Overview

Dataset statistics

Number of variables11
Number of observations73
Missing cells7
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.6 KiB
Average record size in memory92.8 B

Variable types

Text6
Numeric3
Categorical2

Dataset

Description대구광역시 달성군_기업체 현황에 대한 데이터로 달성군 관내 종업원 100인이상 기업체 현황 업체명, 종업원수, 생산품목, 전화번호, 팩스번호, 위도, 경동 등의 항목을 제공합니다.
Author대구광역시 달성군
URLhttps://www.data.go.kr/data/15006780/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
X좌표 is highly overall correlated with Y좌표 and 1 other fieldsHigh correlation
Y좌표 is highly overall correlated with X좌표 and 1 other fieldsHigh correlation
구분 is highly overall correlated with X좌표 and 1 other fieldsHigh correlation
팩스번호 has 7 (9.6%) missing valuesMissing

Reproduction

Analysis started2024-03-14 09:18:34.304772
Analysis finished2024-03-14 09:18:38.848720
Duration4.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

Distinct71
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size712.0 B
2024-03-14T18:18:39.569549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length8.3150685
Min length5

Characters and Unicode

Total characters607
Distinct characters132
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)94.5%

Sample

1st row(주)이수페타시스
2nd row(주)대동
3rd row이래에이엠에스(주)
4th row평화오일씰공업㈜
5th row에스트라오토모티브시스템
ValueCountFrequency (%)
주)아진피앤피 2
 
2.6%
주식회사 2
 
2.6%
삼우기업(주 2
 
2.6%
주)씨티알모빌리티 1
 
1.3%
현대모비스(주 1
 
1.3%
주)대주기계 1
 
1.3%
유한회사 1
 
1.3%
현대커민스엔진 1
 
1.3%
주)하이컨코리아 1
 
1.3%
주)대동모빌리티 1
 
1.3%
Other values (63) 63
82.9%
2024-03-14T18:18:40.645299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 69
 
11.4%
( 65
 
10.7%
) 65
 
10.7%
이 24
 
4.0%
대 18
 
3.0%
스 18
 
3.0%
에 18
 
3.0%
아 10
 
1.6%
피 8
 
1.3%
업 8
 
1.3%
Other values (122) 304
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 471
77.6%
Open Punctuation 65
 
10.7%
Close Punctuation 65
 
10.7%
Space Separator 3
 
0.5%
Other Punctuation 2
 
0.3%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 69
 
14.6%
이 24
 
5.1%
대 18
 
3.8%
스 18
 
3.8%
에 18
 
3.8%
아 10
 
2.1%
피 8
 
1.7%
업 8
 
1.7%
금 7
 
1.5%
티 7
 
1.5%
Other values (117) 284
60.3%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 472
77.8%
Common 135
 
22.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 69
 
14.6%
이 24
 
5.1%
대 18
 
3.8%
스 18
 
3.8%
에 18
 
3.8%
아 10
 
2.1%
피 8
 
1.7%
업 8
 
1.7%
금 7
 
1.5%
티 7
 
1.5%
Other values (118) 285
60.4%
Common
ValueCountFrequency (%)
( 65
48.1%
) 65
48.1%
3
 
2.2%
. 2
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 471
77.6%
ASCII 135
 
22.2%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 69
 
14.6%
이 24
 
5.1%
대 18
 
3.8%
스 18
 
3.8%
에 18
 
3.8%
아 10
 
2.1%
피 8
 
1.7%
업 8
 
1.7%
금 7
 
1.5%
티 7
 
1.5%
Other values (117) 284
60.3%
ASCII
ValueCountFrequency (%)
( 65
48.1%
) 65
48.1%
3
 
2.2%
. 2
 
1.5%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지주소
Text

Distinct70
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size712.0 B
2024-03-14T18:18:41.670418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length34
Mean length24.465753
Min length21

Characters and Unicode

Total characters1786
Distinct characters70
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)91.8%

Sample

1st row대구광역시 달성군 논공읍 논공로53길 36
2nd row대구광역시 달성군 논공읍 북리 1-12번지
3rd row대구광역시 달성군 논공읍 논공로 664
4th row대구광역시 달성군 논공읍 논공중앙로51길 42 (총 3 필지)
5th row대구광역시 달성군 논공읍 논공로 664, 외 25필지
ValueCountFrequency (%)
대구광역시 73
19.3%
달성군 73
19.3%
논공읍 28
 
7.4%
구지면 18
 
4.8%
유가읍 11
 
2.9%
다사읍 11
 
2.9%
논공로 6
 
1.6%
10 5
 
1.3%
논공중앙로 5
 
1.3%
세천로1길 4
 
1.1%
Other values (104) 144
38.1%
2024-03-14T18:18:43.024889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
306
 
17.1%
구 91
 
5.1%
대 82
 
4.6%
성 79
 
4.4%
달 78
 
4.4%
역 73
 
4.1%
시 73
 
4.1%
광 73
 
4.1%
군 73
 
4.1%
1 66
 
3.7%
Other values (60) 792
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1177
65.9%
Space Separator 306
 
17.1%
Decimal Number 281
 
15.7%
Dash Punctuation 9
 
0.5%
Uppercase Letter 5
 
0.3%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 91
 
7.7%
대 82
 
7.0%
성 79
 
6.7%
달 78
 
6.6%
역 73
 
6.2%
시 73
 
6.2%
광 73
 
6.2%
군 73
 
6.2%
로 65
 
5.5%
공 53
 
4.5%
Other values (40) 437
37.1%
Decimal Number
ValueCountFrequency (%)
1 66
23.5%
3 41
14.6%
4 28
10.0%
0 27
9.6%
2 27
9.6%
7 24
 
8.5%
5 22
 
7.8%
6 21
 
7.5%
9 17
 
6.0%
8 8
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
Y 1
20.0%
M 1
20.0%
L 1
20.0%
B 1
20.0%
P 1
20.0%
Space Separator
ValueCountFrequency (%)
306
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1177
65.9%
Common 604
33.8%
Latin 5
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 91
 
7.7%
대 82
 
7.0%
성 79
 
6.7%
달 78
 
6.6%
역 73
 
6.2%
시 73
 
6.2%
광 73
 
6.2%
군 73
 
6.2%
로 65
 
5.5%
공 53
 
4.5%
Other values (40) 437
37.1%
Common
ValueCountFrequency (%)
306
50.7%
1 66
 
10.9%
3 41
 
6.8%
4 28
 
4.6%
0 27
 
4.5%
2 27
 
4.5%
7 24
 
4.0%
5 22
 
3.6%
6 21
 
3.5%
9 17
 
2.8%
Other values (5) 25
 
4.1%
Latin
ValueCountFrequency (%)
Y 1
20.0%
M 1
20.0%
L 1
20.0%
B 1
20.0%
P 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1177
65.9%
ASCII 609
34.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
306
50.2%
1 66
 
10.8%
3 41
 
6.7%
4 28
 
4.6%
0 27
 
4.4%
2 27
 
4.4%
7 24
 
3.9%
5 22
 
3.6%
6 21
 
3.4%
9 17
 
2.8%
Other values (10) 30
 
4.9%
Hangul
ValueCountFrequency (%)
구 91
 
7.7%
대 82
 
7.0%
성 79
 
6.7%
달 78
 
6.6%
역 73
 
6.2%
시 73
 
6.2%
광 73
 
6.2%
군 73
 
6.2%
로 65
 
5.5%
공 53
 
4.5%
Other values (40) 437
37.1%

생산품목
Text

Distinct65
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size712.0 B
2024-03-14T18:18:43.745901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length8.4246575
Min length2

Characters and Unicode

Total characters615
Distinct characters185
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)82.2%

Sample

1st row인쇄회로기판(PCB)
2nd row콤바인,트랙터,경운기
3rd row자동차부품
4th row오일씰,오링
5th row카에어컨,컴프레샤,엑슬,브레이크
ValueCountFrequency (%)
자동차부품 5
 
6.5%
골판지 2
 
2.6%
모터,인버터,iccu 2
 
2.6%
2차전지 2
 
2.6%
오일씰,오링 2
 
2.6%
등 2
 
2.6%
건설장비,발전용디젤엔진 1
 
1.3%
자동차용부품 1
 
1.3%
종이 1
 
1.3%
전기차충전기,머시닝센터 1
 
1.3%
Other values (58) 58
75.3%
2024-03-14T18:18:44.825224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 36
 
5.9%
동 21
 
3.4%
차 21
 
3.4%
품 19
 
3.1%
자 18
 
2.9%
기 16
 
2.6%
부 15
 
2.4%
이 13
 
2.1%
스 13
 
2.1%
전 13
 
2.1%
Other values (175) 430
69.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 538
87.5%
Other Punctuation 36
 
5.9%
Uppercase Letter 27
 
4.4%
Space Separator 8
 
1.3%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Decimal Number 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 21
 
3.9%
차 21
 
3.9%
품 19
 
3.5%
자 18
 
3.3%
기 16
 
3.0%
부 15
 
2.8%
이 13
 
2.4%
스 13
 
2.4%
전 13
 
2.4%
용 12
 
2.2%
Other values (156) 377
70.1%
Uppercase Letter
ValueCountFrequency (%)
C 6
22.2%
U 3
11.1%
I 3
11.1%
B 2
 
7.4%
L 2
 
7.4%
S 2
 
7.4%
T 2
 
7.4%
P 1
 
3.7%
M 1
 
3.7%
O 1
 
3.7%
Other values (4) 4
14.8%
Other Punctuation
ValueCountFrequency (%)
, 36
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Decimal Number
ValueCountFrequency (%)
2 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 538
87.5%
Common 50
 
8.1%
Latin 27
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 21
 
3.9%
차 21
 
3.9%
품 19
 
3.5%
자 18
 
3.3%
기 16
 
3.0%
부 15
 
2.8%
이 13
 
2.4%
스 13
 
2.4%
전 13
 
2.4%
용 12
 
2.2%
Other values (156) 377
70.1%
Latin
ValueCountFrequency (%)
C 6
22.2%
U 3
11.1%
I 3
11.1%
B 2
 
7.4%
L 2
 
7.4%
S 2
 
7.4%
T 2
 
7.4%
P 1
 
3.7%
M 1
 
3.7%
O 1
 
3.7%
Other values (4) 4
14.8%
Common
ValueCountFrequency (%)
, 36
72.0%
8
 
16.0%
) 2
 
4.0%
( 2
 
4.0%
2 2
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 538
87.5%
ASCII 77
 
12.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 36
46.8%
8
 
10.4%
C 6
 
7.8%
U 3
 
3.9%
I 3
 
3.9%
B 2
 
2.6%
L 2
 
2.6%
S 2
 
2.6%
) 2
 
2.6%
( 2
 
2.6%
Other values (9) 11
 
14.3%
Hangul
ValueCountFrequency (%)
동 21
 
3.9%
차 21
 
3.9%
품 19
 
3.5%
자 18
 
3.3%
기 16
 
3.0%
부 15
 
2.8%
이 13
 
2.4%
스 13
 
2.4%
전 13
 
2.4%
용 12
 
2.2%
Other values (156) 377
70.1%

대표자
Text

Distinct70
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size712.0 B
2024-03-14T18:18:46.034895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.6438356
Min length2

Characters and Unicode

Total characters266
Distinct characters101
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)91.8%

Sample

1st row최창복
2nd row김준식외1명
3rd row최칠선
4th row김성익외1명
5th rowZHANGWEI
ValueCountFrequency (%)
김주영 2
 
2.7%
정연욱외1명 2
 
2.7%
김준현 2
 
2.7%
이희화 1
 
1.4%
김완수 1
 
1.4%
최수안 1
 
1.4%
구자근 1
 
1.4%
최창복 1
 
1.4%
최우각외1명 1
 
1.4%
주현 1
 
1.4%
Other values (60) 60
82.2%
2024-03-14T18:18:47.301519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 21
 
7.9%
명 15
 
5.6%
외 14
 
5.3%
1 14
 
5.3%
이 11
 
4.1%
현 8
 
3.0%
영 7
 
2.6%
정 7
 
2.6%
최 6
 
2.3%
준 6
 
2.3%
Other values (91) 157
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
91.4%
Decimal Number 14
 
5.3%
Uppercase Letter 8
 
3.0%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 21
 
8.6%
명 15
 
6.2%
외 14
 
5.8%
이 11
 
4.5%
현 8
 
3.3%
영 7
 
2.9%
정 7
 
2.9%
최 6
 
2.5%
준 6
 
2.5%
호 6
 
2.5%
Other values (81) 142
58.4%
Uppercase Letter
ValueCountFrequency (%)
Z 1
12.5%
H 1
12.5%
A 1
12.5%
N 1
12.5%
G 1
12.5%
W 1
12.5%
E 1
12.5%
I 1
12.5%
Decimal Number
ValueCountFrequency (%)
1 14
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 243
91.4%
Common 15
 
5.6%
Latin 8
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 21
 
8.6%
명 15
 
6.2%
외 14
 
5.8%
이 11
 
4.5%
현 8
 
3.3%
영 7
 
2.9%
정 7
 
2.9%
최 6
 
2.5%
준 6
 
2.5%
호 6
 
2.5%
Other values (81) 142
58.4%
Latin
ValueCountFrequency (%)
Z 1
12.5%
H 1
12.5%
A 1
12.5%
N 1
12.5%
G 1
12.5%
W 1
12.5%
E 1
12.5%
I 1
12.5%
Common
ValueCountFrequency (%)
1 14
93.3%
1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 243
91.4%
ASCII 23
 
8.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 21
 
8.6%
명 15
 
6.2%
외 14
 
5.8%
이 11
 
4.5%
현 8
 
3.3%
영 7
 
2.9%
정 7
 
2.9%
최 6
 
2.5%
준 6
 
2.5%
호 6
 
2.5%
Other values (81) 142
58.4%
ASCII
ValueCountFrequency (%)
1 14
60.9%
1
 
4.3%
Z 1
 
4.3%
H 1
 
4.3%
A 1
 
4.3%
N 1
 
4.3%
G 1
 
4.3%
W 1
 
4.3%
E 1
 
4.3%
I 1
 
4.3%

종업원수(명)
Real number (ℝ)

Distinct62
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean307.90411
Minimum100
Maximum2186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size785.0 B
2024-03-14T18:18:47.715179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile101
Q1120
median182
Q3288
95-th percentile942.8
Maximum2186
Range2086
Interquartile range (IQR)168

Descriptive statistics

Standard deviation342.86068
Coefficient of variation (CV)1.1135307
Kurtosis12.303436
Mean307.90411
Median Absolute Deviation (MAD)68
Skewness3.0832825
Sum22477
Variance117553.45
MonotonicityNot monotonic
2024-03-14T18:18:47.958346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 3
 
4.1%
120 2
 
2.7%
190 2
 
2.7%
250 2
 
2.7%
101 2
 
2.7%
102 2
 
2.7%
115 2
 
2.7%
127 2
 
2.7%
141 2
 
2.7%
150 2
 
2.7%
Other values (52) 52
71.2%
ValueCountFrequency (%)
100 3
4.1%
101 2
2.7%
102 2
2.7%
104 1
 
1.4%
106 1
 
1.4%
107 1
 
1.4%
109 1
 
1.4%
110 1
 
1.4%
111 1
 
1.4%
115 2
2.7%
ValueCountFrequency (%)
2186 1
1.4%
1206 1
1.4%
1048 1
1.4%
1043 1
1.4%
876 1
1.4%
864 1
1.4%
822 1
1.4%
819 1
1.4%
730 1
1.4%
654 1
1.4%

전화번호
Text

Distinct71
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size712.0 B
2024-03-14T18:18:48.810838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters876
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

Unique69 ?
Unique (%)94.5%

Sample

1st row053-610-0300
2nd row053-610-3032
3rd row053-610-2242
4th row053-610-9000
5th row053-610-2111
ValueCountFrequency (%)
053-610-9000 2
 
2.7%
053-670-1000 2
 
2.7%
053-605-3113 1
 
1.4%
053-584-1511 1
 
1.4%
053-582-2870 1
 
1.4%
053-611-1121 1
 
1.4%
053-608-3624 1
 
1.4%
054-770-7700 1
 
1.4%
053-582-6350 1
 
1.4%
053-601-7000 1
 
1.4%
Other values (61) 61
83.6%
2024-03-14T18:18:49.930561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 189
21.6%
- 146
16.7%
5 130
14.8%
1 109
12.4%
3 97
11.1%
6 61
 
7.0%
2 43
 
4.9%
7 39
 
4.5%
4 25
 
2.9%
8 24
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 730
83.3%
Dash Punctuation 146
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 189
25.9%
5 130
17.8%
1 109
14.9%
3 97
13.3%
6 61
 
8.4%
2 43
 
5.9%
7 39
 
5.3%
4 25
 
3.4%
8 24
 
3.3%
9 13
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 146
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 876
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 189
21.6%
- 146
16.7%
5 130
14.8%
1 109
12.4%
3 97
11.1%
6 61
 
7.0%
2 43
 
4.9%
7 39
 
4.5%
4 25
 
2.9%
8 24
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 876
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 189
21.6%
- 146
16.7%
5 130
14.8%
1 109
12.4%
3 97
11.1%
6 61
 
7.0%
2 43
 
4.9%
7 39
 
4.5%
4 25
 
2.9%
8 24
 
2.7%

팩스번호
Text

MISSING 

Distinct64
Distinct (%)97.0%
Missing7
Missing (%)9.6%
Memory size712.0 B
2024-03-14T18:18:50.797842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.015152
Min length12

Characters and Unicode

Total characters793
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

Unique62 ?
Unique (%)93.9%

Sample

1st row053-610-0401
2nd row053-615-1050
3rd row053-610-1700
4th row053-615-0456
5th row053-615-0786
ValueCountFrequency (%)
053-718-2400 2
 
3.0%
053-615-0456 2
 
3.0%
053-614-1274 1
 
1.5%
053-610-0401 1
 
1.5%
053-611-2230 1
 
1.5%
053-592-6559 1
 
1.5%
054-770-7770 1
 
1.5%
053-601-7009 1
 
1.5%
053-615-5862 1
 
1.5%
053-584-1512 1
 
1.5%
Other values (54) 54
81.8%
2024-03-14T18:18:52.175492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 133
16.8%
- 132
16.6%
0 128
16.1%
3 89
11.2%
1 76
9.6%
6 67
8.4%
7 43
 
5.4%
2 38
 
4.8%
4 33
 
4.2%
8 31
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 661
83.4%
Dash Punctuation 132
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 133
20.1%
0 128
19.4%
3 89
13.5%
1 76
11.5%
6 67
10.1%
7 43
 
6.5%
2 38
 
5.7%
4 33
 
5.0%
8 31
 
4.7%
9 23
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 132
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 793
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 133
16.8%
- 132
16.6%
0 128
16.1%
3 89
11.2%
1 76
9.6%
6 67
8.4%
7 43
 
5.4%
2 38
 
4.8%
4 33
 
4.2%
8 31
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 793
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 133
16.8%
- 132
16.6%
0 128
16.1%
3 89
11.2%
1 76
9.6%
6 67
8.4%
7 43
 
5.4%
2 38
 
4.8%
4 33
 
4.2%
8 31
 
3.9%

X좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.45177
Minimum128.39412
Maximum128.62611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size785.0 B
2024-03-14T18:18:52.426120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.39412
5-th percentile128.40596
Q1128.44318
median128.4571
Q3128.46613
95-th percentile128.47345
Maximum128.62611
Range0.2319863
Interquartile range (IQR)0.0229421

Descriptive statistics

Standard deviation0.029925646
Coefficient of variation (CV)0.00023297185
Kurtosis15.226099
Mean128.45177
Median Absolute Deviation (MAD)0.0093942
Skewness2.3081213
Sum9376.979
Variance0.00089554431
MonotonicityNot monotonic
2024-03-14T18:18:52.692829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.4557588 2
 
2.7%
128.4502362 2
 
2.7%
128.4477018 2
 
2.7%
128.4575379 2
 
2.7%
128.4573414 2
 
2.7%
128.4521743 1
 
1.4%
128.4156445 1
 
1.4%
128.626111 1
 
1.4%
128.450495 1
 
1.4%
128.4431848 1
 
1.4%
Other values (58) 58
79.5%
ValueCountFrequency (%)
128.3941247 1
1.4%
128.4035323 1
1.4%
128.4048405 1
1.4%
128.4052099 1
1.4%
128.4064672 1
1.4%
128.4088759 1
1.4%
128.4104403 1
1.4%
128.4134123 1
1.4%
128.4137052 1
1.4%
128.4140007 1
1.4%
ValueCountFrequency (%)
128.626111 1
1.4%
128.4765963 1
1.4%
128.4758867 1
1.4%
128.4737341 1
1.4%
128.4732683 1
1.4%
128.4723891 1
1.4%
128.4718519 1
1.4%
128.4700668 1
1.4%
128.4700205 1
1.4%
128.4696201 1
1.4%

Y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct68
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.724474
Minimum35.630163
Maximum35.880245
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size785.0 B
2024-03-14T18:18:52.966293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.630163
5-th percentile35.636529
Q135.668118
median35.730674
Q335.740272
95-th percentile35.876738
Maximum35.880245
Range0.25008214
Interquartile range (IQR)0.07215361

Descriptive statistics

Standard deviation0.074642589
Coefficient of variation (CV)0.0020893964
Kurtosis0.049058219
Mean35.724474
Median Absolute Deviation (MAD)0.05024538
Skewness0.95017024
Sum2607.8866
Variance0.005571516
MonotonicityNot monotonic
2024-03-14T18:18:53.407046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.68042845 2
 
2.7%
35.73353001 2
 
2.7%
35.67980979 2
 
2.7%
35.74027151 2
 
2.7%
35.7252738 2
 
2.7%
35.70293083 1
 
1.4%
35.64625925 1
 
1.4%
35.79889042 1
 
1.4%
35.6873437 1
 
1.4%
35.6681179 1
 
1.4%
Other values (58) 58
79.5%
ValueCountFrequency (%)
35.63016302 1
1.4%
35.63186732 1
1.4%
35.63250324 1
1.4%
35.63519988 1
1.4%
35.63741555 1
1.4%
35.64067749 1
1.4%
35.64566423 1
1.4%
35.64625925 1
1.4%
35.64656057 1
1.4%
35.64750491 1
1.4%
ValueCountFrequency (%)
35.88024516 1
1.4%
35.8792213 1
1.4%
35.87771873 1
1.4%
35.87739763 1
1.4%
35.87629822 1
1.4%
35.87457547 1
1.4%
35.87424536 1
1.4%
35.87356812 1
1.4%
35.87275925 1
1.4%
35.87221237 1
1.4%

구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Memory size712.0 B
논공읍
28 
구지면
18 
다사읍
11 
유가읍
11 
현풍읍
4 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)1.4%

Sample

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

Common Values

ValueCountFrequency (%)
논공읍 28
38.4%
구지면 18
24.7%
다사읍 11
 
15.1%
유가읍 11
 
15.1%
현풍읍 4
 
5.5%
가창면 1
 
1.4%

Length

2024-03-14T18:18:53.824867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:18:54.166672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
논공읍 28
38.4%
구지면 18
24.7%
다사읍 11
 
15.1%
유가읍 11
 
15.1%
현풍읍 4
 
5.5%
가창면 1
 
1.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size712.0 B
2024-02-26
73 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-26
2nd row2024-02-26
3rd row2024-02-26
4th row2024-02-26
5th row2024-02-26

Common Values

ValueCountFrequency (%)
2024-02-26 73
100.0%

Length

2024-03-14T18:18:54.570148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:18:54.885347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-26 73
100.0%

Interactions

2024-03-14T18:18:37.557898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:18:36.481817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:18:36.944241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:18:37.791560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:18:36.677670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:18:37.085116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:18:38.024792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:18:36.812446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:18:37.323612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T18:18:55.081681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명소재지주소생산품목대표자종업원수(명)전화번호팩스번호X좌표Y좌표구분
업체명1.0000.9850.9991.0001.0000.9990.9940.4460.8810.412
소재지주소0.9851.0000.9800.9860.9780.9850.9931.0001.0001.000
생산품목0.9990.9801.0000.9960.8790.9970.9940.8650.0000.858
대표자1.0000.9860.9961.0001.0000.9980.9930.8180.9480.828
종업원수(명)1.0000.9780.8791.0001.0000.9500.7760.6640.7780.623
전화번호0.9990.9850.9970.9980.9501.0000.9990.8690.9880.984
팩스번호0.9940.9930.9940.9930.7760.9991.0000.8870.9360.939
X좌표0.4461.0000.8650.8180.6640.8690.8871.0000.8510.849
Y좌표0.8811.0000.0000.9480.7780.9880.9360.8511.0000.937
구분0.4121.0000.8580.8280.6230.9840.9390.8490.9371.000
2024-03-14T18:18:55.392601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종업원수(명)X좌표Y좌표구분
종업원수(명)1.0000.0350.1130.429
X좌표0.0351.0000.8340.754
Y좌표0.1130.8341.0000.866
구분0.4290.7540.8661.000

Missing values

2024-03-14T18:18:38.367903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:18:38.744860image/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

업체명소재지주소생산품목대표자종업원수(명)전화번호팩스번호X좌표Y좌표구분데이터기준일자
0(주)이수페타시스대구광역시 달성군 논공읍 논공로53길 36인쇄회로기판(PCB)최창복1048053-610-0300053-610-0401128.45225735.738994논공읍2024-02-26
1(주)대동대구광역시 달성군 논공읍 북리 1-12번지콤바인,트랙터,경운기김준식외1명1043053-610-3032053-615-1050128.45709635.730674논공읍2024-02-26
2이래에이엠에스(주)대구광역시 달성군 논공읍 논공로 664자동차부품최칠선876053-610-2242053-610-1700128.45023635.73353논공읍2024-02-26
3평화오일씰공업㈜대구광역시 달성군 논공읍 논공중앙로51길 42 (총 3 필지)오일씰,오링김성익외1명864053-610-9000053-615-0456128.45882935.736039논공읍2024-02-26
4에스트라오토모티브시스템대구광역시 달성군 논공읍 논공로 664, 외 25필지카에어컨,컴프레샤,엑슬,브레이크ZHANGWEI819053-610-2111053-615-0786128.45023635.73353논공읍2024-02-26
5평화산업(주)대구광역시 달성군 논공읍 29-17번지호스류,전투용차량부품황순용외1명730053-610-7000053-615-0567128.46017935.738197논공읍2024-02-26
6상신브레이크(주)대구광역시 달성군 논공읍 논공중앙로33길 10 (총 4 필지) 외 3필지브레이크라이닝,슈어셈블리김효일654053-615-0101053-614-1708128.45394935.731308논공읍2024-02-26
7(주)남선알미늄대구광역시 달성군 논공읍 논공중앙로 288알미늄샷시박귀봉외1명450053-610-5200053-610-5228128.46630435.73629논공읍2024-02-26
8한국에스케이에프씰(주)대구광역시 달성군 논공읍 논공중앙로45길 40오일씰,오링허용수외1명370053-615-1001053-615-1006128.45846535.736158논공읍2024-02-26
9(주)샤니대구광역시 달성군 논공읍 논공중앙로54길 7빵류이강섭342053-610-1109053-615-0924128.46558735.734715논공읍2024-02-26
업체명소재지주소생산품목대표자종업원수(명)전화번호팩스번호X좌표Y좌표구분데이터기준일자
63(주)와이.엠.피대구광역시 달성군 구지면 달성2차동1로 46 (YMP)자동차차체용부품최석종135053-352-3323<NA>128.4207135.6352구지면2024-02-26
64(주)금성정공대구광역시 달성군 구지면 국가산단대로33길 70자동차부품(램프,공조부품)김도형130053-582-5011053-581-5015128.4104435.645664구지면2024-02-26
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