Overview

Dataset statistics

Number of variables16
Number of observations92
Missing cells63
Missing cells (%)4.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory134.4 B

Variable types

Numeric3
Categorical9
Text3
Boolean1

Dataset

Description여름철 폭염 대비를 위한 횡단보도 그늘막 설치 현황설치장소명, 주소, 위도, 경도, 설치일자, 그늘막유형, 전체높이, 펼침지름, 영조물보험가입여부 등
Author경상북도 김천시
URLhttps://www.data.go.kr/data/15126897/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
보험가입유무 has constant value ""Constant
데이터기준일자 has constant value ""Constant
전체높이(m) is highly overall correlated with 설치일자 and 1 other fieldsHigh correlation
설치일자 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 설치일자 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 읍면동(행정동)High correlation
읍면동(행정동) is highly overall correlated with 경도High correlation
그늘막 유형 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
도로명주소 is highly imbalanced (63.9%)Imbalance
그늘막 유형 is highly imbalanced (57.4%)Imbalance
전체높이(m) is highly imbalanced (50.6%)Imbalance
연번 has 50 (54.3%) missing valuesMissing
설치장소명 has 13 (14.1%) missing valuesMissing
관리번호 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-04-21 14:54:09.023418
Analysis finished2024-04-21 14:54:14.140214
Duration5.12 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct42
Distinct (%)100.0%
Missing50
Missing (%)54.3%
Infinite0
Infinite (%)0.0%
Mean21.5
Minimum1
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-04-21T23:54:14.353815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.05
Q111.25
median21.5
Q331.75
95-th percentile39.95
Maximum42
Range41
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation12.267844
Coefficient of variation (CV)0.5705974
Kurtosis-1.2
Mean21.5
Median Absolute Deviation (MAD)10.5
Skewness0
Sum903
Variance150.5
MonotonicityStrictly increasing
2024-04-21T23:54:14.761612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
33 1
 
1.1%
25 1
 
1.1%
26 1
 
1.1%
27 1
 
1.1%
28 1
 
1.1%
29 1
 
1.1%
30 1
 
1.1%
31 1
 
1.1%
32 1
 
1.1%
34 1
 
1.1%
Other values (32) 32
34.8%
(Missing) 50
54.3%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
42 1
1.1%
41 1
1.1%
40 1
1.1%
39 1
1.1%
38 1
1.1%
37 1
1.1%
36 1
1.1%
35 1
1.1%
34 1
1.1%
33 1
1.1%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size864.0 B
경상북도
92 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 92
100.0%

Length

2024-04-21T23:54:15.155148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:54:15.432719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 92
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size864.0 B
김천시
92 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
김천시 92
100.0%

Length

2024-04-21T23:54:15.723234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:54:16.006049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
김천시 92
100.0%

읍면동(행정동)
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size864.0 B
율곡동
46 
대신동
14 
대곡동
12 
지좌동
10 
평화남산동
6 

Length

Max length5
Median length3
Mean length3.1304348
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대곡동
2nd row대곡동
3rd row율곡동
4th row율곡동
5th row율곡동

Common Values

ValueCountFrequency (%)
율곡동 46
50.0%
대신동 14
 
15.2%
대곡동 12
 
13.0%
지좌동 10
 
10.9%
평화남산동 6
 
6.5%
자산동 4
 
4.3%

Length

2024-04-21T23:54:16.338962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:54:16.689894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
율곡동 46
50.0%
대신동 14
 
15.2%
대곡동 12
 
13.0%
지좌동 10
 
10.9%
평화남산동 6
 
6.5%
자산동 4
 
4.3%

관리번호
Text

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size864.0 B
2024-04-21T23:54:17.788742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7.2608696
Min length7

Characters and Unicode

Total characters668
Distinct characters17
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

Unique92 ?
Unique (%)100.0%

Sample

1st row김천시-001
2nd row김천시-002
3rd row김천시-003
4th row김천시-004
5th row김천시-005
ValueCountFrequency (%)
김천시-001 1
 
1.1%
김천시-058 1
 
1.1%
김천시-068 1
 
1.1%
김천시-067 1
 
1.1%
김천시-066 1
 
1.1%
김천시-065 1
 
1.1%
김천시-064 1
 
1.1%
김천시-063 1
 
1.1%
김천시-062 1
 
1.1%
김천시-061 1
 
1.1%
Other values (82) 82
89.1%
2024-04-21T23:54:19.043613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 109
16.3%
- 100
15.0%
김 92
13.8%
시 92
13.8%
천 92
13.8%
3 20
 
3.0%
5 20
 
3.0%
4 20
 
3.0%
2 20
 
3.0%
1 20
 
3.0%
Other values (7) 83
12.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 300
44.9%
Decimal Number 268
40.1%
Dash Punctuation 100
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 109
40.7%
3 20
 
7.5%
5 20
 
7.5%
4 20
 
7.5%
2 20
 
7.5%
1 20
 
7.5%
6 19
 
7.1%
7 18
 
6.7%
8 15
 
5.6%
9 7
 
2.6%
Other Letter
ValueCountFrequency (%)
김 92
30.7%
시 92
30.7%
천 92
30.7%
스 8
 
2.7%
마 8
 
2.7%
트 8
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 368
55.1%
Hangul 300
44.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 109
29.6%
- 100
27.2%
3 20
 
5.4%
5 20
 
5.4%
4 20
 
5.4%
2 20
 
5.4%
1 20
 
5.4%
6 19
 
5.2%
7 18
 
4.9%
8 15
 
4.1%
Hangul
ValueCountFrequency (%)
김 92
30.7%
시 92
30.7%
천 92
30.7%
스 8
 
2.7%
마 8
 
2.7%
트 8
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 368
55.1%
Hangul 300
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 109
29.6%
- 100
27.2%
3 20
 
5.4%
5 20
 
5.4%
4 20
 
5.4%
2 20
 
5.4%
1 20
 
5.4%
6 19
 
5.2%
7 18
 
4.9%
8 15
 
4.1%
Hangul
ValueCountFrequency (%)
김 92
30.7%
시 92
30.7%
천 92
30.7%
스 8
 
2.7%
마 8
 
2.7%
트 8
 
2.7%

설치장소명
Text

MISSING 

Distinct75
Distinct (%)94.9%
Missing13
Missing (%)14.1%
Memory size864.0 B
2024-04-21T23:54:19.897739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length10.658228
Min length5

Characters and Unicode

Total characters842
Distinct characters175
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)92.4%

Sample

1st row김천고 앞
2nd row시민탑 삼거리
3rd rowKCC스위첸 사거리
4th rowKCC스위첸 사거리
5th row율곡고 앞
ValueCountFrequency (%)
앞 55
25.0%
사거리 14
 
6.4%
건너편 8
 
3.6%
정문 6
 
2.7%
더 4
 
1.8%
횡단보도 4
 
1.8%
공원 4
 
1.8%
테라스앞 4
 
1.8%
율곡고 3
 
1.4%
삼거리 3
 
1.4%
Other values (96) 115
52.3%
2024-04-21T23:54:21.008901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
146
 
17.3%
앞 62
 
7.4%
리 31
 
3.7%
거 27
 
3.2%
사 21
 
2.5%
스 17
 
2.0%
아 14
 
1.7%
트 13
 
1.5%
파 13
 
1.5%
) 12
 
1.4%
Other values (165) 486
57.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 628
74.6%
Space Separator 146
 
17.3%
Uppercase Letter 23
 
2.7%
Decimal Number 18
 
2.1%
Close Punctuation 12
 
1.4%
Open Punctuation 12
 
1.4%
Lowercase Letter 2
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 62
 
9.9%
리 31
 
4.9%
거 27
 
4.3%
사 21
 
3.3%
스 17
 
2.7%
아 14
 
2.2%
트 13
 
2.1%
파 13
 
2.1%
신 11
 
1.8%
곡 11
 
1.8%
Other values (143) 408
65.0%
Uppercase Letter
ValueCountFrequency (%)
K 5
21.7%
C 5
21.7%
T 4
17.4%
L 2
 
8.7%
H 1
 
4.3%
U 1
 
4.3%
D 1
 
4.3%
R 1
 
4.3%
O 1
 
4.3%
W 1
 
4.3%
Decimal Number
ValueCountFrequency (%)
2 6
33.3%
1 5
27.8%
4 3
16.7%
0 2
 
11.1%
6 1
 
5.6%
3 1
 
5.6%
Space Separator
ValueCountFrequency (%)
146
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 628
74.6%
Common 189
 
22.4%
Latin 25
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 62
 
9.9%
리 31
 
4.9%
거 27
 
4.3%
사 21
 
3.3%
스 17
 
2.7%
아 14
 
2.2%
트 13
 
2.1%
파 13
 
2.1%
신 11
 
1.8%
곡 11
 
1.8%
Other values (143) 408
65.0%
Latin
ValueCountFrequency (%)
K 5
20.0%
C 5
20.0%
T 4
16.0%
s 2
 
8.0%
L 2
 
8.0%
H 1
 
4.0%
U 1
 
4.0%
D 1
 
4.0%
R 1
 
4.0%
O 1
 
4.0%
Other values (2) 2
 
8.0%
Common
ValueCountFrequency (%)
146
77.2%
) 12
 
6.3%
( 12
 
6.3%
2 6
 
3.2%
1 5
 
2.6%
4 3
 
1.6%
0 2
 
1.1%
6 1
 
0.5%
3 1
 
0.5%
- 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 628
74.6%
ASCII 214
 
25.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
146
68.2%
) 12
 
5.6%
( 12
 
5.6%
2 6
 
2.8%
K 5
 
2.3%
C 5
 
2.3%
1 5
 
2.3%
T 4
 
1.9%
4 3
 
1.4%
0 2
 
0.9%
Other values (12) 14
 
6.5%
Hangul
ValueCountFrequency (%)
앞 62
 
9.9%
리 31
 
4.9%
거 27
 
4.3%
사 21
 
3.3%
스 17
 
2.7%
아 14
 
2.2%
트 13
 
2.1%
파 13
 
2.1%
신 11
 
1.8%
곡 11
 
1.8%
Other values (143) 408
65.0%

지번주소
Text

Distinct72
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Memory size864.0 B
2024-04-21T23:54:21.832004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length17.934783
Min length15

Characters and Unicode

Total characters1650
Distinct characters45
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

Unique58 ?
Unique (%)63.0%

Sample

1st row경상북도 김천시 부곡동 1557
2nd row경상북도 김천시 부곡동 450-2
3rd row경상북도 김천시 율곡동 831
4th row경상북도 김천시 율곡동 831
5th row경상북도 김천시 율곡동 846
ValueCountFrequency (%)
경상북도 92
24.9%
김천시 92
24.9%
율곡동 46
12.5%
부곡동 9
 
2.4%
신음동 9
 
2.4%
덕곡동 6
 
1.6%
평화동 5
 
1.4%
846 4
 
1.1%
지좌동 4
 
1.1%
883 4
 
1.1%
Other values (79) 98
26.6%
2024-04-21T23:54:22.896592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
369
22.4%
경 92
 
5.6%
북 92
 
5.6%
도 92
 
5.6%
김 92
 
5.6%
천 92
 
5.6%
시 92
 
5.6%
동 92
 
5.6%
상 92
 
5.6%
곡 61
 
3.7%
Other values (35) 484
29.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 918
55.6%
Space Separator 369
22.4%
Decimal Number 328
 
19.9%
Dash Punctuation 35
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 92
10.0%
북 92
10.0%
도 92
10.0%
김 92
10.0%
천 92
10.0%
시 92
10.0%
동 92
10.0%
상 92
10.0%
곡 61
6.6%
율 46
5.0%
Other values (23) 75
8.2%
Decimal Number
ValueCountFrequency (%)
1 55
16.8%
8 48
14.6%
4 45
13.7%
3 34
10.4%
2 28
8.5%
6 28
8.5%
9 26
7.9%
0 24
7.3%
7 21
 
6.4%
5 19
 
5.8%
Space Separator
ValueCountFrequency (%)
369
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 918
55.6%
Common 732
44.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 92
10.0%
북 92
10.0%
도 92
10.0%
김 92
10.0%
천 92
10.0%
시 92
10.0%
동 92
10.0%
상 92
10.0%
곡 61
6.6%
율 46
5.0%
Other values (23) 75
8.2%
Common
ValueCountFrequency (%)
369
50.4%
1 55
 
7.5%
8 48
 
6.6%
4 45
 
6.1%
- 35
 
4.8%
3 34
 
4.6%
2 28
 
3.8%
6 28
 
3.8%
9 26
 
3.6%
0 24
 
3.3%
Other values (2) 40
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 918
55.6%
ASCII 732
44.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
369
50.4%
1 55
 
7.5%
8 48
 
6.6%
4 45
 
6.1%
- 35
 
4.8%
3 34
 
4.6%
2 28
 
3.8%
6 28
 
3.8%
9 26
 
3.6%
0 24
 
3.3%
Other values (2) 40
 
5.5%
Hangul
ValueCountFrequency (%)
경 92
10.0%
북 92
10.0%
도 92
10.0%
김 92
10.0%
천 92
10.0%
시 92
10.0%
동 92
10.0%
상 92
10.0%
곡 61
6.6%
율 46
5.0%
Other values (23) 75
8.2%

도로명주소
Categorical

IMBALANCE 

Distinct18
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Memory size864.0 B
74 
경상북도 김천시 혁신6로 31 (율곡동)
 
2
경상북도 김천시 김천로 149-1 (성내동)
 
1
경상북도 김천시 자산로 148 (성내동)
 
1
경상북도 김천시 용전3로 10 (율곡동, 경북혁신엘에이치천년나무3단지)
 
1
Other values (13)
13 

Length

Max length44
Median length1
Mean length6.0108696
Min length1

Unique

Unique16 ?
Unique (%)17.4%

Sample

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

Common Values

ValueCountFrequency (%)
74
80.4%
경상북도 김천시 혁신6로 31 (율곡동) 2
 
2.2%
경상북도 김천시 김천로 149-1 (성내동) 1
 
1.1%
경상북도 김천시 자산로 148 (성내동) 1
 
1.1%
경상북도 김천시 용전3로 10 (율곡동, 경북혁신엘에이치천년나무3단지) 1
 
1.1%
경상북도 김천시 해오름1로 17 (율곡동, 경북김천혁신엘에이치천년나무4단지) 1
 
1.1%
경상북도 김천시 해오름2로3길 16 (율곡동) 1
 
1.1%
경상북도 김천시 혁신로 269 (율곡동) 1
 
1.1%
경상북도 김천시 혁신3로 5 (율곡동) 1
 
1.1%
경상북도 김천시 혁신8로 8 (율곡동) 1
 
1.1%
Other values (8) 8
 
8.7%

Length

2024-04-21T23:54:23.122225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경상북도 18
19.6%
김천시 18
19.6%
율곡동 10
 
10.9%
영남대로 4
 
4.3%
덕곡동 4
 
4.3%
성내동 2
 
2.2%
5 2
 
2.2%
31 2
 
2.2%
신음동 2
 
2.2%
시청로 2
 
2.2%
Other values (26) 28
30.4%

위도
Real number (ℝ)

UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.123965
Minimum36.114028
Maximum36.149189
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-04-21T23:54:23.347241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.114028
5-th percentile36.115906
Q136.119666
median36.123625
Q336.126785
95-th percentile36.136653
Maximum36.149189
Range0.0351613
Interquartile range (IQR)0.00711905

Descriptive statistics

Standard deviation0.0065172934
Coefficient of variation (CV)0.00018041468
Kurtosis1.670047
Mean36.123965
Median Absolute Deviation (MAD)0.00327585
Skewness1.1055302
Sum3323.4047
Variance4.2475113 × 10-5
MonotonicityNot monotonic
2024-04-21T23:54:23.615613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.1237512 1
 
1.1%
36.1158656 1
 
1.1%
36.124033 1
 
1.1%
36.124256 1
 
1.1%
36.1335187 1
 
1.1%
36.1262172 1
 
1.1%
36.1239019 1
 
1.1%
36.1265197 1
 
1.1%
36.1269707 1
 
1.1%
36.1160624 1
 
1.1%
Other values (82) 82
89.1%
ValueCountFrequency (%)
36.1140277 1
1.1%
36.1142462 1
1.1%
36.114387 1
1.1%
36.1157105 1
1.1%
36.1158656 1
1.1%
36.1159391 1
1.1%
36.1159745 1
1.1%
36.1160624 1
1.1%
36.1162203 1
1.1%
36.116321 1
1.1%
ValueCountFrequency (%)
36.149189 1
1.1%
36.1387595 1
1.1%
36.1384531 1
1.1%
36.1367628 1
1.1%
36.1366572 1
1.1%
36.1366496 1
1.1%
36.1349316 1
1.1%
36.1346707 1
1.1%
36.1345632 1
1.1%
36.1343385 1
1.1%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct92
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.14991
Minimum128.07538
Maximum128.19344
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size956.0 B
2024-04-21T23:54:23.878817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.07538
5-th percentile128.08971
Q1128.11699
median128.16595
Q3128.1827
95-th percentile128.19058
Maximum128.19344
Range0.1180608
Interquartile range (IQR)0.06571635

Descriptive statistics

Standard deviation0.037890666
Coefficient of variation (CV)0.00029567455
Kurtosis-1.4545506
Mean128.14991
Median Absolute Deviation (MAD)0.0240115
Skewness-0.39821064
Sum11789.792
Variance0.0014357026
MonotonicityNot monotonic
2024-04-21T23:54:24.139374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.0948502 1
 
1.1%
128.1824131 1
 
1.1%
128.187864 1
 
1.1%
128.187504 1
 
1.1%
128.1128132 1
 
1.1%
128.0904248 1
 
1.1%
128.100282 1
 
1.1%
128.0784787 1
 
1.1%
128.0753824 1
 
1.1%
128.1814787 1
 
1.1%
Other values (82) 82
89.1%
ValueCountFrequency (%)
128.0753824 1
1.1%
128.0784787 1
1.1%
128.0810218 1
1.1%
128.08914 1
1.1%
128.0891539 1
1.1%
128.0901602 1
1.1%
128.0904248 1
1.1%
128.0948502 1
1.1%
128.0953229 1
1.1%
128.0955854 1
1.1%
ValueCountFrequency (%)
128.1934432 1
1.1%
128.1919425 1
1.1%
128.1908501 1
1.1%
128.190787 1
1.1%
128.1906116 1
1.1%
128.190558 1
1.1%
128.1905353 1
1.1%
128.1904891 1
1.1%
128.1894438 1
1.1%
128.1880017 1
1.1%

설치일자
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size864.0 B
2019-07-01
30 
2018-07-01
10 
2018-06-01
8 
2018-10-01
8 
2018-09-01
6 
Other values (11)
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row2018-06-01
2nd row2018-06-01
3rd row2018-06-01
4th row2018-06-01
5th row2018-06-01

Common Values

ValueCountFrequency (%)
2019-07-01 30
32.6%
2018-07-01 10
 
10.9%
2018-06-01 8
 
8.7%
2018-10-01 8
 
8.7%
2018-09-01 6
 
6.5%
2019-08-01 5
 
5.4%
2022-08-22 5
 
5.4%
2020-08-30 3
 
3.3%
2020-08-31 3
 
3.3%
2021-05-21 3
 
3.3%
Other values (6) 11
 
12.0%

Length

2024-04-21T23:54:24.432791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-07-01 30
32.6%
2018-07-01 10
 
10.9%
2018-06-01 8
 
8.7%
2018-10-01 8
 
8.7%
2018-09-01 6
 
6.5%
2019-08-01 5
 
5.4%
2022-08-22 5
 
5.4%
2020-08-30 3
 
3.3%
2020-08-31 3
 
3.3%
2021-05-21 3
 
3.3%
Other values (6) 11
 
12.0%

그늘막 유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size864.0 B
고정형
84 
스마트형
 
8

Length

Max length4
Median length3
Mean length3.0869565
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고정형 84
91.3%
스마트형 8
 
8.7%

Length

2024-04-21T23:54:24.628067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:54:24.792171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고정형 84
91.3%
스마트형 8
 
8.7%

전체높이(m)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size864.0 B
3.5
72 
3.4
8 
5.0
 
7
3.7
 
3
3.0
 
2

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3.5
2nd row3.4
3rd row3.5
4th row3.5
5th row3.5

Common Values

ValueCountFrequency (%)
3.5 72
78.3%
3.4 8
 
8.7%
5.0 7
 
7.6%
3.7 3
 
3.3%
3.0 2
 
2.2%

Length

2024-04-21T23:54:24.958807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:54:25.126323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3.5 72
78.3%
3.4 8
 
8.7%
5.0 7
 
7.6%
3.7 3
 
3.3%
3.0 2
 
2.2%

펼침지름(m)
Categorical

Distinct3
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size864.0 B
5
62 
4
16 
3
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 62
67.4%
4 16
 
17.4%
3 14
 
15.2%

Length

2024-04-21T23:54:25.311414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:54:25.472564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 62
67.4%
4 16
 
17.4%
3 14
 
15.2%

보험가입유무
Boolean

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size220.0 B
True
92 
ValueCountFrequency (%)
True 92
100.0%
2024-04-21T23:54:25.606375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size864.0 B
2024-02-26
92 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-26
2nd row2024-02-26
3rd row2024-02-26
4th row2024-02-26
5th row2024-02-26

Common Values

ValueCountFrequency (%)
2024-02-26 92
100.0%

Length

2024-04-21T23:54:25.764403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T23:54:25.913540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-26 92
100.0%

Interactions

2024-04-21T23:54:11.939928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T23:54:10.491044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T23:54:11.186194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T23:54:12.171184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T23:54:10.714506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T23:54:11.418496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T23:54:12.431498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T23:54:10.948863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T23:54:11.686145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T23:54:26.029322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동(행정동)관리번호설치장소명지번주소도로명주소위도경도설치일자그늘막 유형전체높이(m)펼침지름(m)
연번1.0000.5411.0001.0000.8130.2390.2890.2930.992NaN0.0000.621
읍면동(행정동)0.5411.0001.0001.0001.0000.4560.7490.9140.5160.0000.3110.817
관리번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설치장소명1.0001.0001.0001.0000.9981.0000.9960.9841.0001.0001.0001.000
지번주소0.8131.0001.0000.9981.0001.0000.9960.9970.9270.0000.8230.959
도로명주소0.2390.4561.0001.0001.0001.0000.5420.0000.7090.0000.7130.641
위도0.2890.7491.0000.9960.9960.5421.0000.6430.4020.0000.3660.315
경도0.2930.9141.0000.9840.9970.0000.6431.0000.3690.2190.4230.791
설치일자0.9920.5161.0001.0000.9270.7090.4020.3691.0000.9980.9920.721
그늘막 유형NaN0.0001.0001.0000.0000.0000.0000.2190.9981.0000.7340.095
전체높이(m)0.0000.3111.0001.0000.8230.7130.3660.4230.9920.7341.0000.460
펼침지름(m)0.6210.8171.0001.0000.9590.6410.3150.7910.7210.0950.4601.000
2024-04-21T23:54:26.483249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
그늘막 유형펼침지름(m)전체높이(m)도로명주소설치일자읍면동(행정동)
그늘막 유형1.0000.1560.8540.0000.8800.000
펼침지름(m)0.1561.0000.3870.3410.4930.492
전체높이(m)0.8540.3871.0000.4260.9170.214
도로명주소0.0000.3410.4261.0000.3030.179
설치일자0.8800.4930.9170.3031.0000.258
읍면동(행정동)0.0000.4920.2140.1790.2581.000
2024-04-21T23:54:26.671064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도읍면동(행정동)도로명주소설치일자그늘막 유형전체높이(m)펼침지름(m)
연번1.0000.066-0.1290.2940.1110.8101.0000.0000.417
위도0.0661.000-0.3850.4800.1930.1640.0000.2140.138
경도-0.129-0.3851.0000.7250.0000.1920.2120.2560.473
읍면동(행정동)0.2940.4800.7251.0000.1790.2580.0000.2140.492
도로명주소0.1110.1930.0000.1791.0000.3030.0000.4260.341
설치일자0.8100.1640.1920.2580.3031.0000.8800.9170.493
그늘막 유형1.0000.0000.2120.0000.0000.8801.0000.8540.156
전체높이(m)0.0000.2140.2560.2140.4260.9170.8541.0000.387
펼침지름(m)0.4170.1380.4730.4920.3410.4930.1560.3871.000

Missing values

2024-04-21T23:54:13.001222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T23:54:13.628279image/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.
2024-04-21T23:54:13.997645image/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

연번시도시군구읍면동(행정동)관리번호설치장소명지번주소도로명주소위도경도설치일자그늘막 유형전체높이(m)펼침지름(m)보험가입유무데이터기준일자
01경상북도김천시대곡동김천시-001김천고 앞경상북도 김천시 부곡동 155736.123751128.094852018-06-01고정형3.55Y2024-02-26
12경상북도김천시대곡동김천시-002시민탑 삼거리경상북도 김천시 부곡동 450-236.124273128.1042822018-06-01고정형3.45Y2024-02-26
23경상북도김천시율곡동김천시-003KCC스위첸 사거리경상북도 김천시 율곡동 83136.120984128.1809242018-06-01고정형3.55Y2024-02-26
34경상북도김천시율곡동김천시-004KCC스위첸 사거리경상북도 김천시 율곡동 83136.121289128.1808892018-06-01고정형3.55Y2024-02-26
45경상북도김천시율곡동김천시-005율곡고 앞경상북도 김천시 율곡동 84636.12403128.190852018-06-01고정형3.55Y2024-02-26
56경상북도김천시율곡동김천시-006혁신우리은행 앞경상북도 김천시 율곡동 780경상북도 김천시 혁신3로 5 (율곡동)36.118499128.1830292018-06-01고정형3.55Y2024-02-26
67경상북도김천시율곡동김천시-007한국전력기술 삼거리경상북도 김천시 율곡동 92836.12677128.1808582018-06-01고정형3.55Y2024-02-26
78경상북도김천시율곡동김천시-008한국도로공사 앞경상북도 김천시 율곡동 94036.128057128.1863772018-06-01고정형3.55Y2024-02-26
89경상북도김천시대곡동김천시-009대곡동주민센터 앞경상북도 김천시 부곡동 153436.124099128.089142018-07-01고정형3.55Y2024-02-26
910경상북도김천시평화남산동김천시-010직지교 사거리 앞경상북도 김천시 평화동 2-636.128178128.1178842018-07-01고정형3.55Y2024-02-26
연번시도시군구읍면동(행정동)관리번호설치장소명지번주소도로명주소위도경도설치일자그늘막 유형전체높이(m)펼침지름(m)보험가입유무데이터기준일자
82<NA>경상북도김천시지좌동김천시-084남혁신코아루 입구경상북도 김천시 덕곡동 760경상북도 김천시 영남대로 2106 (덕곡동)36.114028128.1577132022-09-05고정형3.44Y2024-02-26
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