Overview

Dataset statistics

Number of variables11
Number of observations316
Missing cells216
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.6 KiB
Average record size in memory89.4 B

Variable types

Numeric1
Categorical6
Text3
DateTime1

Dataset

Description충청북도 청주시의 그늘막 설치 현황 데이터로 그늘막의 설치 시도, 시군구, 읍면동 , 장소, 유형, 높이, 설치일자 등을 제공합니다.
URLhttps://www.data.go.kr/data/15114264/fileData.do

Alerts

시도 has constant value ""Constant
읍면동 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
시군구 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 시군구 and 1 other fieldsHigh correlation
유형 is highly overall correlated with 전체높이 and 1 other fieldsHigh correlation
전체높이 is highly overall correlated with 유형 and 1 other fieldsHigh correlation
펼침지름 is highly overall correlated with 유형 and 1 other fieldsHigh correlation
유형 is highly imbalanced (53.7%)Imbalance
설치 도로명주소 has 204 (64.6%) missing valuesMissing
설치 지번주소 has 12 (3.8%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:27:17.866630
Analysis finished2023-12-12 00:27:18.870756
Duration1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct316
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean158.5
Minimum1
Maximum316
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2023-12-12T09:27:18.939693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16.75
Q179.75
median158.5
Q3237.25
95-th percentile300.25
Maximum316
Range315
Interquartile range (IQR)157.5

Descriptive statistics

Standard deviation91.365566
Coefficient of variation (CV)0.5764389
Kurtosis-1.2
Mean158.5
Median Absolute Deviation (MAD)79
Skewness0
Sum50086
Variance8347.6667
MonotonicityStrictly increasing
2023-12-12T09:27:19.093845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
210 1
 
0.3%
217 1
 
0.3%
216 1
 
0.3%
215 1
 
0.3%
214 1
 
0.3%
213 1
 
0.3%
212 1
 
0.3%
211 1
 
0.3%
209 1
 
0.3%
Other values (306) 306
96.8%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
316 1
0.3%
315 1
0.3%
314 1
0.3%
313 1
0.3%
312 1
0.3%
311 1
0.3%
310 1
0.3%
309 1
0.3%
308 1
0.3%
307 1
0.3%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
충청북도
316 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
충청북도 316
100.0%

Length

2023-12-12T09:27:19.217298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:27:19.295421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청북도 316
100.0%

시군구
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
청주시흥덕구
92 
청주시상당구
75 
청주시서원구
75 
청주시청원구
74 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청주시흥덕구 92
29.1%
청주시상당구 75
23.7%
청주시서원구 75
23.7%
청주시청원구 74
23.4%

Length

2023-12-12T09:27:19.389222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:27:19.494994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청주시흥덕구 92
29.1%
청주시상당구 75
23.7%
청주시서원구 75
23.7%
청주시청원구 74
23.4%

읍면동
Categorical

HIGH CORRELATION 

Distinct37
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
오창읍
28 
성화개신죽림동
27 
율량사천동
26 
용암1동
23 
오송읍
22 
Other values (32)
190 

Length

Max length7
Median length6
Mean length4.028481
Min length3

Unique

Unique4 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
오창읍 28
 
8.9%
성화개신죽림동 27
 
8.5%
율량사천동 26
 
8.2%
용암1동 23
 
7.3%
오송읍 22
 
7.0%
복대1동 16
 
5.1%
가경동 14
 
4.4%
용암2동 13
 
4.1%
산남동 13
 
4.1%
금천동 12
 
3.8%
Other values (27) 122
38.6%

Length

2023-12-12T09:27:19.625432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
오창읍 28
 
8.9%
성화개신죽림동 27
 
8.5%
율량사천동 26
 
8.2%
용암1동 23
 
7.3%
오송읍 22
 
7.0%
복대1동 16
 
5.1%
가경동 14
 
4.4%
용암2동 13
 
4.1%
산남동 13
 
4.1%
분평동 12
 
3.8%
Other values (27) 122
38.6%

설치장소
Text

Distinct306
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-12T09:27:19.939094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length12.268987
Min length4

Characters and Unicode

Total characters3877
Distinct characters376
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique298 ?
Unique (%)94.3%

Sample

1st row포토이즘 앞
2nd row신한은행 앞
3rd row한성저축은행 맞은편
4th row방아다리 추어탕집 앞
5th row상당공원사거리 교통섬
ValueCountFrequency (%)
앞 233
26.9%
교통섬 32
 
3.7%
맞은편 29
 
3.3%
횡단보도 21
 
2.4%
건너편 18
 
2.1%
사거리 18
 
2.1%
101동 9
 
1.0%
다이소 7
 
0.8%
파리바게트 6
 
0.7%
정문 5
 
0.6%
Other values (387) 488
56.4%
2023-12-12T09:27:20.385895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
555
 
14.3%
앞 238
 
6.1%
리 130
 
3.4%
거 96
 
2.5%
사 83
 
2.1%
교 77
 
2.0%
동 61
 
1.6%
원 59
 
1.5%
1 57
 
1.5%
편 54
 
1.4%
Other values (366) 2467
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3053
78.7%
Space Separator 555
 
14.3%
Decimal Number 135
 
3.5%
Uppercase Letter 84
 
2.2%
Lowercase Letter 30
 
0.8%
Open Punctuation 8
 
0.2%
Close Punctuation 8
 
0.2%
Dash Punctuation 2
 
0.1%
Other Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 238
 
7.8%
리 130
 
4.3%
거 96
 
3.1%
사 83
 
2.7%
교 77
 
2.5%
동 61
 
2.0%
원 59
 
1.9%
편 54
 
1.8%
지 53
 
1.7%
트 45
 
1.5%
Other values (325) 2157
70.7%
Uppercase Letter
ValueCountFrequency (%)
A 27
32.1%
C 10
 
11.9%
K 8
 
9.5%
T 6
 
7.1%
U 6
 
7.1%
L 5
 
6.0%
G 4
 
4.8%
S 4
 
4.8%
N 3
 
3.6%
B 3
 
3.6%
Other values (7) 8
 
9.5%
Decimal Number
ValueCountFrequency (%)
1 57
42.2%
0 29
21.5%
2 16
 
11.9%
5 9
 
6.7%
3 8
 
5.9%
6 6
 
4.4%
4 5
 
3.7%
9 2
 
1.5%
8 2
 
1.5%
7 1
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
k 5
16.7%
s 4
13.3%
o 4
13.3%
r 4
13.3%
d 4
13.3%
l 4
13.3%
w 3
10.0%
t 2
 
6.7%
Space Separator
ValueCountFrequency (%)
555
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3053
78.7%
Common 710
 
18.3%
Latin 114
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 238
 
7.8%
리 130
 
4.3%
거 96
 
3.1%
사 83
 
2.7%
교 77
 
2.5%
동 61
 
2.0%
원 59
 
1.9%
편 54
 
1.8%
지 53
 
1.7%
트 45
 
1.5%
Other values (325) 2157
70.7%
Latin
ValueCountFrequency (%)
A 27
23.7%
C 10
 
8.8%
K 8
 
7.0%
T 6
 
5.3%
U 6
 
5.3%
L 5
 
4.4%
k 5
 
4.4%
s 4
 
3.5%
o 4
 
3.5%
r 4
 
3.5%
Other values (15) 35
30.7%
Common
ValueCountFrequency (%)
555
78.2%
1 57
 
8.0%
0 29
 
4.1%
2 16
 
2.3%
5 9
 
1.3%
( 8
 
1.1%
) 8
 
1.1%
3 8
 
1.1%
6 6
 
0.8%
4 5
 
0.7%
Other values (6) 9
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3053
78.7%
ASCII 824
 
21.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
555
67.4%
1 57
 
6.9%
0 29
 
3.5%
A 27
 
3.3%
2 16
 
1.9%
C 10
 
1.2%
5 9
 
1.1%
( 8
 
1.0%
K 8
 
1.0%
) 8
 
1.0%
Other values (31) 97
 
11.8%
Hangul
ValueCountFrequency (%)
앞 238
 
7.8%
리 130
 
4.3%
거 96
 
3.1%
사 83
 
2.7%
교 77
 
2.5%
동 61
 
2.0%
원 59
 
1.9%
편 54
 
1.8%
지 53
 
1.7%
트 45
 
1.5%
Other values (325) 2157
70.7%

설치 도로명주소
Text

MISSING 

Distinct107
Distinct (%)95.5%
Missing204
Missing (%)64.6%
Memory size2.6 KiB
2023-12-12T09:27:20.765289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length11.758929
Min length1

Characters and Unicode

Total characters1317
Distinct characters97
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)91.1%

Sample

1st row상당구 사직대로 371
2nd row상당구 사직대로 343
3rd row상당구 상당로 145
4th row상당구 남사로 137
5th row상당구 용담로14-3
ValueCountFrequency (%)
흥덕구 37
 
10.9%
서원구 25
 
7.3%
상당구 22
 
6.5%
청원구 16
 
4.7%
1순환로 9
 
2.6%
오송읍 9
 
2.6%
사직대로 6
 
1.8%
직지대로 5
 
1.5%
대농로 5
 
1.5%
산남로 4
 
1.2%
Other values (151) 203
59.5%
2023-12-12T09:27:21.290830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
238
18.1%
로 110
 
8.4%
구 104
 
7.9%
1 85
 
6.5%
원 44
 
3.3%
3 41
 
3.1%
덕 38
 
2.9%
흥 38
 
2.9%
5 34
 
2.6%
2 34
 
2.6%
Other values (87) 551
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 740
56.2%
Decimal Number 327
24.8%
Space Separator 238
 
18.1%
Dash Punctuation 6
 
0.5%
Open Punctuation 3
 
0.2%
Close Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 110
 
14.9%
구 104
 
14.1%
원 44
 
5.9%
덕 38
 
5.1%
흥 38
 
5.1%
서 29
 
3.9%
상 25
 
3.4%
당 24
 
3.2%
대 22
 
3.0%
오 21
 
2.8%
Other values (73) 285
38.5%
Decimal Number
ValueCountFrequency (%)
1 85
26.0%
3 41
12.5%
5 34
 
10.4%
2 34
 
10.4%
4 29
 
8.9%
8 26
 
8.0%
7 22
 
6.7%
6 19
 
5.8%
9 19
 
5.8%
0 18
 
5.5%
Space Separator
ValueCountFrequency (%)
238
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 740
56.2%
Common 577
43.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 110
 
14.9%
구 104
 
14.1%
원 44
 
5.9%
덕 38
 
5.1%
흥 38
 
5.1%
서 29
 
3.9%
상 25
 
3.4%
당 24
 
3.2%
대 22
 
3.0%
오 21
 
2.8%
Other values (73) 285
38.5%
Common
ValueCountFrequency (%)
238
41.2%
1 85
 
14.7%
3 41
 
7.1%
5 34
 
5.9%
2 34
 
5.9%
4 29
 
5.0%
8 26
 
4.5%
7 22
 
3.8%
6 19
 
3.3%
9 19
 
3.3%
Other values (4) 30
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 740
56.2%
ASCII 577
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
238
41.2%
1 85
 
14.7%
3 41
 
7.1%
5 34
 
5.9%
2 34
 
5.9%
4 29
 
5.0%
8 26
 
4.5%
7 22
 
3.8%
6 19
 
3.3%
9 19
 
3.3%
Other values (4) 30
 
5.2%
Hangul
ValueCountFrequency (%)
로 110
 
14.9%
구 104
 
14.1%
원 44
 
5.9%
덕 38
 
5.1%
흥 38
 
5.1%
서 29
 
3.9%
상 25
 
3.4%
당 24
 
3.2%
대 22
 
3.0%
오 21
 
2.8%
Other values (73) 285
38.5%

설치 지번주소
Text

MISSING 

Distinct292
Distinct (%)96.1%
Missing12
Missing (%)3.8%
Memory size2.6 KiB
2023-12-12T09:27:21.648780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length8.4934211
Min length5

Characters and Unicode

Total characters2582
Distinct characters84
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

Unique281 ?
Unique (%)92.4%

Sample

1st row북문로2가 54-2
2nd row북문로3가 119
3rd row북문로3가 113
4th row북문로2가 39-3
5th row북문로1가 106
ValueCountFrequency (%)
용암동 23
 
3.7%
율량동 22
 
3.6%
복대동 22
 
3.6%
서원구 16
 
2.6%
성화동 15
 
2.4%
분평동 14
 
2.3%
가경동 13
 
2.1%
각리 12
 
1.9%
양청리 11
 
1.8%
금천동 11
 
1.8%
Other values (330) 460
74.3%
2023-12-12T09:27:22.089330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
320
 
12.4%
동 241
 
9.3%
2 187
 
7.2%
1 186
 
7.2%
- 140
 
5.4%
3 116
 
4.5%
5 104
 
4.0%
8 104
 
4.0%
6 101
 
3.9%
4 100
 
3.9%
Other values (74) 983
38.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1154
44.7%
Other Letter 968
37.5%
Space Separator 320
 
12.4%
Dash Punctuation 140
 
5.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 241
24.9%
리 59
 
6.1%
용 31
 
3.2%
암 30
 
3.1%
서 24
 
2.5%
량 22
 
2.3%
대 22
 
2.3%
복 22
 
2.3%
율 22
 
2.3%
천 20
 
2.1%
Other values (62) 475
49.1%
Decimal Number
ValueCountFrequency (%)
2 187
16.2%
1 186
16.1%
3 116
10.1%
5 104
9.0%
8 104
9.0%
6 101
8.8%
4 100
8.7%
0 94
8.1%
7 82
7.1%
9 80
6.9%
Space Separator
ValueCountFrequency (%)
320
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 140
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1614
62.5%
Hangul 968
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 241
24.9%
리 59
 
6.1%
용 31
 
3.2%
암 30
 
3.1%
서 24
 
2.5%
량 22
 
2.3%
대 22
 
2.3%
복 22
 
2.3%
율 22
 
2.3%
천 20
 
2.1%
Other values (62) 475
49.1%
Common
ValueCountFrequency (%)
320
19.8%
2 187
11.6%
1 186
11.5%
- 140
8.7%
3 116
 
7.2%
5 104
 
6.4%
8 104
 
6.4%
6 101
 
6.3%
4 100
 
6.2%
0 94
 
5.8%
Other values (2) 162
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1614
62.5%
Hangul 968
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
320
19.8%
2 187
11.6%
1 186
11.5%
- 140
8.7%
3 116
 
7.2%
5 104
 
6.4%
8 104
 
6.4%
6 101
 
6.3%
4 100
 
6.2%
0 94
 
5.8%
Other values (2) 162
10.0%
Hangul
ValueCountFrequency (%)
동 241
24.9%
리 59
 
6.1%
용 31
 
3.2%
암 30
 
3.1%
서 24
 
2.5%
량 22
 
2.3%
대 22
 
2.3%
복 22
 
2.3%
율 22
 
2.3%
천 20
 
2.1%
Other values (62) 475
49.1%

유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
고정형
285 
스마트형
31 

Length

Max length4
Median length3
Mean length3.0981013
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고정형 285
90.2%
스마트형 31
 
9.8%

Length

2023-12-12T09:27:22.251054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:27:22.384365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고정형 285
90.2%
스마트형 31
 
9.8%

전체높이
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
3.65m
201 
3.52m
29 
3m
26 
3.3m
 
19
3.25m
 
13
Other values (7)
28 

Length

Max length5
Median length5
Mean length4.6075949
Min length2

Unique

Unique2 ?
Unique (%)0.6%

Sample

1st row3.65m
2nd row3.65m
3rd row3.65m
4th row3.65m
5th row3.65m

Common Values

ValueCountFrequency (%)
3.65m 201
63.6%
3.52m 29
 
9.2%
3m 26
 
8.2%
3.3m 19
 
6.0%
3.25m 13
 
4.1%
3.5m 11
 
3.5%
3.1m 6
 
1.9%
3.4m 4
 
1.3%
3.55m 3
 
0.9%
2.8m 2
 
0.6%
Other values (2) 2
 
0.6%

Length

2023-12-12T09:27:22.495125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3.65m 201
63.6%
3.52m 29
 
9.2%
3m 26
 
8.2%
3.3m 19
 
6.0%
3.25m 13
 
4.1%
3.5m 11
 
3.5%
3.1m 6
 
1.9%
3.4m 4
 
1.3%
3.55m 3
 
0.9%
2.8m 2
 
0.6%
Other values (2) 2
 
0.6%

펼침지름
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
5m
113 
4m
103 
3.5m
59 
3m
33 
5.4m
 
6

Length

Max length4
Median length2
Mean length2.4240506
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5m
2nd row5m
3rd row5m
4th row4m
5th row4m

Common Values

ValueCountFrequency (%)
5m 113
35.8%
4m 103
32.6%
3.5m 59
18.7%
3m 33
 
10.4%
5.4m 6
 
1.9%
4.6m 2
 
0.6%

Length

2023-12-12T09:27:22.630334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:27:22.762938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5m 113
35.8%
4m 103
32.6%
3.5m 59
18.7%
3m 33
 
10.4%
5.4m 6
 
1.9%
4.6m 2
 
0.6%

설치일시
Date

Distinct59
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2017-08-11 00:00:00
Maximum2023-05-19 00:00:00
2023-12-12T09:27:23.209358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:27:23.412968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-12T09:27:18.477372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:27:23.550850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구읍면동유형전체높이펼침지름설치일시
연번1.0000.9670.9840.0000.4760.3110.859
시군구0.9671.0001.0000.0000.6210.2560.945
읍면동0.9841.0001.0000.0000.6790.3290.904
유형0.0000.0000.0001.0000.9880.6890.990
전체높이0.4760.6210.6790.9881.0000.9250.987
펼침지름0.3110.2560.3290.6890.9251.0000.975
설치일시0.8590.9450.9040.9900.9870.9751.000
2023-12-12T09:27:23.662879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동펼침지름전체높이유형시군구
읍면동1.0000.1400.2740.0000.946
펼침지름0.1401.0000.6220.5030.167
전체높이0.2740.6221.0000.8890.326
유형0.0000.5030.8891.0000.000
시군구0.9460.1670.3260.0001.000
2023-12-12T09:27:23.768137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구읍면동유형전체높이펼침지름
연번1.0000.9000.8380.0000.2190.175
시군구0.9001.0000.9460.0000.3260.167
읍면동0.8380.9461.0000.0000.2740.140
유형0.0000.0000.0001.0000.8890.503
전체높이0.2190.3260.2740.8891.0000.622
펼침지름0.1750.1670.1400.5030.6221.000

Missing values

2023-12-12T09:27:18.593065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:27:18.727009image/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.
2023-12-12T09:27:18.827295image/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

연번시도시군구읍면동설치장소설치 도로명주소설치 지번주소유형전체높이펼침지름설치일시
01충청북도청주시상당구중앙동포토이즘 앞상당구 사직대로 371북문로2가 54-2고정형3.65m5m2017-08-11
12충청북도청주시상당구중앙동신한은행 앞상당구 사직대로 343<NA>고정형3.65m5m2018-09-13
23충청북도청주시상당구중앙동한성저축은행 맞은편상당구 상당로 145북문로3가 119고정형3.65m5m2018-09-13
34충청북도청주시상당구중앙동방아다리 추어탕집 앞<NA>북문로3가 113고정형3.65m4m2019-07-29
45충청북도청주시상당구중앙동상당공원사거리 교통섬<NA>북문로2가 39-3고정형3.65m4m2019-07-29
56충청북도청주시상당구성안동성안길 에잇세컨즈 앞<NA>북문로1가 106고정형3.65m4m2019-07-29
67충청북도청주시상당구성안동구남궁병원사거리 대원칸타빌 앞상당구 남사로 137<NA>고정형3.65m4m2019-04-22
78충청북도청주시상당구성안동충북도청사거리 도민홍보관 앞<NA>문화동 89-3고정형3.65m4m2019-07-29
89충청북도청주시상당구성안동구법원사거리 맞은편 공원쪽상당구 용담로14-3문화동 52고정형3.25m3.5m2020-04-10
910충청북도청주시상당구성안동석교육거리 유정훈치과 앞 교통섬상당구 상당로1번길 2석교동 126-118고정형3.25m3.5m2021-05-07
연번시도시군구읍면동설치장소설치 도로명주소설치 지번주소유형전체높이펼침지름설치일시
306307충청북도청주시청원구율량사천동주성중학교 사거리 대원칸타빌3차A 610동 앞<NA>율량동 2506스마트형3m4m2022-07-13
307308충청북도청주시청원구율량사천동다비치안경점 앞<NA>사천동 22-15고정형3.3m4m2022-08-18
308309충청북도청주시청원구율량사천동맑은샘치과 건물 앞<NA>사천동 436-5고정형3.3m3m2022-08-18
309310충청북도청주시청원구율량사천동철물점 맞은편<NA>사천동 403-11고정형3.3m4m2022-08-18
310311충청북도청주시청원구율량사천동하이마트 앞<NA>율량동 707고정형3.3m4m2022-08-18
311312충청북도청주시청원구율량사천동중앙초등학교 앞 삼거리 횡단보도<NA>율량동 2105고정형3.55m4m2023-03-17
312313충청북도청주시청원구오근장동마로니에공원 야외학습장 앞청원구 율량로 58주중동 1024고정형3.65m5m2018-09-07
313314충청북도청주시청원구오근장동대원칸타빌2차A 3단지 앞청원구 율량로 77주중동 1023고정형3.65m5m2018-09-07
314315충청북도청주시청원구오근장동율량지구대 앞<NA>주중동 1072고정형3.65m4m2021-04-23
315316충청북도청주시청원구오근장동대원칸타빌1차A 앞<NA>주성동 440고정형3.65m5m2021-09-23