Overview

Dataset statistics

Number of variables19
Number of observations31
Missing cells24
Missing cells (%)4.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory163.3 B

Variable types

Numeric3
Categorical7
Text3
Boolean4
DateTime2

Dataset

Description대구광역시_북구_안전비상벨위치
Author대구광역시 북구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15028206&dataSetDetailId=150282061f9ca7121e779_201909161950&provdMethod=FILE

Alerts

설치목적 has constant value ""Constant
설치장소유형 has constant value ""Constant
경비업체연계유무 has constant value ""Constant
관리사무소연계유무 has constant value ""Constant
부가기능 has constant value ""Constant
최종점검일자 has constant value ""Constant
최종점검결과구분 has constant value ""Constant
데이터기준일자 has constant value ""Constant
안전비상벨설치년도 is highly overall correlated with 연계방식 and 1 other fieldsHigh correlation
관리기관전화번호 is highly overall correlated with 안전비상벨관리번호 and 3 other fieldsHigh correlation
연계방식 is highly overall correlated with 안전비상벨설치년도High correlation
경찰연계유무 is highly overall correlated with 안전비상벨설치년도High correlation
관리기관명 is highly overall correlated with 안전비상벨관리번호 and 3 other fieldsHigh correlation
안전비상벨관리번호 is highly overall correlated with 관리기관명 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 관리기관명 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 관리기관명 and 1 other fieldsHigh correlation
연계방식 is highly imbalanced (79.4%)Imbalance
경찰연계유무 is highly imbalanced (79.4%)Imbalance
안전비상벨설치년도 is highly imbalanced (65.5%)Imbalance
소재지도로명주소 has 24 (77.4%) missing valuesMissing
안전비상벨관리번호 has unique valuesUnique
설치위치 has unique valuesUnique

Reproduction

Analysis started2024-04-19 05:16:09.517374
Analysis finished2024-04-19 05:16:11.009399
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

안전비상벨관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-19T14:16:11.068899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q18.5
median16
Q323.5
95-th percentile29.5
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.0921211
Coefficient of variation (CV)0.56825757
Kurtosis-1.2
Mean16
Median Absolute Deviation (MAD)8
Skewness0
Sum496
Variance82.666667
MonotonicityStrictly increasing
2024-04-19T14:16:11.184202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 1
 
3.2%
2 1
 
3.2%
31 1
 
3.2%
30 1
 
3.2%
29 1
 
3.2%
28 1
 
3.2%
27 1
 
3.2%
26 1
 
3.2%
25 1
 
3.2%
24 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
1 1
3.2%
2 1
3.2%
3 1
3.2%
4 1
3.2%
5 1
3.2%
6 1
3.2%
7 1
3.2%
8 1
3.2%
9 1
3.2%
10 1
3.2%
ValueCountFrequency (%)
31 1
3.2%
30 1
3.2%
29 1
3.2%
28 1
3.2%
27 1
3.2%
26 1
3.2%
25 1
3.2%
24 1
3.2%
23 1
3.2%
22 1
3.2%

설치목적
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
2
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 31
100.0%

Length

2024-04-19T14:16:11.307864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:16:11.406864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 31
100.0%

설치장소유형
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
2
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 31
100.0%

Length

2024-04-19T14:16:11.507197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:16:11.592966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 31
100.0%

설치위치
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-19T14:16:11.762910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.9677419
Min length4

Characters and Unicode

Total characters154
Distinct characters59
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row침산근린A
2nd row침산근린B
3rd row신기근린
4th row관음근린
5th row태전근린
ValueCountFrequency (%)
암 2
 
4.1%
달 2
 
4.1%
샘 2
 
4.1%
들 2
 
4.1%
침산근린a 1
 
2.0%
산 1
 
2.0%
별 1
 
2.0%
송 1
 
2.0%
읍 1
 
2.0%
내 1
 
2.0%
Other values (35) 35
71.4%
2024-04-19T14:16:12.099191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
31.2%
린 16
 
10.4%
근 15
 
9.7%
암 5
 
3.2%
천 3
 
1.9%
산 3
 
1.9%
침 2
 
1.3%
대 2
 
1.3%
해 2
 
1.3%
구 2
 
1.3%
Other values (49) 56
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 103
66.9%
Space Separator 48
31.2%
Uppercase Letter 2
 
1.3%
Decimal Number 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
린 16
 
15.5%
근 15
 
14.6%
암 5
 
4.9%
천 3
 
2.9%
산 3
 
2.9%
침 2
 
1.9%
대 2
 
1.9%
해 2
 
1.9%
구 2
 
1.9%
들 2
 
1.9%
Other values (45) 51
49.5%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 103
66.9%
Common 49
31.8%
Latin 2
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
린 16
 
15.5%
근 15
 
14.6%
암 5
 
4.9%
천 3
 
2.9%
산 3
 
2.9%
침 2
 
1.9%
대 2
 
1.9%
해 2
 
1.9%
구 2
 
1.9%
들 2
 
1.9%
Other values (45) 51
49.5%
Common
ValueCountFrequency (%)
48
98.0%
2 1
 
2.0%
Latin
ValueCountFrequency (%)
A 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 103
66.9%
ASCII 51
33.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48
94.1%
A 1
 
2.0%
B 1
 
2.0%
2 1
 
2.0%
Hangul
ValueCountFrequency (%)
린 16
 
15.5%
근 15
 
14.6%
암 5
 
4.9%
천 3
 
2.9%
산 3
 
2.9%
침 2
 
1.9%
대 2
 
1.9%
해 2
 
1.9%
구 2
 
1.9%
들 2
 
1.9%
Other values (45) 51
49.5%

소재지도로명주소
Text

MISSING 

Distinct6
Distinct (%)85.7%
Missing24
Missing (%)77.4%
Memory size380.0 B
2024-04-19T14:16:12.240842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length18.428571
Min length15

Characters and Unicode

Total characters129
Distinct characters32
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

Unique5 ?
Unique (%)71.4%

Sample

1st row대구광역시 북구 구암로 47
2nd row대구광역시 북구 칠곡중앙대로 397-20
3rd row대구광역시 북구 한강로 96
4th row대구광역시 북구 동북로 229
5th row대구광역시 북구 태암남로11길 19-5
ValueCountFrequency (%)
대구광역시 7
25.0%
북구 7
25.0%
칠곡중앙대로 2
 
7.1%
397-20 2
 
7.1%
구암로 1
 
3.6%
47 1
 
3.6%
한강로 1
 
3.6%
96 1
 
3.6%
동북로 1
 
3.6%
229 1
 
3.6%
Other values (4) 4
14.3%
2024-04-19T14:16:12.506793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
16.3%
구 15
 
11.6%
대 9
 
7.0%
북 8
 
6.2%
로 7
 
5.4%
광 7
 
5.4%
역 7
 
5.4%
시 7
 
5.4%
9 5
 
3.9%
1 4
 
3.1%
Other values (22) 39
30.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79
61.2%
Decimal Number 26
 
20.2%
Space Separator 21
 
16.3%
Dash Punctuation 3
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 15
19.0%
대 9
11.4%
북 8
10.1%
로 7
8.9%
광 7
8.9%
역 7
8.9%
시 7
8.9%
앙 2
 
2.5%
칠 2
 
2.5%
중 2
 
2.5%
Other values (10) 13
16.5%
Decimal Number
ValueCountFrequency (%)
9 5
19.2%
1 4
15.4%
2 4
15.4%
7 3
11.5%
0 2
 
7.7%
4 2
 
7.7%
3 2
 
7.7%
5 2
 
7.7%
6 1
 
3.8%
8 1
 
3.8%
Space Separator
ValueCountFrequency (%)
21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79
61.2%
Common 50
38.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 15
19.0%
대 9
11.4%
북 8
10.1%
로 7
8.9%
광 7
8.9%
역 7
8.9%
시 7
8.9%
앙 2
 
2.5%
칠 2
 
2.5%
중 2
 
2.5%
Other values (10) 13
16.5%
Common
ValueCountFrequency (%)
21
42.0%
9 5
 
10.0%
1 4
 
8.0%
2 4
 
8.0%
7 3
 
6.0%
- 3
 
6.0%
0 2
 
4.0%
4 2
 
4.0%
3 2
 
4.0%
5 2
 
4.0%
Other values (2) 2
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79
61.2%
ASCII 50
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
42.0%
9 5
 
10.0%
1 4
 
8.0%
2 4
 
8.0%
7 3
 
6.0%
- 3
 
6.0%
0 2
 
4.0%
4 2
 
4.0%
3 2
 
4.0%
5 2
 
4.0%
Other values (2) 2
 
4.0%
Hangul
ValueCountFrequency (%)
구 15
19.0%
대 9
11.4%
북 8
10.1%
로 7
8.9%
광 7
8.9%
역 7
8.9%
시 7
8.9%
앙 2
 
2.5%
칠 2
 
2.5%
중 2
 
2.5%
Other values (10) 13
16.5%

소재지지번주소
Text

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2024-04-19T14:16:12.689701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length17.387097
Min length16

Characters and Unicode

Total characters539
Distinct characters45
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

Unique29 ?
Unique (%)93.5%

Sample

1st row대구광역시 북구 침산동 1170-7
2nd row대구광역시 북구 침산동 1329
3rd row대구광역시 북구 산격동 1620
4th row대구광역시 북구 관음동 1372
5th row대구광역시 북구 태전동 938
ValueCountFrequency (%)
대구광역시 31
24.8%
북구 31
24.8%
구암동 7
 
5.6%
관음동 5
 
4.0%
산격동 3
 
2.4%
태전동 3
 
2.4%
동천동 3
 
2.4%
침산동 2
 
1.6%
938 2
 
1.6%
201-20 1
 
0.8%
Other values (37) 37
29.6%
2024-04-19T14:16:12.977223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
94
17.4%
구 69
12.8%
동 34
 
6.3%
대 31
 
5.8%
광 31
 
5.8%
역 31
 
5.8%
시 31
 
5.8%
북 31
 
5.8%
1 25
 
4.6%
2 16
 
3.0%
Other values (35) 146
27.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 315
58.4%
Decimal Number 117
 
21.7%
Space Separator 94
 
17.4%
Dash Punctuation 11
 
2.0%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 69
21.9%
동 34
10.8%
대 31
9.8%
광 31
9.8%
역 31
9.8%
시 31
9.8%
북 31
9.8%
암 7
 
2.2%
산 7
 
2.2%
음 5
 
1.6%
Other values (21) 38
12.1%
Decimal Number
ValueCountFrequency (%)
1 25
21.4%
2 16
13.7%
7 13
11.1%
0 12
10.3%
6 11
9.4%
3 11
9.4%
8 10
 
8.5%
9 8
 
6.8%
5 6
 
5.1%
4 5
 
4.3%
Space Separator
ValueCountFrequency (%)
94
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 315
58.4%
Common 224
41.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 69
21.9%
동 34
10.8%
대 31
9.8%
광 31
9.8%
역 31
9.8%
시 31
9.8%
북 31
9.8%
암 7
 
2.2%
산 7
 
2.2%
음 5
 
1.6%
Other values (21) 38
12.1%
Common
ValueCountFrequency (%)
94
42.0%
1 25
 
11.2%
2 16
 
7.1%
7 13
 
5.8%
0 12
 
5.4%
- 11
 
4.9%
6 11
 
4.9%
3 11
 
4.9%
8 10
 
4.5%
9 8
 
3.6%
Other values (4) 13
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 315
58.4%
ASCII 224
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
94
42.0%
1 25
 
11.2%
2 16
 
7.1%
7 13
 
5.8%
0 12
 
5.4%
- 11
 
4.9%
6 11
 
4.9%
3 11
 
4.9%
8 10
 
4.5%
9 8
 
3.6%
Other values (4) 13
 
5.8%
Hangul
ValueCountFrequency (%)
구 69
21.9%
동 34
10.8%
대 31
9.8%
광 31
9.8%
역 31
9.8%
시 31
9.8%
북 31
9.8%
암 7
 
2.2%
산 7
 
2.2%
음 5
 
1.6%
Other values (21) 38
12.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.920798
Minimum35.888789
Maximum35.944643
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-19T14:16:13.095783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.888789
5-th percentile35.894309
Q135.902482
median35.926658
Q335.934202
95-th percentile35.94264
Maximum35.944643
Range0.055854
Interquartile range (IQR)0.031719

Descriptive statistics

Standard deviation0.017678792
Coefficient of variation (CV)0.00049216034
Kurtosis-1.2960195
Mean35.920798
Median Absolute Deviation (MAD)0.012519
Skewness-0.46554842
Sum1113.5447
Variance0.00031253969
MonotonicityNot monotonic
2024-04-19T14:16:13.210040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
35.931636 2
 
6.5%
35.897064 1
 
3.2%
35.892796 1
 
3.2%
35.926424 1
 
3.2%
35.926163 1
 
3.2%
35.927013 1
 
3.2%
35.925646 1
 
3.2%
35.926658 1
 
3.2%
35.932618 1
 
3.2%
35.933957 1
 
3.2%
Other values (20) 20
64.5%
ValueCountFrequency (%)
35.888789 1
3.2%
35.892796 1
3.2%
35.895822 1
3.2%
35.89652 1
3.2%
35.897064 1
3.2%
35.897266 1
3.2%
35.898678 1
3.2%
35.899601 1
3.2%
35.905364 1
3.2%
35.907327 1
3.2%
ValueCountFrequency (%)
35.944643 1
3.2%
35.942992 1
3.2%
35.942288 1
3.2%
35.940601 1
3.2%
35.939177 1
3.2%
35.937182 1
3.2%
35.935866 1
3.2%
35.934446 1
3.2%
35.933957 1
3.2%
35.932618 1
3.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.56248
Minimum128.5136
Maximum128.61691
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2024-04-19T14:16:13.322871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.5136
5-th percentile128.53249
Q1128.54668
median128.55614
Q3128.5719
95-th percentile128.61229
Maximum128.61691
Range0.103306
Interquartile range (IQR)0.0252245

Descriptive statistics

Standard deviation0.024783267
Coefficient of variation (CV)0.00019277216
Kurtosis0.37954761
Mean128.56248
Median Absolute Deviation (MAD)0.010459
Skewness0.6716267
Sum3985.4369
Variance0.00061421034
MonotonicityNot monotonic
2024-04-19T14:16:13.442559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
128.546161 2
 
6.5%
128.584913 1
 
3.2%
128.569762 1
 
3.2%
128.559251 1
 
3.2%
128.555293 1
 
3.2%
128.552728 1
 
3.2%
128.558759 1
 
3.2%
128.55357 1
 
3.2%
128.558707 1
 
3.2%
128.556141 1
 
3.2%
Other values (20) 20
64.5%
ValueCountFrequency (%)
128.513604 1
3.2%
128.520325 1
3.2%
128.544648 1
3.2%
128.544898 1
3.2%
128.545127 1
3.2%
128.545682 1
3.2%
128.546161 2
6.5%
128.547198 1
3.2%
128.549664 1
3.2%
128.549895 1
3.2%
ValueCountFrequency (%)
128.61691 1
3.2%
128.615647 1
3.2%
128.608926 1
3.2%
128.598587 1
3.2%
128.595371 1
3.2%
128.584913 1
3.2%
128.584859 1
3.2%
128.574046 1
3.2%
128.569762 1
3.2%
128.568728 1
3.2%

연계방식
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
1
30 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 30
96.8%
3 1
 
3.2%

Length

2024-04-19T14:16:13.554628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:16:13.641983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 30
96.8%
3 1
 
3.2%

경찰연계유무
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size163.0 B
False
30 
True
 
1
ValueCountFrequency (%)
False 30
96.8%
True 1
 
3.2%
2024-04-19T14:16:13.726257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

경비업체연계유무
Boolean

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size163.0 B
False
31 
ValueCountFrequency (%)
False 31
100.0%
2024-04-19T14:16:13.802371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리사무소연계유무
Boolean

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size163.0 B
False
31 
ValueCountFrequency (%)
False 31
100.0%
2024-04-19T14:16:13.871856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

부가기능
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
경고등,경보음
31 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경고등,경보음
2nd row경고등,경보음
3rd row경고등,경보음
4th row경고등,경보음
5th row경고등,경보음

Common Values

ValueCountFrequency (%)
경고등,경보음 31
100.0%

Length

2024-04-19T14:16:13.968639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:16:14.053924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경고등,경보음 31
100.0%

안전비상벨설치년도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
2017
28 
2013
 
2
2018
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2017 28
90.3%
2013 2
 
6.5%
2018 1
 
3.2%

Length

2024-04-19T14:16:14.147076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:16:14.234476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 28
90.3%
2013 2
 
6.5%
2018 1
 
3.2%

최종점검일자
Date

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2020-04-16 00:00:00
Maximum2020-04-16 00:00:00
2024-04-19T14:16:14.309137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:16:14.650096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

최종점검결과구분
Boolean

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size163.0 B
True
31 
ValueCountFrequency (%)
True 31
100.0%
2024-04-19T14:16:14.739240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

관리기관명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
강북경찰서
23 
북부경찰서
8 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row북부경찰서
2nd row북부경찰서
3rd row북부경찰서
4th row강북경찰서
5th row강북경찰서

Common Values

ValueCountFrequency (%)
강북경찰서 23
74.2%
북부경찰서 8
 
25.8%

Length

2024-04-19T14:16:14.830580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:16:14.917972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강북경찰서 23
74.2%
북부경찰서 8
 
25.8%

관리기관전화번호
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
053-380-3104
23 
053-380-5104
8 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row053-380-5104
2nd row053-380-5104
3rd row053-380-5104
4th row053-380-3104
5th row053-380-3104

Common Values

ValueCountFrequency (%)
053-380-3104 23
74.2%
053-380-5104 8
 
25.8%

Length

2024-04-19T14:16:15.010560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:16:15.097833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
053-380-3104 23
74.2%
053-380-5104 8
 
25.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2020-05-01 00:00:00
Maximum2020-05-01 00:00:00
2024-04-19T14:16:15.174718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:16:15.260045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-19T14:16:10.418597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:16:09.951673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:16:10.183503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:16:10.508578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:16:10.027782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:16:10.262691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:16:10.589116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:16:10.105460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:16:10.338959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T14:16:15.330121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
안전비상벨관리번호설치위치소재지도로명주소소재지지번주소위도경도연계방식경찰연계유무안전비상벨설치년도관리기관명관리기관전화번호
안전비상벨관리번호1.0001.0000.7190.9620.4800.5920.0000.0000.0000.8890.889
설치위치1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소0.7191.0001.0001.0001.0001.0000.0000.0000.0001.0001.000
소재지지번주소0.9621.0001.0001.0001.0001.0000.0000.0000.0001.0001.000
위도0.4801.0001.0001.0001.0000.7450.0000.0000.7120.6360.636
경도0.5921.0001.0001.0000.7451.0000.0000.0000.5240.8880.888
연계방식0.0001.0000.0000.0000.0000.0001.0000.6571.0000.0000.000
경찰연계유무0.0001.0000.0000.0000.0000.0000.6571.0001.0000.0000.000
안전비상벨설치년도0.0001.0000.0000.0000.7120.5241.0001.0001.0000.0000.000
관리기관명0.8891.0001.0001.0000.6360.8880.0000.0000.0001.0000.991
관리기관전화번호0.8891.0001.0001.0000.6360.8880.0000.0000.0000.9911.000
2024-04-19T14:16:15.462107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
안전비상벨설치년도관리기관전화번호연계방식경찰연계유무관리기관명
안전비상벨설치년도1.0000.0000.9830.9830.000
관리기관전화번호0.0001.0000.0000.0000.913
연계방식0.9830.0001.0000.4550.000
경찰연계유무0.9830.0000.4551.0000.000
관리기관명0.0000.9130.0000.0001.000
2024-04-19T14:16:15.560336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
안전비상벨관리번호위도경도연계방식경찰연계유무안전비상벨설치년도관리기관명관리기관전화번호
안전비상벨관리번호1.0000.262-0.2940.1070.1070.0000.6010.601
위도0.2621.000-0.4400.0000.0000.3610.5550.555
경도-0.294-0.4401.0000.0000.0000.3550.5670.567
연계방식0.1070.0000.0001.0000.4550.9830.0000.000
경찰연계유무0.1070.0000.0000.4551.0000.9830.0000.000
안전비상벨설치년도0.0000.3610.3550.9830.9831.0000.0000.000
관리기관명0.6010.5550.5670.0000.0000.0001.0000.913
관리기관전화번호0.6010.5550.5670.0000.0000.0000.9131.000

Missing values

2024-04-19T14:16:10.711236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:16:10.921356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

안전비상벨관리번호설치목적설치장소유형설치위치소재지도로명주소소재지지번주소위도경도연계방식경찰연계유무경비업체연계유무관리사무소연계유무부가기능안전비상벨설치년도최종점검일자최종점검결과구분관리기관명관리기관전화번호데이터기준일자
0122침산근린A<NA>대구광역시 북구 침산동 1170-735.897064128.5849131NNN경고등,경보음20172020-04-16Y북부경찰서053-380-51042020-05-01
1222침산근린B<NA>대구광역시 북구 침산동 132935.897266128.5848591NNN경고등,경보음20172020-04-16Y북부경찰서053-380-51042020-05-01
2322신기근린<NA>대구광역시 북구 산격동 162035.907327128.6089261NNN경고등,경보음20172020-04-16Y북부경찰서053-380-51042020-05-01
3422관음근린대구광역시 북구 구암로 47대구광역시 북구 관음동 137235.935866128.5451271NNN경고등,경보음20172020-04-16Y강북경찰서053-380-31042020-05-01
4522태전근린대구광역시 북구 칠곡중앙대로 397-20대구광역시 북구 태전동 93835.931636128.5461611NNN경고등,경보음20172020-04-16Y강북경찰서053-380-31042020-05-01
5622대불근린<NA>대구광역시 북구 산격동 산2-135.905364128.6156471NNN경고등,경보음20132020-04-16Y강북경찰서053-380-31042020-05-01
6722구암근린<NA>대구광역시 북구 구암동 69435.928436128.5568161NNN경고등,경보음20172020-04-16Y강북경찰서053-380-31042020-05-01
7822함지근린<NA>대구광역시 북구 구암동 77335.942288128.5687281NNN경고등,경보음20172020-04-16Y강북경찰서053-380-31042020-05-01
8922동천근린<NA>대구광역시 북구 동천동 950-135.934446128.5592631NNN경고등,경보음20172020-04-16Y북부경찰서053-380-51042020-05-01
91022연암근린<NA>대구광역시 북구 산격동 산86-135.899601128.5985871NNN경고등,경보음20132020-04-16Y강북경찰서053-380-31042020-05-01
안전비상벨관리번호설치목적설치장소유형설치위치소재지도로명주소소재지지번주소위도경도연계방식경찰연계유무경비업체연계유무관리사무소연계유무부가기능안전비상벨설치년도최종점검일자최종점검결과구분관리기관명관리기관전화번호데이터기준일자
212222송 암<NA>대구광역시 북구 관음동 129035.942992128.5471981NNN경고등,경보음20172020-04-16Y강북경찰서053-380-31042020-05-01
222322읍 내<NA>대구광역시 북구 관음동 138235.940601128.5496641NNN경고등,경보음20172020-04-16Y강북경찰서053-380-31042020-05-01
232422참 물 샘<NA>대구광역시 북구 동천동 872-135.933957128.5561411NNN경고등,경보음20172020-04-16Y강북경찰서053-380-31042020-05-01
242522들 말<NA>대구광역시 북구 동천동 880-235.932618128.5587071NNN경고등,경보음20172020-04-16Y강북경찰서053-380-31042020-05-01
252622운 암대구광역시 북구 태암남로11길 19-5대구광역시 북구 구암동 665-235.926658128.553571NNN경고등,경보음20172020-04-16Y강북경찰서053-380-31042020-05-01
262722진 달 래대구광역시 북구 학정로48길 15대구광역시 북구 구암동 702-435.925646128.5587591NNN경고등,경보음20172020-04-16Y강북경찰서053-380-31042020-05-01
272822해 당 화<NA>대구광역시 북구 구암동 66235.927013128.5527281NNN경고등,경보음20172020-04-16Y강북경찰서053-380-31042020-05-01
282922다 람 쥐<NA>대구광역시 북구 구암동 67935.926163128.5552931NNN경고등,경보음20172020-04-16Y강북경찰서053-380-31042020-05-01
293022구암어린이공원<NA>대구광역시 북구 구암동 70035.926424128.5592511NNN경고등,경보음20172020-04-16Y강북경찰서053-380-31042020-05-01
303122태전근린2대구광역시 북구 칠곡중앙대로 397-20대구광역시 북구 태전동 93835.931636128.5461613YNN경고등,경보음20182020-04-16Y강북경찰서053-380-31042020-05-01