Overview

Dataset statistics

Number of variables11
Number of observations36
Missing cells4
Missing cells (%)1.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory95.7 B

Variable types

Text3
Categorical4
Numeric3
DateTime1

Dataset

Description인천광역시 부평구에서 운영중인 거주자우선주차 구역의 소재지, 면수, 운영방법, 운영시간, 요금 에 관한 데이터를 제공합니다.
Author인천광역시부평구시설관리공단
URLhttps://www.data.go.kr/data/15003009/fileData.do

Alerts

운영방법 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 행정동High correlation
경도 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
야간시간 is highly imbalanced (81.7%)Imbalance
야간요금 is highly imbalanced (81.7%)Imbalance
설치위치 has 4 (11.1%) missing valuesMissing
관리번호 has unique valuesUnique
소재지위치 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:30:39.186893
Analysis finished2023-12-12 00:30:41.544948
Duration2.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T09:30:41.732460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters396
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

Unique36 ?
Unique (%)100.0%

Sample

1st row28237-01-01
2nd row28237-02-01
3rd row28237-02-02
4th row28237-03-01
5th row28237-03-02
ValueCountFrequency (%)
28237-01-01 1
 
2.8%
28237-02-01 1
 
2.8%
28237-15-01 1
 
2.8%
28237-13-01 1
 
2.8%
28237-13-02 1
 
2.8%
28237-13-03 1
 
2.8%
28237-13-04 1
 
2.8%
28237-14-01 1
 
2.8%
28237-14-02 1
 
2.8%
28237-17-05 1
 
2.8%
Other values (26) 26
72.2%
2023-12-12T09:30:42.166802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 90
22.7%
- 72
18.2%
0 52
13.1%
3 47
11.9%
7 43
10.9%
8 39
9.8%
1 36
 
9.1%
4 10
 
2.5%
6 4
 
1.0%
5 2
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 324
81.8%
Dash Punctuation 72
 
18.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 90
27.8%
0 52
16.0%
3 47
14.5%
7 43
13.3%
8 39
12.0%
1 36
 
11.1%
4 10
 
3.1%
6 4
 
1.2%
5 2
 
0.6%
9 1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 396
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 90
22.7%
- 72
18.2%
0 52
13.1%
3 47
11.9%
7 43
10.9%
8 39
9.8%
1 36
 
9.1%
4 10
 
2.5%
6 4
 
1.0%
5 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 90
22.7%
- 72
18.2%
0 52
13.1%
3 47
11.9%
7 43
10.9%
8 39
9.8%
1 36
 
9.1%
4 10
 
2.5%
6 4
 
1.0%
5 2
 
0.5%

소재지위치
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-12T09:30:42.460222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19.5
Mean length17.805556
Min length13

Characters and Unicode

Total characters641
Distinct characters50
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

Unique36 ?
Unique (%)100.0%

Sample

1st row인천광역시 부평구 경원대로 1344번길
2nd row인천광역시 부평구 동수북로 121
3rd row인천광역시 부평구 동수북로 36
4th row인천광역시 부평구 동수북로 182
5th row인천광역시 부평구 안남로 63번길13
ValueCountFrequency (%)
인천광역시 36
27.3%
부평구 36
27.3%
동수북로 4
 
3.0%
신트리로 4
 
3.0%
평천로 3
 
2.3%
일원 3
 
2.3%
부평북로 2
 
1.5%
30 2
 
1.5%
항동로 2
 
1.5%
경인로1083번길 1
 
0.8%
Other values (39) 39
29.5%
2023-12-12T09:30:42.938995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
15.1%
평 43
 
6.7%
천 40
 
6.2%
인 39
 
6.1%
부 39
 
6.1%
로 36
 
5.6%
구 36
 
5.6%
시 36
 
5.6%
역 36
 
5.6%
광 36
 
5.6%
Other values (40) 203
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 455
71.0%
Space Separator 97
 
15.1%
Decimal Number 86
 
13.4%
Dash Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
평 43
9.5%
천 40
8.8%
인 39
8.6%
부 39
8.6%
로 36
 
7.9%
구 36
 
7.9%
시 36
 
7.9%
역 36
 
7.9%
광 36
 
7.9%
길 19
 
4.2%
Other values (28) 95
20.9%
Decimal Number
ValueCountFrequency (%)
1 18
20.9%
3 16
18.6%
4 11
12.8%
2 10
11.6%
6 9
10.5%
0 8
9.3%
8 5
 
5.8%
5 3
 
3.5%
7 3
 
3.5%
9 3
 
3.5%
Space Separator
ValueCountFrequency (%)
97
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 455
71.0%
Common 186
29.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
평 43
9.5%
천 40
8.8%
인 39
8.6%
부 39
8.6%
로 36
 
7.9%
구 36
 
7.9%
시 36
 
7.9%
역 36
 
7.9%
광 36
 
7.9%
길 19
 
4.2%
Other values (28) 95
20.9%
Common
ValueCountFrequency (%)
97
52.2%
1 18
 
9.7%
3 16
 
8.6%
4 11
 
5.9%
2 10
 
5.4%
6 9
 
4.8%
0 8
 
4.3%
8 5
 
2.7%
5 3
 
1.6%
7 3
 
1.6%
Other values (2) 6
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 455
71.0%
ASCII 186
29.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
97
52.2%
1 18
 
9.7%
3 16
 
8.6%
4 11
 
5.9%
2 10
 
5.4%
6 9
 
4.8%
0 8
 
4.3%
8 5
 
2.7%
5 3
 
1.6%
7 3
 
1.6%
Other values (2) 6
 
3.2%
Hangul
ValueCountFrequency (%)
평 43
9.5%
천 40
8.8%
인 39
8.6%
부 39
8.6%
로 36
 
7.9%
구 36
 
7.9%
시 36
 
7.9%
역 36
 
7.9%
광 36
 
7.9%
길 19
 
4.2%
Other values (28) 95
20.9%

설치위치
Text

MISSING 

Distinct31
Distinct (%)96.9%
Missing4
Missing (%)11.1%
Memory size420.0 B
2023-12-12T09:30:43.157882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length9.1875
Min length5

Characters and Unicode

Total characters294
Distinct characters108
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)93.8%

Sample

1st row부평역광장 옆
2nd row남부고가교~부평역
3rd row백운쌍굴~남부고가교
4th row182-294번지~백운쌍굴
5th row백운역쌍굴~경원대로
ValueCountFrequency (%)
앞 5
 
9.8%
공영주차장 3
 
5.9%
옆 2
 
3.9%
주차장 2
 
3.9%
번길 1
 
2.0%
103번지 1
 
2.0%
성일아파트 1
 
2.0%
담장 1
 
2.0%
부개역남부 1
 
2.0%
갈산시장 1
 
2.0%
Other values (33) 33
64.7%
2023-12-12T09:30:43.534442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
6.5%
부 13
 
4.4%
~ 11
 
3.7%
장 10
 
3.4%
아 10
 
3.4%
파 10
 
3.4%
트 10
 
3.4%
주 9
 
3.1%
동 9
 
3.1%
역 6
 
2.0%
Other values (98) 187
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 238
81.0%
Decimal Number 20
 
6.8%
Space Separator 19
 
6.5%
Math Symbol 11
 
3.7%
Dash Punctuation 3
 
1.0%
Uppercase Letter 2
 
0.7%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 13
 
5.5%
장 10
 
4.2%
아 10
 
4.2%
파 10
 
4.2%
트 10
 
4.2%
주 9
 
3.8%
동 9
 
3.8%
역 6
 
2.5%
평 6
 
2.5%
운 6
 
2.5%
Other values (82) 149
62.6%
Decimal Number
ValueCountFrequency (%)
2 4
20.0%
1 3
15.0%
6 3
15.0%
0 2
10.0%
4 2
10.0%
8 2
10.0%
3 1
 
5.0%
5 1
 
5.0%
9 1
 
5.0%
7 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 238
81.0%
Common 54
 
18.4%
Latin 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 13
 
5.5%
장 10
 
4.2%
아 10
 
4.2%
파 10
 
4.2%
트 10
 
4.2%
주 9
 
3.8%
동 9
 
3.8%
역 6
 
2.5%
평 6
 
2.5%
운 6
 
2.5%
Other values (82) 149
62.6%
Common
ValueCountFrequency (%)
19
35.2%
~ 11
20.4%
2 4
 
7.4%
1 3
 
5.6%
6 3
 
5.6%
- 3
 
5.6%
0 2
 
3.7%
4 2
 
3.7%
8 2
 
3.7%
3 1
 
1.9%
Other values (4) 4
 
7.4%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 238
81.0%
ASCII 56
 
19.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
33.9%
~ 11
19.6%
2 4
 
7.1%
1 3
 
5.4%
6 3
 
5.4%
- 3
 
5.4%
0 2
 
3.6%
4 2
 
3.6%
8 2
 
3.6%
3 1
 
1.8%
Other values (6) 6
 
10.7%
Hangul
ValueCountFrequency (%)
부 13
 
5.5%
장 10
 
4.2%
아 10
 
4.2%
파 10
 
4.2%
트 10
 
4.2%
주 9
 
3.8%
동 9
 
3.8%
역 6
 
2.5%
평 6
 
2.5%
운 6
 
2.5%
Other values (82) 149
62.6%

행정동
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Memory size420.0 B
부개1동
5 
부평4동
4 
청천2동
4 
갈산1동
4 
부평3동
3 
Other values (11)
16 

Length

Max length5
Median length4
Mean length3.9722222
Min length3

Unique

Unique6 ?
Unique (%)16.7%

Sample

1st row부평1동
2nd row부평2동
3rd row부평2동
4th row부평3동
5th row부평3동

Common Values

ValueCountFrequency (%)
부개1동 5
13.9%
부평4동 4
11.1%
청천2동 4
11.1%
갈산1동 4
11.1%
부평3동 3
8.3%
부평2동 2
 
5.6%
부평6동 2
 
5.6%
청천1동 2
 
5.6%
갈산2동 2
 
5.6%
일신동 2
 
5.6%
Other values (6) 6
16.7%

Length

2023-12-12T09:30:43.692675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부개1동 5
13.9%
부평4동 4
11.1%
청천2동 4
11.1%
갈산1동 4
11.1%
부평3동 3
8.3%
부평2동 2
 
5.6%
부평6동 2
 
5.6%
청천1동 2
 
5.6%
갈산2동 2
 
5.6%
일신동 2
 
5.6%
Other values (6) 6
16.7%

면수
Real number (ℝ)

Distinct30
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.888889
Minimum6
Maximum94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T09:30:43.834711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile10
Q113
median22.5
Q341.25
95-th percentile70.5
Maximum94
Range88
Interquartile range (IQR)28.25

Descriptive statistics

Standard deviation21.675236
Coefficient of variation (CV)0.72519378
Kurtosis1.3288757
Mean29.888889
Median Absolute Deviation (MAD)10
Skewness1.3613908
Sum1076
Variance469.81587
MonotonicityNot monotonic
2023-12-12T09:30:43.949473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
13 3
 
8.3%
10 3
 
8.3%
47 2
 
5.6%
12 2
 
5.6%
32 1
 
2.8%
67 1
 
2.8%
16 1
 
2.8%
24 1
 
2.8%
41 1
 
2.8%
22 1
 
2.8%
Other values (20) 20
55.6%
ValueCountFrequency (%)
6 1
 
2.8%
10 3
8.3%
11 1
 
2.8%
12 2
5.6%
13 3
8.3%
14 1
 
2.8%
16 1
 
2.8%
17 1
 
2.8%
18 1
 
2.8%
19 1
 
2.8%
ValueCountFrequency (%)
94 1
2.8%
81 1
2.8%
67 1
2.8%
65 1
2.8%
60 1
2.8%
52 1
2.8%
47 2
5.6%
42 1
2.8%
41 1
2.8%
34 1
2.8%

운영방법
Categorical

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
야간
36 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
야간 36
100.0%

Length

2023-12-12T09:30:44.070274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:30:44.171754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
야간 36
100.0%

야간시간
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
19:00~익일01:00
35 
18:00~익일09:00
 
1

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row19:00~익일01:00
2nd row19:00~익일01:00
3rd row19:00~익일01:00
4th row19:00~익일01:00
5th row19:00~익일01:00

Common Values

ValueCountFrequency (%)
19:00~익일01:00 35
97.2%
18:00~익일09:00 1
 
2.8%

Length

2023-12-12T09:30:44.275198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:30:44.371521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
19:00~익일01:00 35
97.2%
18:00~익일09:00 1
 
2.8%

야간요금
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
10000
35 
20000
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row10000
2nd row10000
3rd row10000
4th row10000
5th row10000

Common Values

ValueCountFrequency (%)
10000 35
97.2%
20000 1
 
2.8%

Length

2023-12-12T09:30:44.467489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:30:44.568028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10000 35
97.2%
20000 1
 
2.8%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.500794
Minimum37.472473
Maximum37.523034
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T09:30:44.678394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.472473
5-th percentile37.482449
Q137.487908
median37.503514
Q337.515306
95-th percentile37.522226
Maximum37.523034
Range0.05056069
Interquartile range (IQR)0.02739845

Descriptive statistics

Standard deviation0.015434522
Coefficient of variation (CV)0.00041157855
Kurtosis-1.4839503
Mean37.500794
Median Absolute Deviation (MAD)0.01512374
Skewness0.077912298
Sum1350.0286
Variance0.00023822448
MonotonicityNot monotonic
2023-12-12T09:30:44.815167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
37.49014265 1
 
2.8%
37.52029265 1
 
2.8%
37.51784011 1
 
2.8%
37.52195915 1
 
2.8%
37.51824235 1
 
2.8%
37.51178053 1
 
2.8%
37.51195573 1
 
2.8%
37.52303379 1
 
2.8%
37.48796345 1
 
2.8%
37.4885395 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
37.4724731 1
2.8%
37.48180972 1
2.8%
37.48266257 1
2.8%
37.48327611 1
2.8%
37.48456616 1
2.8%
37.48458821 1
2.8%
37.48515066 1
2.8%
37.48623165 1
2.8%
37.48774016 1
2.8%
37.48796345 1
2.8%
ValueCountFrequency (%)
37.52303379 1
2.8%
37.52302744 1
2.8%
37.52195915 1
2.8%
37.52131951 1
2.8%
37.5211219 1
2.8%
37.52079458 1
2.8%
37.52029265 1
2.8%
37.51824235 1
2.8%
37.51784011 1
2.8%
37.5144614 1
2.8%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.72175
Minimum126.69185
Maximum126.74745
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T09:30:44.934994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.69185
5-th percentile126.70023
Q1126.70928
median126.72283
Q3126.73225
95-th percentile126.74218
Maximum126.74745
Range0.0555958
Interquartile range (IQR)0.02297055

Descriptive statistics

Standard deviation0.014139491
Coefficient of variation (CV)0.00011157904
Kurtosis-0.80662318
Mean126.72175
Median Absolute Deviation (MAD)0.0118629
Skewness-0.10808112
Sum4561.9831
Variance0.00019992521
MonotonicityNot monotonic
2023-12-12T09:30:45.070555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
126.7196654 1
 
2.8%
126.7085828 1
 
2.8%
126.7305877 1
 
2.8%
126.7312319 1
 
2.8%
126.7233497 1
 
2.8%
126.7226525 1
 
2.8%
126.7243654 1
 
2.8%
126.7333067 1
 
2.8%
126.740928 1
 
2.8%
126.7365841 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
126.6918518 1
2.8%
126.6998293 1
2.8%
126.700369 1
2.8%
126.7036362 1
2.8%
126.7055956 1
2.8%
126.7068668 1
2.8%
126.7068832 1
2.8%
126.7075175 1
2.8%
126.7085828 1
2.8%
126.7095158 1
2.8%
ValueCountFrequency (%)
126.7474476 1
2.8%
126.7440896 1
2.8%
126.7415421 1
2.8%
126.7413313 1
2.8%
126.740928 1
2.8%
126.7365841 1
2.8%
126.7356172 1
2.8%
126.7350036 1
2.8%
126.7333067 1
2.8%
126.7319019 1
2.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size420.0 B
Minimum2023-10-31 00:00:00
Maximum2023-10-31 00:00:00
2023-12-12T09:30:45.187516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:30:45.270878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T09:30:40.744684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:30:39.671404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:30:40.078758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:30:40.966067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:30:39.759543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:30:40.291361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:30:41.096266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:30:39.868130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:30:40.506861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:30:45.347679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호소재지위치설치위치행정동면수야간시간야간요금위도경도
관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지위치1.0001.0001.0001.0001.0001.0001.0001.0001.000
설치위치1.0001.0001.0000.8630.9770.0000.0000.9100.975
행정동1.0001.0000.8631.0000.1650.0000.0000.9530.871
면수1.0001.0000.9770.1651.0000.0000.0000.6060.412
야간시간1.0001.0000.0000.0000.0001.0000.6640.0000.000
야간요금1.0001.0000.0000.0000.0000.6641.0000.0000.000
위도1.0001.0000.9100.9530.6060.0000.0001.0000.522
경도1.0001.0000.9750.8710.4120.0000.0000.5221.000
2023-12-12T09:30:45.507442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
야간시간행정동야간요금
야간시간1.0000.0000.462
행정동0.0001.0000.000
야간요금0.4620.0001.000
2023-12-12T09:30:45.605695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면수위도경도행정동야간시간야간요금
면수1.000-0.3250.1360.0000.0000.000
위도-0.3251.000-0.2960.5650.0000.000
경도0.136-0.2961.0000.5030.0000.000
행정동0.0000.5650.5031.0000.0000.000
야간시간0.0000.0000.0000.0001.0000.462
야간요금0.0000.0000.0000.0000.4621.000

Missing values

2023-12-12T09:30:41.256913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:30:41.462299image/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

관리번호소재지위치설치위치행정동면수운영방법야간시간야간요금위도경도데이터기준일자
028237-01-01인천광역시 부평구 경원대로 1344번길부평역광장 옆부평1동32야간19:00~익일01:001000037.490143126.7196652023-10-31
128237-02-01인천광역시 부평구 동수북로 121남부고가교~부평역부평2동52야간19:00~익일01:001000037.489514126.7206512023-10-31
228237-02-02인천광역시 부평구 동수북로 36백운쌍굴~남부고가교부평2동65야간19:00~익일01:001000037.48774126.7144162023-10-31
328237-03-01인천광역시 부평구 동수북로 182182-294번지~백운쌍굴부평3동34야간19:00~익일01:001000037.484588126.7095162023-10-31
428237-03-02인천광역시 부평구 안남로 63번길13백운역쌍굴~경원대로부평3동60야간19:00~익일01:001000037.488907126.7125182023-10-31
528237-03-03인천광역시 부평구 마장로55번길브라운스톤백운@ 뒤부평3동13야간19:00~익일01:001000037.482663126.7068832023-10-31
628237-04-01인천광역시 부평구 신트리로 30<NA>부평4동47야간19:00~익일01:001000037.505751126.7249542023-10-31
728237-04-04인천광역시 부평구 신트리로 20-1<NA>부평4동13야간19:00~익일01:001000037.506125126.723012023-10-31
828237-04-06인천광역시 부평구 신트리로 10<NA>부평4동13야간19:00~익일01:001000037.506285126.7218812023-10-31
928237-04-07인천광역시 부평구 신트리로 8번길공영주차장부평4동14야간18:00~익일09:002000037.505511126.7223192023-10-31
관리번호소재지위치설치위치행정동면수운영방법야간시간야간요금위도경도데이터기준일자
2628237-15-01인천광역시 부평구 부평북로 363삼산동62-6삼산1동41야간19:00~익일01:001000037.523034126.7333072023-10-31
2728237-17-05인천광역시 부평구 경인로1083번길번길 현대아파트담장주변부개1동22야간19:00~익일01:001000037.487963126.7409282023-10-31
2828237-17-06인천광역시 부평구 수변로19번길동원빌라~부개남부역부개1동67야간19:00~익일01:001000037.48854126.7365842023-10-31
2928237-17-07인천광역시 부평구 경인로1034번길경인로~동수로부개1동17야간19:00~익일01:001000037.486232126.7350042023-10-31
3028237-17-08인천광역시 부평구 항동로 3부개동254~주공아파트부개1동94야간19:00~익일01:001000037.484566126.7356172023-10-31
3128237-17-09인천광역시 부평구 경인로 1083번길부개역남부부개1동47야간19:00~익일01:001000037.488241126.7413312023-10-31
3228237-18-02인천광역시 부평구 수변로 52번길성일아파트 담장부개2동18야간19:00~익일01:001000037.491067126.7415422023-10-31
3328237-20-01인천광역시 부평구 서촌로4일신동 103번지 공영주차장일신동6야간19:00~익일01:001000037.485151126.7474482023-10-31
3428237-20-02인천광역시 부평구 항동로 46번길 30주공아파트~무네미로일신동81야간19:00~익일01:001000037.48181126.744092023-10-31
3528237-22-01인천광역시 부평구 아트센터로 48-1동암마을 주차장십정2동19야간19:00~익일01:001000037.472473126.7036362023-10-31