Overview

Dataset statistics

Number of variables16
Number of observations150
Missing cells598
Missing cells (%)24.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.8 KiB
Average record size in memory134.9 B

Variable types

Text3
Unsupported2
Categorical4
DateTime3
Numeric4

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실) 각 기관에서 등록한 표준데이터를 취합하여 제공하기 때문에 갱신주기는 개별 파일마다 다릅니다.(기관에서 등록한 데이터를 취합한 것으로 개별 파일별 갱신시점이 다름)
URLhttps://www.data.go.kr/data/15021104/fileData.do

Alerts

위험시설지정사유 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
시설유형 is highly overall correlated with 위험시설지정고시번호High correlation
위험시설지정고시번호 is highly overall correlated with 시설유형High correlation
위험시설지정고시번호 is highly imbalanced (83.9%)Imbalance
소재지도로명주소 has 150 (100.0%) missing valuesMissing
위험시설지정사유 has 148 (98.7%) missing valuesMissing
위험시설해제일자 has 146 (97.3%) missing valuesMissing
연장 has 2 (1.3%) missing valuesMissing
폭 has 2 (1.3%) missing valuesMissing
시설부속물 has 150 (100.0%) missing valuesMissing
시설명 has unique valuesUnique
소재지도로명주소 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시설부속물 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 20:11:33.761841
Analysis finished2023-12-12 20:11:36.438591
Duration2.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct150
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T05:11:36.607059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.6133333
Min length3

Characters and Unicode

Total characters1292
Distinct characters85
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

Unique150 ?
Unique (%)100.0%

Sample

1st row온막24-11 농로
2nd row온막23-40 농로
3rd row용산17-2 농로
4th row용산18-7 농로
5th row용산18-13 농로
ValueCountFrequency (%)
농로 94
34.8%
안길 26
 
9.6%
오산6-4 2
 
0.7%
동곡16-2 2
 
0.7%
사전12-13 1
 
0.4%
동곡16-4 1
 
0.4%
동곡11-22 1
 
0.4%
동곡11-23 1
 
0.4%
동곡11-24 1
 
0.4%
박곡21-34 1
 
0.4%
Other values (140) 140
51.9%
2023-12-13T05:11:37.032804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 136
 
10.5%
1 121
 
9.4%
120
 
9.3%
로 109
 
8.4%
농 109
 
8.4%
2 62
 
4.8%
6 54
 
4.2%
4 34
 
2.6%
3 32
 
2.5%
안 28
 
2.2%
Other values (75) 487
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 626
48.5%
Decimal Number 408
31.6%
Dash Punctuation 136
 
10.5%
Space Separator 120
 
9.3%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 109
17.4%
농 109
17.4%
안 28
 
4.5%
전 28
 
4.5%
길 27
 
4.3%
지 25
 
4.0%
천 21
 
3.4%
곡 18
 
2.9%
소 15
 
2.4%
산 15
 
2.4%
Other values (61) 231
36.9%
Decimal Number
ValueCountFrequency (%)
1 121
29.7%
2 62
15.2%
6 54
13.2%
4 34
 
8.3%
3 32
 
7.8%
7 24
 
5.9%
9 24
 
5.9%
8 20
 
4.9%
5 19
 
4.7%
0 18
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 136
100.0%
Space Separator
ValueCountFrequency (%)
120
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 666
51.5%
Hangul 626
48.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 109
17.4%
농 109
17.4%
안 28
 
4.5%
전 28
 
4.5%
길 27
 
4.3%
지 25
 
4.0%
천 21
 
3.4%
곡 18
 
2.9%
소 15
 
2.4%
산 15
 
2.4%
Other values (61) 231
36.9%
Common
ValueCountFrequency (%)
- 136
20.4%
1 121
18.2%
120
18.0%
2 62
9.3%
6 54
 
8.1%
4 34
 
5.1%
3 32
 
4.8%
7 24
 
3.6%
9 24
 
3.6%
8 20
 
3.0%
Other values (4) 39
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 666
51.5%
Hangul 626
48.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 136
20.4%
1 121
18.2%
120
18.0%
2 62
9.3%
6 54
 
8.1%
4 34
 
5.1%
3 32
 
4.8%
7 24
 
3.6%
9 24
 
3.6%
8 20
 
3.0%
Other values (4) 39
 
5.9%
Hangul
ValueCountFrequency (%)
로 109
17.4%
농 109
17.4%
안 28
 
4.5%
전 28
 
4.5%
길 27
 
4.3%
지 25
 
4.0%
천 21
 
3.4%
곡 18
 
2.9%
소 15
 
2.4%
산 15
 
2.4%
Other values (61) 231
36.9%

소재지도로명주소
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing150
Missing (%)100.0%
Memory size1.4 KiB

소재지지번주소
Text

Distinct144
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-13T05:11:37.585291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length21.64
Min length19

Characters and Unicode

Total characters3246
Distinct characters79
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

Unique140 ?
Unique (%)93.3%

Sample

1st row경상북도 청도군 매전면 온막리 439
2nd row경상북도 청도군 매전면 온막리 1185-4
3rd row경상북도 청도군 매전면 용산리 910-1
4th row경상북도 청도군 매전면 용산리 670-2
5th row경상북도 청도군 매전면 용산리 344
ValueCountFrequency (%)
경상북도 150
20.0%
청도군 150
20.0%
금천면 48
 
6.4%
매전면 34
 
4.5%
각북면 33
 
4.4%
운문면 14
 
1.9%
지슬리 12
 
1.6%
김전리 12
 
1.6%
사전리 11
 
1.5%
화양읍 10
 
1.3%
Other values (190) 275
36.7%
2023-12-13T05:11:38.239998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
599
18.5%
도 302
 
9.3%
북 185
 
5.7%
1 155
 
4.8%
상 152
 
4.7%
청 152
 
4.7%
리 151
 
4.7%
경 150
 
4.6%
군 150
 
4.6%
면 138
 
4.3%
Other values (69) 1112
34.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1965
60.5%
Space Separator 599
 
18.5%
Decimal Number 589
 
18.1%
Dash Punctuation 93
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 302
15.4%
북 185
9.4%
상 152
 
7.7%
청 152
 
7.7%
리 151
 
7.7%
경 150
 
7.6%
군 150
 
7.6%
면 138
 
7.0%
천 68
 
3.5%
전 62
 
3.2%
Other values (57) 455
23.2%
Decimal Number
ValueCountFrequency (%)
1 155
26.3%
2 78
13.2%
3 61
 
10.4%
9 52
 
8.8%
4 49
 
8.3%
6 42
 
7.1%
5 42
 
7.1%
0 39
 
6.6%
7 37
 
6.3%
8 34
 
5.8%
Space Separator
ValueCountFrequency (%)
599
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1965
60.5%
Common 1281
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 302
15.4%
북 185
9.4%
상 152
 
7.7%
청 152
 
7.7%
리 151
 
7.7%
경 150
 
7.6%
군 150
 
7.6%
면 138
 
7.0%
천 68
 
3.5%
전 62
 
3.2%
Other values (57) 455
23.2%
Common
ValueCountFrequency (%)
599
46.8%
1 155
 
12.1%
- 93
 
7.3%
2 78
 
6.1%
3 61
 
4.8%
9 52
 
4.1%
4 49
 
3.8%
6 42
 
3.3%
5 42
 
3.3%
0 39
 
3.0%
Other values (2) 71
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1965
60.5%
ASCII 1281
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
599
46.8%
1 155
 
12.1%
- 93
 
7.3%
2 78
 
6.1%
3 61
 
4.8%
9 52
 
4.1%
4 49
 
3.8%
6 42
 
3.3%
5 42
 
3.3%
0 39
 
3.0%
Other values (2) 71
 
5.5%
Hangul
ValueCountFrequency (%)
도 302
15.4%
북 185
9.4%
상 152
 
7.7%
청 152
 
7.7%
리 151
 
7.7%
경 150
 
7.6%
군 150
 
7.6%
면 138
 
7.0%
천 68
 
3.5%
전 62
 
3.2%
Other values (57) 455
23.2%

시설유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
농로
109 
마을진입로
27 
소교량
13 
세천
 
1

Length

Max length5
Median length2
Mean length2.6266667
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
농로 109
72.7%
마을진입로 27
 
18.0%
소교량 13
 
8.7%
세천 1
 
0.7%

Length

2023-12-13T05:11:38.423068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:11:38.597464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농로 109
72.7%
마을진입로 27
 
18.0%
소교량 13
 
8.7%
세천 1
 
0.7%

위험시설지정고시번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
제2017-22호
142 
제2016-91호
 
3
제2022-33호
 
2
제2016-76호
 
1
제2019-29호
 
1

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique3 ?
Unique (%)2.0%

Sample

1st row제2017-22호
2nd row제2017-22호
3rd row제2017-22호
4th row제2017-22호
5th row제2017-22호

Common Values

ValueCountFrequency (%)
제2017-22호 142
94.7%
제2016-91호 3
 
2.0%
제2022-33호 2
 
1.3%
제2016-76호 1
 
0.7%
제2019-29호 1
 
0.7%
제2020-49호 1
 
0.7%

Length

2023-12-13T05:11:38.734245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:11:38.854617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제2017-22호 142
94.7%
제2016-91호 3
 
2.0%
제2022-33호 2
 
1.3%
제2016-76호 1
 
0.7%
제2019-29호 1
 
0.7%
제2020-49호 1
 
0.7%

위험시설지정일자
Date

Distinct6
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2016-11-03 00:00:00
Maximum2022-04-18 00:00:00
2023-12-13T05:11:38.950385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:39.082488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)

위험시설지정사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing148
Missing (%)98.7%
Memory size1.3 KiB
2023-12-13T05:11:39.257677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters28
Distinct characters13
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정밀안전진단결과 D등급판정
2nd row정밀안전진단결과 D등급판정
ValueCountFrequency (%)
정밀안전진단결과 2
50.0%
d등급판정 2
50.0%
2023-12-13T05:11:39.579061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 4
14.3%
밀 2
 
7.1%
안 2
 
7.1%
전 2
 
7.1%
진 2
 
7.1%
단 2
 
7.1%
결 2
 
7.1%
과 2
 
7.1%
2
 
7.1%
D 2
 
7.1%
Other values (3) 6
21.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24
85.7%
Space Separator 2
 
7.1%
Uppercase Letter 2
 
7.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 4
16.7%
밀 2
8.3%
안 2
8.3%
전 2
8.3%
진 2
8.3%
단 2
8.3%
결 2
8.3%
과 2
8.3%
등 2
8.3%
급 2
8.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24
85.7%
Common 2
 
7.1%
Latin 2
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 4
16.7%
밀 2
8.3%
안 2
8.3%
전 2
8.3%
진 2
8.3%
단 2
8.3%
결 2
8.3%
과 2
8.3%
등 2
8.3%
급 2
8.3%
Common
ValueCountFrequency (%)
2
100.0%
Latin
ValueCountFrequency (%)
D 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24
85.7%
ASCII 4
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 4
16.7%
밀 2
8.3%
안 2
8.3%
전 2
8.3%
진 2
8.3%
단 2
8.3%
결 2
8.3%
과 2
8.3%
등 2
8.3%
급 2
8.3%
ASCII
ValueCountFrequency (%)
2
50.0%
D 2
50.0%

위험시설해제일자
Date

MISSING 

Distinct2
Distinct (%)50.0%
Missing146
Missing (%)97.3%
Memory size1.3 KiB
Minimum2018-01-19 00:00:00
Maximum2018-11-08 00:00:00
2023-12-13T05:11:39.695471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:39.795382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

위도
Real number (ℝ)

Distinct143
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.702242
Minimum35.610554
Maximum35.823513
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T05:11:39.933076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.610554
5-th percentile35.630977
Q135.662198
median35.712393
Q335.730661
95-th percentile35.793337
Maximum35.823513
Range0.212959
Interquartile range (IQR)0.068462862

Descriptive statistics

Standard deviation0.047451118
Coefficient of variation (CV)0.0013290795
Kurtosis-0.11477615
Mean35.702242
Median Absolute Deviation (MAD)0.0239855
Skewness0.21060635
Sum5355.3363
Variance0.0022516086
MonotonicityNot monotonic
2023-12-13T05:11:40.083271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.7143237 4
 
2.7%
35.71345465 2
 
1.3%
35.698071 2
 
1.3%
35.71239334 2
 
1.3%
35.733231 2
 
1.3%
35.644771 1
 
0.7%
35.731631 1
 
0.7%
35.72041723 1
 
0.7%
35.71379263 1
 
0.7%
35.71475151 1
 
0.7%
Other values (133) 133
88.7%
ValueCountFrequency (%)
35.610554 1
0.7%
35.61114728 1
0.7%
35.617646 1
0.7%
35.620229 1
0.7%
35.62170167 1
0.7%
35.621733 1
0.7%
35.622392 1
0.7%
35.630797 1
0.7%
35.63119724 1
0.7%
35.631328986 1
0.7%
ValueCountFrequency (%)
35.823513 1
0.7%
35.823409 1
0.7%
35.813027 1
0.7%
35.810315 1
0.7%
35.808014 1
0.7%
35.806508 1
0.7%
35.803759 1
0.7%
35.797185 1
0.7%
35.78863323 1
0.7%
35.782401 1
0.7%

경도
Real number (ℝ)

Distinct144
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.78263
Minimum128.54783
Maximum128.99306
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T05:11:40.235802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.54783
5-th percentile128.57425
Q1128.6073
median128.83346
Q3128.88279
95-th percentile128.96832
Maximum128.99306
Range0.445231
Interquartile range (IQR)0.27548618

Descriptive statistics

Standard deviation0.13589469
Coefficient of variation (CV)0.0010552254
Kurtosis-1.2189013
Mean128.78263
Median Absolute Deviation (MAD)0.06993295
Skewness-0.46432963
Sum19317.394
Variance0.018467368
MonotonicityNot monotonic
2023-12-13T05:11:40.371402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6001572 4
 
2.7%
128.8830029 2
 
1.3%
128.5815923 2
 
1.3%
128.587742 2
 
1.3%
128.8317062 1
 
0.7%
128.893721 1
 
0.7%
128.872778 1
 
0.7%
128.875751 1
 
0.7%
128.885802 1
 
0.7%
128.882043 1
 
0.7%
Other values (134) 134
89.3%
ValueCountFrequency (%)
128.547831 1
0.7%
128.555951 1
0.7%
128.557846 1
0.7%
128.5579902 1
0.7%
128.5635049 1
0.7%
128.5698782 1
0.7%
128.5710946 1
0.7%
128.572858 1
0.7%
128.575943 1
0.7%
128.576528 1
0.7%
ValueCountFrequency (%)
128.993062 1
0.7%
128.9927128 1
0.7%
128.988051 1
0.7%
128.9869482 1
0.7%
128.981726 1
0.7%
128.977403 1
0.7%
128.9756909 1
0.7%
128.968541 1
0.7%
128.968045 1
0.7%
128.965824 1
0.7%

연장
Real number (ℝ)

MISSING 

Distinct132
Distinct (%)89.2%
Missing2
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean384.72297
Minimum6
Maximum3357
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T05:11:40.533665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile16.35
Q1102.75
median255.5
Q3491.25
95-th percentile1073.45
Maximum3357
Range3351
Interquartile range (IQR)388.5

Descriptive statistics

Standard deviation448.19136
Coefficient of variation (CV)1.1649717
Kurtosis15.489624
Mean384.72297
Median Absolute Deviation (MAD)180.5
Skewness3.2397119
Sum56939
Variance200875.49
MonotonicityNot monotonic
2023-12-13T05:11:40.691228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
146 2
 
1.3%
519 2
 
1.3%
324 2
 
1.3%
303 2
 
1.3%
789 2
 
1.3%
443 2
 
1.3%
66 2
 
1.3%
170 2
 
1.3%
141 2
 
1.3%
7 2
 
1.3%
Other values (122) 128
85.3%
ValueCountFrequency (%)
6 2
1.3%
7 2
1.3%
10 2
1.3%
13 1
0.7%
16 1
0.7%
17 1
0.7%
19 1
0.7%
20 1
0.7%
22 1
0.7%
27 1
0.7%
ValueCountFrequency (%)
3357 1
0.7%
2221 1
0.7%
2212 1
0.7%
1517 1
0.7%
1355 1
0.7%
1208 1
0.7%
1164 1
0.7%
1106 1
0.7%
1013 1
0.7%
944 1
0.7%

폭
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)6.1%
Missing2
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean3.6182432
Minimum2.5
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-13T05:11:40.840718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.5
5-th percentile3
Q13
median3
Q34
95-th percentile6
Maximum11
Range8.5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2499816
Coefficient of variation (CV)0.34546644
Kurtosis11.35685
Mean3.6182432
Median Absolute Deviation (MAD)0
Skewness3.0185535
Sum535.5
Variance1.562454
MonotonicityNot monotonic
2023-12-13T05:11:40.945807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
3.0 100
66.7%
4.0 25
 
16.7%
5.0 13
 
8.7%
6.0 3
 
2.0%
8.0 2
 
1.3%
7.0 2
 
1.3%
9.0 1
 
0.7%
11.0 1
 
0.7%
2.5 1
 
0.7%
(Missing) 2
 
1.3%
ValueCountFrequency (%)
2.5 1
 
0.7%
3.0 100
66.7%
4.0 25
 
16.7%
5.0 13
 
8.7%
6.0 3
 
2.0%
7.0 2
 
1.3%
8.0 2
 
1.3%
9.0 1
 
0.7%
11.0 1
 
0.7%
ValueCountFrequency (%)
11.0 1
 
0.7%
9.0 1
 
0.7%
8.0 2
 
1.3%
7.0 2
 
1.3%
6.0 3
 
2.0%
5.0 13
 
8.7%
4.0 25
 
16.7%
3.0 100
66.7%
2.5 1
 
0.7%

시설부속물
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing150
Missing (%)100.0%
Memory size1.4 KiB

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
054-370-2092
150 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row054-370-2092
2nd row054-370-2092
3rd row054-370-2092
4th row054-370-2092
5th row054-370-2092

Common Values

ValueCountFrequency (%)
054-370-2092 150
100.0%

Length

2023-12-13T05:11:41.098679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:11:41.214185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
054-370-2092 150
100.0%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
경상북도 청도군청
150 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상북도 청도군청 150
100.0%

Length

2023-12-13T05:11:41.317613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:11:41.430246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 150
50.0%
청도군청 150
50.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2023-08-29 00:00:00
Maximum2023-08-29 00:00:00
2023-12-13T05:11:41.510993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:41.607354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T05:11:35.609164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:34.267819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:34.930087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:35.257254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:35.697393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:34.678103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:35.012899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:35.335551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:35.783834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:34.756244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:35.100253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:35.422317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:35.868788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:34.848731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:35.184850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:11:35.521962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:11:41.702831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형위험시설지정고시번호위험시설지정일자위험시설해제일자위도경도연장폭
시설유형1.0000.8380.838NaN0.0000.4470.3230.594
위험시설지정고시번호0.8381.0001.0000.0000.0000.5160.0000.266
위험시설지정일자0.8381.0001.0000.0000.0000.5160.0000.266
위험시설해제일자NaN0.0000.0001.0000.0000.000NaNNaN
위도0.0000.0000.0000.0001.0000.7200.0000.000
경도0.4470.5160.5160.0000.7201.0000.1170.170
연장0.3230.0000.000NaN0.0000.1171.0000.000
폭0.5940.2660.266NaN0.0000.1700.0001.000
2023-12-13T05:11:41.853581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형위험시설지정고시번호
시설유형1.0000.694
위험시설지정고시번호0.6941.000
2023-12-13T05:11:41.949326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도연장폭시설유형위험시설지정고시번호
위도1.0000.428-0.0350.0420.0000.000
경도0.4281.000-0.0560.1180.2970.283
연장-0.035-0.0561.000-0.0810.2240.000
폭0.0420.118-0.0811.0000.2940.163
시설유형0.0000.2970.2240.2941.0000.694
위험시설지정고시번호0.0000.2830.0000.1630.6941.000

Missing values

2023-12-13T05:11:35.986309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:11:36.214517image/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.
2023-12-13T05:11:36.363628image/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

시설명소재지도로명주소소재지지번주소시설유형위험시설지정고시번호위험시설지정일자위험시설지정사유위험시설해제일자위도경도연장폭시설부속물관리기관전화번호관리기관명데이터기준일자
0온막24-11 농로<NA>경상북도 청도군 매전면 온막리 439농로제2017-22호2017-04-06<NA><NA>35.644771128.8317062353.0<NA>054-370-2092경상북도 청도군청2023-08-29
1온막23-40 농로<NA>경상북도 청도군 매전면 온막리 1185-4농로제2017-22호2017-04-06<NA><NA>35.635599128.82319713554.0<NA>054-370-2092경상북도 청도군청2023-08-29
2용산17-2 농로<NA>경상북도 청도군 매전면 용산리 910-1농로제2017-22호2017-04-06<NA><NA>35.652708128.8241561238.0<NA>054-370-2092경상북도 청도군청2023-08-29
3용산18-7 농로<NA>경상북도 청도군 매전면 용산리 670-2농로제2017-22호2017-04-06<NA><NA>35.651455128.8335741473.0<NA>054-370-2092경상북도 청도군청2023-08-29
4용산18-13 농로<NA>경상북도 청도군 매전면 용산리 344농로제2017-22호2017-04-06<NA><NA>35.667313128.8255993.0<NA>054-370-2092경상북도 청도군청2023-08-29
5장연24-12 농로<NA>경상북도 청도군 매전면 장연리 942농로제2017-22호2017-04-06<NA><NA>35.630797128.8478542644.0<NA>054-370-2092경상북도 청도군청2023-08-29
6하평13-11 농로<NA>경상북도 청도군 매전면 하평리 428-2농로제2017-22호2017-04-06<NA><NA>35.692715128.826192723.0<NA>054-370-2092경상북도 청도군청2023-08-29
7하평13-23 농로<NA>경상북도 청도군 매전면 하평리 930-1농로제2017-22호2017-04-06<NA><NA>35.683214128.837971923.0<NA>054-370-2092경상북도 청도군청2023-08-29
8월봉15-3 안길<NA>경상북도 청도군 풍각면 월봉리 965마을진입로제2017-22호2017-04-06<NA><NA>35.611147128.591449443.0<NA>054-370-2092경상북도 청도군청2023-08-29
9명대16-4 안길<NA>경상북도 청도군 각북면 명대리 885-11마을진입로제2017-22호2017-04-06<NA><NA>35.64942128.6262559423.0<NA>054-370-2092경상북도 청도군청2023-08-29
시설명소재지도로명주소소재지지번주소시설유형위험시설지정고시번호위험시설지정일자위험시설지정사유위험시설해제일자위도경도연장폭시설부속물관리기관전화번호관리기관명데이터기준일자
140사전7-4 안길<NA>경상북도 청도군 금천면 사전리 863-1마을진입로제2017-22호2017-04-06<NA><NA>35.727226128.8821376775.0<NA>054-370-2092경상북도 청도군청2023-08-29
141사전11-5 안길<NA>경상북도 청도군 금천면 사전리 1429-1마을진입로제2017-22호2017-04-06<NA><NA>35.719921128.8745412573.0<NA>054-370-2092경상북도 청도군청2023-08-29
142사전12-8 안길<NA>경상북도 청도군 금천면 사전리 280-3마을진입로제2017-22호2017-04-06<NA><NA>35.714022128.8870754823.0<NA>054-370-2092경상북도 청도군청2023-08-29
143신지19-4 안길<NA>경상북도 청도군 금천면 신지리 499-2마을진입로제2017-22호2017-04-06<NA><NA>35.674253128.8935135775.0<NA>054-370-2092경상북도 청도군청2023-08-29
144온막24-3 안길<NA>경상북도 청도군 매전면 온막리 699-3마을진입로제2017-22호2017-04-06<NA><NA>35.643334128.83755433574.0<NA>054-370-2092경상북도 청도군청2023-08-29
145하평13-2안길<NA>경상북도 청도군 매전면 하평리 629-2마을진입로제2017-22호2017-04-06<NA><NA>35.690454128.8325667326.0<NA>054-370-2092경상북도 청도군청2023-08-29
146무등이박정1교<NA>경상북도 청도군 청도읍 무등리 90소교량제2019-29호2019-04-08<NA><NA>35.672209128.75354273.0<NA>054-370-2092경상북도 청도군청2023-08-29
147금천(마당)세천<NA>경상북도 청도군 매전면 금천리 390세천제2020-49호2020-09-04<NA><NA>35.733245128.8111911702.5<NA>054-370-2092경상북도 청도군청2023-08-29
148동화교<NA>경상북도 청도군 매전면 호화리 117소교량제2022-33호2022-04-18정밀안전진단결과 D등급판정<NA>35.650713128.848908<NA><NA><NA>054-370-2092경상북도 청도군청2023-08-29
149장연4교<NA>경상북도 청도군 매전면 장연리 394소교량제2022-33호2022-04-18정밀안전진단결과 D등급판정<NA>35.631329128.848156<NA><NA><NA>054-370-2092경상북도 청도군청2023-08-29