Overview

Dataset statistics

Number of variables7
Number of observations136
Missing cells16
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.0 KiB
Average record size in memory60.0 B

Variable types

Numeric3
Text4

Dataset

Description김해시 액화석유가스 판매업체 현황(상호, 지번주소, 도로명주소, 연락처, 위도, 경도 등)에 대한 데이터를 제공합니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15033416/fileData.do

Alerts

지번주소 has 2 (1.5%) missing valuesMissing
연락처 has 14 (10.3%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:11:27.637529
Analysis finished2023-12-12 21:11:29.066974
Duration1.43 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct136
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.5
Minimum1
Maximum136
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:11:29.135148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.75
Q134.75
median68.5
Q3102.25
95-th percentile129.25
Maximum136
Range135
Interquartile range (IQR)67.5

Descriptive statistics

Standard deviation39.403892
Coefficient of variation (CV)0.57523929
Kurtosis-1.2
Mean68.5
Median Absolute Deviation (MAD)34
Skewness0
Sum9316
Variance1552.6667
MonotonicityStrictly increasing
2023-12-13T06:11:29.254826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
95 1
 
0.7%
89 1
 
0.7%
90 1
 
0.7%
91 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
96 1
 
0.7%
70 1
 
0.7%
Other values (126) 126
92.6%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%
131 1
0.7%
130 1
0.7%
129 1
0.7%
128 1
0.7%
127 1
0.7%

상호
Text

Distinct132
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T06:11:29.460269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.7426471
Min length4

Characters and Unicode

Total characters781
Distinct characters136
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique128 ?
Unique (%)94.1%

Sample

1st row상동.대동가스
2nd row김해가스
3rd row경남가스
4th row안전가스
5th row김해에너지
ValueCountFrequency (%)
주 5
 
3.4%
5
 
3.4%
화성산업가스 2
 
1.4%
진영에너지 2
 
1.4%
장유가스 2
 
1.4%
㈜삼흥에너지 2
 
1.4%
삼성가스 1
 
0.7%
주공가스 1
 
0.7%
에스티이㈜ 1
 
0.7%
광진가스텍 1
 
0.7%
Other values (125) 125
85.0%
2023-12-13T06:11:29.855302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 100
 
12.8%
가 97
 
12.4%
합 36
 
4.6%
종 35
 
4.5%
에 34
 
4.4%
너 29
 
3.7%
지 28
 
3.6%
진 19
 
2.4%
산 17
 
2.2%
㈜ 16
 
2.0%
Other values (126) 370
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 722
92.4%
Other Symbol 16
 
2.0%
Space Separator 11
 
1.4%
Uppercase Letter 11
 
1.4%
Lowercase Letter 7
 
0.9%
Open Punctuation 6
 
0.8%
Close Punctuation 6
 
0.8%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 100
 
13.9%
가 97
 
13.4%
합 36
 
5.0%
종 35
 
4.8%
에 34
 
4.7%
너 29
 
4.0%
지 28
 
3.9%
진 19
 
2.6%
산 17
 
2.4%
동 16
 
2.2%
Other values (105) 311
43.1%
Uppercase Letter
ValueCountFrequency (%)
B 2
18.2%
S 2
18.2%
K 1
9.1%
M 1
9.1%
J 1
9.1%
Y 1
9.1%
A 1
9.1%
R 1
9.1%
T 1
9.1%
Lowercase Letter
ValueCountFrequency (%)
o 2
28.6%
s 1
14.3%
d 1
14.3%
g 1
14.3%
r 1
14.3%
i 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 16
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 738
94.5%
Common 25
 
3.2%
Latin 18
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 100
 
13.6%
가 97
 
13.1%
합 36
 
4.9%
종 35
 
4.7%
에 34
 
4.6%
너 29
 
3.9%
지 28
 
3.8%
진 19
 
2.6%
산 17
 
2.3%
㈜ 16
 
2.2%
Other values (106) 327
44.3%
Latin
ValueCountFrequency (%)
B 2
 
11.1%
o 2
 
11.1%
S 2
 
11.1%
K 1
 
5.6%
M 1
 
5.6%
J 1
 
5.6%
Y 1
 
5.6%
s 1
 
5.6%
d 1
 
5.6%
g 1
 
5.6%
Other values (5) 5
27.8%
Common
ValueCountFrequency (%)
11
44.0%
( 6
24.0%
) 6
24.0%
, 1
 
4.0%
. 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 722
92.4%
ASCII 43
 
5.5%
None 16
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 100
 
13.9%
가 97
 
13.4%
합 36
 
5.0%
종 35
 
4.8%
에 34
 
4.7%
너 29
 
4.0%
지 28
 
3.9%
진 19
 
2.6%
산 17
 
2.4%
동 16
 
2.2%
Other values (105) 311
43.1%
None
ValueCountFrequency (%)
㈜ 16
100.0%
ASCII
ValueCountFrequency (%)
11
25.6%
( 6
14.0%
) 6
14.0%
B 2
 
4.7%
o 2
 
4.7%
S 2
 
4.7%
K 1
 
2.3%
M 1
 
2.3%
J 1
 
2.3%
, 1
 
2.3%
Other values (10) 10
23.3%

지번주소
Text

MISSING 

Distinct97
Distinct (%)72.4%
Missing2
Missing (%)1.5%
Memory size1.2 KiB
2023-12-13T06:11:30.187775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length20.544776
Min length15

Characters and Unicode

Total characters2753
Distinct characters82
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

Unique79 ?
Unique (%)59.0%

Sample

1st row경상남도 김해시 대동면 초정리 136-1
2nd row경상남도 김해시 봉황동 386-3
3rd row경상남도 김해시 진영읍 본산리 308-19
4th row경상남도 김해시 동상동 770
5th row경상남도 김해시 삼방동 106-6
ValueCountFrequency (%)
경상남도 134
21.3%
김해시 134
21.3%
생림면 30
 
4.8%
진영읍 16
 
2.5%
주촌면 14
 
2.2%
한림면 14
 
2.2%
생철리 13
 
2.1%
상동면 12
 
1.9%
내삼리 12
 
1.9%
사촌리 8
 
1.3%
Other values (143) 243
38.6%
2023-12-13T06:11:30.694047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
496
18.0%
상 150
 
5.4%
시 135
 
4.9%
경 134
 
4.9%
남 134
 
4.9%
도 134
 
4.9%
김 134
 
4.9%
해 134
 
4.9%
1 112
 
4.1%
- 106
 
3.9%
Other values (72) 1084
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1614
58.6%
Decimal Number 537
 
19.5%
Space Separator 496
 
18.0%
Dash Punctuation 106
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 150
 
9.3%
시 135
 
8.4%
경 134
 
8.3%
남 134
 
8.3%
도 134
 
8.3%
김 134
 
8.3%
해 134
 
8.3%
리 94
 
5.8%
면 78
 
4.8%
동 60
 
3.7%
Other values (60) 427
26.5%
Decimal Number
ValueCountFrequency (%)
1 112
20.9%
2 85
15.8%
3 65
12.1%
5 51
9.5%
8 45
8.4%
7 45
8.4%
0 40
 
7.4%
4 36
 
6.7%
6 35
 
6.5%
9 23
 
4.3%
Space Separator
ValueCountFrequency (%)
496
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1614
58.6%
Common 1139
41.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 150
 
9.3%
시 135
 
8.4%
경 134
 
8.3%
남 134
 
8.3%
도 134
 
8.3%
김 134
 
8.3%
해 134
 
8.3%
리 94
 
5.8%
면 78
 
4.8%
동 60
 
3.7%
Other values (60) 427
26.5%
Common
ValueCountFrequency (%)
496
43.5%
1 112
 
9.8%
- 106
 
9.3%
2 85
 
7.5%
3 65
 
5.7%
5 51
 
4.5%
8 45
 
4.0%
7 45
 
4.0%
0 40
 
3.5%
4 36
 
3.2%
Other values (2) 58
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1614
58.6%
ASCII 1139
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
496
43.5%
1 112
 
9.8%
- 106
 
9.3%
2 85
 
7.5%
3 65
 
5.7%
5 51
 
4.5%
8 45
 
4.0%
7 45
 
4.0%
0 40
 
3.5%
4 36
 
3.2%
Other values (2) 58
 
5.1%
Hangul
ValueCountFrequency (%)
상 150
 
9.3%
시 135
 
8.4%
경 134
 
8.3%
남 134
 
8.3%
도 134
 
8.3%
김 134
 
8.3%
해 134
 
8.3%
리 94
 
5.8%
면 78
 
4.8%
동 60
 
3.7%
Other values (60) 427
26.5%

도로명주소
Text

Distinct101
Distinct (%)74.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-13T06:11:31.047053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length29
Mean length22.470588
Min length15

Characters and Unicode

Total characters3056
Distinct characters82
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)61.8%

Sample

1st row경상남도 김해시 대동면 동남로49번길 85
2nd row경상남도 김해시 분성로288번길 6-1
3rd row경상남도 김해시 진영읍 본산로269번길 15-43
4th row경상남도 김해시 호계로 494
5th row경상남도 김해시 생림면 인제로 687
ValueCountFrequency (%)
경상남도 138
21.2%
김해시 133
20.5%
생림면 32
 
4.9%
진영읍 16
 
2.5%
주촌면 14
 
2.2%
마사로 14
 
2.2%
한림면 14
 
2.2%
상동면 12
 
1.8%
나전로 8
 
1.2%
진례면 7
 
1.1%
Other values (174) 262
40.3%
2023-12-13T06:11:31.493681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
535
17.5%
상 160
 
5.2%
남 140
 
4.6%
경 139
 
4.5%
김 139
 
4.5%
해 139
 
4.5%
도 138
 
4.5%
로 135
 
4.4%
시 133
 
4.4%
1 118
 
3.9%
Other values (72) 1280
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1837
60.1%
Decimal Number 619
 
20.3%
Space Separator 535
 
17.5%
Dash Punctuation 52
 
1.7%
Close Punctuation 6
 
0.2%
Open Punctuation 6
 
0.2%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 160
 
8.7%
남 140
 
7.6%
경 139
 
7.6%
김 139
 
7.6%
해 139
 
7.6%
도 138
 
7.5%
로 135
 
7.3%
시 133
 
7.2%
면 80
 
4.4%
길 73
 
4.0%
Other values (57) 561
30.5%
Decimal Number
ValueCountFrequency (%)
1 118
19.1%
2 79
12.8%
4 72
11.6%
3 67
10.8%
6 63
10.2%
9 60
9.7%
5 56
9.0%
7 42
 
6.8%
8 37
 
6.0%
0 25
 
4.0%
Space Separator
ValueCountFrequency (%)
535
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1838
60.1%
Common 1218
39.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 160
 
8.7%
남 140
 
7.6%
경 139
 
7.6%
김 139
 
7.6%
해 139
 
7.6%
도 138
 
7.5%
로 135
 
7.3%
시 133
 
7.2%
면 80
 
4.4%
길 73
 
4.0%
Other values (58) 562
30.6%
Common
ValueCountFrequency (%)
535
43.9%
1 118
 
9.7%
2 79
 
6.5%
4 72
 
5.9%
3 67
 
5.5%
6 63
 
5.2%
9 60
 
4.9%
5 56
 
4.6%
- 52
 
4.3%
7 42
 
3.4%
Other values (4) 74
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1837
60.1%
ASCII 1218
39.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
535
43.9%
1 118
 
9.7%
2 79
 
6.5%
4 72
 
5.9%
3 67
 
5.5%
6 63
 
5.2%
9 60
 
4.9%
5 56
 
4.6%
- 52
 
4.3%
7 42
 
3.4%
Other values (4) 74
 
6.1%
Hangul
ValueCountFrequency (%)
상 160
 
8.7%
남 140
 
7.6%
경 139
 
7.6%
김 139
 
7.6%
해 139
 
7.6%
도 138
 
7.5%
로 135
 
7.3%
시 133
 
7.2%
면 80
 
4.4%
길 73
 
4.0%
Other values (57) 561
30.5%
None
ValueCountFrequency (%)
㈜ 1
100.0%

연락처
Text

MISSING 

Distinct117
Distinct (%)95.9%
Missing14
Missing (%)10.3%
Memory size1.2 KiB
2023-12-13T06:11:31.746335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.97541
Min length11

Characters and Unicode

Total characters1461
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

Unique113 ?
Unique (%)92.6%

Sample

1st row055-335-7755
2nd row055-326-3651
3rd row055-342-1515
4th row055-336-3939
5th row055-333-5003
ValueCountFrequency (%)
055-621-802 3
 
2.5%
055-343-0500 2
 
1.6%
055-338-7618 2
 
1.6%
055-335-4282 2
 
1.6%
051-312-1447 1
 
0.8%
055-345-2900 1
 
0.8%
055-345-7100 1
 
0.8%
055-336-1261 1
 
0.8%
055-313-9540 1
 
0.8%
055-327-6700 1
 
0.8%
Other values (107) 107
87.7%
2023-12-13T06:11:32.168341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 313
21.4%
- 244
16.7%
3 231
15.8%
0 203
13.9%
2 101
 
6.9%
1 95
 
6.5%
4 74
 
5.1%
7 60
 
4.1%
6 55
 
3.8%
8 48
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1217
83.3%
Dash Punctuation 244
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 313
25.7%
3 231
19.0%
0 203
16.7%
2 101
 
8.3%
1 95
 
7.8%
4 74
 
6.1%
7 60
 
4.9%
6 55
 
4.5%
8 48
 
3.9%
9 37
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 244
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1461
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 313
21.4%
- 244
16.7%
3 231
15.8%
0 203
13.9%
2 101
 
6.9%
1 95
 
6.5%
4 74
 
5.1%
7 60
 
4.1%
6 55
 
3.8%
8 48
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1461
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 313
21.4%
- 244
16.7%
3 231
15.8%
0 203
13.9%
2 101
 
6.9%
1 95
 
6.5%
4 74
 
5.1%
7 60
 
4.1%
6 55
 
3.8%
8 48
 
3.3%

위도
Real number (ℝ)

Distinct98
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.275532
Minimum35.183609
Maximum35.375311
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:11:32.339810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.183609
5-th percentile35.208586
Q135.232527
median35.28527
Q335.31703
95-th percentile35.348855
Maximum35.375311
Range0.19170233
Interquartile range (IQR)0.084502235

Descriptive statistics

Standard deviation0.047967187
Coefficient of variation (CV)0.0013597864
Kurtosis-1.2266018
Mean35.275532
Median Absolute Deviation (MAD)0.04521765
Skewness0.042892095
Sum4797.4724
Variance0.0023008511
MonotonicityNot monotonic
2023-12-13T06:11:32.523872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.34689198 6
 
4.4%
35.2865243 6
 
4.4%
35.31825877 5
 
3.7%
35.32405403 4
 
2.9%
35.2338484 4
 
2.9%
35.34999736 3
 
2.2%
35.23082198 3
 
2.2%
35.34885487 3
 
2.2%
35.26614114 3
 
2.2%
35.31697258 2
 
1.5%
Other values (88) 97
71.3%
ValueCountFrequency (%)
35.18360858 1
0.7%
35.19237558 1
0.7%
35.19285234 1
0.7%
35.1948886 1
0.7%
35.19739974 1
0.7%
35.1994309 1
0.7%
35.20692341 1
0.7%
35.20913996 1
0.7%
35.21060109 1
0.7%
35.21079906 1
0.7%
ValueCountFrequency (%)
35.37531091 1
 
0.7%
35.37427365 1
 
0.7%
35.35050613 1
 
0.7%
35.34999736 3
2.2%
35.34885487 3
2.2%
35.34689198 6
4.4%
35.32856977 1
 
0.7%
35.32405403 4
2.9%
35.32390776 1
 
0.7%
35.32363047 2
 
1.5%

경도
Real number (ℝ)

Distinct98
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.83665
Minimum128.72648
Maximum128.98578
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-13T06:11:32.687507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.72648
5-th percentile128.74427
Q1128.8
median128.84723
Q3128.87842
95-th percentile128.92266
Maximum128.98578
Range0.2592997
Interquartile range (IQR)0.07842045

Descriptive statistics

Standard deviation0.057533609
Coefficient of variation (CV)0.00044656245
Kurtosis-0.56258775
Mean128.83665
Median Absolute Deviation (MAD)0.0389124
Skewness-0.051025925
Sum17521.784
Variance0.0033101161
MonotonicityNot monotonic
2023-12-13T06:11:32.841973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8516631 6
 
4.4%
128.726481 6
 
4.4%
128.8719965 5
 
3.7%
128.7805542 4
 
2.9%
128.8155595 4
 
2.9%
128.8512141 3
 
2.2%
128.8154777 3
 
2.2%
128.8521952 3
 
2.2%
128.7497673 3
 
2.2%
128.8687392 2
 
1.5%
Other values (88) 97
71.3%
ValueCountFrequency (%)
128.726481 6
4.4%
128.7393396 1
 
0.7%
128.7459075 1
 
0.7%
128.7497673 3
2.2%
128.7498176 1
 
0.7%
128.7507711 1
 
0.7%
128.7532476 2
 
1.5%
128.75525 1
 
0.7%
128.7576985 1
 
0.7%
128.7583961 1
 
0.7%
ValueCountFrequency (%)
128.9857807 1
0.7%
128.9587045 2
1.5%
128.9403683 2
1.5%
128.9306994 1
0.7%
128.9300513 1
0.7%
128.9201907 1
0.7%
128.9186525 1
0.7%
128.9186412 1
0.7%
128.9121551 1
0.7%
128.9091156 1
0.7%

Interactions

2023-12-13T06:11:28.348831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:11:27.899881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:11:28.123526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:11:28.417935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:11:27.972896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:11:28.197311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:11:28.491054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:11:28.054338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:11:28.280170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:11:32.957271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지번주소위도경도
연번1.0000.9520.5660.485
지번주소0.9521.0001.0001.000
위도0.5661.0001.0000.779
경도0.4851.0000.7791.000
2023-12-13T06:11:33.057117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.0000.378-0.131
위도0.3781.0000.009
경도-0.1310.0091.000

Missing values

2023-12-13T06:11:28.576577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:11:28.676355image/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.
2023-12-13T06:11:29.029109image/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

연번상호지번주소도로명주소연락처위도경도
01상동.대동가스경상남도 김해시 대동면 초정리 136-1경상남도 김해시 대동면 동남로49번길 85055-335-775535.236381128.985781
12김해가스경상남도 김해시 봉황동 386-3경상남도 김해시 분성로288번길 6-1055-326-365135.232438128.877481
23경남가스경상남도 김해시 진영읍 본산리 308-19경상남도 김해시 진영읍 본산로269번길 15-43055-342-151535.3172128.753248
34안전가스경상남도 김해시 동상동 770경상남도 김해시 호계로 494055-336-393935.23462128.884641
45김해에너지<NA>경상남도 김해시 생림면 인제로 687055-333-500335.286128128.885933
56안동가스경상남도 김해시 삼방동 106-6경상남도 김해시 분성로627번길 61055-332-030435.241104128.912155
67새음종합가스경상남도 김해시 한림면 장방리 1253-19경상남도 김해시 한림면 한림로 384055-342-744735.321714128.802944
78한림가스경상남도 김해시 한림면 명동리 62-12경상남도 김해시 한림면 한림로 130055-342-711135.305004128.808108
89부원가스경상남도 김해시 동상동 1118-28경상남도 김해시 호계로 544055-333-079735.239028128.884306
910진례가스경상남도 김해시 진례면 송정리 263-3경상남도 김해시 진례면 송현로 14055-345-512035.248744128.749818
연번상호지번주소도로명주소연락처위도경도
126127모라종합가스경상남도 김해시 상동면 매리 464-97경상남도 김해시 상동면 상동로 844-1<NA>35.316144128.958705
127128삼화특수가스경상남도 김해시 상동면 매리 464-97경상남도 김해시 상동면 상동로 844-1<NA>35.316144128.958705
128129삼보가스<NA>경상남도 김해시 생림면 인제로 687055-334-261135.286128128.885933
129130삼일종합가스경상남도 김해시 주촌면 내삼리 356경상남도 김해시 주촌면 서부로1541번안길 44-71<NA>35.237662128.811632
130131진영에너지경상남도 김해시 진영읍 하계리 208-1경상남도 김해시 진영읍 하계로 215055-621-80235.286524128.726481
131132화성산업가스경상남도 김해시 진영읍 하계리 208-1경상남도 김해시 진영읍 하계로 215055-621-80235.286524128.726481
132133장유가스경상남도 김해시 진영읍 하계리 208-1경상남도 김해시 진영읍 하계로 215055-621-80235.286524128.726481
133134대진가스경상남도 김해시 생림면 나전리 784-4경상남도 김해시 생림면 생림대로 544-33<NA>35.316973128.868739
134135상동종합가스경상남도 김해시 생림면 나전리 784-4경상남도 김해시 생림면 생림대로 544-33<NA>35.316973128.868739
135136창신산업가스경상남도 김해시 진영읍 본산리 947경상남도 김해시 진영읍 본산로86번길 34-11<NA>35.311823128.745907