Overview

Dataset statistics

Number of variables7
Number of observations197
Missing cells11
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.5 KiB
Average record size in memory59.6 B

Variable types

Numeric3
Text4

Dataset

Description전북특별자치도 전주시의 나들가게를 제공하며 매장명, 도로명주소, 지번주소, 위도, 경도, 연락처 등을 제공합니다.항목 : 매장명, 도로명주소, 지번주소, 위도, 경도, 연락처제공부서 : 소상공인시장진흥공단
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15020605/fileData.do

Alerts

연락처 has 10 (5.1%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 18:25:36.269624
Analysis finished2024-03-14 18:25:41.307804
Duration5.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct197
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99
Minimum1
Maximum197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-03-15T03:25:41.539427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.8
Q150
median99
Q3148
95-th percentile187.2
Maximum197
Range196
Interquartile range (IQR)98

Descriptive statistics

Standard deviation57.013156
Coefficient of variation (CV)0.57589047
Kurtosis-1.2
Mean99
Median Absolute Deviation (MAD)49
Skewness0
Sum19503
Variance3250.5
MonotonicityStrictly increasing
2024-03-15T03:25:42.008309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
125 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
Other values (187) 187
94.9%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
197 1
0.5%
196 1
0.5%
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%

매장명
Text

Distinct188
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-03-15T03:25:43.131684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length5.0101523
Min length3

Characters and Unicode

Total characters987
Distinct characters218
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179 ?
Unique (%)90.9%

Sample

1st rowe편한마트
2nd rowk마트
3rd row가나다마트
4th row거성복지매장
5th row거시기마트
ValueCountFrequency (%)
코사마트 3
 
1.5%
와이마트 2
 
1.0%
마트유 2
 
1.0%
프랜드마트 2
 
1.0%
한별마트 2
 
1.0%
두산마트 2
 
1.0%
애플마트 2
 
1.0%
예다음마트 2
 
1.0%
정마트 2
 
1.0%
그린마트 2
 
1.0%
Other values (182) 184
89.8%
2024-03-15T03:25:44.618983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 128
 
13.0%
트 126
 
12.8%
퍼 44
 
4.5%
슈 39
 
4.0%
점 24
 
2.4%
성 15
 
1.5%
이 14
 
1.4%
우 13
 
1.3%
사 12
 
1.2%
의 11
 
1.1%
Other values (208) 561
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 964
97.7%
Decimal Number 9
 
0.9%
Space Separator 8
 
0.8%
Lowercase Letter 4
 
0.4%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 128
 
13.3%
트 126
 
13.1%
퍼 44
 
4.6%
슈 39
 
4.0%
점 24
 
2.5%
성 15
 
1.6%
이 14
 
1.5%
우 13
 
1.3%
사 12
 
1.2%
의 11
 
1.1%
Other values (198) 538
55.8%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
k 1
25.0%
i 1
25.0%
v 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 5
55.6%
5 3
33.3%
4 1
 
11.1%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 964
97.7%
Common 19
 
1.9%
Latin 4
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 128
 
13.3%
트 126
 
13.1%
퍼 44
 
4.6%
슈 39
 
4.0%
점 24
 
2.5%
성 15
 
1.6%
이 14
 
1.5%
우 13
 
1.3%
사 12
 
1.2%
의 11
 
1.1%
Other values (198) 538
55.8%
Common
ValueCountFrequency (%)
8
42.1%
2 5
26.3%
5 3
 
15.8%
) 1
 
5.3%
( 1
 
5.3%
4 1
 
5.3%
Latin
ValueCountFrequency (%)
e 1
25.0%
k 1
25.0%
i 1
25.0%
v 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 964
97.7%
ASCII 23
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 128
 
13.3%
트 126
 
13.1%
퍼 44
 
4.6%
슈 39
 
4.0%
점 24
 
2.5%
성 15
 
1.6%
이 14
 
1.5%
우 13
 
1.3%
사 12
 
1.2%
의 11
 
1.1%
Other values (198) 538
55.8%
ASCII
ValueCountFrequency (%)
8
34.8%
2 5
21.7%
5 3
 
13.0%
e 1
 
4.3%
) 1
 
4.3%
( 1
 
4.3%
k 1
 
4.3%
i 1
 
4.3%
v 1
 
4.3%
4 1
 
4.3%

도로명주소
Text

Distinct194
Distinct (%)99.0%
Missing1
Missing (%)0.5%
Memory size1.7 KiB
2024-03-15T03:25:46.316453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length27
Mean length23.479592
Min length21

Characters and Unicode

Total characters4602
Distinct characters160
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

Unique192 ?
Unique (%)98.0%

Sample

1st row전북특별자치도 전주시 완산구 효동2길 33-138
2nd row전북특별자치도 전주시 덕진구 한배미3길 17
3rd row전북특별자치도 전주시 덕진구 송천로 1
4th row전북특별자치도 전주시 완산구 선너머로 40
5th row전북특별자치도 전주시 완산구 선너머4길 9-2
ValueCountFrequency (%)
전북특별자치도 196
20.0%
전주시 196
20.0%
완산구 103
 
10.5%
덕진구 93
 
9.5%
견훤로 7
 
0.7%
매봉로 5
 
0.5%
기린대로 5
 
0.5%
13 5
 
0.5%
모악로 5
 
0.5%
10 5
 
0.5%
Other values (258) 360
36.7%
2024-03-15T03:25:48.337901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
784
17.0%
전 402
 
8.7%
구 199
 
4.3%
주 199
 
4.3%
북 198
 
4.3%
도 197
 
4.3%
치 196
 
4.3%
자 196
 
4.3%
별 196
 
4.3%
시 196
 
4.3%
Other values (150) 1839
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3234
70.3%
Space Separator 784
 
17.0%
Decimal Number 550
 
12.0%
Dash Punctuation 34
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 402
 
12.4%
구 199
 
6.2%
주 199
 
6.2%
북 198
 
6.1%
도 197
 
6.1%
치 196
 
6.1%
자 196
 
6.1%
별 196
 
6.1%
시 196
 
6.1%
특 196
 
6.1%
Other values (138) 1059
32.7%
Decimal Number
ValueCountFrequency (%)
1 124
22.5%
2 84
15.3%
3 63
11.5%
4 58
10.5%
5 57
10.4%
6 41
 
7.5%
7 35
 
6.4%
0 33
 
6.0%
9 29
 
5.3%
8 26
 
4.7%
Space Separator
ValueCountFrequency (%)
784
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3234
70.3%
Common 1368
29.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 402
 
12.4%
구 199
 
6.2%
주 199
 
6.2%
북 198
 
6.1%
도 197
 
6.1%
치 196
 
6.1%
자 196
 
6.1%
별 196
 
6.1%
시 196
 
6.1%
특 196
 
6.1%
Other values (138) 1059
32.7%
Common
ValueCountFrequency (%)
784
57.3%
1 124
 
9.1%
2 84
 
6.1%
3 63
 
4.6%
4 58
 
4.2%
5 57
 
4.2%
6 41
 
3.0%
7 35
 
2.6%
- 34
 
2.5%
0 33
 
2.4%
Other values (2) 55
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3234
70.3%
ASCII 1368
29.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
784
57.3%
1 124
 
9.1%
2 84
 
6.1%
3 63
 
4.6%
4 58
 
4.2%
5 57
 
4.2%
6 41
 
3.0%
7 35
 
2.6%
- 34
 
2.5%
0 33
 
2.4%
Other values (2) 55
 
4.0%
Hangul
ValueCountFrequency (%)
전 402
 
12.4%
구 199
 
6.2%
주 199
 
6.2%
북 198
 
6.1%
도 197
 
6.1%
치 196
 
6.1%
자 196
 
6.1%
별 196
 
6.1%
시 196
 
6.1%
특 196
 
6.1%
Other values (138) 1059
32.7%

지번주소
Text

Distinct194
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-03-15T03:25:49.934477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length28
Mean length26.629442
Min length23

Characters and Unicode

Total characters5246
Distinct characters64
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

Unique191 ?
Unique (%)97.0%

Sample

1st row전북특별자치도 전주시 완산구 효자동1가 216-63
2nd row전북특별자치도 전주시 덕진구 인후동1가 934-2
3rd row전북특별자치도 전주시 덕진구 송천동1가 292-7
4th row전북특별자치도 전주시 완산구 중화산동2가 17
5th row전북특별자치도 전주시 완산구 중화산동1가 313-2
ValueCountFrequency (%)
전북특별자치도 197
20.0%
전주시 197
20.0%
완산구 103
 
10.5%
덕진구 94
 
9.5%
삼천동1가 19
 
1.9%
인후동1가 17
 
1.7%
금암동 15
 
1.5%
효자동1가 12
 
1.2%
효자동3가 10
 
1.0%
평화동2가 9
 
0.9%
Other values (228) 312
31.7%
2024-03-15T03:25:52.002483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
790
 
15.1%
전 394
 
7.5%
1 232
 
4.4%
자 223
 
4.3%
북 202
 
3.9%
동 200
 
3.8%
시 197
 
3.8%
구 197
 
3.8%
별 197
 
3.8%
주 197
 
3.8%
Other values (54) 2417
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3310
63.1%
Decimal Number 975
 
18.6%
Space Separator 790
 
15.1%
Dash Punctuation 171
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 394
 
11.9%
자 223
 
6.7%
북 202
 
6.1%
동 200
 
6.0%
시 197
 
6.0%
구 197
 
6.0%
별 197
 
6.0%
주 197
 
6.0%
도 197
 
6.0%
치 197
 
6.0%
Other values (42) 1109
33.5%
Decimal Number
ValueCountFrequency (%)
1 232
23.8%
2 166
17.0%
5 103
10.6%
3 95
9.7%
7 73
 
7.5%
6 73
 
7.5%
4 70
 
7.2%
8 66
 
6.8%
9 54
 
5.5%
0 43
 
4.4%
Space Separator
ValueCountFrequency (%)
790
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3310
63.1%
Common 1936
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 394
 
11.9%
자 223
 
6.7%
북 202
 
6.1%
동 200
 
6.0%
시 197
 
6.0%
구 197
 
6.0%
별 197
 
6.0%
주 197
 
6.0%
도 197
 
6.0%
치 197
 
6.0%
Other values (42) 1109
33.5%
Common
ValueCountFrequency (%)
790
40.8%
1 232
 
12.0%
- 171
 
8.8%
2 166
 
8.6%
5 103
 
5.3%
3 95
 
4.9%
7 73
 
3.8%
6 73
 
3.8%
4 70
 
3.6%
8 66
 
3.4%
Other values (2) 97
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3310
63.1%
ASCII 1936
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
790
40.8%
1 232
 
12.0%
- 171
 
8.8%
2 166
 
8.6%
5 103
 
5.3%
3 95
 
4.9%
7 73
 
3.8%
6 73
 
3.8%
4 70
 
3.6%
8 66
 
3.4%
Other values (2) 97
 
5.0%
Hangul
ValueCountFrequency (%)
전 394
 
11.9%
자 223
 
6.7%
북 202
 
6.1%
동 200
 
6.0%
시 197
 
6.0%
구 197
 
6.0%
별 197
 
6.0%
주 197
 
6.0%
도 197
 
6.0%
치 197
 
6.0%
Other values (42) 1109
33.5%

위도
Real number (ℝ)

Distinct195
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.826739
Minimum35.786636
Maximum35.873776
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-03-15T03:25:52.270056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.786636
5-th percentile35.793115
Q135.809481
median35.828672
Q335.840442
95-th percentile35.866369
Maximum35.873776
Range0.0871405
Interquartile range (IQR)0.03096181

Descriptive statistics

Standard deviation0.021434047
Coefficient of variation (CV)0.00059826956
Kurtosis-0.64023783
Mean35.826739
Median Absolute Deviation (MAD)0.01497395
Skewness0.086187237
Sum7057.8675
Variance0.00045941838
MonotonicityNot monotonic
2024-03-15T03:25:52.621117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.79764746 2
 
1.0%
35.83081041 2
 
1.0%
35.79851397 1
 
0.5%
35.8659173 1
 
0.5%
35.79952595 1
 
0.5%
35.84010792 1
 
0.5%
35.85404826 1
 
0.5%
35.84046556 1
 
0.5%
35.83720632 1
 
0.5%
35.80471641 1
 
0.5%
Other values (185) 185
93.9%
ValueCountFrequency (%)
35.78663581 1
0.5%
35.78769188 1
0.5%
35.78798652 1
0.5%
35.78947492 1
0.5%
35.78963847 1
0.5%
35.79010371 1
0.5%
35.79082877 1
0.5%
35.79110725 1
0.5%
35.79301562 1
0.5%
35.79302701 1
0.5%
ValueCountFrequency (%)
35.87377631 1
0.5%
35.87332076 1
0.5%
35.87255111 1
0.5%
35.87107405 1
0.5%
35.87042032 1
0.5%
35.86931383 1
0.5%
35.86834549 1
0.5%
35.86832995 1
0.5%
35.8682208 1
0.5%
35.86817476 1
0.5%

경도
Real number (ℝ)

Distinct195
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.13337
Minimum127.06874
Maximum127.17569
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-03-15T03:25:53.035954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.06874
5-th percentile127.0972
Q1127.12031
median127.13213
Q3127.15016
95-th percentile127.16527
Maximum127.17569
Range0.1069522
Interquartile range (IQR)0.0298567

Descriptive statistics

Standard deviation0.021566493
Coefficient of variation (CV)0.00016963677
Kurtosis0.31973955
Mean127.13337
Median Absolute Deviation (MAD)0.0142503
Skewness-0.53440313
Sum25045.273
Variance0.00046511364
MonotonicityNot monotonic
2024-03-15T03:25:53.336952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1298133 2
 
1.0%
127.1586753 2
 
1.0%
127.1502164 1
 
0.5%
127.1218326 1
 
0.5%
127.1196595 1
 
0.5%
127.1232093 1
 
0.5%
127.1556822 1
 
0.5%
127.1558634 1
 
0.5%
127.1286215 1
 
0.5%
127.1309079 1
 
0.5%
Other values (185) 185
93.9%
ValueCountFrequency (%)
127.0687368 1
0.5%
127.0710217 1
0.5%
127.0712743 1
0.5%
127.0728361 1
0.5%
127.0758276 1
0.5%
127.0761168 1
0.5%
127.0944864 1
0.5%
127.0954851 1
0.5%
127.0966134 1
0.5%
127.0971632 1
0.5%
ValueCountFrequency (%)
127.175689 1
0.5%
127.1712688 1
0.5%
127.1708908 1
0.5%
127.1697008 1
0.5%
127.1694174 1
0.5%
127.1683323 1
0.5%
127.1675484 1
0.5%
127.1659419 1
0.5%
127.1659111 1
0.5%
127.1653216 1
0.5%

연락처
Text

MISSING 

Distinct185
Distinct (%)98.9%
Missing10
Missing (%)5.1%
Memory size1.7 KiB
2024-03-15T03:25:54.259441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.02139
Min length12

Characters and Unicode

Total characters2248
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

Unique183 ?
Unique (%)97.9%

Sample

1st row063-229-7755
2nd row063-245-6584
3rd row063-253-0037
4th row063-225-1566
5th row063-288-9153
ValueCountFrequency (%)
063-275-3222 2
 
1.1%
070-8833-3559 2
 
1.1%
063-252-8224 1
 
0.5%
063-245-7574 1
 
0.5%
063-243-5581 1
 
0.5%
063-242-0735 1
 
0.5%
063-229-7755 1
 
0.5%
063-226-1758 1
 
0.5%
063-251-0979 1
 
0.5%
063-227-0072 1
 
0.5%
Other values (175) 175
93.6%
2024-03-15T03:25:55.728454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 374
16.6%
2 329
14.6%
3 297
13.2%
0 279
12.4%
6 251
11.2%
5 164
7.3%
4 138
 
6.1%
7 127
 
5.6%
8 115
 
5.1%
1 108
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1874
83.4%
Dash Punctuation 374
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 329
17.6%
3 297
15.8%
0 279
14.9%
6 251
13.4%
5 164
8.8%
4 138
7.4%
7 127
 
6.8%
8 115
 
6.1%
1 108
 
5.8%
9 66
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 374
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2248
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 374
16.6%
2 329
14.6%
3 297
13.2%
0 279
12.4%
6 251
11.2%
5 164
7.3%
4 138
 
6.1%
7 127
 
5.6%
8 115
 
5.1%
1 108
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2248
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 374
16.6%
2 329
14.6%
3 297
13.2%
0 279
12.4%
6 251
11.2%
5 164
7.3%
4 138
 
6.1%
7 127
 
5.6%
8 115
 
5.1%
1 108
 
4.8%

Interactions

2024-03-15T03:25:39.197216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:25:36.877552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:25:38.056077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:25:39.599396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:25:37.314497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:25:38.488929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:25:39.844293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:25:37.715249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:25:38.791332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T03:25:55.961519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.0000.000
위도0.0001.0000.574
경도0.0000.5741.000
2024-03-15T03:25:56.199154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.000-0.0240.108
위도-0.0241.0000.083
경도0.1080.0831.000

Missing values

2024-03-15T03:25:40.456071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T03:25:40.834339image/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.
2024-03-15T03:25:41.126524image/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

연번매장명도로명주소지번주소위도경도연락처
01e편한마트전북특별자치도 전주시 완산구 효동2길 33-138전북특별자치도 전주시 완산구 효자동1가 216-6335.803167127.127834063-229-7755
12k마트전북특별자치도 전주시 덕진구 한배미3길 17전북특별자치도 전주시 덕진구 인후동1가 934-235.824683127.164945063-245-6584
23가나다마트전북특별자치도 전주시 덕진구 송천로 1전북특별자치도 전주시 덕진구 송천동1가 292-735.852983127.118903063-253-0037
34거성복지매장전북특별자치도 전주시 완산구 선너머로 40전북특별자치도 전주시 완산구 중화산동2가 1735.815758127.128946063-225-1566
45거시기마트전북특별자치도 전주시 완산구 선너머4길 9-2전북특별자치도 전주시 완산구 중화산동1가 313-235.813698127.131964063-288-9153
56경기전슈퍼전북특별자치도 전주시 완산구 태조로 45전북특별자치도 전주시 완산구 교동 278-135.813953127.150023063-288-2425
67공영쇼핑전북특별자치도 전주시 덕진구 기린대로 1018-12전북특별자치도 전주시 덕진구 여의동 658-535.868175127.075828063-212-6421
78광명슈퍼전북특별자치도 전주시 덕진구 모래내3길 14-4전북특별자치도 전주시 덕진구 인후동2가 211-2335.834591127.142406063-252-3785
89광진하이퍼마트전북특별자치도 전주시 완산구 선너머로 16전북특별자치도 전주시 완산구 중화산동2가 19035.815423127.126893063-224-3501
910국민청과수퍼전북특별자치도 전주시 덕진구 매봉5길 28전북특별자치도 전주시 덕진구 금암동 1601-1435.841995127.143821063-274-9565
연번매장명도로명주소지번주소위도경도연락처
187188호남마트전북특별자치도 전주시 완산구 태평5길 58전북특별자치도 전주시 완산구 서노송동 642-435.825286127.14337063-252-3740
188189호반슈퍼전북특별자치도 전주시 덕진구 호반6길 12전북특별자치도 전주시 덕진구 덕진동2가 167-5435.850829127.117534063-252-8700
189190환영슈퍼전북특별자치도 전주시 완산구 전라감영로 27전북특별자치도 전주시 완산구 다가동1가 52-535.814952127.142345063-231-5111
190191황궁슈퍼마트전북특별자치도 전주시 완산구 장승배기로 404전북특별자치도 전주시 완산구 동서학동 290-335.806078127.15307063-285-7834
191192황금편의점전북특별자치도 전주시 덕진구 산정2길 8전북특별자치도 전주시 덕진구 산정동 871-435.837154127.169701063-245-4618
192193황방쇼핑전북특별자치도 전주시 완산구 서신천변4길 2전북특별자치도 전주시 완산구 서신동 84735.82778127.114323063-252-8224
193194황소마트전북특별자치도 전주시 덕진구 도당산로 8전북특별자치도 전주시 덕진구 우아동3가 754-1735.844051127.154647063-211-8116
194195효궁농수산물슈퍼전북특별자치도 전주시 덕진구 매봉로 17-1전북특별자치도 전주시 덕진구 금암동 1579-1735.839665127.141599<NA>
195196효문알뜰마트전북특별자치도 전주시 완산구 거마서로 48전북특별자치도 전주시 완산구 삼천동1가 63135.796827127.119513063-252-9377
196197희망슈퍼전북특별자치도 전주시 완산구 산월1길 17전북특별자치도 전주시 완산구 중화산동2가 529-735.812759127.121239<NA>