Overview

Dataset statistics

Number of variables5
Number of observations1017
Missing cells817
Missing cells (%)16.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory40.8 KiB
Average record size in memory41.1 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description경상남도 김해시 의료기기판매임대업소 현황에 대한 데이터로 영업구분, 영업소명,영업소소재지,영업소전화번호 항목을 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15033425

Alerts

영업구분 is highly imbalanced (83.1%)Imbalance
영업소전화번호 has 816 (80.2%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-13 00:09:13.761540
Analysis finished2024-03-13 00:09:14.402422
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct1017
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean509
Minimum1
Maximum1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-03-13T09:09:14.463767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile51.8
Q1255
median509
Q3763
95-th percentile966.2
Maximum1017
Range1016
Interquartile range (IQR)508

Descriptive statistics

Standard deviation293.72691
Coefficient of variation (CV)0.57706663
Kurtosis-1.2
Mean509
Median Absolute Deviation (MAD)254
Skewness0
Sum517653
Variance86275.5
MonotonicityStrictly increasing
2024-03-13T09:09:14.567427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
684 1
 
0.1%
671 1
 
0.1%
672 1
 
0.1%
673 1
 
0.1%
674 1
 
0.1%
675 1
 
0.1%
676 1
 
0.1%
677 1
 
0.1%
678 1
 
0.1%
Other values (1007) 1007
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 (%)
1017 1
0.1%
1016 1
0.1%
1015 1
0.1%
1014 1
0.1%
1013 1
0.1%
1012 1
0.1%
1011 1
0.1%
1010 1
0.1%
1009 1
0.1%
1008 1
0.1%

영업구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
판매업
974 
판매(임대)업
 
40
임대업
 
3

Length

Max length7
Median length3
Mean length3.1573255
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
판매업 974
95.8%
판매(임대)업 40
 
3.9%
임대업 3
 
0.3%

Length

2024-03-13T09:09:14.670871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T09:09:14.754904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
판매업 974
95.8%
판매(임대)업 40
 
3.9%
임대업 3
 
0.3%

영업소명
Text

Distinct1010
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-03-13T09:09:14.944841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length21
Mean length9.1474926
Min length2

Characters and Unicode

Total characters9303
Distinct characters517
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1003 ?
Unique (%)98.6%

Sample

1st row퓨어리티
2nd row씨유 김해구산수로점
3rd row지앤지래드콘 영남지사
4th row리브레타
5th row하이케어팜(Highcare pharm)
ValueCountFrequency (%)
씨유 75
 
5.0%
세븐일레븐 58
 
3.9%
주식회사 44
 
2.9%
gs25 31
 
2.1%
지에스25 21
 
1.4%
이마트24 19
 
1.3%
지에스(gs)25 13
 
0.9%
주)코리아세븐 13
 
0.9%
김해점 13
 
0.9%
cu 12
 
0.8%
Other values (1084) 1199
80.0%
2024-03-13T09:09:15.288852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 550
 
5.9%
482
 
5.2%
해 333
 
3.6%
김 318
 
3.4%
유 248
 
2.7%
스 236
 
2.5%
이 193
 
2.1%
주 170
 
1.8%
2 170
 
1.8%
) 163
 
1.8%
Other values (507) 6440
69.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7641
82.1%
Space Separator 482
 
5.2%
Uppercase Letter 377
 
4.1%
Decimal Number 368
 
4.0%
Close Punctuation 163
 
1.8%
Open Punctuation 161
 
1.7%
Lowercase Letter 95
 
1.0%
Other Punctuation 8
 
0.1%
Other Symbol 6
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 550
 
7.2%
해 333
 
4.4%
김 318
 
4.2%
유 248
 
3.2%
스 236
 
3.1%
이 193
 
2.5%
주 170
 
2.2%
씨 150
 
2.0%
븐 146
 
1.9%
지 136
 
1.8%
Other values (446) 5161
67.5%
Uppercase Letter
ValueCountFrequency (%)
S 103
27.3%
G 97
25.7%
C 43
11.4%
U 40
 
10.6%
H 13
 
3.4%
M 7
 
1.9%
Y 7
 
1.9%
I 7
 
1.9%
B 6
 
1.6%
N 6
 
1.6%
Other values (13) 48
12.7%
Lowercase Letter
ValueCountFrequency (%)
c 10
 
10.5%
i 9
 
9.5%
e 8
 
8.4%
a 8
 
8.4%
n 6
 
6.3%
u 6
 
6.3%
h 5
 
5.3%
m 5
 
5.3%
l 5
 
5.3%
r 4
 
4.2%
Other values (11) 29
30.5%
Decimal Number
ValueCountFrequency (%)
2 170
46.2%
5 141
38.3%
4 32
 
8.7%
3 10
 
2.7%
6 5
 
1.4%
0 5
 
1.4%
1 3
 
0.8%
7 2
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 6
75.0%
& 1
 
12.5%
? 1
 
12.5%
Space Separator
ValueCountFrequency (%)
482
100.0%
Close Punctuation
ValueCountFrequency (%)
) 163
100.0%
Open Punctuation
ValueCountFrequency (%)
( 161
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7647
82.2%
Common 1184
 
12.7%
Latin 472
 
5.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 550
 
7.2%
해 333
 
4.4%
김 318
 
4.2%
유 248
 
3.2%
스 236
 
3.1%
이 193
 
2.5%
주 170
 
2.2%
씨 150
 
2.0%
븐 146
 
1.9%
지 136
 
1.8%
Other values (447) 5167
67.6%
Latin
ValueCountFrequency (%)
S 103
21.8%
G 97
20.6%
C 43
 
9.1%
U 40
 
8.5%
H 13
 
2.8%
c 10
 
2.1%
i 9
 
1.9%
e 8
 
1.7%
a 8
 
1.7%
M 7
 
1.5%
Other values (34) 134
28.4%
Common
ValueCountFrequency (%)
482
40.7%
2 170
 
14.4%
) 163
 
13.8%
( 161
 
13.6%
5 141
 
11.9%
4 32
 
2.7%
3 10
 
0.8%
. 6
 
0.5%
6 5
 
0.4%
0 5
 
0.4%
Other values (6) 9
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7641
82.1%
ASCII 1656
 
17.8%
None 6
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 550
 
7.2%
해 333
 
4.4%
김 318
 
4.2%
유 248
 
3.2%
스 236
 
3.1%
이 193
 
2.5%
주 170
 
2.2%
씨 150
 
2.0%
븐 146
 
1.9%
지 136
 
1.8%
Other values (446) 5161
67.5%
ASCII
ValueCountFrequency (%)
482
29.1%
2 170
 
10.3%
) 163
 
9.8%
( 161
 
9.7%
5 141
 
8.5%
S 103
 
6.2%
G 97
 
5.9%
C 43
 
2.6%
U 40
 
2.4%
4 32
 
1.9%
Other values (50) 224
13.5%
None
ValueCountFrequency (%)
㈜ 6
100.0%

영업소소재지(도로명)
Text

Distinct996
Distinct (%)98.0%
Missing1
Missing (%)0.1%
Memory size8.1 KiB
2024-03-13T09:09:15.536579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length50
Mean length31.179134
Min length18

Characters and Unicode

Total characters31678
Distinct characters289
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique980 ?
Unique (%)96.5%

Sample

1st row경상남도 김해시 금관대로1365번길 10-19 (내동)
2nd row경상남도 김해시 가락로176번길 2, 1층 (구산동)
3rd row경상남도 김해시 전하로13번길 3 (풍유동)
4th row경상남도 김해시 칠산로387번길 59, 1층 (풍유동)
5th row경상남도 김해시 분성로 155, 322동 1408호 (외동, 한국2차아파트)
ValueCountFrequency (%)
경상남도 1016
 
16.3%
김해시 1016
 
16.3%
1층 235
 
3.8%
진영읍 91
 
1.5%
외동 78
 
1.2%
대청동 60
 
1.0%
삼계동 57
 
0.9%
2층 55
 
0.9%
내동 54
 
0.9%
101호 51
 
0.8%
Other values (1375) 3539
56.6%
2024-03-13T09:09:15.913495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5240
 
16.5%
1 1577
 
5.0%
해 1183
 
3.7%
상 1176
 
3.7%
김 1155
 
3.6%
동 1126
 
3.6%
시 1031
 
3.3%
경 1030
 
3.3%
남 1030
 
3.3%
도 1018
 
3.2%
Other values (279) 16112
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17715
55.9%
Decimal Number 5993
 
18.9%
Space Separator 5240
 
16.5%
Close Punctuation 834
 
2.6%
Open Punctuation 834
 
2.6%
Other Punctuation 804
 
2.5%
Dash Punctuation 221
 
0.7%
Uppercase Letter 26
 
0.1%
Math Symbol 7
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
해 1183
 
6.7%
상 1176
 
6.6%
김 1155
 
6.5%
동 1126
 
6.4%
시 1031
 
5.8%
경 1030
 
5.8%
남 1030
 
5.8%
도 1018
 
5.7%
로 1009
 
5.7%
번 520
 
2.9%
Other values (252) 7437
42.0%
Decimal Number
ValueCountFrequency (%)
1 1577
26.3%
2 905
15.1%
0 728
12.1%
3 644
10.7%
4 478
 
8.0%
5 400
 
6.7%
6 352
 
5.9%
9 311
 
5.2%
7 303
 
5.1%
8 295
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
B 8
30.8%
S 5
19.2%
A 4
15.4%
D 2
 
7.7%
T 2
 
7.7%
Q 1
 
3.8%
M 1
 
3.8%
H 1
 
3.8%
I 1
 
3.8%
E 1
 
3.8%
Space Separator
ValueCountFrequency (%)
5240
100.0%
Close Punctuation
ValueCountFrequency (%)
) 834
100.0%
Open Punctuation
ValueCountFrequency (%)
( 834
100.0%
Other Punctuation
ValueCountFrequency (%)
, 804
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 221
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17715
55.9%
Common 13933
44.0%
Latin 30
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
해 1183
 
6.7%
상 1176
 
6.6%
김 1155
 
6.5%
동 1126
 
6.4%
시 1031
 
5.8%
경 1030
 
5.8%
남 1030
 
5.8%
도 1018
 
5.7%
로 1009
 
5.7%
번 520
 
2.9%
Other values (252) 7437
42.0%
Common
ValueCountFrequency (%)
5240
37.6%
1 1577
 
11.3%
2 905
 
6.5%
) 834
 
6.0%
( 834
 
6.0%
, 804
 
5.8%
0 728
 
5.2%
3 644
 
4.6%
4 478
 
3.4%
5 400
 
2.9%
Other values (6) 1489
 
10.7%
Latin
ValueCountFrequency (%)
B 8
26.7%
S 5
16.7%
e 4
13.3%
A 4
13.3%
D 2
 
6.7%
T 2
 
6.7%
Q 1
 
3.3%
M 1
 
3.3%
H 1
 
3.3%
I 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17714
55.9%
ASCII 13963
44.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5240
37.5%
1 1577
 
11.3%
2 905
 
6.5%
) 834
 
6.0%
( 834
 
6.0%
, 804
 
5.8%
0 728
 
5.2%
3 644
 
4.6%
4 478
 
3.4%
5 400
 
2.9%
Other values (17) 1519
 
10.9%
Hangul
ValueCountFrequency (%)
해 1183
 
6.7%
상 1176
 
6.6%
김 1155
 
6.5%
동 1126
 
6.4%
시 1031
 
5.8%
경 1030
 
5.8%
남 1030
 
5.8%
도 1018
 
5.7%
로 1009
 
5.7%
번 520
 
2.9%
Other values (251) 7436
42.0%
Compat Jamo
ValueCountFrequency (%)
ㅡ 1
100.0%

영업소전화번호
Text

MISSING 

Distinct197
Distinct (%)98.0%
Missing816
Missing (%)80.2%
Memory size8.1 KiB
2024-03-13T09:09:16.107981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.746269
Min length8

Characters and Unicode

Total characters2361
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

Unique194 ?
Unique (%)96.5%

Sample

1st row055-321-2747
2nd row055-324-9836
3rd row070-8989-9099
4th row055-337-3221
5th row055-312-7722
ValueCountFrequency (%)
055-330-4503 3
 
1.5%
055-338-8566 2
 
1.0%
055-338-9295 2
 
1.0%
055-339-4232 1
 
0.5%
055-314-6964 1
 
0.5%
055-343-1388 1
 
0.5%
055-346-7890 1
 
0.5%
055-299-8530 1
 
0.5%
055-343-1561 1
 
0.5%
055-332-3036 1
 
0.5%
Other values (187) 187
93.0%
2024-03-13T09:09:16.408332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 457
19.4%
- 387
16.4%
3 364
15.4%
0 323
13.7%
2 197
8.3%
1 144
 
6.1%
4 114
 
4.8%
7 102
 
4.3%
6 99
 
4.2%
8 93
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1974
83.6%
Dash Punctuation 387
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 457
23.2%
3 364
18.4%
0 323
16.4%
2 197
10.0%
1 144
 
7.3%
4 114
 
5.8%
7 102
 
5.2%
6 99
 
5.0%
8 93
 
4.7%
9 81
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 387
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2361
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 457
19.4%
- 387
16.4%
3 364
15.4%
0 323
13.7%
2 197
8.3%
1 144
 
6.1%
4 114
 
4.8%
7 102
 
4.3%
6 99
 
4.2%
8 93
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2361
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 457
19.4%
- 387
16.4%
3 364
15.4%
0 323
13.7%
2 197
8.3%
1 144
 
6.1%
4 114
 
4.8%
7 102
 
4.3%
6 99
 
4.2%
8 93
 
3.9%

Interactions

2024-03-13T09:09:14.142838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T09:09:16.487450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번영업구분
순번1.0000.152
영업구분0.1521.000
2024-03-13T09:09:16.549376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번영업구분
순번1.0000.091
영업구분0.0911.000

Missing values

2024-03-13T09:09:14.228685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T09:09:14.301329image/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.
2024-03-13T09:09:14.366651image/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

순번영업구분영업소명영업소소재지(도로명)영업소전화번호
01판매업퓨어리티경상남도 김해시 금관대로1365번길 10-19 (내동)<NA>
12판매업씨유 김해구산수로점경상남도 김해시 가락로176번길 2, 1층 (구산동)<NA>
23판매업지앤지래드콘 영남지사경상남도 김해시 전하로13번길 3 (풍유동)<NA>
34판매업리브레타경상남도 김해시 칠산로387번길 59, 1층 (풍유동)055-321-2747
45판매업하이케어팜(Highcare pharm)경상남도 김해시 분성로 155, 322동 1408호 (외동, 한국2차아파트)<NA>
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