Overview

Dataset statistics

Number of variables11
Number of observations31
Missing cells12
Missing cells (%)3.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory93.3 B

Variable types

Numeric1
Text7
Categorical2
DateTime1

Dataset

Description인천광역시 중구 관내에 위치한 소독업소 현황에 대한 데이터 입니다.
Author인천광역시 중구
URLhttps://www.data.go.kr/data/15066187/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
법인명 has 12 (38.7%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:49:48.575368
Analysis finished2023-12-12 10:49:50.322658
Duration1.75 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T19:49:50.421134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q18.5
median16
Q323.5
95-th percentile29.5
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.0921211
Coefficient of variation (CV)0.56825757
Kurtosis-1.2
Mean16
Median Absolute Deviation (MAD)8
Skewness0
Sum496
Variance82.666667
MonotonicityStrictly increasing
2023-12-12T19:49:50.594841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 1
 
3.2%
2 1
 
3.2%
31 1
 
3.2%
30 1
 
3.2%
29 1
 
3.2%
28 1
 
3.2%
27 1
 
3.2%
26 1
 
3.2%
25 1
 
3.2%
24 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
1 1
3.2%
2 1
3.2%
3 1
3.2%
4 1
3.2%
5 1
3.2%
6 1
3.2%
7 1
3.2%
8 1
3.2%
9 1
3.2%
10 1
3.2%
ValueCountFrequency (%)
31 1
3.2%
30 1
3.2%
29 1
3.2%
28 1
3.2%
27 1
3.2%
26 1
3.2%
25 1
3.2%
24 1
3.2%
23 1
3.2%
22 1
3.2%

신고번호
Text

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T19:49:50.941335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters775
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)93.5%

Sample

1st rowPHMB520203490019042500008
2nd rowPHMB520203490019042500005
3rd rowPHMB520203490019042500006
4th rowPHMB520203490019042500004
5th rowPHMB520203490019042500003
ValueCountFrequency (%)
phmb520103490019042500004 2
 
6.5%
phmb520203490019042500008 1
 
3.2%
phmb520203490019042500005 1
 
3.2%
phmb519953490019042500001 1
 
3.2%
phmb519973490019042500001 1
 
3.2%
phmb519993490019042500001 1
 
3.2%
phmb519993490019042500002 1
 
3.2%
phmb520063490019042500001 1
 
3.2%
phmb520073490019042500001 1
 
3.2%
phmb520103490019042500002 1
 
3.2%
Other values (20) 20
64.5%
2023-12-12T19:49:51.470524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 256
33.0%
9 74
 
9.5%
2 71
 
9.2%
5 67
 
8.6%
4 67
 
8.6%
1 64
 
8.3%
3 36
 
4.6%
P 31
 
4.0%
H 31
 
4.0%
M 31
 
4.0%
Other values (4) 47
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 651
84.0%
Uppercase Letter 124
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 256
39.3%
9 74
 
11.4%
2 71
 
10.9%
5 67
 
10.3%
4 67
 
10.3%
1 64
 
9.8%
3 36
 
5.5%
6 6
 
0.9%
8 5
 
0.8%
7 5
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
P 31
25.0%
H 31
25.0%
M 31
25.0%
B 31
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 651
84.0%
Latin 124
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 256
39.3%
9 74
 
11.4%
2 71
 
10.9%
5 67
 
10.3%
4 67
 
10.3%
1 64
 
9.8%
3 36
 
5.5%
6 6
 
0.9%
8 5
 
0.8%
7 5
 
0.8%
Latin
ValueCountFrequency (%)
P 31
25.0%
H 31
25.0%
M 31
25.0%
B 31
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 775
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 256
33.0%
9 74
 
9.5%
2 71
 
9.2%
5 67
 
8.6%
4 67
 
8.6%
1 64
 
8.3%
3 36
 
4.6%
P 31
 
4.0%
H 31
 
4.0%
M 31
 
4.0%
Other values (4) 47
 
6.1%

소독업소명칭
Text

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T19:49:51.765587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length8.1935484
Min length3

Characters and Unicode

Total characters254
Distinct characters111
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)93.5%

Sample

1st row인천중구지역자활센터
2nd row(주)스카이피엠씨
3rd row우광크린
4th row아이크린 홈케어
5th row미래환경
ValueCountFrequency (%)
주식회사 6
 
14.0%
한국진돗개안전c＆s(주 2
 
4.7%
신성종합관리 1
 
2.3%
주)효자건설 1
 
2.3%
다잡아 1
 
2.3%
콜 1
 
2.3%
주)해피크린 1
 
2.3%
주)세스코인천공항지사 1
 
2.3%
비알엘(주 1
 
2.3%
주)나래환경 1
 
2.3%
Other values (27) 27
62.8%
2023-12-12T19:49:52.548107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 18
 
7.1%
12
 
4.7%
) 11
 
4.3%
사 11
 
4.3%
( 10
 
3.9%
회 7
 
2.8%
식 7
 
2.8%
아 5
 
2.0%
인 5
 
2.0%
린 5
 
2.0%
Other values (101) 163
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 200
78.7%
Space Separator 12
 
4.7%
Uppercase Letter 12
 
4.7%
Close Punctuation 11
 
4.3%
Open Punctuation 10
 
3.9%
Lowercase Letter 6
 
2.4%
Other Punctuation 2
 
0.8%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 18
 
9.0%
사 11
 
5.5%
회 7
 
3.5%
식 7
 
3.5%
아 5
 
2.5%
인 5
 
2.5%
린 5
 
2.5%
크 4
 
2.0%
경 4
 
2.0%
환 4
 
2.0%
Other values (82) 130
65.0%
Uppercase Letter
ValueCountFrequency (%)
C 3
25.0%
E 2
16.7%
S 2
16.7%
G 1
 
8.3%
R 1
 
8.3%
N 1
 
8.3%
F 1
 
8.3%
B 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
l 1
16.7%
n 1
16.7%
i 1
16.7%
o 1
16.7%
e 1
16.7%
a 1
16.7%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
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 200
78.7%
Common 36
 
14.2%
Latin 18
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 18
 
9.0%
사 11
 
5.5%
회 7
 
3.5%
식 7
 
3.5%
아 5
 
2.5%
인 5
 
2.5%
린 5
 
2.5%
크 4
 
2.0%
경 4
 
2.0%
환 4
 
2.0%
Other values (82) 130
65.0%
Latin
ValueCountFrequency (%)
C 3
16.7%
E 2
11.1%
S 2
11.1%
l 1
 
5.6%
n 1
 
5.6%
G 1
 
5.6%
R 1
 
5.6%
N 1
 
5.6%
F 1
 
5.6%
B 1
 
5.6%
Other values (4) 4
22.2%
Common
ValueCountFrequency (%)
12
33.3%
) 11
30.6%
( 10
27.8%
＆ 2
 
5.6%
5 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 200
78.7%
ASCII 52
 
20.5%
None 2
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 18
 
9.0%
사 11
 
5.5%
회 7
 
3.5%
식 7
 
3.5%
아 5
 
2.5%
인 5
 
2.5%
린 5
 
2.5%
크 4
 
2.0%
경 4
 
2.0%
환 4
 
2.0%
Other values (82) 130
65.0%
ASCII
ValueCountFrequency (%)
12
23.1%
) 11
21.2%
( 10
19.2%
C 3
 
5.8%
E 2
 
3.8%
S 2
 
3.8%
l 1
 
1.9%
n 1
 
1.9%
G 1
 
1.9%
R 1
 
1.9%
Other values (8) 8
15.4%
None
ValueCountFrequency (%)
＆ 2
100.0%

허가명
Text

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T19:49:53.055502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length8.1935484
Min length3

Characters and Unicode

Total characters254
Distinct characters111
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)93.5%

Sample

1st row인천중구지역자활센터
2nd row(주)스카이피엠씨
3rd row우광크린
4th row아이크린 홈케어
5th row미래환경
ValueCountFrequency (%)
주식회사 6
 
14.0%
한국진돗개안전c＆s(주 2
 
4.7%
신성종합관리 1
 
2.3%
주)효자건설 1
 
2.3%
다잡아 1
 
2.3%
콜 1
 
2.3%
주)해피크린 1
 
2.3%
주)세스코인천공항지사 1
 
2.3%
비알엘(주 1
 
2.3%
주)나래환경 1
 
2.3%
Other values (27) 27
62.8%
2023-12-12T19:49:53.658447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 18
 
7.1%
12
 
4.7%
) 11
 
4.3%
사 11
 
4.3%
( 10
 
3.9%
회 7
 
2.8%
식 7
 
2.8%
아 5
 
2.0%
인 5
 
2.0%
린 5
 
2.0%
Other values (101) 163
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 200
78.7%
Space Separator 12
 
4.7%
Uppercase Letter 12
 
4.7%
Close Punctuation 11
 
4.3%
Open Punctuation 10
 
3.9%
Lowercase Letter 6
 
2.4%
Other Punctuation 2
 
0.8%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 18
 
9.0%
사 11
 
5.5%
회 7
 
3.5%
식 7
 
3.5%
아 5
 
2.5%
인 5
 
2.5%
린 5
 
2.5%
크 4
 
2.0%
경 4
 
2.0%
환 4
 
2.0%
Other values (82) 130
65.0%
Uppercase Letter
ValueCountFrequency (%)
C 3
25.0%
E 2
16.7%
S 2
16.7%
G 1
 
8.3%
R 1
 
8.3%
N 1
 
8.3%
F 1
 
8.3%
B 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
l 1
16.7%
n 1
16.7%
i 1
16.7%
o 1
16.7%
e 1
16.7%
a 1
16.7%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
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 200
78.7%
Common 36
 
14.2%
Latin 18
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 18
 
9.0%
사 11
 
5.5%
회 7
 
3.5%
식 7
 
3.5%
아 5
 
2.5%
인 5
 
2.5%
린 5
 
2.5%
크 4
 
2.0%
경 4
 
2.0%
환 4
 
2.0%
Other values (82) 130
65.0%
Latin
ValueCountFrequency (%)
C 3
16.7%
E 2
11.1%
S 2
11.1%
l 1
 
5.6%
n 1
 
5.6%
G 1
 
5.6%
R 1
 
5.6%
N 1
 
5.6%
F 1
 
5.6%
B 1
 
5.6%
Other values (4) 4
22.2%
Common
ValueCountFrequency (%)
12
33.3%
) 11
30.6%
( 10
27.8%
＆ 2
 
5.6%
5 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 200
78.7%
ASCII 52
 
20.5%
None 2
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 18
 
9.0%
사 11
 
5.5%
회 7
 
3.5%
식 7
 
3.5%
아 5
 
2.5%
인 5
 
2.5%
린 5
 
2.5%
크 4
 
2.0%
경 4
 
2.0%
환 4
 
2.0%
Other values (82) 130
65.0%
ASCII
ValueCountFrequency (%)
12
23.1%
) 11
21.2%
( 10
19.2%
C 3
 
5.8%
E 2
 
3.8%
S 2
 
3.8%
l 1
 
1.9%
n 1
 
1.9%
G 1
 
1.9%
R 1
 
1.9%
Other values (8) 8
15.4%
None
ValueCountFrequency (%)
＆ 2
100.0%

업소명
Text

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T19:49:53.978080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length8.1935484
Min length3

Characters and Unicode

Total characters254
Distinct characters111
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)93.5%

Sample

1st row인천중구지역자활센터
2nd row(주)스카이피엠씨
3rd row우광크린
4th row아이크린 홈케어
5th row미래환경
ValueCountFrequency (%)
주식회사 6
 
14.0%
한국진돗개안전c＆s(주 2
 
4.7%
신성종합관리 1
 
2.3%
주)효자건설 1
 
2.3%
다잡아 1
 
2.3%
콜 1
 
2.3%
주)해피크린 1
 
2.3%
주)세스코인천공항지사 1
 
2.3%
비알엘(주 1
 
2.3%
주)나래환경 1
 
2.3%
Other values (27) 27
62.8%
2023-12-12T19:49:54.901183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 18
 
7.1%
12
 
4.7%
) 11
 
4.3%
사 11
 
4.3%
( 10
 
3.9%
회 7
 
2.8%
식 7
 
2.8%
아 5
 
2.0%
인 5
 
2.0%
린 5
 
2.0%
Other values (101) 163
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 200
78.7%
Space Separator 12
 
4.7%
Uppercase Letter 12
 
4.7%
Close Punctuation 11
 
4.3%
Open Punctuation 10
 
3.9%
Lowercase Letter 6
 
2.4%
Other Punctuation 2
 
0.8%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 18
 
9.0%
사 11
 
5.5%
회 7
 
3.5%
식 7
 
3.5%
아 5
 
2.5%
인 5
 
2.5%
린 5
 
2.5%
크 4
 
2.0%
경 4
 
2.0%
환 4
 
2.0%
Other values (82) 130
65.0%
Uppercase Letter
ValueCountFrequency (%)
C 3
25.0%
E 2
16.7%
S 2
16.7%
G 1
 
8.3%
R 1
 
8.3%
N 1
 
8.3%
F 1
 
8.3%
B 1
 
8.3%
Lowercase Letter
ValueCountFrequency (%)
l 1
16.7%
n 1
16.7%
i 1
16.7%
o 1
16.7%
e 1
16.7%
a 1
16.7%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
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 200
78.7%
Common 36
 
14.2%
Latin 18
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 18
 
9.0%
사 11
 
5.5%
회 7
 
3.5%
식 7
 
3.5%
아 5
 
2.5%
인 5
 
2.5%
린 5
 
2.5%
크 4
 
2.0%
경 4
 
2.0%
환 4
 
2.0%
Other values (82) 130
65.0%
Latin
ValueCountFrequency (%)
C 3
16.7%
E 2
11.1%
S 2
11.1%
l 1
 
5.6%
n 1
 
5.6%
G 1
 
5.6%
R 1
 
5.6%
N 1
 
5.6%
F 1
 
5.6%
B 1
 
5.6%
Other values (4) 4
22.2%
Common
ValueCountFrequency (%)
12
33.3%
) 11
30.6%
( 10
27.8%
＆ 2
 
5.6%
5 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 200
78.7%
ASCII 52
 
20.5%
None 2
 
0.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 18
 
9.0%
사 11
 
5.5%
회 7
 
3.5%
식 7
 
3.5%
아 5
 
2.5%
인 5
 
2.5%
린 5
 
2.5%
크 4
 
2.0%
경 4
 
2.0%
환 4
 
2.0%
Other values (82) 130
65.0%
ASCII
ValueCountFrequency (%)
12
23.1%
) 11
21.2%
( 10
19.2%
C 3
 
5.8%
E 2
 
3.8%
S 2
 
3.8%
l 1
 
1.9%
n 1
 
1.9%
G 1
 
1.9%
R 1
 
1.9%
Other values (8) 8
15.4%
None
ValueCountFrequency (%)
＆ 2
100.0%

사무실소재지(도로명)
Text

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T19:49:55.344729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length33
Mean length27.870968
Min length20

Characters and Unicode

Total characters864
Distinct characters99
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)93.5%

Sample

1st row인천광역시 중구 연안부두로 20, 2층 (항동7가)
2nd row인천광역시 중구 영종대로 108, 비2빌 202호 (운서동)
3rd row인천광역시 중구 참외전로 8 (송월동1가)
4th row인천광역시 중구 영종대로196번길 19, 지엘플렉스1 327호 (운서동)
5th row인천광역시 중구 우현로90번길 19-1 (인현동)
ValueCountFrequency (%)
인천광역시 31
 
18.1%
중구 31
 
18.1%
운서동 6
 
3.5%
제물량로 5
 
2.9%
운북동 3
 
1.8%
송월동1가 3
 
1.8%
신흥동3가 2
 
1.2%
108 2
 
1.2%
신흥동1가 2
 
1.2%
서해대로483번길 2
 
1.2%
Other values (72) 84
49.1%
2023-12-12T19:49:55.943525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
140
 
16.2%
인 34
 
3.9%
시 33
 
3.8%
1 33
 
3.8%
중 32
 
3.7%
천 32
 
3.7%
역 31
 
3.6%
광 31
 
3.6%
구 31
 
3.6%
( 31
 
3.6%
Other values (89) 436
50.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 510
59.0%
Space Separator 140
 
16.2%
Decimal Number 132
 
15.3%
Open Punctuation 31
 
3.6%
Close Punctuation 31
 
3.6%
Other Punctuation 14
 
1.6%
Dash Punctuation 6
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 34
 
6.7%
시 33
 
6.5%
중 32
 
6.3%
천 32
 
6.3%
역 31
 
6.1%
광 31
 
6.1%
구 31
 
6.1%
로 31
 
6.1%
동 31
 
6.1%
가 13
 
2.5%
Other values (74) 211
41.4%
Decimal Number
ValueCountFrequency (%)
1 33
25.0%
2 23
17.4%
4 14
10.6%
3 13
 
9.8%
8 12
 
9.1%
7 9
 
6.8%
0 8
 
6.1%
9 8
 
6.1%
6 7
 
5.3%
5 5
 
3.8%
Space Separator
ValueCountFrequency (%)
140
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 510
59.0%
Common 354
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 34
 
6.7%
시 33
 
6.5%
중 32
 
6.3%
천 32
 
6.3%
역 31
 
6.1%
광 31
 
6.1%
구 31
 
6.1%
로 31
 
6.1%
동 31
 
6.1%
가 13
 
2.5%
Other values (74) 211
41.4%
Common
ValueCountFrequency (%)
140
39.5%
1 33
 
9.3%
( 31
 
8.8%
) 31
 
8.8%
2 23
 
6.5%
, 14
 
4.0%
4 14
 
4.0%
3 13
 
3.7%
8 12
 
3.4%
7 9
 
2.5%
Other values (5) 34
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 510
59.0%
ASCII 354
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
140
39.5%
1 33
 
9.3%
( 31
 
8.8%
) 31
 
8.8%
2 23
 
6.5%
, 14
 
4.0%
4 14
 
4.0%
3 13
 
3.7%
8 12
 
3.4%
7 9
 
2.5%
Other values (5) 34
 
9.6%
Hangul
ValueCountFrequency (%)
인 34
 
6.7%
시 33
 
6.5%
중 32
 
6.3%
천 32
 
6.3%
역 31
 
6.1%
광 31
 
6.1%
구 31
 
6.1%
로 31
 
6.1%
동 31
 
6.1%
가 13
 
2.5%
Other values (74) 211
41.4%

유형
Categorical

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
개인
17 
법인
14 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인 17
54.8%
법인 14
45.2%

Length

2023-12-12T19:49:56.234998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:49:56.473726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 17
54.8%
법인 14
45.2%

법인명
Text

MISSING 

Distinct18
Distinct (%)94.7%
Missing12
Missing (%)38.7%
Memory size380.0 B
2023-12-12T19:49:56.704140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length9.2631579
Min length4

Characters and Unicode

Total characters176
Distinct characters71
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)89.5%

Sample

1st row주식회사 인화비엠에스
2nd row에이비씨페스트컨트롤주식회사
3rd row주식회사 한성환경
4th row주식회사 그린온
5th row주식회사 미래종합관리
ValueCountFrequency (%)
주식회사 7
26.9%
한국진돗개안전c&s(주 2
 
7.7%
세스코인천공항지사 1
 
3.8%
두손테크 1
 
3.8%
인천방역공사 1
 
3.8%
삼진환경 1
 
3.8%
동아방역공사 1
 
3.8%
주)선진알앤디 1
 
3.8%
주)나래환경 1
 
3.8%
비알엘주식회사 1
 
3.8%
Other values (9) 9
34.6%
2023-12-12T19:49:57.080225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 16
 
9.1%
사 14
 
8.0%
회 10
 
5.7%
식 10
 
5.7%
7
 
4.0%
) 6
 
3.4%
( 5
 
2.8%
진 4
 
2.3%
인 4
 
2.3%
경 3
 
1.7%
Other values (61) 97
55.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 152
86.4%
Space Separator 7
 
4.0%
Close Punctuation 6
 
3.4%
Open Punctuation 5
 
2.8%
Uppercase Letter 4
 
2.3%
Other Punctuation 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 16
 
10.5%
사 14
 
9.2%
회 10
 
6.6%
식 10
 
6.6%
진 4
 
2.6%
인 4
 
2.6%
경 3
 
2.0%
스 3
 
2.0%
비 3
 
2.0%
성 3
 
2.0%
Other values (55) 82
53.9%
Uppercase Letter
ValueCountFrequency (%)
C 2
50.0%
S 2
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 152
86.4%
Common 20
 
11.4%
Latin 4
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 16
 
10.5%
사 14
 
9.2%
회 10
 
6.6%
식 10
 
6.6%
진 4
 
2.6%
인 4
 
2.6%
경 3
 
2.0%
스 3
 
2.0%
비 3
 
2.0%
성 3
 
2.0%
Other values (55) 82
53.9%
Common
ValueCountFrequency (%)
7
35.0%
) 6
30.0%
( 5
25.0%
& 2
 
10.0%
Latin
ValueCountFrequency (%)
C 2
50.0%
S 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 152
86.4%
ASCII 24
 
13.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 16
 
10.5%
사 14
 
9.2%
회 10
 
6.6%
식 10
 
6.6%
진 4
 
2.6%
인 4
 
2.6%
경 3
 
2.0%
스 3
 
2.0%
비 3
 
2.0%
성 3
 
2.0%
Other values (55) 82
53.9%
ASCII
ValueCountFrequency (%)
7
29.2%
) 6
25.0%
( 5
20.8%
C 2
 
8.3%
S 2
 
8.3%
& 2
 
8.3%

창고소재지(도로명)
Text

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T19:49:57.375032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length27.193548
Min length20

Characters and Unicode

Total characters843
Distinct characters98
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)93.5%

Sample

1st row인천광역시 중구 연안부두로 20, 2층 (항동7가)
2nd row인천광역시 중구 영종대로 108, 비2빌 202호 (운서동)
3rd row인천광역시 중구 참외전로 8 (송월동1가)
4th row인천광역시 중구 백운로107번길 24-12 (운남동)
5th row인천광역시 중구 우현로90번길 19-1 (인현동)
ValueCountFrequency (%)
인천광역시 31
 
18.5%
중구 30
 
17.9%
제물량로 6
 
3.6%
운서동 5
 
3.0%
송월동1가 3
 
1.8%
운북동 3
 
1.8%
1층 2
 
1.2%
신흥동1가 2
 
1.2%
7 2
 
1.2%
해안동2가 2
 
1.2%
Other values (71) 82
48.8%
2023-12-12T19:49:57.882618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
137
 
16.3%
인 33
 
3.9%
시 33
 
3.9%
천 32
 
3.8%
광 31
 
3.7%
역 31
 
3.7%
중 31
 
3.7%
구 31
 
3.7%
로 31
 
3.7%
( 30
 
3.6%
Other values (88) 423
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 502
59.5%
Space Separator 137
 
16.3%
Decimal Number 126
 
14.9%
Open Punctuation 30
 
3.6%
Close Punctuation 30
 
3.6%
Other Punctuation 13
 
1.5%
Dash Punctuation 5
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 33
 
6.6%
시 33
 
6.6%
천 32
 
6.4%
광 31
 
6.2%
역 31
 
6.2%
중 31
 
6.2%
구 31
 
6.2%
로 31
 
6.2%
동 30
 
6.0%
운 16
 
3.2%
Other values (73) 203
40.4%
Decimal Number
ValueCountFrequency (%)
1 30
23.8%
2 23
18.3%
4 14
11.1%
8 13
10.3%
3 11
 
8.7%
7 10
 
7.9%
0 8
 
6.3%
9 6
 
4.8%
6 6
 
4.8%
5 5
 
4.0%
Space Separator
ValueCountFrequency (%)
137
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 502
59.5%
Common 341
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 33
 
6.6%
시 33
 
6.6%
천 32
 
6.4%
광 31
 
6.2%
역 31
 
6.2%
중 31
 
6.2%
구 31
 
6.2%
로 31
 
6.2%
동 30
 
6.0%
운 16
 
3.2%
Other values (73) 203
40.4%
Common
ValueCountFrequency (%)
137
40.2%
( 30
 
8.8%
1 30
 
8.8%
) 30
 
8.8%
2 23
 
6.7%
4 14
 
4.1%
8 13
 
3.8%
, 13
 
3.8%
3 11
 
3.2%
7 10
 
2.9%
Other values (5) 30
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 502
59.5%
ASCII 341
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
137
40.2%
( 30
 
8.8%
1 30
 
8.8%
) 30
 
8.8%
2 23
 
6.7%
4 14
 
4.1%
8 13
 
3.8%
, 13
 
3.8%
3 11
 
3.2%
7 10
 
2.9%
Other values (5) 30
 
8.8%
Hangul
ValueCountFrequency (%)
인 33
 
6.6%
시 33
 
6.6%
천 32
 
6.4%
광 31
 
6.2%
역 31
 
6.2%
중 31
 
6.2%
구 31
 
6.2%
로 31
 
6.2%
동 30
 
6.0%
운 16
 
3.2%
Other values (73) 203
40.4%

처리일자
Date

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum2008-12-24 00:00:00
Maximum2021-09-10 00:00:00
2023-12-12T19:49:58.063534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:49:58.305233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
2021-09-10
31 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-09-10
2nd row2021-09-10
3rd row2021-09-10
4th row2021-09-10
5th row2021-09-10

Common Values

ValueCountFrequency (%)
2021-09-10 31
100.0%

Length

2023-12-12T19:49:58.816673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:49:59.289761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-09-10 31
100.0%

Interactions

2023-12-12T19:49:49.302455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:49:59.639835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번신고번호소독업소명칭허가명업소명사무실소재지(도로명)유형법인명창고소재지(도로명)처리일자
연번1.0001.0001.0001.0001.0001.0000.7301.0001.0000.961
신고번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소독업소명칭1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
허가명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
사무실소재지(도로명)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
유형0.7301.0001.0001.0001.0001.0001.0001.0001.0000.705
법인명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
창고소재지(도로명)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
처리일자0.9611.0001.0001.0001.0001.0000.7051.0001.0001.000
2023-12-12T19:50:00.112507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번유형
연번1.0000.430
유형0.4301.000

Missing values

2023-12-12T19:49:49.908492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:49:50.222538image/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

연번신고번호소독업소명칭허가명업소명사무실소재지(도로명)유형법인명창고소재지(도로명)처리일자데이터기준일자
01PHMB520203490019042500008인천중구지역자활센터인천중구지역자활센터인천중구지역자활센터인천광역시 중구 연안부두로 20, 2층 (항동7가)개인<NA>인천광역시 중구 연안부두로 20, 2층 (항동7가)2020-07-062021-09-10
12PHMB520203490019042500005(주)스카이피엠씨(주)스카이피엠씨(주)스카이피엠씨인천광역시 중구 영종대로 108, 비2빌 202호 (운서동)개인<NA>인천광역시 중구 영종대로 108, 비2빌 202호 (운서동)2020-06-152021-09-10
23PHMB520203490019042500006우광크린우광크린우광크린인천광역시 중구 참외전로 8 (송월동1가)개인<NA>인천광역시 중구 참외전로 8 (송월동1가)2020-06-152021-09-10
34PHMB520203490019042500004아이크린 홈케어아이크린 홈케어아이크린 홈케어인천광역시 중구 영종대로196번길 19, 지엘플렉스1 327호 (운서동)개인<NA>인천광역시 중구 백운로107번길 24-12 (운남동)2020-05-192021-09-10
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