Overview

Dataset statistics

Number of variables9
Number of observations283
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.1 KiB
Average record size in memory76.5 B

Variable types

Text3
Numeric4
Categorical2

Dataset

Description버스안내정보 단말기 설치 현황에 대한 정보로 단말기 관리번호, 설치 정류소명, 설치 정류소 번호, 설치위치 주소, 지역, 설치연도, 장비유형, 위도, 경도 정보를 제공
Author경기도 이천시
URLhttps://www.data.go.kr/data/15009737/fileData.do

Alerts

설치연도 is highly overall correlated with 장비 유형High correlation
위도 is highly overall correlated with 지역High correlation
경도 is highly overall correlated with 지역High correlation
지역 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
장비 유형 is highly overall correlated with 설치연도High correlation
장비 유형 is highly imbalanced (68.7%)Imbalance
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:50:36.872935
Analysis finished2023-12-12 14:50:39.659648
Duration2.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct283
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-12T23:50:39.954096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters1981
Distinct characters13
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

Unique283 ?
Unique (%)100.0%

Sample

1st rowBIT0001
2nd rowBIT0002
3rd rowBIT0003
4th rowBIT0004
5th rowBIT0005
ValueCountFrequency (%)
bit0001 1
 
0.4%
bit0190 1
 
0.4%
bit0196 1
 
0.4%
bit0195 1
 
0.4%
bit0194 1
 
0.4%
bit0193 1
 
0.4%
bit0192 1
 
0.4%
bit0202 1
 
0.4%
bit0189 1
 
0.4%
bit0198 1
 
0.4%
Other values (273) 273
96.5%
2023-12-12T23:50:40.524894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 435
22.0%
B 283
14.3%
I 283
14.3%
T 283
14.3%
1 156
 
7.9%
2 146
 
7.4%
4 59
 
3.0%
5 59
 
3.0%
7 58
 
2.9%
3 57
 
2.9%
Other values (3) 162
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1132
57.1%
Uppercase Letter 849
42.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 435
38.4%
1 156
 
13.8%
2 146
 
12.9%
4 59
 
5.2%
5 59
 
5.2%
7 58
 
5.1%
3 57
 
5.0%
6 57
 
5.0%
8 56
 
4.9%
9 49
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
B 283
33.3%
I 283
33.3%
T 283
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 1132
57.1%
Latin 849
42.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 435
38.4%
1 156
 
13.8%
2 146
 
12.9%
4 59
 
5.2%
5 59
 
5.2%
7 58
 
5.1%
3 57
 
5.0%
6 57
 
5.0%
8 56
 
4.9%
9 49
 
4.3%
Latin
ValueCountFrequency (%)
B 283
33.3%
I 283
33.3%
T 283
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1981
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 435
22.0%
B 283
14.3%
I 283
14.3%
T 283
14.3%
1 156
 
7.9%
2 146
 
7.4%
4 59
 
3.0%
5 59
 
3.0%
7 58
 
2.9%
3 57
 
2.9%
Other values (3) 162
 
8.2%

정류소명
Text

Distinct224
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-12T23:50:40.972190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length5.1448763
Min length2

Characters and Unicode

Total characters1456
Distinct characters210
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique170 ?
Unique (%)60.1%

Sample

1st row수광2리나뭇가지마을
2nd row수광1리
3rd row수광1리
4th row현방리
5th row백사중학교
ValueCountFrequency (%)
부대앞 4
 
1.4%
관고동 4
 
1.4%
이천터미널 3
 
1.1%
오천리 2
 
0.7%
이치1리 2
 
0.7%
에스케이하이닉스 2
 
0.7%
유산3리 2
 
0.7%
부발역 2
 
0.7%
표교2리롯데아울렛 2
 
0.7%
ob앞 2
 
0.7%
Other values (214) 258
91.2%
2023-12-12T23:50:41.615805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 125
 
8.6%
아 51
 
3.5%
트 49
 
3.4%
파 43
 
3.0%
교 42
 
2.9%
이 35
 
2.4%
2 31
 
2.1%
대 31
 
2.1%
동 28
 
1.9%
1 27
 
1.9%
Other values (200) 994
68.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1344
92.3%
Decimal Number 80
 
5.5%
Other Punctuation 23
 
1.6%
Uppercase Letter 6
 
0.4%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 125
 
9.3%
아 51
 
3.8%
트 49
 
3.6%
파 43
 
3.2%
교 42
 
3.1%
이 35
 
2.6%
대 31
 
2.3%
동 28
 
2.1%
천 26
 
1.9%
사 25
 
1.9%
Other values (184) 889
66.1%
Decimal Number
ValueCountFrequency (%)
2 31
38.8%
1 27
33.8%
3 14
17.5%
4 5
 
6.2%
7 1
 
1.2%
5 1
 
1.2%
6 1
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
O 2
33.3%
B 2
33.3%
K 1
16.7%
T 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 21
91.3%
· 2
 
8.7%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1345
92.4%
Common 105
 
7.2%
Latin 6
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 125
 
9.3%
아 51
 
3.8%
트 49
 
3.6%
파 43
 
3.2%
교 42
 
3.1%
이 35
 
2.6%
대 31
 
2.3%
동 28
 
2.1%
천 26
 
1.9%
사 25
 
1.9%
Other values (185) 890
66.2%
Common
ValueCountFrequency (%)
2 31
29.5%
1 27
25.7%
. 21
20.0%
3 14
13.3%
4 5
 
4.8%
· 2
 
1.9%
7 1
 
1.0%
( 1
 
1.0%
) 1
 
1.0%
5 1
 
1.0%
Latin
ValueCountFrequency (%)
O 2
33.3%
B 2
33.3%
K 1
16.7%
T 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1344
92.3%
ASCII 109
 
7.5%
None 3
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 125
 
9.3%
아 51
 
3.8%
트 49
 
3.6%
파 43
 
3.2%
교 42
 
3.1%
이 35
 
2.6%
대 31
 
2.3%
동 28
 
2.1%
천 26
 
1.9%
사 25
 
1.9%
Other values (184) 889
66.1%
ASCII
ValueCountFrequency (%)
2 31
28.4%
1 27
24.8%
. 21
19.3%
3 14
12.8%
4 5
 
4.6%
O 2
 
1.8%
B 2
 
1.8%
7 1
 
0.9%
K 1
 
0.9%
T 1
 
0.9%
Other values (4) 4
 
3.7%
None
ValueCountFrequency (%)
· 2
66.7%
㈜ 1
33.3%

정류소번호
Real number (ℝ)

Distinct282
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34290.58
Minimum32004
Maximum51309
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T23:50:41.789414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32004
5-th percentile32032.3
Q132112.5
median32337
Q332724
95-th percentile51172.3
Maximum51309
Range19305
Interquartile range (IQR)611.5

Descriptive statistics

Standard deviation5716.1081
Coefficient of variation (CV)0.16669617
Kurtosis4.9462689
Mean34290.58
Median Absolute Deviation (MAD)264
Skewness2.6240478
Sum9704234
Variance32673892
MonotonicityNot monotonic
2023-12-12T23:50:41.997435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32082 2
 
0.7%
32189 1
 
0.4%
32015 1
 
0.4%
32330 1
 
0.4%
32914 1
 
0.4%
32689 1
 
0.4%
51166 1
 
0.4%
32427 1
 
0.4%
32636 1
 
0.4%
32048 1
 
0.4%
Other values (272) 272
96.1%
ValueCountFrequency (%)
32004 1
0.4%
32005 1
0.4%
32006 1
0.4%
32008 1
0.4%
32009 1
0.4%
32011 1
0.4%
32015 1
0.4%
32016 1
0.4%
32017 1
0.4%
32020 1
0.4%
ValueCountFrequency (%)
51309 1
0.4%
51307 1
0.4%
51303 1
0.4%
51284 1
0.4%
51278 1
0.4%
51255 1
0.4%
51217 1
0.4%
51216 1
0.4%
51212 1
0.4%
51199 1
0.4%

소재지 주소
Text

Distinct258
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2023-12-12T23:50:42.462093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length19.342756
Min length14

Characters and Unicode

Total characters5474
Distinct characters122
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

Unique241 ?
Unique (%)85.2%

Sample

1st row경기도 이천시 신둔면 수광리 406-12
2nd row경기도 이천시 신둔면 수광리 716
3rd row경기도 이천시 신둔면 수광리 716
4th row경기도 이천시 백사면 현방리 73-16
5th row경기도 이천시 백사면 조읍리 산 85-7
ValueCountFrequency (%)
경기도 283
20.9%
이천시 282
20.8%
부발읍 44
 
3.2%
마장면 31
 
2.3%
산 25
 
1.8%
백사면 23
 
1.7%
신둔면 23
 
1.7%
호법면 20
 
1.5%
장호원읍 15
 
1.1%
대월면 13
 
1.0%
Other values (353) 595
43.9%
2023-12-12T23:50:43.106305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1074
19.6%
천 294
 
5.4%
이 293
 
5.4%
도 290
 
5.3%
경 287
 
5.2%
시 284
 
5.2%
기 283
 
5.2%
리 205
 
3.7%
- 189
 
3.5%
1 162
 
3.0%
Other values (112) 2113
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3192
58.3%
Space Separator 1074
 
19.6%
Decimal Number 1019
 
18.6%
Dash Punctuation 189
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 294
 
9.2%
이 293
 
9.2%
도 290
 
9.1%
경 287
 
9.0%
시 284
 
8.9%
기 283
 
8.9%
리 205
 
6.4%
면 134
 
4.2%
동 94
 
2.9%
읍 61
 
1.9%
Other values (100) 967
30.3%
Decimal Number
ValueCountFrequency (%)
1 162
15.9%
3 138
13.5%
2 122
12.0%
5 110
10.8%
4 95
9.3%
6 91
8.9%
7 89
8.7%
8 78
7.7%
0 72
7.1%
9 62
 
6.1%
Space Separator
ValueCountFrequency (%)
1074
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 189
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3192
58.3%
Common 2282
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 294
 
9.2%
이 293
 
9.2%
도 290
 
9.1%
경 287
 
9.0%
시 284
 
8.9%
기 283
 
8.9%
리 205
 
6.4%
면 134
 
4.2%
동 94
 
2.9%
읍 61
 
1.9%
Other values (100) 967
30.3%
Common
ValueCountFrequency (%)
1074
47.1%
- 189
 
8.3%
1 162
 
7.1%
3 138
 
6.0%
2 122
 
5.3%
5 110
 
4.8%
4 95
 
4.2%
6 91
 
4.0%
7 89
 
3.9%
8 78
 
3.4%
Other values (2) 134
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3192
58.3%
ASCII 2282
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1074
47.1%
- 189
 
8.3%
1 162
 
7.1%
3 138
 
6.0%
2 122
 
5.3%
5 110
 
4.8%
4 95
 
4.2%
6 91
 
4.0%
7 89
 
3.9%
8 78
 
3.4%
Other values (2) 134
 
5.9%
Hangul
ValueCountFrequency (%)
천 294
 
9.2%
이 293
 
9.2%
도 290
 
9.1%
경 287
 
9.0%
시 284
 
8.9%
기 283
 
8.9%
리 205
 
6.4%
면 134
 
4.2%
동 94
 
2.9%
읍 61
 
1.9%
Other values (100) 967
30.3%

지역
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
부발
44 
마장
32 
신둔
24 
백사
23 
호법
20 
Other values (19)
140 

Length

Max length3
Median length2
Mean length2.0530035
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row신둔
2nd row신둔
3rd row신둔
4th row백사
5th row백사

Common Values

ValueCountFrequency (%)
부발 44
15.5%
마장 32
11.3%
신둔 24
 
8.5%
백사 23
 
8.1%
호법 20
 
7.1%
장호원 15
 
5.3%
중리 15
 
5.3%
대월 13
 
4.6%
모가 13
 
4.6%
증포 12
 
4.2%
Other values (14) 72
25.4%

Length

2023-12-12T23:50:43.267487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부발 44
15.5%
마장 32
11.3%
신둔 24
 
8.5%
백사 23
 
8.1%
호법 20
 
7.1%
장호원 15
 
5.3%
중리 15
 
5.3%
대월 13
 
4.6%
모가 13
 
4.6%
증포 12
 
4.2%
Other values (14) 72
25.4%

설치연도
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.8799
Minimum2008
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T23:50:43.397454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2010
Q12010
median2013
Q32014
95-th percentile2018.9
Maximum2019
Range11
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.9845436
Coefficient of variation (CV)0.0014827232
Kurtosis-0.88466373
Mean2012.8799
Median Absolute Deviation (MAD)3
Skewness0.51449179
Sum569645
Variance8.9075007
MonotonicityNot monotonic
2023-12-12T23:50:43.535947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2010 114
40.3%
2014 73
25.8%
2017 33
 
11.7%
2013 29
 
10.2%
2019 15
 
5.3%
2018 9
 
3.2%
2011 6
 
2.1%
2008 4
 
1.4%
ValueCountFrequency (%)
2008 4
 
1.4%
2010 114
40.3%
2011 6
 
2.1%
2013 29
 
10.2%
2014 73
25.8%
2017 33
 
11.7%
2018 9
 
3.2%
2019 15
 
5.3%
ValueCountFrequency (%)
2019 15
 
5.3%
2018 9
 
3.2%
2017 33
 
11.7%
2014 73
25.8%
2013 29
 
10.2%
2011 6
 
2.1%
2010 114
40.3%
2008 4
 
1.4%

장비 유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
LCD 거치형
248 
LED 거치형
30 
LCD 독립형
 
4
LED 독립형
 
1

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st rowLCD 거치형
2nd rowLCD 거치형
3rd rowLCD 거치형
4th rowLCD 거치형
5th rowLCD 거치형

Common Values

ValueCountFrequency (%)
LCD 거치형 248
87.6%
LED 거치형 30
 
10.6%
LCD 독립형 4
 
1.4%
LED 독립형 1
 
0.4%

Length

2023-12-12T23:50:43.703563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:50:43.844343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
거치형 278
49.1%
lcd 252
44.5%
led 31
 
5.5%
독립형 5
 
0.9%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct282
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.253236
Minimum37.052395
Maximum37.344103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T23:50:44.018801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.052395
5-th percentile37.116839
Q137.234616
median37.263578
Q337.291777
95-th percentile37.319684
Maximum37.344103
Range0.2917081
Interquartile range (IQR)0.05716065

Descriptive statistics

Standard deviation0.056981034
Coefficient of variation (CV)0.0015295593
Kurtosis1.1130926
Mean37.253236
Median Absolute Deviation (MAD)0.0282218
Skewness-1.2185288
Sum10542.666
Variance0.0032468383
MonotonicityNot monotonic
2023-12-12T23:50:44.193460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.2818053 2
 
0.7%
37.2942347 1
 
0.4%
37.2466532 1
 
0.4%
37.2317152 1
 
0.4%
37.2118027 1
 
0.4%
37.2385086 1
 
0.4%
37.246471 1
 
0.4%
37.2057907 1
 
0.4%
37.2244657 1
 
0.4%
37.3133203 1
 
0.4%
Other values (272) 272
96.1%
ValueCountFrequency (%)
37.0523952 1
0.4%
37.0875202 1
0.4%
37.0943203 1
0.4%
37.1052736 1
0.4%
37.1062397 1
0.4%
37.1063441 1
0.4%
37.1083084 1
0.4%
37.1124403 1
0.4%
37.1134446 1
0.4%
37.1151201 1
0.4%
ValueCountFrequency (%)
37.3441033 1
0.4%
37.3401333 1
0.4%
37.338958 1
0.4%
37.3381338 1
0.4%
37.3365528 1
0.4%
37.3344644 1
0.4%
37.3338322 1
0.4%
37.3298439 1
0.4%
37.3296416 1
0.4%
37.3281711 1
0.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct282
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.45939
Minimum127.35149
Maximum127.63322
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2023-12-12T23:50:44.394816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.35149
5-th percentile127.36019
Q1127.43249
median127.45518
Q3127.48988
95-th percentile127.57467
Maximum127.63322
Range0.2817364
Interquartile range (IQR)0.0573903

Descriptive statistics

Standard deviation0.058857526
Coefficient of variation (CV)0.00046177475
Kurtosis1.1080088
Mean127.45939
Median Absolute Deviation (MAD)0.030687
Skewness0.64483394
Sum36071.006
Variance0.0034642083
MonotonicityNot monotonic
2023-12-12T23:50:44.946889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.4399126 2
 
0.7%
127.53447 1
 
0.4%
127.3601229 1
 
0.4%
127.4342073 1
 
0.4%
127.429201 1
 
0.4%
127.4385896 1
 
0.4%
127.4166014 1
 
0.4%
127.3814742 1
 
0.4%
127.4017922 1
 
0.4%
127.3979173 1
 
0.4%
Other values (272) 272
96.1%
ValueCountFrequency (%)
127.3514861 1
0.4%
127.3518168 1
0.4%
127.3518557 1
0.4%
127.3524895 1
0.4%
127.3527308 1
0.4%
127.3529282 1
0.4%
127.3530447 1
0.4%
127.354027 1
0.4%
127.3543164 1
0.4%
127.3568532 1
0.4%
ValueCountFrequency (%)
127.6332225 1
0.4%
127.6320171 1
0.4%
127.6305014 1
0.4%
127.6290192 1
0.4%
127.6283196 1
0.4%
127.6280722 1
0.4%
127.6251899 1
0.4%
127.6246507 1
0.4%
127.6183826 1
0.4%
127.6180884 1
0.4%

Interactions

2023-12-12T23:50:38.886667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:37.309019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:37.864913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:38.356046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:39.004680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:37.418654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:37.999022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:38.515611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:39.100388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:37.547517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:38.110158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:38.661205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:39.252525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:37.686336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:38.227462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:50:38.785760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:50:45.068625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정류소번호지역설치연도장비 유형위도경도
정류소번호1.0000.0000.3480.1280.0000.000
지역0.0001.0000.5420.4630.9230.915
설치연도0.3480.5421.0000.6820.2950.332
장비 유형0.1280.4630.6821.0000.4520.528
위도0.0000.9230.2950.4521.0000.909
경도0.0000.9150.3320.5280.9091.000
2023-12-12T23:50:45.197557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역장비 유형
지역1.0000.226
장비 유형0.2261.000
2023-12-12T23:50:45.329960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정류소번호설치연도위도경도지역장비 유형
정류소번호1.0000.243-0.0100.3170.0000.077
설치연도0.2431.000-0.032-0.2080.2350.507
위도-0.010-0.0321.000-0.2050.6560.283
경도0.317-0.208-0.2051.0000.6360.340
지역0.0000.2350.6560.6361.0000.226
장비 유형0.0770.5070.2830.3400.2261.000

Missing values

2023-12-12T23:50:39.411480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:50:39.590969image/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

관리번호정류소명정류소번호소재지 주소지역설치연도장비 유형위도경도
0BIT0001수광2리나뭇가지마을32048경기도 이천시 신둔면 수광리 406-12신둔2010LCD 거치형37.31332127.397917
1BIT0002수광1리32051경기도 이천시 신둔면 수광리 716신둔2010LCD 거치형37.307058127.402948
2BIT0003수광1리32050경기도 이천시 신둔면 수광리 716신둔2010LCD 거치형37.307324127.402425
3BIT0004현방리32721경기도 이천시 백사면 현방리 73-16백사2010LCD 거치형37.340133127.492409
4BIT0005백사중학교32725경기도 이천시 백사면 조읍리 산 85-7백사2010LCD 거치형37.323959127.474957
5BIT0008모전1리32589경기도 이천시 백사면 모전리 977-4백사2010LCD 거치형37.307166127.463787
6BIT0009모전리현대아파트32136경기도 이천시 백사면 모전리 780-2백사2010LCD 거치형37.303852127.469955
7BIT0010모전리현대아파트32135경기도 이천시 백사면 모전리 535-2백사2017LED 거치형37.303785127.470141
8BIT0011도지초등학교32152경기도 이천시 백사면 도지리 13백사2010LCD 거치형37.307876127.483508
9BIT0012사음2동.동일냉장32056경기도 이천시 사음동 570-3사음2010LCD 거치형37.298768127.408582
관리번호정류소명정류소번호소재지 주소지역설치연도장비 유형위도경도
273BIT0278이천센트럴푸르지오51307경기도 이천시 증포동 93-6증포2018LED 거치형37.289144127.459586
274BIT0279마장고등학교32806경기도 이천시 마장면 양촌리 335마장2019LED 거치형37.257723127.352928
275BIT0280마장고등학교32805경기도 이천시 마장면 양촌리 94-2마장2019LED 거치형37.257713127.353045
276BIT0281양촌리51085경기도 이천시 마장면 양촌리 36-3마장2019LED 거치형37.255624127.351486
277BIT0282명지빌라32787경기도 이천시 사음동 202-1신둔2019LED 거치형37.296077127.420507
278BIT0283양촌1리32035경기도 이천시 마장면 양촌리 63마장2019LED 거치형37.256338127.35249
279BIT0284양촌1리32036경기도 이천시 마장면 양촌리 32-2마장2019LED 거치형37.256301127.352731
280BIT0285마장우체국32063경기도 이천시 마장면 오천리 377마장2019LED 거치형37.251553127.354316
281BIT0287부발역32641경기도 이천시 부발읍 아미리 505-22부발2019LED 거치형37.259341127.490524
282BIT0289송정4통51303경기도 이천시송정동191-6송정2019LED 거치형37.299936127.438415