Overview

Dataset statistics

Number of variables4
Number of observations1299
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory40.7 KiB
Average record size in memory32.1 B

Variable types

Text2
Boolean2

Dataset

Description통계청에서 제공하는 통계정책관리시스템 통계작성기관에 대한 자료입니다. 일반인들도 쉽게 이해할수있는 통계자료를 쉽고 빠르고 정확하게 찾아보실수 있습니다.
Author통계청
URLhttps://www.data.go.kr/data/15040079/fileData.do

Alerts

사용여부 has constant value ""Constant
대표기관여부 is highly imbalanced (87.2%)Imbalance

Reproduction

Analysis started2023-12-12 09:29:18.514399
Analysis finished2023-12-12 09:29:19.115403
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계명
Text

Distinct1261
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
2023-12-12T18:29:19.348094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length21
Mean length9.482679
Min length3

Characters and Unicode

Total characters12318
Distinct characters391
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1240 ?
Unique (%)95.5%

Sample

1st row인구총조사
2nd row주택총조사
3rd row인구동향조사
4th row경제활동인구조사
5th row가계동향조사
ValueCountFrequency (%)
주민등록인구통계 16
 
1.2%
귀농어·귀촌인통계 3
 
0.2%
가계금융복지조사 3
 
0.2%
보험통계 3
 
0.2%
중소기업경기전망조사 2
 
0.2%
건강보험통계 2
 
0.2%
의료급여통계 2
 
0.2%
항공통계 2
 
0.2%
국내신규박사학위취득자조사 2
 
0.2%
방송산업실태조사 2
 
0.2%
Other values (1263) 1274
97.2%
2023-12-12T18:29:19.959615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 760
 
6.2%
계 593
 
4.8%
조 583
 
4.7%
통 581
 
4.7%
시 432
 
3.5%
기 415
 
3.4%
도 261
 
2.1%
본 249
 
2.0%
실 244
 
2.0%
산 237
 
1.9%
Other values (381) 7963
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12197
99.0%
Uppercase Letter 58
 
0.5%
Other Punctuation 22
 
0.2%
Space Separator 12
 
0.1%
Open Punctuation 11
 
0.1%
Close Punctuation 11
 
0.1%
Decimal Number 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 760
 
6.2%
계 593
 
4.9%
조 583
 
4.8%
통 581
 
4.8%
시 432
 
3.5%
기 415
 
3.4%
도 261
 
2.1%
본 249
 
2.0%
실 244
 
2.0%
산 237
 
1.9%
Other values (356) 7842
64.3%
Uppercase Letter
ValueCountFrequency (%)
I 13
22.4%
T 11
19.0%
C 9
15.5%
S 5
 
8.6%
A 3
 
5.2%
B 3
 
5.2%
M 3
 
5.2%
R 2
 
3.4%
O 2
 
3.4%
V 2
 
3.4%
Other values (5) 5
 
8.6%
Other Punctuation
ValueCountFrequency (%)
· 17
77.3%
/ 2
 
9.1%
. 2
 
9.1%
, 1
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 5
71.4%
2 1
 
14.3%
9 1
 
14.3%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12197
99.0%
Common 63
 
0.5%
Latin 58
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 760
 
6.2%
계 593
 
4.9%
조 583
 
4.8%
통 581
 
4.8%
시 432
 
3.5%
기 415
 
3.4%
도 261
 
2.1%
본 249
 
2.0%
실 244
 
2.0%
산 237
 
1.9%
Other values (356) 7842
64.3%
Latin
ValueCountFrequency (%)
I 13
22.4%
T 11
19.0%
C 9
15.5%
S 5
 
8.6%
A 3
 
5.2%
B 3
 
5.2%
M 3
 
5.2%
R 2
 
3.4%
O 2
 
3.4%
V 2
 
3.4%
Other values (5) 5
 
8.6%
Common
ValueCountFrequency (%)
· 17
27.0%
12
19.0%
( 11
17.5%
) 11
17.5%
1 5
 
7.9%
/ 2
 
3.2%
. 2
 
3.2%
, 1
 
1.6%
2 1
 
1.6%
9 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12197
99.0%
ASCII 104
 
0.8%
None 17
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 760
 
6.2%
계 593
 
4.9%
조 583
 
4.8%
통 581
 
4.8%
시 432
 
3.5%
기 415
 
3.4%
도 261
 
2.1%
본 249
 
2.0%
실 244
 
2.0%
산 237
 
1.9%
Other values (356) 7842
64.3%
None
ValueCountFrequency (%)
· 17
100.0%
ASCII
ValueCountFrequency (%)
I 13
12.5%
12
11.5%
( 11
10.6%
T 11
10.6%
) 11
10.6%
C 9
8.7%
1 5
 
4.8%
S 5
 
4.8%
A 3
 
2.9%
B 3
 
2.9%
Other values (14) 21
20.2%

작성기관
Text

Distinct401
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Memory size10.3 KiB
2023-12-12T18:29:20.480148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length6.4988453
Min length3

Characters and Unicode

Total characters8442
Distinct characters239
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique178 ?
Unique (%)13.7%

Sample

1st row통계청
2nd row통계청
3rd row통계청
4th row통계청
5th row통계청
ValueCountFrequency (%)
경기도 127
 
7.2%
통계청 67
 
3.8%
경상북도 65
 
3.7%
충청남도 61
 
3.4%
강원도 50
 
2.8%
서울특별시 46
 
2.6%
경상남도 44
 
2.5%
전라남도 43
 
2.4%
보건복지부 38
 
2.1%
과학기술정보통신부 36
 
2.0%
Other values (370) 1192
67.4%
2023-12-12T18:29:20.991084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 477
 
5.7%
470
 
5.6%
시 416
 
4.9%
부 351
 
4.2%
경 284
 
3.4%
청 224
 
2.7%
기 211
 
2.5%
국 207
 
2.5%
산 205
 
2.4%
원 188
 
2.2%
Other values (229) 5409
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7959
94.3%
Space Separator 470
 
5.6%
Close Punctuation 6
 
0.1%
Open Punctuation 6
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 477
 
6.0%
시 416
 
5.2%
부 351
 
4.4%
경 284
 
3.6%
청 224
 
2.8%
기 211
 
2.7%
국 207
 
2.6%
산 205
 
2.6%
원 188
 
2.4%
광 176
 
2.2%
Other values (225) 5220
65.6%
Space Separator
ValueCountFrequency (%)
470
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7959
94.3%
Common 483
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 477
 
6.0%
시 416
 
5.2%
부 351
 
4.4%
경 284
 
3.6%
청 224
 
2.8%
기 211
 
2.7%
국 207
 
2.6%
산 205
 
2.6%
원 188
 
2.4%
광 176
 
2.2%
Other values (225) 5220
65.6%
Common
ValueCountFrequency (%)
470
97.3%
) 6
 
1.2%
( 6
 
1.2%
· 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7959
94.3%
ASCII 482
 
5.7%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 477
 
6.0%
시 416
 
5.2%
부 351
 
4.4%
경 284
 
3.6%
청 224
 
2.8%
기 211
 
2.7%
국 207
 
2.6%
산 205
 
2.6%
원 188
 
2.4%
광 176
 
2.2%
Other values (225) 5220
65.6%
ASCII
ValueCountFrequency (%)
470
97.5%
) 6
 
1.2%
( 6
 
1.2%
None
ValueCountFrequency (%)
· 1
100.0%

사용여부
Boolean

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
True
1299 
ValueCountFrequency (%)
True 1299
100.0%
2023-12-12T18:29:21.120620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

대표기관여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
True
1276 
False
 
23
ValueCountFrequency (%)
True 1276
98.2%
False 23
 
1.8%
2023-12-12T18:29:21.200547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T18:29:18.929749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:29:19.061198image/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

통계명작성기관사용여부대표기관여부
0인구총조사통계청YY
1주택총조사통계청YY
2인구동향조사통계청YY
3경제활동인구조사통계청YY
4가계동향조사통계청YY
5소비자물가조사통계청YY
6광업제조업조사통계청YY
7광업제조업동향조사통계청YY
8통계인력및예산조사통계청YY
9건설업조사통계청YY
통계명작성기관사용여부대표기관여부
1289교육기관(고등교육기관및직업계고)졸업자취업통계통계청YN
1290가계금융복지조사통계청YY
1291가계금융복지조사한국은행YN
1292가계금융복지조사금융감독원YN
1293귀농어·귀촌인통계통계청YY
1294귀농어·귀촌인통계농림축산식품부YN
1295귀농어·귀촌인통계해양수산부YN
1296보험통계보험개발원YY
1297보험통계생명보험협회YN
1298보험통계손해보험협회YN