Overview

Dataset statistics

Number of variables12
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory105.3 B

Variable types

Categorical3
Text4
Numeric3
Boolean1
DateTime1

Dataset

Description대구광역시_중구_어린이보호구역_20190601
Author대구광역시 중구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15009111&dataSetDetailId=150091111b29d483f7bb2_201910021420&provdMethod=FILE

Alerts

관리기관명 has constant value ""Constant
관할경찰서명 has constant value ""Constant
CCTV설치여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
대상시설명 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
소재지지번주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:58:08.025648
Analysis finished2023-12-10 17:58:10.830418
Duration2.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설종류
Categorical

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
초등학교
11 
유치원
5 
어린이집
5 

Length

Max length4
Median length4
Mean length3.7619048
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
초등학교 11
52.4%
유치원 5
23.8%
어린이집 5
23.8%

Length

2023-12-11T02:58:10.959135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:58:11.161802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초등학교 11
52.4%
유치원 5
23.8%
어린이집 5
23.8%

대상시설명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T02:58:11.508840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length6.5714286
Min length5

Characters and Unicode

Total characters138
Distinct characters48
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row수창초등학교
2nd row남산초등학교
3rd row명덕초등학교
4th row종로초등학교
5th row삼덕초등학교
ValueCountFrequency (%)
수창초등학교 1
 
4.8%
ymca유치원 1
 
4.8%
동화나라어린이집 1
 
4.8%
대구삼성어린이집 1
 
4.8%
대구초등학교 1
 
4.8%
남산교회어린이집 1
 
4.8%
백합어린이집 1
 
4.8%
보나유치원 1
 
4.8%
성모유치원 1
 
4.8%
원만사유치원 1
 
4.8%
Other values (11) 11
52.4%
2023-12-11T02:58:12.239717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 13
 
9.4%
초 11
 
8.0%
등 11
 
8.0%
학 11
 
8.0%
원 6
 
4.3%
대 5
 
3.6%
집 5
 
3.6%
이 5
 
3.6%
유 5
 
3.6%
린 5
 
3.6%
Other values (38) 61
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 134
97.1%
Uppercase Letter 4
 
2.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 13
 
9.7%
초 11
 
8.2%
등 11
 
8.2%
학 11
 
8.2%
원 6
 
4.5%
대 5
 
3.7%
집 5
 
3.7%
이 5
 
3.7%
유 5
 
3.7%
린 5
 
3.7%
Other values (34) 57
42.5%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
A 1
25.0%
M 1
25.0%
Y 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 134
97.1%
Latin 4
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 13
 
9.7%
초 11
 
8.2%
등 11
 
8.2%
학 11
 
8.2%
원 6
 
4.5%
대 5
 
3.7%
집 5
 
3.7%
이 5
 
3.7%
유 5
 
3.7%
린 5
 
3.7%
Other values (34) 57
42.5%
Latin
ValueCountFrequency (%)
C 1
25.0%
A 1
25.0%
M 1
25.0%
Y 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 134
97.1%
ASCII 4
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 13
 
9.7%
초 11
 
8.2%
등 11
 
8.2%
학 11
 
8.2%
원 6
 
4.5%
대 5
 
3.7%
집 5
 
3.7%
이 5
 
3.7%
유 5
 
3.7%
린 5
 
3.7%
Other values (34) 57
42.5%
ASCII
ValueCountFrequency (%)
C 1
25.0%
A 1
25.0%
M 1
25.0%
Y 1
25.0%

소재지도로명주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T02:58:12.577973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length17.666667
Min length14

Characters and Unicode

Total characters371
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

Unique21 ?
Unique (%)100.0%

Sample

1st row대구광역시 중구 달성로22길 30
2nd row대구광역시 중구 남산로 70
3rd row대구광역시 중구 남산로2길 125
4th row대구광역시 중구 경상감영길 49
5th row대구광역시 중구 달구벌대로447길 10
ValueCountFrequency (%)
대구광역시 21
25.0%
중구 21
25.0%
달구벌대로 3
 
3.6%
남산로7길 2
 
2.4%
남산로4길 2
 
2.4%
20 2
 
2.4%
남산로2길 1
 
1.2%
9 1
 
1.2%
남산로3안길 1
 
1.2%
2016-40 1
 
1.2%
Other values (29) 29
34.5%
2023-12-11T02:58:13.172181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
17.0%
구 46
12.4%
대 26
 
7.0%
중 22
 
5.9%
광 21
 
5.7%
역 21
 
5.7%
시 21
 
5.7%
로 19
 
5.1%
길 13
 
3.5%
2 12
 
3.2%
Other values (31) 107
28.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 237
63.9%
Decimal Number 70
 
18.9%
Space Separator 63
 
17.0%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 46
19.4%
대 26
11.0%
중 22
9.3%
광 21
8.9%
역 21
8.9%
시 21
8.9%
로 19
8.0%
길 13
 
5.5%
남 7
 
3.0%
산 7
 
3.0%
Other values (19) 34
14.3%
Decimal Number
ValueCountFrequency (%)
2 12
17.1%
0 11
15.7%
1 10
14.3%
3 8
11.4%
4 7
10.0%
7 6
8.6%
5 5
7.1%
6 4
 
5.7%
9 4
 
5.7%
8 3
 
4.3%
Space Separator
ValueCountFrequency (%)
63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 237
63.9%
Common 134
36.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 46
19.4%
대 26
11.0%
중 22
9.3%
광 21
8.9%
역 21
8.9%
시 21
8.9%
로 19
8.0%
길 13
 
5.5%
남 7
 
3.0%
산 7
 
3.0%
Other values (19) 34
14.3%
Common
ValueCountFrequency (%)
63
47.0%
2 12
 
9.0%
0 11
 
8.2%
1 10
 
7.5%
3 8
 
6.0%
4 7
 
5.2%
7 6
 
4.5%
5 5
 
3.7%
6 4
 
3.0%
9 4
 
3.0%
Other values (2) 4
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 237
63.9%
ASCII 134
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
47.0%
2 12
 
9.0%
0 11
 
8.2%
1 10
 
7.5%
3 8
 
6.0%
4 7
 
5.2%
7 6
 
4.5%
5 5
 
3.7%
6 4
 
3.0%
9 4
 
3.0%
Other values (2) 4
 
3.0%
Hangul
ValueCountFrequency (%)
구 46
19.4%
대 26
11.0%
중 22
9.3%
광 21
8.9%
역 21
8.9%
시 21
8.9%
로 19
8.0%
길 13
 
5.5%
남 7
 
3.0%
산 7
 
3.0%
Other values (19) 34
14.3%

소재지지번주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T02:58:13.536160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length17.380952
Min length15

Characters and Unicode

Total characters365
Distinct characters33
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

Unique21 ?
Unique (%)100.0%

Sample

1st row대구광역시 중구 수창동 73
2nd row대구광역시 중구 남산동 122
3rd row대구광역시 중구 남산동 2113
4th row대구광역시 중구 서문로1가 1-5
5th row대구광역시 중구 삼덕동3가 316
ValueCountFrequency (%)
대구광역시 21
25.0%
중구 21
25.0%
남산동 9
 
10.7%
대신동 2
 
2.4%
봉산동 2
 
2.4%
708 1
 
1.2%
180-1 1
 
1.2%
덕산동 1
 
1.2%
116 1
 
1.2%
동산동 1
 
1.2%
Other values (24) 24
28.6%
2023-12-11T02:58:14.260988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
17.3%
구 42
11.5%
대 23
 
6.3%
동 22
 
6.0%
광 21
 
5.8%
역 21
 
5.8%
시 21
 
5.8%
중 21
 
5.8%
2 19
 
5.2%
1 17
 
4.7%
Other values (23) 95
26.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 214
58.6%
Decimal Number 79
 
21.6%
Space Separator 63
 
17.3%
Dash Punctuation 9
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 42
19.6%
대 23
10.7%
동 22
10.3%
광 21
9.8%
역 21
9.8%
시 21
9.8%
중 21
9.8%
산 13
 
6.1%
남 10
 
4.7%
가 4
 
1.9%
Other values (11) 16
 
7.5%
Decimal Number
ValueCountFrequency (%)
2 19
24.1%
1 17
21.5%
3 7
 
8.9%
0 7
 
8.9%
8 7
 
8.9%
5 6
 
7.6%
6 5
 
6.3%
4 5
 
6.3%
7 4
 
5.1%
9 2
 
2.5%
Space Separator
ValueCountFrequency (%)
63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 214
58.6%
Common 151
41.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 42
19.6%
대 23
10.7%
동 22
10.3%
광 21
9.8%
역 21
9.8%
시 21
9.8%
중 21
9.8%
산 13
 
6.1%
남 10
 
4.7%
가 4
 
1.9%
Other values (11) 16
 
7.5%
Common
ValueCountFrequency (%)
63
41.7%
2 19
 
12.6%
1 17
 
11.3%
- 9
 
6.0%
3 7
 
4.6%
0 7
 
4.6%
8 7
 
4.6%
5 6
 
4.0%
6 5
 
3.3%
4 5
 
3.3%
Other values (2) 6
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 214
58.6%
ASCII 151
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
41.7%
2 19
 
12.6%
1 17
 
11.3%
- 9
 
6.0%
3 7
 
4.6%
0 7
 
4.6%
8 7
 
4.6%
5 6
 
4.0%
6 5
 
3.3%
4 5
 
3.3%
Other values (2) 6
 
4.0%
Hangul
ValueCountFrequency (%)
구 42
19.6%
대 23
10.7%
동 22
10.3%
광 21
9.8%
역 21
9.8%
시 21
9.8%
중 21
9.8%
산 13
 
6.1%
남 10
 
4.7%
가 4
 
1.9%
Other values (11) 16
 
7.5%

위도
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.864849
Minimum35.857539
Maximum35.874296
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T02:58:14.489200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.857539
5-th percentile35.858483
Q135.862322
median35.864469
Q335.866686
95-th percentile35.872496
Maximum35.874296
Range0.016756985
Interquartile range (IQR)0.0043641186

Descriptive statistics

Standard deviation0.0043744563
Coefficient of variation (CV)0.00012197058
Kurtosis-0.029699001
Mean35.864849
Median Absolute Deviation (MAD)0.002217
Skewness0.46772839
Sum753.16183
Variance1.9135868 × 10-5
MonotonicityNot monotonic
2023-12-11T02:58:14.735390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
35.874296 1
 
4.8%
35.863204 1
 
4.8%
35.8584830648 1
 
4.8%
35.860371 1
 
4.8%
35.864469 1
 
4.8%
35.8640369029 1
 
4.8%
35.8650401 1
 
4.8%
35.8623218814 1
 
4.8%
35.860456 1
 
4.8%
35.8606148493 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
35.8575390152 1
4.8%
35.8584830648 1
4.8%
35.860371 1
4.8%
35.860456 1
4.8%
35.8606148493 1
4.8%
35.8623218814 1
4.8%
35.863204 1
4.8%
35.863582926 1
4.8%
35.863588 1
4.8%
35.8640369029 1
4.8%
ValueCountFrequency (%)
35.874296 1
4.8%
35.8724962299 1
4.8%
35.871007 1
4.8%
35.868893 1
4.8%
35.8680836639 1
4.8%
35.866686 1
4.8%
35.8660756184 1
4.8%
35.8658471992 1
4.8%
35.8650401 1
4.8%
35.864739 1
4.8%

경도
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.58932
Minimum128.57749
Maximum128.60951
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T02:58:15.348778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.57749
5-th percentile128.57924
Q1128.58276
median128.58621
Q3128.59317
95-th percentile128.60784
Maximum128.60951
Range0.03201465
Interquartile range (IQR)0.010413181

Descriptive statistics

Standard deviation0.0093011789
Coefficient of variation (CV)7.2332434 × 10-5
Kurtosis0.067763302
Mean128.58932
Median Absolute Deviation (MAD)0.0056305436
Skewness0.94689812
Sum2700.3758
Variance8.6511929 × 10-5
MonotonicityNot monotonic
2023-12-11T02:58:15.560369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
128.5834440055 1
 
4.8%
128.5827598189 1
 
4.8%
128.5805840705 1
 
4.8%
128.577492 1
 
4.8%
128.584301 1
 
4.8%
128.595369577 1
 
4.8%
128.590565 1
 
4.8%
128.5860582232 1
 
4.8%
128.579243 1
 
4.8%
128.5862146141 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
128.577492 1
4.8%
128.579243 1
4.8%
128.580485 1
4.8%
128.5805840705 1
4.8%
128.5815806743 1
4.8%
128.5827598189 1
4.8%
128.5834440055 1
4.8%
128.5838700214 1
4.8%
128.584301 1
4.8%
128.5860582232 1
4.8%
ValueCountFrequency (%)
128.6095066499 1
4.8%
128.6078430869 1
4.8%
128.604646 1
4.8%
128.5980661173 1
4.8%
128.595369577 1
4.8%
128.593173 1
4.8%
128.5918827 1
4.8%
128.590565 1
4.8%
128.5897065682 1
4.8%
128.589027021 1
4.8%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
대구광역시 중구청
21 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 중구청 21
100.0%

Length

2023-12-11T02:58:15.758281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:58:15.933256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 21
50.0%
중구청 21
50.0%

관할경찰서명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
대구광역시 중부경찰서
21 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 중부경찰서 21
100.0%

Length

2023-12-11T02:58:16.110752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:58:16.285228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 21
50.0%
중부경찰서 21
50.0%

CCTV설치여부
Boolean

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size153.0 B
True
21 
ValueCountFrequency (%)
True 21
100.0%
2023-12-11T02:58:16.450154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

CCTV설치대수
Real number (ℝ)

Distinct11
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.047619
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T02:58:16.605177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8
Q311
95-th percentile12
Maximum14
Range13
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.1288762
Coefficient of variation (CV)0.58585406
Kurtosis-1.3080919
Mean7.047619
Median Absolute Deviation (MAD)4
Skewness0.047335523
Sum148
Variance17.047619
MonotonicityNot monotonic
2023-12-11T02:58:16.809608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
12 4
19.0%
8 3
14.3%
9 2
9.5%
1 2
9.5%
4 2
9.5%
2 2
9.5%
5 2
9.5%
14 1
 
4.8%
11 1
 
4.8%
6 1
 
4.8%
ValueCountFrequency (%)
1 2
9.5%
2 2
9.5%
3 1
 
4.8%
4 2
9.5%
5 2
9.5%
6 1
 
4.8%
8 3
14.3%
9 2
9.5%
11 1
 
4.8%
12 4
19.0%
ValueCountFrequency (%)
14 1
 
4.8%
12 4
19.0%
11 1
 
4.8%
9 2
9.5%
8 3
14.3%
6 1
 
4.8%
5 2
9.5%
4 2
9.5%
3 1
 
4.8%
2 2
9.5%

보호구역도로폭
Text

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T02:58:17.058845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.8095238
Min length2

Characters and Unicode

Total characters80
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)81.0%

Sample

1st row7~30
2nd row9~32
3rd row4~15
4th row6~12
5th row4~8
ValueCountFrequency (%)
7~11 2
 
9.5%
10~11 2
 
9.5%
12 1
 
4.8%
7~30 1
 
4.8%
7~9 1
 
4.8%
7~8 1
 
4.8%
3~12 1
 
4.8%
6~10 1
 
4.8%
43~44 1
 
4.8%
8~9 1
 
4.8%
Other values (9) 9
42.9%
2023-12-11T02:58:17.558434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
~ 20
25.0%
1 19
23.8%
3 6
 
7.5%
4 6
 
7.5%
7 5
 
6.2%
2 5
 
6.2%
5 5
 
6.2%
0 4
 
5.0%
8 4
 
5.0%
9 3
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
75.0%
Math Symbol 20
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
31.7%
3 6
 
10.0%
4 6
 
10.0%
7 5
 
8.3%
2 5
 
8.3%
5 5
 
8.3%
0 4
 
6.7%
8 4
 
6.7%
9 3
 
5.0%
6 3
 
5.0%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
~ 20
25.0%
1 19
23.8%
3 6
 
7.5%
4 6
 
7.5%
7 5
 
6.2%
2 5
 
6.2%
5 5
 
6.2%
0 4
 
5.0%
8 4
 
5.0%
9 3
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
~ 20
25.0%
1 19
23.8%
3 6
 
7.5%
4 6
 
7.5%
7 5
 
6.2%
2 5
 
6.2%
5 5
 
6.2%
0 4
 
5.0%
8 4
 
5.0%
9 3
 
3.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2019-06-01 00:00:00
Maximum2019-06-01 00:00:00
2023-12-11T02:58:17.744993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:58:17.909213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-11T02:58:09.835489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:58:08.656283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:58:09.174074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:58:09.997890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:58:08.835823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:58:09.391576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:58:10.151523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:58:09.011660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:58:09.623249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:58:18.031205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류대상시설명소재지도로명주소소재지지번주소위도경도CCTV설치대수보호구역도로폭
시설종류1.0001.0001.0001.0000.5760.2900.7270.000
대상시설명1.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.000
위도0.5761.0001.0001.0001.0000.0000.7690.512
경도0.2901.0001.0001.0000.0001.0000.7731.000
CCTV설치대수0.7271.0001.0001.0000.7690.7731.0000.512
보호구역도로폭0.0001.0001.0001.0000.5121.0000.5121.000
2023-12-11T02:58:18.232274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도CCTV설치대수시설종류
위도1.0000.239-0.1280.209
경도0.2391.0000.1880.000
CCTV설치대수-0.1280.1881.0000.328
시설종류0.2090.0000.3281.000

Missing values

2023-12-11T02:58:10.381724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:58:10.695167image/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
0초등학교수창초등학교대구광역시 중구 달성로22길 30대구광역시 중구 수창동 7335.874296128.583444대구광역시 중구청대구광역시 중부경찰서Y127~302019-06-01
1초등학교남산초등학교대구광역시 중구 남산로 70대구광역시 중구 남산동 12235.863204128.58276대구광역시 중구청대구광역시 중부경찰서Y129~322019-06-01
2초등학교명덕초등학교대구광역시 중구 남산로2길 125대구광역시 중구 남산동 211335.857539128.589027대구광역시 중구청대구광역시 중부경찰서Y144~152019-06-01
3초등학교종로초등학교대구광역시 중구 경상감영길 49대구광역시 중구 서문로1가 1-535.872496128.589707대구광역시 중구청대구광역시 중부경찰서Y86~122019-06-01
4초등학교삼덕초등학교대구광역시 중구 달구벌대로447길 10대구광역시 중구 삼덕동3가 31635.863588128.607843대구광역시 중구청대구광역시 중부경찰서Y114~82019-06-01
5초등학교동인초등학교대구광역시 중구 국채보상로 728대구광역시 중구 동인동4가 38835.868084128.609507대구광역시 중구청대구광역시 중부경찰서Y125~152019-06-01
6초등학교경대사범대부설초등학교대구광역시 중구 달구벌대로 2150대구광역시 중구 봉산동 16235.863583128.598066대구광역시 중구청대구광역시 중부경찰서Y65~112019-06-01
7초등학교계성초등학교대구광역시 중구 달성로 15대구광역시 중구 대신동 280-235.866076128.581581대구광역시 중구청대구광역시 중부경찰서Y94~322019-06-01
8초등학교동덕초등학교대구광역시 중구 동덕로26길 20대구광역시 중구 삼덕동2가 22735.864739128.604646대구광역시 중구청대구광역시 중부경찰서Y95~132019-06-01
9초등학교대구화교초등학교대구광역시 중구 종로 34대구광역시 중구 남일동 14235.868893128.591883대구광역시 중구청대구광역시 중부경찰서Y1122019-06-01
시설종류대상시설명소재지도로명주소소재지지번주소위도경도관리기관명관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭데이터기준일자
11유치원YMCA유치원대구광역시 중구 중앙대로 375대구광역시 중구 덕산동 11635.866686128.593173대구광역시 중구청대구광역시 중부경찰서Y18~92019-06-01
12유치원원만사유치원대구광역시 중구 달구벌대로 2013대구광역시 중구 동산동 70835.865847128.58387대구광역시 중구청대구광역시 중부경찰서Y243~442019-06-01
13유치원성모유치원대구광역시 중구 남산로4길 90대구광역시 중구 남산동 220035.860615128.586215대구광역시 중구청대구광역시 중부경찰서Y810~112019-06-01
14유치원보나유치원대구광역시 중구 남산로7길 86대구광역시 중구 남산동 2482-45535.860456128.579243대구광역시 중구청대구광역시 중부경찰서Y87~112019-06-01
15어린이집백합어린이집대구광역시 중구 남산로4길 111대구광역시 중구 남산동 190-135.862322128.586058대구광역시 중구청대구광역시 중부경찰서Y310~112019-06-01
16어린이집남산교회어린이집대구광역시 중구 관덕정길 16대구광역시 중구 남산동 941-135.86504128.590565대구광역시 중구청대구광역시 중부경찰서Y56~102019-06-01
17초등학교대구초등학교대구광역시 중구 명륜로23길 80대구광역시 중구 봉산동 5735.864037128.59537대구광역시 중구청대구광역시 중부경찰서Y123~122019-06-01
18어린이집대구삼성어린이집대구광역시 중구 달구벌대로 2016-40대구광역시 중구 남산동 153-235.864469128.584301대구광역시 중구청대구광역시 중부경찰서Y27~82019-06-01
19어린이집동화나라어린이집대구광역시 중구 남산로3안길 20대구광역시 중구 남산동 2623-635.860371128.577492대구광역시 중구청대구광역시 중부경찰서Y56~82019-06-01
20어린이집꿈나무어린이집대구광역시 중구 남산로7길 35대구광역시 중구 남산동 2508-235.858483128.580584대구광역시 중구청대구광역시 중부경찰서Y47~112019-06-01