Overview

Dataset statistics

Number of variables8
Number of observations83
Missing cells64
Missing cells (%)9.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory68.6 B

Variable types

Numeric3
Text4
DateTime1

Dataset

Description경기도 시흥시 스마트교차로 현황입니다.(시흥시 스마트교차로 현황에는 현장번호, 스마트교차로명, 스마트 교차로 주소, 위도, 경도가 있습니다),
Author경기도 시흥시
URLhttps://www.data.go.kr/data/15090289/fileData.do

Alerts

데이터기준일 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
스마트 교차로 주소(도로명) has 64 (77.1%) missing valuesMissing
연번 has unique valuesUnique
현장번호 has unique valuesUnique
스마트 교차로명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:34:30.472563
Analysis finished2023-12-12 16:34:31.969069
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42
Minimum1
Maximum83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2023-12-13T01:34:32.033581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.1
Q121.5
median42
Q362.5
95-th percentile78.9
Maximum83
Range82
Interquartile range (IQR)41

Descriptive statistics

Standard deviation24.103942
Coefficient of variation (CV)0.57390337
Kurtosis-1.2
Mean42
Median Absolute Deviation (MAD)21
Skewness0
Sum3486
Variance581
MonotonicityStrictly increasing
2023-12-13T01:34:32.144848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
54 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
Other values (73) 73
88.0%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%

현장번호
Text

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-13T01:34:32.381720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters498
Distinct characters14
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

Unique83 ?
Unique (%)100.0%

Sample

1st row스마트_01
2nd row스마트_02
3rd row스마트_03
4th row스마트_04
5th row스마트_05
ValueCountFrequency (%)
스마트_01 1
 
1.2%
스마트_43 1
 
1.2%
스마트_61 1
 
1.2%
스마트_60 1
 
1.2%
스마트_59 1
 
1.2%
스마트_58 1
 
1.2%
스마트_57 1
 
1.2%
스마트_56 1
 
1.2%
스마트_55 1
 
1.2%
스마트_54 1
 
1.2%
Other values (73) 73
88.0%
2023-12-13T01:34:32.734043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 83
16.7%
마 83
16.7%
트 83
16.7%
_ 83
16.7%
1 19
 
3.8%
2 19
 
3.8%
3 19
 
3.8%
4 18
 
3.6%
5 18
 
3.6%
6 18
 
3.6%
Other values (4) 55
11.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 249
50.0%
Decimal Number 166
33.3%
Connector Punctuation 83
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
11.4%
2 19
11.4%
3 19
11.4%
4 18
10.8%
5 18
10.8%
6 18
10.8%
7 18
10.8%
0 17
10.2%
8 12
7.2%
9 8
4.8%
Other Letter
ValueCountFrequency (%)
스 83
33.3%
마 83
33.3%
트 83
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 249
50.0%
Common 249
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 83
33.3%
1 19
 
7.6%
2 19
 
7.6%
3 19
 
7.6%
4 18
 
7.2%
5 18
 
7.2%
6 18
 
7.2%
7 18
 
7.2%
0 17
 
6.8%
8 12
 
4.8%
Hangul
ValueCountFrequency (%)
스 83
33.3%
마 83
33.3%
트 83
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 249
50.0%
ASCII 249
50.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 83
33.3%
마 83
33.3%
트 83
33.3%
ASCII
ValueCountFrequency (%)
_ 83
33.3%
1 19
 
7.6%
2 19
 
7.6%
3 19
 
7.6%
4 18
 
7.2%
5 18
 
7.2%
6 18
 
7.2%
7 18
 
7.2%
0 17
 
6.8%
8 12
 
4.8%

스마트 교차로명
Text

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-13T01:34:32.928846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length6.9879518
Min length4

Characters and Unicode

Total characters580
Distinct characters144
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)100.0%

Sample

1st row봉우제삼거리
2nd row보도2교
3rd row어린이도서관
4th row동원아파트앞
5th row거모사거리
ValueCountFrequency (%)
3r 18
 
14.2%
4r 12
 
9.4%
사거리 8
 
6.3%
삼거리 5
 
3.9%
동남아파트 2
 
1.6%
외곽3교 1
 
0.8%
대야교차로 1
 
0.8%
안현교차로 1
 
0.8%
체육공원 1
 
0.8%
네이처포레 1
 
0.8%
Other values (77) 77
60.6%
2023-12-13T01:34:33.276042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44
 
7.6%
거 34
 
5.9%
리 33
 
5.7%
R 30
 
5.2%
사 26
 
4.5%
교 22
 
3.8%
3 19
 
3.3%
차 14
 
2.4%
4 13
 
2.2%
로 11
 
1.9%
Other values (134) 334
57.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 444
76.6%
Decimal Number 56
 
9.7%
Space Separator 44
 
7.6%
Uppercase Letter 32
 
5.5%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
거 34
 
7.7%
리 33
 
7.4%
사 26
 
5.9%
교 22
 
5.0%
차 14
 
3.2%
로 11
 
2.5%
동 10
 
2.3%
트 10
 
2.3%
서 9
 
2.0%
구 8
 
1.8%
Other values (120) 267
60.1%
Decimal Number
ValueCountFrequency (%)
3 19
33.9%
4 13
23.2%
2 9
16.1%
1 7
 
12.5%
0 3
 
5.4%
6 2
 
3.6%
9 2
 
3.6%
5 1
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
R 30
93.8%
I 1
 
3.1%
C 1
 
3.1%
Space Separator
ValueCountFrequency (%)
44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 444
76.6%
Common 104
 
17.9%
Latin 32
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
거 34
 
7.7%
리 33
 
7.4%
사 26
 
5.9%
교 22
 
5.0%
차 14
 
3.2%
로 11
 
2.5%
동 10
 
2.3%
트 10
 
2.3%
서 9
 
2.0%
구 8
 
1.8%
Other values (120) 267
60.1%
Common
ValueCountFrequency (%)
44
42.3%
3 19
18.3%
4 13
 
12.5%
2 9
 
8.7%
1 7
 
6.7%
0 3
 
2.9%
6 2
 
1.9%
9 2
 
1.9%
) 2
 
1.9%
( 2
 
1.9%
Latin
ValueCountFrequency (%)
R 30
93.8%
I 1
 
3.1%
C 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 444
76.6%
ASCII 136
 
23.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44
32.4%
R 30
22.1%
3 19
14.0%
4 13
 
9.6%
2 9
 
6.6%
1 7
 
5.1%
0 3
 
2.2%
6 2
 
1.5%
9 2
 
1.5%
) 2
 
1.5%
Other values (4) 5
 
3.7%
Hangul
ValueCountFrequency (%)
거 34
 
7.7%
리 33
 
7.4%
사 26
 
5.9%
교 22
 
5.0%
차 14
 
3.2%
로 11
 
2.5%
동 10
 
2.3%
트 10
 
2.3%
서 9
 
2.0%
구 8
 
1.8%
Other values (120) 267
60.1%

스마트 교차로 주소(도로명)
Text

MISSING 

Distinct16
Distinct (%)84.2%
Missing64
Missing (%)77.1%
Memory size796.0 B
2023-12-13T01:34:33.439347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length22.894737
Min length21

Characters and Unicode

Total characters435
Distinct characters48
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)73.7%

Sample

1st row경기도 시흥시 마유로 376, (정왕동)
2nd row경기도 시흥시 서해안로 551, (정왕동)
3rd row경기도 시흥시 황고개로 179, (거모동)
4th row경기도 시흥시 역전로 249, (정왕동)
5th row경기도 시흥시 마유로 435, (정왕동)
ValueCountFrequency (%)
경기도 19
19.8%
시흥시 19
19.8%
정왕동 15
15.6%
정왕대로 6
 
6.2%
마유로 5
 
5.2%
355 3
 
3.1%
역전로 2
 
2.1%
62 2
 
2.1%
서해안로 2
 
2.1%
호현로 1
 
1.0%
Other values (22) 22
22.9%
2023-12-13T01:34:33.727163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
77
17.7%
시 38
 
8.7%
정 23
 
5.3%
왕 22
 
5.1%
경 19
 
4.4%
, 19
 
4.4%
기 19
 
4.4%
동 19
 
4.4%
( 19
 
4.4%
) 19
 
4.4%
Other values (38) 161
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
55.9%
Space Separator 77
 
17.7%
Decimal Number 57
 
13.1%
Other Punctuation 19
 
4.4%
Open Punctuation 19
 
4.4%
Close Punctuation 19
 
4.4%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 38
15.6%
정 23
9.5%
왕 22
9.1%
경 19
7.8%
기 19
7.8%
동 19
7.8%
도 19
7.8%
로 19
7.8%
흥 19
7.8%
대 8
 
3.3%
Other values (23) 38
15.6%
Decimal Number
ValueCountFrequency (%)
5 10
17.5%
3 9
15.8%
2 9
15.8%
1 7
12.3%
6 6
10.5%
7 4
 
7.0%
8 4
 
7.0%
4 3
 
5.3%
0 3
 
5.3%
9 2
 
3.5%
Space Separator
ValueCountFrequency (%)
77
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 243
55.9%
Common 192
44.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 38
15.6%
정 23
9.5%
왕 22
9.1%
경 19
7.8%
기 19
7.8%
동 19
7.8%
도 19
7.8%
로 19
7.8%
흥 19
7.8%
대 8
 
3.3%
Other values (23) 38
15.6%
Common
ValueCountFrequency (%)
77
40.1%
, 19
 
9.9%
( 19
 
9.9%
) 19
 
9.9%
5 10
 
5.2%
3 9
 
4.7%
2 9
 
4.7%
1 7
 
3.6%
6 6
 
3.1%
7 4
 
2.1%
Other values (5) 13
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 243
55.9%
ASCII 192
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
77
40.1%
, 19
 
9.9%
( 19
 
9.9%
) 19
 
9.9%
5 10
 
5.2%
3 9
 
4.7%
2 9
 
4.7%
1 7
 
3.6%
6 6
 
3.1%
7 4
 
2.1%
Other values (5) 13
 
6.8%
Hangul
ValueCountFrequency (%)
시 38
15.6%
정 23
9.5%
왕 22
9.1%
경 19
7.8%
기 19
7.8%
동 19
7.8%
도 19
7.8%
로 19
7.8%
흥 19
7.8%
대 8
 
3.3%
Other values (23) 38
15.6%

스마트 교차로 주소(지번)
Text

Distinct71
Distinct (%)85.5%
Missing0
Missing (%)0.0%
Memory size796.0 B
2023-12-13T01:34:33.991315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length16.638554
Min length15

Characters and Unicode

Total characters1381
Distinct characters56
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 (%)75.9%

Sample

1st row경기도 시흥시 정왕동 산119-47
2nd row경기도 시흥시 정왕동 1800-3
3rd row경기도 시흥시 정왕동 1632
4th row경기도 시흥시 정왕동 1776
5th row경기도 시흥시 거모동 1379-2
ValueCountFrequency (%)
경기도 83
24.9%
시흥시 83
24.9%
정왕동 44
13.2%
월곶동 6
 
1.8%
대야동 4
 
1.2%
배곧동 4
 
1.2%
1795 3
 
0.9%
1890 3
 
0.9%
신천동 3
 
0.9%
1631 3
 
0.9%
Other values (86) 97
29.1%
2023-12-13T01:34:34.393441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
250
18.1%
시 166
12.0%
1 84
 
6.1%
도 84
 
6.1%
경 83
 
6.0%
흥 83
 
6.0%
기 83
 
6.0%
동 82
 
5.9%
왕 46
 
3.3%
정 45
 
3.3%
Other values (46) 375
27.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 752
54.5%
Decimal Number 341
24.7%
Space Separator 250
 
18.1%
Dash Punctuation 38
 
2.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 166
22.1%
도 84
11.2%
경 83
11.0%
흥 83
11.0%
기 83
11.0%
동 82
10.9%
왕 46
 
6.1%
정 45
 
6.0%
산 7
 
0.9%
월 6
 
0.8%
Other values (34) 67
8.9%
Decimal Number
ValueCountFrequency (%)
1 84
24.6%
2 38
11.1%
3 35
10.3%
9 32
 
9.4%
0 29
 
8.5%
7 29
 
8.5%
8 25
 
7.3%
5 24
 
7.0%
6 24
 
7.0%
4 21
 
6.2%
Space Separator
ValueCountFrequency (%)
250
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 752
54.5%
Common 629
45.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 166
22.1%
도 84
11.2%
경 83
11.0%
흥 83
11.0%
기 83
11.0%
동 82
10.9%
왕 46
 
6.1%
정 45
 
6.0%
산 7
 
0.9%
월 6
 
0.8%
Other values (34) 67
8.9%
Common
ValueCountFrequency (%)
250
39.7%
1 84
 
13.4%
- 38
 
6.0%
2 38
 
6.0%
3 35
 
5.6%
9 32
 
5.1%
0 29
 
4.6%
7 29
 
4.6%
8 25
 
4.0%
5 24
 
3.8%
Other values (2) 45
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 752
54.5%
ASCII 629
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
250
39.7%
1 84
 
13.4%
- 38
 
6.0%
2 38
 
6.0%
3 35
 
5.6%
9 32
 
5.1%
0 29
 
4.6%
7 29
 
4.6%
8 25
 
4.0%
5 24
 
3.8%
Other values (2) 45
 
7.2%
Hangul
ValueCountFrequency (%)
시 166
22.1%
도 84
11.2%
경 83
11.0%
흥 83
11.0%
기 83
11.0%
동 82
10.9%
왕 46
 
6.1%
정 45
 
6.0%
산 7
 
0.9%
월 6
 
0.8%
Other values (34) 67
8.9%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct82
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.373066
Minimum37.334269
Maximum37.459078
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2023-12-13T01:34:34.528513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.334269
5-th percentile37.340059
Q137.348452
median37.356264
Q337.388709
95-th percentile37.439691
Maximum37.459078
Range0.1248085
Interquartile range (IQR)0.040257015

Descriptive statistics

Standard deviation0.034241378
Coefficient of variation (CV)0.00091620466
Kurtosis-0.084731233
Mean37.373066
Median Absolute Deviation (MAD)0.0142413
Skewness1.0648875
Sum3101.9645
Variance0.0011724719
MonotonicityNot monotonic
2023-12-13T01:34:34.660584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3385178 2
 
2.4%
37.437367 1
 
1.2%
37.349931 1
 
1.2%
37.351951 1
 
1.2%
37.353361 1
 
1.2%
37.397492 1
 
1.2%
37.419586 1
 
1.2%
37.429245 1
 
1.2%
37.410167 1
 
1.2%
37.435129 1
 
1.2%
Other values (72) 72
86.7%
ValueCountFrequency (%)
37.3342694 1
1.2%
37.336732 1
1.2%
37.3385178 2
2.4%
37.34003617 1
1.2%
37.340263 1
1.2%
37.340968 1
1.2%
37.34128474 1
1.2%
37.342023 1
1.2%
37.342263 1
1.2%
37.34247317 1
1.2%
ValueCountFrequency (%)
37.4590779 1
1.2%
37.4504063 1
1.2%
37.4497241 1
1.2%
37.4475655 1
1.2%
37.43978819 1
1.2%
37.438818 1
1.2%
37.43875113 1
1.2%
37.437367 1
1.2%
37.4354614 1
1.2%
37.435129 1
1.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct82
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.76033
Minimum126.69262
Maximum126.86789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2023-12-13T01:34:34.814310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.69262
5-th percentile126.72018
Q1126.73402
median126.74815
Q3126.78785
95-th percentile126.82895
Maximum126.86789
Range0.1752695
Interquartile range (IQR)0.0538343

Descriptive statistics

Standard deviation0.03698982
Coefficient of variation (CV)0.00029180912
Kurtosis0.53706974
Mean126.76033
Median Absolute Deviation (MAD)0.0196835
Skewness0.99387209
Sum10521.107
Variance0.0013682468
MonotonicityNot monotonic
2023-12-13T01:34:34.975437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.7503779 2
 
2.4%
126.804498 1
 
1.2%
126.723388 1
 
1.2%
126.720139 1
 
1.2%
126.717755 1
 
1.2%
126.79597 1
 
1.2%
126.789498 1
 
1.2%
126.792008 1
 
1.2%
126.822467 1
 
1.2%
126.807568 1
 
1.2%
Other values (72) 72
86.7%
ValueCountFrequency (%)
126.6926174 1
1.2%
126.7062866 1
1.2%
126.717755 1
1.2%
126.718418 1
1.2%
126.720139 1
1.2%
126.7205322 1
1.2%
126.7228773 1
1.2%
126.723388 1
1.2%
126.725691 1
1.2%
126.7261123 1
1.2%
ValueCountFrequency (%)
126.8678869 1
1.2%
126.861912 1
1.2%
126.8525422 1
1.2%
126.846842 1
1.2%
126.8296704 1
1.2%
126.822467 1
1.2%
126.8214582 1
1.2%
126.8170855 1
1.2%
126.8089037 1
1.2%
126.807568 1
1.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
Minimum2023-11-27 00:00:00
Maximum2023-11-27 00:00:00
2023-12-13T01:34:35.094525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:35.195666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T01:34:31.441669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:30.888088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:31.162318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:31.558902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:30.971671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:31.255544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:31.660702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:31.064951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:34:31.344033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:34:35.265027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번현장번호스마트 교차로명스마트 교차로 주소(도로명)스마트 교차로 주소(지번)위도경도
연번1.0001.0001.0001.0000.9960.7430.766
현장번호1.0001.0001.0001.0001.0001.0001.000
스마트 교차로명1.0001.0001.0001.0001.0001.0001.000
스마트 교차로 주소(도로명)1.0001.0001.0001.0001.0001.0001.000
스마트 교차로 주소(지번)0.9961.0001.0001.0001.0000.9970.996
위도0.7431.0001.0001.0000.9971.0000.806
경도0.7661.0001.0001.0000.9960.8061.000
2023-12-13T01:34:35.359898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도
연번1.000-0.019-0.029
위도-0.0191.0000.555
경도-0.0290.5551.000

Missing values

2023-12-13T01:34:31.808873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:34:31.920485image/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

연번현장번호스마트 교차로명스마트 교차로 주소(도로명)스마트 교차로 주소(지번)위도경도데이터기준일
01스마트_01봉우제삼거리<NA>경기도 시흥시 정왕동 산119-4737.357516126.7439452023-11-27
12스마트_02보도2교경기도 시흥시 마유로 376, (정왕동)경기도 시흥시 정왕동 1800-337.34862126.7386422023-11-27
23스마트_03어린이도서관<NA>경기도 시흥시 정왕동 163237.343916126.7470382023-11-27
34스마트_04동원아파트앞경기도 시흥시 서해안로 551, (정왕동)경기도 시흥시 정왕동 177637.369213126.7356112023-11-27
45스마트_05거모사거리경기도 시흥시 황고개로 179, (거모동)경기도 시흥시 거모동 1379-237.348718126.7815412023-11-27
56스마트_06서해고사거리<NA>경기도 시흥시 정왕동 189337.364509126.7280132023-11-27
67스마트_07상곡교차로<NA>경기도 시흥시 월곶동 942-3037.383013126.7615992023-11-27
78스마트_08동보아파트<NA>경기도 시흥시 정왕동 213937.357837126.7184182023-11-27
89스마트_09군서중사거리(시화농협)경기도 시흥시 역전로 249, (정왕동)경기도 시흥시 정왕동 168437.345486126.7463582023-11-27
910스마트_10능곡사거리<NA>경기도 시흥시 능곡동 249-137.369892126.8089042023-11-27
연번현장번호스마트 교차로명스마트 교차로 주소(도로명)스마트 교차로 주소(지번)위도경도데이터기준일
7374스마트_74성당앞 3R<NA>경기도 시흥시 정왕동 189037.355486126.7364512023-11-27
7475스마트_75삼성부동산 4R<NA>경기도 시흥시 정왕동 192737.350133126.7440762023-11-27
7576스마트_76정왕농협 4R<NA>경기도 시흥시 정왕동 192737.348492126.7469932023-11-27
7677스마트_77군서초교앞 3R<NA>경기도 시흥시 정왕동 122037.347806126.7501762023-11-27
7778스마트_78외곽4교 4R<NA>경기도 시흥시 정왕동 122037.347231126.7549262023-11-27
7879스마트_79외곽3교 3R<NA>경기도 시흥시 정왕동 163137.342263126.7585132023-11-27
7980스마트_80체육공원 3R<NA>경기도 시흥시 정왕동 163137.340968126.7572632023-11-27
8081스마트_81신천IC 3R<NA>경기도 시흥시 방산동 19237.428748126.7740022023-11-27
8182스마트_82월곶교차로 3R<NA>경기도 시흥시 월곶동 520-3937.389987126.750142023-11-27
8283스마트_83수질보건센터 3R<NA>경기도 시흥시 산현동 15-637.378305126.8468422023-11-27