Overview

Dataset statistics

Number of variables13
Number of observations38
Missing cells75
Missing cells (%)15.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory111.5 B

Variable types

Categorical5
Text4
Numeric3
Unsupported1

Dataset

Description서울특별시 용산구 어린이보호구역현황(시설종류 대상시설명 소재지도로명주소 소재지지번주소 위도 경도 관리기관명 관할경찰서명 CCTV설치여부 CCTV설치대수 보호구역도로폭)에 대한 데이터를 제공합니다
Author서울특별시 용산구
URLhttps://www.data.go.kr/data/3077862/fileData.do

Alerts

관리기관명 has constant value ""Constant
관할경찰서명 has constant value ""Constant
CCTV설치여부 has constant value ""Constant
시설종류 대상시설명 소재지도로명주소 소재지지번주소 위도 경도 관리기관명 관할경찰서명 CCTV설치여부 CCTV설치대수 보호구역도로폭 has constant value ""Constant
Unnamed: 11 has 38 (100.0%) missing valuesMissing
시설종류 대상시설명 소재지도로명주소 소재지지번주소 위도 경도 관리기관명 관할경찰서명 CCTV설치여부 CCTV설치대수 보호구역도로폭 has 37 (97.4%) missing valuesMissing
대상시설명 has unique valuesUnique
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 05:23:30.074282
Analysis finished2023-12-12 05:23:32.269602
Duration2.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설종류
Categorical

Distinct4
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size436.0 B
초등학교
15 
유치원
15 
어린이집
6 
기타
2 

Length

Max length4
Median length4
Mean length3.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
초등학교 15
39.5%
유치원 15
39.5%
어린이집 6
 
15.8%
기타 2
 
5.3%

Length

2023-12-12T14:23:32.348126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:23:32.486141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초등학교 15
39.5%
유치원 15
39.5%
어린이집 6
 
15.8%
기타 2
 
5.3%

대상시설명
Text

UNIQUE 

Distinct38
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T14:23:32.746305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.1578947
Min length4

Characters and Unicode

Total characters234
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)100.0%

Sample

1st row용암초등학교
2nd row원효초등학교
3rd row신용산초등학교
4th row서빙고초등학교
5th row보광초등학교
ValueCountFrequency (%)
용암초등학교 1
 
2.6%
남정초병설유치원 1
 
2.6%
이태원삼성어린이집 1
 
2.6%
유성유치원 1
 
2.6%
한가람유치원 1
 
2.6%
계성유치원 1
 
2.6%
대건유치원 1
 
2.6%
원유치원 1
 
2.6%
한남초병설유치원 1
 
2.6%
청파초병설유치원 1
 
2.6%
Other values (28) 28
73.7%
2023-12-12T14:23:33.240886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 20
 
8.5%
초 19
 
8.1%
교 18
 
7.7%
학 17
 
7.3%
유 16
 
6.8%
등 15
 
6.4%
치 15
 
6.4%
이 9
 
3.8%
집 6
 
2.6%
린 6
 
2.6%
Other values (45) 93
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 234
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 20
 
8.5%
초 19
 
8.1%
교 18
 
7.7%
학 17
 
7.3%
유 16
 
6.8%
등 15
 
6.4%
치 15
 
6.4%
이 9
 
3.8%
집 6
 
2.6%
린 6
 
2.6%
Other values (45) 93
39.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 234
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 20
 
8.5%
초 19
 
8.1%
교 18
 
7.7%
학 17
 
7.3%
유 16
 
6.8%
등 15
 
6.4%
치 15
 
6.4%
이 9
 
3.8%
집 6
 
2.6%
린 6
 
2.6%
Other values (45) 93
39.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 234
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 20
 
8.5%
초 19
 
8.1%
교 18
 
7.7%
학 17
 
7.3%
유 16
 
6.8%
등 15
 
6.4%
치 15
 
6.4%
이 9
 
3.8%
집 6
 
2.6%
린 6
 
2.6%
Other values (45) 93
39.7%

소재지도로명주소
Text

Distinct35
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T14:23:33.570768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length19.710526
Min length17

Characters and Unicode

Total characters749
Distinct characters57
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

Unique32 ?
Unique (%)84.2%

Sample

1st row서울특별시 용산구 녹사평대로60길 39
2nd row서울특별시 용산구 효창원로13길 38
3rd row서울특별시 용산구 이촌로 255
4th row서울특별시 용산구 서빙고로51길 14
5th row서울특별시 용산구 우사단로 20
ValueCountFrequency (%)
서울특별시 38
25.0%
용산구 38
25.0%
효창원로 4
 
2.6%
서빙고로51길 2
 
1.3%
14 2
 
1.3%
원효로64길 2
 
1.3%
17-10 2
 
1.3%
한남대로 2
 
1.3%
112 2
 
1.3%
38 2
 
1.3%
Other values (55) 58
38.2%
2023-12-12T14:23:34.077437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
123
16.4%
서 41
 
5.5%
특 38
 
5.1%
별 38
 
5.1%
시 38
 
5.1%
용 38
 
5.1%
산 38
 
5.1%
구 38
 
5.1%
울 38
 
5.1%
로 38
 
5.1%
Other values (47) 281
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 474
63.3%
Decimal Number 143
 
19.1%
Space Separator 123
 
16.4%
Dash Punctuation 9
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 41
 
8.6%
특 38
 
8.0%
별 38
 
8.0%
시 38
 
8.0%
용 38
 
8.0%
산 38
 
8.0%
구 38
 
8.0%
울 38
 
8.0%
로 38
 
8.0%
길 25
 
5.3%
Other values (35) 104
21.9%
Decimal Number
ValueCountFrequency (%)
1 37
25.9%
2 20
14.0%
4 17
11.9%
3 14
 
9.8%
8 14
 
9.8%
7 11
 
7.7%
5 9
 
6.3%
0 8
 
5.6%
9 7
 
4.9%
6 6
 
4.2%
Space Separator
ValueCountFrequency (%)
123
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 474
63.3%
Common 275
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 41
 
8.6%
특 38
 
8.0%
별 38
 
8.0%
시 38
 
8.0%
용 38
 
8.0%
산 38
 
8.0%
구 38
 
8.0%
울 38
 
8.0%
로 38
 
8.0%
길 25
 
5.3%
Other values (35) 104
21.9%
Common
ValueCountFrequency (%)
123
44.7%
1 37
 
13.5%
2 20
 
7.3%
4 17
 
6.2%
3 14
 
5.1%
8 14
 
5.1%
7 11
 
4.0%
5 9
 
3.3%
- 9
 
3.3%
0 8
 
2.9%
Other values (2) 13
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 474
63.3%
ASCII 275
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
123
44.7%
1 37
 
13.5%
2 20
 
7.3%
4 17
 
6.2%
3 14
 
5.1%
8 14
 
5.1%
7 11
 
4.0%
5 9
 
3.3%
- 9
 
3.3%
0 8
 
2.9%
Other values (2) 13
 
4.7%
Hangul
ValueCountFrequency (%)
서 41
 
8.6%
특 38
 
8.0%
별 38
 
8.0%
시 38
 
8.0%
용 38
 
8.0%
산 38
 
8.0%
구 38
 
8.0%
울 38
 
8.0%
로 38
 
8.0%
길 25
 
5.3%
Other values (35) 104
21.9%

소재지지번주소
Text

Distinct34
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size436.0 B
2023-12-12T14:23:34.340156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length19.342105
Min length17

Characters and Unicode

Total characters735
Distinct characters42
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 (%)78.9%

Sample

1st row서울특별시 용산구 용산동2가 5-1488
2nd row서울특별시 용산구 산천동 7-73
3rd row서울특별시 용산구 이촌동 301-75
4th row서울특별시 용산구 서빙고동 235-1
5th row서울특별시 용산구 이태원동 15-13
ValueCountFrequency (%)
서울특별시 38
24.7%
용산구 38
24.7%
이촌동 7
 
4.5%
한남동 5
 
3.2%
이태원동 4
 
2.6%
산천동 3
 
1.9%
후암동 3
 
1.9%
54-1 2
 
1.3%
보광동 2
 
1.3%
원효로2가 2
 
1.3%
Other values (45) 50
32.5%
2023-12-12T14:23:34.750093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116
15.8%
산 43
 
5.9%
서 40
 
5.4%
용 39
 
5.3%
특 38
 
5.2%
별 38
 
5.2%
시 38
 
5.2%
구 38
 
5.2%
울 38
 
5.2%
1 35
 
4.8%
Other values (32) 272
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 434
59.0%
Decimal Number 152
 
20.7%
Space Separator 116
 
15.8%
Dash Punctuation 33
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 43
9.9%
서 40
9.2%
용 39
9.0%
특 38
8.8%
별 38
8.8%
시 38
8.8%
구 38
8.8%
울 38
8.8%
동 35
8.1%
이 12
 
2.8%
Other values (20) 75
17.3%
Decimal Number
ValueCountFrequency (%)
1 35
23.0%
2 23
15.1%
3 22
14.5%
0 17
11.2%
4 14
 
9.2%
5 13
 
8.6%
6 9
 
5.9%
7 8
 
5.3%
8 7
 
4.6%
9 4
 
2.6%
Space Separator
ValueCountFrequency (%)
116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 434
59.0%
Common 301
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 43
9.9%
서 40
9.2%
용 39
9.0%
특 38
8.8%
별 38
8.8%
시 38
8.8%
구 38
8.8%
울 38
8.8%
동 35
8.1%
이 12
 
2.8%
Other values (20) 75
17.3%
Common
ValueCountFrequency (%)
116
38.5%
1 35
 
11.6%
- 33
 
11.0%
2 23
 
7.6%
3 22
 
7.3%
0 17
 
5.6%
4 14
 
4.7%
5 13
 
4.3%
6 9
 
3.0%
7 8
 
2.7%
Other values (2) 11
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 434
59.0%
ASCII 301
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
116
38.5%
1 35
 
11.6%
- 33
 
11.0%
2 23
 
7.6%
3 22
 
7.3%
0 17
 
5.6%
4 14
 
4.7%
5 13
 
4.3%
6 9
 
3.0%
7 8
 
2.7%
Other values (2) 11
 
3.7%
Hangul
ValueCountFrequency (%)
산 43
9.9%
서 40
9.2%
용 39
9.0%
특 38
8.8%
별 38
8.8%
시 38
8.8%
구 38
8.8%
울 38
8.8%
동 35
8.1%
이 12
 
2.8%
Other values (20) 75
17.3%

위도
Real number (ℝ)

Distinct34
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.533637
Minimum37.518331
Maximum37.551865
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T14:23:34.923333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.518331
5-th percentile37.519601
Q137.523948
median37.535665
Q337.540202
95-th percentile37.548037
Maximum37.551865
Range0.033534
Interquartile range (IQR)0.0162535

Descriptive statistics

Standard deviation0.0098576352
Coefficient of variation (CV)0.00026263469
Kurtosis-1.0329484
Mean37.533637
Median Absolute Deviation (MAD)0.007253
Skewness-0.016578108
Sum1426.2782
Variance9.7172972 × 10-5
MonotonicityNot monotonic
2023-12-12T14:23:35.067252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
37.521308 2
 
5.3%
37.539292 2
 
5.3%
37.536263 2
 
5.3%
37.547478 2
 
5.3%
37.545023 1
 
2.6%
37.537255 1
 
2.6%
37.519469 1
 
2.6%
37.536091 1
 
2.6%
37.520866 1
 
2.6%
37.519624 1
 
2.6%
Other values (24) 24
63.2%
ValueCountFrequency (%)
37.518331 1
2.6%
37.519469 1
2.6%
37.519624 1
2.6%
37.520254 1
2.6%
37.520487 1
2.6%
37.520866 1
2.6%
37.521063 1
2.6%
37.521308 2
5.3%
37.523549 1
2.6%
37.525146 1
2.6%
ValueCountFrequency (%)
37.551865 1
2.6%
37.551204 1
2.6%
37.547478 2
5.3%
37.547311 1
2.6%
37.545023 1
2.6%
37.543162 1
2.6%
37.540615 1
2.6%
37.540517 1
2.6%
37.540505 1
2.6%
37.539292 2
5.3%

경도
Real number (ℝ)

Distinct34
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.97936
Minimum126.94994
Maximum127.01217
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T14:23:35.209077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.94994
5-th percentile126.9528
Q1126.96501
median126.97741
Q3126.99343
95-th percentile127.00511
Maximum127.01217
Range0.06223
Interquartile range (IQR)0.0284175

Descriptive statistics

Standard deviation0.017089354
Coefficient of variation (CV)0.00013458372
Kurtosis-1.0595782
Mean126.97936
Median Absolute Deviation (MAD)0.0132295
Skewness0.052154673
Sum4825.2157
Variance0.00029204603
MonotonicityNot monotonic
2023-12-12T14:23:35.350846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
126.991682 2
 
5.3%
127.005114 2
 
5.3%
126.964988 2
 
5.3%
126.964177 2
 
5.3%
126.989237 1
 
2.6%
127.012166 1
 
2.6%
126.981243 1
 
2.6%
126.953004 1
 
2.6%
126.977505 1
 
2.6%
126.976795 1
 
2.6%
Other values (24) 24
63.2%
ValueCountFrequency (%)
126.949936 1
2.6%
126.951671 1
2.6%
126.953004 1
2.6%
126.954468 1
2.6%
126.957831 1
2.6%
126.961196 1
2.6%
126.964177 2
5.3%
126.964988 2
5.3%
126.965087 1
2.6%
126.967768 1
2.6%
ValueCountFrequency (%)
127.012166 1
2.6%
127.005114 2
5.3%
127.000912 1
2.6%
127.000591 1
2.6%
127.000481 1
2.6%
126.999598 1
2.6%
126.996349 1
2.6%
126.995375 1
2.6%
126.994013 1
2.6%
126.991682 2
5.3%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
용산구청
38 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용산구청 38
100.0%

Length

2023-12-12T14:23:35.526408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:23:35.668034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
용산구청 38
100.0%

관할경찰서명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
서울용산경찰서
38 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울용산경찰서 38
100.0%

Length

2023-12-12T14:23:35.796537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:23:35.924502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울용산경찰서 38
100.0%

CCTV설치여부
Categorical

CONSTANT 

Distinct1
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size436.0 B
설치
38 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
설치 38
100.0%

Length

2023-12-12T14:23:36.049342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:23:36.159451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
설치 38
100.0%

CCTV설치대수
Real number (ℝ)

Distinct7
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8684211
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size474.0 B
2023-12-12T14:23:36.239891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33.75
95-th percentile7
Maximum9
Range8
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation2.1831177
Coefficient of variation (CV)0.7610869
Kurtosis0.59698422
Mean2.8684211
Median Absolute Deviation (MAD)1
Skewness1.2138159
Sum109
Variance4.7660028
MonotonicityNot monotonic
2023-12-12T14:23:36.350954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 14
36.8%
2 7
18.4%
3 7
18.4%
4 3
 
7.9%
6 3
 
7.9%
7 3
 
7.9%
9 1
 
2.6%
ValueCountFrequency (%)
1 14
36.8%
2 7
18.4%
3 7
18.4%
4 3
 
7.9%
6 3
 
7.9%
7 3
 
7.9%
9 1
 
2.6%
ValueCountFrequency (%)
9 1
 
2.6%
7 3
 
7.9%
6 3
 
7.9%
4 3
 
7.9%
3 7
18.4%
2 7
18.4%
1 14
36.8%

보호구역도로폭
Categorical

Distinct18
Distinct (%)47.4%
Missing0
Missing (%)0.0%
Memory size436.0 B
6
8 
10
4 
5
3 
5~8
3 
15
3 
Other values (13)
17 

Length

Max length4
Median length3
Mean length2.1842105
Min length1

Unique

Unique9 ?
Unique (%)23.7%

Sample

1st row5
2nd row6~14
3rd row6~20
4th row4~15
5th row10

Common Values

ValueCountFrequency (%)
6 8
21.1%
10 4
10.5%
5 3
 
7.9%
5~8 3
 
7.9%
15 3
 
7.9%
4~15 2
 
5.3%
5~7 2
 
5.3%
7 2
 
5.3%
6~8 2
 
5.3%
8~10 1
 
2.6%
Other values (8) 8
21.1%

Length

2023-12-12T14:23:36.479694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
6 8
21.1%
10 4
10.5%
5 3
 
7.9%
5~8 3
 
7.9%
15 3
 
7.9%
4~15 2
 
5.3%
5~7 2
 
5.3%
7 2
 
5.3%
6~8 2
 
5.3%
8 1
 
2.6%
Other values (8) 8
21.1%

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing38
Missing (%)100.0%
Memory size474.0 B

시설종류 대상시설명 소재지도로명주소 소재지지번주소 위도 경도 관리기관명 관할경찰서명 CCTV설치여부 CCTV설치대수 보호구역도로폭
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing37
Missing (%)97.4%
Memory size436.0 B
2023-12-12T14:23:36.647844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length72
Mean length72
Min length72

Characters and Unicode

Total characters72
Distinct characters35
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

Unique1 ?
Unique (%)100.0%

Sample

1st row시설종류 대상시설명 소재지도로명주소 소재지지번주소 위도 경도 관리기관명 관할경찰서명 CCTV설치여부 CCTV설치대수 보호구역도로폭
ValueCountFrequency (%)
시설종류 1
9.1%
대상시설명 1
9.1%
소재지도로명주소 1
9.1%
소재지지번주소 1
9.1%
위도 1
9.1%
경도 1
9.1%
관리기관명 1
9.1%
관할경찰서명 1
9.1%
cctv설치여부 1
9.1%
cctv설치대수 1
9.1%
2023-12-12T14:23:36.951678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
 
13.9%
C 4
 
5.6%
명 4
 
5.6%
소 4
 
5.6%
설 4
 
5.6%
도 4
 
5.6%
관 3
 
4.2%
지 3
 
4.2%
주 2
 
2.8%
치 2
 
2.8%
Other values (25) 32
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54
75.0%
Space Separator 10
 
13.9%
Uppercase Letter 8
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
명 4
 
7.4%
소 4
 
7.4%
설 4
 
7.4%
도 4
 
7.4%
관 3
 
5.6%
지 3
 
5.6%
주 2
 
3.7%
치 2
 
3.7%
경 2
 
3.7%
시 2
 
3.7%
Other values (21) 24
44.4%
Uppercase Letter
ValueCountFrequency (%)
C 4
50.0%
V 2
25.0%
T 2
25.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54
75.0%
Common 10
 
13.9%
Latin 8
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
명 4
 
7.4%
소 4
 
7.4%
설 4
 
7.4%
도 4
 
7.4%
관 3
 
5.6%
지 3
 
5.6%
주 2
 
3.7%
치 2
 
3.7%
경 2
 
3.7%
시 2
 
3.7%
Other values (21) 24
44.4%
Latin
ValueCountFrequency (%)
C 4
50.0%
V 2
25.0%
T 2
25.0%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54
75.0%
ASCII 18
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
55.6%
C 4
 
22.2%
V 2
 
11.1%
T 2
 
11.1%
Hangul
ValueCountFrequency (%)
명 4
 
7.4%
소 4
 
7.4%
설 4
 
7.4%
도 4
 
7.4%
관 3
 
5.6%
지 3
 
5.6%
주 2
 
3.7%
치 2
 
3.7%
경 2
 
3.7%
시 2
 
3.7%
Other values (21) 24
44.4%

Interactions

2023-12-12T14:23:31.156118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:23:30.521297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:23:30.862008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:23:31.264110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:23:30.629517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:23:30.952096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:23:31.408439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:23:30.746612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:23:31.052176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:23:37.037309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류대상시설명소재지도로명주소소재지지번주소위도경도CCTV설치대수보호구역도로폭
시설종류1.0001.0000.8400.8140.0000.4950.2270.662
대상시설명1.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소0.8401.0001.0001.0001.0001.0001.0001.000
소재지지번주소0.8141.0001.0001.0001.0001.0001.0001.000
위도0.0001.0001.0001.0001.0000.5840.6300.797
경도0.4951.0001.0001.0000.5841.0000.2320.576
CCTV설치대수0.2271.0001.0001.0000.6300.2321.0000.767
보호구역도로폭0.6621.0001.0001.0000.7970.5760.7671.000
2023-12-12T14:23:37.144609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보호구역도로폭시설종류
보호구역도로폭1.0000.311
시설종류0.3111.000
2023-12-12T14:23:37.244613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도CCTV설치대수시설종류보호구역도로폭
위도1.000-0.0390.4210.0000.373
경도-0.0391.000-0.1170.2780.185
CCTV설치대수0.421-0.1171.0000.1350.369
시설종류0.0000.2780.1351.0000.311
보호구역도로폭0.3730.1850.3690.3111.000

Missing values

2023-12-12T14:23:31.614570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:23:32.184831image/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

시설종류대상시설명소재지도로명주소소재지지번주소위도경도관리기관명관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭Unnamed: 11시설종류 대상시설명 소재지도로명주소 소재지지번주소 위도 경도 관리기관명 관할경찰서명 CCTV설치여부 CCTV설치대수 보호구역도로폭
0초등학교용암초등학교서울특별시 용산구 녹사평대로60길 39서울특별시 용산구 용산동2가 5-148837.545023126.989237용산구청서울용산경찰서설치95<NA>시설종류 대상시설명 소재지도로명주소 소재지지번주소 위도 경도 관리기관명 관할경찰서명 CCTV설치여부 CCTV설치대수 보호구역도로폭
1초등학교원효초등학교서울특별시 용산구 효창원로13길 38서울특별시 용산구 산천동 7-7337.536213126.951671용산구청서울용산경찰서설치26~14<NA><NA>
2초등학교신용산초등학교서울특별시 용산구 이촌로 255서울특별시 용산구 이촌동 301-7537.520254126.975607용산구청서울용산경찰서설치26~20<NA><NA>
3초등학교서빙고초등학교서울특별시 용산구 서빙고로51길 14서울특별시 용산구 서빙고동 235-137.521308126.991682용산구청서울용산경찰서설치34~15<NA><NA>
4초등학교보광초등학교서울특별시 용산구 우사단로 20서울특별시 용산구 이태원동 15-1337.532433126.996349용산구청서울용산경찰서설치410<NA><NA>
5초등학교한남초등학교서울특별시 용산구 한남대로 112서울특별시 용산구 한남동 726-137.539292127.005114용산구청서울용산경찰서설치210<NA><NA>
6초등학교남정초등학교서울특별시 용산구 원효로64길 17-10서울특별시 용산구 원효로2가 54-137.536263126.964988용산구청서울용산경찰서설치65~7<NA><NA>
7초등학교이태원초등학교서울특별시 용산구 녹사평대로40길 19서울특별시 용산구 이태원동 40637.536016126.987945용산구청서울용산경찰서설치66~7<NA><NA>
8초등학교청파초등학교서울특별시 용산구 효창원로 228서울특별시 용산구 청파동2가 1-4237.547478126.964177용산구청서울용산경찰서설치35~8<NA><NA>
9초등학교후암초등학교서울특별시 용산구 두텁바위로 140서울특별시 용산구 후암동 30-13837.551204126.982087용산구청서울용산경찰서설치75~8<NA><NA>
시설종류대상시설명소재지도로명주소소재지지번주소위도경도관리기관명관할경찰서명CCTV설치여부CCTV설치대수보호구역도로폭Unnamed: 11시설종류 대상시설명 소재지도로명주소 소재지지번주소 위도 경도 관리기관명 관할경찰서명 CCTV설치여부 CCTV설치대수 보호구역도로폭
28유치원서빙고초병설유치원서울특별시 용산구 서빙고로51길 14서울특별시 용산구 서빙고동 235-137.521308126.991682용산구청서울용산경찰서설치34~15<NA><NA>
29유치원청파초병설유치원서울특별시 용산구 효창원로 228서울특별시 용산구 청파동2가 1-4237.547478126.964177용산구청서울용산경찰서설치35~8<NA><NA>
30기타용산국제학교서울특별시 용산구 이태원로 285서울특별시 용산구 한남동 산 10-21237.540505127.000591용산구청서울용산경찰서설치115<NA><NA>
31기타독일인학교서울특별시 용산구 독서당로 123서울특별시 용산구 한남동 4-1837.537255127.012166용산구청서울용산경찰서설치115<NA><NA>
32어린이집이촌어린이집서울특별시 용산구 이촌로14길 11-22서울특별시 용산구 이촌동 206-137.526866126.954468용산구청서울용산경찰서설치18~9<NA><NA>
33어린이집보광어린이집서울특별시 용산구 보광로12가길 48-4서울특별시 용산구 보광동 9-1237.528781127.000912용산구청서울용산경찰서설치24<NA><NA>
34어린이집충신교회어린이집서울특별시 용산구 이촌로64길 72서울특별시 용산구 이촌1동 302-9137.520487126.967768용산구청서울용산경찰서설치16<NA><NA>
35어린이집동빙고어린이집서울특별시 용산구 녹사평대로14길 7서울특별시 용산구 동빙고동 7-4037.523549126.994013용산구청서울용산경찰서설치36<NA><NA>
36어린이집이태원삼성어린이집서울특별시 용산구 이태원로27길 34-30서울특별시 용산구 이태원동 111-637.535315126.995375용산구청서울용산경찰서설치17<NA><NA>
37어린이집한남어린이집서울특별시 용산구 대사관로5길 1서울특별시 용산구 한남동 685-4337.534517127.000481용산구청서울용산경찰서설치16~15<NA><NA>