Overview

Dataset statistics

Number of variables9
Number of observations259
Missing cells258
Missing cells (%)11.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.6 KiB
Average record size in memory73.5 B

Variable types

Numeric1
Categorical3
Text5

Dataset

Description인천시 관내 (예비)사회적기업의 기업명, 대표자, 사회적목적유형, 업종, 서비스유형(사업내용), 관할 구, 주소 등의 정보를 제공합니다.
Author인천광역시
URLhttps://www.incheon.go.kr/data/DATA010201/view?docId=15078032

Alerts

Unnamed: 8 has constant value ""Constant
연번 is highly overall correlated with 구분 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 연번High correlation
군구 is highly overall correlated with 연번High correlation
Unnamed: 8 has 258 (99.6%) missing valuesMissing
연번 has unique valuesUnique
기업명 has unique valuesUnique

Reproduction

Analysis started2024-01-28 05:04:35.037579
Analysis finished2024-01-28 05:04:35.981102
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct259
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean130
Minimum1
Maximum259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2024-01-28T14:04:36.099245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.9
Q165.5
median130
Q3194.5
95-th percentile246.1
Maximum259
Range258
Interquartile range (IQR)129

Descriptive statistics

Standard deviation74.911058
Coefficient of variation (CV)0.57623891
Kurtosis-1.2
Mean130
Median Absolute Deviation (MAD)65
Skewness0
Sum33670
Variance5611.6667
MonotonicityStrictly increasing
2024-01-28T14:04:36.263940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
164 1
 
0.4%
166 1
 
0.4%
167 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
172 1
 
0.4%
173 1
 
0.4%
Other values (249) 249
96.1%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
259 1
0.4%
258 1
0.4%
257 1
0.4%
256 1
0.4%
255 1
0.4%
254 1
0.4%
253 1
0.4%
252 1
0.4%
251 1
0.4%
250 1
0.4%

구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
인증
190 
예비(지역형)
41 
예비(부처형)
23 
예비(지역형)+예비(부처형)
 
5

Length

Max length15
Median length2
Mean length3.4864865
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인증 190
73.4%
예비(지역형) 41
 
15.8%
예비(부처형) 23
 
8.9%
예비(지역형)+예비(부처형) 5
 
1.9%

Length

2024-01-28T14:04:36.386867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:04:36.478878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인증 190
73.4%
예비(지역형 41
 
15.8%
예비(부처형 23
 
8.9%
예비(지역형)+예비(부처형 5
 
1.9%

기업명
Text

UNIQUE 

Distinct259
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-01-28T14:04:36.654897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length16
Mean length7.4671815
Min length3

Characters and Unicode

Total characters1934
Distinct characters360
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique259 ?
Unique (%)100.0%

Sample

1st row㈜정부물품재활용
2nd row㈜두손테크
3rd row㈜인천개항
4th row㈜해피크린
5th row사회적협동조합엠커뮤니티
ValueCountFrequency (%)
사회적협동조합 8
 
2.6%
협동조합 7
 
2.3%
농업회사법인 5
 
1.6%
㈜ 3
 
1.0%
사회복지법인 2
 
0.6%
손과손 2
 
0.6%
사단법인 2
 
0.6%
㈜다사랑 2
 
0.6%
㈜더원아트코리아 1
 
0.3%
㈜파이코 1
 
0.3%
Other values (275) 275
89.3%
2024-01-28T14:04:36.972322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 204
 
10.5%
59
 
3.1%
사 54
 
2.8%
인 43
 
2.2%
이 42
 
2.2%
스 40
 
2.1%
합 40
 
2.1%
협 38
 
2.0%
동 37
 
1.9%
조 37
 
1.9%
Other values (350) 1340
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1623
83.9%
Other Symbol 204
 
10.5%
Space Separator 59
 
3.1%
Uppercase Letter 21
 
1.1%
Close Punctuation 10
 
0.5%
Open Punctuation 10
 
0.5%
Lowercase Letter 4
 
0.2%
Other Punctuation 2
 
0.1%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 54
 
3.3%
인 43
 
2.6%
이 42
 
2.6%
스 40
 
2.5%
합 40
 
2.5%
협 38
 
2.3%
동 37
 
2.3%
조 37
 
2.3%
회 37
 
2.3%
아 25
 
1.5%
Other values (331) 1230
75.8%
Uppercase Letter
ValueCountFrequency (%)
E 3
14.3%
O 3
14.3%
I 3
14.3%
A 2
9.5%
P 2
9.5%
R 2
9.5%
T 2
9.5%
Z 1
 
4.8%
J 1
 
4.8%
L 1
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
c 2
50.0%
n 2
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 204
100.0%
Space Separator
ValueCountFrequency (%)
59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Decimal Number
ValueCountFrequency (%)
5 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1827
94.5%
Common 82
 
4.2%
Latin 25
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 204
 
11.2%
사 54
 
3.0%
인 43
 
2.4%
이 42
 
2.3%
스 40
 
2.2%
합 40
 
2.2%
협 38
 
2.1%
동 37
 
2.0%
조 37
 
2.0%
회 37
 
2.0%
Other values (332) 1255
68.7%
Latin
ValueCountFrequency (%)
E 3
12.0%
O 3
12.0%
I 3
12.0%
A 2
8.0%
P 2
8.0%
R 2
8.0%
c 2
8.0%
n 2
8.0%
T 2
8.0%
Z 1
 
4.0%
Other values (3) 3
12.0%
Common
ValueCountFrequency (%)
59
72.0%
) 10
 
12.2%
( 10
 
12.2%
. 2
 
2.4%
5 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1623
83.9%
None 204
 
10.5%
ASCII 107
 
5.5%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 204
100.0%
ASCII
ValueCountFrequency (%)
59
55.1%
) 10
 
9.3%
( 10
 
9.3%
E 3
 
2.8%
O 3
 
2.8%
I 3
 
2.8%
A 2
 
1.9%
P 2
 
1.9%
R 2
 
1.9%
. 2
 
1.9%
Other values (8) 11
 
10.3%
Hangul
ValueCountFrequency (%)
사 54
 
3.3%
인 43
 
2.6%
이 42
 
2.6%
스 40
 
2.5%
합 40
 
2.5%
협 38
 
2.3%
동 37
 
2.3%
조 37
 
2.3%
회 37
 
2.3%
아 25
 
1.5%
Other values (331) 1230
75.8%

대표자
Text

Distinct257
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-01-28T14:04:37.219397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length3
Mean length3.3320463
Min length2

Characters and Unicode

Total characters863
Distinct characters160
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

Unique255 ?
Unique (%)98.5%

Sample

1st row윤성구
2nd row지금련,오상준
3rd row장미진
4th row방미호
5th row이명선
ValueCountFrequency (%)
이기선 2
 
0.7%
장영순 2
 
0.7%
허정문 1
 
0.4%
윤혜숙 1
 
0.4%
장슬아 1
 
0.4%
김태신 1
 
0.4%
장선영 1
 
0.4%
윤성구 1
 
0.4%
양경애 1
 
0.4%
호윤기 1
 
0.4%
Other values (259) 259
95.6%
2024-01-28T14:04:37.563767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 65
 
7.5%
이 37
 
4.3%
정 29
 
3.4%
영 28
 
3.2%
경 18
 
2.1%
박 16
 
1.9%
호 16
 
1.9%
수 16
 
1.9%
, 16
 
1.9%
은 15
 
1.7%
Other values (150) 607
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 833
96.5%
Other Punctuation 17
 
2.0%
Space Separator 13
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 65
 
7.8%
이 37
 
4.4%
정 29
 
3.5%
영 28
 
3.4%
경 18
 
2.2%
박 16
 
1.9%
호 16
 
1.9%
수 16
 
1.9%
은 15
 
1.8%
성 15
 
1.8%
Other values (147) 578
69.4%
Other Punctuation
ValueCountFrequency (%)
, 16
94.1%
. 1
 
5.9%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 833
96.5%
Common 30
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 65
 
7.8%
이 37
 
4.4%
정 29
 
3.5%
영 28
 
3.4%
경 18
 
2.2%
박 16
 
1.9%
호 16
 
1.9%
수 16
 
1.9%
은 15
 
1.8%
성 15
 
1.8%
Other values (147) 578
69.4%
Common
ValueCountFrequency (%)
, 16
53.3%
13
43.3%
. 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 833
96.5%
ASCII 30
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 65
 
7.8%
이 37
 
4.4%
정 29
 
3.5%
영 28
 
3.4%
경 18
 
2.2%
박 16
 
1.9%
호 16
 
1.9%
수 16
 
1.9%
은 15
 
1.8%
성 15
 
1.8%
Other values (147) 578
69.4%
ASCII
ValueCountFrequency (%)
, 16
53.3%
13
43.3%
. 1
 
3.3%

업종
Categorical

Distinct14
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
제조
59 
교육
37 
기타
29 
문화예술
28 
청소
22 
Other values (9)
84 

Length

Max length4
Median length2
Mean length2.4247104
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row재활용
2nd row청소
3rd row식품
4th row청소
5th row교육

Common Values

ValueCountFrequency (%)
제조 59
22.8%
교육 37
14.3%
기타 29
11.2%
문화예술 28
10.8%
청소 22
 
8.5%
식품 20
 
7.7%
도소매 19
 
7.3%
간병가사 12
 
4.6%
건설 9
 
3.5%
IT 8
 
3.1%
Other values (4) 16
 
6.2%

Length

2024-01-28T14:04:37.687879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제조 59
22.8%
교육 37
14.3%
기타 29
11.2%
문화예술 28
10.8%
청소 22
 
8.5%
식품 20
 
7.7%
도소매 19
 
7.3%
간병가사 12
 
4.6%
건설 9
 
3.5%
it 8
 
3.1%
Other values (4) 16
 
6.2%

서비스유형
Text

Distinct256
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-01-28T14:04:37.922673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length111
Median length43
Mean length17.602317
Min length3

Characters and Unicode

Total characters4559
Distinct characters397
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique253 ?
Unique (%)97.7%

Sample

1st row공공기관물품재활용, 사무용가구 등
2nd row건물위생관리, 경비, 방역 등
3rd row카페, 관광기념품, 체험
4th row청소, 소독, 인테리어
5th row복지 서비스
ValueCountFrequency (%)
및 81
 
7.7%
등 32
 
3.0%
제조 24
 
2.3%
판매 23
 
2.2%
교육 22
 
2.1%
도소매 14
 
1.3%
운영 12
 
1.1%
서비스 11
 
1.0%
제작 10
 
0.9%
소독 8
 
0.8%
Other values (635) 817
77.5%
2024-01-28T14:04:38.284945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
811
 
17.8%
, 252
 
5.5%
제 98
 
2.1%
및 81
 
1.8%
매 67
 
1.5%
교 66
 
1.4%
조 63
 
1.4%
판 62
 
1.4%
소 61
 
1.3%
스 61
 
1.3%
Other values (387) 2937
64.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3392
74.4%
Space Separator 811
 
17.8%
Other Punctuation 299
 
6.6%
Uppercase Letter 25
 
0.5%
Open Punctuation 13
 
0.3%
Close Punctuation 13
 
0.3%
Decimal Number 4
 
0.1%
Final Punctuation 1
 
< 0.1%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 98
 
2.9%
및 81
 
2.4%
매 67
 
2.0%
교 66
 
1.9%
조 63
 
1.9%
판 62
 
1.8%
소 61
 
1.8%
스 61
 
1.8%
공 57
 
1.7%
기 57
 
1.7%
Other values (360) 2719
80.2%
Uppercase Letter
ValueCountFrequency (%)
D 4
16.0%
E 4
16.0%
L 3
12.0%
R 2
8.0%
P 2
8.0%
T 2
8.0%
C 2
8.0%
J 1
 
4.0%
N 1
 
4.0%
I 1
 
4.0%
Other values (3) 3
12.0%
Other Punctuation
ValueCountFrequency (%)
, 252
84.3%
· 24
 
8.0%
/ 17
 
5.7%
& 4
 
1.3%
. 1
 
0.3%
: 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
4 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
811
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3392
74.4%
Common 1142
 
25.0%
Latin 25
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 98
 
2.9%
및 81
 
2.4%
매 67
 
2.0%
교 66
 
1.9%
조 63
 
1.9%
판 62
 
1.8%
소 61
 
1.8%
스 61
 
1.8%
공 57
 
1.7%
기 57
 
1.7%
Other values (360) 2719
80.2%
Common
ValueCountFrequency (%)
811
71.0%
, 252
 
22.1%
· 24
 
2.1%
/ 17
 
1.5%
( 13
 
1.1%
) 13
 
1.1%
& 4
 
0.4%
1 2
 
0.2%
4 1
 
0.1%
. 1
 
0.1%
Other values (4) 4
 
0.4%
Latin
ValueCountFrequency (%)
D 4
16.0%
E 4
16.0%
L 3
12.0%
R 2
8.0%
P 2
8.0%
T 2
8.0%
C 2
8.0%
J 1
 
4.0%
N 1
 
4.0%
I 1
 
4.0%
Other values (3) 3
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3392
74.4%
ASCII 1141
 
25.0%
None 24
 
0.5%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
811
71.1%
, 252
 
22.1%
/ 17
 
1.5%
( 13
 
1.1%
) 13
 
1.1%
& 4
 
0.4%
D 4
 
0.4%
E 4
 
0.4%
L 3
 
0.3%
R 2
 
0.2%
Other values (14) 18
 
1.6%
Hangul
ValueCountFrequency (%)
제 98
 
2.9%
및 81
 
2.4%
매 67
 
2.0%
교 66
 
1.9%
조 63
 
1.9%
판 62
 
1.8%
소 61
 
1.8%
스 61
 
1.8%
공 57
 
1.7%
기 57
 
1.7%
Other values (360) 2719
80.2%
None
ValueCountFrequency (%)
· 24
100.0%
Punctuation
ValueCountFrequency (%)
’ 1
50.0%
‘ 1
50.0%

군구
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
남동구
54 
미추홀구
45 
서구
39 
연수구
33 
부평구
22 
Other values (5)
66 

Length

Max length4
Median length3
Mean length2.9227799
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남동구 54
20.8%
미추홀구 45
17.4%
서구 39
15.1%
연수구 33
12.7%
부평구 22
8.5%
계양구 22
8.5%
중구 13
 
5.0%
동구 13
 
5.0%
강화군 11
 
4.2%
옹진군 7
 
2.7%

Length

2024-01-28T14:04:38.407785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:04:38.800475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남동구 54
20.8%
미추홀구 45
17.4%
서구 39
15.1%
연수구 33
12.7%
부평구 22
8.5%
계양구 22
8.5%
중구 13
 
5.0%
동구 13
 
5.0%
강화군 11
 
4.2%
옹진군 7
 
2.7%

주소(신주소)
Text

Distinct256
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-01-28T14:04:39.145829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length45
Mean length26.88417
Min length15

Characters and Unicode

Total characters6963
Distinct characters299
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique253 ?
Unique (%)97.7%

Sample

1st row인천광역시 중구 서해대로 324
2nd row인천광역시 중구 서해대로 483번길 68번지
3rd row인천광역시 중구 신포로23번길 83, 202호(중앙동1가)
4th row인천광역시 중구 개항로53번길 13
5th row인천광역시 중구 율목로 54, 2층
ValueCountFrequency (%)
인천광역시 259
 
19.3%
남동구 55
 
4.1%
미추홀구 45
 
3.4%
서구 39
 
2.9%
연수구 33
 
2.5%
부평구 22
 
1.6%
계양구 22
 
1.6%
1층 19
 
1.4%
2층 14
 
1.0%
동구 13
 
1.0%
Other values (583) 821
61.2%
2024-01-28T14:04:39.600183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1096
 
15.7%
인 291
 
4.2%
천 275
 
3.9%
1 265
 
3.8%
시 263
 
3.8%
역 261
 
3.7%
광 260
 
3.7%
로 258
 
3.7%
구 258
 
3.7%
2 189
 
2.7%
Other values (289) 3547
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4179
60.0%
Decimal Number 1301
 
18.7%
Space Separator 1096
 
15.7%
Other Punctuation 166
 
2.4%
Close Punctuation 70
 
1.0%
Open Punctuation 69
 
1.0%
Dash Punctuation 54
 
0.8%
Uppercase Letter 24
 
0.3%
Lowercase Letter 2
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 291
 
7.0%
천 275
 
6.6%
시 263
 
6.3%
역 261
 
6.2%
광 260
 
6.2%
로 258
 
6.2%
구 258
 
6.2%
동 189
 
4.5%
길 108
 
2.6%
번 102
 
2.4%
Other values (257) 1914
45.8%
Uppercase Letter
ValueCountFrequency (%)
B 5
20.8%
C 5
20.8%
E 3
12.5%
A 2
 
8.3%
T 2
 
8.3%
I 2
 
8.3%
V 1
 
4.2%
N 1
 
4.2%
R 1
 
4.2%
L 1
 
4.2%
Decimal Number
ValueCountFrequency (%)
1 265
20.4%
2 189
14.5%
0 158
12.1%
3 148
11.4%
5 116
8.9%
4 110
8.5%
6 88
 
6.8%
8 81
 
6.2%
7 74
 
5.7%
9 72
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 164
98.8%
@ 1
 
0.6%
. 1
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
o 1
50.0%
e 1
50.0%
Math Symbol
ValueCountFrequency (%)
~ 1
50.0%
～ 1
50.0%
Space Separator
ValueCountFrequency (%)
1096
100.0%
Close Punctuation
ValueCountFrequency (%)
) 70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4179
60.0%
Common 2758
39.6%
Latin 26
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 291
 
7.0%
천 275
 
6.6%
시 263
 
6.3%
역 261
 
6.2%
광 260
 
6.2%
로 258
 
6.2%
구 258
 
6.2%
동 189
 
4.5%
길 108
 
2.6%
번 102
 
2.4%
Other values (257) 1914
45.8%
Common
ValueCountFrequency (%)
1096
39.7%
1 265
 
9.6%
2 189
 
6.9%
, 164
 
5.9%
0 158
 
5.7%
3 148
 
5.4%
5 116
 
4.2%
4 110
 
4.0%
6 88
 
3.2%
8 81
 
2.9%
Other values (9) 343
 
12.4%
Latin
ValueCountFrequency (%)
B 5
19.2%
C 5
19.2%
E 3
11.5%
A 2
 
7.7%
T 2
 
7.7%
I 2
 
7.7%
V 1
 
3.8%
o 1
 
3.8%
N 1
 
3.8%
R 1
 
3.8%
Other values (3) 3
11.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4179
60.0%
ASCII 2783
40.0%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1096
39.4%
1 265
 
9.5%
2 189
 
6.8%
, 164
 
5.9%
0 158
 
5.7%
3 148
 
5.3%
5 116
 
4.2%
4 110
 
4.0%
6 88
 
3.2%
8 81
 
2.9%
Other values (21) 368
 
13.2%
Hangul
ValueCountFrequency (%)
인 291
 
7.0%
천 275
 
6.6%
시 263
 
6.3%
역 261
 
6.2%
광 260
 
6.2%
로 258
 
6.2%
구 258
 
6.2%
동 189
 
4.5%
길 108
 
2.6%
번 102
 
2.4%
Other values (257) 1914
45.8%
None
ValueCountFrequency (%)
～ 1
100.0%

Unnamed: 8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing258
Missing (%)99.6%
Memory size2.2 KiB
2024-01-28T14:04:39.748140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length21
Mean length21
Min length21

Characters and Unicode

Total characters21
Distinct characters17
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row통지일:7.12(6.29일자소재지변경)
ValueCountFrequency (%)
통지일:7.12(6.29일자소재지변경 1
100.0%
2024-01-28T14:04:39.989672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
일 2
 
9.5%
. 2
 
9.5%
2 2
 
9.5%
지 2
 
9.5%
통 1
 
4.8%
자 1
 
4.8%
경 1
 
4.8%
변 1
 
4.8%
재 1
 
4.8%
소 1
 
4.8%
Other values (7) 7
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
47.6%
Decimal Number 6
28.6%
Other Punctuation 3
 
14.3%
Open Punctuation 1
 
4.8%
Close Punctuation 1
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 2
20.0%
지 2
20.0%
통 1
10.0%
자 1
10.0%
경 1
10.0%
변 1
10.0%
재 1
10.0%
소 1
10.0%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
9 1
16.7%
6 1
16.7%
1 1
16.7%
7 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
: 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11
52.4%
Hangul 10
47.6%

Most frequent character per script

Common
ValueCountFrequency (%)
. 2
18.2%
2 2
18.2%
( 1
9.1%
9 1
9.1%
6 1
9.1%
1 1
9.1%
7 1
9.1%
: 1
9.1%
) 1
9.1%
Hangul
ValueCountFrequency (%)
일 2
20.0%
지 2
20.0%
통 1
10.0%
자 1
10.0%
경 1
10.0%
변 1
10.0%
재 1
10.0%
소 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
52.4%
Hangul 10
47.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
일 2
20.0%
지 2
20.0%
통 1
10.0%
자 1
10.0%
경 1
10.0%
변 1
10.0%
재 1
10.0%
소 1
10.0%
ASCII
ValueCountFrequency (%)
. 2
18.2%
2 2
18.2%
( 1
9.1%
9 1
9.1%
6 1
9.1%
1 1
9.1%
7 1
9.1%
: 1
9.1%
) 1
9.1%

Interactions

2024-01-28T14:04:35.738111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T14:04:40.061918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분업종군구
연번1.0000.8940.2100.947
구분0.8941.0000.1340.119
업종0.2100.1341.0000.344
군구0.9470.1190.3441.000
2024-01-28T14:04:40.139231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종군구구분
업종1.0000.1440.073
군구0.1441.0000.070
구분0.0730.0701.000
2024-01-28T14:04:40.207231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분업종군구
연번1.0000.7610.0840.614
구분0.7611.0000.0730.070
업종0.0840.0731.0000.144
군구0.6140.0700.1441.000

Missing values

2024-01-28T14:04:35.830492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T14:04:35.937095image/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

연번구분기업명대표자업종서비스유형군구주소(신주소)Unnamed: 8
01인증㈜정부물품재활용윤성구재활용공공기관물품재활용, 사무용가구 등중구인천광역시 중구 서해대로 324<NA>
12인증㈜두손테크지금련,오상준청소건물위생관리, 경비, 방역 등중구인천광역시 중구 서해대로 483번길 68번지<NA>
23인증㈜인천개항장미진식품카페, 관광기념품, 체험중구인천광역시 중구 신포로23번길 83, 202호(중앙동1가)<NA>
34인증㈜해피크린방미호청소청소, 소독, 인테리어중구인천광역시 중구 개항로53번길 13<NA>
45인증사회적협동조합엠커뮤니티이명선교육복지 서비스중구인천광역시 중구 율목로 54, 2층<NA>
56인증㈜차이나브이중국어마을조경순교육중국문화체험, 중국진로체험중구인천광역시 중구 신포로23번길 80, 202~204호<NA>
67인증㈜한사랑 식판선생님지정호기타어린이집, 유치원 식판세척 소독배달업중구인천광역시 중구 도산로 17<NA>
78인증㈜풍성인더스호민재제조태양광발전장치, 전기공사, 금속창호 및 시설물공사, 경관조명설치중구인천광역시 중구 차이나타운로 27(북성동3가)<NA>
89인증㈜행복을 나누는 도시락김연자식품도시락, 출장부페동구인천광역시 동구 화수로 74-1<NA>
910인증㈜청소사랑김순옥청소건물위생관리, 경비, 방역 등동구인천광역시 동구 화도진로34번길 7<NA>
연번구분기업명대표자업종서비스유형군구주소(신주소)Unnamed: 8
249250예비(부처형)㈜허니랩김동은제조친환경 식품 포장랩 등 생산남동구인천광역시 남동구 남동대로 350, 에이동 1층 일부<NA>
250251예비(부처형)㈜청솔기획김택환.배정현문화예술예술, 스포츠 및 여가관련 서비스업, 공연기획 및 이벤트남동구인천광역시 남동구 복개동로66번길 34-1, 1층<NA>
251252예비(부처형)두손식품윤진제조식품 제조 판매남동구인천광역시 남동구 장승남로81번길 27<NA>
252253예비(부처형)㈜한밥안선화기타영유아 식단 정보를 무료 제공하고, 해당 이유식 및 반찬을 제조남동구인천광역시 남동구 앵고개로 928, 3층 E-107호<NA>
253254예비(부처형)㈜코워킹소사이어티한가늠기타스마트역량진단 앱개발, 전문 경영컨설팅서구인천광역시 서구 보듬로 158, 221호<NA>
254255예비(부처형)정약용컴퍼니㈜박보민청소영유아 가정과 대가족 세대를 위한 가사 청소관리 서비스 제공 및 생활용품 소매업서구인천광역시 서구 염곡로464번길 15 쓰리엠타워8층 입주사무실7호<NA>
255256예비(부처형)위즈덤랩㈜허정문기타가족 고객을 대상으로 교육, 체험, 돌봄, 상담 등을 위한 전문가를 연결하는 재능 공유 플랫폼을 제작 운영서구인천광역시 서구 염곡로464번길 15 8층, 인천서구사회적경제마을지원센터 입주기업사무실6<NA>
256257예비(부처형)㈜애드밸구혜은교육난독증·다문화 어린이들의 읽기 개선을 위한 도서 출판, 콘텐츠 제작서구인천광역시 서구 염곡로464번길 15 801호<NA>
257258예비(부처형)㈜더하트컴퍼니박대은기타저출산 문제 완화를 위한아기 엄마 대상의 커뮤니티 및 교육, 워크숍, 공간사업서구인천광역시 서구 보듬로 158, 미플존 221호(오류동, 블루텍)<NA>
258259예비(부처형)㈜파밀리앤장혜영제조향초 및 공예관련제품, 전자상거래, 향초공예관련교육서구인천광역시 서구 염곡로464번길 15, 8층 809호 내 코워킹룸 8(가정동, 서구사회적경제마을지원센터)통지일:7.12(6.29일자소재지변경)