Overview

Dataset statistics

Number of variables6
Number of observations418
Missing cells418
Missing cells (%)16.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory20.5 KiB
Average record size in memory50.3 B

Variable types

Text3
Categorical2
Numeric1

Dataset

Description대전광역시 관내 방역 및 소독업체 현황입니다(업체명, 시군구, 업체 소재지, 업체 대표자 등) 총 418개소 동구 57개소, 중구 88개소, 서구 139개소, 유성구 71개소(휴업1개소포함), 대덕구 63개소
Author대전광역시
URLhttps://www.data.go.kr/data/15080615/fileData.do

Alerts

Unnamed: 5 has constant value ""Constant
대표자(명) is highly imbalanced (87.4%)Imbalance
Unnamed: 5 has 417 (99.8%) missing valuesMissing

Reproduction

Analysis started2023-12-12 05:50:05.783747
Analysis finished2023-12-12 05:50:06.714155
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct417
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2023-12-12T14:50:06.901692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length7.4186603
Min length2

Characters and Unicode

Total characters3101
Distinct characters341
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

Unique416 ?
Unique (%)99.5%

Sample

1st row하얀종합클린
2nd row(주)천연살균의학처 청주
3rd row스탠다드
4th row케이인터내셔날
5th row(주)어벤져스
ValueCountFrequency (%)
주식회사 54
 
10.5%
주)세스코 3
 
0.6%
세상 3
 
0.6%
스마트맨 3
 
0.6%
사회적협동조합 3
 
0.6%
합자회사 3
 
0.6%
깨끗한세상 2
 
0.4%
대전지사 2
 
0.4%
사단법인 2
 
0.4%
어르신이 2
 
0.4%
Other values (436) 437
85.0%
2023-12-12T14:50:07.386588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 233
 
7.5%
) 161
 
5.2%
( 153
 
4.9%
사 116
 
3.7%
98
 
3.2%
회 85
 
2.7%
스 77
 
2.5%
식 76
 
2.5%
이 58
 
1.9%
린 57
 
1.8%
Other values (331) 1987
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2612
84.2%
Close Punctuation 161
 
5.2%
Open Punctuation 153
 
4.9%
Space Separator 98
 
3.2%
Uppercase Letter 58
 
1.9%
Decimal Number 11
 
0.4%
Lowercase Letter 4
 
0.1%
Other Punctuation 3
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 233
 
8.9%
사 116
 
4.4%
회 85
 
3.3%
스 77
 
2.9%
식 76
 
2.9%
이 58
 
2.2%
린 57
 
2.2%
에 54
 
2.1%
업 54
 
2.1%
대 51
 
2.0%
Other values (297) 1751
67.0%
Uppercase Letter
ValueCountFrequency (%)
E 8
13.8%
A 7
12.1%
O 4
 
6.9%
G 4
 
6.9%
S 4
 
6.9%
R 3
 
5.2%
I 3
 
5.2%
M 3
 
5.2%
B 3
 
5.2%
D 3
 
5.2%
Other values (10) 16
27.6%
Decimal Number
ValueCountFrequency (%)
5 4
36.4%
1 3
27.3%
3 2
18.2%
6 1
 
9.1%
9 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
o 2
50.0%
m 1
25.0%
z 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
· 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 161
100.0%
Open Punctuation
ValueCountFrequency (%)
( 153
100.0%
Space Separator
ValueCountFrequency (%)
98
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2613
84.3%
Common 426
 
13.7%
Latin 62
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 233
 
8.9%
사 116
 
4.4%
회 85
 
3.3%
스 77
 
2.9%
식 76
 
2.9%
이 58
 
2.2%
린 57
 
2.2%
에 54
 
2.1%
업 54
 
2.1%
대 51
 
2.0%
Other values (298) 1752
67.0%
Latin
ValueCountFrequency (%)
E 8
 
12.9%
A 7
 
11.3%
O 4
 
6.5%
G 4
 
6.5%
S 4
 
6.5%
R 3
 
4.8%
I 3
 
4.8%
M 3
 
4.8%
B 3
 
4.8%
D 3
 
4.8%
Other values (13) 20
32.3%
Common
ValueCountFrequency (%)
) 161
37.8%
( 153
35.9%
98
23.0%
5 4
 
0.9%
1 3
 
0.7%
3 2
 
0.5%
. 2
 
0.5%
6 1
 
0.2%
9 1
 
0.2%
· 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2612
84.2%
ASCII 487
 
15.7%
None 2
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 233
 
8.9%
사 116
 
4.4%
회 85
 
3.3%
스 77
 
2.9%
식 76
 
2.9%
이 58
 
2.2%
린 57
 
2.2%
에 54
 
2.1%
업 54
 
2.1%
대 51
 
2.0%
Other values (297) 1751
67.0%
ASCII
ValueCountFrequency (%)
) 161
33.1%
( 153
31.4%
98
20.1%
E 8
 
1.6%
A 7
 
1.4%
O 4
 
0.8%
G 4
 
0.8%
5 4
 
0.8%
S 4
 
0.8%
R 3
 
0.6%
Other values (22) 41
 
8.4%
None
ValueCountFrequency (%)
· 1
50.0%
㈜ 1
50.0%

시군구
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
서구
139 
중구
88 
유성구
71 
대덕구
63 
동구
57 

Length

Max length3
Median length2
Mean length2.3205742
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서구 139
33.3%
중구 88
21.1%
유성구 71
17.0%
대덕구 63
15.1%
동구 57
13.6%

Length

2023-12-12T14:50:07.535827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:50:07.689513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구 139
33.3%
중구 88
21.1%
유성구 71
17.0%
대덕구 63
15.1%
동구 57
13.6%

사무실 소재지
Text

Distinct409
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
2023-12-12T14:50:08.056517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length41
Mean length29.492823
Min length20

Characters and Unicode

Total characters12328
Distinct characters250
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique401 ?
Unique (%)95.9%

Sample

1st row대전광역시 동구 우암로295번길 13 (가양동)
2nd row대전광역시 동구 우암로195번길 20 (가양동)
3rd row대전광역시 동구 대전로867번길 52, 한밭오피스텔 602호 (삼성동)
4th row대전광역시 동구 동대전로284번길 57, 1층 (가양동)
5th row대전광역시 동구 동대전로256번길 8, 1층 (가양동)
ValueCountFrequency (%)
대전광역시 418
 
16.7%
서구 139
 
5.6%
중구 88
 
3.5%
유성구 71
 
2.8%
1층 65
 
2.6%
대덕구 63
 
2.5%
동구 56
 
2.2%
2층 52
 
2.1%
3층 28
 
1.1%
가양동 21
 
0.8%
Other values (733) 1496
59.9%
2023-12-12T14:50:08.679151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2081
 
16.9%
대 659
 
5.3%
동 546
 
4.4%
1 478
 
3.9%
전 460
 
3.7%
구 426
 
3.5%
광 419
 
3.4%
역 418
 
3.4%
시 418
 
3.4%
) 418
 
3.4%
Other values (240) 6005
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6968
56.5%
Space Separator 2081
 
16.9%
Decimal Number 2072
 
16.8%
Close Punctuation 418
 
3.4%
Open Punctuation 417
 
3.4%
Other Punctuation 296
 
2.4%
Dash Punctuation 58
 
0.5%
Uppercase Letter 16
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 659
 
9.5%
동 546
 
7.8%
전 460
 
6.6%
구 426
 
6.1%
광 419
 
6.0%
역 418
 
6.0%
시 418
 
6.0%
로 403
 
5.8%
길 211
 
3.0%
번 193
 
2.8%
Other values (216) 2815
40.4%
Decimal Number
ValueCountFrequency (%)
1 478
23.1%
2 285
13.8%
3 231
11.1%
0 197
9.5%
4 190
 
9.2%
5 167
 
8.1%
6 165
 
8.0%
7 130
 
6.3%
8 123
 
5.9%
9 106
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
B 5
31.2%
T 3
18.8%
K 3
18.8%
A 2
 
12.5%
F 1
 
6.2%
I 1
 
6.2%
S 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 295
99.7%
. 1
 
0.3%
Space Separator
ValueCountFrequency (%)
2081
100.0%
Close Punctuation
ValueCountFrequency (%)
) 418
100.0%
Open Punctuation
ValueCountFrequency (%)
( 417
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6968
56.5%
Common 5344
43.3%
Latin 16
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 659
 
9.5%
동 546
 
7.8%
전 460
 
6.6%
구 426
 
6.1%
광 419
 
6.0%
역 418
 
6.0%
시 418
 
6.0%
로 403
 
5.8%
길 211
 
3.0%
번 193
 
2.8%
Other values (216) 2815
40.4%
Common
ValueCountFrequency (%)
2081
38.9%
1 478
 
8.9%
) 418
 
7.8%
( 417
 
7.8%
, 295
 
5.5%
2 285
 
5.3%
3 231
 
4.3%
0 197
 
3.7%
4 190
 
3.6%
5 167
 
3.1%
Other values (7) 585
 
10.9%
Latin
ValueCountFrequency (%)
B 5
31.2%
T 3
18.8%
K 3
18.8%
A 2
 
12.5%
F 1
 
6.2%
I 1
 
6.2%
S 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6968
56.5%
ASCII 5360
43.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2081
38.8%
1 478
 
8.9%
) 418
 
7.8%
( 417
 
7.8%
, 295
 
5.5%
2 285
 
5.3%
3 231
 
4.3%
0 197
 
3.7%
4 190
 
3.5%
5 167
 
3.1%
Other values (14) 601
 
11.2%
Hangul
ValueCountFrequency (%)
대 659
 
9.5%
동 546
 
7.8%
전 460
 
6.6%
구 426
 
6.1%
광 419
 
6.0%
역 418
 
6.0%
시 418
 
6.0%
로 403
 
5.8%
길 211
 
3.0%
번 193
 
2.8%
Other values (216) 2815
40.4%

대표자(명)
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.4 KiB
1
406 
2
 
11
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 406
97.1%
2 11
 
2.6%
3 1
 
0.2%

Length

2023-12-12T14:50:08.856342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:50:09.033759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 406
97.1%
2 11
 
2.6%
3 1
 
0.2%

종사자(명)
Real number (ℝ)

Distinct15
Distinct (%)3.6%
Missing1
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean1.6906475
Minimum1
Maximum19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-12T14:50:09.176649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile4
Maximum19
Range18
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.0138305
Coefficient of variation (CV)1.1911593
Kurtosis32.681468
Mean1.6906475
Median Absolute Deviation (MAD)0
Skewness5.1984305
Sum705
Variance4.0555133
MonotonicityNot monotonic
2023-12-12T14:50:09.316811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 311
74.4%
2 54
 
12.9%
3 22
 
5.3%
4 11
 
2.6%
6 4
 
1.0%
5 4
 
1.0%
10 2
 
0.5%
13 2
 
0.5%
14 1
 
0.2%
19 1
 
0.2%
Other values (5) 5
 
1.2%
ValueCountFrequency (%)
1 311
74.4%
2 54
 
12.9%
3 22
 
5.3%
4 11
 
2.6%
5 4
 
1.0%
6 4
 
1.0%
7 1
 
0.2%
8 1
 
0.2%
9 1
 
0.2%
10 2
 
0.5%
ValueCountFrequency (%)
19 1
 
0.2%
18 1
 
0.2%
14 1
 
0.2%
13 2
0.5%
11 1
 
0.2%
10 2
0.5%
9 1
 
0.2%
8 1
 
0.2%
7 1
 
0.2%
6 4
1.0%

Unnamed: 5
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing417
Missing (%)99.8%
Memory size3.4 KiB
2023-12-12T14:50:09.454282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
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

Unique1 ?
Unique (%)100.0%

Sample

1st row휴업중
ValueCountFrequency (%)
휴업중 1
100.0%
2023-12-12T14:50:09.676163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
휴 1
33.3%
업 1
33.3%
중 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
휴 1
33.3%
업 1
33.3%
중 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
휴 1
33.3%
업 1
33.3%
중 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
휴 1
33.3%
업 1
33.3%
중 1
33.3%

Interactions

2023-12-12T14:50:06.248393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:50:09.760744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구대표자(명)종사자(명)
시군구1.0000.0950.132
대표자(명)0.0951.0000.078
종사자(명)0.1320.0781.000
2023-12-12T14:50:09.859190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대표자(명)시군구
대표자(명)1.0000.071
시군구0.0711.000
2023-12-12T14:50:09.933599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종사자(명)시군구대표자(명)
종사자(명)1.0000.0760.033
시군구0.0761.0000.071
대표자(명)0.0330.0711.000

Missing values

2023-12-12T14:50:06.401685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:50:06.533640image/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.
2023-12-12T14:50:06.662506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업소명시군구사무실 소재지대표자(명)종사자(명)Unnamed: 5
0하얀종합클린동구대전광역시 동구 우암로295번길 13 (가양동)11<NA>
1(주)천연살균의학처 청주동구대전광역시 동구 우암로195번길 20 (가양동)11<NA>
2스탠다드동구대전광역시 동구 대전로867번길 52, 한밭오피스텔 602호 (삼성동)11<NA>
3케이인터내셔날동구대전광역시 동구 동대전로284번길 57, 1층 (가양동)11<NA>
4(주)어벤져스동구대전광역시 동구 동대전로256번길 8, 1층 (가양동)11<NA>
5합동개발동구대전광역시 동구 현암로 13 (삼성동)11<NA>
6나래동구대전광역시 동구 합내로 46, 1층 (가양동)11<NA>
7(주)금화대한동구대전광역시 동구 소랑길 44, 1층 (삼성동)11<NA>
8그린F5동구대전광역시 동구 동대전로256번길 8, 1층 (가양동)11<NA>
9주식회사 에이치케이동구대전광역시 동구 흥룡로75번길 7 (가양동)11<NA>
업소명시군구사무실 소재지대표자(명)종사자(명)Unnamed: 5
408(주)동영대덕구대전광역시 대덕구 동서대로1761번길 1 (송촌동)11<NA>
409청인건설주식회사대덕구대전광역시 대덕구 대화1길 13 (대화동)14<NA>
410공영기업주식회사대덕구대전광역시 대덕구 벚꽃길 71 (평촌동)19<NA>
411주식회사유일종합관리대덕구대전광역시 대덕구 비래동로 44 (비래동)13<NA>
412포시즌환경주식회사대덕구대전광역시 대덕구 아리랑로 211 (법동)12<NA>
413주식회사크린뱅크코리아대덕구대전광역시 대덕구 계족로608번길 18, 1층 (법동)12<NA>
414투인시스템대덕구대전광역시 대덕구 대화로 160, 산업용재유통상가 3동 3층 307호 (대화동)12<NA>
415주식회사새한환경대덕구대전광역시 대덕구 비래동로24번길 4 (비래동)13<NA>
416주식회사엔코아대덕구대전광역시 대덕구 동춘당로15번길 15, 106동 1층 102호 (송촌동, 거상파크빌라)12<NA>
417한국보건공사대덕구대전광역시 대덕구 오정로42번길 61 (오정동)11<NA>