Overview

Dataset statistics

Number of variables18
Number of observations537
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory78.3 KiB
Average record size in memory149.2 B

Variable types

Categorical12
Numeric5
Text1

Dataset

Description경기도 의정부시 관내 정류장 데이터로 지형지물부호, 관리번호, 행정동, 도엽번호, 관리기관, 도로구간번호, 설치일자 , 정류장종류, 정류장명 , 정류장유형, 대장초기화여부, 위치, 입력일자, 입력자, 최종수정일자, 최종수정자, 경도, 위도 등의 항목으로 구성되어 있습니다.
Author경기도 의정부시
URLhttps://www.data.go.kr/data/15062028/fileData.do

Alerts

지형지물부호 has constant value ""Constant
관리기관 has constant value ""Constant
대장초기화여부 is highly overall correlated with 정류장종류 and 1 other fieldsHigh correlation
입력자 is highly overall correlated with 관리번호 and 5 other fieldsHigh correlation
최종수정일자 is highly overall correlated with 관리번호 and 5 other fieldsHigh correlation
최종수정자 is highly overall correlated with 관리번호 and 5 other fieldsHigh correlation
입력일자 is highly overall correlated with 관리번호 and 5 other fieldsHigh correlation
정류장종류 is highly overall correlated with 대장초기화여부High correlation
관리번호 is highly overall correlated with 설치일자 and 5 other fieldsHigh correlation
도엽번호 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
도로구간번호 is highly overall correlated with 행정동 and 5 other fieldsHigh correlation
경도 is highly overall correlated with 행정동High correlation
위도 is highly overall correlated with 도엽번호 and 1 other fieldsHigh correlation
행정동 is highly overall correlated with 도로구간번호 and 2 other fieldsHigh correlation
설치일자 is highly overall correlated with 관리번호 and 6 other fieldsHigh correlation
정류장유형 is highly overall correlated with 관리번호 and 2 other fieldsHigh correlation
위치 is highly overall correlated with 도엽번호High correlation
설치일자 is highly imbalanced (64.0%)Imbalance
정류장유형 is highly imbalanced (62.2%)Imbalance
대장초기화여부 is highly imbalanced (92.4%)Imbalance
위치 is highly imbalanced (89.1%)Imbalance
경도 has unique valuesUnique
위도 has unique valuesUnique
도로구간번호 has 24 (4.5%) zerosZeros

Reproduction

Analysis started2023-12-12 12:45:51.381098
Analysis finished2023-12-12 12:45:55.963305
Duration4.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지형지물부호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
정류장
537 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정류장 537
100.0%

Length

2023-12-12T21:45:56.023550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:45:56.403620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정류장 537
100.0%

관리번호
Real number (ℝ)

HIGH CORRELATION 

Distinct536
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52442832
Minimum1
Maximum2.0210003 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-12T21:45:56.512855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile31.8
Q1148
median305
Q31.9112 × 108
95-th percentile2.0210001 × 108
Maximum2.0210003 × 108
Range2.0210003 × 108
Interquartile range (IQR)1.9111986 × 108

Descriptive statistics

Standard deviation87080807
Coefficient of variation (CV)1.6604902
Kurtosis-0.86585805
Mean52442832
Median Absolute Deviation (MAD)207
Skewness1.0639574
Sum2.8161801 × 1010
Variance7.5830669 × 1015
MonotonicityDecreasing
2023-12-12T21:45:56.643596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
343 2
 
0.4%
202100034 1
 
0.2%
200 1
 
0.2%
185 1
 
0.2%
188 1
 
0.2%
189 1
 
0.2%
190 1
 
0.2%
191 1
 
0.2%
192 1
 
0.2%
193 1
 
0.2%
Other values (526) 526
98.0%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
10 1
0.2%
11 1
0.2%
12 1
0.2%
13 1
0.2%
ValueCountFrequency (%)
202100034 1
0.2%
202100033 1
0.2%
202100032 1
0.2%
202100031 1
0.2%
202100030 1
0.2%
202100029 1
0.2%
202100028 1
0.2%
202100027 1
0.2%
202100026 1
0.2%
202100025 1
0.2%

행정동
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
송산2동
91 
<NA>
70 
신곡2동
56 
의정부2동
46 
의정부1동
44 
Other values (9)
230 

Length

Max length5
Median length4
Mean length3.990689
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row신곡2동
2nd row신곡2동
3rd row신곡2동
4th row신곡1동
5th row장암동

Common Values

ValueCountFrequency (%)
송산2동 91
16.9%
<NA> 70
13.0%
신곡2동 56
10.4%
의정부2동 46
8.6%
의정부1동 44
8.2%
자금동 43
8.0%
송산1동 40
7.4%
신곡1동 36
 
6.7%
녹양동 33
 
6.1%
호원1동 31
 
5.8%
Other values (4) 47
8.8%

Length

2023-12-12T21:45:56.780909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
송산2동 91
16.9%
na 70
13.0%
신곡2동 56
10.4%
의정부2동 46
8.6%
의정부1동 44
8.2%
자금동 43
8.0%
송산1동 40
7.4%
신곡1동 36
 
6.7%
녹양동 33
 
6.1%
호원1동 31
 
5.8%
Other values (4) 47
8.8%

도엽번호
Real number (ℝ)

HIGH CORRELATION 

Distinct256
Distinct (%)47.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6124514 × 109
Minimum3.770121 × 108
Maximum3.7705072 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-12T21:45:56.905456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.770121 × 108
5-th percentile3.770121 × 109
Q13.7705011 × 109
median3.770502 × 109
Q33.7705023 × 109
95-th percentile3.7705029 × 109
Maximum3.7705072 × 109
Range3.3934951 × 109
Interquartile range (IQR)1197

Descriptive statistics

Standard deviation7.156004 × 108
Coefficient of variation (CV)0.19809274
Kurtosis16.695021
Mean3.6124514 × 109
Median Absolute Deviation (MAD)520
Skewness-4.3165791
Sum1.9398864 × 1012
Variance5.1208394 × 1017
MonotonicityNot monotonic
2023-12-12T21:45:57.035773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3770502124 8
 
1.5%
3770501192 7
 
1.3%
3770122953 6
 
1.1%
3770502304 6
 
1.1%
3770123922 6
 
1.1%
3770502042 5
 
0.9%
3770502292 4
 
0.7%
3770502301 4
 
0.7%
3770121784 4
 
0.7%
3770121783 4
 
0.7%
Other values (246) 483
89.9%
ValueCountFrequency (%)
377012100 2
0.4%
377012190 2
0.4%
377012269 2
0.4%
377012270 3
0.6%
377012278 1
 
0.2%
377012279 1
 
0.2%
377012291 2
0.4%
377050114 2
0.4%
377050115 2
0.4%
377050160 1
 
0.2%
ValueCountFrequency (%)
3770507224 1
 
0.2%
3770507223 1
 
0.2%
3770507023 1
 
0.2%
3770507021 1
 
0.2%
3770506203 2
0.4%
3770506103 1
 
0.2%
3770506102 1
 
0.2%
3770503721 2
0.4%
3770503712 1
 
0.2%
3770503614 3
0.6%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
의정부시
537 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
의정부시 537
100.0%

Length

2023-12-12T21:45:57.155843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:45:57.239784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의정부시 537
100.0%

도로구간번호
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct336
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41927732
Minimum0
Maximum2.0210004 × 108
Zeros24
Zeros (%)4.5%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-12T21:45:57.350621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile27.4
Q11197
median170065
Q3800095
95-th percentile2.0202012 × 108
Maximum2.0210004 × 108
Range2.0210004 × 108
Interquartile range (IQR)798898

Descriptive statistics

Standard deviation80220723
Coefficient of variation (CV)1.9133094
Kurtosis-0.031701194
Mean41927732
Median Absolute Deviation (MAD)169000
Skewness1.4009491
Sum2.2515192 × 1010
Variance6.4353645 × 1015
MonotonicityNot monotonic
2023-12-12T21:45:57.494641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 24
 
4.5%
800095 6
 
1.1%
2021 4
 
0.7%
202011004 4
 
0.7%
800135 4
 
0.7%
1512 4
 
0.7%
202020125 4
 
0.7%
1051 4
 
0.7%
260 4
 
0.7%
202030093 4
 
0.7%
Other values (326) 475
88.5%
ValueCountFrequency (%)
0 24
4.5%
3 1
 
0.2%
10 1
 
0.2%
25 1
 
0.2%
28 1
 
0.2%
29 2
 
0.4%
35 3
 
0.6%
36 2
 
0.4%
37 3
 
0.6%
40 2
 
0.4%
ValueCountFrequency (%)
202100044 2
0.4%
202040060 1
 
0.2%
202040058 1
 
0.2%
202040047 1
 
0.2%
202040039 1
 
0.2%
202030135 2
0.4%
202030134 1
 
0.2%
202030103 3
0.6%
202030097 1
 
0.2%
202030096 2
0.4%

설치일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct9
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
386 
1900-01-01
128 
2019-01-01
 
7
2018-01-01
 
6
2020-09-01
 
2
Other values (4)
 
8

Length

Max length10
Median length1
Mean length3.5083799
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
386
71.9%
1900-01-01 128
 
23.8%
2019-01-01 7
 
1.3%
2018-01-01 6
 
1.1%
2020-09-01 2
 
0.4%
2020-05-01 2
 
0.4%
2018-10-09 2
 
0.4%
2017-01-01 2
 
0.4%
<NA> 2
 
0.4%

Length

2023-12-12T21:45:57.621626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:45:57.727725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1900-01-01 128
84.8%
2019-01-01 7
 
4.6%
2018-01-01 6
 
4.0%
2020-09-01 2
 
1.3%
2020-05-01 2
 
1.3%
2018-10-09 2
 
1.3%
2017-01-01 2
 
1.3%
na 2
 
1.3%

정류장종류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
일반버스
323 
마을버스
148 
<NA>
36 
기타
 
21
택시
 
7

Length

Max length4
Median length4
Mean length3.8957169
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반버스
2nd row택시
3rd row택시
4th row택시
5th row택시

Common Values

ValueCountFrequency (%)
일반버스 323
60.1%
마을버스 148
27.6%
<NA> 36
 
6.7%
기타 21
 
3.9%
택시 7
 
1.3%
좌석버스 2
 
0.4%

Length

2023-12-12T21:45:57.863698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:45:57.969496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반버스 323
60.1%
마을버스 148
27.6%
na 36
 
6.7%
기타 21
 
3.9%
택시 7
 
1.3%
좌석버스 2
 
0.4%

정류장명
Text

Distinct318
Distinct (%)59.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-12T21:45:58.198979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length5.7020484
Min length1

Characters and Unicode

Total characters3062
Distinct characters271
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

Unique172 ?
Unique (%)32.0%

Sample

1st row은하수아파트
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
의정부경찰서 5
 
1.0%
시외버스터미널앞 5
 
1.0%
경기도청북부청사 5
 
1.0%
회룡역 5
 
1.0%
경민대학교 4
 
0.8%
녹양초등학교 4
 
0.8%
롯데마트앞 4
 
0.8%
주택앞 4
 
0.8%
금오초교 4
 
0.8%
검은돌 4
 
0.8%
Other values (309) 477
91.6%
2023-12-12T21:45:58.644333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
앞 129
 
4.2%
아 109
 
3.6%
트 106
 
3.5%
파 98
 
3.2%
교 78
 
2.5%
부 72
 
2.4%
지 68
 
2.2%
정 57
 
1.9%
신 57
 
1.9%
구 56
 
1.8%
Other values (261) 2232
72.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2856
93.3%
Decimal Number 96
 
3.1%
Other Punctuation 29
 
0.9%
Uppercase Letter 29
 
0.9%
Space Separator 26
 
0.8%
Open Punctuation 13
 
0.4%
Close Punctuation 13
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 129
 
4.5%
아 109
 
3.8%
트 106
 
3.7%
파 98
 
3.4%
교 78
 
2.7%
부 72
 
2.5%
지 68
 
2.4%
정 57
 
2.0%
신 57
 
2.0%
구 56
 
2.0%
Other values (234) 2026
70.9%
Uppercase Letter
ValueCountFrequency (%)
K 5
17.2%
R 5
17.2%
P 3
10.3%
A 3
10.3%
I 3
10.3%
B 2
 
6.9%
T 2
 
6.9%
C 2
 
6.9%
S 2
 
6.9%
L 1
 
3.4%
Decimal Number
ValueCountFrequency (%)
1 26
27.1%
2 18
18.8%
3 16
16.7%
6 8
 
8.3%
5 7
 
7.3%
4 6
 
6.2%
0 5
 
5.2%
8 4
 
4.2%
9 3
 
3.1%
7 3
 
3.1%
Other Punctuation
ValueCountFrequency (%)
, 17
58.6%
. 8
27.6%
/ 4
 
13.8%
Space Separator
ValueCountFrequency (%)
26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2856
93.3%
Common 177
 
5.8%
Latin 29
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 129
 
4.5%
아 109
 
3.8%
트 106
 
3.7%
파 98
 
3.4%
교 78
 
2.7%
부 72
 
2.5%
지 68
 
2.4%
정 57
 
2.0%
신 57
 
2.0%
구 56
 
2.0%
Other values (234) 2026
70.9%
Common
ValueCountFrequency (%)
1 26
14.7%
26
14.7%
2 18
10.2%
, 17
9.6%
3 16
9.0%
( 13
7.3%
) 13
7.3%
6 8
 
4.5%
. 8
 
4.5%
5 7
 
4.0%
Other values (6) 25
14.1%
Latin
ValueCountFrequency (%)
K 5
17.2%
R 5
17.2%
P 3
10.3%
A 3
10.3%
I 3
10.3%
B 2
 
6.9%
T 2
 
6.9%
C 2
 
6.9%
S 2
 
6.9%
L 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2855
93.2%
ASCII 206
 
6.7%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
앞 129
 
4.5%
아 109
 
3.8%
트 106
 
3.7%
파 98
 
3.4%
교 78
 
2.7%
부 72
 
2.5%
지 68
 
2.4%
정 57
 
2.0%
신 57
 
2.0%
구 56
 
2.0%
Other values (233) 2025
70.9%
ASCII
ValueCountFrequency (%)
1 26
12.6%
26
12.6%
2 18
 
8.7%
, 17
 
8.3%
3 16
 
7.8%
( 13
 
6.3%
) 13
 
6.3%
6 8
 
3.9%
. 8
 
3.9%
5 7
 
3.4%
Other values (17) 54
26.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

정류장유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
표지설치
419 
승강장설치
59 
지붕설치
 
41
미분류
 
11
표지/승강장설치
 
2
Other values (3)
 
5

Length

Max length8
Median length4
Mean length4.1117318
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row승강장설치
2nd row미분류
3rd row미분류
4th row미분류
5th row미분류

Common Values

ValueCountFrequency (%)
표지설치 419
78.0%
승강장설치 59
 
11.0%
지붕설치 41
 
7.6%
미분류 11
 
2.0%
표지/승강장설치 2
 
0.4%
표지판 2
 
0.4%
표지,지붕설치 2
 
0.4%
<NA> 1
 
0.2%

Length

2023-12-12T21:45:58.795323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:45:58.916733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
표지설치 419
78.0%
승강장설치 59
 
11.0%
지붕설치 41
 
7.6%
미분류 11
 
2.0%
표지/승강장설치 2
 
0.4%
표지판 2
 
0.4%
표지,지붕설치 2
 
0.4%
na 1
 
0.2%

대장초기화여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
대장입력완료
532 
대장초기화
 
5

Length

Max length6
Median length6
Mean length5.990689
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대장입력완료 532
99.1%
대장초기화 5
 
0.9%

Length

2023-12-12T21:45:59.108340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:45:59.234553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대장입력완료 532
99.1%
대장초기화 5
 
0.9%

위치
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct18
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
512 
맑은물사업소
 
3
롯데마트 앞 도로
 
3
양지마을
 
2
하동촌
 
2
Other values (13)
 
15

Length

Max length9
Median length1
Mean length1.2011173
Min length1

Unique

Unique11 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
512
95.3%
맑은물사업소 3
 
0.6%
롯데마트 앞 도로 3
 
0.6%
양지마을 2
 
0.4%
하동촌 2
 
0.4%
금호사거리 2
 
0.4%
주택앞 2
 
0.4%
신도브레뉴아파 1
 
0.2%
환경자원센터 1
 
0.2%
금곡교앞 1
 
0.2%
Other values (8) 8
 
1.5%

Length

2023-12-12T21:45:59.366276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
앞 4
 
12.1%
맑은물사업소 3
 
9.1%
도로 3
 
9.1%
롯데마트 3
 
9.1%
양지마을 2
 
6.1%
하동촌 2
 
6.1%
금호사거리 2
 
6.1%
주택앞 2
 
6.1%
금오중학교 1
 
3.0%
사랑의교회 1
 
3.0%
Other values (10) 10
30.3%

입력일자
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
294 
2020-10-29
104 
2019-12-16
68 
2021-01-11
35 
2020-11-13
33 
Other values (2)
 
3

Length

Max length10
Median length1
Mean length5.0726257
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row2021-01-11
2nd row2021-01-11
3rd row2021-01-11
4th row2021-01-11
5th row2021-01-11

Common Values

ValueCountFrequency (%)
294
54.7%
2020-10-29 104
 
19.4%
2019-12-16 68
 
12.7%
2021-01-11 35
 
6.5%
2020-11-13 33
 
6.1%
2021-03-04 2
 
0.4%
2019-03-11 1
 
0.2%

Length

2023-12-12T21:45:59.494223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:45:59.604067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-10-29 104
42.8%
2019-12-16 68
28.0%
2021-01-11 35
 
14.4%
2020-11-13 33
 
13.6%
2021-03-04 2
 
0.8%
2019-03-11 1
 
0.4%

입력자
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
294 
삼아항업(주)
139 
지오스토리컨소시엄
101 
(주)유현정보기술
 
2
제일항업(주)
 
1

Length

Max length9
Median length1
Mean length4.0986965
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row삼아항업(주)
2nd row삼아항업(주)
3rd row삼아항업(주)
4th row삼아항업(주)
5th row삼아항업(주)

Common Values

ValueCountFrequency (%)
294
54.7%
삼아항업(주) 139
25.9%
지오스토리컨소시엄 101
 
18.8%
(주)유현정보기술 2
 
0.4%
제일항업(주) 1
 
0.2%

Length

2023-12-12T21:45:59.752537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:45:59.879659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
삼아항업(주 139
57.2%
지오스토리컨소시엄 101
41.6%
주)유현정보기술 2
 
0.8%
제일항업(주 1
 
0.4%

최종수정일자
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
294 
2020-10-29
104 
2019-12-16
68 
2021-01-11
35 
2020-11-13
33 
Other values (2)
 
3

Length

Max length10
Median length1
Mean length5.0726257
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row2021-01-11
2nd row2021-01-11
3rd row2021-01-11
4th row2021-01-11
5th row2021-01-11

Common Values

ValueCountFrequency (%)
294
54.7%
2020-10-29 104
 
19.4%
2019-12-16 68
 
12.7%
2021-01-11 35
 
6.5%
2020-11-13 33
 
6.1%
2021-03-04 2
 
0.4%
2019-03-11 1
 
0.2%

Length

2023-12-12T21:45:59.996294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:46:00.110670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-10-29 104
42.8%
2019-12-16 68
28.0%
2021-01-11 35
 
14.4%
2020-11-13 33
 
13.6%
2021-03-04 2
 
0.8%
2019-03-11 1
 
0.4%

최종수정자
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
294 
삼아항업
139 
컨소시엄
68 
지오스토리
33 
유현정보
 
2

Length

Max length5
Median length1
Mean length2.4171322
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
294
54.7%
삼아항업 139
25.9%
컨소시엄 68
 
12.7%
지오스토리 33
 
6.1%
유현정보 2
 
0.4%
제일항 1
 
0.2%

Length

2023-12-12T21:46:00.240643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:46:00.357699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
삼아항업 139
57.2%
컨소시엄 68
28.0%
지오스토리 33
 
13.6%
유현정보 2
 
0.8%
제일항 1
 
0.4%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct537
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.06203
Minimum127.01199
Maximum127.11792
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-12T21:46:00.502004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.01199
5-th percentile127.03277
Q1127.04347
median127.05578
Q3127.08007
95-th percentile127.10787
Maximum127.11792
Range0.10593306
Interquartile range (IQR)0.036599104

Descriptive statistics

Standard deviation0.024164628
Coefficient of variation (CV)0.00019017977
Kurtosis-0.69213208
Mean127.06203
Median Absolute Deviation (MAD)0.014771243
Skewness0.59421283
Sum68232.312
Variance0.00058392924
MonotonicityNot monotonic
2023-12-12T21:46:00.670504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.058120972 1
 
0.2%
127.048236775 1
 
0.2%
127.058938537 1
 
0.2%
127.059302794 1
 
0.2%
127.059434073 1
 
0.2%
127.059471836 1
 
0.2%
127.084701443 1
 
0.2%
127.084787157 1
 
0.2%
127.084978149 1
 
0.2%
127.088991918 1
 
0.2%
Other values (527) 527
98.1%
ValueCountFrequency (%)
127.011988544 1
0.2%
127.013247865 1
0.2%
127.016700511 1
0.2%
127.019821178 1
0.2%
127.019893314 1
0.2%
127.020785168 1
0.2%
127.020833976 1
0.2%
127.023028868 1
0.2%
127.023234941 1
0.2%
127.02492527 1
0.2%
ValueCountFrequency (%)
127.117921608 1
0.2%
127.117598626 1
0.2%
127.116990163 1
0.2%
127.11668676 1
0.2%
127.116377378 1
0.2%
127.11556328 1
0.2%
127.115164778 1
0.2%
127.113766297 1
0.2%
127.113654092 1
0.2%
127.113153652 1
0.2%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct537
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.740832
Minimum37.688925
Maximum37.767349
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-12T21:46:00.849422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.688925
5-th percentile37.713607
Q137.734113
median37.742986
Q337.750216
95-th percentile37.759787
Maximum37.767349
Range0.07842452
Interquartile range (IQR)0.016102786

Descriptive statistics

Standard deviation0.01364806
Coefficient of variation (CV)0.00036162583
Kurtosis1.2938228
Mean37.740832
Median Absolute Deviation (MAD)0.007649966
Skewness-1.0024606
Sum20266.827
Variance0.00018626953
MonotonicityNot monotonic
2023-12-12T21:46:01.035397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.741098766 1
 
0.2%
37.723547191 1
 
0.2%
37.730654848 1
 
0.2%
37.730352784 1
 
0.2%
37.728095244 1
 
0.2%
37.727890147 1
 
0.2%
37.73219172 1
 
0.2%
37.730756142 1
 
0.2%
37.730423817 1
 
0.2%
37.731522562 1
 
0.2%
Other values (527) 527
98.1%
ValueCountFrequency (%)
37.688924794 1
0.2%
37.688942721 1
0.2%
37.694183217 1
0.2%
37.694766314 1
0.2%
37.698035364 1
0.2%
37.700160666 1
0.2%
37.700213389 1
0.2%
37.702502103 1
0.2%
37.702629014 1
0.2%
37.702760489 1
0.2%
ValueCountFrequency (%)
37.767349314 1
0.2%
37.767328533 1
0.2%
37.767012243 1
0.2%
37.765572541 1
0.2%
37.765101504 1
0.2%
37.765072882 1
0.2%
37.764934227 1
0.2%
37.76432734 1
0.2%
37.762229829 1
0.2%
37.762099265 1
0.2%

Interactions

2023-12-12T21:45:55.181266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:52.913321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:53.506550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:54.068584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:54.668146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:55.275512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:53.032690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:53.641658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:54.189283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:54.803806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:55.362424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:53.140855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:53.737046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:54.315662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:54.908896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:55.463442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:53.271567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:53.840608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:54.453326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:55.011571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:55.543947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:53.388175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:53.952859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:54.546003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:45:55.091084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:46:01.188577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호행정동도엽번호도로구간번호설치일자정류장종류정류장유형대장초기화여부위치입력일자입력자최종수정일자최종수정자경도위도
관리번호1.0000.4590.1710.9650.8790.1850.5980.0000.0000.8880.7030.8880.9670.6390.373
행정동0.4591.0000.3550.5620.5550.1950.3780.1760.4190.7100.6180.7100.7250.8820.834
도엽번호0.1710.3551.0000.1410.4870.1220.0000.0001.0000.1320.1250.1320.2040.4160.303
도로구간번호0.9650.5620.1411.0000.9640.1280.4570.0000.0000.8630.8040.8630.9940.7560.390
설치일자0.8790.5550.4870.9641.0000.0980.7490.0000.0000.7750.8180.7750.8010.4890.430
정류장종류0.1850.1950.1220.1280.0981.0000.793NaN0.2760.4720.2100.4720.1780.3540.294
정류장유형0.5980.3780.0000.4570.7490.7931.0000.6180.0000.8520.6040.8520.6400.4400.292
대장초기화여부0.0000.1760.0000.0000.000NaN0.6181.0000.0000.0000.0150.0000.0000.1840.136
위치0.0000.4191.0000.0000.0000.2760.0000.0001.0000.0000.0000.0000.0000.5150.284
입력일자0.8880.7100.1320.8630.7750.4720.8520.0000.0001.0001.0001.0001.0000.6540.448
입력자0.7030.6180.1250.8040.8180.2100.6040.0150.0001.0001.0001.0001.0000.7430.413
최종수정일자0.8880.7100.1320.8630.7750.4720.8520.0000.0001.0001.0001.0001.0000.6540.448
최종수정자0.9670.7250.2040.9940.8010.1780.6400.0000.0001.0001.0001.0001.0000.6840.460
경도0.6390.8820.4160.7560.4890.3540.4400.1840.5150.6540.7430.6540.6841.0000.674
위도0.3730.8340.3030.3900.4300.2940.2920.1360.2840.4480.4130.4480.4600.6741.000
2023-12-12T21:46:01.358463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대장초기화여부입력자행정동최종수정일자최종수정자입력일자설치일자위치정류장종류정류장유형
대장초기화여부1.0000.0170.1610.0000.0000.0000.0000.0001.0000.663
입력자0.0171.0000.3910.9980.9990.9980.6840.0000.1610.444
행정동0.1610.3911.0000.4270.4640.4270.2880.2540.1050.185
최종수정일자0.0000.9980.4271.0000.9991.0000.5580.0000.1920.459
최종수정자0.0000.9990.4640.9991.0000.9990.6110.0000.1460.449
입력일자0.0000.9980.4271.0000.9991.0000.5580.0000.1920.459
설치일자0.0000.6840.2880.5580.6110.5581.0000.0000.0660.526
위치0.0000.0000.2540.0000.0000.0000.0001.0000.1420.000
정류장종류1.0000.1610.1050.1920.1460.1920.0660.1421.0000.416
정류장유형0.6630.4440.1850.4590.4490.4590.5260.0000.4161.000
2023-12-12T21:46:01.540727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호도엽번호도로구간번호경도위도행정동설치일자정류장종류정류장유형대장초기화여부위치입력일자입력자최종수정일자최종수정자
관리번호1.000-0.0330.4210.3970.2060.4230.6980.2250.6410.0000.0000.9520.8350.9520.834
도엽번호-0.0331.000-0.3850.396-0.6410.3270.3780.1490.0000.0000.9850.1500.1620.1500.156
도로구간번호0.421-0.3851.000-0.0380.1750.5210.8290.1560.4880.0000.0000.9290.9310.9290.930
경도0.3970.396-0.0381.0000.0950.6420.2580.1540.2400.1400.2230.4050.3990.4050.445
위도0.206-0.6410.1750.0951.0000.5440.2210.1260.1520.1030.1110.2460.1830.2460.262
행정동0.4230.3270.5210.6420.5441.0000.2880.1050.1850.1610.2540.4270.3910.4270.464
설치일자0.6980.3780.8290.2580.2210.2881.0000.0660.5260.0000.0000.5580.6840.5580.611
정류장종류0.2250.1490.1560.1540.1260.1050.0661.0000.4161.0000.1420.1920.1610.1920.146
정류장유형0.6410.0000.4880.2400.1520.1850.5260.4161.0000.6630.0000.4590.4440.4590.449
대장초기화여부0.0000.0000.0000.1400.1030.1610.0001.0000.6631.0000.0000.0000.0170.0000.000
위치0.0000.9850.0000.2230.1110.2540.0000.1420.0000.0001.0000.0000.0000.0000.000
입력일자0.9520.1500.9290.4050.2460.4270.5580.1920.4590.0000.0001.0000.9981.0000.999
입력자0.8350.1620.9310.3990.1830.3910.6840.1610.4440.0170.0000.9981.0000.9980.999
최종수정일자0.9520.1500.9290.4050.2460.4270.5580.1920.4590.0000.0001.0000.9981.0000.999
최종수정자0.8340.1560.9300.4450.2620.4640.6110.1460.4490.0000.0000.9990.9990.9991.000

Missing values

2023-12-12T21:45:55.669079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:45:55.891468image/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

지형지물부호관리번호행정동도엽번호관리기관도로구간번호설치일자정류장종류정류장명정류장유형대장초기화여부위치입력일자입력자최종수정일자최종수정자경도위도
0정류장202100034신곡2동3770502124의정부시163일반버스은하수아파트승강장설치대장입력완료2021-01-11삼아항업(주)2021-01-11삼아항업127.05812137.741099
1정류장202100033신곡2동3770502121의정부시1422택시미분류대장입력완료2021-01-11삼아항업(주)2021-01-11삼아항업127.0570437.742824
2정류장202100032신곡2동3770502032의정부시288택시미분류대장입력완료2021-01-11삼아항업(주)2021-01-11삼아항업127.06338437.748678
3정류장202100031신곡1동3770502243의정부시181202택시미분류대장입력완료2021-01-11삼아항업(주)2021-01-11삼아항업127.06586937.736873
4정류장202100030장암동3770502531의정부시35택시미분류대장입력완료2021-01-11삼아항업(주)2021-01-11삼아항업127.06050137.723021
5정류장202100029호원1동3770501602의정부시271택시미분류대장입력완료2021-01-11삼아항업(주)2021-01-11삼아항업127.04817937.724486
6정류장202100028호원1동3770501902의정부시202100044일반버스망월사역.신한대학교승강장설치대장입력완료2021-01-11삼아항업(주)2021-01-11삼아항업127.04807137.709608
7정류장202100027송산1동3770502071의정부시1739일반버스라인1차아파트지붕설치대장입력완료2021-01-11삼아항업(주)2021-01-11삼아항업127.08103337.748292
8정류장202100026송산1동3770502071의정부시1742일반버스어룡초교승강장설치대장입력완료2021-01-11삼아항업(주)2021-01-11삼아항업127.08145337.747581
9정류장202100025송산1동3770502071의정부시1736마을버스송산주공1단지.의정부세관표지설치대장입력완료2021-01-11삼아항업(주)2021-01-11삼아항업127.08010337.749376
지형지물부호관리번호행정동도엽번호관리기관도로구간번호설치일자정류장종류정류장명정류장유형대장초기화여부위치입력일자입력자최종수정일자최종수정자경도위도
527정류장13녹양동3770121893의정부시10마을버스화인빌딩표지설치대장입력완료127.03896437.758521
528정류장12녹양동3770121883의정부시170018마을버스청구아파트표지설치대장입력완료127.0332637.757971
529정류장11녹양동3770121883의정부시0일반버스녹양현대아파트표지설치대장입력완료127.03413337.758522
530정류장10녹양동3770121883의정부시170170일반버스녹양현대아파트표지설치대장입력완료127.03482837.759078
531정류장7녹양동3770121874의정부시3마을버스현대아파트표지설치대장입력완료127.03170737.75982
532정류장6녹양동3770121871의정부시170164마을버스대림,신도아파트표지설치대장입력완료127.03027937.760335
533정류장5녹양동3770121803의정부시923010일반버스비석거리표지설치대장입력완료2020-10-29삼아항업(주)2020-10-29삼아항업127.04364937.764327
534정류장3의정부1동3770121003의정부시170244마을버스13번종점표지설치대장입력완료2020-10-29삼아항업(주)2020-10-29삼아항업127.04354637.753191
535정류장2의정부1동3770121001의정부시170210일반버스대원표지설치대장입력완료2020-10-29삼아항업(주)2020-10-29삼아항업127.04331537.755519
536정류장1의정부1동3770121001의정부시170219일반버스녹양로터리표지설치대장입력완료127.04297337.757158