Overview

Dataset statistics

Number of variables10
Number of observations97
Missing cells6
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.1 KiB
Average record size in memory85.4 B

Variable types

Numeric4
Categorical2
Text3
DateTime1

Dataset

Description서울특별시_ 광진구_경로당 현황에 관련하여 연번, 동, 형태, 경로당명, 전화번호, 주소 등의 정보를 제공합니다.
Author서울특별시 광진구
URLhttps://www.data.go.kr/data/15041530/fileData.do

Alerts

연번 is highly overall correlated with 행정동High correlation
회원수(남) is highly overall correlated with 회원수(총원)High correlation
회원수(여) is highly overall correlated with 회원수(총원)High correlation
회원수(총원) is highly overall correlated with 회원수(남) and 1 other fieldsHigh correlation
행정동 is highly overall correlated with 연번High correlation
전화번호 has 6 (6.2%) missing valuesMissing
연번 has unique valuesUnique
경로당명 has unique valuesUnique
주소 has unique valuesUnique
회원수(남) has 19 (19.6%) zerosZeros
회원수(여) has 7 (7.2%) zerosZeros
회원수(총원) has 4 (4.1%) zerosZeros

Reproduction

Analysis started2024-04-06 08:13:42.962209
Analysis finished2024-04-06 08:13:47.043775
Duration4.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49
Minimum1
Maximum97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2024-04-06T17:13:47.201641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.8
Q125
median49
Q373
95-th percentile92.2
Maximum97
Range96
Interquartile range (IQR)48

Descriptive statistics

Standard deviation28.145456
Coefficient of variation (CV)0.57439705
Kurtosis-1.2
Mean49
Median Absolute Deviation (MAD)24
Skewness0
Sum4753
Variance792.16667
MonotonicityStrictly increasing
2024-04-06T17:13:47.466632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
74 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
67 1
 
1.0%
66 1
 
1.0%
65 1
 
1.0%
Other values (87) 87
89.7%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%
90 1
1.0%
89 1
1.0%
88 1
1.0%

행정동
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)15.5%
Missing0
Missing (%)0.0%
Memory size908.0 B
광장동
21 
자양3동
17 
자양2동
11 
구의3동
9 
자양4동
7 
Other values (10)
32 

Length

Max length4
Median length4
Mean length3.6804124
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row중곡1동
2nd row중곡1동
3rd row중곡2동
4th row중곡2동
5th row중곡3동

Common Values

ValueCountFrequency (%)
광장동 21
21.6%
자양3동 17
17.5%
자양2동 11
11.3%
구의3동 9
9.3%
자양4동 7
 
7.2%
자양1동 5
 
5.2%
군자동 5
 
5.2%
중곡4동 4
 
4.1%
구의1동 4
 
4.1%
구의2동 4
 
4.1%
Other values (5) 10
10.3%

Length

2024-04-06T17:13:47.763448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
광장동 21
21.6%
자양3동 17
17.5%
자양2동 11
11.3%
구의3동 9
9.3%
자양4동 7
 
7.2%
자양1동 5
 
5.2%
군자동 5
 
5.2%
중곡4동 4
 
4.1%
구의1동 4
 
4.1%
구의2동 4
 
4.1%
Other values (5) 10
10.3%

형태
Categorical

Distinct4
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size908.0 B
사립
55 
구립
40 
구립
 
1
사립
 
1

Length

Max length3
Median length2
Mean length2.0206186
Min length2

Unique

Unique2 ?
Unique (%)2.1%

Sample

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

Common Values

ValueCountFrequency (%)
사립 55
56.7%
구립 40
41.2%
구립 1
 
1.0%
사립 1
 
1.0%

Length

2024-04-06T17:13:47.996668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:13:48.185871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립 56
57.7%
구립 41
42.3%

경로당명
Text

UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
2024-04-06T17:13:48.664362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.6494845
Min length2

Characters and Unicode

Total characters451
Distinct characters115
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)100.0%

Sample

1st row중곡1동 제1
2nd row중곡1동 제2
3rd row한마음
4th row장수
5th row용마
ValueCountFrequency (%)
자양4동 3
 
2.9%
중곡1동 2
 
1.9%
화양동 2
 
1.9%
제1 2
 
1.9%
제2 2
 
1.9%
자양2현대3차 1
 
1.0%
우성1차 1
 
1.0%
마실 1
 
1.0%
자양3동 1
 
1.0%
신양 1
 
1.0%
Other values (87) 87
84.5%
2024-04-06T17:13:49.478096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
차 25
 
5.5%
대 23
 
5.1%
양 23
 
5.1%
동 22
 
4.9%
현 20
 
4.4%
자 19
 
4.2%
2 17
 
3.8%
장 15
 
3.3%
광 14
 
3.1%
1 14
 
3.1%
Other values (105) 259
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 389
86.3%
Decimal Number 53
 
11.8%
Space Separator 7
 
1.6%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
차 25
 
6.4%
대 23
 
5.9%
양 23
 
5.9%
동 22
 
5.7%
현 20
 
5.1%
자 19
 
4.9%
장 15
 
3.9%
광 14
 
3.6%
구 11
 
2.8%
의 11
 
2.8%
Other values (92) 206
53.0%
Decimal Number
ValueCountFrequency (%)
2 17
32.1%
1 14
26.4%
3 6
 
11.3%
4 5
 
9.4%
9 2
 
3.8%
5 2
 
3.8%
0 2
 
3.8%
8 2
 
3.8%
7 2
 
3.8%
6 1
 
1.9%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 389
86.3%
Common 62
 
13.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
차 25
 
6.4%
대 23
 
5.9%
양 23
 
5.9%
동 22
 
5.7%
현 20
 
5.1%
자 19
 
4.9%
장 15
 
3.9%
광 14
 
3.6%
구 11
 
2.8%
의 11
 
2.8%
Other values (92) 206
53.0%
Common
ValueCountFrequency (%)
2 17
27.4%
1 14
22.6%
7
11.3%
3 6
 
9.7%
4 5
 
8.1%
9 2
 
3.2%
5 2
 
3.2%
0 2
 
3.2%
8 2
 
3.2%
7 2
 
3.2%
Other values (3) 3
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 389
86.3%
ASCII 62
 
13.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
차 25
 
6.4%
대 23
 
5.9%
양 23
 
5.9%
동 22
 
5.7%
현 20
 
5.1%
자 19
 
4.9%
장 15
 
3.9%
광 14
 
3.6%
구 11
 
2.8%
의 11
 
2.8%
Other values (92) 206
53.0%
ASCII
ValueCountFrequency (%)
2 17
27.4%
1 14
22.6%
7
11.3%
3 6
 
9.7%
4 5
 
8.1%
9 2
 
3.2%
5 2
 
3.2%
0 2
 
3.2%
8 2
 
3.2%
7 2
 
3.2%
Other values (3) 3
 
4.8%

전화번호
Text

MISSING 

Distinct91
Distinct (%)100.0%
Missing6
Missing (%)6.2%
Memory size908.0 B
2024-04-06T17:13:50.020623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length11.208791
Min length11

Characters and Unicode

Total characters1020
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)100.0%

Sample

1st row02-467-0014
2nd row02-465-2104
3rd row02-444-0652
4th row02-454-3811
5th row02-466-1020
ValueCountFrequency (%)
02-446-9039 1
 
1.1%
02-444-1015 1
 
1.1%
02-446-1800 1
 
1.1%
02-456-3247 1
 
1.1%
02-446-2161 1
 
1.1%
02-456-2864 1
 
1.1%
02-446-5563 1
 
1.1%
02-455-7270 1
 
1.1%
02-444-9243 1
 
1.1%
02-444-5366 1
 
1.1%
Other values (81) 81
89.0%
2024-04-06T17:13:51.018237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 182
17.8%
4 154
15.1%
2 150
14.7%
0 135
13.2%
5 79
7.7%
3 70
 
6.9%
6 64
 
6.3%
1 48
 
4.7%
7 47
 
4.6%
9 45
 
4.4%
Other values (2) 46
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 836
82.0%
Dash Punctuation 182
 
17.8%
Space Separator 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 154
18.4%
2 150
17.9%
0 135
16.1%
5 79
9.4%
3 70
8.4%
6 64
7.7%
1 48
 
5.7%
7 47
 
5.6%
9 45
 
5.4%
8 44
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 182
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 182
17.8%
4 154
15.1%
2 150
14.7%
0 135
13.2%
5 79
7.7%
3 70
 
6.9%
6 64
 
6.3%
1 48
 
4.7%
7 47
 
4.6%
9 45
 
4.4%
Other values (2) 46
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 182
17.8%
4 154
15.1%
2 150
14.7%
0 135
13.2%
5 79
7.7%
3 70
 
6.9%
6 64
 
6.3%
1 48
 
4.7%
7 47
 
4.6%
9 45
 
4.4%
Other values (2) 46
 
4.5%

주소
Text

UNIQUE 

Distinct97
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
2024-04-06T17:13:51.537552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length42
Mean length36.773196
Min length30

Characters and Unicode

Total characters3567
Distinct characters137
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

Unique97 ?
Unique (%)100.0%

Sample

1st row서울특별시 광진구 긴고랑로5길 10(중곡동, 중곡1동 제1경로당)
2nd row서울특별시 광진구 긴고랑로8길 51(중곡동, 중곡1동 제2경로당)
3rd row서울특별시 광진구 긴고랑로22길 39-4(중곡동, 한마음경로당)
4th row서울특별시 광진구 긴고랑로31길 44(중곡동, 장수경로당)
5th row서울특별시 광진구 용마산로31길 38-8 (중곡동, 용마경로당)
ValueCountFrequency (%)
서울특별시 97
 
15.1%
광진구 97
 
15.1%
경로당 65
 
10.1%
자양동 35
 
5.5%
광장동 18
 
2.8%
구의동 16
 
2.5%
아차산로 11
 
1.7%
중곡동 6
 
0.9%
군자동 5
 
0.8%
39 4
 
0.6%
Other values (243) 288
44.9%
2024-04-06T17:13:52.444671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
545
 
15.3%
로 194
 
5.4%
광 131
 
3.7%
동 130
 
3.6%
구 127
 
3.6%
, 100
 
2.8%
시 99
 
2.8%
( 98
 
2.7%
진 98
 
2.7%
경 98
 
2.7%
Other values (127) 1947
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2292
64.3%
Space Separator 545
 
15.3%
Decimal Number 415
 
11.6%
Other Punctuation 100
 
2.8%
Open Punctuation 98
 
2.7%
Close Punctuation 98
 
2.7%
Dash Punctuation 13
 
0.4%
Uppercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 194
 
8.5%
광 131
 
5.7%
동 130
 
5.7%
구 127
 
5.5%
시 99
 
4.3%
진 98
 
4.3%
경 98
 
4.3%
서 97
 
4.2%
특 97
 
4.2%
별 97
 
4.2%
Other values (109) 1124
49.0%
Decimal Number
ValueCountFrequency (%)
1 62
14.9%
2 62
14.9%
3 58
14.0%
5 48
11.6%
4 41
9.9%
6 36
8.7%
7 36
8.7%
9 27
6.5%
0 23
 
5.5%
8 22
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
P 2
33.3%
T 2
33.3%
A 2
33.3%
Space Separator
ValueCountFrequency (%)
545
100.0%
Other Punctuation
ValueCountFrequency (%)
, 100
100.0%
Open Punctuation
ValueCountFrequency (%)
( 98
100.0%
Close Punctuation
ValueCountFrequency (%)
) 98
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2292
64.3%
Common 1269
35.6%
Latin 6
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 194
 
8.5%
광 131
 
5.7%
동 130
 
5.7%
구 127
 
5.5%
시 99
 
4.3%
진 98
 
4.3%
경 98
 
4.3%
서 97
 
4.2%
특 97
 
4.2%
별 97
 
4.2%
Other values (109) 1124
49.0%
Common
ValueCountFrequency (%)
545
42.9%
, 100
 
7.9%
( 98
 
7.7%
) 98
 
7.7%
1 62
 
4.9%
2 62
 
4.9%
3 58
 
4.6%
5 48
 
3.8%
4 41
 
3.2%
6 36
 
2.8%
Other values (5) 121
 
9.5%
Latin
ValueCountFrequency (%)
P 2
33.3%
T 2
33.3%
A 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2292
64.3%
ASCII 1275
35.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
545
42.7%
, 100
 
7.8%
( 98
 
7.7%
) 98
 
7.7%
1 62
 
4.9%
2 62
 
4.9%
3 58
 
4.5%
5 48
 
3.8%
4 41
 
3.2%
6 36
 
2.8%
Other values (8) 127
 
10.0%
Hangul
ValueCountFrequency (%)
로 194
 
8.5%
광 131
 
5.7%
동 130
 
5.7%
구 127
 
5.5%
시 99
 
4.3%
진 98
 
4.3%
경 98
 
4.3%
서 97
 
4.2%
특 97
 
4.2%
별 97
 
4.2%
Other values (109) 1124
49.0%

회원수(남)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)29.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.649485
Minimum0
Maximum52
Zeros19
Zeros (%)19.6%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2024-04-06T17:13:52.700165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median8
Q315
95-th percentile30.6
Maximum52
Range52
Interquartile range (IQR)11

Descriptive statistics

Standard deviation10.214411
Coefficient of variation (CV)0.95914605
Kurtosis3.1267256
Mean10.649485
Median Absolute Deviation (MAD)6
Skewness1.5430359
Sum1033
Variance104.33419
MonotonicityNot monotonic
2024-04-06T17:13:52.961435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 19
19.6%
9 7
 
7.2%
17 7
 
7.2%
14 6
 
6.2%
4 6
 
6.2%
6 6
 
6.2%
7 5
 
5.2%
8 5
 
5.2%
12 4
 
4.1%
18 4
 
4.1%
Other values (19) 28
28.9%
ValueCountFrequency (%)
0 19
19.6%
1 1
 
1.0%
2 2
 
2.1%
3 2
 
2.1%
4 6
 
6.2%
5 3
 
3.1%
6 6
 
6.2%
7 5
 
5.2%
8 5
 
5.2%
9 7
 
7.2%
ValueCountFrequency (%)
52 1
1.0%
43 1
1.0%
40 1
1.0%
36 1
1.0%
33 1
1.0%
30 1
1.0%
29 1
1.0%
26 1
1.0%
23 1
1.0%
22 1
1.0%

회원수(여)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct33
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.639175
Minimum0
Maximum51
Zeros7
Zeros (%)7.2%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2024-04-06T17:13:53.276891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q114
median19
Q323
95-th percentile38.6
Maximum51
Range51
Interquartile range (IQR)9

Descriptive statistics

Standard deviation10.606784
Coefficient of variation (CV)0.54008296
Kurtosis0.87900436
Mean19.639175
Median Absolute Deviation (MAD)5
Skewness0.6235265
Sum1905
Variance112.50387
MonotonicityNot monotonic
2024-04-06T17:13:53.639469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
20 8
 
8.2%
0 7
 
7.2%
15 7
 
7.2%
21 6
 
6.2%
16 6
 
6.2%
30 5
 
5.2%
22 5
 
5.2%
11 4
 
4.1%
19 4
 
4.1%
14 4
 
4.1%
Other values (23) 41
42.3%
ValueCountFrequency (%)
0 7
7.2%
8 2
 
2.1%
9 2
 
2.1%
10 3
3.1%
11 4
4.1%
12 3
3.1%
13 2
 
2.1%
14 4
4.1%
15 7
7.2%
16 6
6.2%
ValueCountFrequency (%)
51 1
1.0%
50 1
1.0%
45 1
1.0%
44 1
1.0%
41 1
1.0%
38 1
1.0%
37 2
2.1%
36 1
1.0%
35 1
1.0%
33 2
2.1%

회원수(총원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)40.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.28866
Minimum0
Maximum63
Zeros4
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size1005.0 B
2024-04-06T17:13:54.007019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.4
Q122
median28
Q339
95-th percentile54.2
Maximum63
Range63
Interquartile range (IQR)17

Descriptive statistics

Standard deviation13.03118
Coefficient of variation (CV)0.43023295
Kurtosis0.21374561
Mean30.28866
Median Absolute Deviation (MAD)8
Skewness0.21705292
Sum2938
Variance169.81164
MonotonicityNot monotonic
2024-04-06T17:13:54.261922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
20 9
 
9.3%
25 7
 
7.2%
22 5
 
5.2%
35 5
 
5.2%
24 5
 
5.2%
28 5
 
5.2%
23 4
 
4.1%
21 4
 
4.1%
27 4
 
4.1%
0 4
 
4.1%
Other values (29) 45
46.4%
ValueCountFrequency (%)
0 4
4.1%
12 1
 
1.0%
15 2
 
2.1%
16 1
 
1.0%
17 1
 
1.0%
19 1
 
1.0%
20 9
9.3%
21 4
4.1%
22 5
5.2%
23 4
4.1%
ValueCountFrequency (%)
63 1
1.0%
60 1
1.0%
56 1
1.0%
55 2
2.1%
54 1
1.0%
52 2
2.1%
51 2
2.1%
48 2
2.1%
47 1
1.0%
46 1
1.0%

경로당설립일
Date

Distinct65
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Memory size908.0 B
Minimum1984-03-01 00:00:00
Maximum2023-02-01 00:00:00
2024-04-06T17:13:54.536878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:54.831634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-04-06T17:13:45.993448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:44.085772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:44.739656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:45.345757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:46.154738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:44.232012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:44.893293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:45.491004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:46.304456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:44.368033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:45.045279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:45.646770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:46.447265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:44.581493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:45.189547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:13:45.824755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:13:55.043672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동형태경로당명전화번호주소회원수(남)회원수(여)회원수(총원)경로당설립일
연번1.0000.9550.5301.0001.0001.0000.0000.2380.4280.000
행정동0.9551.0000.4711.0001.0001.0000.4360.4860.6080.000
형태0.5300.4711.0001.0001.0001.0000.0000.3290.4820.966
경로당명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
회원수(남)0.0000.4360.0001.0001.0001.0001.0000.5050.6130.642
회원수(여)0.2380.4860.3291.0001.0001.0000.5051.0000.8100.766
회원수(총원)0.4280.6080.4821.0001.0001.0000.6130.8101.0000.000
경로당설립일0.0000.0000.9661.0001.0001.0000.6420.7660.0001.000
2024-04-06T17:13:55.253546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동형태
행정동1.0000.266
형태0.2661.000
2024-04-06T17:13:55.411779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번회원수(남)회원수(여)회원수(총원)행정동형태
연번1.000-0.009-0.143-0.1160.7390.333
회원수(남)-0.0091.000-0.1620.6290.0500.000
회원수(여)-0.143-0.1621.0000.5670.1930.193
회원수(총원)-0.1160.6290.5671.0000.2650.297
행정동0.7390.0500.1930.2651.0000.266
형태0.3330.0000.1930.2970.2661.000

Missing values

2024-04-06T17:13:46.674312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:13:46.940718image/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

연번행정동형태경로당명전화번호주소회원수(남)회원수(여)회원수(총원)경로당설립일
01중곡1동구립중곡1동 제102-467-0014서울특별시 광진구 긴고랑로5길 10(중곡동, 중곡1동 제1경로당)730371994-06-01
12중곡1동구립중곡1동 제202-465-2104서울특별시 광진구 긴고랑로8길 51(중곡동, 중곡1동 제2경로당)2214362003-09-01
23중곡2동구립한마음02-444-0652서울특별시 광진구 긴고랑로22길 39-4(중곡동, 한마음경로당)923321989-06-01
34중곡2동구립장수02-454-3811서울특별시 광진구 긴고랑로31길 44(중곡동, 장수경로당)022222006-11-01
45중곡3동구립용마02-466-1020서울특별시 광진구 용마산로31길 38-8 (중곡동, 용마경로당)530351989-06-01
56중곡3동구립중곡3동02-466-5977서울특별시 광진구 동일로80길 20 (중곡동, 중곡3동 경로당)1941601998-08-01
67중곡4동구립중곡4동02-457-3073서울특별시 광진구 긴고랑로39길 57 (중곡동, 중곡4동 경로당)416201994-05-01
78중곡4동구립용곡02-455-8192서울특별시 광진구 용마산28길 31 (중곡동, 용곡경로당)916251995-02-01
89중곡4동구립대원02-457-9203서울특별시 광진구 긴고랑로36길 57-27 (중곡동, 대원경로당)645511998-02-01
910중곡4동사립신향빌라02-3437-1334서울특별시 광진구 용마산로24길 13 (중곡동, 신향빌라 경로당)016161995-05-01
연번행정동형태경로당명전화번호주소회원수(남)회원수(여)회원수(총원)경로당설립일
8788자양4동사립꿈에그린02-463-8234서울특별시 광진구 뚝섬로24길 74, (자양동, 한화꿈에그린아파트 경로당)424282008-02-01
8889자양4동사립한강우성02-464-9501서울특별시 광진구 능동로1길 15 (자양동, 한강우성아파트 경로당)820281995-02-01
8990화양동구립화양동02-462-2669서울특별시 광진구 능동로17길 39 (화양동, 화양동경로당)021211989-06-01
9091화양동구립모진동02-454-3545서울특별시 광진구 광나루로24길 53 (화양동, 모진동경로당)149231995-05-01
9192화양동사립화양동 현대02-499-5599서울특별시 광진구 동일로24길 5 (화양동, 현대아파트 경로당)814222002-10-01
9293군자동구립군자02-499-2920서울특별시 광진구 동일로52길 27 (군자동, 군자경로당)4312551994-06-01
9394군자동구립양마02-466-9838서울특별시 광진구 동일로42길 2 (군자동, 양마경로당)930391989-06-01
9495군자동구립양마제202-461-2719서울특별시 광진구 군자로13길 35 (군자동, 양마제2 경로당)400402007-05-01
9596군자동구립복조리02-464-1123서울특별시 광진구 광나루로17길 28 102호 (군자동, 복조리경로당)1922412022-09-01
9697군자동사립일성파크02-465-5897서울특별시 광진구 군자로12길 46 (군자동, 일성파크아파트 경로당)1738551996-11-01