Overview

Dataset statistics

Number of variables4
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory410.2 KiB
Average record size in memory42.0 B

Variable types

Text2
Numeric1
Categorical1

Dataset

Description한국노인인력개발원에서 운영하는 노인일자리 중에서 대한노인회의 모집 기본 정보(사업번호, 사업명 등) 등을 제공하는 데이터 입니다.
Author한국노인인력개발원
URLhttps://www.data.go.kr/data/15050144/fileData.do

Alerts

사업연도 has constant value ""Constant
사업번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:45:00.502181
Analysis finished2023-12-12 02:45:01.551052
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:45:01.852213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters100000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row2022-06155
2nd row2022-07059
3rd row2022-00813
4th row2022-02833
5th row2022-08740
ValueCountFrequency (%)
2022-06155 1
 
< 0.1%
2022-11390 1
 
< 0.1%
2022-10349 1
 
< 0.1%
2022-10018 1
 
< 0.1%
2022-08484 1
 
< 0.1%
2022-07633 1
 
< 0.1%
2022-07651 1
 
< 0.1%
2022-07119 1
 
< 0.1%
2022-01248 1
 
< 0.1%
2022-04260 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-12T11:45:02.359653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 33944
33.9%
0 23086
23.1%
- 10000
 
10.0%
1 5618
 
5.6%
5 3998
 
4.0%
3 3993
 
4.0%
4 3971
 
4.0%
7 3915
 
3.9%
6 3870
 
3.9%
8 3844
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90000
90.0%
Dash Punctuation 10000
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 33944
37.7%
0 23086
25.7%
1 5618
 
6.2%
5 3998
 
4.4%
3 3993
 
4.4%
4 3971
 
4.4%
7 3915
 
4.3%
6 3870
 
4.3%
8 3844
 
4.3%
9 3761
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 100000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 33944
33.9%
0 23086
23.1%
- 10000
 
10.0%
1 5618
 
5.6%
5 3998
 
4.0%
3 3993
 
4.0%
4 3971
 
4.0%
7 3915
 
3.9%
6 3870
 
3.9%
8 3844
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 33944
33.9%
0 23086
23.1%
- 10000
 
10.0%
1 5618
 
5.6%
5 3998
 
4.0%
3 3993
 
4.0%
4 3971
 
4.0%
7 3915
 
3.9%
6 3870
 
3.9%
8 3844
 
3.8%

사업계획서변경순번
Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2287
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T11:45:02.509371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum13
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4309441
Coefficient of variation (CV)0.64205327
Kurtosis4.2172924
Mean2.2287
Median Absolute Deviation (MAD)1
Skewness1.7546611
Sum22287
Variance2.0476011
MonotonicityNot monotonic
2023-12-12T11:45:02.645457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 3725
37.2%
2 3197
32.0%
3 1578
15.8%
4 754
 
7.5%
5 388
 
3.9%
6 177
 
1.8%
7 95
 
0.9%
8 46
 
0.5%
9 23
 
0.2%
10 13
 
0.1%
Other values (2) 4
 
< 0.1%
ValueCountFrequency (%)
1 3725
37.2%
2 3197
32.0%
3 1578
15.8%
4 754
 
7.5%
5 388
 
3.9%
6 177
 
1.8%
7 95
 
0.9%
8 46
 
0.5%
9 23
 
0.2%
10 13
 
0.1%
ValueCountFrequency (%)
13 1
 
< 0.1%
11 3
 
< 0.1%
10 13
 
0.1%
9 23
 
0.2%
8 46
 
0.5%
7 95
 
0.9%
6 177
 
1.8%
5 388
 
3.9%
4 754
7.5%
3 1578
15.8%

사업연도
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 10000
100.0%

Length

2023-12-12T11:45:02.801088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:45:02.917335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 10000
100.0%

사업명
Text

Distinct7802
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T11:45:03.227427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length9.5204
Min length2

Characters and Unicode

Total characters95204
Distinct characters873
Distinct categories17 ?
Distinct scripts4 ?
Distinct blocks9 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7175 ?
Unique (%)71.8%

Sample

1st row복지시설봉사
2nd row지역아동센터지원사업
3rd row말벗친구(주안동)
4th row아이사랑도우미
5th row경로당 깔끄미-(평해읍)
ValueCountFrequency (%)
노노케어 275
 
1.9%
및 197
 
1.4%
시니어 180
 
1.2%
사업 137
 
1.0%
경로당 126
 
0.9%
지원 125
 
0.9%
도우미 116
 
0.8%
사업단 86
 
0.6%
지원사업 70
 
0.5%
봉사 70
 
0.5%
Other values (8002) 13029
90.4%
2023-12-12T11:45:04.024329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4538
 
4.8%
사 4364
 
4.6%
지 4276
 
4.5%
업 2889
 
3.0%
시 2689
 
2.8%
원 2296
 
2.4%
이 1894
 
2.0%
도 1765
 
1.9%
설 1685
 
1.8%
노 1671
 
1.8%
Other values (863) 67137
70.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 85923
90.3%
Space Separator 4538
 
4.8%
Close Punctuation 1276
 
1.3%
Open Punctuation 1274
 
1.3%
Decimal Number 967
 
1.0%
Other Punctuation 370
 
0.4%
Uppercase Letter 355
 
0.4%
Dash Punctuation 226
 
0.2%
Lowercase Letter 178
 
0.2%
Letter Number 33
 
< 0.1%
Other values (7) 64
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 4364
 
5.1%
지 4276
 
5.0%
업 2889
 
3.4%
시 2689
 
3.1%
원 2296
 
2.7%
이 1894
 
2.2%
도 1765
 
2.1%
설 1685
 
2.0%
노 1671
 
1.9%
공 1652
 
1.9%
Other values (771) 60742
70.7%
Uppercase Letter
ValueCountFrequency (%)
E 45
12.7%
C 43
12.1%
M 39
11.0%
S 34
9.6%
T 23
 
6.5%
O 22
 
6.2%
G 21
 
5.9%
K 19
 
5.4%
A 18
 
5.1%
I 11
 
3.1%
Other values (14) 80
22.5%
Lowercase Letter
ValueCountFrequency (%)
e 44
24.7%
a 26
14.6%
f 20
11.2%
i 10
 
5.6%
r 10
 
5.6%
c 9
 
5.1%
o 9
 
5.1%
m 7
 
3.9%
n 7
 
3.9%
l 6
 
3.4%
Other values (12) 30
16.9%
Other Punctuation
ValueCountFrequency (%)
' 106
28.6%
, 87
23.5%
" 66
17.8%
. 33
 
8.9%
& 24
 
6.5%
! 17
 
4.6%
· 14
 
3.8%
: 13
 
3.5%
# 7
 
1.9%
/ 2
 
0.5%
Decimal Number
ValueCountFrequency (%)
2 299
30.9%
1 187
19.3%
0 129
13.3%
9 74
 
7.7%
8 69
 
7.1%
3 67
 
6.9%
6 52
 
5.4%
5 46
 
4.8%
7 22
 
2.3%
4 22
 
2.3%
Letter Number
ValueCountFrequency (%)
Ⅱ 19
57.6%
Ⅰ 12
36.4%
Ⅳ 1
 
3.0%
Ⅲ 1
 
3.0%
Math Symbol
ValueCountFrequency (%)
+ 5
55.6%
~ 2
 
22.2%
> 1
 
11.1%
< 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 1257
98.5%
] 17
 
1.3%
〕 2
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 1255
98.5%
[ 17
 
1.3%
〔 2
 
0.2%
Initial Punctuation
ValueCountFrequency (%)
‘ 12
75.0%
“ 4
 
25.0%
Final Punctuation
ValueCountFrequency (%)
’ 12
75.0%
” 4
 
25.0%
Other Number
ValueCountFrequency (%)
② 2
50.0%
① 2
50.0%
Space Separator
ValueCountFrequency (%)
4538
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 226
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 17
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 85863
90.2%
Common 8715
 
9.2%
Latin 566
 
0.6%
Han 60
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 4364
 
5.1%
지 4276
 
5.0%
업 2889
 
3.4%
시 2689
 
3.1%
원 2296
 
2.7%
이 1894
 
2.2%
도 1765
 
2.1%
설 1685
 
2.0%
노 1671
 
1.9%
공 1652
 
1.9%
Other values (755) 60682
70.7%
Latin
ValueCountFrequency (%)
E 45
 
8.0%
e 44
 
7.8%
C 43
 
7.6%
M 39
 
6.9%
S 34
 
6.0%
a 26
 
4.6%
T 23
 
4.1%
O 22
 
3.9%
G 21
 
3.7%
f 20
 
3.5%
Other values (40) 249
44.0%
Common
ValueCountFrequency (%)
4538
52.1%
) 1257
 
14.4%
( 1255
 
14.4%
2 299
 
3.4%
- 226
 
2.6%
1 187
 
2.1%
0 129
 
1.5%
' 106
 
1.2%
, 87
 
1.0%
9 74
 
0.8%
Other values (32) 557
 
6.4%
Han
ValueCountFrequency (%)
愛 28
46.7%
老 11
 
18.3%
老 3
 
5.0%
水 2
 
3.3%
美 2
 
3.3%
家 2
 
3.3%
樂 2
 
3.3%
通 2
 
3.3%
犬 1
 
1.7%
心 1
 
1.7%
Other values (6) 6
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 85863
90.2%
ASCII 9193
 
9.7%
CJK 47
 
< 0.1%
Number Forms 33
 
< 0.1%
Punctuation 32
 
< 0.1%
None 18
 
< 0.1%
CJK Compat Ideographs 13
 
< 0.1%
Enclosed Alphanum 4
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4538
49.4%
) 1257
 
13.7%
( 1255
 
13.7%
2 299
 
3.3%
- 226
 
2.5%
1 187
 
2.0%
0 129
 
1.4%
' 106
 
1.2%
, 87
 
0.9%
9 74
 
0.8%
Other values (68) 1035
 
11.3%
Hangul
ValueCountFrequency (%)
사 4364
 
5.1%
지 4276
 
5.0%
업 2889
 
3.4%
시 2689
 
3.1%
원 2296
 
2.7%
이 1894
 
2.2%
도 1765
 
2.1%
설 1685
 
2.0%
노 1671
 
1.9%
공 1652
 
1.9%
Other values (755) 60682
70.7%
CJK
ValueCountFrequency (%)
愛 28
59.6%
老 3
 
6.4%
水 2
 
4.3%
美 2
 
4.3%
家 2
 
4.3%
通 2
 
4.3%
犬 1
 
2.1%
心 1
 
2.1%
多 1
 
2.1%
溫 1
 
2.1%
Other values (4) 4
 
8.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 19
57.6%
Ⅰ 12
36.4%
Ⅳ 1
 
3.0%
Ⅲ 1
 
3.0%
None
ValueCountFrequency (%)
· 14
77.8%
〕 2
 
11.1%
〔 2
 
11.1%
Punctuation
ValueCountFrequency (%)
‘ 12
37.5%
’ 12
37.5%
“ 4
 
12.5%
” 4
 
12.5%
CJK Compat Ideographs
ValueCountFrequency (%)
老 11
84.6%
樂 2
 
15.4%
Enclosed Alphanum
ValueCountFrequency (%)
② 2
50.0%
① 2
50.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%

Interactions

2023-12-12T11:45:01.239158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T11:45:01.383372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:45:01.501430image/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

사업번호사업계획서변경순번사업연도사업명
46562022-0615532022복지시설봉사
39512022-0705942022지역아동센터지원사업
97192022-0081312022말벗친구(주안동)
87742022-0283332022아이사랑도우미
15122022-0874022022경로당 깔끄미-(평해읍)
41882022-0840612022우체국지원관리
44962022-0508312022독거노인돌보미
55522022-0523512022정류장 환경가꿈이
97052022-0116612022플러스카페 종로구청점
55442022-0579012022야외운동기구관리지원
사업번호사업계획서변경순번사업연도사업명
10512022-0871822022노노케어
63092022-0358122022노노케어(노노보둠이파견사업)
89612022-0286812022소래어시장계도
65082022-0196822022지하철안전지킴이
28412022-1032632022경로당코디봉사단
91092022-0417832022노노케어
39082022-0608722022희망날개(보육)
92932022-0143912022스쿨존 교통지원 봉사(노란발자국 쌍문동)
60702022-0355422022행복소반
17432022-1049922022노-노케어 "친구야 놀자"