Overview

Dataset statistics

Number of variables10
Number of observations27
Missing cells1
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory85.7 B

Variable types

Numeric1
Categorical5
Text4

Dataset

Description부산광역시 연제구 음식물류폐기물 전용용기 행정구역별 판매소 현황(주소, 전화번호, 판매 전용용기 용량, 납부필증판매여부)입니다.
Author부산광역시 연제구
URLhttps://www.data.go.kr/data/15051592/fileData.do

Alerts

5리터(L) has constant value ""Constant
비고 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
20리터(L) is highly overall correlated with 연번 and 3 other fieldsHigh correlation
소재동 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
3리터(L) is highly overall correlated with 연번 and 3 other fieldsHigh correlation
연번 is highly overall correlated with 소재동 and 3 other fieldsHigh correlation
전화번호 has 1 (3.7%) missing valuesMissing
연번 has unique valuesUnique
상호 has unique valuesUnique
소재지(신주소) has unique valuesUnique
소재지(구주소) has unique valuesUnique

Reproduction

Analysis started2024-03-14 18:46:02.033535
Analysis finished2024-03-14 18:46:03.435055
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T03:46:03.831714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.3
Q17.5
median14
Q320.5
95-th percentile25.7
Maximum27
Range26
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.9372539
Coefficient of variation (CV)0.56694671
Kurtosis-1.2
Mean14
Median Absolute Deviation (MAD)7
Skewness0
Sum378
Variance63
MonotonicityStrictly increasing
2024-03-15T03:46:04.198956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 1
 
3.7%
2 1
 
3.7%
27 1
 
3.7%
26 1
 
3.7%
25 1
 
3.7%
24 1
 
3.7%
23 1
 
3.7%
22 1
 
3.7%
21 1
 
3.7%
20 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1 1
3.7%
2 1
3.7%
3 1
3.7%
4 1
3.7%
5 1
3.7%
6 1
3.7%
7 1
3.7%
8 1
3.7%
9 1
3.7%
10 1
3.7%
ValueCountFrequency (%)
27 1
3.7%
26 1
3.7%
25 1
3.7%
24 1
3.7%
23 1
3.7%
22 1
3.7%
21 1
3.7%
20 1
3.7%
19 1
3.7%
18 1
3.7%

소재동
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)40.7%
Missing0
Missing (%)0.0%
Memory size344.0 B
연산1동
4 
연산6동
4 
연산9동
4 
연산4동
3 
거제3동
2 
Other values (6)
10 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique2 ?
Unique (%)7.4%

Sample

1st row거제1동
2nd row거제3동
3rd row거제3동
4th row거제4동
5th row거제4동

Common Values

ValueCountFrequency (%)
연산1동 4
14.8%
연산6동 4
14.8%
연산9동 4
14.8%
연산4동 3
11.1%
거제3동 2
7.4%
거제4동 2
7.4%
연산2동 2
7.4%
연산5동 2
7.4%
연산8동 2
7.4%
거제1동 1
 
3.7%

Length

2024-03-15T03:46:04.597559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연산1동 4
14.8%
연산6동 4
14.8%
연산9동 4
14.8%
연산4동 3
11.1%
거제3동 2
7.4%
거제4동 2
7.4%
연산2동 2
7.4%
연산5동 2
7.4%
연산8동 2
7.4%
거제1동 1
 
3.7%

상호
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size344.0 B
2024-03-15T03:46:05.330935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length6.1111111
Min length3

Characters and Unicode

Total characters165
Distinct characters85
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row농축산마트
2nd row거제3동새마을금고
3rd row대양그릇
4th row경동세일마트
5th row패밀리1000
ValueCountFrequency (%)
주식회사 2
 
6.2%
농축산마트 1
 
3.1%
탑후레쉬마트 1
 
3.1%
빅세일마트 1
 
3.1%
store 1
 
3.1%
한양스토아((주)h.y 1
 
3.1%
연산한양점 1
 
3.1%
이마트24 1
 
3.1%
홈마트 1
 
3.1%
연동dc마트 1
 
3.1%
Other values (21) 21
65.6%
2024-03-15T03:46:06.757993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 13
 
7.9%
트 12
 
7.3%
양 6
 
3.6%
물 5
 
3.0%
동 5
 
3.0%
연 5
 
3.0%
5
 
3.0%
한 4
 
2.4%
산 4
 
2.4%
회 4
 
2.4%
Other values (75) 102
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139
84.2%
Uppercase Letter 9
 
5.5%
Decimal Number 7
 
4.2%
Space Separator 5
 
3.0%
Open Punctuation 2
 
1.2%
Close Punctuation 2
 
1.2%
Other Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 13
 
9.4%
트 12
 
8.6%
양 6
 
4.3%
물 5
 
3.6%
동 5
 
3.6%
연 5
 
3.6%
한 4
 
2.9%
산 4
 
2.9%
회 4
 
2.9%
철 4
 
2.9%
Other values (57) 77
55.4%
Uppercase Letter
ValueCountFrequency (%)
E 1
11.1%
R 1
11.1%
D 1
11.1%
C 1
11.1%
H 1
11.1%
Y 1
11.1%
S 1
11.1%
T 1
11.1%
O 1
11.1%
Decimal Number
ValueCountFrequency (%)
0 3
42.9%
2 1
 
14.3%
4 1
 
14.3%
3 1
 
14.3%
1 1
 
14.3%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 139
84.2%
Common 17
 
10.3%
Latin 9
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 13
 
9.4%
트 12
 
8.6%
양 6
 
4.3%
물 5
 
3.6%
동 5
 
3.6%
연 5
 
3.6%
한 4
 
2.9%
산 4
 
2.9%
회 4
 
2.9%
철 4
 
2.9%
Other values (57) 77
55.4%
Common
ValueCountFrequency (%)
5
29.4%
0 3
17.6%
( 2
 
11.8%
) 2
 
11.8%
2 1
 
5.9%
4 1
 
5.9%
3 1
 
5.9%
. 1
 
5.9%
1 1
 
5.9%
Latin
ValueCountFrequency (%)
E 1
11.1%
R 1
11.1%
D 1
11.1%
C 1
11.1%
H 1
11.1%
Y 1
11.1%
S 1
11.1%
T 1
11.1%
O 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139
84.2%
ASCII 26
 
15.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 13
 
9.4%
트 12
 
8.6%
양 6
 
4.3%
물 5
 
3.6%
동 5
 
3.6%
연 5
 
3.6%
한 4
 
2.9%
산 4
 
2.9%
회 4
 
2.9%
철 4
 
2.9%
Other values (57) 77
55.4%
ASCII
ValueCountFrequency (%)
5
19.2%
0 3
 
11.5%
( 2
 
7.7%
) 2
 
7.7%
E 1
 
3.8%
R 1
 
3.8%
D 1
 
3.8%
C 1
 
3.8%
2 1
 
3.8%
4 1
 
3.8%
Other values (8) 8
30.8%

전화번호
Text

MISSING 

Distinct26
Distinct (%)100.0%
Missing1
Missing (%)3.7%
Memory size344.0 B
2024-03-15T03:46:07.507869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters312
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

Unique26 ?
Unique (%)100.0%

Sample

1st row051-501-2884
2nd row051-863-0770
3rd row051-853-3423
4th row051-506-8001
5th row051-503-1728
ValueCountFrequency (%)
051-501-2884 1
 
3.8%
051-863-0770 1
 
3.8%
051-759-2334 1
 
3.8%
051-757-8876 1
 
3.8%
051-759-0806 1
 
3.8%
051-851-8249 1
 
3.8%
051-868-1281 1
 
3.8%
051-866-3813 1
 
3.8%
051-864-8971 1
 
3.8%
051-863-9448 1
 
3.8%
Other values (16) 16
61.5%
2024-03-15T03:46:08.765949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 52
16.7%
0 45
14.4%
5 43
13.8%
8 41
13.1%
1 40
12.8%
6 20
 
6.4%
2 18
 
5.8%
3 18
 
5.8%
7 17
 
5.4%
4 12
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 260
83.3%
Dash Punctuation 52
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 45
17.3%
5 43
16.5%
8 41
15.8%
1 40
15.4%
6 20
7.7%
2 18
 
6.9%
3 18
 
6.9%
7 17
 
6.5%
4 12
 
4.6%
9 6
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 52
16.7%
0 45
14.4%
5 43
13.8%
8 41
13.1%
1 40
12.8%
6 20
 
6.4%
2 18
 
5.8%
3 18
 
5.8%
7 17
 
5.4%
4 12
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 52
16.7%
0 45
14.4%
5 43
13.8%
8 41
13.1%
1 40
12.8%
6 20
 
6.4%
2 18
 
5.8%
3 18
 
5.8%
7 17
 
5.4%
4 12
 
3.8%

소재지(신주소)
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size344.0 B
2024-03-15T03:46:10.005974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length18.62963
Min length7

Characters and Unicode

Total characters503
Distinct characters123
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row법원북로 34(거제1차현대홈타운상가 지하)
2nd row거제시장로 37
3rd row거제시장로14번길 64 거제리시장 신풍상가
4th row해맞이로61번길 22 주민센터 뒤 우진빌라 옆
5th row 해맞이로 101 창녕고물상 근처
ValueCountFrequency (%)
내 5
 
4.5%
근처 3
 
2.7%
맞은편 3
 
2.7%
9 3
 
2.7%
주민센터 3
 
2.7%
29 2
 
1.8%
도로변 2
 
1.8%
연일시장 2
 
1.8%
고분로 2
 
1.8%
배산로 2
 
1.8%
Other values (78) 83
75.5%
2024-03-15T03:46:11.548248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
88
 
17.5%
로 30
 
6.0%
1 17
 
3.4%
연 15
 
3.0%
3 14
 
2.8%
길 13
 
2.6%
2 12
 
2.4%
번 12
 
2.4%
장 10
 
2.0%
시 10
 
2.0%
Other values (113) 282
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 324
64.4%
Space Separator 88
 
17.5%
Decimal Number 81
 
16.1%
Uppercase Letter 4
 
0.8%
Other Punctuation 2
 
0.4%
Dash Punctuation 2
 
0.4%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 30
 
9.3%
연 15
 
4.6%
길 13
 
4.0%
번 12
 
3.7%
장 10
 
3.1%
시 10
 
3.1%
고 9
 
2.8%
제 8
 
2.5%
동 7
 
2.2%
산 7
 
2.2%
Other values (95) 203
62.7%
Decimal Number
ValueCountFrequency (%)
1 17
21.0%
3 14
17.3%
2 12
14.8%
6 7
8.6%
4 7
8.6%
9 6
 
7.4%
0 6
 
7.4%
7 5
 
6.2%
5 4
 
4.9%
8 3
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
G 2
50.0%
L 1
25.0%
S 1
25.0%
Space Separator
ValueCountFrequency (%)
88
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 324
64.4%
Common 175
34.8%
Latin 4
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 30
 
9.3%
연 15
 
4.6%
길 13
 
4.0%
번 12
 
3.7%
장 10
 
3.1%
시 10
 
3.1%
고 9
 
2.8%
제 8
 
2.5%
동 7
 
2.2%
산 7
 
2.2%
Other values (95) 203
62.7%
Common
ValueCountFrequency (%)
88
50.3%
1 17
 
9.7%
3 14
 
8.0%
2 12
 
6.9%
6 7
 
4.0%
4 7
 
4.0%
9 6
 
3.4%
0 6
 
3.4%
7 5
 
2.9%
5 4
 
2.3%
Other values (5) 9
 
5.1%
Latin
ValueCountFrequency (%)
G 2
50.0%
L 1
25.0%
S 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 324
64.4%
ASCII 179
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
88
49.2%
1 17
 
9.5%
3 14
 
7.8%
2 12
 
6.7%
6 7
 
3.9%
4 7
 
3.9%
9 6
 
3.4%
0 6
 
3.4%
7 5
 
2.8%
5 4
 
2.2%
Other values (8) 13
 
7.3%
Hangul
ValueCountFrequency (%)
로 30
 
9.3%
연 15
 
4.6%
길 13
 
4.0%
번 12
 
3.7%
장 10
 
3.1%
시 10
 
3.1%
고 9
 
2.8%
제 8
 
2.5%
동 7
 
2.2%
산 7
 
2.2%
Other values (95) 203
62.7%

소재지(구주소)
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size344.0 B
2024-03-15T03:46:12.352812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length11.740741
Min length6

Characters and Unicode

Total characters317
Distinct characters46
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row거제동 1481
2nd row거제동 592-3
3rd row거제3동 458-1 (신풍상가A-6)
4th row거제4동 676-82
5th row거제4동 815-89
ValueCountFrequency (%)
연산동 5
 
8.6%
연산6동 3
 
5.2%
연산4동 3
 
5.2%
연산9동 2
 
3.4%
연산8동 2
 
3.4%
연제구 2
 
3.4%
거제동 2
 
3.4%
거제4동 2
 
3.4%
주민센터옆 1
 
1.7%
앞 1
 
1.7%
Other values (35) 35
60.3%
2024-03-15T03:46:13.849355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
11.0%
동 28
 
8.8%
1 27
 
8.5%
연 25
 
7.9%
- 24
 
7.6%
산 21
 
6.6%
4 19
 
6.0%
3 17
 
5.4%
6 14
 
4.4%
2 13
 
4.1%
Other values (36) 94
29.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 130
41.0%
Other Letter 118
37.2%
Space Separator 35
 
11.0%
Dash Punctuation 24
 
7.6%
Open Punctuation 3
 
0.9%
Close Punctuation 3
 
0.9%
Uppercase Letter 3
 
0.9%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 28
23.7%
연 25
21.2%
산 21
17.8%
제 7
 
5.9%
거 5
 
4.2%
구 3
 
2.5%
트 2
 
1.7%
파 2
 
1.7%
아 2
 
1.7%
장 2
 
1.7%
Other values (18) 21
17.8%
Decimal Number
ValueCountFrequency (%)
1 27
20.8%
4 19
14.6%
3 17
13.1%
6 14
10.8%
2 13
10.0%
8 12
9.2%
5 8
 
6.2%
9 7
 
5.4%
7 7
 
5.4%
0 6
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
G 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 196
61.8%
Hangul 118
37.2%
Latin 3
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 28
23.7%
연 25
21.2%
산 21
17.8%
제 7
 
5.9%
거 5
 
4.2%
구 3
 
2.5%
트 2
 
1.7%
파 2
 
1.7%
아 2
 
1.7%
장 2
 
1.7%
Other values (18) 21
17.8%
Common
ValueCountFrequency (%)
35
17.9%
1 27
13.8%
- 24
12.2%
4 19
9.7%
3 17
8.7%
6 14
 
7.1%
2 13
 
6.6%
8 12
 
6.1%
5 8
 
4.1%
9 7
 
3.6%
Other values (5) 20
10.2%
Latin
ValueCountFrequency (%)
L 1
33.3%
G 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 199
62.8%
Hangul 118
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
17.6%
1 27
13.6%
- 24
12.1%
4 19
9.5%
3 17
8.5%
6 14
 
7.0%
2 13
 
6.5%
8 12
 
6.0%
5 8
 
4.0%
9 7
 
3.5%
Other values (8) 23
11.6%
Hangul
ValueCountFrequency (%)
동 28
23.7%
연 25
21.2%
산 21
17.8%
제 7
 
5.9%
거 5
 
4.2%
구 3
 
2.5%
트 2
 
1.7%
파 2
 
1.7%
아 2
 
1.7%
장 2
 
1.7%
Other values (18) 21
17.8%

3리터(L)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size344.0 B
o
22 
<NA>
5 

Length

Max length4
Median length1
Mean length1.5555556
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
o 22
81.5%
<NA> 5
 
18.5%

Length

2024-03-15T03:46:14.296753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:46:14.645715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 22
81.5%
na 5
 
18.5%

5리터(L)
Categorical

CONSTANT 

Distinct1
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size344.0 B
o
27 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
o 27
100.0%

Length

2024-03-15T03:46:15.066071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:46:15.383239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 27
100.0%

20리터(L)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size344.0 B
o
18 
<NA>
9 

Length

Max length4
Median length1
Mean length2
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowo
2nd rowo
3rd rowo
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
o 18
66.7%
<NA> 9
33.3%

Length

2024-03-15T03:46:15.723945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:46:16.022662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 18
66.7%
na 9
33.3%

비고
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size344.0 B
<NA>
20 
칩 판매 X
7 

Length

Max length6
Median length4
Mean length4.5185185
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row칩 판매 X
3rd row칩 판매 X
4th row<NA>
5th row칩 판매 X

Common Values

ValueCountFrequency (%)
<NA> 20
74.1%
칩 판매 X 7
 
25.9%

Length

2024-03-15T03:46:16.406427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:46:16.830615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
48.8%
칩 7
 
17.1%
판매 7
 
17.1%
x 7
 
17.1%

Interactions

2024-03-15T03:46:02.584050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T03:46:17.071785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소재동상호전화번호소재지(신주소)소재지(구주소)
연번1.0000.8911.0001.0001.0001.000
소재동0.8911.0001.0001.0001.0001.000
상호1.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.000
소재지(신주소)1.0001.0001.0001.0001.0001.000
소재지(구주소)1.0001.0001.0001.0001.0001.000
2024-03-15T03:46:17.566415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비고20리터(L)소재동3리터(L)
비고1.0001.0001.0001.000
20리터(L)1.0001.0001.0001.000
소재동1.0001.0001.0001.000
3리터(L)1.0001.0001.0001.000
2024-03-15T03:46:17.993873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소재동3리터(L)20리터(L)비고
연번1.0000.6161.0001.0001.000
소재동0.6161.0001.0001.0001.000
3리터(L)1.0001.0001.0001.0001.000
20리터(L)1.0001.0001.0001.0001.000
비고1.0001.0001.0001.0001.000

Missing values

2024-03-15T03:46:02.924042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T03:46:03.251059image/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

연번소재동상호전화번호소재지(신주소)소재지(구주소)3리터(L)5리터(L)20리터(L)비고
01거제1동농축산마트051-501-2884법원북로 34(거제1차현대홈타운상가 지하)거제동 1481ooo<NA>
12거제3동거제3동새마을금고051-863-0770거제시장로 37거제동 592-3ooo칩 판매 X
23거제3동대양그릇051-853-3423거제시장로14번길 64 거제리시장 신풍상가거제3동 458-1 (신풍상가A-6)ooo칩 판매 X
34거제4동경동세일마트051-506-8001해맞이로61번길 22 주민센터 뒤 우진빌라 옆거제4동 676-82oo<NA><NA>
45거제4동패밀리1000051-503-1728해맞이로 101 창녕고물상 근처거제4동 815-89oo<NA>칩 판매 X
56연산1동연동기물051-868-3224연동로8번길 11 연동시장 내연동시장안ooo칩 판매 X
67연산1동다온유통051-851-9877과정로 314연산4동 309-9ooo<NA>
78연산1동아름슈퍼051-852-2367연동로 10-1 연동시장 내연산동 317-51oo<NA><NA>
89연산1동코사마트051-866-8470과정로344번길 50 경동아파트 내연제구 연산1동 304-1ooo<NA>
910연산2동평구상회051-868-7343월드컵대로3번길 24 연산시장 내연산2동 787-3ooo칩 판매 X
연번소재동상호전화번호소재지(신주소)소재지(구주소)3리터(L)5리터(L)20리터(L)비고
1718연산6동정선철물051-863-9448배산로 5 연산6동새마을금고 맞은편연산6동 2132-31ooo<NA>
1819연산6동함양철물051-864-8971월드컵대로32번길 3 연제중앙새마을금고 맞은편연산동 685-1ooo<NA>
1920연산6동연산철물051-866-3813배산로 9 연미상가아파트 골목시장 내연산6동 2131-8<NA>o<NA>칩 판매 X
2021연산6동신흥철물<NA>배산로23번길 3, 골목시장내연산6동 2124-16<NA>o<NA>칩 판매 X
2122연산8동연동DC마트051-868-1281연동로 9 고분터널 입구 약국 아래연산8동 341-1 연동시장 입구ooo<NA>
2223연산8동홈마트051-851-8249신금로 6 연산제일새마을금고 뒤편연산8동 344-1oo<NA><NA>
2324연산9동이마트24 연산한양점051-759-0806과정로208번길 9 주민센터 근처연산9동 주민센터옆ooo<NA>
2425연산9동한양스토아((주)H.Y STORE)051-757-8876토곡로 29 LG아파트 연제경찰서 인근연산동 40-3 (LG아파트 앞)ooo<NA>
2526연산9동주식회사 빅세일마트051-759-2334연안로 19 과정로 GS칼텍스 맞은편연제구 연산9동 420-8ooo<NA>
2627연산9동주식회사 한양스토아현대051-853-6100연제구 고분로236번길 13 현대아파트 상가(연산동,현대아파트1층상가)ooo<NA>