Overview

Dataset statistics

Number of variables7
Number of observations44
Missing cells14
Missing cells (%)4.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory62.0 B

Variable types

Numeric3
Text4

Dataset

Description인천광역시 미추홀구의 배달대행업소 현황 데이터로 상호명, 도로명주소, 지번주소, 전화번호 등의 정보를 제공하고 있습니다.
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15087019/fileData.do

Alerts

전화번호 has 14 (31.8%) missing valuesMissing
연번 has unique valuesUnique
상호명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:03:44.601503
Analysis finished2023-12-12 05:03:45.984066
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.5
Minimum1
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T14:03:46.056842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.15
Q111.75
median22.5
Q333.25
95-th percentile41.85
Maximum44
Range43
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation12.845233
Coefficient of variation (CV)0.57089923
Kurtosis-1.2
Mean22.5
Median Absolute Deviation (MAD)11
Skewness0
Sum990
Variance165
MonotonicityStrictly increasing
2023-12-12T14:03:46.186378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 1
 
2.3%
24 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
33 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
44 1
2.3%
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%

상호명
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-12T14:03:46.395776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11
Mean length8.3409091
Min length2

Characters and Unicode

Total characters367
Distinct characters105
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

Unique44 ?
Unique (%)100.0%

Sample

1st row냠냠박스 주안지점
2nd row냠냠박스 용현지점
3rd row바로고 주안3허브
4th row바로고
5th row생각대로 주안지원센터
ValueCountFrequency (%)
바로고 13
 
16.7%
생각대로 9
 
11.5%
숭의점 4
 
5.1%
냠냠박스 2
 
2.6%
용현지사 2
 
2.6%
부릉 2
 
2.6%
주안지사 2
 
2.6%
보스배달대행 1
 
1.3%
더킹지사 1
 
1.3%
주안점 1
 
1.3%
Other values (41) 41
52.6%
2023-12-12T14:03:46.771425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34
 
9.3%
로 22
 
6.0%
고 15
 
4.1%
바 15
 
4.1%
대 13
 
3.5%
지 13
 
3.5%
점 12
 
3.3%
사 10
 
2.7%
각 9
 
2.5%
생 9
 
2.5%
Other values (95) 215
58.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 303
82.6%
Space Separator 34
 
9.3%
Uppercase Letter 13
 
3.5%
Lowercase Letter 12
 
3.3%
Decimal Number 5
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 22
 
7.3%
고 15
 
5.0%
바 15
 
5.0%
대 13
 
4.3%
지 13
 
4.3%
점 12
 
4.0%
사 10
 
3.3%
각 9
 
3.0%
생 9
 
3.0%
브 8
 
2.6%
Other values (76) 177
58.4%
Lowercase Letter
ValueCountFrequency (%)
e 2
16.7%
l 2
16.7%
i 2
16.7%
y 1
8.3%
n 1
8.3%
g 1
8.3%
r 1
8.3%
v 1
8.3%
b 1
8.3%
Uppercase Letter
ValueCountFrequency (%)
K 3
23.1%
C 2
15.4%
D 2
15.4%
T 2
15.4%
O 2
15.4%
I 1
 
7.7%
F 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
2 3
60.0%
3 2
40.0%
Space Separator
ValueCountFrequency (%)
34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 303
82.6%
Common 39
 
10.6%
Latin 25
 
6.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 22
 
7.3%
고 15
 
5.0%
바 15
 
5.0%
대 13
 
4.3%
지 13
 
4.3%
점 12
 
4.0%
사 10
 
3.3%
각 9
 
3.0%
생 9
 
3.0%
브 8
 
2.6%
Other values (76) 177
58.4%
Latin
ValueCountFrequency (%)
K 3
12.0%
C 2
 
8.0%
e 2
 
8.0%
D 2
 
8.0%
l 2
 
8.0%
T 2
 
8.0%
O 2
 
8.0%
i 2
 
8.0%
y 1
 
4.0%
n 1
 
4.0%
Other values (6) 6
24.0%
Common
ValueCountFrequency (%)
34
87.2%
2 3
 
7.7%
3 2
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 303
82.6%
ASCII 64
 
17.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34
53.1%
K 3
 
4.7%
2 3
 
4.7%
3 2
 
3.1%
C 2
 
3.1%
e 2
 
3.1%
D 2
 
3.1%
l 2
 
3.1%
T 2
 
3.1%
O 2
 
3.1%
Other values (9) 10
 
15.6%
Hangul
ValueCountFrequency (%)
로 22
 
7.3%
고 15
 
5.0%
바 15
 
5.0%
대 13
 
4.3%
지 13
 
4.3%
점 12
 
4.0%
사 10
 
3.3%
각 9
 
3.0%
생 9
 
3.0%
브 8
 
2.6%
Other values (76) 177
58.4%

도로명주소
Text

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-12T14:03:47.099343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32
Mean length23.659091
Min length17

Characters and Unicode

Total characters1041
Distinct characters88
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

Unique40 ?
Unique (%)90.9%

Sample

1st row인천광역시 미추홀구 경인로 403 101동 1층 101호, 102호
2nd row인천광역시 미추홀구 한나루로 420 1층
3rd row인천광역시 미추홀구 석바위로 99 5층
4th row인천광역시 미추홀구 경인로504번길 22
5th row인천광역시 미추홀구 주안로 156
ValueCountFrequency (%)
인천광역시 44
20.6%
미추홀구 44
20.6%
1층 5
 
2.3%
바로고 3
 
1.4%
인주대로 3
 
1.4%
2 3
 
1.4%
5층 2
 
0.9%
생각대로 2
 
0.9%
경인로 2
 
0.9%
3층 2
 
0.9%
Other values (92) 104
48.6%
2023-12-12T14:03:47.556879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
170
 
16.3%
인 58
 
5.6%
미 46
 
4.4%
추 46
 
4.4%
로 46
 
4.4%
홀 45
 
4.3%
구 45
 
4.3%
광 44
 
4.2%
역 44
 
4.2%
시 44
 
4.2%
Other values (78) 453
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 673
64.6%
Decimal Number 190
 
18.3%
Space Separator 170
 
16.3%
Dash Punctuation 4
 
0.4%
Uppercase Letter 3
 
0.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 58
 
8.6%
미 46
 
6.8%
추 46
 
6.8%
로 46
 
6.8%
홀 45
 
6.7%
구 45
 
6.7%
광 44
 
6.5%
역 44
 
6.5%
시 44
 
6.5%
천 44
 
6.5%
Other values (63) 211
31.4%
Decimal Number
ValueCountFrequency (%)
1 33
17.4%
2 31
16.3%
3 21
11.1%
4 21
11.1%
0 19
10.0%
7 17
8.9%
9 14
7.4%
8 13
 
6.8%
5 11
 
5.8%
6 10
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
B 2
66.7%
D 1
33.3%
Space Separator
ValueCountFrequency (%)
170
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 673
64.6%
Common 365
35.1%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 58
 
8.6%
미 46
 
6.8%
추 46
 
6.8%
로 46
 
6.8%
홀 45
 
6.7%
구 45
 
6.7%
광 44
 
6.5%
역 44
 
6.5%
시 44
 
6.5%
천 44
 
6.5%
Other values (63) 211
31.4%
Common
ValueCountFrequency (%)
170
46.6%
1 33
 
9.0%
2 31
 
8.5%
3 21
 
5.8%
4 21
 
5.8%
0 19
 
5.2%
7 17
 
4.7%
9 14
 
3.8%
8 13
 
3.6%
5 11
 
3.0%
Other values (3) 15
 
4.1%
Latin
ValueCountFrequency (%)
B 2
66.7%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 673
64.6%
ASCII 368
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
170
46.2%
1 33
 
9.0%
2 31
 
8.4%
3 21
 
5.7%
4 21
 
5.7%
0 19
 
5.2%
7 17
 
4.6%
9 14
 
3.8%
8 13
 
3.5%
5 11
 
3.0%
Other values (5) 18
 
4.9%
Hangul
ValueCountFrequency (%)
인 58
 
8.6%
미 46
 
6.8%
추 46
 
6.8%
로 46
 
6.8%
홀 45
 
6.7%
구 45
 
6.7%
광 44
 
6.5%
역 44
 
6.5%
시 44
 
6.5%
천 44
 
6.5%
Other values (63) 211
31.4%

지번주소
Text

Distinct43
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-12T14:03:47.835596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length23.636364
Min length19

Characters and Unicode

Total characters1040
Distinct characters66
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

Unique42 ?
Unique (%)95.5%

Sample

1st row인천광역시 미추홀구 주안동 77-3 101동 1층 101호, 102호
2nd row인천광역시 미추홀구 학익동 293-37 1층
3rd row인천광역시 미추홀구 주안동 91-6 5층
4th row인천광역시 미추홀구 주안동 1593-27 1층 호세야오리바베큐
5th row인천광역시 미추홀구 주안동 50-2
ValueCountFrequency (%)
인천광역시 44
21.5%
미추홀구 44
21.5%
주안동 17
 
8.3%
용현동 10
 
4.9%
숭의동 9
 
4.4%
1층 5
 
2.4%
도화동 4
 
2.0%
바로고 3
 
1.5%
102호 2
 
1.0%
684-116 2
 
1.0%
Other values (61) 65
31.7%
2023-12-12T14:03:48.348875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
 
15.6%
1 61
 
5.9%
동 46
 
4.4%
인 45
 
4.3%
광 44
 
4.2%
역 44
 
4.2%
시 44
 
4.2%
미 44
 
4.2%
추 44
 
4.2%
홀 44
 
4.2%
Other values (56) 462
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 595
57.2%
Decimal Number 237
 
22.8%
Space Separator 162
 
15.6%
Dash Punctuation 44
 
4.2%
Uppercase Letter 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 46
 
7.7%
인 45
 
7.6%
광 44
 
7.4%
역 44
 
7.4%
시 44
 
7.4%
미 44
 
7.4%
추 44
 
7.4%
홀 44
 
7.4%
구 44
 
7.4%
천 44
 
7.4%
Other values (42) 152
25.5%
Decimal Number
ValueCountFrequency (%)
1 61
25.7%
2 30
12.7%
4 26
11.0%
5 22
 
9.3%
7 20
 
8.4%
0 19
 
8.0%
3 19
 
8.0%
6 18
 
7.6%
8 12
 
5.1%
9 10
 
4.2%
Space Separator
ValueCountFrequency (%)
162
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 595
57.2%
Common 444
42.7%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 46
 
7.7%
인 45
 
7.6%
광 44
 
7.4%
역 44
 
7.4%
시 44
 
7.4%
미 44
 
7.4%
추 44
 
7.4%
홀 44
 
7.4%
구 44
 
7.4%
천 44
 
7.4%
Other values (42) 152
25.5%
Common
ValueCountFrequency (%)
162
36.5%
1 61
 
13.7%
- 44
 
9.9%
2 30
 
6.8%
4 26
 
5.9%
5 22
 
5.0%
7 20
 
4.5%
0 19
 
4.3%
3 19
 
4.3%
6 18
 
4.1%
Other values (3) 23
 
5.2%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 595
57.2%
ASCII 445
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
162
36.4%
1 61
 
13.7%
- 44
 
9.9%
2 30
 
6.7%
4 26
 
5.8%
5 22
 
4.9%
7 20
 
4.5%
0 19
 
4.3%
3 19
 
4.3%
6 18
 
4.0%
Other values (4) 24
 
5.4%
Hangul
ValueCountFrequency (%)
동 46
 
7.7%
인 45
 
7.6%
광 44
 
7.4%
역 44
 
7.4%
시 44
 
7.4%
미 44
 
7.4%
추 44
 
7.4%
홀 44
 
7.4%
구 44
 
7.4%
천 44
 
7.4%
Other values (42) 152
25.5%

전화번호
Text

MISSING 

Distinct30
Distinct (%)100.0%
Missing14
Missing (%)31.8%
Memory size484.0 B
2023-12-12T14:03:48.660803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length12.8
Min length9

Characters and Unicode

Total characters384
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

Unique30 ?
Unique (%)100.0%

Sample

1st row032-429-8858
2nd row070-8666-6242
3rd row032-426-1040
4th row032-1544-7252
5th row0507-1342-0236
ValueCountFrequency (%)
0507-1488-8893 1
 
3.3%
032-426-1040 1
 
3.3%
0507-1381-7425 1
 
3.3%
032-887-7344 1
 
3.3%
032-881-6755 1
 
3.3%
032-446-3082 1
 
3.3%
0507-1376-1447 1
 
3.3%
032-435-7772 1
 
3.3%
032-863-7282 1
 
3.3%
0507-1361-7343 1
 
3.3%
Other values (20) 20
66.7%
2023-12-12T14:03:49.041719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 59
15.4%
0 55
14.3%
3 43
11.2%
2 40
10.4%
7 35
9.1%
8 33
8.6%
5 31
8.1%
4 31
8.1%
1 29
7.6%
6 20
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 325
84.6%
Dash Punctuation 59
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 55
16.9%
3 43
13.2%
2 40
12.3%
7 35
10.8%
8 33
10.2%
5 31
9.5%
4 31
9.5%
1 29
8.9%
6 20
 
6.2%
9 8
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 384
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 59
15.4%
0 55
14.3%
3 43
11.2%
2 40
10.4%
7 35
9.1%
8 33
8.6%
5 31
8.1%
4 31
8.1%
1 29
7.6%
6 20
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 384
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 59
15.4%
0 55
14.3%
3 43
11.2%
2 40
10.4%
7 35
9.1%
8 33
8.6%
5 31
8.1%
4 31
8.1%
1 29
7.6%
6 20
 
5.2%

위도
Real number (ℝ)

Distinct41
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.457394
Minimum37.437267
Maximum37.475474
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T14:03:49.180184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.437267
5-th percentile37.444801
Q137.452649
median37.457974
Q337.4636
95-th percentile37.467719
Maximum37.475474
Range0.03820779
Interquartile range (IQR)0.010950837

Descriptive statistics

Standard deviation0.008268044
Coefficient of variation (CV)0.00022073196
Kurtosis-0.17362228
Mean37.457394
Median Absolute Deviation (MAD)0.00576946
Skewness-0.18775225
Sum1648.1253
Variance6.8360551 × 10-5
MonotonicityNot monotonic
2023-12-12T14:03:49.346391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
37.46647751 2
 
4.5%
37.45808453 2
 
4.5%
37.46623876 2
 
4.5%
37.45133289 1
 
2.3%
37.45068271 1
 
2.3%
37.47100763 1
 
2.3%
37.45489393 1
 
2.3%
37.44971255 1
 
2.3%
37.46763838 1
 
2.3%
37.46773316 1
 
2.3%
Other values (31) 31
70.5%
ValueCountFrequency (%)
37.43726653 1
2.3%
37.4408565 1
2.3%
37.44466548 1
2.3%
37.4455657 1
2.3%
37.44781115 1
2.3%
37.44823914 1
2.3%
37.44844243 1
2.3%
37.44916898 1
2.3%
37.44971255 1
2.3%
37.45068271 1
2.3%
ValueCountFrequency (%)
37.47547432 1
2.3%
37.47100763 1
2.3%
37.46773316 1
2.3%
37.46763838 1
2.3%
37.46747941 1
2.3%
37.46713781 1
2.3%
37.46647751 2
4.5%
37.46623876 2
4.5%
37.46403152 1
2.3%
37.4634564 1
2.3%

경도
Real number (ℝ)

Distinct41
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.6668
Minimum126.64076
Maximum126.69529
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T14:03:49.515914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.64076
5-th percentile126.64186
Q1126.64752
median126.66734
Q3126.68523
95-th percentile126.69116
Maximum126.69529
Range0.0545307
Interquartile range (IQR)0.03771435

Descriptive statistics

Standard deviation0.018444264
Coefficient of variation (CV)0.00014561246
Kurtosis-1.6124006
Mean126.6668
Median Absolute Deviation (MAD)0.0182333
Skewness-0.013649387
Sum5573.3391
Variance0.00034019086
MonotonicityNot monotonic
2023-12-12T14:03:49.698354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
126.6463961 2
 
4.5%
126.6417893 2
 
4.5%
126.6458915 2
 
4.5%
126.6845207 1
 
2.3%
126.6872284 1
 
2.3%
126.6686075 1
 
2.3%
126.6494057 1
 
2.3%
126.6660696 1
 
2.3%
126.6540416 1
 
2.3%
126.6742671 1
 
2.3%
Other values (31) 31
70.5%
ValueCountFrequency (%)
126.640764 1
2.3%
126.6417893 2
4.5%
126.6422558 1
2.3%
126.642525 1
2.3%
126.643722 1
2.3%
126.6458915 2
4.5%
126.6463902 1
2.3%
126.6463961 2
4.5%
126.6478886 1
2.3%
126.6494057 1
2.3%
ValueCountFrequency (%)
126.6952947 1
2.3%
126.6942227 1
2.3%
126.6914332 1
2.3%
126.6895816 1
2.3%
126.6892816 1
2.3%
126.6872284 1
2.3%
126.6869864 1
2.3%
126.6866655 1
2.3%
126.6858881 1
2.3%
126.6856306 1
2.3%

Interactions

2023-12-12T14:03:45.524274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:03:44.956416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:03:45.216204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:03:45.618406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:03:45.031108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:03:45.316570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:03:45.713368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:03:45.117500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:03:45.418235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:03:49.813069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명도로명주소지번주소전화번호위도경도
연번1.0001.0000.8630.9331.0000.6150.393
상호명1.0001.0001.0001.0001.0001.0001.000
도로명주소0.8631.0001.0001.0001.0001.0001.000
지번주소0.9331.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000
위도0.6151.0001.0001.0001.0001.0000.734
경도0.3931.0001.0001.0001.0000.7341.000
2023-12-12T14:03:49.943363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.100-0.185
위도0.1001.000-0.371
경도-0.185-0.3711.000

Missing values

2023-12-12T14:03:45.827308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:03:45.940484image/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

연번상호명도로명주소지번주소전화번호위도경도
01냠냠박스 주안지점인천광역시 미추홀구 경인로 403 101동 1층 101호, 102호인천광역시 미추홀구 주안동 77-3 101동 1층 101호, 102호032-429-885837.458506126.685135
12냠냠박스 용현지점인천광역시 미추홀구 한나루로 420 1층인천광역시 미추홀구 학익동 293-37 1층070-8666-624237.444665126.665983
23바로고 주안3허브인천광역시 미추홀구 석바위로 99 5층인천광역시 미추홀구 주안동 91-6 5층<NA>37.460862126.684211
34바로고인천광역시 미추홀구 경인로504번길 22인천광역시 미추홀구 주안동 1593-27 1층 호세야오리바베큐032-426-104037.459409126.695295
45생각대로 주안지원센터인천광역시 미추홀구 주안로 156인천광역시 미추홀구 주안동 50-2032-1544-725237.463456126.686986
56행복드림콜인천광역시 미추홀구 미추홀대로646번길 24인천광역시 미추홀구 주안동 450-21<NA>37.454833126.681462
67생각대로 제물포지사인천광역시 미추홀구 석정로 94 나동 B01호인천광역시 미추홀구 숭의동 81-1 나동 B01호<NA>37.467479126.64639
78바로고 용현점인천광역시 미추홀구 인주대로 128 3층 바로고 용현점인천광역시 미추홀구 용현동 450-177 3층 바로고 용현점<NA>37.456242126.651186
89부릉 용현지사인천광역시 미추홀구 낙섬동로 90 바로고용오허브인천광역시 미추홀구 용현동 610-176 바로고용오허브0507-1342-023637.453392126.642525
910바로고 도화청운허브인천광역시 미추홀구 염전로202번길 89 1층인천광역시 미추홀구 도화동 854-1 1층032-766-245637.475474126.658995
연번상호명도로명주소지번주소전화번호위도경도
3435배달바다인천광역시 미추홀구 샛골로9번길 10인천광역시 미추홀구 숭의동 432-3032-863-728237.464032126.642256
3536배고파딜리버리배달대행인천광역시 미추홀구 인하로267번길 14인천광역시 미추홀구 주안동 1461-4032-435-777237.449169126.678418
3637생각대로 용현지사인천광역시 미추홀구 인주대로174번길 38인천광역시 미추홀구 용현동 152-3<NA>37.454346126.657746
3738생각대로 숭의지사인천광역시 미추홀구 독정이로 4인천광역시 미추홀구 용현동 490-21<NA>37.45651126.655237
3839보스배달대행인천광역시 미추홀구 인주대로407번길 39인천광역시 미추홀구 주안동 1474-680507-1376-144737.453239126.681842
3940탑콜배달대행인천광역시 미추홀구 경원대로 737인천광역시 미추홀구 주안동 1527-7032-446-308237.448442126.689582
4041DeliveryKing 숭의점인천광역시 미추홀구 석정로76번길 5인천광역시 미추홀구 숭의동 124-143032-881-675537.466239126.645892
4142바로고 미추홀2허브인천광역시 미추홀구 독정이로 59 이자녹스파라상사인천광역시 미추홀구 숭의동 207-5<NA>37.460933126.65224
4243웅콜인천광역시 미추홀구 참외전로 288-8인천광역시 미추홀구 숭의동 124-167032-887-734437.466478126.646396
4344생각대로 용현FDC인천광역시 미추홀구 능해길77번길 2 2층인천광역시 미추홀구 용현동 684-1160507-1366-986537.458085126.641789