Overview

Dataset statistics

Number of variables7
Number of observations335
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.1 KiB
Average record size in memory58.4 B

Variable types

Numeric2
Text2
Boolean1
DateTime2

Dataset

Description포항시 스마트포항앱에 나와있는 생활정보데이터(주제, 키워드,분류번호, 공개여부,등록일시)에 대한 데이터를 제공합니다
URLhttps://www.data.go.kr/data/15120844/fileData.do

Alerts

생활정보번호 is highly overall correlated with 공개여부High correlation
분류번호 is highly overall correlated with 공개여부High correlation
공개여부 is highly overall correlated with 생활정보번호 and 1 other fieldsHigh correlation
생활정보번호 has unique valuesUnique
주제 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:44:15.325818
Analysis finished2023-12-12 20:44:16.502598
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

생활정보번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct335
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean209.93433
Minimum1
Maximum417
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T05:44:16.597512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile23.4
Q1109.5
median210
Q3312.5
95-th percentile394.9
Maximum417
Range416
Interquartile range (IQR)203

Descriptive statistics

Standard deviation118.76055
Coefficient of variation (CV)0.56570332
Kurtosis-1.1546258
Mean209.93433
Median Absolute Deviation (MAD)102
Skewness-0.020096299
Sum70328
Variance14104.068
MonotonicityStrictly increasing
2023-12-13T05:44:16.778675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
278 1
 
0.3%
290 1
 
0.3%
289 1
 
0.3%
288 1
 
0.3%
286 1
 
0.3%
285 1
 
0.3%
284 1
 
0.3%
282 1
 
0.3%
280 1
 
0.3%
Other values (325) 325
97.0%
ValueCountFrequency (%)
1 1
0.3%
3 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
9 1
0.3%
10 1
0.3%
11 1
0.3%
12 1
0.3%
14 1
0.3%
ValueCountFrequency (%)
417 1
0.3%
416 1
0.3%
415 1
0.3%
414 1
0.3%
413 1
0.3%
412 1
0.3%
411 1
0.3%
409 1
0.3%
408 1
0.3%
406 1
0.3%

주제
Text

UNIQUE 

Distinct335
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T05:44:17.125809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length58
Median length32
Mean length14.898507
Min length4

Characters and Unicode

Total characters4991
Distinct characters429
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique335 ?
Unique (%)100.0%

Sample

1st row당직근무자 준수사항
2nd row비상근무발령시 근무체계
3rd row행정전화 녹취방법
4th row당직근무요령
5th row알리미 문자서비스 사용법
ValueCountFrequency (%)
및 40
 
3.7%
안내 25
 
2.3%
발급 19
 
1.8%
포항시 18
 
1.7%
변경 13
 
1.2%
자동차 12
 
1.1%
운영 11
 
1.0%
신고 10
 
0.9%
지원 10
 
0.9%
등록 9
 
0.8%
Other values (777) 901
84.4%
2023-12-13T05:44:17.706860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
733
 
14.7%
+ 95
 
1.9%
) 78
 
1.6%
( 78
 
1.6%
업 64
 
1.3%
인 62
 
1.2%
시 61
 
1.2%
지 60
 
1.2%
자 59
 
1.2%
동 58
 
1.2%
Other values (419) 3643
73.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3901
78.2%
Space Separator 733
 
14.7%
Math Symbol 97
 
1.9%
Close Punctuation 81
 
1.6%
Open Punctuation 81
 
1.6%
Decimal Number 45
 
0.9%
Uppercase Letter 22
 
0.4%
Other Punctuation 16
 
0.3%
Lowercase Letter 8
 
0.2%
Connector Punctuation 3
 
0.1%
Other values (2) 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 64
 
1.6%
인 62
 
1.6%
시 61
 
1.6%
지 60
 
1.5%
자 59
 
1.5%
동 58
 
1.5%
안 56
 
1.4%
기 56
 
1.4%
전 54
 
1.4%
장 54
 
1.4%
Other values (369) 3317
85.0%
Uppercase Letter
ValueCountFrequency (%)
S 6
27.3%
A 4
18.2%
N 1
 
4.5%
D 1
 
4.5%
I 1
 
4.5%
B 1
 
4.5%
F 1
 
4.5%
O 1
 
4.5%
R 1
 
4.5%
H 1
 
4.5%
Other values (4) 4
18.2%
Decimal Number
ValueCountFrequency (%)
1 12
26.7%
0 7
15.6%
2 7
15.6%
8 5
11.1%
9 5
11.1%
3 3
 
6.7%
5 3
 
6.7%
7 2
 
4.4%
4 1
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
f 1
12.5%
o 1
12.5%
r 1
12.5%
a 1
12.5%
i 1
12.5%
l 1
12.5%
c 1
12.5%
p 1
12.5%
Other Punctuation
ValueCountFrequency (%)
/ 5
31.2%
. 4
25.0%
! 2
 
12.5%
? 2
 
12.5%
· 1
 
6.2%
& 1
 
6.2%
: 1
 
6.2%
Close Punctuation
ValueCountFrequency (%)
) 78
96.3%
』 2
 
2.5%
] 1
 
1.2%
Open Punctuation
ValueCountFrequency (%)
( 78
96.3%
『 2
 
2.5%
[ 1
 
1.2%
Math Symbol
ValueCountFrequency (%)
+ 95
97.9%
~ 2
 
2.1%
Space Separator
ValueCountFrequency (%)
733
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Symbol
ValueCountFrequency (%)
★ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3901
78.2%
Common 1060
 
21.2%
Latin 30
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 64
 
1.6%
인 62
 
1.6%
시 61
 
1.6%
지 60
 
1.5%
자 59
 
1.5%
동 58
 
1.5%
안 56
 
1.4%
기 56
 
1.4%
전 54
 
1.4%
장 54
 
1.4%
Other values (369) 3317
85.0%
Common
ValueCountFrequency (%)
733
69.2%
+ 95
 
9.0%
) 78
 
7.4%
( 78
 
7.4%
1 12
 
1.1%
0 7
 
0.7%
2 7
 
0.7%
/ 5
 
0.5%
8 5
 
0.5%
9 5
 
0.5%
Other values (18) 35
 
3.3%
Latin
ValueCountFrequency (%)
S 6
20.0%
A 4
 
13.3%
f 1
 
3.3%
o 1
 
3.3%
r 1
 
3.3%
a 1
 
3.3%
i 1
 
3.3%
l 1
 
3.3%
N 1
 
3.3%
D 1
 
3.3%
Other values (12) 12
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3901
78.2%
ASCII 1084
 
21.7%
None 5
 
0.1%
Misc Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
733
67.6%
+ 95
 
8.8%
) 78
 
7.2%
( 78
 
7.2%
1 12
 
1.1%
0 7
 
0.6%
2 7
 
0.6%
S 6
 
0.6%
/ 5
 
0.5%
8 5
 
0.5%
Other values (36) 58
 
5.4%
Hangul
ValueCountFrequency (%)
업 64
 
1.6%
인 62
 
1.6%
시 61
 
1.6%
지 60
 
1.5%
자 59
 
1.5%
동 58
 
1.5%
안 56
 
1.4%
기 56
 
1.4%
전 54
 
1.4%
장 54
 
1.4%
Other values (369) 3317
85.0%
None
ValueCountFrequency (%)
』 2
40.0%
『 2
40.0%
· 1
20.0%
Misc Symbols
ValueCountFrequency (%)
★ 1
100.0%

키워드
Text

Distinct331
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T05:44:18.133908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length30
Mean length10.343284
Min length2

Characters and Unicode

Total characters3465
Distinct characters373
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique327 ?
Unique (%)97.6%

Sample

1st row준수사항
2nd row비상근무
3rd row녹취
4th row당직근무+ 요령
5th row알리미+ 문자
ValueCountFrequency (%)
자동차 12
 
1.6%
등록 9
 
1.2%
장애인 7
 
0.9%
변경 7
 
0.9%
발급 7
 
0.9%
지원 5
 
0.7%
음식물쓰레기 5
 
0.7%
신고 5
 
0.7%
종량제봉투 4
 
0.5%
부동산 3
 
0.4%
Other values (595) 700
91.6%
2023-12-13T05:44:18.763369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
429
 
12.4%
+ 372
 
10.7%
동 58
 
1.7%
장 49
 
1.4%
기 48
 
1.4%
자 47
 
1.4%
물 44
 
1.3%
지 42
 
1.2%
수 42
 
1.2%
전 41
 
1.2%
Other values (363) 2293
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2587
74.7%
Space Separator 429
 
12.4%
Math Symbol 372
 
10.7%
Other Punctuation 40
 
1.2%
Lowercase Letter 15
 
0.4%
Decimal Number 12
 
0.3%
Uppercase Letter 7
 
0.2%
Dash Punctuation 2
 
0.1%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 58
 
2.2%
장 49
 
1.9%
기 48
 
1.9%
자 47
 
1.8%
물 44
 
1.7%
지 42
 
1.6%
수 42
 
1.6%
전 41
 
1.6%
차 40
 
1.5%
인 36
 
1.4%
Other values (337) 2140
82.7%
Lowercase Letter
ValueCountFrequency (%)
l 3
20.0%
i 2
13.3%
a 2
13.3%
r 2
13.3%
o 2
13.3%
f 2
13.3%
g 1
 
6.7%
p 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 3
25.0%
1 2
16.7%
8 2
16.7%
4 2
16.7%
5 1
 
8.3%
6 1
 
8.3%
3 1
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
S 2
28.6%
H 1
14.3%
O 1
14.3%
X 1
14.3%
K 1
14.3%
T 1
14.3%
Space Separator
ValueCountFrequency (%)
429
100.0%
Math Symbol
ValueCountFrequency (%)
+ 372
100.0%
Other Punctuation
ValueCountFrequency (%)
. 40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2587
74.7%
Common 856
 
24.7%
Latin 22
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 58
 
2.2%
장 49
 
1.9%
기 48
 
1.9%
자 47
 
1.8%
물 44
 
1.7%
지 42
 
1.6%
수 42
 
1.6%
전 41
 
1.6%
차 40
 
1.5%
인 36
 
1.4%
Other values (337) 2140
82.7%
Latin
ValueCountFrequency (%)
l 3
13.6%
S 2
9.1%
i 2
9.1%
a 2
9.1%
r 2
9.1%
o 2
9.1%
f 2
9.1%
H 1
 
4.5%
g 1
 
4.5%
p 1
 
4.5%
Other values (4) 4
18.2%
Common
ValueCountFrequency (%)
429
50.1%
+ 372
43.5%
. 40
 
4.7%
2 3
 
0.4%
1 2
 
0.2%
- 2
 
0.2%
8 2
 
0.2%
4 2
 
0.2%
5 1
 
0.1%
6 1
 
0.1%
Other values (2) 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2587
74.7%
ASCII 878
 
25.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
429
48.9%
+ 372
42.4%
. 40
 
4.6%
l 3
 
0.3%
2 3
 
0.3%
S 2
 
0.2%
1 2
 
0.2%
- 2
 
0.2%
8 2
 
0.2%
4 2
 
0.2%
Other values (16) 21
 
2.4%
Hangul
ValueCountFrequency (%)
동 58
 
2.2%
장 49
 
1.9%
기 48
 
1.9%
자 47
 
1.8%
물 44
 
1.7%
지 42
 
1.6%
수 42
 
1.6%
전 41
 
1.6%
차 40
 
1.5%
인 36
 
1.4%
Other values (337) 2140
82.7%

분류번호
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.39403
Minimum1
Maximum123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2023-12-13T05:44:18.929543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.7
Q17
median8
Q38
95-th percentile109
Maximum123
Range122
Interquartile range (IQR)1

Descriptive statistics

Standard deviation36.117158
Coefficient of variation (CV)1.6881886
Kurtosis2.4643479
Mean21.39403
Median Absolute Deviation (MAD)1
Skewness2.0730655
Sum7167
Variance1304.4491
MonotonicityNot monotonic
2023-12-13T05:44:19.096365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
8 159
47.5%
7 57
 
17.0%
3 33
 
9.9%
109 25
 
7.5%
1 17
 
5.1%
123 13
 
3.9%
86 11
 
3.3%
5 8
 
2.4%
6 7
 
2.1%
10 2
 
0.6%
Other values (2) 3
 
0.9%
ValueCountFrequency (%)
1 17
 
5.1%
2 2
 
0.6%
3 33
 
9.9%
4 1
 
0.3%
5 8
 
2.4%
6 7
 
2.1%
7 57
 
17.0%
8 159
47.5%
10 2
 
0.6%
86 11
 
3.3%
ValueCountFrequency (%)
123 13
 
3.9%
109 25
 
7.5%
86 11
 
3.3%
10 2
 
0.6%
8 159
47.5%
7 57
 
17.0%
6 7
 
2.1%
5 8
 
2.4%
4 1
 
0.3%
3 33
 
9.9%

공개여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size467.0 B
True
280 
False
55 
ValueCountFrequency (%)
True 280
83.6%
False 55
 
16.4%
2023-12-13T05:44:19.249077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

등록일시
Date

Distinct134
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
Minimum2017-10-25 00:00:00
Maximum2019-12-24 00:00:00
2023-12-13T05:44:19.385658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:44:19.557352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최종변경일시
Date

Distinct139
Distinct (%)41.5%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
Minimum2017-10-25 00:00:00
Maximum2020-05-14 00:00:00
2023-12-13T05:44:19.747714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:44:19.920686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-13T05:44:16.094192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:44:15.857364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:44:16.200289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:44:15.975825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:44:20.018945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생활정보번호분류번호공개여부
생활정보번호1.0000.6200.781
분류번호0.6201.0000.825
공개여부0.7810.8251.000
2023-12-13T05:44:20.133257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생활정보번호분류번호공개여부
생활정보번호1.000-0.0610.609
분류번호-0.0611.0000.617
공개여부0.6090.6171.000

Missing values

2023-12-13T05:44:16.333471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:44:16.447100image/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

생활정보번호주제키워드분류번호공개여부등록일시최종변경일시
01당직근무자 준수사항준수사항86N2017-10-252017-10-25
13비상근무발령시 근무체계비상근무86N2017-10-252017-10-25
25행정전화 녹취방법녹취86N2017-10-252017-12-08
36당직근무요령당직근무+ 요령86N2017-10-252019-01-21
47알리미 문자서비스 사용법알리미+ 문자86N2017-10-252017-12-08
59(비공개)급수공사대행(주간)누수+ 급수공사5N2017-10-252020-05-14
610(비공개)급수공사대행(야간)급수공사+ 대행5N2017-10-252020-05-14
711버스분실물 습득문의버스+ 분실물습득4Y2017-10-252018-03-13
812동물민원처리유해동물+ 유기동물+ 사체처리. 천연기념물6N2017-10-252017-12-01
914법률상담무료+ 법률상담8Y2017-10-252020-05-14
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