Overview

Dataset statistics

Number of variables11
Number of observations26
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory96.1 B

Variable types

Numeric3
Categorical3
Text4
DateTime1

Dataset

Description대구광역시 중구 자치구 내 소독업체 현황 대한 데이터로 소독업소명칭, 사무실소재지, 전화번호 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15080730/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
경도 is highly overall correlated with 행정동High correlation
행정동 is highly overall correlated with 경도High correlation
영업소전화번호 has 1 (3.8%) missing valuesMissing
순번 has unique valuesUnique
신고번호 has unique valuesUnique
소독업소명칭 has unique valuesUnique
사무실소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:06:40.262307
Analysis finished2023-12-12 15:06:41.604758
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T00:06:41.666988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2023-12-13T00:06:41.800293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
대구광역시
26 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 26
100.0%

Length

2023-12-13T00:06:41.913476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:06:42.030839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 26
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size340.0 B
중구
26 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 26
100.0%

Length

2023-12-13T00:06:42.130144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:06:42.226398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 26
100.0%

행정동
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)38.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
성내2동
6 
남산1동
4 
대봉1동
4 
성내3동
3 
남산2동
3 
Other values (5)
6 

Length

Max length4
Median length4
Mean length3.8461538
Min length3

Unique

Unique4 ?
Unique (%)15.4%

Sample

1st row남산1동
2nd row성내3동
3rd row남산1동
4th row성내2동
5th row동인동

Common Values

ValueCountFrequency (%)
성내2동 6
23.1%
남산1동 4
15.4%
대봉1동 4
15.4%
성내3동 3
11.5%
남산2동 3
11.5%
동인동 2
 
7.7%
삼덕동 1
 
3.8%
대봉2동 1
 
3.8%
남산3동 1
 
3.8%
대신동 1
 
3.8%

Length

2023-12-13T00:06:42.336186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:06:42.462558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
성내2동 6
23.1%
남산1동 4
15.4%
대봉1동 4
15.4%
성내3동 3
11.5%
남산2동 3
11.5%
동인동 2
 
7.7%
삼덕동 1
 
3.8%
대봉2동 1
 
3.8%
남산3동 1
 
3.8%
대신동 1
 
3.8%

신고번호
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T00:06:42.673663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters650
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

Unique26 ?
Unique (%)100.0%

Sample

1st rowPHMB520223410023042500002
2nd rowPHMB520223410023042500001
3rd rowPHMB520213410023042500004
4th rowPHMB520213410023042500002
5th rowPHMB520203410023042500006
ValueCountFrequency (%)
phmb520223410023042500002 1
 
3.8%
phmb520223410023042500001 1
 
3.8%
phmb519993410023042500002 1
 
3.8%
phmb519993410023042500001 1
 
3.8%
phmb519993410023042500004 1
 
3.8%
phmb520053410023042500001 1
 
3.8%
phmb520203410023042500007 1
 
3.8%
phmb520113410023042500005 1
 
3.8%
phmb520193410023042500004 1
 
3.8%
phmb520163410023042500003 1
 
3.8%
Other values (16) 16
61.5%
2023-12-13T00:06:43.013453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 212
32.6%
2 94
14.5%
5 57
 
8.8%
4 56
 
8.6%
3 55
 
8.5%
1 49
 
7.5%
P 26
 
4.0%
H 26
 
4.0%
M 26
 
4.0%
B 26
 
4.0%
Other values (4) 23
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 546
84.0%
Uppercase Letter 104
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 212
38.8%
2 94
17.2%
5 57
 
10.4%
4 56
 
10.3%
3 55
 
10.1%
1 49
 
9.0%
9 15
 
2.7%
6 4
 
0.7%
8 2
 
0.4%
7 2
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
P 26
25.0%
H 26
25.0%
M 26
25.0%
B 26
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 546
84.0%
Latin 104
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 212
38.8%
2 94
17.2%
5 57
 
10.4%
4 56
 
10.3%
3 55
 
10.1%
1 49
 
9.0%
9 15
 
2.7%
6 4
 
0.7%
8 2
 
0.4%
7 2
 
0.4%
Latin
ValueCountFrequency (%)
P 26
25.0%
H 26
25.0%
M 26
25.0%
B 26
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 650
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 212
32.6%
2 94
14.5%
5 57
 
8.8%
4 56
 
8.6%
3 55
 
8.5%
1 49
 
7.5%
P 26
 
4.0%
H 26
 
4.0%
M 26
 
4.0%
B 26
 
4.0%
Other values (4) 23
 
3.5%

신고일자
Date

Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
Minimum1987-03-02 00:00:00
Maximum2022-06-10 00:00:00
2023-12-13T00:06:43.501431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:43.656590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

소독업소명칭
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T00:06:43.907101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length11.5
Mean length8.6153846
Min length4

Characters and Unicode

Total characters224
Distinct characters91
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

Unique26 ?
Unique (%)100.0%

Sample

1st row남문올래협동조합
2nd row에코환경
3rd row온라이프 생활방역
4th row주식회사 대경티엠에스
5th row버그닥터스
ValueCountFrequency (%)
대구지사 2
 
5.6%
주식회사 2
 
5.6%
대구광역시지체장애인협회 2
 
5.6%
남문올래협동조합 1
 
2.8%
케어원 1
 
2.8%
주)티에스글로벌 1
 
2.8%
숙박방역 1
 
2.8%
주)대성공사 1
 
2.8%
페스콤방역 1
 
2.8%
지에스종합관리 1
 
2.8%
Other values (23) 23
63.9%
2023-12-13T00:06:44.316138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 11
 
4.9%
10
 
4.5%
사 10
 
4.5%
) 9
 
4.0%
대 9
 
4.0%
( 9
 
4.0%
스 9
 
4.0%
역 8
 
3.6%
에 6
 
2.7%
방 6
 
2.7%
Other values (81) 137
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 193
86.2%
Space Separator 10
 
4.5%
Close Punctuation 9
 
4.0%
Open Punctuation 9
 
4.0%
Decimal Number 3
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 11
 
5.7%
사 10
 
5.2%
대 9
 
4.7%
스 9
 
4.7%
역 8
 
4.1%
에 6
 
3.1%
방 6
 
3.1%
지 6
 
3.1%
구 5
 
2.6%
리 4
 
2.1%
Other values (76) 119
61.7%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Space Separator
ValueCountFrequency (%)
10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 193
86.2%
Common 31
 
13.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 11
 
5.7%
사 10
 
5.2%
대 9
 
4.7%
스 9
 
4.7%
역 8
 
4.1%
에 6
 
3.1%
방 6
 
3.1%
지 6
 
3.1%
구 5
 
2.6%
리 4
 
2.1%
Other values (76) 119
61.7%
Common
ValueCountFrequency (%)
10
32.3%
) 9
29.0%
( 9
29.0%
1 2
 
6.5%
9 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 193
86.2%
ASCII 31
 
13.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 11
 
5.7%
사 10
 
5.2%
대 9
 
4.7%
스 9
 
4.7%
역 8
 
4.1%
에 6
 
3.1%
방 6
 
3.1%
지 6
 
3.1%
구 5
 
2.6%
리 4
 
2.1%
Other values (76) 119
61.7%
ASCII
ValueCountFrequency (%)
10
32.3%
) 9
29.0%
( 9
29.0%
1 2
 
6.5%
9 1
 
3.2%

사무실소재지(도로명)
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T00:06:44.577460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length32.5
Mean length31.807692
Min length23

Characters and Unicode

Total characters827
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

Unique26 ?
Unique (%)100.0%

Sample

1st row대구광역시 중구 중앙대로 289-36, 남산동커뮤니티센터 (남산동)
2nd row대구광역시 중구 태평로 17, 부광빌딩 204호 (달성동)
3rd row대구광역시 중구 중앙대로66길 13-2, 201호 (남산동)
4th row대구광역시 중구 서성로 20, 대구매일신문사,대구은행계산동지점 (계산동2가)
5th row대구광역시 중구 국채보상로 726, 강남빌딩 2층 281호 (동인동4가)
ValueCountFrequency (%)
대구광역시 26
 
15.7%
중구 26
 
15.7%
남산동 8
 
4.8%
대봉동 5
 
3.0%
3층 3
 
1.8%
동덕로 3
 
1.8%
달구벌대로 3
 
1.8%
2층 3
 
1.8%
20 2
 
1.2%
4층 2
 
1.2%
Other values (75) 85
51.2%
2023-12-13T00:06:44.938068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
140
 
16.9%
구 58
 
7.0%
대 41
 
5.0%
1 32
 
3.9%
동 32
 
3.9%
광 28
 
3.4%
중 28
 
3.4%
2 27
 
3.3%
( 26
 
3.1%
) 26
 
3.1%
Other values (89) 389
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 470
56.8%
Space Separator 140
 
16.9%
Decimal Number 138
 
16.7%
Open Punctuation 26
 
3.1%
Close Punctuation 26
 
3.1%
Other Punctuation 22
 
2.7%
Dash Punctuation 5
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 58
 
12.3%
대 41
 
8.7%
동 32
 
6.8%
광 28
 
6.0%
중 28
 
6.0%
시 26
 
5.5%
역 26
 
5.5%
로 25
 
5.3%
산 14
 
3.0%
층 13
 
2.8%
Other values (74) 179
38.1%
Decimal Number
ValueCountFrequency (%)
1 32
23.2%
2 27
19.6%
0 17
12.3%
4 13
9.4%
3 12
 
8.7%
8 9
 
6.5%
6 9
 
6.5%
5 8
 
5.8%
7 6
 
4.3%
9 5
 
3.6%
Space Separator
ValueCountFrequency (%)
140
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 470
56.8%
Common 357
43.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 58
 
12.3%
대 41
 
8.7%
동 32
 
6.8%
광 28
 
6.0%
중 28
 
6.0%
시 26
 
5.5%
역 26
 
5.5%
로 25
 
5.3%
산 14
 
3.0%
층 13
 
2.8%
Other values (74) 179
38.1%
Common
ValueCountFrequency (%)
140
39.2%
1 32
 
9.0%
2 27
 
7.6%
( 26
 
7.3%
) 26
 
7.3%
, 22
 
6.2%
0 17
 
4.8%
4 13
 
3.6%
3 12
 
3.4%
8 9
 
2.5%
Other values (5) 33
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 470
56.8%
ASCII 357
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
140
39.2%
1 32
 
9.0%
2 27
 
7.6%
( 26
 
7.3%
) 26
 
7.3%
, 22
 
6.2%
0 17
 
4.8%
4 13
 
3.6%
3 12
 
3.4%
8 9
 
2.5%
Other values (5) 33
 
9.2%
Hangul
ValueCountFrequency (%)
구 58
 
12.3%
대 41
 
8.7%
동 32
 
6.8%
광 28
 
6.0%
중 28
 
6.0%
시 26
 
5.5%
역 26
 
5.5%
로 25
 
5.3%
산 14
 
3.0%
층 13
 
2.8%
Other values (74) 179
38.1%

위도
Real number (ℝ)

Distinct22
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.866494
Minimum35.856844
Maximum35.878141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T00:06:45.041321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.856844
5-th percentile35.858008
Q135.860456
median35.865023
Q335.871815
95-th percentile35.877392
Maximum35.878141
Range0.0212968
Interquartile range (IQR)0.011358763

Descriptive statistics

Standard deviation0.006425826
Coefficient of variation (CV)0.00017915958
Kurtosis-1.0976079
Mean35.866494
Median Absolute Deviation (MAD)0.005245415
Skewness0.26998288
Sum932.52885
Variance4.129124 × 10-5
MonotonicityNot monotonic
2023-12-13T00:06:45.133528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
35.86846151 2
 
7.7%
35.86495081 2
 
7.7%
35.86037624 2
 
7.7%
35.87814113 2
 
7.7%
35.85983364 1
 
3.8%
35.87514484 1
 
3.8%
35.87196137 1
 
3.8%
35.87248595 1
 
3.8%
35.86069619 1
 
3.8%
35.85937687 1
 
3.8%
Other values (12) 12
46.2%
ValueCountFrequency (%)
35.85684433 1
3.8%
35.85755166 1
3.8%
35.85937687 1
3.8%
35.85942639 1
3.8%
35.85983364 1
3.8%
35.86037624 2
7.7%
35.86069619 1
3.8%
35.86209248 1
3.8%
35.86266546 1
3.8%
35.86463146 1
3.8%
ValueCountFrequency (%)
35.87814113 2
7.7%
35.87514484 1
3.8%
35.87376983 1
3.8%
35.8733431 1
3.8%
35.87248595 1
3.8%
35.87196137 1
3.8%
35.87137585 1
3.8%
35.87032447 1
3.8%
35.86846151 2
7.7%
35.86836727 1
3.8%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.59277
Minimum128.58011
Maximum128.60987
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T00:06:45.222872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.58011
5-th percentile128.58027
Q1128.58668
median128.59006
Q3128.60111
95-th percentile128.60735
Maximum128.60987
Range0.0297604
Interquartile range (IQR)0.0144328

Descriptive statistics

Standard deviation0.0088673013
Coefficient of variation (CV)6.8956452 × 10-5
Kurtosis-0.94342915
Mean128.59277
Median Absolute Deviation (MAD)0.00553705
Skewness0.42030259
Sum3343.4121
Variance7.8629032 × 10-5
MonotonicityNot monotonic
2023-12-13T00:06:45.320756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
128.5873927 2
 
7.7%
128.5864809 2
 
7.7%
128.6037974 2
 
7.7%
128.5801106 2
 
7.7%
128.5896762 1
 
3.8%
128.5883059 1
 
3.8%
128.6085254 1
 
3.8%
128.5846207 1
 
3.8%
128.5956948 1
 
3.8%
128.6017857 1
 
3.8%
Other values (12) 12
46.2%
ValueCountFrequency (%)
128.5801106 2
7.7%
128.5807289 1
3.8%
128.5842726 1
3.8%
128.5846207 1
3.8%
128.5864809 2
7.7%
128.5872757 1
3.8%
128.5873927 2
7.7%
128.5881784 1
3.8%
128.5883059 1
3.8%
128.5896762 1
3.8%
ValueCountFrequency (%)
128.609871 1
3.8%
128.6085254 1
3.8%
128.6038259 1
3.8%
128.6037974 2
7.7%
128.6026595 1
3.8%
128.6017857 1
3.8%
128.5990925 1
3.8%
128.5956948 1
3.8%
128.5945256 1
3.8%
128.5940334 1
3.8%

영업소전화번호
Text

MISSING 

Distinct23
Distinct (%)92.0%
Missing1
Missing (%)3.8%
Memory size340.0 B
2023-12-13T00:06:45.482854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.8
Min length9

Characters and Unicode

Total characters295
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)84.0%

Sample

1st row053-428-8788
2nd row053-256-8088
3rd row053-253-2546
4th row1833-5821
5th row053-257-6866
ValueCountFrequency (%)
053-257-6866 2
 
8.0%
053-954-0170 2
 
8.0%
053-428-1119 1
 
4.0%
053-428-8788 1
 
4.0%
053-255-1600 1
 
4.0%
053-252-6855 1
 
4.0%
053-423-0337 1
 
4.0%
053-427-9898 1
 
4.0%
053-527-8885 1
 
4.0%
053-743-4888 1
 
4.0%
Other values (13) 13
52.0%
2023-12-13T00:06:45.837427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 48
16.3%
5 42
14.2%
0 41
13.9%
3 33
11.2%
8 25
8.5%
2 23
7.8%
6 22
7.5%
4 17
 
5.8%
7 15
 
5.1%
1 15
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 247
83.7%
Dash Punctuation 48
 
16.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 42
17.0%
0 41
16.6%
3 33
13.4%
8 25
10.1%
2 23
9.3%
6 22
8.9%
4 17
6.9%
7 15
 
6.1%
1 15
 
6.1%
9 14
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 295
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 48
16.3%
5 42
14.2%
0 41
13.9%
3 33
11.2%
8 25
8.5%
2 23
7.8%
6 22
7.5%
4 17
 
5.8%
7 15
 
5.1%
1 15
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 295
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 48
16.3%
5 42
14.2%
0 41
13.9%
3 33
11.2%
8 25
8.5%
2 23
7.8%
6 22
7.5%
4 17
 
5.8%
7 15
 
5.1%
1 15
 
5.1%

Interactions

2023-12-13T00:06:41.116177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:40.628159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:40.884781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:41.204936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:40.707753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:40.967554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:41.288499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:40.796627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:06:41.037764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:06:45.970919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동신고번호신고일자소독업소명칭사무실소재지(도로명)위도경도영업소전화번호
순번1.0000.6991.0001.0001.0001.0000.3020.3210.820
행정동0.6991.0001.0000.9591.0001.0000.6950.8831.000
신고번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
신고일자1.0000.9591.0001.0001.0001.0000.9620.0000.959
소독업소명칭1.0001.0001.0001.0001.0001.0001.0001.0001.000
사무실소재지(도로명)1.0001.0001.0001.0001.0001.0001.0001.0001.000
위도0.3020.6951.0000.9621.0001.0001.0000.3261.000
경도0.3210.8831.0000.0001.0001.0000.3261.0001.000
영업소전화번호0.8201.0001.0000.9591.0001.0001.0001.0001.000
2023-12-13T00:06:46.101723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번위도경도행정동
순번1.0000.2420.0000.000
위도0.2421.000-0.4980.373
경도0.000-0.4981.0000.572
행정동0.0000.3730.5721.000

Missing values

2023-12-13T00:06:41.404635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:06:41.548800image/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

순번시도명시군구명행정동신고번호신고일자소독업소명칭사무실소재지(도로명)위도경도영업소전화번호
01대구광역시중구남산1동PHMB5202234100230425000022022-06-10남문올래협동조합대구광역시 중구 중앙대로 289-36, 남산동커뮤니티센터 (남산동)35.859834128.589676053-428-8788
12대구광역시중구성내3동PHMB5202234100230425000012022-05-13에코환경대구광역시 중구 태평로 17, 부광빌딩 204호 (달성동)35.878141128.580111<NA>
23대구광역시중구남산1동PHMB5202134100230425000042021-06-11온라이프 생활방역대구광역시 중구 중앙대로66길 13-2, 201호 (남산동)35.862092128.594033053-256-8088
34대구광역시중구성내2동PHMB5202134100230425000022021-04-16주식회사 대경티엠에스대구광역시 중구 서성로 20, 대구매일신문사,대구은행계산동지점 (계산동2가)35.868462128.587393053-253-2546
45대구광역시중구동인동PHMB5202034100230425000062020-09-22버그닥터스대구광역시 중구 국채보상로 726, 강남빌딩 2층 281호 (동인동4가)35.868367128.6098711833-5821
56대구광역시중구남산2동PHMB5202034100230425000052020-07-22(주)유칼릭스 대구지점대구광역시 중구 달구벌대로 2034, 401호 (남산동)35.864951128.586481053-257-6866
67대구광역시중구남산1동PHMB5202034100230425000042020-05-25오늘의 방역대구광역시 중구 명덕로 221, 1층 85호 (남산동, 수도맨션아파트)35.856844128.5945261800-9286
78대구광역시중구성내2동PHMB5202034100230425000032020-04-20현대티엠에스(주)대구광역시 중구 서성로 20, 대구매일신문사 9층 905호 (계산동2가)35.868462128.587393053-559-6661
89대구광역시중구삼덕동PHMB5202034100230425000022020-03-30신천종합관리(주)대구광역시 중구 동덕로 115, 진석타워 15층 1503호 (삼덕동2가)35.865096128.602659053-429-6199
910대구광역시중구대봉1동PHMB5201934100230425000062019-09-04대구광역시지체장애인협회 장애인일자리사업소대구광역시 중구 동덕로 61, 선모빌딩 5층 (대봉동)35.860376128.603797053-954-0170
순번시도명시군구명행정동신고번호신고일자소독업소명칭사무실소재지(도로명)위도경도영업소전화번호
1617대구광역시중구성내2동PHMB5201634100230425000052016-11-09(주)대성공사대구광역시 중구 경상감영길 54 (서문로1가, 쌍용화재)35.871376128.590437053-424-1926
1718대구광역시중구성내2동PHMB5201634100230425000032016-08-12페스콤방역대구광역시 중구 서성로20길 7, 2층 (수창동)35.875145128.588306053-428-1119
1819대구광역시중구대봉1동PHMB5201934100230425000042015-07-24주식회사 케어원 대구지사대구광역시 중구 달구벌대로 2200, 3층 (대봉동)35.862665128.603826070-4870-3010
1920대구광역시중구대신동PHMB5201134100230425000052011-10-04지에스종합관리대구광역시 중구 달성공원로8길 10, 달성빌딩 3층 312호 (대신동)35.873343128.580729053-290-8373
2021대구광역시중구성내2동PHMB5202034100230425000072008-01-31(주)세루대구광역시 중구 국채보상로 488, 섬유회관 11층 1101호 (동산동)35.870324128.584273053-743-4888
2122대구광역시중구성내3동PHMB5200534100230425000012005-03-04(주)삼일이엔에스대구광역시 중구 태평로 17, 부광빌딩 206호 (달성동)35.878141128.580111053-527-8885
2223대구광역시중구대봉1동PHMB5199934100230425000041999-11-01한국종합관리(주)대구광역시 중구 대봉로 228-17 (대봉동)35.859377128.601786053-427-9898
2324대구광역시중구남산1동PHMB5199934100230425000011999-09-08덕우환경대구광역시 중구 명륜로 97-10, 3층 (남산동)35.860696128.595695053-423-0337
2425대구광역시중구성내3동PHMB5199934100230425000021999-09-08신라방역공사대구광역시 중구 북성로4길 34 (인교동)35.872486128.584621053-252-6855
2526대구광역시중구동인동PHMB5201934100230425000051987-03-02현대방역공사대구광역시 중구 국채보상로143길 69, 4층 (동인동3가)35.871961128.608525053-754-0265