Overview

Dataset statistics

Number of variables9
Number of observations63
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory77.1 B

Variable types

Text4
Numeric3
Categorical2

Dataset

Description인천광역시 부평구시설관리공단에서 관리하는 노인여가시설(노인정) 현황 (위치, 회원수 등)에 관한 데이터를 제공합니다.
Author인천광역시부평구시설관리공단
URLhttps://www.data.go.kr/data/15003011/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
시설명 has unique valuesUnique
소재지지번주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:51:02.966262
Analysis finished2023-12-12 11:51:04.705657
Duration1.74 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-12T20:51:04.886441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.6190476
Min length6

Characters and Unicode

Total characters480
Distinct characters79
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

Unique63 ?
Unique (%)100.0%

Sample

1st row부평1동 분회
2nd row부평1동 부원
3rd row부평2동 분회
4th row부평2동 희망천
5th row부평3동 신촌
ValueCountFrequency (%)
분회 15
 
11.9%
부개1동 7
 
5.6%
십정2동 5
 
4.0%
부평3동 4
 
3.2%
부개2동 4
 
3.2%
십정1동 4
 
3.2%
부평4동 4
 
3.2%
갈산1동 3
 
2.4%
부평5동 3
 
2.4%
부평6동 3
 
2.4%
Other values (60) 74
58.7%
2023-12-12T20:51:05.300217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 69
 
14.4%
63
 
13.1%
부 42
 
8.8%
1 23
 
4.8%
평 20
 
4.2%
산 18
 
3.8%
2 17
 
3.5%
분 16
 
3.3%
회 15
 
3.1%
개 13
 
2.7%
Other values (69) 184
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 356
74.2%
Space Separator 63
 
13.1%
Decimal Number 61
 
12.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 69
19.4%
부 42
 
11.8%
평 20
 
5.6%
산 18
 
5.1%
분 16
 
4.5%
회 15
 
4.2%
개 13
 
3.7%
정 10
 
2.8%
곡 10
 
2.8%
십 9
 
2.5%
Other values (62) 134
37.6%
Decimal Number
ValueCountFrequency (%)
1 23
37.7%
2 17
27.9%
3 9
 
14.8%
4 6
 
9.8%
6 3
 
4.9%
5 3
 
4.9%
Space Separator
ValueCountFrequency (%)
63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 356
74.2%
Common 124
 
25.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 69
19.4%
부 42
 
11.8%
평 20
 
5.6%
산 18
 
5.1%
분 16
 
4.5%
회 15
 
4.2%
개 13
 
3.7%
정 10
 
2.8%
곡 10
 
2.8%
십 9
 
2.5%
Other values (62) 134
37.6%
Common
ValueCountFrequency (%)
63
50.8%
1 23
 
18.5%
2 17
 
13.7%
3 9
 
7.3%
4 6
 
4.8%
6 3
 
2.4%
5 3
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 356
74.2%
ASCII 124
 
25.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 69
19.4%
부 42
 
11.8%
평 20
 
5.6%
산 18
 
5.1%
분 16
 
4.5%
회 15
 
4.2%
개 13
 
3.7%
정 10
 
2.8%
곡 10
 
2.8%
십 9
 
2.5%
Other values (62) 134
37.6%
ASCII
ValueCountFrequency (%)
63
50.8%
1 23
 
18.5%
2 17
 
13.7%
3 9
 
7.3%
4 6
 
4.8%
6 3
 
2.4%
5 3
 
2.4%

소재지지번주소
Text

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-12T20:51:05.612481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length19.730159
Min length10

Characters and Unicode

Total characters1243
Distinct characters41
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

Unique63 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 부평1동 546-105
2nd row인천광역시 부평구 부평1동 451-48
3rd row인천광역시 부평구 부평2동 760-104
4th row인천광역시 부평구 부평2동 768-110
5th row인천광역시 부평구 부평3동 788-13
ValueCountFrequency (%)
인천광역시 57
23.6%
부평구 57
23.6%
부개1동 7
 
2.9%
십정2동 5
 
2.1%
부평4동 4
 
1.7%
십정1동 4
 
1.7%
부개2동 4
 
1.7%
부평6동 3
 
1.2%
청천2동 3
 
1.2%
산곡3동 3
 
1.2%
Other values (82) 95
39.3%
2023-12-12T20:51:06.115978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
179
 
14.4%
부 86
 
6.9%
1 77
 
6.2%
평 73
 
5.9%
동 63
 
5.1%
천 62
 
5.0%
2 59
 
4.7%
구 58
 
4.7%
광 58
 
4.7%
- 58
 
4.7%
Other values (31) 470
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 661
53.2%
Decimal Number 345
27.8%
Space Separator 179
 
14.4%
Dash Punctuation 58
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 86
13.0%
평 73
11.0%
동 63
9.5%
천 62
9.4%
구 58
8.8%
광 58
8.8%
시 57
8.6%
역 57
8.6%
인 57
8.6%
산 18
 
2.7%
Other values (19) 72
10.9%
Decimal Number
ValueCountFrequency (%)
1 77
22.3%
2 59
17.1%
3 31
9.0%
0 29
 
8.4%
4 27
 
7.8%
6 27
 
7.8%
7 27
 
7.8%
5 25
 
7.2%
8 25
 
7.2%
9 18
 
5.2%
Space Separator
ValueCountFrequency (%)
179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 661
53.2%
Common 582
46.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 86
13.0%
평 73
11.0%
동 63
9.5%
천 62
9.4%
구 58
8.8%
광 58
8.8%
시 57
8.6%
역 57
8.6%
인 57
8.6%
산 18
 
2.7%
Other values (19) 72
10.9%
Common
ValueCountFrequency (%)
179
30.8%
1 77
13.2%
2 59
 
10.1%
- 58
 
10.0%
3 31
 
5.3%
0 29
 
5.0%
4 27
 
4.6%
6 27
 
4.6%
7 27
 
4.6%
5 25
 
4.3%
Other values (2) 43
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 661
53.2%
ASCII 582
46.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
179
30.8%
1 77
13.2%
2 59
 
10.1%
- 58
 
10.0%
3 31
 
5.3%
0 29
 
5.0%
4 27
 
4.6%
6 27
 
4.6%
7 27
 
4.6%
5 25
 
4.3%
Other values (2) 43
 
7.4%
Hangul
ValueCountFrequency (%)
부 86
13.0%
평 73
11.0%
동 63
9.5%
천 62
9.4%
구 58
8.8%
광 58
8.8%
시 57
8.6%
역 57
8.6%
인 57
8.6%
산 18
 
2.7%
Other values (19) 72
10.9%

소재지도로명주소
Text

Distinct62
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-12T20:51:06.405125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length20.777778
Min length16

Characters and Unicode

Total characters1309
Distinct characters71
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

Unique61 ?
Unique (%)96.8%

Sample

1st row인천광역시 부평구 경원대로1367번길 48
2nd row인천광역시 부평구 원적로488번길 20
3rd row인천광역시 부평구 부영로28번길 12-6
4th row인천광역시 부평구 경인로834번길 8
5th row인천광역시 부평구 경원대로1256번길 3
ValueCountFrequency (%)
인천광역시 63
25.4%
부평구 63
25.4%
20 3
 
1.2%
3 3
 
1.2%
48 2
 
0.8%
동수천로 2
 
0.8%
주부토로 2
 
0.8%
18 2
 
0.8%
39 2
 
0.8%
11 2
 
0.8%
Other values (103) 104
41.9%
2023-12-12T20:51:06.834220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
185
 
14.1%
부 74
 
5.7%
평 67
 
5.1%
인 66
 
5.0%
천 66
 
5.0%
광 63
 
4.8%
역 63
 
4.8%
시 63
 
4.8%
구 63
 
4.8%
로 63
 
4.8%
Other values (61) 536
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 819
62.6%
Decimal Number 281
 
21.5%
Space Separator 185
 
14.1%
Dash Punctuation 24
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 74
9.0%
평 67
 
8.2%
인 66
 
8.1%
천 66
 
8.1%
광 63
 
7.7%
역 63
 
7.7%
시 63
 
7.7%
구 63
 
7.7%
로 63
 
7.7%
길 51
 
6.2%
Other values (49) 180
22.0%
Decimal Number
ValueCountFrequency (%)
1 50
17.8%
2 38
13.5%
4 30
10.7%
0 30
10.7%
3 29
10.3%
8 27
9.6%
9 22
7.8%
6 21
7.5%
5 17
 
6.0%
7 17
 
6.0%
Space Separator
ValueCountFrequency (%)
185
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 819
62.6%
Common 490
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 74
9.0%
평 67
 
8.2%
인 66
 
8.1%
천 66
 
8.1%
광 63
 
7.7%
역 63
 
7.7%
시 63
 
7.7%
구 63
 
7.7%
로 63
 
7.7%
길 51
 
6.2%
Other values (49) 180
22.0%
Common
ValueCountFrequency (%)
185
37.8%
1 50
 
10.2%
2 38
 
7.8%
4 30
 
6.1%
0 30
 
6.1%
3 29
 
5.9%
8 27
 
5.5%
- 24
 
4.9%
9 22
 
4.5%
6 21
 
4.3%
Other values (2) 34
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 819
62.6%
ASCII 490
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
185
37.8%
1 50
 
10.2%
2 38
 
7.8%
4 30
 
6.1%
0 30
 
6.1%
3 29
 
5.9%
8 27
 
5.5%
- 24
 
4.9%
9 22
 
4.5%
6 21
 
4.3%
Other values (2) 34
 
6.9%
Hangul
ValueCountFrequency (%)
부 74
9.0%
평 67
 
8.2%
인 66
 
8.1%
천 66
 
8.1%
광 63
 
7.7%
역 63
 
7.7%
시 63
 
7.7%
구 63
 
7.7%
로 63
 
7.7%
길 51
 
6.2%
Other values (49) 180
22.0%

회원수
Real number (ℝ)

Distinct33
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.15873
Minimum1
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T20:51:06.977777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile20.1
Q128.5
median40
Q350
95-th percentile65
Maximum120
Range119
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation18.508243
Coefficient of variation (CV)0.44967963
Kurtosis4.3923974
Mean41.15873
Median Absolute Deviation (MAD)11
Skewness1.1135751
Sum2593
Variance342.55504
MonotonicityNot monotonic
2023-12-12T20:51:07.117203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
40 5
 
7.9%
27 4
 
6.3%
35 4
 
6.3%
45 3
 
4.8%
48 3
 
4.8%
60 3
 
4.8%
28 2
 
3.2%
1 2
 
3.2%
29 2
 
3.2%
30 2
 
3.2%
Other values (23) 33
52.4%
ValueCountFrequency (%)
1 2
3.2%
15 1
 
1.6%
20 1
 
1.6%
21 1
 
1.6%
22 2
3.2%
23 2
3.2%
25 1
 
1.6%
27 4
6.3%
28 2
3.2%
29 2
3.2%
ValueCountFrequency (%)
120 1
 
1.6%
80 1
 
1.6%
67 1
 
1.6%
65 2
3.2%
63 1
 
1.6%
61 1
 
1.6%
60 3
4.8%
55 1
 
1.6%
54 1
 
1.6%
53 2
3.2%

준공연도
Text

Distinct37
Distinct (%)58.7%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-12-12T20:51:07.302686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters252
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)39.7%

Sample

1st row1988
2nd row2002
3rd row2021
4th row2009
5th row1965
ValueCountFrequency (%)
정보없음 7
 
11.1%
1992 5
 
7.9%
2002 5
 
7.9%
1984 3
 
4.8%
1991 3
 
4.8%
1988 3
 
4.8%
2014 2
 
3.2%
1995 2
 
3.2%
1993 2
 
3.2%
1999 2
 
3.2%
Other values (27) 29
46.0%
2023-12-12T20:51:07.610951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 62
24.6%
1 47
18.7%
0 38
15.1%
2 33
13.1%
8 17
 
6.7%
4 8
 
3.2%
정 7
 
2.8%
보 7
 
2.8%
없 7
 
2.8%
음 7
 
2.8%
Other values (4) 19
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 224
88.9%
Other Letter 28
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 62
27.7%
1 47
21.0%
0 38
17.0%
2 33
14.7%
8 17
 
7.6%
4 8
 
3.6%
5 6
 
2.7%
7 6
 
2.7%
6 4
 
1.8%
3 3
 
1.3%
Other Letter
ValueCountFrequency (%)
정 7
25.0%
보 7
25.0%
없 7
25.0%
음 7
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 224
88.9%
Hangul 28
 
11.1%

Most frequent character per script

Common
ValueCountFrequency (%)
9 62
27.7%
1 47
21.0%
0 38
17.0%
2 33
14.7%
8 17
 
7.6%
4 8
 
3.6%
5 6
 
2.7%
7 6
 
2.7%
6 4
 
1.8%
3 3
 
1.3%
Hangul
ValueCountFrequency (%)
정 7
25.0%
보 7
25.0%
없 7
25.0%
음 7
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 224
88.9%
Hangul 28
 
11.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 62
27.7%
1 47
21.0%
0 38
17.0%
2 33
14.7%
8 17
 
7.6%
4 8
 
3.6%
5 6
 
2.7%
7 6
 
2.7%
6 4
 
1.8%
3 3
 
1.3%
Hangul
ValueCountFrequency (%)
정 7
25.0%
보 7
25.0%
없 7
25.0%
음 7
25.0%

유형
Categorical

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
구립
45 
사립
11 
민간
7 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구립 45
71.4%
사립 11
 
17.5%
민간 7
 
11.1%

Length

2023-12-12T20:51:07.763988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:51:07.885505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
구립 45
71.4%
사립 11
 
17.5%
민간 7
 
11.1%

위도
Real number (ℝ)

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.494692
Minimum37.469986
Maximum37.521187
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T20:51:08.027794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.469986
5-th percentile37.472599
Q137.484554
median37.493937
Q337.504157
95-th percentile37.519143
Maximum37.521187
Range0.051201
Interquartile range (IQR)0.0196035

Descriptive statistics

Standard deviation0.014175635
Coefficient of variation (CV)0.00037807044
Kurtosis-0.87853358
Mean37.494692
Median Absolute Deviation (MAD)0.010087
Skewness0.19389852
Sum2362.1656
Variance0.00020094862
MonotonicityNot monotonic
2023-12-12T20:51:08.183365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.493385 1
 
1.6%
37.502183 1
 
1.6%
37.518803 1
 
1.6%
37.517573 1
 
1.6%
37.485014 1
 
1.6%
37.484463 1
 
1.6%
37.486234 1
 
1.6%
37.488464 1
 
1.6%
37.485034 1
 
1.6%
37.493937 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
37.469986 1
1.6%
37.470695 1
1.6%
37.470998 1
1.6%
37.472513 1
1.6%
37.473371 1
1.6%
37.475499 1
1.6%
37.475943 1
1.6%
37.476046 1
1.6%
37.480718 1
1.6%
37.481305 1
1.6%
ValueCountFrequency (%)
37.521187 1
1.6%
37.520165 1
1.6%
37.519599 1
1.6%
37.519181 1
1.6%
37.518803 1
1.6%
37.517573 1
1.6%
37.51547 1
1.6%
37.515389 1
1.6%
37.513807 1
1.6%
37.511903 1
1.6%

경도
Real number (ℝ)

UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.7201
Minimum126.68808
Maximum126.75176
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2023-12-12T20:51:08.322159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.68808
5-th percentile126.69575
Q1126.70543
median126.72244
Q3126.73425
95-th percentile126.74194
Maximum126.75176
Range0.063674
Interquartile range (IQR)0.0288115

Descriptive statistics

Standard deviation0.016204164
Coefficient of variation (CV)0.00012787367
Kurtosis-1.2555848
Mean126.7201
Median Absolute Deviation (MAD)0.01547
Skewness-0.081393879
Sum7983.3661
Variance0.00026257493
MonotonicityNot monotonic
2023-12-12T20:51:08.465631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.720848 1
 
1.6%
126.720851 1
 
1.6%
126.742426 1
 
1.6%
126.741964 1
 
1.6%
126.73346 1
 
1.6%
126.737908 1
 
1.6%
126.738539 1
 
1.6%
126.734738 1
 
1.6%
126.740725 1
 
1.6%
126.740082 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
126.688084 1
1.6%
126.692929 1
1.6%
126.693739 1
1.6%
126.69554 1
1.6%
126.697641 1
1.6%
126.699967 1
1.6%
126.700268 1
1.6%
126.701591 1
1.6%
126.701677 1
1.6%
126.702027 1
1.6%
ValueCountFrequency (%)
126.751758 1
1.6%
126.744554 1
1.6%
126.742426 1
1.6%
126.741964 1
1.6%
126.741704 1
1.6%
126.740725 1
1.6%
126.740082 1
1.6%
126.738819 1
1.6%
126.738539 1
1.6%
126.738162 1
1.6%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
2023-10-31
63 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-31
2nd row2023-10-31
3rd row2023-10-31
4th row2023-10-31
5th row2023-10-31

Common Values

ValueCountFrequency (%)
2023-10-31 63
100.0%

Length

2023-12-12T20:51:08.634446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:51:08.746168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-31 63
100.0%

Interactions

2023-12-12T20:51:04.127728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:03.467603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:03.800146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:04.221921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:03.578459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:03.929738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:04.329075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:03.690134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:51:04.026207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:51:08.811903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명소재지지번주소소재지도로명주소회원수준공연도유형위도경도
시설명1.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0000.9970.5620.9101.000
회원수1.0001.0001.0001.0000.4240.5190.0000.358
준공연도1.0001.0000.9970.4241.0000.9680.8490.795
유형1.0001.0000.5620.5190.9681.0000.0000.297
위도1.0001.0000.9100.0000.8490.0001.0000.402
경도1.0001.0001.0000.3580.7950.2970.4021.000
2023-12-12T20:51:08.933948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회원수위도경도유형
회원수1.000-0.0690.1890.367
위도-0.0691.0000.0930.000
경도0.1890.0931.0000.168
유형0.3670.0000.1681.000

Missing values

2023-12-12T20:51:04.483169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:51:04.634101image/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

시설명소재지지번주소소재지도로명주소회원수준공연도유형위도경도데이터기준일자
0부평1동 분회인천광역시 부평구 부평1동 546-105인천광역시 부평구 경원대로1367번길 48471988구립37.493385126.7208482023-10-31
1부평1동 부원인천광역시 부평구 부평1동 451-48인천광역시 부평구 원적로488번길 20362002구립37.502183126.7208512023-10-31
2부평2동 분회인천광역시 부평구 부평2동 760-104인천광역시 부평구 부영로28번길 12-6652021구립37.487628126.7180052023-10-31
3부평2동 희망천인천광역시 부평구 부평2동 768-110인천광역시 부평구 경인로834번길 8532009구립37.482232126.7144932023-10-31
4부평3동 신촌인천광역시 부평구 부평3동 788-13인천광역시 부평구 경원대로1256번길 3491965사립37.488691126.7096542023-10-31
5부평3동 창휘인천광역시 부평구 부평3동 767-39인천광역시 부평구 동수북로50번길 49381979구립37.484644126.7121242023-10-31
6부평3동 장수인천광역시 부평구 십정동 569-1인천광역시 부평구 백운로 14451992구립37.481305126.710132023-10-31
7부평3동 백운인천광역시 부평구 경원대로1184번길 20인천광역시 부평구 이규보로 139-5452014구립37.483252126.7046082023-10-31
8부평4동 중앙인천광역시 부평구 부평4동 372-9인천광역시 부평구 주부토로 28-1432002구립37.497451126.7253162023-10-31
9부평4동 해바라기인천광역시 부평구 부평4동 10-1209인천광역시 부평구 부흥북로57번길 20352019사립37.502163126.7287732023-10-31
시설명소재지지번주소소재지도로명주소회원수준공연도유형위도경도데이터기준일자
53십정2동 동암남부인천광역시 부평구 십정2동 486-25인천광역시 부평구 이규보로22번길 27602014구립37.469986126.7055132023-10-31
54십정2동 동암마을십정2동 479-19인천광역시 부평구 아트센터로 44번길 15-12502020구립37.472513126.7038412023-10-31
55십정2동 하정인천광역시 부평구 십정2동 388-15인천광역시 부평구 동암남로 20번길 16402006구립37.475499126.7016772023-10-31
56부평4동 건영아파트부평4동 252-29인천광역시 부평구 부흥로304번길 1751정보없음민간37.497463126.7262132023-10-31
57산곡3동 부평현대14차산곡3동 311-76인천광역시 부평구 마장로144번길 8727정보없음민간37.494421126.7064492023-10-31
58삼산1동 동남아파트삼산1동 206-2인천광역시 부평구 후정동로25번길 3-1023정보없음민간37.519599126.7367992023-10-31
59부개1동 리노빌애화아파트부개1동 296-2인천광역시 부평구 수변로9번길 1045정보없음민간37.487825126.7388192023-10-31
60부개2동 백영아파트부개2동 120-46인천광역시 부평구 수변로 11528정보없음민간37.496428126.7417042023-10-31
61부개1동 노인의집인천광역시 부평구 부개1동 402번지 광일아파트인천광역시 부평구 마분로 391정보없음민간37.482571126.7381622023-10-31
62부개3동 노인의집인천광역시 부평구 부개3동 477-1 대동아파트인천광역시 부평구 길주로 6401정보없음민간37.505519126.7337552023-10-31