Overview

Dataset statistics

Number of variables6
Number of observations69
Missing cells93
Missing cells (%)22.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory49.9 B

Variable types

Categorical1
Text4
DateTime1

Dataset

Description광주광역시 여성긴급전화 1366광주센터 폭력피해여성 보호 및 지원관련 유관기관 현황 (기관명 및 기관 전화번호 포함)
Author광주광역시
URLhttps://www.data.go.kr/data/15043849/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
팩스번호 has 38 (55.1%) missing valuesMissing
전화번호 has 10 (14.5%) missing valuesMissing
비고(추가전화번호) has 45 (65.2%) missing valuesMissing

Reproduction

Analysis started2023-12-11 23:17:33.042669
Analysis finished2023-12-11 23:17:33.864500
Duration0.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct22
Distinct (%)31.9%
Missing0
Missing (%)0.0%
Memory size684.0 B
가정폭력&쉼터
6 
법률
6 
여성, 아동 성폭력상담소
6 
청소년상담&쉼터
5 
중독관리센터
5 
Other values (17)
41 

Length

Max length13
Median length7
Mean length5.8695652
Min length2

Unique

Unique4 ?
Unique (%)5.8%

Sample

1st row가정폭력&쉼터
2nd row가정폭력&쉼터
3rd row가정폭력&쉼터
4th row가정폭력&쉼터
5th row가정폭력&쉼터

Common Values

ValueCountFrequency (%)
가정폭력&쉼터 6
 
8.7%
법률 6
 
8.7%
여성, 아동 성폭력상담소 6
 
8.7%
청소년상담&쉼터 5
 
7.2%
중독관리센터 5
 
7.2%
건강가정지원센터 5
 
7.2%
알코올&정신병원 4
 
5.8%
심리상담 3
 
4.3%
자살 3
 
4.3%
도박중독 3
 
4.3%
Other values (12) 23
33.3%

Length

2023-12-12T08:17:33.957539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가정폭력&쉼터 6
 
7.4%
법률 6
 
7.4%
여성 6
 
7.4%
아동 6
 
7.4%
성폭력상담소 6
 
7.4%
청소년상담&쉼터 5
 
6.2%
중독관리센터 5
 
6.2%
건강가정지원센터 5
 
6.2%
알코올&정신병원 4
 
4.9%
보호기관 3
 
3.7%
Other values (14) 29
35.8%

기관명
Text

Distinct67
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size684.0 B
2023-12-12T08:17:34.213819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length24
Mean length12.768116
Min length4

Characters and Unicode

Total characters881
Distinct characters182
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)94.2%

Sample

1st rowYWCA가정상담센터
2nd row광주여성의전화 가정폭력상담소
3rd row광주여성의전화 가정폭력보호시설
4th row광주장애인 가정상담소/새날
5th row(사)광주장애인가족복지회
ValueCountFrequency (%)
건강가정지원센터 5
 
4.2%
성매매 3
 
2.5%
성폭력상담소 3
 
2.5%
국립나주정신병원(알코올 2
 
1.7%
다누리콜 2
 
1.7%
심리상담센터 2
 
1.7%
광주장애인 2
 
1.7%
서구 2
 
1.7%
광주여성민우회 2
 
1.7%
남구 2
 
1.7%
Other values (93) 95
79.2%
2023-12-12T08:17:34.930713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51
 
5.8%
터 34
 
3.9%
센 28
 
3.2%
상 28
 
3.2%
담 27
 
3.1%
광 23
 
2.6%
정 22
 
2.5%
성 19
 
2.2%
) 18
 
2.0%
주 18
 
2.0%
Other values (172) 613
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 739
83.9%
Space Separator 51
 
5.8%
Decimal Number 27
 
3.1%
Close Punctuation 18
 
2.0%
Open Punctuation 18
 
2.0%
Other Punctuation 14
 
1.6%
Uppercase Letter 8
 
0.9%
Dash Punctuation 2
 
0.2%
Control 2
 
0.2%
Initial Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 34
 
4.6%
센 28
 
3.8%
상 28
 
3.8%
담 27
 
3.7%
광 23
 
3.1%
정 22
 
3.0%
성 19
 
2.6%
주 18
 
2.4%
소 17
 
2.3%
가 17
 
2.3%
Other values (149) 506
68.5%
Decimal Number
ValueCountFrequency (%)
6 5
18.5%
2 5
18.5%
3 5
18.5%
4 4
14.8%
1 3
11.1%
9 2
 
7.4%
5 1
 
3.7%
7 1
 
3.7%
0 1
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 2
25.0%
C 2
25.0%
W 2
25.0%
Y 2
25.0%
Other Punctuation
ValueCountFrequency (%)
, 10
71.4%
/ 3
 
21.4%
: 1
 
7.1%
Space Separator
ValueCountFrequency (%)
51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 739
83.9%
Common 134
 
15.2%
Latin 8
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 34
 
4.6%
센 28
 
3.8%
상 28
 
3.8%
담 27
 
3.7%
광 23
 
3.1%
정 22
 
3.0%
성 19
 
2.6%
주 18
 
2.4%
소 17
 
2.3%
가 17
 
2.3%
Other values (149) 506
68.5%
Common
ValueCountFrequency (%)
51
38.1%
) 18
 
13.4%
( 18
 
13.4%
, 10
 
7.5%
6 5
 
3.7%
2 5
 
3.7%
3 5
 
3.7%
4 4
 
3.0%
1 3
 
2.2%
/ 3
 
2.2%
Other values (9) 12
 
9.0%
Latin
ValueCountFrequency (%)
A 2
25.0%
C 2
25.0%
W 2
25.0%
Y 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 739
83.9%
ASCII 140
 
15.9%
Punctuation 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51
36.4%
) 18
 
12.9%
( 18
 
12.9%
, 10
 
7.1%
6 5
 
3.6%
2 5
 
3.6%
3 5
 
3.6%
4 4
 
2.9%
1 3
 
2.1%
/ 3
 
2.1%
Other values (11) 18
 
12.9%
Hangul
ValueCountFrequency (%)
터 34
 
4.6%
센 28
 
3.8%
상 28
 
3.8%
담 27
 
3.7%
광 23
 
3.1%
정 22
 
3.0%
성 19
 
2.6%
주 18
 
2.4%
소 17
 
2.3%
가 17
 
2.3%
Other values (149) 506
68.5%
Punctuation
ValueCountFrequency (%)
‘ 1
50.0%
’ 1
50.0%

팩스번호
Text

MISSING 

Distinct30
Distinct (%)96.8%
Missing38
Missing (%)55.1%
Memory size684.0 B
2023-12-12T08:17:35.130013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.032258
Min length12

Characters and Unicode

Total characters373
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

Unique29 ?
Unique (%)93.5%

Sample

1st row062-672-1356
2nd row062-363-0486
3rd row062-654-0424
4th row062-944-1366
5th row062-671-1366
ValueCountFrequency (%)
062-376-4795 2
 
6.5%
070-8280-7711 1
 
3.2%
062-672-1356 1
 
3.2%
062-223-6860 1
 
3.2%
062-527-3370 1
 
3.2%
062-671-1461 1
 
3.2%
062-654-3804 1
 
3.2%
062-222-6446 1
 
3.2%
062-352-2979 1
 
3.2%
062-369-1367 1
 
3.2%
Other values (20) 20
64.5%
2023-12-12T08:17:35.488591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 62
16.6%
6 61
16.4%
2 56
15.0%
0 46
12.3%
3 35
9.4%
4 23
 
6.2%
1 23
 
6.2%
7 22
 
5.9%
5 19
 
5.1%
9 15
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 311
83.4%
Dash Punctuation 62
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 61
19.6%
2 56
18.0%
0 46
14.8%
3 35
11.3%
4 23
 
7.4%
1 23
 
7.4%
7 22
 
7.1%
5 19
 
6.1%
9 15
 
4.8%
8 11
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 373
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 62
16.6%
6 61
16.4%
2 56
15.0%
0 46
12.3%
3 35
9.4%
4 23
 
6.2%
1 23
 
6.2%
7 22
 
5.9%
5 19
 
5.1%
9 15
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 373
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 62
16.6%
6 61
16.4%
2 56
15.0%
0 46
12.3%
3 35
9.4%
4 23
 
6.2%
1 23
 
6.2%
7 22
 
5.9%
5 19
 
5.1%
9 15
 
4.0%

전화번호
Text

MISSING 

Distinct58
Distinct (%)98.3%
Missing10
Missing (%)14.5%
Memory size684.0 B
2023-12-12T08:17:35.742213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.847458
Min length9

Characters and Unicode

Total characters699
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

Unique57 ?
Unique (%)96.6%

Sample

1st row062-672-1355
2nd row062-363-0442
3rd row062-654-0420
4th row062-385-0422
5th row062-452-1366
ValueCountFrequency (%)
062-526-3370 2
 
3.4%
062-613-5790 1
 
1.7%
062-949-5200 1
 
1.7%
062-672-1355 1
 
1.7%
1577-1366 1
 
1.7%
062-351-0075 1
 
1.7%
062-234-5790 1
 
1.7%
062-369-0072 1
 
1.7%
062-351-9337 1
 
1.7%
062-430-2963 1
 
1.7%
Other values (48) 48
81.4%
2023-12-12T08:17:36.121594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 115
16.5%
6 106
15.2%
2 106
15.2%
0 96
13.7%
3 73
10.4%
1 47
6.7%
5 36
 
5.2%
7 34
 
4.9%
4 34
 
4.9%
9 29
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 584
83.5%
Dash Punctuation 115
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 106
18.2%
2 106
18.2%
0 96
16.4%
3 73
12.5%
1 47
8.0%
5 36
 
6.2%
7 34
 
5.8%
4 34
 
5.8%
9 29
 
5.0%
8 23
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 115
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 699
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 115
16.5%
6 106
15.2%
2 106
15.2%
0 96
13.7%
3 73
10.4%
1 47
6.7%
5 36
 
5.2%
7 34
 
4.9%
4 34
 
4.9%
9 29
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 699
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 115
16.5%
6 106
15.2%
2 106
15.2%
0 96
13.7%
3 73
10.4%
1 47
6.7%
5 36
 
5.2%
7 34
 
4.9%
4 34
 
4.9%
9 29
 
4.1%

비고(추가전화번호)
Text

MISSING 

Distinct21
Distinct (%)87.5%
Missing45
Missing (%)65.2%
Memory size684.0 B
2023-12-12T08:17:36.307407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length10.916667
Min length8

Characters and Unicode

Total characters262
Distinct characters23
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)75.0%

Sample

1st row062-363-0443
2nd row국번없이 132
3rd row062-608-1255
4th row062-222-0430
5th row062-225-3117(경찰)
ValueCountFrequency (%)
국번없이 9
27.3%
1388 2
 
6.1%
117 2
 
6.1%
112 2
 
6.1%
062-351-0074 1
 
3.0%
1599-0075 1
 
3.0%
062-600-1913(야간 1
 
3.0%
1393 1
 
3.0%
062-654-3803 1
 
3.0%
062-222-3993 1
 
3.0%
Other values (12) 12
36.4%
2023-12-12T08:17:36.628312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 30
11.5%
- 28
10.7%
0 27
10.3%
1 26
9.9%
3 24
 
9.2%
6 22
 
8.4%
9 13
 
5.0%
7 12
 
4.6%
5 10
 
3.8%
번 9
 
3.4%
Other values (13) 61
23.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 180
68.7%
Other Letter 40
 
15.3%
Dash Punctuation 28
 
10.7%
Space Separator 9
 
3.4%
Open Punctuation 2
 
0.8%
Close Punctuation 2
 
0.8%
Math Symbol 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 30
16.7%
0 27
15.0%
1 26
14.4%
3 24
13.3%
6 22
12.2%
9 13
7.2%
7 12
 
6.7%
5 10
 
5.6%
8 8
 
4.4%
4 8
 
4.4%
Other Letter
ValueCountFrequency (%)
번 9
22.5%
국 9
22.5%
이 9
22.5%
없 9
22.5%
경 1
 
2.5%
찰 1
 
2.5%
야 1
 
2.5%
간 1
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 222
84.7%
Hangul 40
 
15.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 30
13.5%
- 28
12.6%
0 27
12.2%
1 26
11.7%
3 24
10.8%
6 22
9.9%
9 13
5.9%
7 12
 
5.4%
5 10
 
4.5%
9
 
4.1%
Other values (5) 21
9.5%
Hangul
ValueCountFrequency (%)
번 9
22.5%
국 9
22.5%
이 9
22.5%
없 9
22.5%
경 1
 
2.5%
찰 1
 
2.5%
야 1
 
2.5%
간 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 222
84.7%
Hangul 40
 
15.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 30
13.5%
- 28
12.6%
0 27
12.2%
1 26
11.7%
3 24
10.8%
6 22
9.9%
9 13
5.9%
7 12
 
5.4%
5 10
 
4.5%
9
 
4.1%
Other values (5) 21
9.5%
Hangul
ValueCountFrequency (%)
번 9
22.5%
국 9
22.5%
이 9
22.5%
없 9
22.5%
경 1
 
2.5%
찰 1
 
2.5%
야 1
 
2.5%
간 1
 
2.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size684.0 B
Minimum2022-09-16 00:00:00
Maximum2022-09-16 00:00:00
2023-12-12T08:17:36.773238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:17:36.876041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T08:17:36.958538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분기관명팩스번호전화번호비고(추가전화번호)
구분1.0000.9460.0000.9740.970
기관명0.9461.0001.0000.9971.000
팩스번호0.0001.0001.0001.0001.000
전화번호0.9740.9971.0001.0001.000
비고(추가전화번호)0.9701.0001.0001.0001.000

Missing values

2023-12-12T08:17:33.565426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:17:33.674843image/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.
2023-12-12T08:17:33.798435image/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

구분기관명팩스번호전화번호비고(추가전화번호)데이터기준일자
0가정폭력&쉼터YWCA가정상담센터062-672-1356062-672-1355<NA>2022-09-16
1가정폭력&쉼터광주여성의전화 가정폭력상담소062-363-0486062-363-0442062-363-04432022-09-16
2가정폭력&쉼터광주여성의전화 가정폭력보호시설<NA><NA><NA>2022-09-16
3가정폭력&쉼터광주장애인 가정상담소/새날062-654-0424062-654-0420<NA>2022-09-16
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