Overview

Dataset statistics

Number of variables10
Number of observations240
Missing cells10
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.6 KiB
Average record size in memory83.5 B

Variable types

Categorical3
Text3
Numeric3
DateTime1

Dataset

Description광주광역시 서구 경로당의 경로당명, 주소, 면적, 회원수, 전화번호, 주택유형, 소유, 설치일자 등에 대한 정보입니다.
Author광주광역시 서구
URLhttps://www.data.go.kr/data/15033516/fileData.do

Alerts

우편번호 is highly overall correlated with 주택유형High correlation
주택유형 is highly overall correlated with 우편번호 and 1 other fieldsHigh correlation
소유 is highly overall correlated with 주택유형High correlation
전화번호 has 10 (4.2%) missing valuesMissing
경로당명 has unique valuesUnique

Reproduction

Analysis started2024-01-06 13:02:23.876674
Analysis finished2024-01-06 13:02:28.623953
Duration4.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동
Categorical

Distinct18
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
서창동
23 
상무2동
22 
풍암동
20 
금호1동
20 
화정4동
16 
Other values (13)
139 

Length

Max length4
Median length4
Mean length3.5625
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서창동 23
 
9.6%
상무2동 22
 
9.2%
풍암동 20
 
8.3%
금호1동 20
 
8.3%
화정4동 16
 
6.7%
치평동 16
 
6.7%
금호2동 15
 
6.2%
화정2동 15
 
6.2%
화정1동 14
 
5.8%
유덕동 13
 
5.4%
Other values (8) 66
27.5%

Length

2024-01-06T13:02:29.141802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서창동 23
 
9.6%
상무2동 22
 
9.2%
풍암동 20
 
8.3%
금호1동 20
 
8.3%
화정4동 16
 
6.7%
치평동 16
 
6.7%
금호2동 15
 
6.2%
화정2동 15
 
6.2%
화정1동 14
 
5.8%
상무1동 13
 
5.4%
Other values (8) 66
27.5%

경로당명
Text

UNIQUE 

Distinct240
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-01-06T13:02:29.986373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length8.3375
Min length5

Characters and Unicode

Total characters2001
Distinct characters222
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique240 ?
Unique (%)100.0%

Sample

1st row광암경로당
2nd row광천e편한세상아파트경로당
3rd row광천경로당
4th row남성경로당
5th row영락경로당
ValueCountFrequency (%)
광암경로당 1
 
0.4%
상무금호대우아파트경로당 1
 
0.4%
내방마을주공경로당 1
 
0.4%
주은모아경로당 1
 
0.4%
중흥1단지경로당 1
 
0.4%
중흥2단지경로당 1
 
0.4%
한국아파트경로당(치평 1
 
0.4%
해광한신경로당 1
 
0.4%
오색경로당 1
 
0.4%
금당정경로당 1
 
0.4%
Other values (232) 232
95.9%
2024-01-06T13:02:31.796050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
당 244
 
12.2%
로 243
 
12.1%
경 240
 
12.0%
아 83
 
4.1%
파 78
 
3.9%
트 75
 
3.7%
호 36
 
1.8%
금 27
 
1.3%
( 24
 
1.2%
) 24
 
1.2%
Other values (212) 927
46.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1884
94.2%
Decimal Number 53
 
2.6%
Open Punctuation 24
 
1.2%
Close Punctuation 24
 
1.2%
Uppercase Letter 9
 
0.4%
Space Separator 2
 
0.1%
Lowercase Letter 2
 
0.1%
Other Punctuation 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
당 244
 
13.0%
로 243
 
12.9%
경 240
 
12.7%
아 83
 
4.4%
파 78
 
4.1%
트 75
 
4.0%
호 36
 
1.9%
금 27
 
1.4%
마 23
 
1.2%
화 22
 
1.2%
Other values (191) 813
43.2%
Decimal Number
ValueCountFrequency (%)
1 19
35.8%
2 17
32.1%
3 8
15.1%
4 4
 
7.5%
5 2
 
3.8%
0 1
 
1.9%
8 1
 
1.9%
6 1
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
S 3
33.3%
K 2
22.2%
L 1
 
11.1%
H 1
 
11.1%
G 1
 
11.1%
E 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
＆ 1
50.0%
. 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1884
94.2%
Common 106
 
5.3%
Latin 11
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
당 244
 
13.0%
로 243
 
12.9%
경 240
 
12.7%
아 83
 
4.4%
파 78
 
4.1%
트 75
 
4.0%
호 36
 
1.9%
금 27
 
1.4%
마 23
 
1.2%
화 22
 
1.2%
Other values (191) 813
43.2%
Common
ValueCountFrequency (%)
( 24
22.6%
) 24
22.6%
1 19
17.9%
2 17
16.0%
3 8
 
7.5%
4 4
 
3.8%
2
 
1.9%
5 2
 
1.9%
＆ 1
 
0.9%
0 1
 
0.9%
Other values (4) 4
 
3.8%
Latin
ValueCountFrequency (%)
S 3
27.3%
K 2
18.2%
e 2
18.2%
L 1
 
9.1%
H 1
 
9.1%
G 1
 
9.1%
E 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1884
94.2%
ASCII 116
 
5.8%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
당 244
 
13.0%
로 243
 
12.9%
경 240
 
12.7%
아 83
 
4.4%
파 78
 
4.1%
트 75
 
4.0%
호 36
 
1.9%
금 27
 
1.4%
마 23
 
1.2%
화 22
 
1.2%
Other values (191) 813
43.2%
ASCII
ValueCountFrequency (%)
( 24
20.7%
) 24
20.7%
1 19
16.4%
2 17
14.7%
3 8
 
6.9%
4 4
 
3.4%
S 3
 
2.6%
2
 
1.7%
5 2
 
1.7%
K 2
 
1.7%
Other values (10) 11
9.5%
None
ValueCountFrequency (%)
＆ 1
100.0%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct131
Distinct (%)54.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61864.579
Minimum32021
Maximum62078
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-06T13:02:32.432436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32021
5-th percentile61905
Q161942.5
median61995
Q362030
95-th percentile62070
Maximum62078
Range30057
Interquartile range (IQR)87.5

Descriptive statistics

Standard deviation1935.1511
Coefficient of variation (CV)0.031280437
Kurtosis239.65052
Mean61864.579
Median Absolute Deviation (MAD)40
Skewness-15.475083
Sum14847499
Variance3744809.7
MonotonicityNot monotonic
2024-01-06T13:02:33.106242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
61998 6
 
2.5%
62077 5
 
2.1%
61967 4
 
1.7%
61997 4
 
1.7%
61987 4
 
1.7%
61918 4
 
1.7%
62010 4
 
1.7%
61925 4
 
1.7%
62030 4
 
1.7%
62028 4
 
1.7%
Other values (121) 197
82.1%
ValueCountFrequency (%)
32021 1
 
0.4%
61900 2
0.8%
61901 2
0.8%
61902 3
1.2%
61903 2
0.8%
61904 1
 
0.4%
61905 3
1.2%
61906 2
0.8%
61907 1
 
0.4%
61908 2
0.8%
ValueCountFrequency (%)
62078 3
1.2%
62077 5
2.1%
62076 3
1.2%
62070 2
 
0.8%
62069 1
 
0.4%
62068 1
 
0.4%
62067 2
 
0.8%
62066 3
1.2%
62065 2
 
0.8%
62064 1
 
0.4%

주소
Text

Distinct238
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-01-06T13:02:33.798474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length29
Mean length19.35
Min length14

Characters and Unicode

Total characters4644
Distinct characters136
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique236 ?
Unique (%)98.3%

Sample

1st row광주광역시 서구 천변좌하로584번길 11
2nd row광주광역시 서구 화운로 278
3rd row광주광역시 서구 죽봉대로120번길 8
4th row광주광역시 서구 화운로303번길 19-2
5th row광주광역시 서구 광천1길 9
ValueCountFrequency (%)
광주광역시 240
24.4%
서구 240
24.4%
풍암순환로 9
 
0.9%
화정로 9
 
0.9%
11 6
 
0.6%
10 6
 
0.6%
9 6
 
0.6%
19 5
 
0.5%
20 5
 
0.5%
12 5
 
0.5%
Other values (317) 451
45.9%
2024-01-06T13:02:35.472461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
806
17.4%
광 487
 
10.5%
서 243
 
5.2%
주 243
 
5.2%
시 242
 
5.2%
구 241
 
5.2%
역 240
 
5.2%
1 230
 
5.0%
로 211
 
4.5%
길 140
 
3.0%
Other values (126) 1561
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2833
61.0%
Decimal Number 917
 
19.7%
Space Separator 806
 
17.4%
Dash Punctuation 57
 
1.2%
Open Punctuation 10
 
0.2%
Close Punctuation 10
 
0.2%
Other Punctuation 9
 
0.2%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 487
17.2%
서 243
 
8.6%
주 243
 
8.6%
시 242
 
8.5%
구 241
 
8.5%
역 240
 
8.5%
로 211
 
7.4%
길 140
 
4.9%
번 110
 
3.9%
화 67
 
2.4%
Other values (109) 609
21.5%
Decimal Number
ValueCountFrequency (%)
1 230
25.1%
2 114
12.4%
5 90
 
9.8%
3 87
 
9.5%
4 86
 
9.4%
0 75
 
8.2%
9 64
 
7.0%
6 62
 
6.8%
8 55
 
6.0%
7 54
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
806
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2833
61.0%
Common 1809
39.0%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 487
17.2%
서 243
 
8.6%
주 243
 
8.6%
시 242
 
8.5%
구 241
 
8.5%
역 240
 
8.5%
로 211
 
7.4%
길 140
 
4.9%
번 110
 
3.9%
화 67
 
2.4%
Other values (109) 609
21.5%
Common
ValueCountFrequency (%)
806
44.6%
1 230
 
12.7%
2 114
 
6.3%
5 90
 
5.0%
3 87
 
4.8%
4 86
 
4.8%
0 75
 
4.1%
9 64
 
3.5%
6 62
 
3.4%
- 57
 
3.2%
Other values (5) 138
 
7.6%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2833
61.0%
ASCII 1811
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
806
44.5%
1 230
 
12.7%
2 114
 
6.3%
5 90
 
5.0%
3 87
 
4.8%
4 86
 
4.7%
0 75
 
4.1%
9 64
 
3.5%
6 62
 
3.4%
- 57
 
3.1%
Other values (7) 140
 
7.7%
Hangul
ValueCountFrequency (%)
광 487
17.2%
서 243
 
8.6%
주 243
 
8.6%
시 242
 
8.5%
구 241
 
8.5%
역 240
 
8.5%
로 211
 
7.4%
길 140
 
4.9%
번 110
 
3.9%
화 67
 
2.4%
Other values (109) 609
21.5%

면적(제곱미터)
Real number (ℝ)

Distinct197
Distinct (%)82.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.37265
Minimum23
Maximum273.38
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-06T13:02:36.109295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile48.1545
Q168.2425
median90.725
Q3126.8925
95-th percentile175.546
Maximum273.38
Range250.38
Interquartile range (IQR)58.65

Descriptive statistics

Standard deviation43.672623
Coefficient of variation (CV)0.43510479
Kurtosis1.4932258
Mean100.37265
Median Absolute Deviation (MAD)26.585
Skewness1.0528705
Sum24089.437
Variance1907.298
MonotonicityNot monotonic
2024-01-06T13:02:36.675091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90.0 5
 
2.1%
59.0 4
 
1.7%
99.0 4
 
1.7%
80.0 4
 
1.7%
144.0 3
 
1.2%
63.0 3
 
1.2%
105.6 3
 
1.2%
49.0 3
 
1.2%
132.0 3
 
1.2%
66.0 3
 
1.2%
Other values (187) 205
85.4%
ValueCountFrequency (%)
23.0 1
0.4%
28.42 1
0.4%
30.8 1
0.4%
31.5 2
0.8%
33.1 1
0.4%
35.28 1
0.4%
36.0 1
0.4%
37.7 1
0.4%
42.0 1
0.4%
44.0 1
0.4%
ValueCountFrequency (%)
273.38 1
0.4%
264.16 1
0.4%
238.28 1
0.4%
233.12 1
0.4%
226.0 1
0.4%
202.0 1
0.4%
201.11 1
0.4%
194.75 1
0.4%
190.49 1
0.4%
189.88 1
0.4%

회원수
Real number (ℝ)

Distinct49
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.025
Minimum20
Maximum217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-01-06T13:02:37.250523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q125
median32
Q341.25
95-th percentile62.05
Maximum217
Range197
Interquartile range (IQR)16.25

Descriptive statistics

Standard deviation18.830654
Coefficient of variation (CV)0.52271072
Kurtosis38.112322
Mean36.025
Median Absolute Deviation (MAD)8
Skewness4.734902
Sum8646
Variance354.59351
MonotonicityNot monotonic
2024-01-06T13:02:37.886283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
20 14
 
5.8%
22 14
 
5.8%
21 12
 
5.0%
30 12
 
5.0%
32 12
 
5.0%
24 11
 
4.6%
28 11
 
4.6%
25 10
 
4.2%
27 10
 
4.2%
23 8
 
3.3%
Other values (39) 126
52.5%
ValueCountFrequency (%)
20 14
5.8%
21 12
5.0%
22 14
5.8%
23 8
3.3%
24 11
4.6%
25 10
4.2%
26 8
3.3%
27 10
4.2%
28 11
4.6%
29 4
 
1.7%
ValueCountFrequency (%)
217 1
0.4%
137 1
0.4%
85 1
0.4%
82 1
0.4%
78 2
0.8%
72 2
0.8%
67 1
0.4%
64 2
0.8%
63 1
0.4%
62 1
0.4%

전화번호
Text

MISSING 

Distinct228
Distinct (%)99.1%
Missing10
Missing (%)4.2%
Memory size2.0 KiB
2024-01-06T13:02:38.753812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2760
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

Unique226 ?
Unique (%)98.3%

Sample

1st row062-385-0224
2nd row062-367-1257
3rd row062-369-2166
4th row062-374-2676
5th row062-368-1785
ValueCountFrequency (%)
062-371-5301 2
 
0.9%
062-521-8745 2
 
0.9%
062-682-1168 1
 
0.4%
062-456-5053 1
 
0.4%
062-456-8055 1
 
0.4%
062-682-9920 1
 
0.4%
062-385-0224 1
 
0.4%
062-431-8009 1
 
0.4%
062-371-3015 1
 
0.4%
062-372-4705 1
 
0.4%
Other values (218) 218
94.8%
2024-01-06T13:02:40.290133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 460
16.7%
6 408
14.8%
0 364
13.2%
2 356
12.9%
3 330
12.0%
7 174
 
6.3%
1 156
 
5.7%
4 145
 
5.3%
5 141
 
5.1%
8 136
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2300
83.3%
Dash Punctuation 460
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 408
17.7%
0 364
15.8%
2 356
15.5%
3 330
14.3%
7 174
7.6%
1 156
 
6.8%
4 145
 
6.3%
5 141
 
6.1%
8 136
 
5.9%
9 90
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 460
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2760
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 460
16.7%
6 408
14.8%
0 364
13.2%
2 356
12.9%
3 330
12.0%
7 174
 
6.3%
1 156
 
5.7%
4 145
 
5.3%
5 141
 
5.1%
8 136
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 460
16.7%
6 408
14.8%
0 364
13.2%
2 356
12.9%
3 330
12.0%
7 174
 
6.3%
1 156
 
5.7%
4 145
 
5.3%
5 141
 
5.1%
8 136
 
4.9%

주택유형
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
공동주택
147 
단독주택
80 
상가
 
10
다세대주택
 
2
연립주택
 
1

Length

Max length5
Median length4
Mean length3.925
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
공동주택 147
61.3%
단독주택 80
33.3%
상가 10
 
4.2%
다세대주택 2
 
0.8%
연립주택 1
 
0.4%

Length

2024-01-06T13:02:40.952117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T13:02:41.365702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동주택 147
61.3%
단독주택 80
33.3%
상가 10
 
4.2%
다세대주택 2
 
0.8%
연립주택 1
 
0.4%

소유
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
아파트
146 
구소유
70 
마을
 
14
임차
 
10

Length

Max length3
Median length3
Mean length2.9
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row구소유
2nd row아파트
3rd row구소유
4th row마을
5th row마을

Common Values

ValueCountFrequency (%)
아파트 146
60.8%
구소유 70
29.2%
마을 14
 
5.8%
임차 10
 
4.2%

Length

2024-01-06T13:02:41.760659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-06T13:02:42.158260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아파트 146
60.8%
구소유 70
29.2%
마을 14
 
5.8%
임차 10
 
4.2%

설치일자
Date

Distinct124
Distinct (%)51.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum1983-01-01 00:00:00
Maximum2023-11-16 00:00:00
2024-01-06T13:02:42.584540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:02:43.010631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-01-06T13:02:26.823269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:02:25.120991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:02:25.903847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:02:27.119390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:02:25.376555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:02:26.240638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:02:27.376935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:02:25.627196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-06T13:02:26.554672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-06T13:02:43.299662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동우편번호면적(제곱미터)회원수주택유형소유
행정동1.000NaN0.2480.4420.5840.630
우편번호NaN1.000NaNNaNNaNNaN
면적(제곱미터)0.248NaN1.0000.5940.0000.000
회원수0.442NaN0.5941.0000.2270.264
주택유형0.584NaN0.0000.2271.0000.714
소유0.630NaN0.0000.2640.7141.000
2024-01-06T13:02:43.610099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소유주택유형행정동
소유1.0000.6510.386
주택유형0.6511.0000.335
행정동0.3860.3351.000
2024-01-06T13:02:43.865005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호면적(제곱미터)회원수행정동주택유형소유
우편번호1.000-0.016-0.1420.0000.6950.000
면적(제곱미터)-0.0161.0000.1080.0940.0000.000
회원수-0.1420.1081.0000.1860.1550.172
행정동0.0000.0940.1861.0000.3350.386
주택유형0.6950.0000.1550.3351.0000.651
소유0.0000.0000.1720.3860.6511.000

Missing values

2024-01-06T13:02:27.797297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-06T13:02:28.370161image/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

행정동경로당명우편번호주소면적(제곱미터)회원수전화번호주택유형소유설치일자
0광천동광암경로당61908광주광역시 서구 천변좌하로584번길 1185.1436062-385-0224단독주택구소유2009-09-23
1광천동광천e편한세상아파트경로당61916광주광역시 서구 화운로 27880.055062-367-1257단독주택아파트2010-06-28
2광천동광천경로당61917광주광역시 서구 죽봉대로120번길 885.1425062-369-2166단독주택구소유1998-03-07
3광천동남성경로당61908광주광역시 서구 화운로303번길 19-280.031062-374-2676단독주택마을1985-01-01
4광천동영락경로당61915광주광역시 서구 광천1길 9169.3122062-368-1785단독주택마을1990-01-01
5광천동인동경로당61914광주광역시 서구 광천효광길 25, B-10859.1625062-351-2288단독주택구소유2011-04-11
6광천동인화경로당61913광주광역시 서구 광천효광길 756.4331062-366-6615단독주택구소유2004-07-23
7금호1동금부마을한국아파트경로당62036광주광역시 서구 금화로115번길 968.0428062-381-1899공동주택아파트1999-01-01
8금호1동금호3차호반경로당62035광주광역시 서구 금화로149번길 1166.0622062-454-7725공동주택아파트2003-07-24
9금호1동금호경로당62006광주광역시 서구 금화로73번길 32102.8934062-371-3448단독주택구소유2009-09-23
행정동경로당명우편번호주소면적(제곱미터)회원수전화번호주택유형소유설치일자
230화정2동유니버시아드힐스테이트3단지경로당62046광주광역시 서구 화운로 24273.3850062-361-1130공동주택아파트2017-01-18
231화정2동유니버시아드힐스테이트1단지경로당61982광주광역시 서구 화운로 94190.4935062-369-9411공동주택아파트2017-06-16
232농성1동농성빛여울채경로당61921광주광역시 서구 월산로 164-3(101동 1층)111.3720062-361-2233공동주택아파트2018-04-26
233금호2동아델리움＆로제비앙아파트경로당62011광주광역시 서구 화개중앙로87번길 15110.027062-654-7734공동주택아파트2018-11-16
234서창동상무양우내안애경로당62000광주광역시 서구 백석길 22-14114.1825<NA>공동주택아파트2021-05-17
235서창동희망가아파트경로당61998광주광역시 서구 백석길 1950.25750<NA>공동주택아파트2021-12-28
236유덕동광천모아엘가경로당61906광주광역시 서구 칠성로89107.3624<NA>공동주택아파트2023-07-04
237상무1동상무힐스테이트아파트경로당61969광주광역시 서구 상무대로911번길42100.053<NA>공동주택아파트2023-07-10
238화정4동더샵염주센트럴파크아파트경로당62027광주광역시 서구 월드컵4강로 27264.1664<NA>공동주택아파트2023-09-25
239금호1동대광로제비앙아파트경로당62004광주광역시 서구 금호심곡길21112.023<NA>공동주택아파트2023-11-16