Overview

Dataset statistics

Number of variables10
Number of observations30
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory85.4 B

Variable types

Numeric1
Categorical5
Text4

Dataset

Description부산광역시연제구_음식물류폐기물전용용기판매소현황_20230214
Author부산광역시 연제구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15051592

Alerts

5리터(L) has constant value ""Constant
3리터(L) is highly overall correlated with 연번 and 3 other fieldsHigh correlation
20리터(L) is highly overall correlated with 연번 and 3 other fieldsHigh correlation
비고 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
소재동 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 (3.3%) missing valuesMissing
연번 has unique valuesUnique
상호 has unique valuesUnique
소재지(신주소) has unique valuesUnique
소재지(구주소) has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:13:04.231471
Analysis finished2023-12-10 16:13:05.159910
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-11T01:13:05.255315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2023-12-11T01:13:05.445540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

소재동
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
연산5동
5 
연산1동
4 
연산6동
4 
연산9동
4 
연산4동
3 
Other values (6)
10 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
연산5동 5
16.7%
연산1동 4
13.3%
연산6동 4
13.3%
연산9동 4
13.3%
연산4동 3
10.0%
거제3동 2
 
6.7%
거제4동 2
 
6.7%
연산2동 2
 
6.7%
연산8동 2
 
6.7%
거제1동 1
 
3.3%

Length

2023-12-11T01:13:05.647982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연산5동 5
16.7%
연산1동 4
13.3%
연산6동 4
13.3%
연산9동 4
13.3%
연산4동 3
10.0%
거제3동 2
 
6.7%
거제4동 2
 
6.7%
연산2동 2
 
6.7%
연산8동 2
 
6.7%
거제1동 1
 
3.3%

상호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-11T01:13:05.941931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length6.0333333
Min length3

Characters and Unicode

Total characters181
Distinct characters86
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

Unique30 ?
Unique (%)100.0%

Sample

1st row농축산마트
2nd row거제3동새마을금고
3rd row대양그릇
4th row경동세일마트
5th row패밀리1000
ValueCountFrequency (%)
빅세일마트 2
 
5.7%
주식회사 2
 
5.7%
탑플러스마트 2
 
5.7%
농축산마트 1
 
2.9%
store 1
 
2.9%
한양스토아((주)h.y 1
 
2.9%
연산한양점 1
 
2.9%
이마트24 1
 
2.9%
홈마트 1
 
2.9%
연동dc마트 1
 
2.9%
Other values (22) 22
62.9%
2023-12-11T01:13:06.475016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 16
 
8.8%
트 15
 
8.3%
양 6
 
3.3%
물 5
 
2.8%
5
 
2.8%
동 5
 
2.8%
연 5
 
2.8%
한 4
 
2.2%
회 4
 
2.2%
철 4
 
2.2%
Other values (76) 112
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 155
85.6%
Uppercase Letter 9
 
5.0%
Decimal Number 7
 
3.9%
Space Separator 5
 
2.8%
Close Punctuation 2
 
1.1%
Open Punctuation 2
 
1.1%
Other Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 16
 
10.3%
트 15
 
9.7%
양 6
 
3.9%
물 5
 
3.2%
동 5
 
3.2%
연 5
 
3.2%
한 4
 
2.6%
회 4
 
2.6%
철 4
 
2.6%
스 4
 
2.6%
Other values (58) 87
56.1%
Uppercase Letter
ValueCountFrequency (%)
T 1
11.1%
S 1
11.1%
D 1
11.1%
C 1
11.1%
E 1
11.1%
R 1
11.1%
H 1
11.1%
Y 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%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 155
85.6%
Common 17
 
9.4%
Latin 9
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 16
 
10.3%
트 15
 
9.7%
양 6
 
3.9%
물 5
 
3.2%
동 5
 
3.2%
연 5
 
3.2%
한 4
 
2.6%
회 4
 
2.6%
철 4
 
2.6%
스 4
 
2.6%
Other values (58) 87
56.1%
Common
ValueCountFrequency (%)
5
29.4%
0 3
17.6%
) 2
 
11.8%
( 2
 
11.8%
2 1
 
5.9%
4 1
 
5.9%
. 1
 
5.9%
3 1
 
5.9%
1 1
 
5.9%
Latin
ValueCountFrequency (%)
T 1
11.1%
S 1
11.1%
D 1
11.1%
C 1
11.1%
E 1
11.1%
R 1
11.1%
H 1
11.1%
Y 1
11.1%
O 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 155
85.6%
ASCII 26
 
14.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 16
 
10.3%
트 15
 
9.7%
양 6
 
3.9%
물 5
 
3.2%
동 5
 
3.2%
연 5
 
3.2%
한 4
 
2.6%
회 4
 
2.6%
철 4
 
2.6%
스 4
 
2.6%
Other values (58) 87
56.1%
ASCII
ValueCountFrequency (%)
5
19.2%
0 3
 
11.5%
) 2
 
7.7%
( 2
 
7.7%
T 1
 
3.8%
S 1
 
3.8%
D 1
 
3.8%
C 1
 
3.8%
2 1
 
3.8%
E 1
 
3.8%
Other values (8) 8
30.8%

전화번호
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing1
Missing (%)3.3%
Memory size372.0 B
2023-12-11T01:13:06.763948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters348
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

Unique29 ?
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
 
3.4%
051-864-5344 1
 
3.4%
051-759-2334 1
 
3.4%
051-757-8876 1
 
3.4%
051-759-0806 1
 
3.4%
051-851-8249 1
 
3.4%
051-868-1281 1
 
3.4%
051-866-3813 1
 
3.4%
051-864-8971 1
 
3.4%
051-863-9448 1
 
3.4%
Other values (19) 19
65.5%
2023-12-11T01:13:07.236792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 58
16.7%
0 50
14.4%
5 49
14.1%
8 44
12.6%
1 43
12.4%
6 23
 
6.6%
2 19
 
5.5%
3 19
 
5.5%
7 18
 
5.2%
4 16
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 290
83.3%
Dash Punctuation 58
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 50
17.2%
5 49
16.9%
8 44
15.2%
1 43
14.8%
6 23
7.9%
2 19
 
6.6%
3 19
 
6.6%
7 18
 
6.2%
4 16
 
5.5%
9 9
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 348
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 58
16.7%
0 50
14.4%
5 49
14.1%
8 44
12.6%
1 43
12.4%
6 23
 
6.6%
2 19
 
5.5%
3 19
 
5.5%
7 18
 
5.2%
4 16
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 58
16.7%
0 50
14.4%
5 49
14.1%
8 44
12.6%
1 43
12.4%
6 23
 
6.6%
2 19
 
5.5%
3 19
 
5.5%
7 18
 
5.2%
4 16
 
4.6%

소재지(신주소)
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-11T01:13:07.658928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length22.5
Mean length19.133333
Min length7

Characters and Unicode

Total characters574
Distinct characters138
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

Unique30 ?
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
 
4.0%
맞은편 4
 
3.2%
9 3
 
2.4%
근처 3
 
2.4%
주민센터 3
 
2.4%
옆 2
 
1.6%
3 2
 
1.6%
배산로 2
 
1.6%
연동로 2
 
1.6%
과정로 2
 
1.6%
Other values (89) 96
77.4%
2023-12-11T01:13:08.280222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
100
 
17.4%
로 33
 
5.7%
1 20
 
3.5%
연 16
 
2.8%
3 15
 
2.6%
길 15
 
2.6%
번 14
 
2.4%
2 12
 
2.1%
시 11
 
1.9%
장 10
 
1.7%
Other values (128) 328
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 370
64.5%
Space Separator 100
 
17.4%
Decimal Number 93
 
16.2%
Uppercase Letter 4
 
0.7%
Other Punctuation 3
 
0.5%
Dash Punctuation 2
 
0.3%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 33
 
8.9%
연 16
 
4.3%
길 15
 
4.1%
번 14
 
3.8%
시 11
 
3.0%
장 10
 
2.7%
고 9
 
2.4%
제 9
 
2.4%
대 9
 
2.4%
동 7
 
1.9%
Other values (110) 237
64.1%
Decimal Number
ValueCountFrequency (%)
1 20
21.5%
3 15
16.1%
2 12
12.9%
4 9
9.7%
5 8
 
8.6%
6 7
 
7.5%
9 6
 
6.5%
0 6
 
6.5%
8 5
 
5.4%
7 5
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
G 2
50.0%
S 1
25.0%
L 1
25.0%
Space Separator
ValueCountFrequency (%)
100
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 370
64.5%
Common 200
34.8%
Latin 4
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 33
 
8.9%
연 16
 
4.3%
길 15
 
4.1%
번 14
 
3.8%
시 11
 
3.0%
장 10
 
2.7%
고 9
 
2.4%
제 9
 
2.4%
대 9
 
2.4%
동 7
 
1.9%
Other values (110) 237
64.1%
Common
ValueCountFrequency (%)
100
50.0%
1 20
 
10.0%
3 15
 
7.5%
2 12
 
6.0%
4 9
 
4.5%
5 8
 
4.0%
6 7
 
3.5%
9 6
 
3.0%
0 6
 
3.0%
8 5
 
2.5%
Other values (5) 12
 
6.0%
Latin
ValueCountFrequency (%)
G 2
50.0%
S 1
25.0%
L 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 370
64.5%
ASCII 204
35.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
100
49.0%
1 20
 
9.8%
3 15
 
7.4%
2 12
 
5.9%
4 9
 
4.4%
5 8
 
3.9%
6 7
 
3.4%
9 6
 
2.9%
0 6
 
2.9%
8 5
 
2.5%
Other values (8) 16
 
7.8%
Hangul
ValueCountFrequency (%)
로 33
 
8.9%
연 16
 
4.3%
길 15
 
4.1%
번 14
 
3.8%
시 11
 
3.0%
장 10
 
2.7%
고 9
 
2.4%
제 9
 
2.4%
대 9
 
2.4%
동 7
 
1.9%
Other values (110) 237
64.1%

소재지(구주소)
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-11T01:13:08.650592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length12.133333
Min length6

Characters and Unicode

Total characters364
Distinct characters50
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

Unique30 ?
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 7
 
10.4%
연산4동 3
 
4.5%
연산6동 3
 
4.5%
연제구 3
 
4.5%
거제동 2
 
3.0%
연산9동 2
 
3.0%
연산8동 2
 
3.0%
연산5동 2
 
3.0%
거제4동 2
 
3.0%
815-89 1
 
1.5%
Other values (40) 40
59.7%
2023-12-11T01:13:09.323355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41
 
11.3%
동 31
 
8.5%
1 31
 
8.5%
연 30
 
8.2%
- 27
 
7.4%
산 24
 
6.6%
4 21
 
5.8%
3 20
 
5.5%
2 15
 
4.1%
6 14
 
3.8%
Other values (40) 110
30.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 147
40.4%
Other Letter 137
37.6%
Space Separator 41
 
11.3%
Dash Punctuation 27
 
7.4%
Close Punctuation 4
 
1.1%
Open Punctuation 4
 
1.1%
Uppercase Letter 3
 
0.8%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 31
22.6%
연 30
21.9%
산 24
17.5%
제 9
 
6.6%
거 5
 
3.6%
구 4
 
2.9%
파 2
 
1.5%
상 2
 
1.5%
시 2
 
1.5%
장 2
 
1.5%
Other values (22) 26
19.0%
Decimal Number
ValueCountFrequency (%)
1 31
21.1%
4 21
14.3%
3 20
13.6%
2 15
10.2%
6 14
9.5%
8 14
9.5%
5 11
 
7.5%
9 7
 
4.8%
0 7
 
4.8%
7 7
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
G 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 224
61.5%
Hangul 137
37.6%
Latin 3
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 31
22.6%
연 30
21.9%
산 24
17.5%
제 9
 
6.6%
거 5
 
3.6%
구 4
 
2.9%
파 2
 
1.5%
상 2
 
1.5%
시 2
 
1.5%
장 2
 
1.5%
Other values (22) 26
19.0%
Common
ValueCountFrequency (%)
41
18.3%
1 31
13.8%
- 27
12.1%
4 21
9.4%
3 20
8.9%
2 15
 
6.7%
6 14
 
6.2%
8 14
 
6.2%
5 11
 
4.9%
9 7
 
3.1%
Other values (5) 23
10.3%
Latin
ValueCountFrequency (%)
L 1
33.3%
G 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 227
62.4%
Hangul 137
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41
18.1%
1 31
13.7%
- 27
11.9%
4 21
9.3%
3 20
8.8%
2 15
 
6.6%
6 14
 
6.2%
8 14
 
6.2%
5 11
 
4.8%
9 7
 
3.1%
Other values (8) 26
11.5%
Hangul
ValueCountFrequency (%)
동 31
22.6%
연 30
21.9%
산 24
17.5%
제 9
 
6.6%
거 5
 
3.6%
구 4
 
2.9%
파 2
 
1.5%
상 2
 
1.5%
시 2
 
1.5%
장 2
 
1.5%
Other values (22) 26
19.0%

3리터(L)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
o
25 
<NA>
5 

Length

Max length4
Median length1
Mean length1.5
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
o 25
83.3%
<NA> 5
 
16.7%

Length

2023-12-11T01:13:09.534595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:13:09.684277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 25
83.3%
na 5
 
16.7%

5리터(L)
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
o
30 

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 30
100.0%

Length

2023-12-11T01:13:09.827390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:13:09.956813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 30
100.0%

20리터(L)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
o
19 
<NA>
11 

Length

Max length4
Median length1
Mean length2.1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
o 19
63.3%
<NA> 11
36.7%

Length

2023-12-11T01:13:10.120791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:13:10.293227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 19
63.3%
na 11
36.7%

비고
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
23 
칩 판매 X
7 

Length

Max length6
Median length4
Mean length4.4666667
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> 23
76.7%
칩 판매 X 7
 
23.3%

Length

2023-12-11T01:13:10.429183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:13:10.610923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 23
52.3%
칩 7
 
15.9%
판매 7
 
15.9%
x 7
 
15.9%

Interactions

2023-12-11T01:13:04.722048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:13:10.706852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소재동상호전화번호소재지(신주소)소재지(구주소)
연번1.0000.9431.0001.0001.0001.000
소재동0.9431.0001.0001.0001.0001.000
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
2023-12-11T01:13:10.873377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
3리터(L)20리터(L)비고소재동
3리터(L)1.0001.0001.0001.000
20리터(L)1.0001.0001.0001.000
비고1.0001.0001.0001.000
소재동1.0001.0001.0001.000
2023-12-11T01:13:11.011928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번소재동3리터(L)20리터(L)비고
연번1.0000.7611.0001.0001.000
소재동0.7611.0001.0001.0001.000
3리터(L)1.0001.0001.0001.0001.000
20리터(L)1.0001.0001.0001.0001.000
비고1.0001.0001.0001.0001.000

Missing values

2023-12-11T01:13:04.881113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:13:05.077066image/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
2021연산6동정선철물051-863-9448배산로 5 연산6동새마을금고 맞은편연산6동 2132-31ooo<NA>
2122연산6동함양철물051-864-8971월드컵대로32번길 3 연제중앙새마을금고 맞은편연산동 685-1ooo<NA>
2223연산6동연산철물051-866-3813배산로 9 연미상가아파트 골목시장 내연산6동 2131-8<NA>o<NA>칩 판매 X
2324연산6동신흥철물<NA>배산로23번길 3, 골목시장내연산6동 2124-16<NA>o<NA>칩 판매 X
2425연산8동연동DC마트051-868-1281연동로 9 고분터널 입구 약국 아래연산8동 341-1 연동시장 입구ooo<NA>
2526연산8동홈마트051-851-8249신금로 6 연산제일새마을금고 뒤편연산8동 344-1oo<NA><NA>
2627연산9동이마트24 연산한양점051-759-0806과정로208번길 9 주민센터 근처연산9동 주민센터옆ooo<NA>
2728연산9동한양스토아((주)H.Y STORE)051-757-8876토곡로 29 LG아파트 연제경찰서 인근연산동 40-3 (LG아파트 앞)ooo<NA>
2829연산9동주식회사 빅세일마트051-759-2334연안로 19 과정로 GS칼텍스 맞은편연제구 연산9동 420-8ooo<NA>
2930연산9동주식회사 한양스토아현대051-853-6100연제구 고분로236번길 13 현대아파트 상가(연산동,현대아파트1층상가)ooo<NA>