Overview

Dataset statistics

Number of variables6
Number of observations77
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory49.7 B

Variable types

Text6

Dataset

Description2015년 2월 6일 안전신문고 개통 이후 접수된 2021년 6월 30일 까지의 대전지역 안전신문고 신고건수입니다.
Author대전광역시
URLhttps://www.data.go.kr/data/15077673/fileData.do

Alerts

(비교일자) 년월 has unique valuesUnique
(기준일자)년월 has unique valuesUnique
증감율 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:54:43.954514
Analysis finished2023-12-12 16:54:44.796406
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

(비교일자) 년월
Text

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-13T01:54:44.941376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters693
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)100.0%

Sample

1st row2015년 01월
2nd row2015년 02월
3rd row2015년 03월
4th row2015년 04월
5th row2015년 05월
ValueCountFrequency (%)
2015년 12
 
7.8%
2016년 12
 
7.8%
2018년 12
 
7.8%
2020년 12
 
7.8%
2019년 12
 
7.8%
2017년 12
 
7.8%
02월 7
 
4.5%
03월 7
 
4.5%
04월 7
 
4.5%
05월 7
 
4.5%
Other values (9) 54
35.1%
2023-12-13T01:54:45.284947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 154
22.2%
2 107
15.4%
1 96
13.9%
년 77
11.1%
77
11.1%
월 77
11.1%
5 19
 
2.7%
8 18
 
2.6%
6 18
 
2.6%
7 18
 
2.6%
Other values (3) 32
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 462
66.7%
Other Letter 154
 
22.2%
Space Separator 77
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 154
33.3%
2 107
23.2%
1 96
20.8%
5 19
 
4.1%
8 18
 
3.9%
6 18
 
3.9%
7 18
 
3.9%
9 18
 
3.9%
3 7
 
1.5%
4 7
 
1.5%
Other Letter
ValueCountFrequency (%)
년 77
50.0%
월 77
50.0%
Space Separator
ValueCountFrequency (%)
77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 539
77.8%
Hangul 154
 
22.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 154
28.6%
2 107
19.9%
1 96
17.8%
77
14.3%
5 19
 
3.5%
8 18
 
3.3%
6 18
 
3.3%
7 18
 
3.3%
9 18
 
3.3%
3 7
 
1.3%
Hangul
ValueCountFrequency (%)
년 77
50.0%
월 77
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 539
77.8%
Hangul 154
 
22.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 154
28.6%
2 107
19.9%
1 96
17.8%
77
14.3%
5 19
 
3.5%
8 18
 
3.3%
6 18
 
3.3%
7 18
 
3.3%
9 18
 
3.3%
3 7
 
1.3%
Hangul
ValueCountFrequency (%)
년 77
50.0%
월 77
50.0%

(비교일자)신고건수
Text

Distinct76
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-13T01:54:45.559531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.1298701
Min length2

Characters and Unicode

Total characters318
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

Unique75 ?
Unique (%)97.4%

Sample

1st row10
2nd row15
3rd row87
4th row151
5th row127
ValueCountFrequency (%)
421 2
 
2.6%
1,830 1
 
1.3%
2,547 1
 
1.3%
6,449 1
 
1.3%
5,858 1
 
1.3%
6,111 1
 
1.3%
4,765 1
 
1.3%
4,627 1
 
1.3%
4,388 1
 
1.3%
6,200 1
 
1.3%
Other values (66) 66
85.7%
2023-12-13T01:54:46.000454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 49
15.4%
, 42
13.2%
6 33
10.4%
5 33
10.4%
8 29
9.1%
4 28
8.8%
7 27
8.5%
2 25
7.9%
3 23
7.2%
0 17
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 276
86.8%
Other Punctuation 42
 
13.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 49
17.8%
6 33
12.0%
5 33
12.0%
8 29
10.5%
4 28
10.1%
7 27
9.8%
2 25
9.1%
3 23
8.3%
0 17
 
6.2%
9 12
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 318
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 49
15.4%
, 42
13.2%
6 33
10.4%
5 33
10.4%
8 29
9.1%
4 28
8.8%
7 27
8.5%
2 25
7.9%
3 23
7.2%
0 17
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 49
15.4%
, 42
13.2%
6 33
10.4%
5 33
10.4%
8 29
9.1%
4 28
8.8%
7 27
8.5%
2 25
7.9%
3 23
7.2%
0 17
 
5.3%

(기준일자)년월
Text

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-13T01:54:46.211024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters693
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)100.0%

Sample

1st row2015년 02월
2nd row2015년 03월
3rd row2015년 04월
4th row2015년 05월
5th row2015년 06월
ValueCountFrequency (%)
2018년 12
 
7.8%
2020년 12
 
7.8%
2019년 12
 
7.8%
2017년 12
 
7.8%
2016년 12
 
7.8%
2015년 11
 
7.1%
03월 7
 
4.5%
04월 7
 
4.5%
05월 7
 
4.5%
06월 7
 
4.5%
Other values (9) 55
35.7%
2023-12-13T01:54:46.607866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 154
22.2%
2 108
15.6%
1 95
13.7%
년 77
11.1%
77
11.1%
월 77
11.1%
6 19
 
2.7%
5 18
 
2.6%
8 18
 
2.6%
7 18
 
2.6%
Other values (3) 32
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 462
66.7%
Other Letter 154
 
22.2%
Space Separator 77
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 154
33.3%
2 108
23.4%
1 95
20.6%
6 19
 
4.1%
5 18
 
3.9%
8 18
 
3.9%
7 18
 
3.9%
9 18
 
3.9%
3 7
 
1.5%
4 7
 
1.5%
Other Letter
ValueCountFrequency (%)
년 77
50.0%
월 77
50.0%
Space Separator
ValueCountFrequency (%)
77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 539
77.8%
Hangul 154
 
22.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 154
28.6%
2 108
20.0%
1 95
17.6%
77
14.3%
6 19
 
3.5%
5 18
 
3.3%
8 18
 
3.3%
7 18
 
3.3%
9 18
 
3.3%
3 7
 
1.3%
Hangul
ValueCountFrequency (%)
년 77
50.0%
월 77
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 539
77.8%
Hangul 154
 
22.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 154
28.6%
2 108
20.0%
1 95
17.6%
77
14.3%
6 19
 
3.5%
5 18
 
3.3%
8 18
 
3.3%
7 18
 
3.3%
9 18
 
3.3%
3 7
 
1.3%
Hangul
ValueCountFrequency (%)
년 77
50.0%
월 77
50.0%

(기준일자)신고건수
Text

Distinct76
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-13T01:54:46.958972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.1818182
Min length2

Characters and Unicode

Total characters322
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

Unique75 ?
Unique (%)97.4%

Sample

1st row15
2nd row87
3rd row151
4th row127
5th row117
ValueCountFrequency (%)
421 2
 
2.6%
2,547 1
 
1.3%
4,388 1
 
1.3%
6,965 1
 
1.3%
6,449 1
 
1.3%
5,858 1
 
1.3%
6,111 1
 
1.3%
4,765 1
 
1.3%
4,627 1
 
1.3%
6,036 1
 
1.3%
Other values (66) 66
85.7%
2023-12-13T01:54:47.492461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 49
15.2%
, 43
13.4%
5 34
10.6%
6 33
10.2%
8 30
9.3%
4 28
8.7%
7 27
8.4%
2 26
8.1%
3 23
7.1%
0 16
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 279
86.6%
Other Punctuation 43
 
13.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 49
17.6%
5 34
12.2%
6 33
11.8%
8 30
10.8%
4 28
10.0%
7 27
9.7%
2 26
9.3%
3 23
8.2%
0 16
 
5.7%
9 13
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 43
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 322
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 49
15.2%
, 43
13.4%
5 34
10.6%
6 33
10.2%
8 30
9.3%
4 28
8.7%
7 27
8.4%
2 26
8.1%
3 23
7.1%
0 16
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 322
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 49
15.2%
, 43
13.4%
5 34
10.6%
6 33
10.2%
8 30
9.3%
4 28
8.7%
7 27
8.4%
2 26
8.1%
3 23
7.1%
0 16
 
5.0%

증감건수
Text

Distinct70
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-13T01:54:47.766092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.1688312
Min length1

Characters and Unicode

Total characters244
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)83.1%

Sample

1st row5
2nd row72
3rd row64
4th row-24
5th row-10
ValueCountFrequency (%)
37 3
 
3.9%
900 2
 
2.6%
54 2
 
2.6%
125 2
 
2.6%
253 2
 
2.6%
33 2
 
2.6%
6 2
 
2.6%
10 2
 
2.6%
82 1
 
1.3%
136 1
 
1.3%
Other values (58) 58
75.3%
2023-12-13T01:54:48.212452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 31
12.7%
1 27
11.1%
3 25
10.2%
2 25
10.2%
5 22
9.0%
6 22
9.0%
8 20
8.2%
7 18
7.4%
9 16
6.6%
0 16
6.6%
Other values (2) 22
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 205
84.0%
Dash Punctuation 31
 
12.7%
Other Punctuation 8
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 27
13.2%
3 25
12.2%
2 25
12.2%
5 22
10.7%
6 22
10.7%
8 20
9.8%
7 18
8.8%
9 16
7.8%
0 16
7.8%
4 14
6.8%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 244
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 31
12.7%
1 27
11.1%
3 25
10.2%
2 25
10.2%
5 22
9.0%
6 22
9.0%
8 20
8.2%
7 18
7.4%
9 16
6.6%
0 16
6.6%
Other values (2) 22
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 244
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 31
12.7%
1 27
11.1%
3 25
10.2%
2 25
10.2%
5 22
9.0%
6 22
9.0%
8 20
8.2%
7 18
7.4%
9 16
6.6%
0 16
6.6%
Other values (2) 22
9.0%

증감율
Text

UNIQUE 

Distinct77
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-13T01:54:48.543817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.038961
Min length5

Characters and Unicode

Total characters465
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)100.0%

Sample

1st row50.00%
2nd row480.00%
3rd row73.56%
4th row-15.89%
5th row-7.87%
ValueCountFrequency (%)
50.00 1
 
1.3%
12.56 1
 
1.3%
8.00 1
 
1.3%
10.09 1
 
1.3%
4.14 1
 
1.3%
28.25 1
 
1.3%
2.98 1
 
1.3%
5.45 1
 
1.3%
72.28 1
 
1.3%
0.33 1
 
1.3%
Other values (67) 67
87.0%
2023-12-13T01:54:49.023723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 77
16.6%
% 77
16.6%
1 44
9.5%
2 33
7.1%
4 32
6.9%
- 31
6.7%
0 30
 
6.5%
3 27
 
5.8%
5 26
 
5.6%
8 24
 
5.2%
Other values (3) 64
13.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 280
60.2%
Other Punctuation 154
33.1%
Dash Punctuation 31
 
6.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 44
15.7%
2 33
11.8%
4 32
11.4%
0 30
10.7%
3 27
9.6%
5 26
9.3%
8 24
8.6%
6 23
8.2%
9 23
8.2%
7 18
6.4%
Other Punctuation
ValueCountFrequency (%)
. 77
50.0%
% 77
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 465
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 77
16.6%
% 77
16.6%
1 44
9.5%
2 33
7.1%
4 32
6.9%
- 31
6.7%
0 30
 
6.5%
3 27
 
5.8%
5 26
 
5.6%
8 24
 
5.2%
Other values (3) 64
13.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 465
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 77
16.6%
% 77
16.6%
1 44
9.5%
2 33
7.1%
4 32
6.9%
- 31
6.7%
0 30
 
6.5%
3 27
 
5.8%
5 26
 
5.6%
8 24
 
5.2%
Other values (3) 64
13.8%

Correlations

2023-12-13T01:54:49.149936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
(비교일자) 년월(비교일자)신고건수(기준일자)년월(기준일자)신고건수증감건수증감율
(비교일자) 년월1.0001.0001.0001.0001.0001.000
(비교일자)신고건수1.0001.0001.0000.9990.9971.000
(기준일자)년월1.0001.0001.0001.0001.0001.000
(기준일자)신고건수1.0000.9991.0001.0000.9941.000
증감건수1.0000.9971.0000.9941.0001.000
증감율1.0001.0001.0001.0001.0001.000

Missing values

2023-12-13T01:54:44.614599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:54:44.744623image/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

(비교일자) 년월(비교일자)신고건수(기준일자)년월(기준일자)신고건수증감건수증감율
02015년 01월102015년 02월15550.00%
12015년 02월152015년 03월8772480.00%
22015년 03월872015년 04월1516473.56%
32015년 04월1512015년 05월127-24-15.89%
42015년 05월1272015년 06월117-10-7.87%
52015년 06월1172015년 07월88-29-24.79%
62015년 07월882015년 08월1183034.09%
72015년 08월1182015년 09월442324274.58%
82015년 09월4422015년 10월66822651.13%
92015년 10월6682015년 11월1,05338557.63%
(비교일자) 년월(비교일자)신고건수(기준일자)년월(기준일자)신고건수증감건수증감율
672020년 08월6,9292020년 09월6,359-570-8.23%
682020년 09월6,3592020년 10월7,34798815.54%
692020년 10월7,3472020년 11월13,3686,02181.95%
702020년 11월13,3682020년 12월16,2302,86221.41%
712020년 12월16,2302021년 01월18,1161,88611.62%
722021년 01월18,1162021년 02월17,561-555-3.06%
732021년 02월17,5612021년 03월22,2124,65126.48%
742021년 03월22,2122021년 04월21,929-283-1.27%
752021년 04월21,9292021년 05월23,7751,8468.42%
762021년 05월23,7752021년 06월25,8912,1168.90%