Overview

Dataset statistics

Number of variables9
Number of observations954
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory68.1 KiB
Average record size in memory73.1 B

Variable types

Numeric1
Categorical3
Text5

Dataset

Description2인 이상의 수급자 또는 저소득층이 상호 협력하여, 조합 또는 공동사업자의 형태로 탈빈곤을 위한 자활사업을 운영하는 업체- 국민기초생활보장법 개정에 따라 2012년 8월 2일부터 "자활공동체"를 "자활기업"으로 명칭 변경- 시도, 시군구, 자활기업, 기업유형, 주소, 대표자, 업종, 사업자구분
Author한국자활복지개발원
URLhttps://www.data.go.kr/data/15091502/fileData.do

Alerts

순번 is highly overall correlated with 시도High correlation
시도 is highly overall correlated with 순번High correlation
기업유형 is highly imbalanced (80.8%)Imbalance
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-30 08:59:42.776969
Analysis finished2024-03-30 08:59:48.186861
Duration5.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct954
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean477.5
Minimum1
Maximum954
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-03-30T08:59:48.404194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile48.65
Q1239.25
median477.5
Q3715.75
95-th percentile906.35
Maximum954
Range953
Interquartile range (IQR)476.5

Descriptive statistics

Standard deviation275.54038
Coefficient of variation (CV)0.57704791
Kurtosis-1.2
Mean477.5
Median Absolute Deviation (MAD)238.5
Skewness0
Sum455535
Variance75922.5
MonotonicityStrictly increasing
2024-03-30T08:59:48.876280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
642 1
 
0.1%
630 1
 
0.1%
631 1
 
0.1%
632 1
 
0.1%
633 1
 
0.1%
634 1
 
0.1%
635 1
 
0.1%
636 1
 
0.1%
637 1
 
0.1%
Other values (944) 944
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
954 1
0.1%
953 1
0.1%
952 1
0.1%
951 1
0.1%
950 1
0.1%
949 1
0.1%
948 1
0.1%
947 1
0.1%
946 1
0.1%
945 1
0.1%

시도
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
경기도
173 
서울특별시
130 
전라북도
86 
전라남도
71 
경상북도
67 
Other values (12)
427 

Length

Max length7
Median length5
Mean length4.4046122
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 173
18.1%
서울특별시 130
13.6%
전라북도 86
9.0%
전라남도 71
7.4%
경상북도 67
 
7.0%
부산광역시 64
 
6.7%
경상남도 58
 
6.1%
강원특별자치도 47
 
4.9%
충청남도 45
 
4.7%
충청북도 41
 
4.3%
Other values (7) 172
18.0%

Length

2024-03-30T08:59:49.169712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 173
18.1%
서울특별시 130
13.6%
전라북도 86
9.0%
전라남도 71
7.4%
경상북도 67
 
7.0%
부산광역시 64
 
6.7%
경상남도 58
 
6.1%
강원특별자치도 47
 
4.9%
충청남도 45
 
4.7%
충청북도 41
 
4.3%
Other values (7) 172
18.0%

시군구
Text

Distinct209
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
2024-03-30T08:59:49.726216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length2.9412998
Min length2

Characters and Unicode

Total characters2806
Distinct characters130
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)3.6%

Sample

1st row강릉시
2nd row강릉시
3rd row강릉시
4th row강릉시
5th row고성군
ValueCountFrequency (%)
북구 25
 
2.6%
서구 22
 
2.3%
부천시 21
 
2.2%
동구 20
 
2.1%
강서구 17
 
1.8%
전주시 17
 
1.8%
중구 16
 
1.7%
구로구 15
 
1.6%
포항시 14
 
1.5%
노원구 14
 
1.5%
Other values (199) 773
81.0%
2024-03-30T08:59:50.782773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 428
 
15.3%
구 336
 
12.0%
군 195
 
6.9%
주 110
 
3.9%
천 83
 
3.0%
서 77
 
2.7%
산 74
 
2.6%
성 68
 
2.4%
남 66
 
2.4%
양 53
 
1.9%
Other values (120) 1316
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2806
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 428
 
15.3%
구 336
 
12.0%
군 195
 
6.9%
주 110
 
3.9%
천 83
 
3.0%
서 77
 
2.7%
산 74
 
2.6%
성 68
 
2.4%
남 66
 
2.4%
양 53
 
1.9%
Other values (120) 1316
46.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2806
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 428
 
15.3%
구 336
 
12.0%
군 195
 
6.9%
주 110
 
3.9%
천 83
 
3.0%
서 77
 
2.7%
산 74
 
2.6%
성 68
 
2.4%
남 66
 
2.4%
양 53
 
1.9%
Other values (120) 1316
46.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2806
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 428
 
15.3%
구 336
 
12.0%
군 195
 
6.9%
주 110
 
3.9%
천 83
 
3.0%
서 77
 
2.7%
산 74
 
2.6%
성 68
 
2.4%
남 66
 
2.4%
양 53
 
1.9%
Other values (120) 1316
46.9%

자활기업
Text

Distinct942
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
2024-03-30T08:59:51.501826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length7.9129979
Min length2

Characters and Unicode

Total characters7549
Distinct characters519
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

Unique932 ?
Unique (%)97.7%

Sample

1st row유한회사두레건축
2nd row유한회사따슴재가요양기관
3rd row주식회사 강릉희망유통
4th row행복농장
5th row협동조합 자연살림
ValueCountFrequency (%)
주식회사 95
 
8.0%
협동조합 34
 
2.9%
사회적협동조합 22
 
1.9%
유한회사 14
 
1.2%
씨유 5
 
0.4%
희망나르미 4
 
0.3%
gs25 3
 
0.3%
행복드림 3
 
0.3%
행복나르미 3
 
0.3%
나눔택배 3
 
0.3%
Other values (977) 997
84.3%
2024-03-30T08:59:53.926729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 322
 
4.3%
236
 
3.1%
사 235
 
3.1%
회 204
 
2.7%
) 200
 
2.6%
( 198
 
2.6%
동 192
 
2.5%
조 176
 
2.3%
합 174
 
2.3%
협 169
 
2.2%
Other values (509) 5443
72.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6734
89.2%
Space Separator 236
 
3.1%
Close Punctuation 200
 
2.6%
Open Punctuation 198
 
2.6%
Uppercase Letter 72
 
1.0%
Decimal Number 58
 
0.8%
Lowercase Letter 27
 
0.4%
Other Symbol 13
 
0.2%
Dash Punctuation 5
 
0.1%
Other Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 322
 
4.8%
사 235
 
3.5%
회 204
 
3.0%
동 192
 
2.9%
조 176
 
2.6%
합 174
 
2.6%
협 169
 
2.5%
식 129
 
1.9%
리 124
 
1.8%
나 116
 
1.7%
Other values (464) 4893
72.7%
Uppercase Letter
ValueCountFrequency (%)
S 19
26.4%
G 16
22.2%
H 5
 
6.9%
C 5
 
6.9%
U 5
 
6.9%
E 4
 
5.6%
L 4
 
5.6%
M 3
 
4.2%
O 2
 
2.8%
B 2
 
2.8%
Other values (5) 7
 
9.7%
Lowercase Letter
ValueCountFrequency (%)
o 6
22.2%
r 3
11.1%
n 3
11.1%
t 2
 
7.4%
e 2
 
7.4%
d 2
 
7.4%
a 2
 
7.4%
i 1
 
3.7%
u 1
 
3.7%
s 1
 
3.7%
Other values (4) 4
14.8%
Decimal Number
ValueCountFrequency (%)
2 26
44.8%
5 21
36.2%
4 3
 
5.2%
3 3
 
5.2%
1 2
 
3.4%
8 1
 
1.7%
9 1
 
1.7%
0 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
& 3
75.0%
, 1
 
25.0%
Space Separator
ValueCountFrequency (%)
236
100.0%
Close Punctuation
ValueCountFrequency (%)
) 200
100.0%
Open Punctuation
ValueCountFrequency (%)
( 198
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6747
89.4%
Common 703
 
9.3%
Latin 99
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 322
 
4.8%
사 235
 
3.5%
회 204
 
3.0%
동 192
 
2.8%
조 176
 
2.6%
합 174
 
2.6%
협 169
 
2.5%
식 129
 
1.9%
리 124
 
1.8%
나 116
 
1.7%
Other values (465) 4906
72.7%
Latin
ValueCountFrequency (%)
S 19
19.2%
G 16
16.2%
o 6
 
6.1%
H 5
 
5.1%
C 5
 
5.1%
U 5
 
5.1%
E 4
 
4.0%
L 4
 
4.0%
M 3
 
3.0%
r 3
 
3.0%
Other values (19) 29
29.3%
Common
ValueCountFrequency (%)
236
33.6%
) 200
28.4%
( 198
28.2%
2 26
 
3.7%
5 21
 
3.0%
- 5
 
0.7%
4 3
 
0.4%
& 3
 
0.4%
3 3
 
0.4%
1 2
 
0.3%
Other values (5) 6
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6734
89.2%
ASCII 802
 
10.6%
None 13
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 322
 
4.8%
사 235
 
3.5%
회 204
 
3.0%
동 192
 
2.9%
조 176
 
2.6%
합 174
 
2.6%
협 169
 
2.5%
식 129
 
1.9%
리 124
 
1.8%
나 116
 
1.7%
Other values (464) 4893
72.7%
ASCII
ValueCountFrequency (%)
236
29.4%
) 200
24.9%
( 198
24.7%
2 26
 
3.2%
5 21
 
2.6%
S 19
 
2.4%
G 16
 
2.0%
o 6
 
0.7%
H 5
 
0.6%
- 5
 
0.6%
Other values (34) 70
 
8.7%
None
ValueCountFrequency (%)
㈜ 13
100.0%

기업유형
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
지역
907 
광역
 
43
전국
 
4

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지역 907
95.1%
광역 43
 
4.5%
전국 4
 
0.4%

Length

2024-03-30T08:59:54.433163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-30T08:59:54.878312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지역 907
95.1%
광역 43
 
4.5%
전국 4
 
0.4%

주소
Text

Distinct938
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
2024-03-30T08:59:55.537591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length42
Mean length25.57652
Min length11

Characters and Unicode

Total characters24400
Distinct characters472
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique926 ?
Unique (%)97.1%

Sample

1st row강릉시경강로1804번길 63(홍제동)
2nd row강원특별자치도 강릉시 강릉대로 161 2층
3rd row강원도 강릉시 경강로2224번길 23 1층 2호(포남동)
4th row강원도 강릉시 성산면 지암길 139-7 1층
5th row강원도 고성군 간성읍 간성로 99-1 협동조합자연살림
ValueCountFrequency (%)
1층 248
 
4.8%
경기도 168
 
3.3%
서울특별시 118
 
2.3%
전라북도 85
 
1.7%
경상북도 62
 
1.2%
전라남도 60
 
1.2%
부산광역시 58
 
1.1%
2층 56
 
1.1%
경상남도 55
 
1.1%
충청남도 42
 
0.8%
Other values (2245) 4176
81.4%
2024-03-30T08:59:56.649735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4980
 
20.4%
1 1289
 
5.3%
로 793
 
3.2%
시 777
 
3.2%
2 641
 
2.6%
도 620
 
2.5%
구 551
 
2.3%
길 517
 
2.1%
3 470
 
1.9%
층 418
 
1.7%
Other values (462) 13344
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14305
58.6%
Space Separator 4980
 
20.4%
Decimal Number 4541
 
18.6%
Dash Punctuation 257
 
1.1%
Close Punctuation 116
 
0.5%
Open Punctuation 115
 
0.5%
Other Punctuation 50
 
0.2%
Uppercase Letter 27
 
0.1%
Math Symbol 5
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 793
 
5.5%
시 777
 
5.4%
도 620
 
4.3%
구 551
 
3.9%
길 517
 
3.6%
층 418
 
2.9%
동 363
 
2.5%
경 348
 
2.4%
남 317
 
2.2%
광 290
 
2.0%
Other values (429) 9311
65.1%
Decimal Number
ValueCountFrequency (%)
1 1289
28.4%
2 641
14.1%
3 470
 
10.4%
0 412
 
9.1%
4 360
 
7.9%
5 330
 
7.3%
6 310
 
6.8%
7 276
 
6.1%
8 228
 
5.0%
9 225
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 10
37.0%
A 4
 
14.8%
C 4
 
14.8%
G 2
 
7.4%
S 2
 
7.4%
U 1
 
3.7%
N 1
 
3.7%
J 1
 
3.7%
D 1
 
3.7%
F 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 40
80.0%
" 6
 
12.0%
. 3
 
6.0%
/ 1
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
k 1
25.0%
l 1
25.0%
s 1
25.0%
g 1
25.0%
Space Separator
ValueCountFrequency (%)
4980
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 257
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Open Punctuation
ValueCountFrequency (%)
( 115
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14305
58.6%
Common 10064
41.2%
Latin 31
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 793
 
5.5%
시 777
 
5.4%
도 620
 
4.3%
구 551
 
3.9%
길 517
 
3.6%
층 418
 
2.9%
동 363
 
2.5%
경 348
 
2.4%
남 317
 
2.2%
광 290
 
2.0%
Other values (429) 9311
65.1%
Common
ValueCountFrequency (%)
4980
49.5%
1 1289
 
12.8%
2 641
 
6.4%
3 470
 
4.7%
0 412
 
4.1%
4 360
 
3.6%
5 330
 
3.3%
6 310
 
3.1%
7 276
 
2.7%
- 257
 
2.6%
Other values (9) 739
 
7.3%
Latin
ValueCountFrequency (%)
B 10
32.3%
A 4
 
12.9%
C 4
 
12.9%
G 2
 
6.5%
S 2
 
6.5%
k 1
 
3.2%
l 1
 
3.2%
U 1
 
3.2%
N 1
 
3.2%
J 1
 
3.2%
Other values (4) 4
 
12.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14305
58.6%
ASCII 10095
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4980
49.3%
1 1289
 
12.8%
2 641
 
6.3%
3 470
 
4.7%
0 412
 
4.1%
4 360
 
3.6%
5 330
 
3.3%
6 310
 
3.1%
7 276
 
2.7%
- 257
 
2.5%
Other values (23) 770
 
7.6%
Hangul
ValueCountFrequency (%)
로 793
 
5.5%
시 777
 
5.4%
도 620
 
4.3%
구 551
 
3.9%
길 517
 
3.6%
층 418
 
2.9%
동 363
 
2.5%
경 348
 
2.4%
남 317
 
2.2%
광 290
 
2.0%
Other values (429) 9311
65.1%

대표자
Text

Distinct891
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
2024-03-30T08:59:57.301480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length3
Mean length3.3312369
Min length2

Characters and Unicode

Total characters3178
Distinct characters211
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique836 ?
Unique (%)87.6%

Sample

1st row배재국
2nd row이병기
3rd row최규식
4th row신완철
5th row박영복
ValueCountFrequency (%)
1명 22
 
2.2%
외 17
 
1.7%
2명 4
 
0.4%
이미숙 3
 
0.3%
김경희 3
 
0.3%
김현정 3
 
0.3%
김은숙 3
 
0.3%
최재혁 3
 
0.3%
김현미 3
 
0.3%
김인숙 3
 
0.3%
Other values (899) 950
93.7%
2024-03-30T08:59:58.426325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 231
 
7.3%
이 145
 
4.6%
정 105
 
3.3%
박 84
 
2.6%
영 82
 
2.6%
희 69
 
2.2%
명 69
 
2.2%
미 68
 
2.1%
67
 
2.1%
경 66
 
2.1%
Other values (201) 2192
69.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3023
95.1%
Space Separator 67
 
2.1%
Decimal Number 51
 
1.6%
Other Punctuation 22
 
0.7%
Uppercase Letter 15
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 231
 
7.6%
이 145
 
4.8%
정 105
 
3.5%
박 84
 
2.8%
영 82
 
2.7%
희 69
 
2.3%
명 69
 
2.3%
미 68
 
2.2%
경 66
 
2.2%
숙 60
 
2.0%
Other values (186) 2044
67.6%
Uppercase Letter
ValueCountFrequency (%)
I 3
20.0%
Y 2
13.3%
O 2
13.3%
A 2
13.3%
K 2
13.3%
M 1
 
6.7%
H 1
 
6.7%
S 1
 
6.7%
B 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 43
84.3%
2 7
 
13.7%
3 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 21
95.5%
. 1
 
4.5%
Space Separator
ValueCountFrequency (%)
67
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3023
95.1%
Common 140
 
4.4%
Latin 15
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 231
 
7.6%
이 145
 
4.8%
정 105
 
3.5%
박 84
 
2.8%
영 82
 
2.7%
희 69
 
2.3%
명 69
 
2.3%
미 68
 
2.2%
경 66
 
2.2%
숙 60
 
2.0%
Other values (186) 2044
67.6%
Latin
ValueCountFrequency (%)
I 3
20.0%
Y 2
13.3%
O 2
13.3%
A 2
13.3%
K 2
13.3%
M 1
 
6.7%
H 1
 
6.7%
S 1
 
6.7%
B 1
 
6.7%
Common
ValueCountFrequency (%)
67
47.9%
1 43
30.7%
, 21
 
15.0%
2 7
 
5.0%
. 1
 
0.7%
3 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3023
95.1%
ASCII 155
 
4.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 231
 
7.6%
이 145
 
4.8%
정 105
 
3.5%
박 84
 
2.8%
영 82
 
2.7%
희 69
 
2.3%
명 69
 
2.3%
미 68
 
2.2%
경 66
 
2.2%
숙 60
 
2.0%
Other values (186) 2044
67.6%
ASCII
ValueCountFrequency (%)
67
43.2%
1 43
27.7%
, 21
 
13.5%
2 7
 
4.5%
I 3
 
1.9%
Y 2
 
1.3%
O 2
 
1.3%
A 2
 
1.3%
K 2
 
1.3%
. 1
 
0.6%
Other values (5) 5
 
3.2%

업종
Text

Distinct86
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
2024-03-30T08:59:58.976675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length8.9685535
Min length3

Characters and Unicode

Total characters8556
Distinct characters186
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

Unique32 ?
Unique (%)3.4%

Sample

1st row집수리
2nd row사회서비스(장기요양)
3rd row배송ㆍ운전(양곡택배)
4th row축산물생산ㆍ가공(양계)
5th row유통ㆍ판매(슈퍼마켓)
ValueCountFrequency (%)
집수리 206
21.5%
배송ㆍ운전(양곡택배 113
 
11.8%
청소(학교 84
 
8.8%
유통ㆍ판매(편의점 61
 
6.4%
음식점(한식,일식,중식,기타외국음식 47
 
4.9%
청소(방역,소독,방제 35
 
3.7%
배송ㆍ운전(일반택배 32
 
3.3%
청소(일반건물 32
 
3.3%
음식점(일반시장-카페,찻집 31
 
3.2%
재활용ㆍ수선(기타 22
 
2.3%
Other values (78) 295
30.8%
2024-03-30T09:00:00.017910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 746
 
8.7%
) 746
 
8.7%
식 376
 
4.4%
, 324
 
3.8%
배 290
 
3.4%
ㆍ 281
 
3.3%
집 248
 
2.9%
수 242
 
2.8%
소 241
 
2.8%
리 207
 
2.4%
Other values (176) 4855
56.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6686
78.1%
Open Punctuation 746
 
8.7%
Close Punctuation 746
 
8.7%
Other Punctuation 326
 
3.8%
Dash Punctuation 45
 
0.5%
Space Separator 4
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 376
 
5.6%
배 290
 
4.3%
ㆍ 281
 
4.2%
집 248
 
3.7%
수 242
 
3.6%
소 241
 
3.6%
리 207
 
3.1%
청 205
 
3.1%
점 177
 
2.6%
음 166
 
2.5%
Other values (167) 4253
63.6%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
t 1
33.3%
a 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 324
99.4%
' 2
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 746
100.0%
Close Punctuation
ValueCountFrequency (%)
) 746
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6686
78.1%
Common 1867
 
21.8%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 376
 
5.6%
배 290
 
4.3%
ㆍ 281
 
4.2%
집 248
 
3.7%
수 242
 
3.6%
소 241
 
3.6%
리 207
 
3.1%
청 205
 
3.1%
점 177
 
2.6%
음 166
 
2.5%
Other values (167) 4253
63.6%
Common
ValueCountFrequency (%)
( 746
40.0%
) 746
40.0%
, 324
17.4%
- 45
 
2.4%
4
 
0.2%
' 2
 
0.1%
Latin
ValueCountFrequency (%)
e 1
33.3%
t 1
33.3%
a 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6405
74.9%
ASCII 1870
 
21.9%
Compat Jamo 281
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 746
39.9%
) 746
39.9%
, 324
17.3%
- 45
 
2.4%
4
 
0.2%
' 2
 
0.1%
e 1
 
0.1%
t 1
 
0.1%
a 1
 
0.1%
Hangul
ValueCountFrequency (%)
식 376
 
5.9%
배 290
 
4.5%
집 248
 
3.9%
수 242
 
3.8%
소 241
 
3.8%
리 207
 
3.2%
청 205
 
3.2%
점 177
 
2.8%
음 166
 
2.6%
전 152
 
2.4%
Other values (166) 4101
64.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 281
100.0%

사업자구분
Categorical

Distinct8
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
개인사업자
419 
법인사업자 - 주식회사
283 
협동조합(일반)
128 
법인사업자 - 유한회사
67 
협동조합(사회적)
53 
Other values (3)
 
4

Length

Max length14
Median length12
Mean length8.2222222
Min length5

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row법인사업자 - 유한회사
2nd row법인사업자 - 유한회사
3rd row법인사업자 - 주식회사
4th row개인사업자
5th row협동조합(일반)

Common Values

ValueCountFrequency (%)
개인사업자 419
43.9%
법인사업자 - 주식회사 283
29.7%
협동조합(일반) 128
 
13.4%
법인사업자 - 유한회사 67
 
7.0%
협동조합(사회적) 53
 
5.6%
법인사업자 - 비영리 2
 
0.2%
법인사업자 - 사단법인 1
 
0.1%
법인사업자 - 영농조합법인 1
 
0.1%

Length

2024-03-30T09:00:00.548301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-30T09:00:00.923731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인사업자 419
25.2%
법인사업자 354
21.3%
354
21.3%
주식회사 283
17.0%
협동조합(일반 128
 
7.7%
유한회사 67
 
4.0%
협동조합(사회적 53
 
3.2%
비영리 2
 
0.1%
사단법인 1
 
0.1%
영농조합법인 1
 
0.1%

Interactions

2024-03-30T08:59:47.250920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-30T09:00:01.274774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시도기업유형업종사업자구분
순번1.0000.9590.2050.3730.298
시도0.9591.0000.0000.4610.480
기업유형0.2050.0001.0000.7320.421
업종0.3730.4610.7321.0000.779
사업자구분0.2980.4800.4210.7791.000
2024-03-30T09:00:01.679856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기업유형시도사업자구분
기업유형1.0000.0000.295
시도0.0001.0000.223
사업자구분0.2950.2231.000
2024-03-30T09:00:01.925450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시도기업유형사업자구분
순번1.0000.8150.1240.147
시도0.8151.0000.0000.223
기업유형0.1240.0001.0000.295
사업자구분0.1470.2230.2951.000

Missing values

2024-03-30T08:59:47.624401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-30T08:59:48.016961image/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

순번시도시군구자활기업기업유형주소대표자업종사업자구분
01강원특별자치도강릉시유한회사두레건축지역강릉시경강로1804번길 63(홍제동)배재국집수리법인사업자 - 유한회사
12강원특별자치도강릉시유한회사따슴재가요양기관지역강원특별자치도 강릉시 강릉대로 161 2층이병기사회서비스(장기요양)법인사업자 - 유한회사
23강원특별자치도강릉시주식회사 강릉희망유통지역강원도 강릉시 경강로2224번길 23 1층 2호(포남동)최규식배송ㆍ운전(양곡택배)법인사업자 - 주식회사
34강원특별자치도강릉시행복농장지역강원도 강릉시 성산면 지암길 139-7 1층신완철축산물생산ㆍ가공(양계)개인사업자
45강원특별자치도고성군협동조합 자연살림지역강원도 고성군 간성읍 간성로 99-1 협동조합자연살림박영복유통ㆍ판매(슈퍼마켓)협동조합(일반)
56강원특별자치도강원강원주거복지사회적협동조합광역강원도 춘천시 후석로420번길 7 503호임형석집수리협동조합(일반)
67강원특별자치도동해시주식회사 행복유통지역강원특별자치도 동해시 일출로 10-1 비동 1층전두희배송ㆍ운전(양곡택배)법인사업자 - 주식회사
78강원특별자치도동해시희망건축지역강원도 동해시 동호4길 1최미란집수리개인사업자
89강원특별자치도동해시희망택배지역강원도 동해시 발한로 211 동해지역자활센터 2호윤철현외1배송ㆍ운전(일반택배)개인사업자
910강원특별자치도양양군환경자원센터지역강원도 양양군 양양읍 거마천로 463-54 00임무경외재활용ㆍ수선(기타)법인사업자 - 유한회사
순번시도시군구자활기업기업유형주소대표자업종사업자구분
944945충청북도청주시청주희망나르미협동조합지역충청북도 청주시 상당구 무농정로16번길 16-16김성구배송ㆍ운전(양곡택배)협동조합(일반)
945946충청북도청주시하나환경주식회사지역충청북도 청주시 상당구 중흥로31번길 12 1층한용희청소(방역,소독,방제)법인사업자 - 주식회사
946947충청북도충주시(주)성실기업지역충청북도 충주시 만리산로 34-1 104호이종성집수리법인사업자 - 주식회사
947948충청북도충주시(주)크린충주지역충청북도 충주시 천변로 179박정일청소(학교)법인사업자 - 주식회사
948949경기도경기도사회적협동조합 한국클린쿱전국경기도 수원시 장안구 파장천로 1-4 4층유보현청소(일반건물)협동조합(사회적)
949950전라북도전라북도한국주거복지사회적협동조합전국전라북도 전주시 완산구 천잠로 555 B동 3층곽병현집수리협동조합(사회적)
950951서울특별시서울특별시희망나르미사회적협동조합전국서울특별시 용산구 한강대로11길21(한강로3가, 명약국)심재옥유통ㆍ판매협동조합(사회적)
951952서울특별시서울특별시한국돌봄사회적협동조합전국서울특별시 용산구 한강대로11길21 3층정경록사회서비스협동조합(사회적)
952953대전광역시대전광역시클린매니저사회적협동조합광역대전광역시 유성구 동서대로5번길 21-5 1층김정일청소(준공,입주,이사)협동조합(사회적)
953954강원특별자치도강원에스에이치로직스협동조합광역강원특별자치도 동해시 일출로 10-1 B동 1층전두희배송ㆍ운전(양곡택배)협동조합(일반)