Overview

Dataset statistics

Number of variables8
Number of observations285
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.8 KiB
Average record size in memory67.5 B

Variable types

Numeric3
Categorical1
Text4

Dataset

Description김해시 마을회관 현황(읍면동, 마을명, 회관명, 지번주소, 도로명주소, 위도, 경도 등)에 대한 데이터를 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15008085

Alerts

연번 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 읍면동High correlation
경도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
읍면동 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:22:12.687438
Analysis finished2023-12-10 23:22:14.097326
Duration1.41 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct285
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean143
Minimum1
Maximum285
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T08:22:14.163323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.2
Q172
median143
Q3214
95-th percentile270.8
Maximum285
Range284
Interquartile range (IQR)142

Descriptive statistics

Standard deviation82.416625
Coefficient of variation (CV)0.57634003
Kurtosis-1.2
Mean143
Median Absolute Deviation (MAD)71
Skewness0
Sum40755
Variance6792.5
MonotonicityStrictly increasing
2023-12-11T08:22:14.337097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
189 1
 
0.4%
195 1
 
0.4%
194 1
 
0.4%
193 1
 
0.4%
192 1
 
0.4%
191 1
 
0.4%
190 1
 
0.4%
188 1
 
0.4%
197 1
 
0.4%
Other values (275) 275
96.5%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
285 1
0.4%
284 1
0.4%
283 1
0.4%
282 1
0.4%
281 1
0.4%
280 1
0.4%
279 1
0.4%
278 1
0.4%
277 1
0.4%
276 1
0.4%

읍면동
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
진영읍
45 
한림면
45 
진례면
33 
대동면
32 
생림면
25 
Other values (12)
105 

Length

Max length5
Median length3
Mean length3.2035088
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
진영읍 45
15.8%
한림면 45
15.8%
진례면 33
11.6%
대동면 32
11.2%
생림면 25
8.8%
주촌면 22
7.7%
칠산서부동 18
 
6.3%
상동면 17
 
6.0%
장유1동 12
 
4.2%
장유3동 8
 
2.8%
Other values (7) 28
9.8%

Length

2023-12-11T08:22:14.498744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
진영읍 45
15.8%
한림면 45
15.8%
진례면 33
11.6%
대동면 32
11.2%
생림면 25
8.8%
주촌면 22
7.7%
칠산서부동 18
 
6.3%
상동면 17
 
6.0%
장유1동 12
 
4.2%
장유3동 8
 
2.8%
Other values (7) 28
9.8%

마을명(리_통)
Text

Distinct96
Distinct (%)33.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-11T08:22:14.770273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9052632
Min length2

Characters and Unicode

Total characters828
Distinct characters104
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)3.9%

Sample

1st row우동리
2nd row우동리
3rd row하계리
4th row하계리
5th row하계리
ValueCountFrequency (%)
진영리 11
 
3.9%
대감리 6
 
2.1%
송정리 6
 
2.1%
장방리 6
 
2.1%
초정리 6
 
2.1%
여래리 6
 
2.1%
시산리 5
 
1.8%
퇴래리 5
 
1.8%
예안리 5
 
1.8%
본산리 5
 
1.8%
Other values (86) 224
78.6%
2023-12-11T08:22:15.167504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 206
24.9%
동 84
 
10.1%
안 24
 
2.9%
산 23
 
2.8%
정 17
 
2.1%
신 16
 
1.9%
곡 15
 
1.8%
방 15
 
1.8%
덕 14
 
1.7%
하 12
 
1.4%
Other values (94) 402
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 822
99.3%
Decimal Number 4
 
0.5%
Space Separator 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 206
25.1%
동 84
 
10.2%
안 24
 
2.9%
산 23
 
2.8%
정 17
 
2.1%
신 16
 
1.9%
곡 15
 
1.8%
방 15
 
1.8%
덕 14
 
1.7%
하 12
 
1.5%
Other values (89) 396
48.2%
Decimal Number
ValueCountFrequency (%)
0 1
25.0%
2 1
25.0%
4 1
25.0%
1 1
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 822
99.3%
Common 6
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 206
25.1%
동 84
 
10.2%
안 24
 
2.9%
산 23
 
2.8%
정 17
 
2.1%
신 16
 
1.9%
곡 15
 
1.8%
방 15
 
1.8%
덕 14
 
1.7%
하 12
 
1.5%
Other values (89) 396
48.2%
Common
ValueCountFrequency (%)
2
33.3%
0 1
16.7%
2 1
16.7%
4 1
16.7%
1 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 822
99.3%
ASCII 6
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 206
25.1%
동 84
 
10.2%
안 24
 
2.9%
산 23
 
2.8%
정 17
 
2.1%
신 16
 
1.9%
곡 15
 
1.8%
방 15
 
1.8%
덕 14
 
1.7%
하 12
 
1.5%
Other values (89) 396
48.2%
ASCII
ValueCountFrequency (%)
2
33.3%
0 1
16.7%
2 1
16.7%
4 1
16.7%
1 1
16.7%

회관명
Text

Distinct270
Distinct (%)94.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-11T08:22:15.507675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length2
Mean length2.922807
Min length2

Characters and Unicode

Total characters833
Distinct characters170
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique258 ?
Unique (%)90.5%

Sample

1st row서천
2nd row우동
3rd row오척
4th row오척2
5th row하계
ValueCountFrequency (%)
용전 3
 
1.0%
신안 3
 
1.0%
신촌 3
 
1.0%
용덕 2
 
0.7%
선암 2
 
0.7%
소감 2
 
0.7%
중리 2
 
0.7%
퇴은 2
 
0.7%
송정 2
 
0.7%
신기 2
 
0.7%
Other values (260) 263
92.0%
2023-12-11T08:22:15.953321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
통 48
 
5.8%
구 40
 
4.8%
동 38
 
4.6%
1 37
 
4.4%
2 26
 
3.1%
신 24
 
2.9%
( 20
 
2.4%
) 20
 
2.4%
곡 18
 
2.2%
산 18
 
2.2%
Other values (160) 544
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 685
82.2%
Decimal Number 100
 
12.0%
Open Punctuation 20
 
2.4%
Close Punctuation 20
 
2.4%
Other Punctuation 7
 
0.8%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
통 48
 
7.0%
구 40
 
5.8%
동 38
 
5.5%
신 24
 
3.5%
곡 18
 
2.6%
산 18
 
2.6%
안 17
 
2.5%
하 17
 
2.5%
전 15
 
2.2%
천 14
 
2.0%
Other values (146) 436
63.6%
Decimal Number
ValueCountFrequency (%)
1 37
37.0%
2 26
26.0%
3 11
 
11.0%
5 7
 
7.0%
4 7
 
7.0%
7 6
 
6.0%
0 3
 
3.0%
8 2
 
2.0%
9 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
. 1
 
14.3%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 685
82.2%
Common 148
 
17.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
통 48
 
7.0%
구 40
 
5.8%
동 38
 
5.5%
신 24
 
3.5%
곡 18
 
2.6%
산 18
 
2.6%
안 17
 
2.5%
하 17
 
2.5%
전 15
 
2.2%
천 14
 
2.0%
Other values (146) 436
63.6%
Common
ValueCountFrequency (%)
1 37
25.0%
2 26
17.6%
( 20
13.5%
) 20
13.5%
3 11
 
7.4%
5 7
 
4.7%
4 7
 
4.7%
7 6
 
4.1%
, 6
 
4.1%
0 3
 
2.0%
Other values (4) 5
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 685
82.2%
ASCII 148
 
17.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
통 48
 
7.0%
구 40
 
5.8%
동 38
 
5.5%
신 24
 
3.5%
곡 18
 
2.6%
산 18
 
2.6%
안 17
 
2.5%
하 17
 
2.5%
전 15
 
2.2%
천 14
 
2.0%
Other values (146) 436
63.6%
ASCII
ValueCountFrequency (%)
1 37
25.0%
2 26
17.6%
( 20
13.5%
) 20
13.5%
3 11
 
7.4%
5 7
 
4.7%
4 7
 
4.7%
7 6
 
4.1%
, 6
 
4.1%
0 3
 
2.0%
Other values (4) 5
 
3.4%

지번주소
Text

Distinct284
Distinct (%)100.0%
Missing1
Missing (%)0.4%
Memory size2.4 KiB
2023-12-11T08:22:16.296402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length22.848592
Min length15

Characters and Unicode

Total characters6489
Distinct characters152
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

Unique284 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 진영읍 우동리 826-56
2nd row경상남도 김해시 진영읍 우동리 165-20
3rd row경상남도 김해시 진영읍 하계리 산90-1
4th row경상남도 김해시 진영읍 하계리 539-2
5th row경상남도 김해시 진영읍 하계리 279-7
ValueCountFrequency (%)
경상남도 284
19.7%
김해시 284
19.7%
진영읍 45
 
3.1%
한림면 45
 
3.1%
진례면 33
 
2.3%
대동면 31
 
2.2%
생림면 25
 
1.7%
주촌면 22
 
1.5%
상동면 17
 
1.2%
진영리 11
 
0.8%
Other values (461) 642
44.6%
2023-12-11T08:22:16.806843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1156
17.8%
상 309
 
4.8%
경 294
 
4.5%
시 293
 
4.5%
도 287
 
4.4%
남 284
 
4.4%
김 284
 
4.4%
해 284
 
4.4%
- 228
 
3.5%
리 218
 
3.4%
Other values (142) 2852
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3969
61.2%
Space Separator 1156
 
17.8%
Decimal Number 1136
 
17.5%
Dash Punctuation 228
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 309
 
7.8%
경 294
 
7.4%
시 293
 
7.4%
도 287
 
7.2%
남 284
 
7.2%
김 284
 
7.2%
해 284
 
7.2%
리 218
 
5.5%
면 173
 
4.4%
동 141
 
3.6%
Other values (130) 1402
35.3%
Decimal Number
ValueCountFrequency (%)
1 211
18.6%
2 156
13.7%
3 130
11.4%
5 111
9.8%
6 98
8.6%
4 94
8.3%
8 90
7.9%
7 88
7.7%
9 86
7.6%
0 72
 
6.3%
Space Separator
ValueCountFrequency (%)
1156
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 228
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3969
61.2%
Common 2520
38.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 309
 
7.8%
경 294
 
7.4%
시 293
 
7.4%
도 287
 
7.2%
남 284
 
7.2%
김 284
 
7.2%
해 284
 
7.2%
리 218
 
5.5%
면 173
 
4.4%
동 141
 
3.6%
Other values (130) 1402
35.3%
Common
ValueCountFrequency (%)
1156
45.9%
- 228
 
9.0%
1 211
 
8.4%
2 156
 
6.2%
3 130
 
5.2%
5 111
 
4.4%
6 98
 
3.9%
4 94
 
3.7%
8 90
 
3.6%
7 88
 
3.5%
Other values (2) 158
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3969
61.2%
ASCII 2520
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1156
45.9%
- 228
 
9.0%
1 211
 
8.4%
2 156
 
6.2%
3 130
 
5.2%
5 111
 
4.4%
6 98
 
3.9%
4 94
 
3.7%
8 90
 
3.6%
7 88
 
3.5%
Other values (2) 158
 
6.3%
Hangul
ValueCountFrequency (%)
상 309
 
7.8%
경 294
 
7.4%
시 293
 
7.4%
도 287
 
7.2%
남 284
 
7.2%
김 284
 
7.2%
해 284
 
7.2%
리 218
 
5.5%
면 173
 
4.4%
동 141
 
3.6%
Other values (130) 1402
35.3%

도로명주소
Text

UNIQUE 

Distinct285
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2023-12-11T08:22:17.099078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length30
Mean length23.522807
Min length14

Characters and Unicode

Total characters6704
Distinct characters112
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique285 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 진영읍 하계로96번안길 108-13
2nd row경상남도 김해시 진영읍 하계로96번길 133
3rd row경상남도 김해시 진영읍 하계로138번길 125-10
4th row경상남도 김해시 진영읍 하계로138번길 144
5th row경상남도 김해시 진영읍 하계로 260
ValueCountFrequency (%)
김해시 288
21.1%
경상남도 285
20.9%
한림면 45
 
3.3%
진영읍 45
 
3.3%
상동면 34
 
2.5%
진례면 33
 
2.4%
대동면 32
 
2.3%
생림면 25
 
1.8%
주촌면 22
 
1.6%
동북로 8
 
0.6%
Other values (444) 549
40.2%
2023-12-11T08:22:17.566009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1088
 
16.2%
상 326
 
4.9%
해 309
 
4.6%
김 308
 
4.6%
1 298
 
4.4%
남 298
 
4.4%
시 288
 
4.3%
경 285
 
4.3%
도 285
 
4.3%
로 270
 
4.0%
Other values (102) 2949
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4082
60.9%
Decimal Number 1411
 
21.0%
Space Separator 1088
 
16.2%
Dash Punctuation 105
 
1.6%
Open Punctuation 9
 
0.1%
Close Punctuation 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 326
 
8.0%
해 309
 
7.6%
김 308
 
7.5%
남 298
 
7.3%
시 288
 
7.1%
경 285
 
7.0%
도 285
 
7.0%
로 270
 
6.6%
길 231
 
5.7%
번 218
 
5.3%
Other values (88) 1264
31.0%
Decimal Number
ValueCountFrequency (%)
1 298
21.1%
2 194
13.7%
4 142
10.1%
3 141
10.0%
7 115
 
8.2%
9 113
 
8.0%
6 113
 
8.0%
5 108
 
7.7%
8 99
 
7.0%
0 88
 
6.2%
Space Separator
ValueCountFrequency (%)
1088
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 105
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4082
60.9%
Common 2622
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 326
 
8.0%
해 309
 
7.6%
김 308
 
7.5%
남 298
 
7.3%
시 288
 
7.1%
경 285
 
7.0%
도 285
 
7.0%
로 270
 
6.6%
길 231
 
5.7%
번 218
 
5.3%
Other values (88) 1264
31.0%
Common
ValueCountFrequency (%)
1088
41.5%
1 298
 
11.4%
2 194
 
7.4%
4 142
 
5.4%
3 141
 
5.4%
7 115
 
4.4%
9 113
 
4.3%
6 113
 
4.3%
5 108
 
4.1%
- 105
 
4.0%
Other values (4) 205
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4082
60.9%
ASCII 2622
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1088
41.5%
1 298
 
11.4%
2 194
 
7.4%
4 142
 
5.4%
3 141
 
5.4%
7 115
 
4.4%
9 113
 
4.3%
6 113
 
4.3%
5 108
 
4.1%
- 105
 
4.0%
Other values (4) 205
 
7.8%
Hangul
ValueCountFrequency (%)
상 326
 
8.0%
해 309
 
7.6%
김 308
 
7.5%
남 298
 
7.3%
시 288
 
7.1%
경 285
 
7.0%
도 285
 
7.0%
로 270
 
6.6%
길 231
 
5.7%
번 218
 
5.3%
Other values (88) 1264
31.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct284
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.270223
Minimum35.170824
Maximum35.385421
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T08:22:17.706611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.170824
5-th percentile35.192358
Q135.2332
median35.269761
Q335.304832
95-th percentile35.347358
Maximum35.385421
Range0.21459692
Interquartile range (IQR)0.07163149

Descriptive statistics

Standard deviation0.047896708
Coefficient of variation (CV)0.0013579928
Kurtosis-0.66874587
Mean35.270223
Median Absolute Deviation (MAD)0.03530215
Skewness0.10390436
Sum10052.014
Variance0.0022940946
MonotonicityNot monotonic
2023-12-11T08:22:17.859771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.3100276 2
 
0.7%
35.26928989 1
 
0.4%
35.2393801 1
 
0.4%
35.23596506 1
 
0.4%
35.23185196 1
 
0.4%
35.23034028 1
 
0.4%
35.23717639 1
 
0.4%
35.24478087 1
 
0.4%
35.23824113 1
 
0.4%
35.22913085 1
 
0.4%
Other values (274) 274
96.1%
ValueCountFrequency (%)
35.17082407 1
0.4%
35.17281905 1
0.4%
35.17564494 1
0.4%
35.17643535 1
0.4%
35.17684104 1
0.4%
35.17770166 1
0.4%
35.17783281 1
0.4%
35.18049516 1
0.4%
35.18346691 1
0.4%
35.18437342 1
0.4%
ValueCountFrequency (%)
35.38542099 1
0.4%
35.38462032 1
0.4%
35.38007793 1
0.4%
35.37454127 1
0.4%
35.37357762 1
0.4%
35.37224664 1
0.4%
35.36884805 1
0.4%
35.36638047 1
0.4%
35.36387641 1
0.4%
35.35791761 1
0.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct283
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.83413
Minimum128.70835
Maximum129.00339
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-11T08:22:18.009235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.70835
5-th percentile128.72789
Q1128.76787
median128.82637
Q3128.87333
95-th percentile128.98084
Maximum129.00339
Range0.295039
Interquartile range (IQR)0.1054532

Descriptive statistics

Standard deviation0.076907056
Coefficient of variation (CV)0.00059694629
Kurtosis-0.61627382
Mean128.83413
Median Absolute Deviation (MAD)0.0527511
Skewness0.48216255
Sum36717.727
Variance0.0059146952
MonotonicityNot monotonic
2023-12-11T08:22:18.196282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.9613366 2
 
0.7%
128.8342863 2
 
0.7%
128.712803 1
 
0.4%
128.9451711 1
 
0.4%
128.9730409 1
 
0.4%
128.9678953 1
 
0.4%
128.9525131 1
 
0.4%
128.949911 1
 
0.4%
128.9415632 1
 
0.4%
128.9469257 1
 
0.4%
Other values (273) 273
95.8%
ValueCountFrequency (%)
128.7083516 1
0.4%
128.7088155 1
0.4%
128.7096608 1
0.4%
128.7103915 1
0.4%
128.712803 1
0.4%
128.7137983 1
0.4%
128.7167501 1
0.4%
128.7189576 1
0.4%
128.7197452 1
0.4%
128.7206762 1
0.4%
ValueCountFrequency (%)
129.0033906 1
0.4%
128.9999375 1
0.4%
128.9999185 1
0.4%
128.9968041 1
0.4%
128.9965412 1
0.4%
128.99618 1
0.4%
128.9932953 1
0.4%
128.9925431 1
0.4%
128.9924075 1
0.4%
128.9906002 1
0.4%

Interactions

2023-12-11T08:22:13.629602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:22:13.177039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:22:13.402204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:22:13.731044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:22:13.251405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:22:13.480568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:22:13.812852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:22:13.323293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:22:13.543545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:22:18.284701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동마을명(리_통)위도경도
연번1.0000.9430.9970.8610.936
읍면동0.9431.0001.0000.8360.907
마을명(리_통)0.9971.0001.0000.9740.985
위도0.8610.8360.9741.0000.625
경도0.9360.9070.9850.6251.000
2023-12-11T08:22:18.364070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도읍면동
연번1.000-0.3880.7280.753
위도-0.3881.000-0.1610.517
경도0.728-0.1611.0000.654
읍면동0.7530.5170.6541.000

Missing values

2023-12-11T08:22:13.932380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:22:14.051237image/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

연번읍면동마을명(리_통)회관명지번주소도로명주소위도경도
01진영읍우동리서천경상남도 김해시 진영읍 우동리 826-56경상남도 김해시 진영읍 하계로96번안길 108-1335.26929128.712803
12진영읍우동리우동경상남도 김해시 진영읍 우동리 165-20경상남도 김해시 진영읍 하계로96번길 13335.275617128.720676
23진영읍하계리오척경상남도 김해시 진영읍 하계리 산90-1경상남도 김해시 진영읍 하계로138번길 125-1035.279333128.727799
34진영읍하계리오척2경상남도 김해시 진영읍 하계리 539-2경상남도 김해시 진영읍 하계로138번길 14435.278072128.728278
45진영읍하계리하계경상남도 김해시 진영읍 하계리 279-7경상남도 김해시 진영읍 하계로 26035.28748128.730883
56진영읍방동리방동경상남도 김해시 진영읍 방동리 84-5경상남도 김해시 진영읍 하계로 15535.286217128.719745
67진영읍방동리동산경상남도 김해시 진영읍 방동리 289-3경상남도 김해시 진영읍 하계로79번길 1435.285523128.713798
78진영읍사산리사산경상남도 김해시 진영읍 사산리 360-8경상남도 김해시 진영읍 하계로94번길 8735.280058128.708815
89진영읍좌곤리좌곤경상남도 김해시 진영읍 좌곤리 372-3경상남도 김해시 진영읍 김해대로68번길 835.293977128.708352
910진영읍좌곤리광대현경상남도 김해시 진영읍 좌곤리 39경상남도 김해시 진영읍 김해대로157번길 1135.302329128.709661
연번읍면동마을명(리_통)회관명지번주소도로명주소위도경도
275276내외동내동우암경상남도 김해시 내동 628경상남도 김해시 김해시 금관대로1341번길 235.242995128.864936
276277내외동외동무접경상남도 김해시 외동 321-6경상남도 김해시 김해시 분성로196번길 435.229698128.868741
277278북부동대성동대성1구(1통)경상남도 김해시 대성동 269-7 대성1구경로당경상남도 김해시 가락로134-135.238444128.880491
278279북부동대성동대성2구(7통)경상남도 김해시 대성동 132-2경상남도 김해시 구지로13435.238702128.877926
279280북부동구산동구산1통(11통)경상남도 김해시 구산동 93-3경상남도 김해시 가락로18435.242344128.877845
280281북부동구산동구산2통(31통)경상남도 김해시 구산동 594경상남도 김해시 가락로322번길1235.253691128.872758
281282북부동구산동구산새동네(22통)경상남도 김해시 구산동 305-10경상남도 김해시 구산로42번길19-1535.246953128.873326
282283북부동삼계동곡내(70통)경상남도 김해시 삼계동 1262-1경상남도 김해시 안곡로8135.273193128.85295
283284북부동삼계동감분(70통)경상남도 김해시 삼계동 1121-13경상남도 김해시 안곡로18번길235.271239128.858956
284285북부동삼계동화정마을(44통)경상남도 김해시 삼계동 1468-5경상남도 김해시 해반천로168번길10-1735.26237128.868388