Overview

Dataset statistics

Number of variables5
Number of observations754
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory29.6 KiB
Average record size in memory40.2 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description서울특별시 금천구 관내 식품관련업 현황으로 업종명, 업소명, 소재지(도로명), 소재지전화 등의 항목으로 제공하고 있습니다.
Author서울특별시 금천구
URLhttps://www.data.go.kr/data/3081149/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (0.1%) duplicate rowsDuplicates

Reproduction

Analysis started2024-03-23 06:54:15.823827
Analysis finished2024-03-23 06:54:18.269467
Duration2.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

Distinct10
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
즉석판매제조가공업
332 
유통전문판매업
201 
식품제조가공업
96 
식품소분업
58 
집단급식소 식품판매업
 
21
Other values (5)
46 

Length

Max length11
Median length9
Mean length7.8355438
Min length5

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
즉석판매제조가공업 332
44.0%
유통전문판매업 201
26.7%
식품제조가공업 96
 
12.7%
식품소분업 58
 
7.7%
집단급식소 식품판매업 21
 
2.8%
식품운반업 14
 
1.9%
기타식품판매업 14
 
1.9%
식품첨가물제조업 9
 
1.2%
용기.포장지제조업 8
 
1.1%
식품냉동.냉장업 1
 
0.1%

Length

2024-03-23T06:54:18.590976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:54:19.071926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
즉석판매제조가공업 332
42.8%
유통전문판매업 201
25.9%
식품제조가공업 96
 
12.4%
식품소분업 58
 
7.5%
집단급식소 21
 
2.7%
식품판매업 21
 
2.7%
식품운반업 14
 
1.8%
기타식품판매업 14
 
1.8%
식품첨가물제조업 9
 
1.2%
용기.포장지제조업 8
 
1.0%

업소명
Text

Distinct712
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-03-23T06:54:20.200555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length6.9084881
Min length2

Characters and Unicode

Total characters5209
Distinct characters554
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique676 ?
Unique (%)89.7%

Sample

1st rowJ·A FOOD
2nd row(주)서래
3rd row일동민속과자
4th row(주)이룸리테일
5th row(주)이동천식품
ValueCountFrequency (%)
주식회사 82
 
8.6%
중국식품 5
 
0.5%
주 4
 
0.4%
농업회사법인 4
 
0.4%
food 3
 
0.3%
홈플러스(주 3
 
0.3%
시흥점 3
 
0.3%
제이에프에프 3
 
0.3%
커피 3
 
0.3%
주)일가브라더스 3
 
0.3%
Other values (787) 837
88.1%
2024-03-23T06:54:22.272965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 283
 
5.4%
) 216
 
4.1%
( 216
 
4.1%
196
 
3.8%
이 177
 
3.4%
식 127
 
2.4%
사 119
 
2.3%
회 101
 
1.9%
스 100
 
1.9%
드 78
 
1.5%
Other values (544) 3596
69.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4385
84.2%
Close Punctuation 216
 
4.1%
Open Punctuation 216
 
4.1%
Space Separator 196
 
3.8%
Uppercase Letter 110
 
2.1%
Lowercase Letter 38
 
0.7%
Decimal Number 36
 
0.7%
Other Punctuation 12
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 283
 
6.5%
이 177
 
4.0%
식 127
 
2.9%
사 119
 
2.7%
회 101
 
2.3%
스 100
 
2.3%
드 78
 
1.8%
리 69
 
1.6%
에 63
 
1.4%
푸 55
 
1.3%
Other values (488) 3213
73.3%
Uppercase Letter
ValueCountFrequency (%)
B 11
 
10.0%
O 11
 
10.0%
L 9
 
8.2%
A 9
 
8.2%
F 8
 
7.3%
M 8
 
7.3%
C 7
 
6.4%
E 6
 
5.5%
I 5
 
4.5%
Y 4
 
3.6%
Other values (13) 32
29.1%
Lowercase Letter
ValueCountFrequency (%)
o 7
18.4%
e 6
15.8%
m 5
13.2%
a 3
7.9%
t 3
7.9%
k 2
 
5.3%
i 2
 
5.3%
s 2
 
5.3%
d 1
 
2.6%
b 1
 
2.6%
Other values (6) 6
15.8%
Decimal Number
ValueCountFrequency (%)
1 9
25.0%
3 4
11.1%
2 4
11.1%
9 3
 
8.3%
7 3
 
8.3%
5 3
 
8.3%
6 3
 
8.3%
0 3
 
8.3%
4 2
 
5.6%
8 2
 
5.6%
Other Punctuation
ValueCountFrequency (%)
& 6
50.0%
, 3
25.0%
. 2
 
16.7%
· 1
 
8.3%
Close Punctuation
ValueCountFrequency (%)
) 216
100.0%
Open Punctuation
ValueCountFrequency (%)
( 216
100.0%
Space Separator
ValueCountFrequency (%)
196
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4382
84.1%
Common 676
 
13.0%
Latin 148
 
2.8%
Han 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 283
 
6.5%
이 177
 
4.0%
식 127
 
2.9%
사 119
 
2.7%
회 101
 
2.3%
스 100
 
2.3%
드 78
 
1.8%
리 69
 
1.6%
에 63
 
1.4%
푸 55
 
1.3%
Other values (485) 3210
73.3%
Latin
ValueCountFrequency (%)
B 11
 
7.4%
O 11
 
7.4%
L 9
 
6.1%
A 9
 
6.1%
F 8
 
5.4%
M 8
 
5.4%
o 7
 
4.7%
C 7
 
4.7%
e 6
 
4.1%
E 6
 
4.1%
Other values (29) 66
44.6%
Common
ValueCountFrequency (%)
) 216
32.0%
( 216
32.0%
196
29.0%
1 9
 
1.3%
& 6
 
0.9%
3 4
 
0.6%
2 4
 
0.6%
9 3
 
0.4%
7 3
 
0.4%
5 3
 
0.4%
Other values (7) 16
 
2.4%
Han
ValueCountFrequency (%)
家 1
33.3%
福 1
33.3%
二 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4382
84.1%
ASCII 823
 
15.8%
CJK 3
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 283
 
6.5%
이 177
 
4.0%
식 127
 
2.9%
사 119
 
2.7%
회 101
 
2.3%
스 100
 
2.3%
드 78
 
1.8%
리 69
 
1.6%
에 63
 
1.4%
푸 55
 
1.3%
Other values (485) 3210
73.3%
ASCII
ValueCountFrequency (%)
) 216
26.2%
( 216
26.2%
196
23.8%
B 11
 
1.3%
O 11
 
1.3%
1 9
 
1.1%
L 9
 
1.1%
A 9
 
1.1%
F 8
 
1.0%
M 8
 
1.0%
Other values (45) 130
15.8%
None
ValueCountFrequency (%)
· 1
100.0%
CJK
ValueCountFrequency (%)
家 1
33.3%
福 1
33.3%
二 1
33.3%

소재지(도로명)
Text

Distinct709
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-03-23T06:54:23.518921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length52
Mean length39.172414
Min length23

Characters and Unicode

Total characters29536
Distinct characters275
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique673 ?
Unique (%)89.3%

Sample

1st row서울특별시 금천구 벚꽃로56길 66 (가산동 [순환샛길 58])
2nd row서울특별시 금천구 범안로11길 61 1층 (독산동)
3rd row서울특별시 금천구 독산로64길 34 (독산동 [정훈1길 34])
4th row서울특별시 금천구 벚꽃로 190 3층 (독산동)
5th row서울특별시 금천구 벚꽃로 190 1층 (독산동)
ValueCountFrequency (%)
서울특별시 754
 
13.8%
금천구 754
 
13.8%
가산동 332
 
6.1%
독산동 222
 
4.1%
시흥동 200
 
3.7%
가산디지털1로 142
 
2.6%
1층 138
 
2.5%
가산디지털2로 74
 
1.4%
시흥대로 58
 
1.1%
지상1층 56
 
1.0%
Other values (984) 2735
50.0%
2024-03-23T06:54:25.175673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5428
 
18.4%
1 1562
 
5.3%
시 1164
 
3.9%
산 1021
 
3.5%
금 856
 
2.9%
2 842
 
2.9%
동 835
 
2.8%
( 814
 
2.8%
) 814
 
2.8%
천 799
 
2.7%
Other values (265) 15401
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16585
56.2%
Space Separator 5428
 
18.4%
Decimal Number 5304
 
18.0%
Open Punctuation 880
 
3.0%
Close Punctuation 880
 
3.0%
Uppercase Letter 252
 
0.9%
Dash Punctuation 163
 
0.6%
Lowercase Letter 24
 
0.1%
Math Symbol 11
 
< 0.1%
Other Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1164
 
7.0%
산 1021
 
6.2%
금 856
 
5.2%
동 835
 
5.0%
천 799
 
4.8%
서 785
 
4.7%
울 759
 
4.6%
구 757
 
4.6%
별 754
 
4.5%
특 754
 
4.5%
Other values (220) 8101
48.8%
Uppercase Letter
ValueCountFrequency (%)
B 61
24.2%
T 48
19.0%
I 47
18.7%
A 17
 
6.7%
G 11
 
4.4%
K 11
 
4.4%
C 10
 
4.0%
S 10
 
4.0%
L 9
 
3.6%
V 7
 
2.8%
Other values (8) 21
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 1562
29.4%
2 842
15.9%
0 594
 
11.2%
3 493
 
9.3%
4 387
 
7.3%
5 306
 
5.8%
6 292
 
5.5%
9 289
 
5.4%
7 273
 
5.1%
8 266
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
e 7
29.2%
b 6
25.0%
r 3
12.5%
o 2
 
8.3%
w 2
 
8.3%
u 1
 
4.2%
t 1
 
4.2%
n 1
 
4.2%
a 1
 
4.2%
Open Punctuation
ValueCountFrequency (%)
( 814
92.5%
[ 66
 
7.5%
Close Punctuation
ValueCountFrequency (%)
) 814
92.5%
] 66
 
7.5%
Space Separator
ValueCountFrequency (%)
5428
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 163
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16585
56.2%
Common 12675
42.9%
Latin 276
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1164
 
7.0%
산 1021
 
6.2%
금 856
 
5.2%
동 835
 
5.0%
천 799
 
4.8%
서 785
 
4.7%
울 759
 
4.6%
구 757
 
4.6%
별 754
 
4.5%
특 754
 
4.5%
Other values (220) 8101
48.8%
Latin
ValueCountFrequency (%)
B 61
22.1%
T 48
17.4%
I 47
17.0%
A 17
 
6.2%
G 11
 
4.0%
K 11
 
4.0%
C 10
 
3.6%
S 10
 
3.6%
L 9
 
3.3%
e 7
 
2.5%
Other values (17) 45
16.3%
Common
ValueCountFrequency (%)
5428
42.8%
1 1562
 
12.3%
2 842
 
6.6%
( 814
 
6.4%
) 814
 
6.4%
0 594
 
4.7%
3 493
 
3.9%
4 387
 
3.1%
5 306
 
2.4%
6 292
 
2.3%
Other values (8) 1143
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16585
56.2%
ASCII 12951
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5428
41.9%
1 1562
 
12.1%
2 842
 
6.5%
( 814
 
6.3%
) 814
 
6.3%
0 594
 
4.6%
3 493
 
3.8%
4 387
 
3.0%
5 306
 
2.4%
6 292
 
2.3%
Other values (35) 1419
 
11.0%
Hangul
ValueCountFrequency (%)
시 1164
 
7.0%
산 1021
 
6.2%
금 856
 
5.2%
동 835
 
5.0%
천 799
 
4.8%
서 785
 
4.7%
울 759
 
4.6%
구 757
 
4.6%
별 754
 
4.5%
특 754
 
4.5%
Other values (220) 8101
48.8%

소재지전화번호
Text

Distinct397
Distinct (%)52.7%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-03-23T06:54:25.992818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length9.4814324
Min length7

Characters and Unicode

Total characters7149
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique376 ?
Unique (%)49.9%

Sample

1st row02-858-5236
2nd row02-807-6767
3rd row02-893-0222
4th row02-898-7093
5th row02-867-0025
ValueCountFrequency (%)
데이터 337
30.9%
미집계 337
30.9%
02-6960-2500 3
 
0.3%
02-6407-3937 2
 
0.2%
02-855-6275 2
 
0.2%
02-6265-2399 2
 
0.2%
02-869-6930 2
 
0.2%
02-863-8004 2
 
0.2%
02-804-3980 2
 
0.2%
02-868-8020 2
 
0.2%
Other values (388) 400
36.7%
2024-03-23T06:54:27.737290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 847
 
11.8%
- 825
 
11.5%
2 623
 
8.7%
8 511
 
7.1%
계 337
 
4.7%
이 337
 
4.7%
데 337
 
4.7%
집 337
 
4.7%
미 337
 
4.7%
337
 
4.7%
Other values (8) 2321
32.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3965
55.5%
Other Letter 2022
28.3%
Dash Punctuation 825
 
11.5%
Space Separator 337
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 847
21.4%
2 623
15.7%
8 511
12.9%
6 324
 
8.2%
5 297
 
7.5%
7 297
 
7.5%
3 297
 
7.5%
1 271
 
6.8%
9 265
 
6.7%
4 233
 
5.9%
Other Letter
ValueCountFrequency (%)
계 337
16.7%
이 337
16.7%
데 337
16.7%
집 337
16.7%
미 337
16.7%
터 337
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 825
100.0%
Space Separator
ValueCountFrequency (%)
337
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5127
71.7%
Hangul 2022
 
28.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 847
16.5%
- 825
16.1%
2 623
12.2%
8 511
10.0%
337
 
6.6%
6 324
 
6.3%
5 297
 
5.8%
7 297
 
5.8%
3 297
 
5.8%
1 271
 
5.3%
Other values (2) 498
9.7%
Hangul
ValueCountFrequency (%)
계 337
16.7%
이 337
16.7%
데 337
16.7%
집 337
16.7%
미 337
16.7%
터 337
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5127
71.7%
Hangul 2022
 
28.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 847
16.5%
- 825
16.1%
2 623
12.2%
8 511
10.0%
337
 
6.6%
6 324
 
6.3%
5 297
 
5.8%
7 297
 
5.8%
3 297
 
5.8%
1 271
 
5.3%
Other values (2) 498
9.7%
Hangul
ValueCountFrequency (%)
계 337
16.7%
이 337
16.7%
데 337
16.7%
집 337
16.7%
미 337
16.7%
터 337
16.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
Minimum2024-03-04 00:00:00
Maximum2024-03-04 00:00:00
2024-03-23T06:54:28.327806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:54:28.746544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-03-23T06:54:17.353837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T06:54:18.104511image/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

업종업소명소재지(도로명)소재지전화번호데이터기준일자
0식품제조가공업J·A FOOD서울특별시 금천구 벚꽃로56길 66 (가산동 [순환샛길 58])02-858-52362024-03-04
1식품제조가공업(주)서래서울특별시 금천구 범안로11길 61 1층 (독산동)02-807-67672024-03-04
2식품제조가공업일동민속과자서울특별시 금천구 독산로64길 34 (독산동 [정훈1길 34])02-893-02222024-03-04
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8식품제조가공업한양 다솔서울특별시 금천구 시흥대로18길 7 3층 (시흥동)데이터 미집계2024-03-04
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업종업소명소재지(도로명)소재지전화번호데이터기준일자
744기타식품판매업뉴영슈퍼서울특별시 금천구 시흥대로39길 45 (시흥동)데이터 미집계2024-03-04
745식품냉동.냉장업사조산업(주)독산냉장서울특별시 금천구 두산로7길 13 (독산동 [두산4길 7])데이터 미집계2024-03-04
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0즉석판매제조가공업장원에프엔비서울특별시 금천구 시흥대로 201 홈플러스테스테스코(주)시흥점 지하1층 일부호 (시흥동)데이터 미집계2024-03-042