Overview

Dataset statistics

Number of variables12
Number of observations53
Missing cells87
Missing cells (%)13.7%
Duplicate rows1
Duplicate rows (%)1.9%
Total size in memory5.3 KiB
Average record size in memory101.5 B

Variable types

Categorical6
Text4
Numeric2

Dataset

Description경기도 여주시의 온기나눔쉼터 설치현황 데이터입니다. 설치장소명, 소재지도로명주소, 소재지지번주소, 위도, 경도, 관리기관 등의 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15100794/fileData.do

Alerts

기준년도 has constant value ""Constant
시군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 1 (1.9%) duplicate rowsDuplicates
관리기관 is highly overall correlated with 관리기관전화번호High correlation
관리기관전화번호 is highly overall correlated with 관리기관High correlation
위도 is highly overall correlated with 읍면동명High correlation
경도 is highly overall correlated with 읍면동명High correlation
읍면동명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
관리기관 is highly imbalanced (58.2%)Imbalance
관리기관전화번호 is highly imbalanced (58.2%)Imbalance
관리번호 has 43 (81.1%) missing valuesMissing
소재지도로명주소 has 44 (83.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 14:11:26.510372
Analysis finished2023-12-12 14:11:27.915182
Duration1.4 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
2022
53 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 53
100.0%

Length

2023-12-12T23:11:27.998261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:11:28.093277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 53
100.0%

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
여주시
53 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
여주시 53
100.0%

Length

2023-12-12T23:11:28.208869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:11:28.311390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여주시 53
100.0%

읍면동명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)35.8%
Missing0
Missing (%)0.0%
Memory size556.0 B
홍문동
7 
가남읍
5 
대신면
5 
흥천면
4 
오학동
3 
Other values (14)
29 

Length

Max length3
Median length3
Mean length2.8679245
Min length2

Unique

Unique3 ?
Unique (%)5.7%

Sample

1st row대신면
2nd row대신면
3rd row오학동
4th row오학동
5th row금사면

Common Values

ValueCountFrequency (%)
홍문동 7
13.2%
가남읍 5
 
9.4%
대신면 5
 
9.4%
흥천면 4
 
7.5%
오학동 3
 
5.7%
하동 3
 
5.7%
점동면 3
 
5.7%
산북면 3
 
5.7%
금사면 3
 
5.7%
교동 2
 
3.8%
Other values (9) 15
28.3%

Length

2023-12-12T23:11:28.406806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
홍문동 7
13.2%
대신면 5
 
9.4%
가남읍 5
 
9.4%
흥천면 4
 
7.5%
오학동 3
 
5.7%
하동 3
 
5.7%
점동면 3
 
5.7%
산북면 3
 
5.7%
금사면 3
 
5.7%
강천면 2
 
3.8%
Other values (9) 15
28.3%

관리번호
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing43
Missing (%)81.1%
Memory size556.0 B
2023-12-12T23:11:28.572972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters60
Distinct characters16
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

Unique10 ?
Unique (%)100.0%

Sample

1st row대신-001
2nd row대신-002
3rd row오학-001
4th row오학-002
5th row금사-001
ValueCountFrequency (%)
대신-001 1
10.0%
대신-002 1
10.0%
오학-001 1
10.0%
오학-002 1
10.0%
금사-001 1
10.0%
금사-002 1
10.0%
여흥-001 1
10.0%
산북-001 1
10.0%
가남-001 1
10.0%
가남-002 1
10.0%
2023-12-12T23:11:28.892276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
33.3%
- 10
16.7%
1 6
 
10.0%
2 4
 
6.7%
대 2
 
3.3%
신 2
 
3.3%
오 2
 
3.3%
학 2
 
3.3%
금 2
 
3.3%
사 2
 
3.3%
Other values (6) 8
 
13.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30
50.0%
Other Letter 20
33.3%
Dash Punctuation 10
 
16.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 2
10.0%
신 2
10.0%
오 2
10.0%
학 2
10.0%
금 2
10.0%
사 2
10.0%
가 2
10.0%
남 2
10.0%
여 1
5.0%
흥 1
5.0%
Other values (2) 2
10.0%
Decimal Number
ValueCountFrequency (%)
0 20
66.7%
1 6
 
20.0%
2 4
 
13.3%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40
66.7%
Hangul 20
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 2
10.0%
신 2
10.0%
오 2
10.0%
학 2
10.0%
금 2
10.0%
사 2
10.0%
가 2
10.0%
남 2
10.0%
여 1
5.0%
흥 1
5.0%
Other values (2) 2
10.0%
Common
ValueCountFrequency (%)
0 20
50.0%
- 10
25.0%
1 6
 
15.0%
2 4
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40
66.7%
Hangul 20
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
50.0%
- 10
25.0%
1 6
 
15.0%
2 4
 
10.0%
Hangul
ValueCountFrequency (%)
대 2
10.0%
신 2
10.0%
오 2
10.0%
학 2
10.0%
금 2
10.0%
사 2
10.0%
가 2
10.0%
남 2
10.0%
여 1
5.0%
흥 1
5.0%
Other values (2) 2
10.0%

설치장소명
Text

Distinct47
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T23:11:29.444725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length6.9056604
Min length3

Characters and Unicode

Total characters366
Distinct characters115
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)81.1%

Sample

1st row대신고등학교 앞 버스승강장(여주방면)
2nd row대신고등학교 앞 버스승강장(대신방면)
3rd row벽산아파트 앞
4th row여주오드카운티 앞
5th row금사면사무소 앞
ValueCountFrequency (%)
앞 14
 
15.9%
여주터미널 5
 
5.7%
맞은편 4
 
4.5%
양방향 4
 
4.5%
버스승강장 4
 
4.5%
마을회관 3
 
3.4%
후포리 2
 
2.3%
대신고등학교 2
 
2.3%
농협여주시지부 2
 
2.3%
효지리 2
 
2.3%
Other values (44) 46
52.3%
2023-12-12T23:11:29.873086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
9.6%
리 21
 
5.7%
주 15
 
4.1%
여 14
 
3.8%
앞 14
 
3.8%
장 7
 
1.9%
아 7
 
1.9%
신 7
 
1.9%
스 6
 
1.6%
강 6
 
1.6%
Other values (105) 234
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 322
88.0%
Space Separator 35
 
9.6%
Open Punctuation 3
 
0.8%
Close Punctuation 3
 
0.8%
Decimal Number 3
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 21
 
6.5%
주 15
 
4.7%
여 14
 
4.3%
앞 14
 
4.3%
장 7
 
2.2%
아 7
 
2.2%
신 7
 
2.2%
스 6
 
1.9%
강 6
 
1.9%
승 6
 
1.9%
Other values (100) 219
68.0%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 322
88.0%
Common 44
 
12.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 21
 
6.5%
주 15
 
4.7%
여 14
 
4.3%
앞 14
 
4.3%
장 7
 
2.2%
아 7
 
2.2%
신 7
 
2.2%
스 6
 
1.9%
강 6
 
1.9%
승 6
 
1.9%
Other values (100) 219
68.0%
Common
ValueCountFrequency (%)
35
79.5%
( 3
 
6.8%
) 3
 
6.8%
1 2
 
4.5%
2 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 322
88.0%
ASCII 44
 
12.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35
79.5%
( 3
 
6.8%
) 3
 
6.8%
1 2
 
4.5%
2 1
 
2.3%
Hangul
ValueCountFrequency (%)
리 21
 
6.5%
주 15
 
4.7%
여 14
 
4.3%
앞 14
 
4.3%
장 7
 
2.2%
아 7
 
2.2%
신 7
 
2.2%
스 6
 
1.9%
강 6
 
1.9%
승 6
 
1.9%
Other values (100) 219
68.0%

소재지도로명주소
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing44
Missing (%)83.0%
Memory size556.0 B
2023-12-12T23:11:30.076294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length16.666667
Min length14

Characters and Unicode

Total characters150
Distinct characters36
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

Unique9 ?
Unique (%)100.0%

Sample

1st row경기도 여주시 도예로 83-36
2nd row경기도 여주시 세종로 78
3rd row경기도 여주시 청심로 93
4th row경기도 여주시 가남읍 태평로 21-1
5th row경기도 여주시 능서면 마장로 67
ValueCountFrequency (%)
경기도 9
23.1%
여주시 9
23.1%
능서면 2
 
5.1%
도예로 2
 
5.1%
세종로 2
 
5.1%
마장로 2
 
5.1%
356-8 1
 
2.6%
80 1
 
2.6%
교동로 1
 
2.6%
68 1
 
2.6%
Other values (9) 9
23.1%
2023-12-12T23:11:30.393360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
20.0%
도 11
 
7.3%
경 9
 
6.0%
여 9
 
6.0%
주 9
 
6.0%
시 9
 
6.0%
로 9
 
6.0%
기 9
 
6.0%
8 5
 
3.3%
3 4
 
2.7%
Other values (26) 46
30.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90
60.0%
Space Separator 30
 
20.0%
Decimal Number 26
 
17.3%
Dash Punctuation 4
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 11
12.2%
경 9
10.0%
여 9
10.0%
주 9
10.0%
시 9
10.0%
로 9
10.0%
기 9
10.0%
종 2
 
2.2%
능 2
 
2.2%
장 2
 
2.2%
Other values (14) 19
21.1%
Decimal Number
ValueCountFrequency (%)
8 5
19.2%
3 4
15.4%
6 4
15.4%
7 3
11.5%
1 3
11.5%
9 3
11.5%
2 1
 
3.8%
0 1
 
3.8%
5 1
 
3.8%
4 1
 
3.8%
Space Separator
ValueCountFrequency (%)
30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90
60.0%
Common 60
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 11
12.2%
경 9
10.0%
여 9
10.0%
주 9
10.0%
시 9
10.0%
로 9
10.0%
기 9
10.0%
종 2
 
2.2%
능 2
 
2.2%
장 2
 
2.2%
Other values (14) 19
21.1%
Common
ValueCountFrequency (%)
30
50.0%
8 5
 
8.3%
3 4
 
6.7%
- 4
 
6.7%
6 4
 
6.7%
7 3
 
5.0%
1 3
 
5.0%
9 3
 
5.0%
2 1
 
1.7%
0 1
 
1.7%
Other values (2) 2
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90
60.0%
ASCII 60
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30
50.0%
8 5
 
8.3%
3 4
 
6.7%
- 4
 
6.7%
6 4
 
6.7%
7 3
 
5.0%
1 3
 
5.0%
9 3
 
5.0%
2 1
 
1.7%
0 1
 
1.7%
Other values (2) 2
 
3.3%
Hangul
ValueCountFrequency (%)
도 11
12.2%
경 9
10.0%
여 9
10.0%
주 9
10.0%
시 9
10.0%
로 9
10.0%
기 9
10.0%
종 2
 
2.2%
능 2
 
2.2%
장 2
 
2.2%
Other values (14) 19
21.1%

소재지지번주소
Text

Distinct47
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T23:11:30.668216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length18.641509
Min length14

Characters and Unicode

Total characters988
Distinct characters71
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

Unique41 ?
Unique (%)77.4%

Sample

1st row경기도 여주시 대신면 후포리 271-14
2nd row경기도 여주시 대신면 후포리 271-14
3rd row경기도 여주시 현암동 179-14
4th row경기도 여주시 현암동 683
5th row경기도 여주시 금사면 이포리 250-3
ValueCountFrequency (%)
경기도 53
22.1%
여주시 53
22.1%
홍문동 8
 
3.3%
대신면 5
 
2.1%
가남읍 5
 
2.1%
후포리 4
 
1.7%
현암동 4
 
1.7%
흥천면 4
 
1.7%
점동면 3
 
1.2%
하동 3
 
1.2%
Other values (77) 98
40.8%
2023-12-12T23:11:31.052746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
187
18.9%
도 54
 
5.5%
주 54
 
5.5%
경 53
 
5.4%
기 53
 
5.4%
여 53
 
5.4%
시 53
 
5.4%
1 49
 
5.0%
- 38
 
3.8%
2 30
 
3.0%
Other values (61) 364
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 556
56.3%
Decimal Number 207
 
21.0%
Space Separator 187
 
18.9%
Dash Punctuation 38
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 54
 
9.7%
주 54
 
9.7%
경 53
 
9.5%
기 53
 
9.5%
여 53
 
9.5%
시 53
 
9.5%
리 28
 
5.0%
동 27
 
4.9%
면 24
 
4.3%
신 9
 
1.6%
Other values (49) 148
26.6%
Decimal Number
ValueCountFrequency (%)
1 49
23.7%
2 30
14.5%
4 21
10.1%
3 20
9.7%
5 19
 
9.2%
6 17
 
8.2%
9 17
 
8.2%
7 13
 
6.3%
8 12
 
5.8%
0 9
 
4.3%
Space Separator
ValueCountFrequency (%)
187
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 556
56.3%
Common 432
43.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 54
 
9.7%
주 54
 
9.7%
경 53
 
9.5%
기 53
 
9.5%
여 53
 
9.5%
시 53
 
9.5%
리 28
 
5.0%
동 27
 
4.9%
면 24
 
4.3%
신 9
 
1.6%
Other values (49) 148
26.6%
Common
ValueCountFrequency (%)
187
43.3%
1 49
 
11.3%
- 38
 
8.8%
2 30
 
6.9%
4 21
 
4.9%
3 20
 
4.6%
5 19
 
4.4%
6 17
 
3.9%
9 17
 
3.9%
7 13
 
3.0%
Other values (2) 21
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 556
56.3%
ASCII 432
43.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
187
43.3%
1 49
 
11.3%
- 38
 
8.8%
2 30
 
6.9%
4 21
 
4.9%
3 20
 
4.6%
5 19
 
4.4%
6 17
 
3.9%
9 17
 
3.9%
7 13
 
3.0%
Other values (2) 21
 
4.9%
Hangul
ValueCountFrequency (%)
도 54
 
9.7%
주 54
 
9.7%
경 53
 
9.5%
기 53
 
9.5%
여 53
 
9.5%
시 53
 
9.5%
리 28
 
5.0%
동 27
 
4.9%
면 24
 
4.3%
신 9
 
1.6%
Other values (49) 148
26.6%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.304849
Minimum37.177817
Maximum37.41451
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T23:11:31.208945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.177817
5-th percentile37.20553
Q137.282827
median37.298831
Q337.337908
95-th percentile37.399645
Maximum37.41451
Range0.23669242
Interquartile range (IQR)0.05508088

Descriptive statistics

Standard deviation0.058660672
Coefficient of variation (CV)0.0015724678
Kurtosis-0.37571914
Mean37.304849
Median Absolute Deviation (MAD)0.03346001
Skewness-0.069153309
Sum1977.157
Variance0.0034410744
MonotonicityNot monotonic
2023-12-12T23:11:31.369878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
37.36376409 2
 
3.8%
37.30666296 2
 
3.8%
37.29055055 2
 
3.8%
37.3996448 2
 
3.8%
37.33229112 2
 
3.8%
37.29385265 2
 
3.8%
37.28282679 1
 
1.9%
37.21497666 1
 
1.9%
37.2037301 1
 
1.9%
37.40969862 1
 
1.9%
Other values (37) 37
69.8%
ValueCountFrequency (%)
37.17781745 1
1.9%
37.20280652 1
1.9%
37.2037301 1
1.9%
37.20673065 1
1.9%
37.20781042 1
1.9%
37.20856193 1
1.9%
37.21497666 1
1.9%
37.23828021 1
1.9%
37.25277967 1
1.9%
37.2566084 1
1.9%
ValueCountFrequency (%)
37.41450987 1
1.9%
37.40969862 1
1.9%
37.3996448 2
3.8%
37.39517586 1
1.9%
37.39348611 1
1.9%
37.38912319 1
1.9%
37.37623725 1
1.9%
37.37331517 1
1.9%
37.36376409 2
3.8%
37.35590899 1
1.9%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.60519
Minimum127.44171
Maximum127.71443
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T23:11:31.540883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.44171
5-th percentile127.4915
Q1127.55365
median127.63342
Q3127.63919
95-th percentile127.70734
Maximum127.71443
Range0.2727224
Interquartile range (IQR)0.0855424

Descriptive statistics

Standard deviation0.064606444
Coefficient of variation (CV)0.0005062995
Kurtosis0.39493792
Mean127.60519
Median Absolute Deviation (MAD)0.0291979
Skewness-0.73998739
Sum6763.0751
Variance0.0041739926
MonotonicityNot monotonic
2023-12-12T23:11:31.684630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
127.6042194 2
 
3.8%
127.6395207 2
 
3.8%
127.6349192 2
 
3.8%
127.441709 2
 
3.8%
127.5427556 2
 
3.8%
127.6357814 2
 
3.8%
127.6285287 1
 
1.9%
127.5352379 1
 
1.9%
127.7126049 1
 
1.9%
127.4492902 1
 
1.9%
Other values (37) 37
69.8%
ValueCountFrequency (%)
127.441709 2
3.8%
127.4492902 1
1.9%
127.5196436 1
1.9%
127.5221204 1
1.9%
127.5315095 1
1.9%
127.5334006 1
1.9%
127.5350635 1
1.9%
127.5352379 1
1.9%
127.5427556 2
3.8%
127.5434766 1
1.9%
ValueCountFrequency (%)
127.7144314 1
1.9%
127.712737 1
1.9%
127.7126049 1
1.9%
127.7038221 1
1.9%
127.6803243 1
1.9%
127.663918 1
1.9%
127.6626967 1
1.9%
127.6551297 1
1.9%
127.654686 1
1.9%
127.6405257 1
1.9%

관리기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size556.0 B
여주시 교통행정과
43 
여주시 대신면 행정복지센터
 
2
여주시 오학동 행정복지센터
 
2
여주시 금사면 행정복지센터
 
2
여주시 가남읍 행정복지센터
 
2
Other values (2)
 
2

Length

Max length14
Median length9
Mean length9.9433962
Min length9

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row여주시 대신면 행정복지센터
2nd row여주시 대신면 행정복지센터
3rd row여주시 오학동 행정복지센터
4th row여주시 오학동 행정복지센터
5th row여주시 금사면 행정복지센터

Common Values

ValueCountFrequency (%)
여주시 교통행정과 43
81.1%
여주시 대신면 행정복지센터 2
 
3.8%
여주시 오학동 행정복지센터 2
 
3.8%
여주시 금사면 행정복지센터 2
 
3.8%
여주시 가남읍 행정복지센터 2
 
3.8%
여주시 여흥동 행정복지센터 1
 
1.9%
여주시 산북면 행정복지센터 1
 
1.9%

Length

2023-12-12T23:11:31.831277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:11:31.956254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
여주시 53
45.7%
교통행정과 43
37.1%
행정복지센터 10
 
8.6%
대신면 2
 
1.7%
오학동 2
 
1.7%
금사면 2
 
1.7%
가남읍 2
 
1.7%
여흥동 1
 
0.9%
산북면 1
 
0.9%

관리기관전화번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size556.0 B
031-887-2623
43 
031-887-3948
 
2
031-887-3974
 
2
031-887-3907
 
2
031-887-3346
 
2
Other values (2)
 
2

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique2 ?
Unique (%)3.8%

Sample

1st row031-887-3948
2nd row031-887-3948
3rd row031-887-3974
4th row031-887-3974
5th row031-887-3907

Common Values

ValueCountFrequency (%)
031-887-2623 43
81.1%
031-887-3948 2
 
3.8%
031-887-3974 2
 
3.8%
031-887-3907 2
 
3.8%
031-887-3346 2
 
3.8%
031-887-3772 1
 
1.9%
031-887-3927 1
 
1.9%

Length

2023-12-12T23:11:32.077648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:11:32.184159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-887-2623 43
81.1%
031-887-3948 2
 
3.8%
031-887-3974 2
 
3.8%
031-887-3907 2
 
3.8%
031-887-3346 2
 
3.8%
031-887-3772 1
 
1.9%
031-887-3927 1
 
1.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-06-30
53 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-30
2nd row2023-06-30
3rd row2023-06-30
4th row2023-06-30
5th row2023-06-30

Common Values

ValueCountFrequency (%)
2023-06-30 53
100.0%

Length

2023-12-12T23:11:32.331413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:11:32.444180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-30 53
100.0%

Interactions

2023-12-12T23:11:27.319036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:11:27.113077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:11:27.414569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:11:27.218669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:11:32.517957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명관리번호설치장소명소재지도로명주소소재지지번주소위도경도관리기관관리기관전화번호
읍면동명1.0001.0000.9831.0000.9800.8980.9150.8410.841
관리번호1.0001.0001.000NaN1.0001.0001.0001.0001.000
설치장소명0.9831.0001.0001.0000.9961.0001.0000.9660.966
소재지도로명주소1.000NaN1.0001.0001.0001.0001.0001.0001.000
소재지지번주소0.9801.0000.9961.0001.0001.0001.0000.0000.000
위도0.8981.0001.0001.0001.0001.0000.7360.5820.582
경도0.9151.0001.0001.0001.0000.7361.0000.6560.656
관리기관0.8411.0000.9661.0000.0000.5820.6561.0001.000
관리기관전화번호0.8411.0000.9661.0000.0000.5820.6561.0001.000
2023-12-12T23:11:32.682654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명관리기관관리기관전화번호
읍면동명1.0000.4930.493
관리기관0.4931.0001.000
관리기관전화번호0.4931.0001.000
2023-12-12T23:11:32.801364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도읍면동명관리기관관리기관전화번호
위도1.000-0.3710.5480.3270.327
경도-0.3711.0000.5910.4100.410
읍면동명0.5480.5911.0000.4930.493
관리기관0.3270.4100.4931.0001.000
관리기관전화번호0.3270.4100.4931.0001.000

Missing values

2023-12-12T23:11:27.551419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:11:27.729959image/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.
2023-12-12T23:11:27.854769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

기준년도시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소위도경도관리기관관리기관전화번호데이터기준일자
02022여주시대신면대신-001대신고등학교 앞 버스승강장(여주방면)<NA>경기도 여주시 대신면 후포리 271-1437.363764127.604219여주시 대신면 행정복지센터031-887-39482023-06-30
12022여주시대신면대신-002대신고등학교 앞 버스승강장(대신방면)<NA>경기도 여주시 대신면 후포리 271-1437.363764127.604219여주시 대신면 행정복지센터031-887-39482023-06-30
22022여주시오학동오학-001벽산아파트 앞<NA>경기도 여주시 현암동 179-1437.306663127.639521여주시 오학동 행정복지센터031-887-39742023-06-30
32022여주시오학동오학-002여주오드카운티 앞경기도 여주시 도예로 83-36경기도 여주시 현암동 68337.312136127.640526여주시 오학동 행정복지센터031-887-39742023-06-30
42022여주시금사면금사-001금사면사무소 앞<NA>경기도 여주시 금사면 이포리 250-337.389123127.531509여주시 금사면 행정복지센터031-887-39072023-06-30
52022여주시금사면금사-002금사1리 버스승강장<NA>경기도 여주시 금사면 금사리 112-337.41451127.52212여주시 금사면 행정복지센터031-887-39072023-06-30
62022여주시여흥동여흥-001여주터미널<NA>경기도 여주시 홍문동 29037.290551127.634919여주시 여흥동 행정복지센터031-887-37722023-06-30
72022여주시산북면산북-001상품삼거리 버스승강장<NA>경기도 여주시 산북면 상품리 169-2437.399645127.441709여주시 산북면 행정복지센터031-887-39272023-06-30
82022여주시가남읍가남-001제일고 앞 버스승강장<NA>경기도 여주시 가남읍 심석리 318-537.20781127.553651여주시 가남읍 행정복지센터031-887-33462023-06-30
92022여주시가남읍가남-002마을회관 앞 버스승강장<NA>경기도 여주시 가남읍 오산리 51137.23828127.558121여주시 가남읍 행정복지센터031-887-33462023-06-30
기준년도시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소위도경도관리기관관리기관전화번호데이터기준일자
432022여주시교동<NA>여주대 정문<NA>경기도 여주시 교동 산6-1337.268246127.637393여주시 교통행정과031-887-26232023-06-30
442022여주시하동<NA>여주축협본점<NA>경기도 여주시 하동 192-237.298415127.633417여주시 교통행정과031-887-26232023-06-30
452022여주시오학동<NA>오드카운티아파트경기도 여주시 도예로 199-47경기도 여주시 오학동 4837.319489127.65513여주시 교통행정과031-887-26232023-06-30
462022여주시현암동<NA>이편한세상아파트<NA>경기도 여주시 현암동 152-1337.313383127.639882여주시 교통행정과031-887-26232023-06-30
472022여주시천송동<NA>신륵사 앞<NA>경기도 여주시 천송동 538-537.300769127.654686여주시 교통행정과031-887-26232023-06-30
482022여주시점봉동<NA>세종그랑시아 아파트<NA>경기도 여주시 점봉동 466-637.256608127.638468여주시 교통행정과031-887-26232023-06-30
492022여주시흥천면<NA>이포증학교 앞<NA>경기도 여주시 흥천면 계신리 576-637.376237127.519644여주시 교통행정과031-887-26232023-06-30
502022여주시하동<NA>세종병원 앞<NA>경기도 여주시 하동 63-237.301053127.62542여주시 교통행정과031-887-26232023-06-30
512022여주시창동<NA>여주경찰서 앞<NA>경기도 여주시 창동 154-737.293853127.635781여주시 교통행정과031-887-26232023-06-30
522022여주시홍문동<NA>시민회관 앞<NA>경기도 여주시 홍문동 22737.293221127.635889여주시 교통행정과031-887-26232023-06-30

Duplicate rows

Most frequently occurring

기준년도시군명읍면동명관리번호설치장소명소재지도로명주소소재지지번주소위도경도관리기관관리기관전화번호데이터기준일자# duplicates
02022여주시흥천면<NA>효지리<NA>경기도 여주시 흥천면 효지리 217-1537.332291127.542756여주시 교통행정과031-887-26232023-06-302