Overview

Dataset statistics

Number of variables12
Number of observations56
Missing cells56
Missing cells (%)8.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory102.4 B

Variable types

Categorical3
Text3
Numeric3
Boolean1
Unsupported1
DateTime1

Dataset

Description대구광역시_서구_어린이보호구역_20190924
Author대구광역시 서구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15009661&dataSetDetailId=150096612f766082c03ce_201909241833&provdMethod=FILE

Alerts

관리기관명 has constant value ""Constant
관할경찰서명 has constant value ""Constant
CCTV설치여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
CCTV설치대수 has 56 (100.0%) missing valuesMissing
대상시설명 has unique valuesUnique
CCTV설치대수 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-19 05:34:29.298337
Analysis finished2024-04-19 05:34:30.665163
Duration1.37 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설종류
Categorical

Distinct3
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size580.0 B
유치원
22 
초등학교
17 
어린이집
17 

Length

Max length4
Median length4
Mean length3.6071429
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row초등학교
2nd row초등학교
3rd row유치원
4th row초등학교
5th row유치원

Common Values

ValueCountFrequency (%)
유치원 22
39.3%
초등학교 17
30.4%
어린이집 17
30.4%

Length

2024-04-19T14:34:30.746072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:34:30.861944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유치원 22
39.3%
초등학교 17
30.4%
어린이집 17
30.4%

대상시설명
Text

UNIQUE 

Distinct56
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-04-19T14:34:31.045472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length7.4642857
Min length5

Characters and Unicode

Total characters418
Distinct characters75
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

Unique56 ?
Unique (%)100.0%

Sample

1st row경운초등학교
2nd row내서초등학교
3rd row내서초등학교병설유치원
4th row달서초등학교
5th row달서초등학교병설유치원
ValueCountFrequency (%)
경운초등학교 1
 
1.8%
내서초등학교 1
 
1.8%
대구근로복지공단어린이집 1
 
1.8%
달서유치원 1
 
1.8%
상지유치원 1
 
1.8%
성심유치원 1
 
1.8%
세화유치원 1
 
1.8%
신익유치원 1
 
1.8%
에덴유치원 1
 
1.8%
평리유치원 1
 
1.8%
Other values (46) 46
82.1%
2024-04-19T14:34:31.382090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
초 30
 
7.2%
등 30
 
7.2%
학 30
 
7.2%
교 30
 
7.2%
유 22
 
5.3%
원 22
 
5.3%
치 22
 
5.3%
이 21
 
5.0%
집 17
 
4.1%
린 17
 
4.1%
Other values (65) 177
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 416
99.5%
Lowercase Letter 1
 
0.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 30
 
7.2%
등 30
 
7.2%
학 30
 
7.2%
교 30
 
7.2%
유 22
 
5.3%
원 22
 
5.3%
치 22
 
5.3%
이 21
 
5.0%
집 17
 
4.1%
린 17
 
4.1%
Other values (63) 175
42.1%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 416
99.5%
Latin 1
 
0.2%
Common 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 30
 
7.2%
등 30
 
7.2%
학 30
 
7.2%
교 30
 
7.2%
유 22
 
5.3%
원 22
 
5.3%
치 22
 
5.3%
이 21
 
5.0%
집 17
 
4.1%
린 17
 
4.1%
Other values (63) 175
42.1%
Latin
ValueCountFrequency (%)
e 1
100.0%
Common
ValueCountFrequency (%)
- 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 416
99.5%
ASCII 2
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
초 30
 
7.2%
등 30
 
7.2%
학 30
 
7.2%
교 30
 
7.2%
유 22
 
5.3%
원 22
 
5.3%
치 22
 
5.3%
이 21
 
5.0%
집 17
 
4.1%
린 17
 
4.1%
Other values (63) 175
42.1%
ASCII
ValueCountFrequency (%)
e 1
50.0%
- 1
50.0%

소재지도로명주소
Text

Distinct43
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-04-19T14:34:31.603824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length18.428571
Min length15

Characters and Unicode

Total characters1032
Distinct characters41
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

Unique30 ?
Unique (%)53.6%

Sample

1st row대구광역시 서구 평리로54길 16
2nd row대구광역시 서구 달구벌대로371길 35
3rd row대구광역시 서구 달구벌대로371길 35
4th row대구광역시 서구 국채보상로34길 35
5th row대구광역시 서구 국채보상로34길 35
ValueCountFrequency (%)
대구광역시 56
25.1%
서구 56
25.1%
35 6
 
2.7%
국채보상로 5
 
2.2%
9 3
 
1.3%
평리로 3
 
1.3%
서대구로45길 2
 
0.9%
60 2
 
0.9%
국채보상로37길 2
 
0.9%
135 2
 
0.9%
Other values (66) 86
38.6%
2024-04-19T14:34:32.004843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
167
16.2%
구 122
 
11.8%
서 70
 
6.8%
대 66
 
6.4%
광 56
 
5.4%
역 56
 
5.4%
시 56
 
5.4%
로 56
 
5.4%
길 40
 
3.9%
3 37
 
3.6%
Other values (31) 306
29.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 651
63.1%
Decimal Number 207
 
20.1%
Space Separator 167
 
16.2%
Dash Punctuation 7
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 122
18.7%
서 70
10.8%
대 66
10.1%
광 56
8.6%
역 56
8.6%
시 56
8.6%
로 56
8.6%
길 40
 
6.1%
국 17
 
2.6%
상 17
 
2.6%
Other values (19) 95
14.6%
Decimal Number
ValueCountFrequency (%)
3 37
17.9%
1 27
13.0%
5 27
13.0%
2 25
12.1%
6 23
11.1%
4 19
9.2%
7 15
7.2%
8 14
 
6.8%
0 11
 
5.3%
9 9
 
4.3%
Space Separator
ValueCountFrequency (%)
167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 651
63.1%
Common 381
36.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 122
18.7%
서 70
10.8%
대 66
10.1%
광 56
8.6%
역 56
8.6%
시 56
8.6%
로 56
8.6%
길 40
 
6.1%
국 17
 
2.6%
상 17
 
2.6%
Other values (19) 95
14.6%
Common
ValueCountFrequency (%)
167
43.8%
3 37
 
9.7%
1 27
 
7.1%
5 27
 
7.1%
2 25
 
6.6%
6 23
 
6.0%
4 19
 
5.0%
7 15
 
3.9%
8 14
 
3.7%
0 11
 
2.9%
Other values (2) 16
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 651
63.1%
ASCII 381
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
167
43.8%
3 37
 
9.7%
1 27
 
7.1%
5 27
 
7.1%
2 25
 
6.6%
6 23
 
6.0%
4 19
 
5.0%
7 15
 
3.9%
8 14
 
3.7%
0 11
 
2.9%
Other values (2) 16
 
4.2%
Hangul
ValueCountFrequency (%)
구 122
18.7%
서 70
10.8%
대 66
10.1%
광 56
8.6%
역 56
8.6%
시 56
8.6%
로 56
8.6%
길 40
 
6.1%
국 17
 
2.6%
상 17
 
2.6%
Other values (19) 95
14.6%

소재지지번주소
Text

Distinct43
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
2024-04-19T14:34:32.664802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length18.267857
Min length16

Characters and Unicode

Total characters1023
Distinct characters31
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)53.6%

Sample

1st row대구광역시 서구 내당동 296
2nd row대구광역시 서구 내당동 11-33
3rd row대구광역시 서구 내당동 11-33
4th row대구광역시 서구 중리동 65-2
5th row대구광역시 서구 중리동 65-2
ValueCountFrequency (%)
대구광역시 55
24.8%
서구 55
24.8%
비산동 19
 
8.6%
평리동 18
 
8.1%
내당동 9
 
4.1%
중리동 5
 
2.3%
705-1 2
 
0.9%
1070-37 2
 
0.9%
48-60 2
 
0.9%
1500 2
 
0.9%
Other values (42) 53
23.9%
2024-04-19T14:34:33.015318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
166
16.2%
구 112
 
10.9%
1 73
 
7.1%
대 59
 
5.8%
광 56
 
5.5%
역 56
 
5.5%
시 56
 
5.5%
서 56
 
5.5%
동 56
 
5.5%
- 48
 
4.7%
Other values (21) 285
27.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 563
55.0%
Decimal Number 244
23.9%
Space Separator 166
 
16.2%
Dash Punctuation 48
 
4.7%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 112
19.9%
대 59
10.5%
광 56
9.9%
역 56
9.9%
시 56
9.9%
서 56
9.9%
동 56
9.9%
리 23
 
4.1%
산 19
 
3.4%
비 19
 
3.4%
Other values (8) 51
9.1%
Decimal Number
ValueCountFrequency (%)
1 73
29.9%
0 28
 
11.5%
4 21
 
8.6%
3 21
 
8.6%
5 20
 
8.2%
2 19
 
7.8%
6 17
 
7.0%
7 17
 
7.0%
8 16
 
6.6%
9 12
 
4.9%
Space Separator
ValueCountFrequency (%)
166
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Other Punctuation
ValueCountFrequency (%)
? 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 563
55.0%
Common 460
45.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 112
19.9%
대 59
10.5%
광 56
9.9%
역 56
9.9%
시 56
9.9%
서 56
9.9%
동 56
9.9%
리 23
 
4.1%
산 19
 
3.4%
비 19
 
3.4%
Other values (8) 51
9.1%
Common
ValueCountFrequency (%)
166
36.1%
1 73
15.9%
- 48
 
10.4%
0 28
 
6.1%
4 21
 
4.6%
3 21
 
4.6%
5 20
 
4.3%
2 19
 
4.1%
6 17
 
3.7%
7 17
 
3.7%
Other values (3) 30
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 563
55.0%
ASCII 460
45.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
166
36.1%
1 73
15.9%
- 48
 
10.4%
0 28
 
6.1%
4 21
 
4.6%
3 21
 
4.6%
5 20
 
4.3%
2 19
 
4.1%
6 17
 
3.7%
7 17
 
3.7%
Other values (3) 30
 
6.5%
Hangul
ValueCountFrequency (%)
구 112
19.9%
대 59
10.5%
광 56
9.9%
역 56
9.9%
시 56
9.9%
서 56
9.9%
동 56
9.9%
리 23
 
4.1%
산 19
 
3.4%
비 19
 
3.4%
Other values (8) 51
9.1%

위도
Real number (ℝ)

Distinct43
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.873025
Minimum35.85854
Maximum35.889446
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-19T14:34:33.141780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.85854
5-th percentile35.860871
Q135.866943
median35.872466
Q335.878803
95-th percentile35.885861
Maximum35.889446
Range0.030905536
Interquartile range (IQR)0.01185972

Descriptive statistics

Standard deviation0.0077875489
Coefficient of variation (CV)0.00021708648
Kurtosis-0.85015777
Mean35.873025
Median Absolute Deviation (MAD)0.0057455959
Skewness0.18562039
Sum2008.8894
Variance6.0645917 × 10-5
MonotonicityNot monotonic
2024-04-19T14:34:33.282754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
35.8861819579 2
 
3.6%
35.8668446974 2
 
3.6%
35.8828176132 2
 
3.6%
35.8704052565 2
 
3.6%
35.8638187525 2
 
3.6%
35.8815455172 2
 
3.6%
35.8827649236 2
 
3.6%
35.8723961081 2
 
3.6%
35.8694280582 2
 
3.6%
35.8672722676 2
 
3.6%
Other values (33) 36
64.3%
ValueCountFrequency (%)
35.8585402505 1
1.8%
35.8600071191 1
1.8%
35.860846 1
1.8%
35.8608795079 1
1.8%
35.8616275 1
1.8%
35.8638187525 2
3.6%
35.8649326 1
1.8%
35.865136 1
1.8%
35.8654976 1
1.8%
35.8658663444 1
1.8%
ValueCountFrequency (%)
35.8894457869 1
1.8%
35.8861819579 2
3.6%
35.885754 1
1.8%
35.885643 1
1.8%
35.8833927723 1
1.8%
35.8828176132 2
3.6%
35.8827649236 2
3.6%
35.8815455172 2
3.6%
35.878942 1
1.8%
35.8789341161 1
1.8%

경도
Real number (ℝ)

Distinct43
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.56286
Minimum128.54039
Maximum128.57921
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-19T14:34:33.424724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.54039
5-th percentile128.54473
Q1128.55278
median128.56459
Q3128.57011
95-th percentile128.57758
Maximum128.57921
Range0.038823491
Interquartile range (IQR)0.017334941

Descriptive statistics

Standard deviation0.010318471
Coefficient of variation (CV)8.0260126 × 10-5
Kurtosis-0.77627609
Mean128.56286
Median Absolute Deviation (MAD)0.0065382217
Skewness-0.35770567
Sum7199.5202
Variance0.00010647085
MonotonicityNot monotonic
2024-04-19T14:34:33.568278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
128.5672834167 2
 
3.6%
128.5505173128 2
 
3.6%
128.5792116709 2
 
3.6%
128.5771539788 2
 
3.6%
128.5667587689 2
 
3.6%
128.564592085 2
 
3.6%
128.568631 2
 
3.6%
128.561343031 2
 
3.6%
128.544730788 2
 
3.6%
128.5653520893 2
 
3.6%
Other values (33) 36
64.3%
ValueCountFrequency (%)
128.5403881795 1
1.8%
128.5435966 1
1.8%
128.544730788 2
3.6%
128.547905 2
3.6%
128.5488201 1
1.8%
128.5503987189 2
3.6%
128.5504903845 1
1.8%
128.5505173128 2
3.6%
128.552628 1
1.8%
128.5527372378 1
1.8%
ValueCountFrequency (%)
128.5792116709 2
3.6%
128.578864 1
1.8%
128.5771539788 2
3.6%
128.576145 1
1.8%
128.5758841531 1
1.8%
128.5753861 1
1.8%
128.5742659 1
1.8%
128.5737152 2
3.6%
128.5708117841 1
1.8%
128.5703329138 1
1.8%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
대구광역시 서구청
56 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구광역시 서구청
2nd row대구광역시 서구청
3rd row대구광역시 서구청
4th row대구광역시 서구청
5th row대구광역시 서구청

Common Values

ValueCountFrequency (%)
대구광역시 서구청 56
100.0%

Length

2024-04-19T14:34:33.706405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:34:33.794712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 56
50.0%
서구청 56
50.0%

관할경찰서명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
서부경찰서
56 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서부경찰서 56
100.0%

Length

2024-04-19T14:34:33.885660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:34:33.970256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서부경찰서 56
100.0%

CCTV설치여부
Boolean

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size188.0 B
True
56 
ValueCountFrequency (%)
True 56
100.0%
2024-04-19T14:34:34.038743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

CCTV설치대수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing56
Missing (%)100.0%
Memory size636.0 B

보호구역도로폭
Real number (ℝ)

Distinct16
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.821429
Minimum6
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size636.0 B
2024-04-19T14:34:34.113342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile8
Q18
median11.5
Q316.25
95-th percentile35
Maximum35
Range29
Interquartile range (IQR)8.25

Descriptive statistics

Standard deviation8.629984
Coefficient of variation (CV)0.58226398
Kurtosis0.58265401
Mean14.821429
Median Absolute Deviation (MAD)3.5
Skewness1.3222555
Sum830
Variance74.476623
MonotonicityNot monotonic
2024-04-19T14:34:34.215753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
8 14
25.0%
10 7
12.5%
15 7
12.5%
35 5
 
8.9%
9 4
 
7.1%
12 3
 
5.4%
30 2
 
3.6%
13 2
 
3.6%
21 2
 
3.6%
20 2
 
3.6%
Other values (6) 8
14.3%
ValueCountFrequency (%)
6 1
 
1.8%
7 1
 
1.8%
8 14
25.0%
9 4
 
7.1%
10 7
12.5%
11 1
 
1.8%
12 3
 
5.4%
13 2
 
3.6%
14 2
 
3.6%
15 7
12.5%
ValueCountFrequency (%)
35 5
8.9%
30 2
 
3.6%
26 2
 
3.6%
24 1
 
1.8%
21 2
 
3.6%
20 2
 
3.6%
15 7
12.5%
14 2
 
3.6%
13 2
 
3.6%
12 3
5.4%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size580.0 B
Minimum2019-09-24 00:00:00
Maximum2019-09-24 00:00:00
2024-04-19T14:34:34.320215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:34:34.406340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-19T14:34:30.125973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:34:29.605090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:34:29.840615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:34:30.220557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:34:29.674465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:34:29.932273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:34:30.316159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:34:29.760080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:34:30.035496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T14:34:34.477103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류대상시설명소재지도로명주소소재지지번주소위도경도보호구역도로폭
시설종류1.0001.0000.0000.0000.0000.0000.000
대상시설명1.0001.0001.0001.0001.0001.0001.000
소재지도로명주소0.0001.0001.0001.0001.0001.0001.000
소재지지번주소0.0001.0001.0001.0001.0001.0001.000
위도0.0001.0001.0001.0001.0000.6030.617
경도0.0001.0001.0001.0000.6031.0000.579
보호구역도로폭0.0001.0001.0001.0000.6170.5791.000
2024-04-19T14:34:34.578697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도보호구역도로폭시설종류
위도1.0000.346-0.1130.000
경도0.3461.000-0.1210.000
보호구역도로폭-0.113-0.1211.0000.000
시설종류0.0000.0000.0001.000

Missing values

2024-04-19T14:34:30.435915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:34:30.599096image/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

시설종류대상시설명소재지도로명주소소재지지번주소위도경도관리기관명관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭데이터기준일자
0초등학교경운초등학교대구광역시 서구 평리로54길 16대구광역시 서구 내당동 29635.86088128.552788대구광역시 서구청서부경찰서Y<NA>102019-09-24
1초등학교내서초등학교대구광역시 서구 달구벌대로371길 35대구광역시 서구 내당동 11-3335.863819128.566759대구광역시 서구청서부경찰서Y<NA>92019-09-24
2유치원내서초등학교병설유치원대구광역시 서구 달구벌대로371길 35대구광역시 서구 내당동 11-3335.863819128.566759대구광역시 서구청서부경찰서Y<NA>92019-09-24
3초등학교달서초등학교대구광역시 서구 국채보상로34길 35대구광역시 서구 중리동 65-235.866845128.550517대구광역시 서구청서부경찰서Y<NA>262019-09-24
4유치원달서초등학교병설유치원대구광역시 서구 국채보상로34길 35대구광역시 서구 중리동 65-235.866845128.550517대구광역시 서구청서부경찰서Y<NA>262019-09-24
5초등학교달성초등학교대구광역시 서구 고성로 127대구광역시 서구 원대동1가 1235.882818128.579212대구광역시 서구청서부경찰서Y<NA>152019-09-24
6유치원달성초등학교병설유치원대구광역시 서구 고성로 127대구광역시 서구 원대동1가 1235.882818128.579212대구광역시 서구청서부경찰서Y<NA>152019-09-24
7초등학교대성초등학교대구광역시 서구 국채보상로 426대구광역시 서구 비산동 169-135.870405128.577154대구광역시 서구청서부경찰서Y<NA>352019-09-24
8유치원대성초등학교병설유치원대구광역시 서구 국채보상로 426대구광역시 서구 비산동 169-135.870405128.577154대구광역시 서구청서부경찰서Y<NA>352019-09-24
9초등학교두류초등학교대구광역시 서구 달구벌대로357길 22대구광역시 서구 내당동 211-135.861627128.559932대구광역시 서구청서부경찰서Y<NA>82019-09-24
시설종류대상시설명소재지도로명주소소재지지번주소위도경도관리기관명관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭데이터기준일자
46어린이집서대구공단어린이집대구광역시 서구 평리로35길 10대구광역시 서구 중리동 1136-9235.860846128.543597대구광역시 서구청서부경찰서Y<NA>122019-09-24
47어린이집성산어린이집대구광역시 서구 옥산로6길 9대구광역시?서구?원대동3가 1120-135.885754128.578864대구광역시 서구청서부경찰서Y<NA>82019-09-24
48어린이집아이성어린이집대구광역시 서구 국채보상로83길 49대구광역시 서구 비산동 128-135.875656128.576145대구광역시 서구청서부경찰서Y<NA>62019-09-24
49어린이집영재어린이집대구광역시 서구 평리로 146대구광역시 서구 중리동 701-335.85854128.540388대구광역시 서구청서부경찰서Y<NA>242019-09-24
50어린이집수화어린이집대구광역시 서구 북비산로 389-1대구광역시 서구 비산동 4-535.878942128.575884대구광역시 서구청서부경찰서Y<NA>302019-09-24
51어린이집창의나라어린이집대구광역시 서구 문화로51길 9대구광역시 서구 평리동 945-835.876637128.560603대구광역시 서구청서부경찰서Y<NA>82019-09-24
52어린이집파란나라어린이집대구광역시 서구 통학로 138대구광역시 서구 평리동 1054-135.872537128.563097대구광역시 서구청서부경찰서Y<NA>152019-09-24
53어린이집행복이가득한어린이집대구광역시 서구 달서천로53길 18대구광역시 서구 비산동 928-1735.885643128.562261대구광역시 서구청서부경찰서Y<NA>152019-09-24
54어린이집다인어린이집대구광역시 서구 달서로7길 9대구광역시 서구 내당동 901-2835.864933128.570096대구광역시 서구청서부경찰서Y<NA>302019-09-24
55어린이집e-어린이집대구광역시 서구 통학로20길14-1대구광역시 서구 평리동 1174-1335.86904128.565806대구광역시 서구청서부경찰서Y<NA>122019-09-24