Overview

Dataset statistics

Number of variables8
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory70.9 B

Variable types

Categorical1
Text4
Boolean1
Numeric2

Dataset

Description경상남도 김해시 관내 음식물수거용기 판매소에 대한 자료로 지역, 업소명, 도로명주소, 지번주소, 연락처, 40리터 용기 판매여부, 위도, 경도 데이터로 구성되어 있습니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15086014/fileData.do

Alerts

경도 is highly overall correlated with 지역High correlation
지역 is highly overall correlated with 경도High correlation
업소명 has unique valuesUnique
도로명주소 has unique valuesUnique
지번주소 has unique valuesUnique
연락처 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 03:27:39.851988
Analysis finished2023-12-12 03:27:41.253279
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Memory size348.0 B
삼안동
6 
장유동
3 
동상동
3 
내외동
3 
진영읍
2 
Other values (7)
10 

Length

Max length5
Median length3
Mean length3.0740741
Min length3

Unique

Unique4 ?
Unique (%)14.8%

Sample

1st row진영읍
2nd row진영읍
3rd row장유동
4th row장유동
5th row장유동

Common Values

ValueCountFrequency (%)
삼안동 6
22.2%
장유동 3
11.1%
동상동 3
11.1%
내외동 3
11.1%
진영읍 2
 
7.4%
진례면 2
 
7.4%
회현동 2
 
7.4%
북부동 2
 
7.4%
생림면 1
 
3.7%
상동면 1
 
3.7%
Other values (2) 2
 
7.4%

Length

2023-12-12T12:27:41.373401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
삼안동 6
22.2%
장유동 3
11.1%
동상동 3
11.1%
내외동 3
11.1%
진영읍 2
 
7.4%
진례면 2
 
7.4%
회현동 2
 
7.4%
북부동 2
 
7.4%
생림면 1
 
3.7%
상동면 1
 
3.7%
Other values (2) 2
 
7.4%

업소명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T12:27:41.688320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length5.5185185
Min length4

Characters and Unicode

Total characters149
Distinct characters81
Distinct categories5 ?
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 row탑마트진영점
2nd row대가야식자재마트
3rd row탑마트관동점
4th row행복마트
5th row덕성유통(DS마트)
ValueCountFrequency (%)
탑마트진영점 1
 
3.7%
금동철물 1
 
3.7%
천지환경산업 1
 
3.7%
탑마트삼방점 1
 
3.7%
서원탑할인마트 1
 
3.7%
두배로마트 1
 
3.7%
동일마트 1
 
3.7%
금풍마트 1
 
3.7%
탑마트삼계점 1
 
3.7%
탑마트구산점 1
 
3.7%
Other values (17) 17
63.0%
2023-12-12T12:27:42.222864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
트 19
 
12.8%
마 19
 
12.8%
탑 9
 
6.0%
점 8
 
5.4%
동 4
 
2.7%
금 3
 
2.0%
0 3
 
2.0%
산 3
 
2.0%
인 2
 
1.3%
할 2
 
1.3%
Other values (71) 77
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139
93.3%
Decimal Number 4
 
2.7%
Uppercase Letter 4
 
2.7%
Open Punctuation 1
 
0.7%
Close Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 19
 
13.7%
마 19
 
13.7%
탑 9
 
6.5%
점 8
 
5.8%
동 4
 
2.9%
금 3
 
2.2%
산 3
 
2.2%
인 2
 
1.4%
할 2
 
1.4%
천 2
 
1.4%
Other values (64) 68
48.9%
Uppercase Letter
ValueCountFrequency (%)
D 2
50.0%
S 1
25.0%
C 1
25.0%
Decimal Number
ValueCountFrequency (%)
0 3
75.0%
1 1
 
25.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 139
93.3%
Common 6
 
4.0%
Latin 4
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 19
 
13.7%
마 19
 
13.7%
탑 9
 
6.5%
점 8
 
5.8%
동 4
 
2.9%
금 3
 
2.2%
산 3
 
2.2%
인 2
 
1.4%
할 2
 
1.4%
천 2
 
1.4%
Other values (64) 68
48.9%
Common
ValueCountFrequency (%)
0 3
50.0%
( 1
 
16.7%
) 1
 
16.7%
1 1
 
16.7%
Latin
ValueCountFrequency (%)
D 2
50.0%
S 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139
93.3%
ASCII 10
 
6.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
트 19
 
13.7%
마 19
 
13.7%
탑 9
 
6.5%
점 8
 
5.8%
동 4
 
2.9%
금 3
 
2.2%
산 3
 
2.2%
인 2
 
1.4%
할 2
 
1.4%
천 2
 
1.4%
Other values (64) 68
48.9%
ASCII
ValueCountFrequency (%)
0 3
30.0%
D 2
20.0%
( 1
 
10.0%
S 1
 
10.0%
) 1
 
10.0%
1 1
 
10.0%
C 1
 
10.0%

도로명주소
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T12:27:42.507623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length17.592593
Min length14

Characters and Unicode

Total characters475
Distinct characters61
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

Unique27 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 진영읍 진영로221
2nd row경상남도 김해시 진영읍 김해대로464-35
3rd row경상남도 김해시 덕정로85
4th row경상남도 김해시 장유로334번길2
5th row경상남도 김해시 율하모산길 57
ValueCountFrequency (%)
경상남도 27
30.7%
김해시 27
30.7%
진영읍 2
 
2.3%
진례면 2
 
2.3%
분성로645 1
 
1.1%
활천로255번길16 1
 
1.1%
삼안로235번길3 1
 
1.1%
삼안로268번길4 1
 
1.1%
삼안로255번길4 1
 
1.1%
흥동로99 1
 
1.1%
Other values (24) 24
27.3%
2023-12-12T12:27:42.971219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61
 
12.8%
김 30
 
6.3%
해 30
 
6.3%
상 29
 
6.1%
경 27
 
5.7%
남 27
 
5.7%
도 27
 
5.7%
시 27
 
5.7%
로 26
 
5.5%
5 14
 
2.9%
Other values (51) 177
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 316
66.5%
Decimal Number 95
 
20.0%
Space Separator 61
 
12.8%
Dash Punctuation 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 30
9.5%
해 30
9.5%
상 29
9.2%
경 27
 
8.5%
남 27
 
8.5%
도 27
 
8.5%
시 27
 
8.5%
로 26
 
8.2%
길 11
 
3.5%
번 10
 
3.2%
Other values (39) 72
22.8%
Decimal Number
ValueCountFrequency (%)
5 14
14.7%
1 14
14.7%
3 13
13.7%
2 12
12.6%
4 11
11.6%
6 10
10.5%
0 7
7.4%
7 6
6.3%
8 6
6.3%
9 2
 
2.1%
Space Separator
ValueCountFrequency (%)
61
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 316
66.5%
Common 159
33.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 30
9.5%
해 30
9.5%
상 29
9.2%
경 27
 
8.5%
남 27
 
8.5%
도 27
 
8.5%
시 27
 
8.5%
로 26
 
8.2%
길 11
 
3.5%
번 10
 
3.2%
Other values (39) 72
22.8%
Common
ValueCountFrequency (%)
61
38.4%
5 14
 
8.8%
1 14
 
8.8%
3 13
 
8.2%
2 12
 
7.5%
4 11
 
6.9%
6 10
 
6.3%
0 7
 
4.4%
7 6
 
3.8%
8 6
 
3.8%
Other values (2) 5
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 316
66.5%
ASCII 159
33.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
61
38.4%
5 14
 
8.8%
1 14
 
8.8%
3 13
 
8.2%
2 12
 
7.5%
4 11
 
6.9%
6 10
 
6.3%
0 7
 
4.4%
7 6
 
3.8%
8 6
 
3.8%
Other values (2) 5
 
3.1%
Hangul
ValueCountFrequency (%)
김 30
9.5%
해 30
9.5%
상 29
9.2%
경 27
 
8.5%
남 27
 
8.5%
도 27
 
8.5%
시 27
 
8.5%
로 26
 
8.2%
길 11
 
3.5%
번 10
 
3.2%
Other values (39) 72
22.8%

지번주소
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T12:27:43.261160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length17.481481
Min length15

Characters and Unicode

Total characters472
Distinct characters56
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

Unique27 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 진영읍 여래리454-9
2nd row경상남도 김해시 진영읍 여래리473-2
3rd row경상남도 김해시 관동동590
4th row경상남도 김해시 신문동500-1
5th row경상남도 김해시 장유동 865
ValueCountFrequency (%)
경상남도 27
30.7%
김해시 27
30.7%
진영읍 2
 
2.3%
진례면 2
 
2.3%
안동248-10 1
 
1.1%
삼방동178-1 1
 
1.1%
삼방동688-1 1
 
1.1%
삼방동692 1
 
1.1%
삼방동665-7 1
 
1.1%
흥동55-12 1
 
1.1%
Other values (24) 24
27.3%
2023-12-12T12:27:43.741756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61
 
12.9%
상 32
 
6.8%
김 27
 
5.7%
시 27
 
5.7%
해 27
 
5.7%
경 27
 
5.7%
도 27
 
5.7%
남 27
 
5.7%
동 26
 
5.5%
- 22
 
4.7%
Other values (46) 169
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 283
60.0%
Decimal Number 106
 
22.5%
Space Separator 61
 
12.9%
Dash Punctuation 22
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 32
11.3%
김 27
9.5%
시 27
9.5%
해 27
9.5%
경 27
9.5%
도 27
9.5%
남 27
9.5%
동 26
9.2%
삼 6
 
2.1%
리 6
 
2.1%
Other values (34) 51
18.0%
Decimal Number
ValueCountFrequency (%)
1 19
17.9%
2 14
13.2%
8 11
10.4%
5 11
10.4%
6 10
9.4%
4 10
9.4%
9 9
8.5%
7 8
7.5%
3 8
7.5%
0 6
 
5.7%
Space Separator
ValueCountFrequency (%)
61
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 283
60.0%
Common 189
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 32
11.3%
김 27
9.5%
시 27
9.5%
해 27
9.5%
경 27
9.5%
도 27
9.5%
남 27
9.5%
동 26
9.2%
삼 6
 
2.1%
리 6
 
2.1%
Other values (34) 51
18.0%
Common
ValueCountFrequency (%)
61
32.3%
- 22
 
11.6%
1 19
 
10.1%
2 14
 
7.4%
8 11
 
5.8%
5 11
 
5.8%
6 10
 
5.3%
4 10
 
5.3%
9 9
 
4.8%
7 8
 
4.2%
Other values (2) 14
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 283
60.0%
ASCII 189
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
61
32.3%
- 22
 
11.6%
1 19
 
10.1%
2 14
 
7.4%
8 11
 
5.8%
5 11
 
5.8%
6 10
 
5.3%
4 10
 
5.3%
9 9
 
4.8%
7 8
 
4.2%
Other values (2) 14
 
7.4%
Hangul
ValueCountFrequency (%)
상 32
11.3%
김 27
9.5%
시 27
9.5%
해 27
9.5%
경 27
9.5%
도 27
9.5%
남 27
9.5%
동 26
9.2%
삼 6
 
2.1%
리 6
 
2.1%
Other values (34) 51
18.0%

연락처
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T12:27:44.010106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters324
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

Unique27 ?
Unique (%)100.0%

Sample

1st row055-345-0388
2nd row055-346-5580
3rd row055-337-6133
4th row055-313-4088
5th row055-323-2333
ValueCountFrequency (%)
055-345-0388 1
 
3.7%
055-332-2636 1
 
3.7%
055-328-3179 1
 
3.7%
055-324-6272 1
 
3.7%
055-335-7733 1
 
3.7%
055-325-7222 1
 
3.7%
055-321-8952 1
 
3.7%
055-313-4948 1
 
3.7%
055-333-3553 1
 
3.7%
055-325-6283 1
 
3.7%
Other values (17) 17
63.0%
2023-12-12T12:27:44.463101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 68
21.0%
3 63
19.4%
- 54
16.7%
0 41
12.7%
2 21
 
6.5%
8 15
 
4.6%
6 15
 
4.6%
9 13
 
4.0%
7 12
 
3.7%
1 12
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 270
83.3%
Dash Punctuation 54
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 68
25.2%
3 63
23.3%
0 41
15.2%
2 21
 
7.8%
8 15
 
5.6%
6 15
 
5.6%
9 13
 
4.8%
7 12
 
4.4%
1 12
 
4.4%
4 10
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 324
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 68
21.0%
3 63
19.4%
- 54
16.7%
0 41
12.7%
2 21
 
6.5%
8 15
 
4.6%
6 15
 
4.6%
9 13
 
4.0%
7 12
 
3.7%
1 12
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 324
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 68
21.0%
3 63
19.4%
- 54
16.7%
0 41
12.7%
2 21
 
6.5%
8 15
 
4.6%
6 15
 
4.6%
9 13
 
4.0%
7 12
 
3.7%
1 12
 
3.7%

40리터용기 판매여부
Boolean

Distinct2
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size159.0 B
True
19 
False
8 
ValueCountFrequency (%)
True 19
70.4%
False 8
29.6%
2023-12-12T12:27:44.629822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위도
Real number (ℝ)

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.243051
Minimum35.165047
Maximum35.308986
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T12:27:44.760571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.165047
5-th percentile35.18502
Q135.231482
median35.239538
Q335.24979
95-th percentile35.303735
Maximum35.308986
Range0.14393945
Interquartile range (IQR)0.018308085

Descriptive statistics

Standard deviation0.033406385
Coefficient of variation (CV)0.00094788573
Kurtosis1.0495631
Mean35.243051
Median Absolute Deviation (MAD)0.00930346
Skewness0.079954969
Sum951.56237
Variance0.0011159866
MonotonicityNot monotonic
2023-12-12T12:27:44.926985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
35.30269233 1
 
3.7%
35.3041821 1
 
3.7%
35.23241034 1
 
3.7%
35.23642766 1
 
3.7%
35.24413932 1
 
3.7%
35.24884107 1
 
3.7%
35.25187438 1
 
3.7%
35.25073954 1
 
3.7%
35.22207213 1
 
3.7%
35.25975456 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
35.16504681 1
3.7%
35.17994367 1
3.7%
35.19686319 1
3.7%
35.22207213 1
3.7%
35.22723507 1
3.7%
35.2287845 1
3.7%
35.2305541 1
3.7%
35.23241034 1
3.7%
35.23406861 1
3.7%
35.23571053 1
3.7%
ValueCountFrequency (%)
35.30898626 1
3.7%
35.3041821 1
3.7%
35.30269233 1
3.7%
35.29989864 1
3.7%
35.25975456 1
3.7%
35.25187438 1
3.7%
35.25073954 1
3.7%
35.24884107 1
3.7%
35.24883031 1
3.7%
35.2485405 1
3.7%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.85826
Minimum128.73691
Maximum128.93219
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T12:27:45.088211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.73691
5-th percentile128.74339
Q1128.84106
median128.87706
Q3128.89334
95-th percentile128.91462
Maximum128.93219
Range0.1952774
Interquartile range (IQR)0.05228125

Descriptive statistics

Standard deviation0.055838949
Coefficient of variation (CV)0.0004333362
Kurtosis0.16338123
Mean128.85826
Median Absolute Deviation (MAD)0.0197828
Skewness-1.0772371
Sum3479.173
Variance0.0031179882
MonotonicityNot monotonic
2023-12-12T12:27:45.287950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
128.736909 1
 
3.7%
128.7409251 1
 
3.7%
128.896845 1
 
3.7%
128.9164564 1
 
3.7%
128.9074675 1
 
3.7%
128.910333 1
 
3.7%
128.9097186 1
 
3.7%
128.9095961 1
 
3.7%
128.859515 1
 
3.7%
128.8665292 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
128.736909 1
3.7%
128.7409251 1
3.7%
128.7491559 1
3.7%
128.7674562 1
3.7%
128.7944697 1
3.7%
128.8161142 1
3.7%
128.8246206 1
3.7%
128.8574911 1
3.7%
128.8582753 1
3.7%
128.859515 1
3.7%
ValueCountFrequency (%)
128.9321864 1
3.7%
128.9164564 1
3.7%
128.910333 1
3.7%
128.9097186 1
3.7%
128.9095961 1
3.7%
128.9074675 1
3.7%
128.896845 1
3.7%
128.8898292 1
3.7%
128.8870205 1
3.7%
128.8832362 1
3.7%

Interactions

2023-12-12T12:27:40.613028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:27:40.305593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:27:40.773267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:27:40.473973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:27:45.457394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역업소명도로명주소지번주소연락처40리터용기 판매여부위도경도
지역1.0001.0001.0001.0001.0000.0370.7480.880
업소명1.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
지번주소1.0001.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.0001.000
40리터용기 판매여부0.0371.0001.0001.0001.0001.0000.0000.275
위도0.7481.0001.0001.0001.0000.0001.0000.831
경도0.8801.0001.0001.0001.0000.2750.8311.000
2023-12-12T12:27:45.616925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역40리터용기 판매여부
지역1.0000.000
40리터용기 판매여부0.0001.000
2023-12-12T12:27:45.747274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도지역40리터용기 판매여부
위도1.0000.1130.3610.000
경도0.1131.0000.5640.210
지역0.3610.5641.0000.000
40리터용기 판매여부0.0000.2100.0001.000

Missing values

2023-12-12T12:27:40.989342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:27:41.179311image/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

지역업소명도로명주소지번주소연락처40리터용기 판매여부위도경도
0진영읍탑마트진영점경상남도 김해시 진영읍 진영로221경상남도 김해시 진영읍 여래리454-9055-345-0388Y35.302692128.736909
1진영읍대가야식자재마트경상남도 김해시 진영읍 김해대로464-35경상남도 김해시 진영읍 여래리473-2055-346-5580Y35.304182128.740925
2장유동탑마트관동점경상남도 김해시 덕정로85경상남도 김해시 관동동590055-337-6133N35.179944128.79447
3장유동행복마트경상남도 김해시 장유로334번길2경상남도 김해시 신문동500-1055-313-4088Y35.196863128.816114
4장유동덕성유통(DS마트)경상남도 김해시 율하모산길 57경상남도 김해시 장유동 865055-323-2333Y35.165047128.824621
5진례면정진농산경상남도 김해시 진례면 송현로180경상남도 김해시 진례면 송현리732-2055-345-6895Y35.245822128.767456
6진례면1000냥부터경상남도 김해시 진례면 송현로8경상남도 김해시 진례면 송정리240-4055-346-7961Y35.24883128.749156
7생림면탑훼미리마트경상남도 김해시 생림면 나전로174경상남도 김해시 생림면 나전리596-6055-323-3311Y35.299899128.877062
8상동면천사할인마트경상남도 김해시 상동면 상동로575경상남도 김해시 상동면 대감리651-3055-339-3008Y35.308986128.932186
9동상동신광그릇경상남도 김해시 구지로180번길31-6경상남도 김해시 동상동881055-336-2398Y35.235711128.883236
지역업소명도로명주소지번주소연락처40리터용기 판매여부위도경도
17내외동뉴홀마트경상남도 김해시 평전로106경상남도 김해시 내동187-1055-335-3100N35.239538128.857491
18북부동탑마트구산점경상남도 김해시 구산로50경상남도 김해시 구산동294-1055-325-6283N35.24854128.874134
19북부동탑마트삼계점경상남도 김해시 삼계중앙로12경상남도 김해시 삼계동1492-3055-333-3553N35.259755128.866529
20칠산서부동금풍마트경상남도 김해시 흥동로99경상남도 김해시 흥동55-12055-313-4948Y35.222072128.859515
21삼안동동일마트경상남도 김해시 삼안로255번길4경상남도 김해시 삼방동665-7055-321-8952Y35.25074128.909596
22삼안동두배로마트경상남도 김해시 삼안로268번길4경상남도 김해시 삼방동692055-325-7222Y35.251874128.909719
23삼안동서원탑할인마트경상남도 김해시 삼안로235번길3경상남도 김해시 삼방동688-1055-335-7733N35.248841128.910333
24삼안동탑마트삼방점경상남도 김해시 활천로255번길16경상남도 김해시 삼방동178-1055-324-6272Y35.244139128.907467
25삼안동천지환경산업경상남도 김해시 분성로645경상남도 김해시 안동248-10055-328-3179Y35.236428128.916456
26삼안동한양쇼핑경상남도 김해시 활천로36번길36경상남도 김해시 삼정동594-1055-327-0880Y35.23241128.896845