Overview

Dataset statistics

Number of variables7
Number of observations879
Missing cells624
Missing cells (%)10.1%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory49.1 KiB
Average record size in memory57.1 B

Variable types

Categorical1
Text5
Numeric1

Dataset

Description동래구 관내 건강기능식품판매업소 현황에 대한 데이터로 업종명, 업소명, 소재지, 전화번호, 우편번호 등의 항목을 제공합니다.
Author부산광역시 동래구
URLhttps://www.data.go.kr/data/3081206/fileData.do

Alerts

Dataset has 1 (0.1%) duplicate rowsDuplicates
업종명 is highly imbalanced (85.6%)Imbalance
전화번호 has 612 (69.6%) missing valuesMissing
우편번호(도로명) has 12 (1.4%) missing valuesMissing

Reproduction

Analysis started2024-03-15 00:34:02.008579
Analysis finished2024-03-15 00:34:04.480435
Duration2.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
건강기능식품일반판매업
861 
건강기능식품유통전문판매업
 
18

Length

Max length13
Median length11
Mean length11.040956
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강기능식품일반판매업 861
98.0%
건강기능식품유통전문판매업 18
 
2.0%

Length

2024-03-15T09:34:04.722679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:34:05.081360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강기능식품일반판매업 861
98.0%
건강기능식품유통전문판매업 18
 
2.0%

업소명
Text

Distinct864
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-03-15T09:34:06.222321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length20
Mean length6.7792947
Min length2

Characters and Unicode

Total characters5959
Distinct characters527
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique851 ?
Unique (%)96.8%

Sample

1st row(주)그린바이오
2nd row(주)닥터엔누리
3rd row(주)사임당생활건강
4th row가디온이앤씨
5th row고려인삼제품(주)
ValueCountFrequency (%)
주식회사 22
 
2.1%
인셀덤 11
 
1.1%
동래점 9
 
0.9%
에치와이 5
 
0.5%
사직점 5
 
0.5%
애터미 4
 
0.4%
뉴질랜드 4
 
0.4%
허브다이어트 3
 
0.3%
온천점 3
 
0.3%
유니시티 3
 
0.3%
Other values (936) 967
93.3%
2024-03-15T09:34:08.155151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 186
 
3.1%
스 171
 
2.9%
157
 
2.6%
점 142
 
2.4%
( 131
 
2.2%
) 131
 
2.2%
주 117
 
2.0%
사 108
 
1.8%
리 104
 
1.7%
아 79
 
1.3%
Other values (517) 4633
77.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5174
86.8%
Uppercase Letter 179
 
3.0%
Space Separator 157
 
2.6%
Open Punctuation 131
 
2.2%
Close Punctuation 131
 
2.2%
Lowercase Letter 120
 
2.0%
Decimal Number 51
 
0.9%
Other Punctuation 14
 
0.2%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 186
 
3.6%
스 171
 
3.3%
점 142
 
2.7%
주 117
 
2.3%
사 108
 
2.1%
리 104
 
2.0%
아 79
 
1.5%
원 73
 
1.4%
동 73
 
1.4%
트 71
 
1.4%
Other values (457) 4050
78.3%
Uppercase Letter
ValueCountFrequency (%)
S 15
 
8.4%
E 14
 
7.8%
T 14
 
7.8%
C 12
 
6.7%
M 12
 
6.7%
R 11
 
6.1%
H 9
 
5.0%
L 9
 
5.0%
G 8
 
4.5%
B 8
 
4.5%
Other values (15) 67
37.4%
Lowercase Letter
ValueCountFrequency (%)
o 14
11.7%
n 13
 
10.8%
e 10
 
8.3%
a 10
 
8.3%
i 8
 
6.7%
m 8
 
6.7%
l 7
 
5.8%
h 6
 
5.0%
s 6
 
5.0%
r 5
 
4.2%
Other values (11) 33
27.5%
Decimal Number
ValueCountFrequency (%)
5 17
33.3%
2 12
23.5%
1 7
13.7%
0 6
 
11.8%
3 5
 
9.8%
8 2
 
3.9%
6 2
 
3.9%
Other Punctuation
ValueCountFrequency (%)
. 7
50.0%
& 6
42.9%
: 1
 
7.1%
Space Separator
ValueCountFrequency (%)
157
100.0%
Open Punctuation
ValueCountFrequency (%)
( 131
100.0%
Close Punctuation
ValueCountFrequency (%)
) 131
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5170
86.8%
Common 486
 
8.2%
Latin 299
 
5.0%
Han 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 186
 
3.6%
스 171
 
3.3%
점 142
 
2.7%
주 117
 
2.3%
사 108
 
2.1%
리 104
 
2.0%
아 79
 
1.5%
원 73
 
1.4%
동 73
 
1.4%
트 71
 
1.4%
Other values (453) 4046
78.3%
Latin
ValueCountFrequency (%)
S 15
 
5.0%
o 14
 
4.7%
E 14
 
4.7%
T 14
 
4.7%
n 13
 
4.3%
C 12
 
4.0%
M 12
 
4.0%
R 11
 
3.7%
e 10
 
3.3%
a 10
 
3.3%
Other values (36) 174
58.2%
Common
ValueCountFrequency (%)
157
32.3%
( 131
27.0%
) 131
27.0%
5 17
 
3.5%
2 12
 
2.5%
1 7
 
1.4%
. 7
 
1.4%
0 6
 
1.2%
& 6
 
1.2%
3 5
 
1.0%
Other values (4) 7
 
1.4%
Han
ValueCountFrequency (%)
多 1
25.0%
園 1
25.0%
炅 1
25.0%
溫 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5170
86.8%
ASCII 785
 
13.2%
CJK 4
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 186
 
3.6%
스 171
 
3.3%
점 142
 
2.7%
주 117
 
2.3%
사 108
 
2.1%
리 104
 
2.0%
아 79
 
1.5%
원 73
 
1.4%
동 73
 
1.4%
트 71
 
1.4%
Other values (453) 4046
78.3%
ASCII
ValueCountFrequency (%)
157
20.0%
( 131
16.7%
) 131
16.7%
5 17
 
2.2%
S 15
 
1.9%
o 14
 
1.8%
E 14
 
1.8%
T 14
 
1.8%
n 13
 
1.7%
2 12
 
1.5%
Other values (50) 267
34.0%
CJK
ValueCountFrequency (%)
多 1
25.0%
園 1
25.0%
炅 1
25.0%
溫 1
25.0%

소재지주소(도로명)
Text

Distinct848
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-03-15T09:34:09.463345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length52
Mean length35.278726
Min length21

Characters and Unicode

Total characters31010
Distinct characters301
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

Unique821 ?
Unique (%)93.4%

Sample

1st row부산광역시 동래구 아시아드대로 109, 6층 (사직동)
2nd row부산광역시 동래구 금강로 69, 2층 205호 (온천동, 온천프라자)
3rd row부산광역시 동래구 충렬대로108번길 78-2, 2층 (온천동)
4th row부산광역시 동래구 명륜로 229-1, 2층 (명륜동)
5th row부산광역시 동래구 충렬대로 79, 5층 (온천동)
ValueCountFrequency (%)
부산광역시 879
 
14.9%
동래구 877
 
14.9%
온천동 277
 
4.7%
사직동 163
 
2.8%
안락동 147
 
2.5%
1층 127
 
2.2%
2층 104
 
1.8%
충렬대로 80
 
1.4%
명륜동 74
 
1.3%
명장동 61
 
1.0%
Other values (1103) 3115
52.8%
2024-03-15T09:34:10.986260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5025
 
16.2%
동 2088
 
6.7%
1 1298
 
4.2%
, 1057
 
3.4%
래 979
 
3.2%
시 975
 
3.1%
산 905
 
2.9%
) 896
 
2.9%
( 896
 
2.9%
부 890
 
2.9%
Other values (291) 16001
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17447
56.3%
Decimal Number 5389
 
17.4%
Space Separator 5025
 
16.2%
Other Punctuation 1057
 
3.4%
Close Punctuation 896
 
2.9%
Open Punctuation 896
 
2.9%
Uppercase Letter 162
 
0.5%
Dash Punctuation 114
 
0.4%
Lowercase Letter 21
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2088
 
12.0%
래 979
 
5.6%
시 975
 
5.6%
산 905
 
5.2%
부 890
 
5.1%
광 883
 
5.1%
역 881
 
5.0%
구 881
 
5.0%
로 879
 
5.0%
층 446
 
2.6%
Other values (250) 7640
43.8%
Uppercase Letter
ValueCountFrequency (%)
K 37
22.8%
S 34
21.0%
B 13
 
8.0%
A 10
 
6.2%
W 9
 
5.6%
I 9
 
5.6%
V 8
 
4.9%
E 8
 
4.9%
U 8
 
4.9%
H 8
 
4.9%
Other values (6) 18
11.1%
Decimal Number
ValueCountFrequency (%)
1 1298
24.1%
2 857
15.9%
0 692
12.8%
3 616
11.4%
4 445
 
8.3%
5 361
 
6.7%
7 310
 
5.8%
9 290
 
5.4%
6 284
 
5.3%
8 236
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
e 9
42.9%
i 2
 
9.5%
l 2
 
9.5%
v 2
 
9.5%
o 2
 
9.5%
b 1
 
4.8%
k 1
 
4.8%
s 1
 
4.8%
n 1
 
4.8%
Space Separator
ValueCountFrequency (%)
5025
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1057
100.0%
Close Punctuation
ValueCountFrequency (%)
) 896
100.0%
Open Punctuation
ValueCountFrequency (%)
( 896
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17447
56.3%
Common 13380
43.1%
Latin 183
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2088
 
12.0%
래 979
 
5.6%
시 975
 
5.6%
산 905
 
5.2%
부 890
 
5.1%
광 883
 
5.1%
역 881
 
5.0%
구 881
 
5.0%
로 879
 
5.0%
층 446
 
2.6%
Other values (250) 7640
43.8%
Latin
ValueCountFrequency (%)
K 37
20.2%
S 34
18.6%
B 13
 
7.1%
A 10
 
5.5%
e 9
 
4.9%
W 9
 
4.9%
I 9
 
4.9%
V 8
 
4.4%
E 8
 
4.4%
U 8
 
4.4%
Other values (15) 38
20.8%
Common
ValueCountFrequency (%)
5025
37.6%
1 1298
 
9.7%
, 1057
 
7.9%
) 896
 
6.7%
( 896
 
6.7%
2 857
 
6.4%
0 692
 
5.2%
3 616
 
4.6%
4 445
 
3.3%
5 361
 
2.7%
Other values (6) 1237
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17447
56.3%
ASCII 13563
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5025
37.0%
1 1298
 
9.6%
, 1057
 
7.8%
) 896
 
6.6%
( 896
 
6.6%
2 857
 
6.3%
0 692
 
5.1%
3 616
 
4.5%
4 445
 
3.3%
5 361
 
2.7%
Other values (31) 1420
 
10.5%
Hangul
ValueCountFrequency (%)
동 2088
 
12.0%
래 979
 
5.6%
시 975
 
5.6%
산 905
 
5.2%
부 890
 
5.1%
광 883
 
5.1%
역 881
 
5.0%
구 881
 
5.0%
로 879
 
5.0%
층 446
 
2.6%
Other values (250) 7640
43.8%

소재지주소(지번)
Text

Distinct716
Distinct (%)81.5%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-03-15T09:34:12.000734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length39
Mean length24.463026
Min length18

Characters and Unicode

Total characters21503
Distinct characters280
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

Unique621 ?
Unique (%)70.6%

Sample

1st row부산광역시 동래구 사직동 104-9 6층
2nd row부산광역시 동래구 온천동 435-1 온천프라자
3rd row부산광역시 동래구 온천동 1460-10
4th row부산광역시 동래구 명륜동 67-12
5th row부산광역시 동래구 온천동 1400-6
ValueCountFrequency (%)
부산광역시 879
20.9%
동래구 877
20.8%
온천동 293
 
7.0%
사직동 172
 
4.1%
안락동 156
 
3.7%
명륜동 85
 
2.0%
명장동 64
 
1.5%
수안동 61
 
1.4%
낙민동 37
 
0.9%
1층 35
 
0.8%
Other values (973) 1553
36.9%
2024-03-15T09:34:13.386731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4175
19.4%
동 1880
 
8.7%
래 952
 
4.4%
1 924
 
4.3%
산 903
 
4.2%
시 892
 
4.1%
부 884
 
4.1%
광 882
 
4.1%
역 881
 
4.1%
구 881
 
4.1%
Other values (270) 8249
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12189
56.7%
Space Separator 4175
 
19.4%
Decimal Number 4170
 
19.4%
Dash Punctuation 743
 
3.5%
Uppercase Letter 132
 
0.6%
Close Punctuation 34
 
0.2%
Open Punctuation 34
 
0.2%
Lowercase Letter 20
 
0.1%
Other Punctuation 4
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1880
15.4%
래 952
 
7.8%
산 903
 
7.4%
시 892
 
7.3%
부 884
 
7.3%
광 882
 
7.2%
역 881
 
7.2%
구 881
 
7.2%
천 332
 
2.7%
온 316
 
2.6%
Other values (231) 3386
27.8%
Uppercase Letter
ValueCountFrequency (%)
K 32
24.2%
S 28
21.2%
I 9
 
6.8%
B 8
 
6.1%
V 8
 
6.1%
E 8
 
6.1%
W 8
 
6.1%
H 7
 
5.3%
U 7
 
5.3%
C 6
 
4.5%
Other values (5) 11
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 924
22.2%
2 584
14.0%
4 496
11.9%
3 427
10.2%
5 370
8.9%
0 336
 
8.1%
6 300
 
7.2%
7 269
 
6.5%
9 241
 
5.8%
8 223
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
e 9
45.0%
v 2
 
10.0%
i 2
 
10.0%
l 2
 
10.0%
o 2
 
10.0%
k 1
 
5.0%
s 1
 
5.0%
n 1
 
5.0%
Space Separator
ValueCountFrequency (%)
4175
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 743
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12189
56.7%
Common 9162
42.6%
Latin 152
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1880
15.4%
래 952
 
7.8%
산 903
 
7.4%
시 892
 
7.3%
부 884
 
7.3%
광 882
 
7.2%
역 881
 
7.2%
구 881
 
7.2%
천 332
 
2.7%
온 316
 
2.6%
Other values (231) 3386
27.8%
Latin
ValueCountFrequency (%)
K 32
21.1%
S 28
18.4%
I 9
 
5.9%
e 9
 
5.9%
B 8
 
5.3%
V 8
 
5.3%
E 8
 
5.3%
W 8
 
5.3%
H 7
 
4.6%
U 7
 
4.6%
Other values (13) 28
18.4%
Common
ValueCountFrequency (%)
4175
45.6%
1 924
 
10.1%
- 743
 
8.1%
2 584
 
6.4%
4 496
 
5.4%
3 427
 
4.7%
5 370
 
4.0%
0 336
 
3.7%
6 300
 
3.3%
7 269
 
2.9%
Other values (6) 538
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12189
56.7%
ASCII 9314
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4175
44.8%
1 924
 
9.9%
- 743
 
8.0%
2 584
 
6.3%
4 496
 
5.3%
3 427
 
4.6%
5 370
 
4.0%
0 336
 
3.6%
6 300
 
3.2%
7 269
 
2.9%
Other values (29) 690
 
7.4%
Hangul
ValueCountFrequency (%)
동 1880
15.4%
래 952
 
7.8%
산 903
 
7.4%
시 892
 
7.3%
부 884
 
7.3%
광 882
 
7.2%
역 881
 
7.2%
구 881
 
7.2%
천 332
 
2.7%
온 316
 
2.6%
Other values (231) 3386
27.8%

전화번호
Text

MISSING 

Distinct263
Distinct (%)98.5%
Missing612
Missing (%)69.6%
Memory size7.0 KiB
2024-03-15T09:34:14.268138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters3738
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

Unique259 ?
Unique (%)97.0%

Sample

1st row051 -507 -7670
2nd row051 -711 -2060
3rd row051 -581 -8636
4th row051 -501 -7711
5th row051 -913 -4217
ValueCountFrequency (%)
051 263
37.3%
501 11
 
1.6%
552 10
 
1.4%
507 9
 
1.3%
558 8
 
1.1%
555 8
 
1.1%
553 7
 
1.0%
557 6
 
0.8%
506 6
 
0.8%
532 5
 
0.7%
Other values (321) 373
52.8%
2024-03-15T09:34:15.521307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 726
19.4%
534
14.3%
- 534
14.3%
0 503
13.5%
1 432
11.6%
2 188
 
5.0%
7 172
 
4.6%
8 158
 
4.2%
3 151
 
4.0%
6 133
 
3.6%
Other values (2) 207
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2670
71.4%
Space Separator 534
 
14.3%
Dash Punctuation 534
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 726
27.2%
0 503
18.8%
1 432
16.2%
2 188
 
7.0%
7 172
 
6.4%
8 158
 
5.9%
3 151
 
5.7%
6 133
 
5.0%
4 114
 
4.3%
9 93
 
3.5%
Space Separator
ValueCountFrequency (%)
534
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 534
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3738
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 726
19.4%
534
14.3%
- 534
14.3%
0 503
13.5%
1 432
11.6%
2 188
 
5.0%
7 172
 
4.6%
8 158
 
4.2%
3 151
 
4.0%
6 133
 
3.6%
Other values (2) 207
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3738
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 726
19.4%
534
14.3%
- 534
14.3%
0 503
13.5%
1 432
11.6%
2 188
 
5.0%
7 172
 
4.6%
8 158
 
4.2%
3 151
 
4.0%
6 133
 
3.6%
Other values (2) 207
 
5.5%

우편번호(도로명)
Real number (ℝ)

MISSING 

Distinct178
Distinct (%)20.5%
Missing12
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean47799.724
Minimum46743
Maximum48107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2024-03-15T09:34:15.769631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46743
5-th percentile47711
Q147740.5
median47810
Q347856
95-th percentile47894
Maximum48107
Range1364
Interquartile range (IQR)115.5

Descriptive statistics

Standard deviation71.141056
Coefficient of variation (CV)0.0014883152
Kurtosis54.892139
Mean47799.724
Median Absolute Deviation (MAD)55
Skewness-3.6808747
Sum41442361
Variance5061.0498
MonotonicityNot monotonic
2024-03-15T09:34:16.048506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47814 18
 
2.0%
47727 18
 
2.0%
47813 17
 
1.9%
47710 16
 
1.8%
47905 15
 
1.7%
47734 15
 
1.7%
47889 14
 
1.6%
47711 13
 
1.5%
47837 13
 
1.5%
47712 12
 
1.4%
Other values (168) 716
81.5%
ValueCountFrequency (%)
46743 1
 
0.1%
47703 1
 
0.1%
47705 6
 
0.7%
47706 6
 
0.7%
47708 5
 
0.6%
47709 5
 
0.6%
47710 16
1.8%
47711 13
1.5%
47712 12
1.4%
47713 4
 
0.5%
ValueCountFrequency (%)
48107 1
 
0.1%
47905 15
1.7%
47904 3
 
0.3%
47903 1
 
0.1%
47902 3
 
0.3%
47901 4
 
0.5%
47898 8
0.9%
47897 1
 
0.1%
47896 2
 
0.2%
47895 5
 
0.6%

우편번호(지번)
Text

Distinct73
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size7.0 KiB
2024-03-15T09:34:16.841109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters6153
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

Unique15 ?
Unique (%)1.7%

Sample

1st row607-817
2nd row607-834
3rd row607-843
4th row607-802
5th row607-837
ValueCountFrequency (%)
607-837 45
 
5.1%
607-804 37
 
4.2%
607-838 36
 
4.1%
607-825 32
 
3.6%
607-120 31
 
3.5%
607-824 31
 
3.5%
607-815 30
 
3.4%
607-827 30
 
3.4%
607-842 29
 
3.3%
607-834 29
 
3.3%
Other values (63) 549
62.5%
2024-03-15T09:34:17.823222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1199
19.5%
7 1044
17.0%
6 953
15.5%
- 879
14.3%
8 840
13.7%
3 315
 
5.1%
2 310
 
5.0%
1 281
 
4.6%
4 184
 
3.0%
5 95
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5274
85.7%
Dash Punctuation 879
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1199
22.7%
7 1044
19.8%
6 953
18.1%
8 840
15.9%
3 315
 
6.0%
2 310
 
5.9%
1 281
 
5.3%
4 184
 
3.5%
5 95
 
1.8%
9 53
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 879
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6153
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1199
19.5%
7 1044
17.0%
6 953
15.5%
- 879
14.3%
8 840
13.7%
3 315
 
5.1%
2 310
 
5.0%
1 281
 
4.6%
4 184
 
3.0%
5 95
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6153
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1199
19.5%
7 1044
17.0%
6 953
15.5%
- 879
14.3%
8 840
13.7%
3 315
 
5.1%
2 310
 
5.0%
1 281
 
4.6%
4 184
 
3.0%
5 95
 
1.5%

Interactions

2024-03-15T09:34:03.059431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:34:17.984217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명우편번호(도로명)우편번호(지번)
업종명1.0000.0000.000
우편번호(도로명)0.0001.0000.992
우편번호(지번)0.0000.9921.000
2024-03-15T09:34:18.143252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호(도로명)업종명
우편번호(도로명)1.0000.000
업종명0.0001.000

Missing values

2024-03-15T09:34:03.445896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:34:04.048723image/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.
2024-03-15T09:34:04.343168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업종명업소명소재지주소(도로명)소재지주소(지번)전화번호우편번호(도로명)우편번호(지번)
0건강기능식품유통전문판매업(주)그린바이오부산광역시 동래구 아시아드대로 109, 6층 (사직동)부산광역시 동래구 사직동 104-9 6층<NA>47876607-817
1건강기능식품유통전문판매업(주)닥터엔누리부산광역시 동래구 금강로 69, 2층 205호 (온천동, 온천프라자)부산광역시 동래구 온천동 435-1 온천프라자<NA>47706607-834
2건강기능식품유통전문판매업(주)사임당생활건강부산광역시 동래구 충렬대로108번길 78-2, 2층 (온천동)부산광역시 동래구 온천동 1460-10<NA>47826607-843
3건강기능식품유통전문판매업가디온이앤씨부산광역시 동래구 명륜로 229-1, 2층 (명륜동)부산광역시 동래구 명륜동 67-12<NA>47740607-802
4건강기능식품유통전문판매업고려인삼제품(주)부산광역시 동래구 충렬대로 79, 5층 (온천동)부산광역시 동래구 온천동 1400-6051 -507 -767047731607-837
5건강기능식품유통전문판매업동래봄산부인과의원부산광역시 동래구 동래로 25, 이즈메디컬 9층 (온천동)부산광역시 동래구 온천동 473-21051 -711 -206047715607-834
6건강기능식품유통전문판매업메디리프부산광역시 동래구 온천장로 75, 102호 (온천동, KH파인우스)부산광역시 동래구 온천동 182-7 KH파인우스<NA>47712607-833
7건강기능식품유통전문판매업비알컴퍼니(BRC)부산광역시 동래구 금정마을로 150, 202동 1104호 (온천동, 동래 래미안 아이파크)부산광역시 동래구 온천동 905 동래 래미안 아이파크051 -581 -863647719607-838
8건강기능식품유통전문판매업비엘메딕스부산광역시 동래구 충렬대로75번길 10, 1102호 (온천동)부산광역시 동래구 온천동 1394-1<NA>47724607-837
9건강기능식품유통전문판매업엠에스협동조합부산광역시 동래구 사직북로47번길 17, 경훈빌딩 2층 (사직동)부산광역시 동래구 사직동 26-5 경훈빌딩<NA>47860607-815
업종명업소명소재지주소(도로명)소재지주소(지번)전화번호우편번호(도로명)우편번호(지번)
869건강기능식품일반판매업홍가네 홀쇼핑부산광역시 동래구 명안로9번길 3 (안락동)부산광역시 동래구 안락동 590-10<NA>47796607-828
870건강기능식품일반판매업홍당무부산광역시 동래구 아시아드대로 195, 1층 (온천동)부산광역시 동래구 온천동 1266-22<NA>47852607-841
871건강기능식품일반판매업홍삼나라사직점부산광역시 동래구 사직북로47번길 30-1 (사직동)부산광역시 동래구 사직동 45-42051- 505-032347864607-815
872건강기능식품일반판매업홍삼마을부산광역시 동래구 동래로147번길 16 (복천동)부산광역시 동래구 복천동 181-4 1층<NA>47802607-020
873건강기능식품일반판매업홍삼월드부산광역시 동래구 석사북로 23 (사직동)부산광역시 동래구 사직동 19-42051-502 -158847857607-120
874건강기능식품일반판매업화목건강부산광역시 동래구 충렬사로 50 (안락동)부산광역시 동래구 안락동 946-1051 -528 -035847754607-827
875건강기능식품일반판매업황옥련부산광역시 동래구 충렬대로107번길 54, 9동 509호 (온천동, 럭키아파트)부산광역시 동래구 온천동 707 럭키아파트 9동 509호051- 557-006147732607-753
876건강기능식품일반판매업효소그린부산광역시 동래구 시실로 22 (명륜동,2층)부산광역시 동래구 명륜동 7-1 2층051 -557 -399347744607-802
877건강기능식품일반판매업후니즈부산광역시 동래구 여고북로123번길 58, 601호 (온천동, 두루예시카하우스)부산광역시 동래구 온천동 1450-10 두루예시카하우스<NA>47826607-843
878건강기능식품일반판매업히피니스부산광역시 동래구 충렬대로107번길 54, 8동 905호 (온천동, 럭키아파트)부산광역시 동래구 온천동 707 럭키아파트<NA>47732607-753

Duplicate rows

Most frequently occurring

업종명업소명소재지주소(도로명)소재지주소(지번)전화번호우편번호(도로명)우편번호(지번)# duplicates
0건강기능식품일반판매업인셀덤보나대리점부산광역시 동래구 우장춘로63번길 46, 601호 (온천동, 일신빌라)부산광역시 동래구 온천동 1056-6 일신빌라<NA>47717607-8382