Overview

Dataset statistics

Number of variables15
Number of observations45
Missing cells45
Missing cells (%)6.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory129.9 B

Variable types

Categorical8
Numeric5
Text1
Unsupported1

Dataset

Description경기도 화성시_자전거보관소에 대한 데이터로 지형지물부호, 관리번호, 행정읍면동, 도엽번호, 관리기관, 설치일자, 보관대수, 대장초기화여부, 비고, 도로구간번호, 공사번호, 납품업체, 로딩일자, X좌표, Y좌표 등의 항목을 제공합니다.
Author경기도 화성시
URLhttps://www.data.go.kr/data/15093547/fileData.do

Alerts

지형지물부호 has constant value ""Constant
대장초기화여부 has constant value ""Constant
공사번호 has constant value ""Constant
행정읍면동 is highly overall correlated with 관리번호 and 7 other fieldsHigh correlation
설치일자 is highly overall correlated with 관리번호 and 7 other fieldsHigh correlation
납품업체 is highly overall correlated with 관리번호 and 5 other fieldsHigh correlation
로딩일자 is highly overall correlated with 관리번호 and 7 other fieldsHigh correlation
관리번호 is highly overall correlated with 행정읍면동 and 4 other fieldsHigh correlation
보관대수 is highly overall correlated with 비고High correlation
도로구간번호 is highly overall correlated with 행정읍면동 and 4 other fieldsHigh correlation
X좌표 is highly overall correlated with Y좌표 and 3 other fieldsHigh correlation
Y좌표 is highly overall correlated with X좌표 and 3 other fieldsHigh correlation
비고 is highly overall correlated with 관리번호 and 6 other fieldsHigh correlation
납품업체 is highly imbalanced (63.2%)Imbalance
관리기관 has 45 (100.0%) missing valuesMissing
X좌표 has unique valuesUnique
Y좌표 has unique valuesUnique
관리기관 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 15:42:01.762885
Analysis finished2023-12-12 15:42:05.154521
Duration3.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지형지물부호
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
자전거보관소
45 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
자전거보관소 45
100.0%

Length

2023-12-13T00:42:05.247428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:42:05.398034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자전거보관소 45
100.0%

관리번호
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.277771 × 1012
Minimum100001
Maximum9 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-13T00:42:05.576589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100001
5-th percentile411002.2
Q1411011
median411023
Q3500004
95-th percentile9 × 1013
Maximum9 × 1013
Range9 × 1013
Interquartile range (IQR)88993

Descriptive statistics

Standard deviation2.5876886 × 1013
Coefficient of variation (CV)3.1260694
Kurtosis7.1600048
Mean8.277771 × 1012
Median Absolute Deviation (MAD)16
Skewness2.9656948
Sum3.724997 × 1014
Variance6.6961324 × 1026
MonotonicityNot monotonic
2023-12-13T00:42:05.784085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
90000000000000 4
 
8.9%
411025 1
 
2.2%
411007 1
 
2.2%
411001 1
 
2.2%
411026 1
 
2.2%
411021 1
 
2.2%
411019 1
 
2.2%
411011 1
 
2.2%
411002 1
 
2.2%
411009 1
 
2.2%
Other values (32) 32
71.1%
ValueCountFrequency (%)
100001 1
2.2%
411001 1
2.2%
411002 1
2.2%
411003 1
2.2%
411004 1
2.2%
411005 1
2.2%
411006 1
2.2%
411007 1
2.2%
411008 1
2.2%
411009 1
2.2%
ValueCountFrequency (%)
90000000000000 4
8.9%
12100000000000 1
 
2.2%
99920171004 1
 
2.2%
99920171003 1
 
2.2%
99920171002 1
 
2.2%
99920171001 1
 
2.2%
500006 1
 
2.2%
500005 1
 
2.2%
500004 1
 
2.2%
500003 1
 
2.2%

행정읍면동
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
동탄1동
20 
동탄3동
5 
동탄2동
4 
송산면
4 
<NA>
4 
Other values (4)
8 

Length

Max length4
Median length4
Mean length3.7333333
Min length3

Unique

Unique2 ?
Unique (%)4.4%

Sample

1st row동탄3동
2nd row동탄3동
3rd row동탄3동
4th row동탄3동
5th row동탄3동

Common Values

ValueCountFrequency (%)
동탄1동 20
44.4%
동탄3동 5
 
11.1%
동탄2동 4
 
8.9%
송산면 4
 
8.9%
<NA> 4
 
8.9%
반월동 3
 
6.7%
봉담읍 3
 
6.7%
진안동 1
 
2.2%
화산동 1
 
2.2%

Length

2023-12-13T00:42:05.939331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:42:06.108385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동탄1동 20
44.4%
동탄3동 5
 
11.1%
동탄2동 4
 
8.9%
송산면 4
 
8.9%
na 4
 
8.9%
반월동 3
 
6.7%
봉담읍 3
 
6.7%
진안동 1
 
2.2%
화산동 1
 
2.2%

도엽번호
Text

Distinct29
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-13T00:42:06.350332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters450
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)37.8%

Sample

1st row377130292D
2nd row377130281D
3rd row377130282D
4th row377130283C
5th row377130283A
ValueCountFrequency (%)
377130710a 4
 
8.9%
376122211b 4
 
8.9%
377130286c 2
 
4.4%
377130705a 2
 
4.4%
377130295b 2
 
4.4%
377130285c 2
 
4.4%
376160460d 2
 
4.4%
377130283c 2
 
4.4%
377130292d 2
 
4.4%
377130234c 2
 
4.4%
Other values (19) 21
46.7%
2023-12-13T00:42:06.801350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 93
20.7%
3 91
20.2%
1 59
13.1%
0 53
11.8%
2 44
9.8%
6 25
 
5.6%
8 16
 
3.6%
C 13
 
2.9%
B 12
 
2.7%
A 11
 
2.4%
Other values (4) 33
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 405
90.0%
Uppercase Letter 45
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 93
23.0%
3 91
22.5%
1 59
14.6%
0 53
13.1%
2 44
10.9%
6 25
 
6.2%
8 16
 
4.0%
5 10
 
2.5%
4 7
 
1.7%
9 7
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
C 13
28.9%
B 12
26.7%
A 11
24.4%
D 9
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 405
90.0%
Latin 45
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 93
23.0%
3 91
22.5%
1 59
14.6%
0 53
13.1%
2 44
10.9%
6 25
 
6.2%
8 16
 
4.0%
5 10
 
2.5%
4 7
 
1.7%
9 7
 
1.7%
Latin
ValueCountFrequency (%)
C 13
28.9%
B 12
26.7%
A 11
24.4%
D 9
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 93
20.7%
3 91
20.2%
1 59
13.1%
0 53
11.8%
2 44
9.8%
6 25
 
5.6%
8 16
 
3.6%
C 13
 
2.9%
B 12
 
2.7%
A 11
 
2.4%
Other values (4) 33
 
7.3%

관리기관
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

설치일자
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
2007-12-01
30 
1900-01-01
7 
2017-01-01
4 
2016-01-01
4 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2007-12-01
2nd row2007-12-01
3rd row2007-12-01
4th row2007-12-01
5th row2007-12-01

Common Values

ValueCountFrequency (%)
2007-12-01 30
66.7%
1900-01-01 7
 
15.6%
2017-01-01 4
 
8.9%
2016-01-01 4
 
8.9%

Length

2023-12-13T00:42:07.008251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:42:07.168897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2007-12-01 30
66.7%
1900-01-01 7
 
15.6%
2017-01-01 4
 
8.9%
2016-01-01 4
 
8.9%

보관대수
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4888889
Minimum4
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-13T00:42:07.306745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile4.4
Q16
median6
Q310
95-th percentile10
Maximum12
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.2014687
Coefficient of variation (CV)0.29396467
Kurtosis-1.0994811
Mean7.4888889
Median Absolute Deviation (MAD)1
Skewness0.43689057
Sum337
Variance4.8464646
MonotonicityNot monotonic
2023-12-13T00:42:07.446268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
6 22
48.9%
10 13
28.9%
7 3
 
6.7%
4 3
 
6.7%
12 2
 
4.4%
9 2
 
4.4%
ValueCountFrequency (%)
4 3
 
6.7%
6 22
48.9%
7 3
 
6.7%
9 2
 
4.4%
10 13
28.9%
12 2
 
4.4%
ValueCountFrequency (%)
12 2
 
4.4%
10 13
28.9%
9 2
 
4.4%
7 3
 
6.7%
6 22
48.9%
4 3
 
6.7%

대장초기화여부
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
1
45 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 45
100.0%

Length

2023-12-13T00:42:07.602532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:42:07.742259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 45
100.0%

비고
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size492.0 B
버스정류장
17 
11 
공원
4 
송산그린시티 기반시설 건설공사 도로 및 지하매설물 GIS D/B 구축용역(20171229)
4 
동사무소옆
2 
Other values (7)
7 

Length

Max length50
Median length42
Mean length8.5333333
Min length1

Unique

Unique7 ?
Unique (%)15.6%

Sample

1st row버스정류장
2nd row두산APT
3rd row공원
4th row버스정류장
5th row한솔프라자

Common Values

ValueCountFrequency (%)
버스정류장 17
37.8%
11
24.4%
공원 4
 
8.9%
송산그린시티 기반시설 건설공사 도로 및 지하매설물 GIS D/B 구축용역(20171229) 4
 
8.9%
동사무소옆 2
 
4.4%
두산APT 1
 
2.2%
한솔프라자 1
 
2.2%
반월,기산지구 시가화예정구역 도로 및 하수관거 정비사업 GIS DB 구축용역 1
 
2.2%
교차로 1
 
2.2%
기업은행 1
 
2.2%
Other values (2) 2
 
4.4%

Length

2023-12-13T00:42:07.880480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
버스정류장 17
23.0%
도로 5
 
6.8%
및 5
 
6.8%
gis 5
 
6.8%
건설공사 4
 
5.4%
기반시설 4
 
5.4%
송산그린시티 4
 
5.4%
지하매설물 4
 
5.4%
d/b 4
 
5.4%
구축용역(20171229 4
 
5.4%
Other values (14) 18
24.3%

도로구간번호
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.2796203 × 1012
Minimum1.104321 × 109
Maximum9 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-13T00:42:08.046089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.104321 × 109
5-th percentile1.3315911 × 109
Q12.200119 × 109
median2.300119 × 109
Q32.709219 × 109
95-th percentile9 × 1013
Maximum9 × 1013
Range8.9998896 × 1013
Interquartile range (IQR)5.0909999 × 108

Descriptive statistics

Standard deviation2.5876281 × 1013
Coefficient of variation (CV)3.1252981
Kurtosis7.1600357
Mean8.2796203 × 1012
Median Absolute Deviation (MAD)1.9979999 × 108
Skewness2.9657019
Sum3.7258292 × 1014
Variance6.6958193 × 1026
MonotonicityNot monotonic
2023-12-13T00:42:08.182681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2200619001 5
 
11.1%
90000000000000 4
 
8.9%
99920171019 4
 
8.9%
2300119002 2
 
4.4%
2300119003 2
 
4.4%
2300119005 2
 
4.4%
1104321043 2
 
4.4%
1331831003 2
 
4.4%
2100119004 2
 
4.4%
2300419003 2
 
4.4%
Other values (17) 18
40.0%
ValueCountFrequency (%)
1104321043 2
4.4%
1331531063 1
2.2%
1331831003 2
4.4%
2100119004 2
4.4%
2100219007 1
2.2%
2100319004 1
2.2%
2100319015 1
2.2%
2200119005 1
2.2%
2200119013 1
2.2%
2200119017 1
2.2%
ValueCountFrequency (%)
90000000000000 4
8.9%
12100000000000 1
 
2.2%
99920171019 4
8.9%
9000921003 1
 
2.2%
2709819001 1
 
2.2%
2709219001 1
 
2.2%
2600831004 1
 
2.2%
2401519003 1
 
2.2%
2300419003 2
4.4%
2300119007 1
 
2.2%

공사번호
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
45 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
45
100.0%

Length

2023-12-13T00:42:08.318824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:42:08.461653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

납품업체
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size492.0 B
40 
새한항업
 
4
㈜진성이엔씨
 
1

Length

Max length6
Median length1
Mean length1.3777778
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
40
88.9%
새한항업 4
 
8.9%
㈜진성이엔씨 1
 
2.2%

Length

2023-12-13T00:42:08.597258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:42:08.744483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
새한항업 4
80.0%
㈜진성이엔씨 1
 
20.0%

로딩일자
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Memory size492.0 B
36 
2017-12-29
4 
2019-01-05
4 
2018-05-25
 
1

Length

Max length10
Median length1
Mean length2.8
Min length1

Unique

Unique1 ?
Unique (%)2.2%

Sample

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

Common Values

ValueCountFrequency (%)
36
80.0%
2017-12-29 4
 
8.9%
2019-01-05 4
 
8.9%
2018-05-25 1
 
2.2%

Length

2023-12-13T00:42:08.896345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:42:09.022553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017-12-29 4
44.4%
2019-01-05 4
44.4%
2018-05-25 1
 
11.1%

X좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean203360.36
Minimum182661.57
Maximum208527.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-13T00:42:09.151408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182661.57
5-th percentile182699.98
Q1205269.4
median205956.21
Q3206790.22
95-th percentile208516.56
Maximum208527.65
Range25866.079
Interquartile range (IQR)1520.824

Descriptive statistics

Standard deviation7200.4242
Coefficient of variation (CV)0.035407216
Kurtosis4.0382294
Mean203360.36
Median Absolute Deviation (MAD)802.861
Skewness-2.265183
Sum9151216.2
Variance51846109
MonotonicityNot monotonic
2023-12-13T00:42:09.284026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
205269.398 1
 
2.2%
182661.57 1
 
2.2%
205292.739 1
 
2.2%
205358.823 1
 
2.2%
205447.621 1
 
2.2%
205752.886 1
 
2.2%
205480.191 1
 
2.2%
206226.283 1
 
2.2%
205956.211 1
 
2.2%
206531.689 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
182661.57 1
2.2%
182661.76 1
2.2%
182699.981 1
2.2%
182699.986 1
2.2%
195510.221 1
2.2%
195513.948 1
2.2%
195537.071 1
2.2%
199050.567 1
2.2%
204601.598 1
2.2%
204665.726 1
2.2%
ValueCountFrequency (%)
208527.649 1
2.2%
208523.375 1
2.2%
208517.077 1
2.2%
208514.495 1
2.2%
207083.315 1
2.2%
207046.999 1
2.2%
207045.978 1
2.2%
206884.151 1
2.2%
206874.847 1
2.2%
206872.694 1
2.2%

Y좌표
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean512980.85
Minimum510744.99
Maximum521640.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-13T00:42:09.432879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum510744.99
5-th percentile510842.46
Q1511480.57
median512000.31
Q3513348.39
95-th percentile521626.34
Maximum521640.24
Range10895.255
Interquartile range (IQR)1867.824

Descriptive statistics

Standard deviation2926.2571
Coefficient of variation (CV)0.0057044179
Kurtosis4.8319422
Mean512980.85
Median Absolute Deviation (MAD)768.962
Skewness2.374714
Sum23084138
Variance8562980.8
MonotonicityNot monotonic
2023-12-13T00:42:09.561286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
511231.351 1
 
2.2%
521639.989 1
 
2.2%
511291.522 1
 
2.2%
512000.313 1
 
2.2%
512215.96 1
 
2.2%
512029.669 1
 
2.2%
511570.956 1
 
2.2%
511101.272 1
 
2.2%
511480.565 1
 
2.2%
511490.101 1
 
2.2%
Other values (35) 35
77.8%
ValueCountFrequency (%)
510744.988 1
2.2%
510782.011 1
2.2%
510783.323 1
2.2%
511079.026 1
2.2%
511101.272 1
2.2%
511110.043 1
2.2%
511110.053 1
2.2%
511129.516 1
2.2%
511134.442 1
2.2%
511231.351 1
2.2%
ValueCountFrequency (%)
521640.243 1
2.2%
521639.989 1
2.2%
521626.344 1
2.2%
521626.334 1
2.2%
515140.802 1
2.2%
514650.904 1
2.2%
514646.886 1
2.2%
513930.192 1
2.2%
513451.53 1
2.2%
513448.399 1
2.2%

Interactions

2023-12-13T00:42:04.314834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:02.264015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:02.705956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:03.157789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:03.610524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:04.397874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:02.343262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:02.791673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:03.245129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:03.993279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:04.495885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:02.455157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:02.885191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:03.346654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:04.078235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:04.586601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:02.537637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:02.975269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:03.431165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:04.159685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:04.695247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:02.628165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:03.066028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:03.526278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:42:04.227980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:42:09.655810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호행정읍면동도엽번호설치일자보관대수비고도로구간번호납품업체로딩일자X좌표Y좌표
관리번호1.0001.0001.0000.6580.5260.9511.0001.0001.0000.0000.465
행정읍면동1.0001.0000.9831.0000.5810.8441.0001.0001.0000.9500.849
도엽번호1.0000.9831.0001.0001.0000.9831.0001.0001.0001.0001.000
설치일자0.6581.0001.0001.0000.6150.9610.6570.6580.9790.7620.854
보관대수0.5260.5811.0000.6151.0000.9920.5830.4690.2240.3130.000
비고0.9510.8440.9830.9610.9921.0000.9590.9440.9830.6870.739
도로구간번호1.0001.0001.0000.6570.5830.9591.0001.0001.0000.0000.597
납품업체1.0001.0001.0000.6580.4690.9441.0001.0001.0000.0000.481
로딩일자1.0001.0001.0000.9790.2240.9831.0001.0001.0000.6310.763
X좌표0.0000.9501.0000.7620.3130.6870.0000.0000.6311.0000.717
Y좌표0.4650.8491.0000.8540.0000.7390.5970.4810.7630.7171.000
2023-12-13T00:42:09.774189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정읍면동설치일자납품업체로딩일자비고
행정읍면동1.0000.9320.9200.9320.516
설치일자0.9321.0000.6760.8030.669
납품업체0.9200.6761.0000.9880.647
로딩일자0.9320.8030.9881.0000.743
비고0.5160.6690.6470.7431.000
2023-12-13T00:42:09.880564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호보관대수도로구간번호X좌표Y좌표행정읍면동설치일자비고납품업체로딩일자
관리번호1.0000.4660.441-0.1650.2120.9200.6760.6471.0000.988
보관대수0.4661.0000.166-0.1530.1280.3540.4320.7940.2050.133
도로구간번호0.4410.1661.000-0.072-0.1950.9200.6760.6471.0000.988
X좌표-0.165-0.153-0.0721.000-0.5500.8870.7020.4260.0000.553
Y좌표0.2120.128-0.195-0.5501.0000.6710.6980.3530.2010.584
행정읍면동0.9200.3540.9200.8870.6711.0000.9320.5160.9200.932
설치일자0.6760.4320.6760.7020.6980.9321.0000.6690.6760.803
비고0.6470.7940.6470.4260.3530.5160.6691.0000.6470.743
납품업체1.0000.2051.0000.0000.2010.9200.6760.6471.0000.988
로딩일자0.9880.1330.9880.5530.5840.9320.8030.7430.9881.000

Missing values

2023-12-13T00:42:04.841227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:42:05.059254image/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

지형지물부호관리번호행정읍면동도엽번호관리기관설치일자보관대수대장초기화여부비고도로구간번호공사번호납품업체로딩일자X좌표Y좌표
0자전거보관소411025동탄3동377130292D<NA>2007-12-0161버스정류장2300119002205269.398511231.351
1자전거보관소411024동탄3동377130281D<NA>2007-12-01121두산APT2401519003204665.726511842.597
2자전거보관소411023동탄3동377130282D<NA>2007-12-01121공원2300119003205262.823511805.229
3자전거보관소411022동탄3동377130283C<NA>2007-12-0161버스정류장2300119005205338.25512015.629
4자전거보관소411020동탄3동377130283A<NA>2007-12-0191한솔프라자2200319014205430.4512255.714
5자전거보관소12100000000000진안동377130261A<NA>2007-12-01101반월,기산지구 시가화예정구역 도로 및 하수관거 정비사업 GIS DB 구축용역12100000000000㈜진성이엔씨2018-05-25204601.598513348.389
6자전거보관소500001반월동377130223C<NA>1900-01-011011331531063205500.063515140.802
7자전거보관소500002반월동377130234C<NA>1900-01-011011331831003205903.37514646.886
8자전거보관소500003반월동377130234C<NA>1900-01-011011331831003205905.15514650.904
9자전거보관소100001화산동376160588B<NA>1900-01-011019000921003199050.567512089.161
지형지물부호관리번호행정읍면동도엽번호관리기관설치일자보관대수대장초기화여부비고도로구간번호공사번호납품업체로딩일자X좌표Y좌표
35자전거보관소99920171003송산면376122211B<NA>2017-01-0161송산그린시티 기반시설 건설공사 도로 및 지하매설물 GIS D/B 구축용역(20171229)999201710192017-12-29182661.76521626.344
36자전거보관소99920171002송산면376122211B<NA>2017-01-0161송산그린시티 기반시설 건설공사 도로 및 지하매설물 GIS D/B 구축용역(20171229)999201710192017-12-29182699.986521626.334
37자전거보관소99920171001송산면376122211B<NA>2017-01-0161송산그린시티 기반시설 건설공사 도로 및 지하매설물 GIS D/B 구축용역(20171229)999201710192017-12-29182699.981521640.243
38자전거보관소500006봉담읍376160460D<NA>1900-01-011011104321043195513.948513451.53
39자전거보관소500004봉담읍376160470B<NA>1900-01-011012600831004195537.071513370.922
40자전거보관소500005봉담읍376160460D<NA>1900-01-011011104321043195510.221513448.399
41자전거보관소90000000000000<NA>377130710A<NA>2016-01-0110190000000000000새한항업2019-01-05208517.077511129.516
42자전거보관소90000000000000<NA>377130710A<NA>2016-01-0110190000000000000새한항업2019-01-05208514.495511134.442
43자전거보관소90000000000000<NA>377130710A<NA>2016-01-0110190000000000000새한항업2019-01-05208527.649511110.043
44자전거보관소90000000000000<NA>377130710A<NA>2016-01-0110190000000000000새한항업2019-01-05208523.375511110.053