Overview

Dataset statistics

Number of variables8
Number of observations245
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.7 KiB
Average record size in memory65.5 B

Variable types

Numeric1
Categorical3
Text4

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

연번 is highly overall correlated with 구 분 and 1 other fieldsHigh correlation
구 분 is highly overall correlated with 연번High correlation
군구 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
기 업 명 has unique valuesUnique

Reproduction

Analysis started2024-01-28 05:04:41.103917
Analysis finished2024-01-28 05:04:41.959994
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct245
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean123
Minimum1
Maximum245
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-01-28T14:04:42.020872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.2
Q162
median123
Q3184
95-th percentile232.8
Maximum245
Range244
Interquartile range (IQR)122

Descriptive statistics

Standard deviation70.869599
Coefficient of variation (CV)0.5761756
Kurtosis-1.2
Mean123
Median Absolute Deviation (MAD)61
Skewness0
Sum30135
Variance5022.5
MonotonicityNot monotonic
2024-01-28T14:04:42.194689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
155 1
 
0.4%
157 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
164 1
 
0.4%
Other values (235) 235
95.9%
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 (%)
245 1
0.4%
244 1
0.4%
243 1
0.4%
242 1
0.4%
241 1
0.4%
240 1
0.4%
239 1
0.4%
238 1
0.4%
237 1
0.4%
236 1
0.4%

구 분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
인증
170 
예비(지역형)
45 
예비(부처형)
23 
예비(지역형)+예비(부처형)
 
7

Length

Max length15
Median length2
Mean length3.7591837
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인증 170
69.4%
예비(지역형) 45
 
18.4%
예비(부처형) 23
 
9.4%
예비(지역형)+예비(부처형) 7
 
2.9%

Length

2024-01-28T14:04:42.350601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:04:42.436782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인증 170
69.4%
예비(지역형 45
 
18.4%
예비(부처형 23
 
9.4%
예비(지역형)+예비(부처형 7
 
2.9%

기 업 명
Text

UNIQUE 

Distinct245
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-01-28T14:04:42.618635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length16
Mean length7.5714286
Min length2

Characters and Unicode

Total characters1855
Distinct characters361
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique245 ?
Unique (%)100.0%

Sample

1st row㈜정부물품재활용
2nd row㈜두손테크
3rd row㈜인천개항
4th row㈜해피크린
5th row사회적협동조합엠커뮤니티
ValueCountFrequency (%)
사회적협동조합 8
 
2.8%
협동조합 6
 
2.1%
농업회사법인 4
 
1.4%
㈜ 2
 
0.7%
사단법인 2
 
0.7%
사회복지법인 2
 
0.7%
손과손 2
 
0.7%
㈜다사랑 2
 
0.7%
㈜싸주아리 1
 
0.3%
㈜백양테크 1
 
0.3%
Other values (260) 260
89.7%
2024-01-28T14:04:42.929805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 190
 
10.2%
55
 
3.0%
사 52
 
2.8%
인 41
 
2.2%
이 40
 
2.2%
합 38
 
2.0%
조 38
 
2.0%
협 37
 
2.0%
스 36
 
1.9%
동 36
 
1.9%
Other values (351) 1292
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1568
84.5%
Other Symbol 190
 
10.2%
Space Separator 55
 
3.0%
Uppercase Letter 18
 
1.0%
Open Punctuation 9
 
0.5%
Close Punctuation 9
 
0.5%
Lowercase Letter 4
 
0.2%
Decimal Number 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 52
 
3.3%
인 41
 
2.6%
이 40
 
2.6%
합 38
 
2.4%
조 38
 
2.4%
협 37
 
2.4%
스 36
 
2.3%
동 36
 
2.3%
회 35
 
2.2%
아 24
 
1.5%
Other values (331) 1191
76.0%
Uppercase Letter
ValueCountFrequency (%)
T 3
16.7%
E 3
16.7%
A 2
11.1%
I 2
11.1%
P 2
11.1%
R 2
11.1%
Z 1
 
5.6%
O 1
 
5.6%
V 1
 
5.6%
L 1
 
5.6%
Lowercase Letter
ValueCountFrequency (%)
h 1
25.0%
e 1
25.0%
n 1
25.0%
c 1
25.0%
Other Symbol
ValueCountFrequency (%)
㈜ 190
100.0%
Space Separator
ValueCountFrequency (%)
55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Decimal Number
ValueCountFrequency (%)
5 1
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1757
94.7%
Common 75
 
4.0%
Latin 22
 
1.2%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 190
 
10.8%
사 52
 
3.0%
인 41
 
2.3%
이 40
 
2.3%
합 38
 
2.2%
조 38
 
2.2%
협 37
 
2.1%
스 36
 
2.0%
동 36
 
2.0%
회 35
 
2.0%
Other values (331) 1214
69.1%
Latin
ValueCountFrequency (%)
T 3
13.6%
E 3
13.6%
A 2
9.1%
I 2
9.1%
P 2
9.1%
R 2
9.1%
Z 1
 
4.5%
h 1
 
4.5%
e 1
 
4.5%
O 1
 
4.5%
Other values (4) 4
18.2%
Common
ValueCountFrequency (%)
55
73.3%
( 9
 
12.0%
) 9
 
12.0%
5 1
 
1.3%
. 1
 
1.3%
Han
ValueCountFrequency (%)
律 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1567
84.5%
None 190
 
10.2%
ASCII 97
 
5.2%
CJK Compat Ideographs 1
 
0.1%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 190
100.0%
ASCII
ValueCountFrequency (%)
55
56.7%
( 9
 
9.3%
) 9
 
9.3%
T 3
 
3.1%
E 3
 
3.1%
A 2
 
2.1%
I 2
 
2.1%
P 2
 
2.1%
R 2
 
2.1%
5 1
 
1.0%
Other values (9) 9
 
9.3%
Hangul
ValueCountFrequency (%)
사 52
 
3.3%
인 41
 
2.6%
이 40
 
2.6%
합 38
 
2.4%
조 38
 
2.4%
협 37
 
2.4%
스 36
 
2.3%
동 36
 
2.3%
회 35
 
2.2%
아 24
 
1.5%
Other values (330) 1190
75.9%
CJK Compat Ideographs
ValueCountFrequency (%)
律 1
100.0%

대표자
Text

Distinct243
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-01-28T14:04:43.221757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.244898
Min length2

Characters and Unicode

Total characters795
Distinct characters152
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

Unique241 ?
Unique (%)98.4%

Sample

1st row윤병하
2nd row지금련,오상준
3rd row장미진
4th row방미호
5th row이명선
ValueCountFrequency (%)
이기선 2
 
0.8%
장영순 2
 
0.8%
박보민 1
 
0.4%
박노희 1
 
0.4%
최재학 1
 
0.4%
김혜경,임춘임 1
 
0.4%
김석원 1
 
0.4%
오시식 1
 
0.4%
김은실 1
 
0.4%
곽창열 1
 
0.4%
Other values (241) 241
95.3%
2024-01-28T14:04:43.613616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 56
 
7.0%
이 40
 
5.0%
정 31
 
3.9%
영 24
 
3.0%
은 18
 
2.3%
수 16
 
2.0%
미 16
 
2.0%
윤 14
 
1.8%
박 14
 
1.8%
최 14
 
1.8%
Other values (142) 552
69.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 774
97.4%
Other Punctuation 13
 
1.6%
Space Separator 8
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 56
 
7.2%
이 40
 
5.2%
정 31
 
4.0%
영 24
 
3.1%
은 18
 
2.3%
수 16
 
2.1%
미 16
 
2.1%
윤 14
 
1.8%
박 14
 
1.8%
최 14
 
1.8%
Other values (139) 531
68.6%
Other Punctuation
ValueCountFrequency (%)
, 12
92.3%
. 1
 
7.7%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 774
97.4%
Common 21
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 56
 
7.2%
이 40
 
5.2%
정 31
 
4.0%
영 24
 
3.1%
은 18
 
2.3%
수 16
 
2.1%
미 16
 
2.1%
윤 14
 
1.8%
박 14
 
1.8%
최 14
 
1.8%
Other values (139) 531
68.6%
Common
ValueCountFrequency (%)
, 12
57.1%
8
38.1%
. 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 774
97.4%
ASCII 21
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 56
 
7.2%
이 40
 
5.2%
정 31
 
4.0%
영 24
 
3.1%
은 18
 
2.3%
수 16
 
2.1%
미 16
 
2.1%
윤 14
 
1.8%
박 14
 
1.8%
최 14
 
1.8%
Other values (139) 531
68.6%
ASCII
ValueCountFrequency (%)
, 12
57.1%
8
38.1%
. 1
 
4.8%

업종
Categorical

Distinct14
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
제조
51 
교육
35 
문화예술
29 
기타
27 
청소
22 
Other values (9)
81 

Length

Max length4
Median length2
Mean length2.4326531
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제조 51
20.8%
교육 35
14.3%
문화예술 29
11.8%
기타 27
11.0%
청소 22
9.0%
식품 22
9.0%
도소매 18
 
7.3%
간병가사 11
 
4.5%
건설 11
 
4.5%
IT 6
 
2.4%
Other values (4) 13
 
5.3%

Length

2024-01-28T14:04:43.744880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
제조 51
20.8%
교육 35
14.3%
문화예술 29
11.8%
기타 27
11.0%
청소 22
9.0%
식품 22
9.0%
도소매 18
 
7.3%
간병가사 11
 
4.5%
건설 11
 
4.5%
it 6
 
2.4%
Other values (4) 13
 
5.3%

서비스 유형
Text

Distinct242
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-01-28T14:04:43.979712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length40
Mean length16.22449
Min length3

Characters and Unicode

Total characters3975
Distinct characters382
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

Unique239 ?
Unique (%)97.6%

Sample

1st row공공기관물품재활용, 사무용가구 등
2nd row건물위생관리, 경비, 방역 등
3rd row카페, 관광기념품, 체험
4th row청소, 소독, 인테리어
5th row복지 서비스
ValueCountFrequency (%)
및 65
 
7.0%
등 27
 
2.9%
판매 23
 
2.5%
교육 19
 
2.0%
제조 19
 
2.0%
운영 12
 
1.3%
도소매 12
 
1.3%
제작 10
 
1.1%
서비스 9
 
1.0%
소독 9
 
1.0%
Other values (558) 729
78.1%
2024-01-28T14:04:44.320205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
704
 
17.7%
, 223
 
5.6%
제 83
 
2.1%
및 65
 
1.6%
매 62
 
1.6%
소 58
 
1.5%
판 58
 
1.5%
교 58
 
1.5%
리 54
 
1.4%
공 53
 
1.3%
Other values (372) 2557
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2971
74.7%
Space Separator 704
 
17.7%
Other Punctuation 258
 
6.5%
Uppercase Letter 18
 
0.5%
Open Punctuation 9
 
0.2%
Close Punctuation 9
 
0.2%
Decimal Number 4
 
0.1%
Final Punctuation 1
 
< 0.1%
Initial Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 83
 
2.8%
및 65
 
2.2%
매 62
 
2.1%
소 58
 
2.0%
판 58
 
2.0%
교 58
 
2.0%
리 54
 
1.8%
공 53
 
1.8%
기 52
 
1.8%
육 51
 
1.7%
Other values (348) 2377
80.0%
Uppercase Letter
ValueCountFrequency (%)
D 4
22.2%
L 3
16.7%
E 3
16.7%
R 2
11.1%
J 1
 
5.6%
T 1
 
5.6%
I 1
 
5.6%
P 1
 
5.6%
H 1
 
5.6%
N 1
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 223
86.4%
· 23
 
8.9%
/ 6
 
2.3%
& 4
 
1.6%
: 1
 
0.4%
. 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
4 1
25.0%
2 1
25.0%
Space Separator
ValueCountFrequency (%)
704
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2971
74.7%
Common 986
 
24.8%
Latin 18
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 83
 
2.8%
및 65
 
2.2%
매 62
 
2.1%
소 58
 
2.0%
판 58
 
2.0%
교 58
 
2.0%
리 54
 
1.8%
공 53
 
1.8%
기 52
 
1.8%
육 51
 
1.7%
Other values (348) 2377
80.0%
Common
ValueCountFrequency (%)
704
71.4%
, 223
 
22.6%
· 23
 
2.3%
( 9
 
0.9%
) 9
 
0.9%
/ 6
 
0.6%
& 4
 
0.4%
1 2
 
0.2%
: 1
 
0.1%
4 1
 
0.1%
Other values (4) 4
 
0.4%
Latin
ValueCountFrequency (%)
D 4
22.2%
L 3
16.7%
E 3
16.7%
R 2
11.1%
J 1
 
5.6%
T 1
 
5.6%
I 1
 
5.6%
P 1
 
5.6%
H 1
 
5.6%
N 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2971
74.7%
ASCII 979
 
24.6%
None 23
 
0.6%
Punctuation 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
704
71.9%
, 223
 
22.8%
( 9
 
0.9%
) 9
 
0.9%
/ 6
 
0.6%
D 4
 
0.4%
& 4
 
0.4%
L 3
 
0.3%
E 3
 
0.3%
R 2
 
0.2%
Other values (11) 12
 
1.2%
Hangul
ValueCountFrequency (%)
제 83
 
2.8%
및 65
 
2.2%
매 62
 
2.1%
소 58
 
2.0%
판 58
 
2.0%
교 58
 
2.0%
리 54
 
1.8%
공 53
 
1.8%
기 52
 
1.8%
육 51
 
1.7%
Other values (348) 2377
80.0%
None
ValueCountFrequency (%)
· 23
100.0%
Punctuation
ValueCountFrequency (%)
’ 1
50.0%
‘ 1
50.0%

군구
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
남동구
49 
미추홀구
48 
서구
33 
연수구
28 
계양구
23 
Other values (5)
64 

Length

Max length4
Median length3
Mean length2.9591837
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남동구 49
20.0%
미추홀구 48
19.6%
서구 33
13.5%
연수구 28
11.4%
계양구 23
9.4%
부평구 21
8.6%
동구 14
 
5.7%
중구 11
 
4.5%
강화군 10
 
4.1%
옹진군 8
 
3.3%

Length

2024-01-28T14:04:44.443593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T14:04:44.550684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남동구 49
20.0%
미추홀구 48
19.6%
서구 33
13.5%
연수구 28
11.4%
계양구 23
9.4%
부평구 21
8.6%
동구 14
 
5.7%
중구 11
 
4.5%
강화군 10
 
4.1%
옹진군 8
 
3.3%

주 소 (신주소)
Text

Distinct241
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-01-28T14:04:44.873952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length44
Mean length25.261224
Min length15

Characters and Unicode

Total characters6189
Distinct characters271
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

Unique238 ?
Unique (%)97.1%

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 245
 
20.0%
남동구 50
 
4.1%
미추홀구 47
 
3.8%
서구 33
 
2.7%
연수구 29
 
2.4%
계양구 22
 
1.8%
부평구 21
 
1.7%
1층 19
 
1.5%
동구 14
 
1.1%
2층 14
 
1.1%
Other values (515) 732
59.7%
2024-01-28T14:04:45.317084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
994
 
16.1%
인 278
 
4.5%
천 259
 
4.2%
1 248
 
4.0%
시 248
 
4.0%
역 246
 
4.0%
광 245
 
4.0%
로 244
 
3.9%
구 239
 
3.9%
2 175
 
2.8%
Other values (261) 3013
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3726
60.2%
Decimal Number 1194
 
19.3%
Space Separator 994
 
16.1%
Other Punctuation 129
 
2.1%
Dash Punctuation 51
 
0.8%
Close Punctuation 38
 
0.6%
Open Punctuation 37
 
0.6%
Uppercase Letter 17
 
0.3%
Math Symbol 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 278
 
7.5%
천 259
 
7.0%
시 248
 
6.7%
역 246
 
6.6%
광 245
 
6.6%
로 244
 
6.5%
구 239
 
6.4%
동 144
 
3.9%
길 103
 
2.8%
번 99
 
2.7%
Other values (234) 1621
43.5%
Decimal Number
ValueCountFrequency (%)
1 248
20.8%
2 175
14.7%
0 139
11.6%
3 134
11.2%
5 107
9.0%
4 95
 
8.0%
6 87
 
7.3%
8 81
 
6.8%
7 64
 
5.4%
9 64
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
C 5
29.4%
B 4
23.5%
E 2
 
11.8%
A 1
 
5.9%
R 1
 
5.9%
V 1
 
5.9%
L 1
 
5.9%
T 1
 
5.9%
I 1
 
5.9%
Math Symbol
ValueCountFrequency (%)
~ 1
50.0%
～ 1
50.0%
Space Separator
ValueCountFrequency (%)
994
100.0%
Other Punctuation
ValueCountFrequency (%)
, 129
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3726
60.2%
Common 2445
39.5%
Latin 18
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 278
 
7.5%
천 259
 
7.0%
시 248
 
6.7%
역 246
 
6.6%
광 245
 
6.6%
로 244
 
6.5%
구 239
 
6.4%
동 144
 
3.9%
길 103
 
2.8%
번 99
 
2.7%
Other values (234) 1621
43.5%
Common
ValueCountFrequency (%)
994
40.7%
1 248
 
10.1%
2 175
 
7.2%
0 139
 
5.7%
3 134
 
5.5%
, 129
 
5.3%
5 107
 
4.4%
4 95
 
3.9%
6 87
 
3.6%
8 81
 
3.3%
Other values (7) 256
 
10.5%
Latin
ValueCountFrequency (%)
C 5
27.8%
B 4
22.2%
E 2
 
11.1%
A 1
 
5.6%
e 1
 
5.6%
R 1
 
5.6%
V 1
 
5.6%
L 1
 
5.6%
T 1
 
5.6%
I 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3726
60.2%
ASCII 2462
39.8%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
994
40.4%
1 248
 
10.1%
2 175
 
7.1%
0 139
 
5.6%
3 134
 
5.4%
, 129
 
5.2%
5 107
 
4.3%
4 95
 
3.9%
6 87
 
3.5%
8 81
 
3.3%
Other values (16) 273
 
11.1%
Hangul
ValueCountFrequency (%)
인 278
 
7.5%
천 259
 
7.0%
시 248
 
6.7%
역 246
 
6.6%
광 245
 
6.6%
로 244
 
6.5%
구 239
 
6.4%
동 144
 
3.9%
길 103
 
2.8%
번 99
 
2.7%
Other values (234) 1621
43.5%
None
ValueCountFrequency (%)
～ 1
100.0%

Interactions

2024-01-28T14:04:41.732859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T14:04:45.394421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구 분업종군구
연번1.0000.9130.3170.916
구 분0.9131.0000.1850.173
업종0.3170.1851.0000.236
군구0.9160.1730.2361.000
2024-01-28T14:04:45.462301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종군구구 분
업종1.0000.0950.102
군구0.0951.0000.102
구 분0.1020.1021.000
2024-01-28T14:04:45.529783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구 분업종군구
연번1.0000.7950.1330.532
구 분0.7951.0000.1020.102
업종0.1330.1021.0000.095
군구0.5320.1020.0951.000

Missing values

2024-01-28T14:04:41.823054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T14:04:41.920996image/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

연번구 분기 업 명대표자업종서비스 유형군구주 소 (신주소)
01인증㈜정부물품재활용윤병하재활용공공기관물품재활용, 사무용가구 등중구인천광역시 중구 서해대로 324
12인증㈜두손테크지금련,오상준청소건물위생관리, 경비, 방역 등중구인천광역시 중구 서해대로 483번길 68번지
23인증㈜인천개항장미진식품카페, 관광기념품, 체험중구인천광역시 중구 신포로23번길 83, 202호(중앙동1가)
34인증㈜해피크린방미호청소청소, 소독, 인테리어중구인천광역시 중구 개항로53번길 13
45인증사회적협동조합엠커뮤니티이명선교육복지 서비스중구인천광역시 중구 율목로 54, 2층
56인증㈜차이나브이중국어마을조경순교육중국문화체험, 중국진로체험중구인천광역시 중구 신포로23번길 80, 202~204호
67인증㈜한사랑 식판선생님지정호기타어린이집, 유치원 식판세척 소독배달업중구인천광역시 중구 도산로 17
78인증㈜행복을 나누는 도시락김연자식품도시락, 출장부페동구인천광역시 동구 화수로 74-1
89인증㈜청소사랑김순옥청소건물위생관리, 경비, 방역 등동구인천광역시 동구 화도진로34번길 7
910인증㈜어울푸름정명섭스포츠택견강습, 전통놀이 체험동구인천광역시 동구 송림로 24
연번구 분기 업 명대표자업종서비스 유형군구주 소 (신주소)
235236예비(부처형)사단법인 한국숲교육협회이명환교육유아숲체험 및 유아숲지도사 양성남동구인천광역시 남동구 미래로 45, 벤처빌딩 702호
236237예비(부처형)㈜허니랩김동은제조친환경 식품 포장랩 등 생산남동구인천광역시 남동구 남동대로 350, 에이동 1층 일부
237238예비(부처형)두손식품윤진제조식품 제조 판매남동구인천광역시 남동구 장승남로81번길 27
238239예비(부처형)㈜청솔기획김택환.배정현문화예술예술, 스포츠 및 여가관련 서비스업, 공연기획 및 이벤트남동구인천광역시 남동구 복개동로66번길 34-1, 1층
239240예비(부처형)미소앤미래로사회적협동조합김세훈청소사업시설관리 및 사업지원 서비스, 건물위생관리, 소독남동구인천광역시 남동구 용천로4번길 19, 1층
240241예비(부처형)㈜코워킹소사이어티한가늠기타스마트역량진단 앱개발, 전문 경영컨설팅서구인천광역시 서구 보듬로 158, 221호
241242예비(부처형)정약용컴퍼니㈜박보민청소영유아 가정과 대가족 세대를 위한 가사 청소관리 서비스 제공 및 생활용품 소매업서구인천광역시 서구 염곡로464번길 15 쓰리엠타워8층 입주사무실7호
242243예비(부처형)위즈덤랩㈜허정문기타가족 고객을 대상으로 교육, 체험, 돌봄, 상담 등을 위한 전문가를 연결하는 재능 공유 플랫폼을 제작 운영서구인천광역시 서구 염곡로464번길 15 8층, 인천서구사회적경제마을지원센터 입주기업사무실6
243244예비(부처형)㈜바람꽃출판사구혜은교육난독증·다문화 어린이들의 읽기 개선을 위한 도서 출판, 콘텐츠 제작서구인천광역시 서구 염곡로464번길 15 801호
244245예비(부처형)㈜더하트컴퍼니박대은기타저출산 문제 완화를 위한아기 엄마 대상의 커뮤니티 및 교육, 워크숍, 공간사업서구인천광역시 서구 보듬로 158, 미플존 221호(오류동, 블루텍)