 1000
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1010 1
0.1%
1009 1
0.1%
1008 1
0.1%
1007 1
0.1%
1006 1
0.1%
1005 1
0.1%
1004 1
0.1%
1003 1
0.1%
1002 1
0.1%
1001 1
0.1%

업종
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
유통전문판매업
647 
식품소분업
163 
집단급식소 식품판매업
134 
기타식품판매업
66 

Length

Max length11
Median length7
Mean length7.2079208
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유통전문판매업 647
64.1%
식품소분업 163
 
16.1%
집단급식소 식품판매업 134
 
13.3%
기타식품판매업 66
 
6.5%

Length

2023-12-13T03:56:18.484922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:56:18.666600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유통전문판매업 647
56.6%
식품소분업 163
 
14.2%
집단급식소 134
 
11.7%
식품판매업 134
 
11.7%
기타식품판매업 66
 
5.8%

업소명
Text

Distinct963
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2023-12-13T03:56:18.982121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length20
Mean length7.8079208
Min length2

Characters and Unicode

Total characters7886
Distinct characters557
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

Unique923 ?
Unique (%)91.4%

Sample

1st row에이케이에스앤디 주식회사
2nd row(주) 이랜드 킴스클럽 야탑점
3rd row(주)이마트에브리데이 이매동점
4th row노브랜드 판교운중점
5th row(주)농협하나로유통 농협성남유통센터
ValueCountFrequency (%)
주식회사 162
 
12.4%
농업회사법인 8
 
0.6%
주 5
 
0.4%
주)이마트에브리데이 5
 
0.4%
인하푸드 4
 
0.3%
야탑점 4
 
0.3%
홈플러스(주 4
 
0.3%
하나로마트 3
 
0.2%
조은푸드 3
 
0.2%
오아시스 3
 
0.2%
Other values (1040) 1106
84.6%
2023-12-13T03:56:19.764781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 596
 
7.6%
) 446
 
5.7%
( 432
 
5.5%
298
 
3.8%
이 296
 
3.8%
스 224
 
2.8%
사 220
 
2.8%
식 216
 
2.7%
회 197
 
2.5%
에 146
 
1.9%
Other values (547) 4815
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6476
82.1%
Close Punctuation 446
 
5.7%
Open Punctuation 432
 
5.5%
Space Separator 298
 
3.8%
Uppercase Letter 117
 
1.5%
Lowercase Letter 89
 
1.1%
Other Punctuation 17
 
0.2%
Decimal Number 8
 
0.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 596
 
9.2%
이 296
 
4.6%
스 224
 
3.5%
사 220
 
3.4%
식 216
 
3.3%
회 197
 
3.0%
에 146
 
2.3%
드 136
 
2.1%
푸 108
 
1.7%
리 101
 
1.6%
Other values (492) 4236
65.4%
Uppercase Letter
ValueCountFrequency (%)
S 13
 
11.1%
F 13
 
11.1%
I 10
 
8.5%
M 8
 
6.8%
N 8
 
6.8%
O 8
 
6.8%
G 6
 
5.1%
B 6
 
5.1%
C 6
 
5.1%
R 5
 
4.3%
Other values (13) 34
29.1%
Lowercase Letter
ValueCountFrequency (%)
e 13
14.6%
a 11
12.4%
r 10
11.2%
n 9
10.1%
o 9
10.1%
t 6
 
6.7%
u 5
 
5.6%
c 4
 
4.5%
i 4
 
4.5%
m 3
 
3.4%
Other values (10) 15
16.9%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
7 1
 
12.5%
3 1
 
12.5%
9 1
 
12.5%
4 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
& 8
47.1%
. 8
47.1%
' 1
 
5.9%
Close Punctuation
ValueCountFrequency (%)
) 446
100.0%
Open Punctuation
ValueCountFrequency (%)
( 432
100.0%
Space Separator
ValueCountFrequency (%)
298
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6476
82.1%
Common 1204
 
15.3%
Latin 206
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 596
 
9.2%
이 296
 
4.6%
스 224
 
3.5%
사 220
 
3.4%
식 216
 
3.3%
회 197
 
3.0%
에 146
 
2.3%
드 136
 
2.1%
푸 108
 
1.7%
리 101
 
1.6%
Other values (492) 4236
65.4%
Latin
ValueCountFrequency (%)
e 13
 
6.3%
S 13
 
6.3%
F 13
 
6.3%
a 11
 
5.3%
r 10
 
4.9%
I 10
 
4.9%
n 9
 
4.4%
o 9
 
4.4%
M 8
 
3.9%
N 8
 
3.9%
Other values (33) 102
49.5%
Common
ValueCountFrequency (%)
) 446
37.0%
( 432
35.9%
298
24.8%
& 8
 
0.7%
. 8
 
0.7%
2 4
 
0.3%
- 3
 
0.2%
' 1
 
0.1%
7 1
 
0.1%
3 1
 
0.1%
Other values (2) 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6476
82.1%
ASCII 1410
 
17.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 596
 
9.2%
이 296
 
4.6%
스 224
 
3.5%
사 220
 
3.4%
식 216
 
3.3%
회 197
 
3.0%
에 146
 
2.3%
드 136
 
2.1%
푸 108
 
1.7%
리 101
 
1.6%
Other values (492) 4236
65.4%
ASCII
ValueCountFrequency (%)
) 446
31.6%
( 432
30.6%
298
21.1%
e 13
 
0.9%
S 13
 
0.9%
F 13
 
0.9%
a 11
 
0.8%
r 10
 
0.7%
I 10
 
0.7%
n 9
 
0.6%
Other values (45) 155
 
11.0%

소재지전화번호
Text

MISSING 

Distinct647
Distinct (%)95.1%
Missing330
Missing (%)32.7%
Memory size8.0 KiB
2023-12-13T03:56:20.231147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.975
Min length12

Characters and Unicode

Total characters9503
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

Unique618 ?
Unique (%)90.9%

Sample

1st row 031- 779-3300
2nd row 031- 780-3000
3rd row 031- 703-0074
4th row031 -8017-9652
5th row 031- 738-9000
ValueCountFrequency (%)
031 478
28.0%
070 91
 
5.3%
02 66
 
3.9%
759 13
 
0.8%
701 13
 
0.8%
731 10
 
0.6%
722 9
 
0.5%
752 9
 
0.5%
721 9
 
0.5%
751 9
 
0.5%
Other values (766) 1003
58.7%
2023-12-13T03:56:21.128206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1380
14.5%
- 1360
14.3%
1231
13.0%
1 1016
10.7%
7 936
9.8%
3 899
9.5%
2 548
 
5.8%
5 490
 
5.2%
8 482
 
5.1%
4 427
 
4.5%
Other values (2) 734
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6912
72.7%
Dash Punctuation 1360
 
14.3%
Space Separator 1231
 
13.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1380
20.0%
1 1016
14.7%
7 936
13.5%
3 899
13.0%
2 548
 
7.9%
5 490
 
7.1%
8 482
 
7.0%
4 427
 
6.2%
6 402
 
5.8%
9 332
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 1360
100.0%
Space Separator
ValueCountFrequency (%)
1231
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9503
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1380
14.5%
- 1360
14.3%
1231
13.0%
1 1016
10.7%
7 936
9.8%
3 899
9.5%
2 548
 
5.8%
5 490
 
5.2%
8 482
 
5.1%
4 427
 
4.5%
Other values (2) 734
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9503
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1380
14.5%
- 1360
14.3%
1231
13.0%
1 1016
10.7%
7 936
9.8%
3 899
9.5%
2 548
 
5.8%
5 490
 
5.2%
8 482
 
5.1%
4 427
 
4.5%
Other values (2) 734
7.7%

소재지(도로명)
Text

Distinct972
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
2023-12-13T03:56:21.640497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length55
Mean length40.10396
Min length22

Characters and Unicode

Total characters40505
Distinct characters384
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique939 ?
Unique (%)93.0%

Sample

1st row경기도 성남시 분당구 성남대로 지하 601 (서현동 AK플라자 지하1층)
2nd row경기도 성남시 분당구 야탑로81번길 11 (야탑동 지하1층)
3rd row경기도 성남시 분당구 양현로94번길 29 (이매동 이매촌상가 지하1층 (구렛들길10))
4th row경기도 성남시 분당구 운중로166번길 1 1 2층 (운중동)
5th row경기도 성남시 분당구 성남대로43번길 11 (구미동)
ValueCountFrequency (%)
경기도 1010
 
12.2%
성남시 1010
 
12.2%
분당구 492
 
5.9%
중원구 309
 
3.7%
수정구 209
 
2.5%
일부 199
 
2.4%
1층 168
 
2.0%
상대원동 163
 
2.0%
야탑동 99
 
1.2%
구미동 72
 
0.9%
Other values (1623) 4567
55.0%
2023-12-13T03:56:22.483187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8225
 
20.3%
1 1632
 
4.0%
성 1247
 
3.1%
남 1228
 
3.0%
) 1184
 
2.9%
( 1184
 
2.9%
동 1178
 
2.9%
구 1095
 
2.7%
시 1086
 
2.7%
기 1064
 
2.6%
Other values (374) 21382
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23021
56.8%
Space Separator 8225
 
20.3%
Decimal Number 6349
 
15.7%
Close Punctuation 1185
 
2.9%
Open Punctuation 1185
 
2.9%
Uppercase Letter 304
 
0.8%
Dash Punctuation 201
 
0.5%
Lowercase Letter 18
 
< 0.1%
Math Symbol 11
 
< 0.1%
Letter Number 3
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 1247
 
5.4%
남 1228
 
5.3%
동 1178
 
5.1%
구 1095
 
4.8%
시 1086
 
4.7%
기 1064
 
4.6%
도 1061
 
4.6%
경 1019
 
4.4%
로 1014
 
4.4%
호 625
 
2.7%
Other values (321) 12404
53.9%
Uppercase Letter
ValueCountFrequency (%)
B 91
29.9%
A 49
16.1%
C 18
 
5.9%
S 16
 
5.3%
K 16
 
5.3%
E 16
 
5.3%
I 14
 
4.6%
T 11
 
3.6%
Z 11
 
3.6%
D 10
 
3.3%
Other values (14) 52
17.1%
Decimal Number
ValueCountFrequency (%)
1 1632
25.7%
2 858
13.5%
0 747
11.8%
3 657
10.3%
4 555
 
8.7%
5 537
 
8.5%
6 405
 
6.4%
8 342
 
5.4%
7 336
 
5.3%
9 280
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
n 4
22.2%
c 3
16.7%
r 2
11.1%
e 2
11.1%
w 2
11.1%
o 2
11.1%
t 2
11.1%
k 1
 
5.6%
Close Punctuation
ValueCountFrequency (%)
) 1184
99.9%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1184
99.9%
[ 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/ 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
8225
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 201
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23021
56.8%
Common 17159
42.4%
Latin 325
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 1247
 
5.4%
남 1228
 
5.3%
동 1178
 
5.1%
구 1095
 
4.8%
시 1086
 
4.7%
기 1064
 
4.6%
도 1061
 
4.6%
경 1019
 
4.4%
로 1014
 
4.4%
호 625
 
2.7%
Other values (321) 12404
53.9%
Latin
ValueCountFrequency (%)
B 91
28.0%
A 49
15.1%
C 18
 
5.5%
S 16
 
4.9%
K 16
 
4.9%
E 16
 
4.9%
I 14
 
4.3%
T 11
 
3.4%
Z 11
 
3.4%
D 10
 
3.1%
Other values (23) 73
22.5%
Common
ValueCountFrequency (%)
8225
47.9%
1 1632
 
9.5%
) 1184
 
6.9%
( 1184
 
6.9%
2 858
 
5.0%
0 747
 
4.4%
3 657
 
3.8%
4 555
 
3.2%
5 537
 
3.1%
6 405
 
2.4%
Other values (10) 1175
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23021
56.8%
ASCII 17481
43.2%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8225
47.1%
1 1632
 
9.3%
) 1184
 
6.8%
( 1184
 
6.8%
2 858
 
4.9%
0 747
 
4.3%
3 657
 
3.8%
4 555
 
3.2%
5 537
 
3.1%
6 405
 
2.3%
Other values (42) 1497
 
8.6%
Hangul
ValueCountFrequency (%)
성 1247
 
5.4%
남 1228
 
5.3%
동 1178
 
5.1%
구 1095
 
4.8%
시 1086
 
4.7%
기 1064
 
4.6%
도 1061
 
4.6%
경 1019
 
4.4%
로 1014
 
4.4%
호 625
 
2.7%
Other values (321) 12404
53.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%

데이터 기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size8.0 KiB
Minimum2023-06-01 00:00:00
Maximum2023-06-01 00:00:00
2023-12-13T03:56:22.694894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:56:22.864033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T03:56:17.539205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:56:22.988477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.935
업종0.9351.000
2023-12-13T03:56:23.142546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.845
업종0.8451.000

Missing values

2023-12-13T03:56:17.722806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:56:17.876090image/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

연번업종업소명소재지전화번호소재지(도로명)데이터 기준일자
01기타식품판매업에이케이에스앤디 주식회사031- 779-3300경기도 성남시 분당구 성남대로 지하 601 (서현동 AK플라자 지하1층)2023-06-01
12기타식품판매업(주) 이랜드 킴스클럽 야탑점031- 780-3000경기도 성남시 분당구 야탑로81번길 11 (야탑동 지하1층)2023-06-01
23기타식품판매업(주)이마트에브리데이 이매동점031- 703-0074경기도 성남시 분당구 양현로94번길 29 (이매동 이매촌상가 지하1층 (구렛들길10))2023-06-01
34기타식품판매업노브랜드 판교운중점031 -8017-9652경기도 성남시 분당구 운중로166번길 1 1 2층 (운중동)2023-06-01
45기타식품판매업(주)농협하나로유통 농협성남유통센터031- 738-9000경기도 성남시 분당구 성남대로43번길 11 (구미동)2023-06-01
56기타식품판매업(주)이마트에브리데이 정자점02 -380 -5798경기도 성남시 분당구 정자일로 242 (정자동 1 2층)2023-06-01
67기타식품판매업주식회사 현대백화점 판교점031 -5170-1006경기도 성남시 분당구 판교역로146번길 20 (백현동 현대백화점 판교점 지하1층)2023-06-01
78기타식품판매업성남농협 하나로마트 대왕점031-758 -9421경기도 성남시 수정구 대왕판교로 989 2층 일부호 (고등동)2023-06-01
89기타식품판매업홈플러스(주) 분당오리점031 -884 -2080경기도 성남시 분당구 탄천상로151번길 20 (구미동)2023-06-01
910기타식품판매업홈플러스(주) 야탑점031 -705 -2080경기도 성남시 분당구 성남대로925번길 16 (야탑동 지상3층)2023-06-01
연번업종업소명소재지전화번호소재지(도로명)데이터 기준일자
10001001집단급식소 식품판매업농업회사법인 국민(주)031 -755 -5266경기도 성남시 수정구 대왕판교로 891 (시흥동)2023-06-01
10011002집단급식소 식품판매업(주)거성케터링031 -732 -8989경기도 성남시 중원구 순환로 172 (상대원동 현대빌라트 203-1 203-2호)2023-06-01
10021003집단급식소 식품판매업주식회사 푸드톡070 -7579-8638경기도 성남시 중원구 도촌로7번길 11 지하1층 (도촌동)2023-06-01
10031004집단급식소 식품판매업해선유통031 -754 -3363경기도 성남시 중원구 마지로 277-9 (갈현동 1층 전부)2023-06-01
10041005집단급식소 식품판매업유가원식품031 -712 -5675경기도 성남시 수정구 달래내로 57 (금토동)2023-06-01
10051006집단급식소 식품판매업주식회사 일송푸드<NA>경기도 성남시 수정구 수정남로 120 (신흥동)2023-06-01
10061007집단급식소 식품판매업토성유통<NA>경기도 성남시 수정구 논골로 7 1층 일부호 (단대동)2023-06-01
10071008집단급식소 식품판매업네이처홀딩스주식회사070 -4667-4284경기도 성남시 수정구 설개로14번길 23 (시흥동 1층)2023-06-01
10081009집단급식소 식품판매업와이더블유(주)031 -789 -9747경기도 성남시 분당구 판교로 700 분당테크노파크 관리본동 지하103호 (야탑동)2023-06-01
10091010집단급식소 식품판매업부흥상회<NA>경기도 성남시 수정구 수정로74번길 12 (수진동 1층 일부)2023-06-01