Overview

Dataset statistics

Number of variables7
Number of observations2018
Missing cells279
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory114.4 KiB
Average record size in memory58.1 B

Variable types

Numeric1
Text5
Categorical1

Dataset

Description경상남도 김해시 환경오염물질 배출시설 현황에 대한 데이터로 업체명,전화번호,도로명주소 등의 항목을 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15033435

Alerts

전화번호 has 277 (13.7%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:50:36.610822
Analysis finished2023-12-11 00:50:37.628673
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct2018
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1009.5
Minimum1
Maximum2018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.9 KiB
2023-12-11T09:50:37.709514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile101.85
Q1505.25
median1009.5
Q31513.75
95-th percentile1917.15
Maximum2018
Range2017
Interquartile range (IQR)1008.5

Descriptive statistics

Standard deviation582.69074
Coefficient of variation (CV)0.57720727
Kurtosis-1.2
Mean1009.5
Median Absolute Deviation (MAD)504.5
Skewness0
Sum2037171
Variance339528.5
MonotonicityStrictly increasing
2023-12-11T09:50:37.851946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1342 1
 
< 0.1%
1355 1
 
< 0.1%
1354 1
 
< 0.1%
1353 1
 
< 0.1%
1352 1
 
< 0.1%
1351 1
 
< 0.1%
1350 1
 
< 0.1%
1349 1
 
< 0.1%
1348 1
 
< 0.1%
Other values (2008) 2008
99.5%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2018 1
< 0.1%
2017 1
< 0.1%
2016 1
< 0.1%
2015 1
< 0.1%
2014 1
< 0.1%
2013 1
< 0.1%
2012 1
< 0.1%
2011 1
< 0.1%
2010 1
< 0.1%
2009 1
< 0.1%

업체명
Text

Distinct1758
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size15.9 KiB
2023-12-11T09:50:38.080019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length6.0956392
Min length2

Characters and Unicode

Total characters12301
Distinct characters487
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

Unique1509 ?
Unique (%)74.8%

Sample

1st row㈜중일옥사이드
2nd row㈜씨앤엠
3rd row아세아식품
4th row진례산업㈜
5th row김해축협배합사료공장
ValueCountFrequency (%)
주식회사 54
 
2.4%
2공장 16
 
0.7%
김해지점 14
 
0.6%
김해공장 12
 
0.5%
제2공장 11
 
0.5%
삼부정밀화학㈜ 4
 
0.2%
김해사업소 4
 
0.2%
㈜광신아이앤피 4
 
0.2%
김해시 4
 
0.2%
㈜세연에스씨에스 3
 
0.1%
Other values (1790) 2108
94.4%
2023-12-11T09:50:38.415715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 1189
 
9.7%
업 355
 
2.9%
이 347
 
2.8%
산 337
 
2.7%
스 276
 
2.2%
에 234
 
1.9%
성 219
 
1.8%
219
 
1.8%
동 190
 
1.5%
공 183
 
1.5%
Other values (477) 8752
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10306
83.8%
Other Symbol 1189
 
9.7%
Uppercase Letter 312
 
2.5%
Space Separator 219
 
1.8%
Decimal Number 76
 
0.6%
Open Punctuation 74
 
0.6%
Close Punctuation 74
 
0.6%
Other Punctuation 45
 
0.4%
Dash Punctuation 4
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 355
 
3.4%
이 347
 
3.4%
산 337
 
3.3%
스 276
 
2.7%
에 234
 
2.3%
성 219
 
2.1%
동 190
 
1.8%
공 183
 
1.8%
대 178
 
1.7%
사 172
 
1.7%
Other values (437) 7815
75.8%
Uppercase Letter
ValueCountFrequency (%)
C 34
 
10.9%
S 30
 
9.6%
E 30
 
9.6%
P 20
 
6.4%
T 19
 
6.1%
N 19
 
6.1%
R 18
 
5.8%
M 18
 
5.8%
O 16
 
5.1%
D 14
 
4.5%
Other values (12) 94
30.1%
Other Punctuation
ValueCountFrequency (%)
. 29
64.4%
& 11
 
24.4%
, 2
 
4.4%
\ 1
 
2.2%
/ 1
 
2.2%
: 1
 
2.2%
Decimal Number
ValueCountFrequency (%)
2 48
63.2%
1 16
 
21.1%
3 8
 
10.5%
5 2
 
2.6%
6 2
 
2.6%
Lowercase Letter
ValueCountFrequency (%)
n 1
50.0%
o 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1189
100.0%
Space Separator
ValueCountFrequency (%)
219
100.0%
Open Punctuation
ValueCountFrequency (%)
( 74
100.0%
Close Punctuation
ValueCountFrequency (%)
) 74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11495
93.4%
Common 492
 
4.0%
Latin 314
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 1189
 
10.3%
업 355
 
3.1%
이 347
 
3.0%
산 337
 
2.9%
스 276
 
2.4%
에 234
 
2.0%
성 219
 
1.9%
동 190
 
1.7%
공 183
 
1.6%
대 178
 
1.5%
Other values (438) 7987
69.5%
Latin
ValueCountFrequency (%)
C 34
 
10.8%
S 30
 
9.6%
E 30
 
9.6%
P 20
 
6.4%
T 19
 
6.1%
N 19
 
6.1%
R 18
 
5.7%
M 18
 
5.7%
O 16
 
5.1%
D 14
 
4.5%
Other values (14) 96
30.6%
Common
ValueCountFrequency (%)
219
44.5%
( 74
 
15.0%
) 74
 
15.0%
2 48
 
9.8%
. 29
 
5.9%
1 16
 
3.3%
& 11
 
2.2%
3 8
 
1.6%
- 4
 
0.8%
5 2
 
0.4%
Other values (5) 7
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10306
83.8%
None 1189
 
9.7%
ASCII 806
 
6.6%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 1189
100.0%
Hangul
ValueCountFrequency (%)
업 355
 
3.4%
이 347
 
3.4%
산 337
 
3.3%
스 276
 
2.7%
에 234
 
2.3%
성 219
 
2.1%
동 190
 
1.8%
공 183
 
1.8%
대 178
 
1.7%
사 172
 
1.7%
Other values (437) 7815
75.8%
ASCII
ValueCountFrequency (%)
219
27.2%
( 74
 
9.2%
) 74
 
9.2%
2 48
 
6.0%
C 34
 
4.2%
S 30
 
3.7%
E 30
 
3.7%
. 29
 
3.6%
P 20
 
2.5%
T 19
 
2.4%
Other values (29) 229
28.4%

전화번호
Text

MISSING 

Distinct1558
Distinct (%)89.5%
Missing277
Missing (%)13.7%
Memory size15.9 KiB
2023-12-11T09:50:38.648051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length12
Mean length12.005169
Min length11

Characters and Unicode

Total characters20901
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1399 ?
Unique (%)80.4%

Sample

1st row055-345-9911
2nd row055-330-5021
3rd row055-323-9910
4th row055-345-2600
5th row055-345-8844
ValueCountFrequency (%)
055-343-1491 4
 
0.2%
055-338-4920 4
 
0.2%
055-344-2052 4
 
0.2%
055-337-9297 3
 
0.2%
055-322-8321 3
 
0.2%
055-345-1615 3
 
0.2%
055-323-8181 3
 
0.2%
055-333-3311 3
 
0.2%
055-345-6570 3
 
0.2%
055-329-0490 3
 
0.2%
Other values (1548) 1708
98.1%
2023-12-11T09:50:39.000025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 4416
21.1%
- 3483
16.7%
3 3005
14.4%
0 2799
13.4%
2 1472
 
7.0%
4 1396
 
6.7%
1 1137
 
5.4%
6 936
 
4.5%
7 834
 
4.0%
8 746
 
3.6%
Other values (2) 677
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17417
83.3%
Dash Punctuation 3483
 
16.7%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4416
25.4%
3 3005
17.3%
0 2799
16.1%
2 1472
 
8.5%
4 1396
 
8.0%
1 1137
 
6.5%
6 936
 
5.4%
7 834
 
4.8%
8 746
 
4.3%
9 676
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 3483
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20901
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 4416
21.1%
- 3483
16.7%
3 3005
14.4%
0 2799
13.4%
2 1472
 
7.0%
4 1396
 
6.7%
1 1137
 
5.4%
6 936
 
4.5%
7 834
 
4.0%
8 746
 
3.6%
Other values (2) 677
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20901
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 4416
21.1%
- 3483
16.7%
3 3005
14.4%
0 2799
13.4%
2 1472
 
7.0%
4 1396
 
6.7%
1 1137
 
5.4%
6 936
 
4.5%
7 834
 
4.0%
8 746
 
3.6%
Other values (2) 677
 
3.2%

도로명주소
Text

Distinct1962
Distinct (%)97.3%
Missing2
Missing (%)0.1%
Memory size15.9 KiB
2023-12-11T09:50:39.243920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length35
Mean length25.344742
Min length15

Characters and Unicode

Total characters51095
Distinct characters137
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

Unique1910 ?
Unique (%)94.7%

Sample

1st row경상남도 김해시 진영읍 김해대로 94-11
2nd row경상남도 김해시 김해대로2635번길 29
3rd row경상남도 김해시 생림면 장재로520번안길 8
4th row경상남도 김해시 진례면 서부로476번길 34
5th row경상남도 김해시 한림면 고모로 775
ValueCountFrequency (%)
김해시 2018
20.5%
경상남도 2016
20.5%
한림면 496
 
5.0%
주촌면 283
 
2.9%
진례면 260
 
2.6%
생림면 222
 
2.3%
진영읍 218
 
2.2%
상동면 205
 
2.1%
서부로1499번길 80
 
0.8%
김해대로 71
 
0.7%
Other values (1511) 3971
40.4%
2023-12-11T09:50:39.610455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10395
20.3%
김 2378
 
4.7%
해 2378
 
4.7%
상 2324
 
4.5%
1 2161
 
4.2%
시 2019
 
4.0%
남 2017
 
3.9%
경 2016
 
3.9%
도 2016
 
3.9%
로 1976
 
3.9%
Other values (127) 21415
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28660
56.1%
Decimal Number 10898
 
21.3%
Space Separator 10395
 
20.3%
Dash Punctuation 1060
 
2.1%
Open Punctuation 22
 
< 0.1%
Close Punctuation 22
 
< 0.1%
Other Punctuation 21
 
< 0.1%
Uppercase Letter 17
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 2378
 
8.3%
해 2378
 
8.3%
상 2324
 
8.1%
시 2019
 
7.0%
남 2017
 
7.0%
경 2016
 
7.0%
도 2016
 
7.0%
로 1976
 
6.9%
면 1469
 
5.1%
길 1246
 
4.3%
Other values (108) 8821
30.8%
Decimal Number
ValueCountFrequency (%)
1 2161
19.8%
2 1416
13.0%
3 1194
11.0%
5 1070
9.8%
4 1058
9.7%
6 957
8.8%
9 957
8.8%
7 802
 
7.4%
0 680
 
6.2%
8 603
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
A 8
47.1%
C 5
29.4%
B 3
 
17.6%
L 1
 
5.9%
Space Separator
ValueCountFrequency (%)
10395
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1060
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Other Punctuation
ValueCountFrequency (%)
, 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28660
56.1%
Common 22418
43.9%
Latin 17
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 2378
 
8.3%
해 2378
 
8.3%
상 2324
 
8.1%
시 2019
 
7.0%
남 2017
 
7.0%
경 2016
 
7.0%
도 2016
 
7.0%
로 1976
 
6.9%
면 1469
 
5.1%
길 1246
 
4.3%
Other values (108) 8821
30.8%
Common
ValueCountFrequency (%)
10395
46.4%
1 2161
 
9.6%
2 1416
 
6.3%
3 1194
 
5.3%
5 1070
 
4.8%
- 1060
 
4.7%
4 1058
 
4.7%
6 957
 
4.3%
9 957
 
4.3%
7 802
 
3.6%
Other values (5) 1348
 
6.0%
Latin
ValueCountFrequency (%)
A 8
47.1%
C 5
29.4%
B 3
 
17.6%
L 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28658
56.1%
ASCII 22435
43.9%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10395
46.3%
1 2161
 
9.6%
2 1416
 
6.3%
3 1194
 
5.3%
5 1070
 
4.8%
- 1060
 
4.7%
4 1058
 
4.7%
6 957
 
4.3%
9 957
 
4.3%
7 802
 
3.6%
Other values (9) 1365
 
6.1%
Hangul
ValueCountFrequency (%)
김 2378
 
8.3%
해 2378
 
8.3%
상 2324
 
8.1%
시 2019
 
7.0%
남 2017
 
7.0%
경 2016
 
7.0%
도 2016
 
7.0%
로 1976
 
6.9%
면 1469
 
5.1%
길 1246
 
4.3%
Other values (107) 8819
30.8%
Compat Jamo
ValueCountFrequency (%)
ㄴ 2
100.0%

업종
Text

Distinct788
Distinct (%)39.0%
Missing0
Missing (%)0.0%
Memory size15.9 KiB
2023-12-11T09:50:39.828529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length41
Mean length12.462834
Min length1

Characters and Unicode

Total characters25150
Distinct characters316
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique476 ?
Unique (%)23.6%

Sample

1st row기초무기화합물제조
2nd row전동기및발전기제조업
3rd row식품제조
4th row스폰지제조업
5th row사료제조
ValueCountFrequency (%)
및 101
 
3.8%
지정외폐기물처리업 81
 
3.1%
외 64
 
2.4%
도장및기타피막처리업 61
 
2.3%
선박구성부분품제조업 53
 
2.0%
자동차종합수리업 45
 
1.7%
제조업 41
 
1.6%
그외기타자동차부품제조업 39
 
1.5%
지정외폐기물처리업(38210 32
 
1.2%
금속열처리업 28
 
1.1%
Other values (889) 2094
79.3%
2023-12-11T09:50:40.156832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 1854
 
7.4%
제 1752
 
7.0%
조 1400
 
5.6%
기 987
 
3.9%
품 757
 
3.0%
2 688
 
2.7%
672
 
2.7%
및 572
 
2.3%
타 542
 
2.2%
리 516
 
2.1%
Other values (306) 15410
61.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20869
83.0%
Decimal Number 2451
 
9.7%
Space Separator 672
 
2.7%
Open Punctuation 455
 
1.8%
Close Punctuation 452
 
1.8%
Other Punctuation 251
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1854
 
8.9%
제 1752
 
8.4%
조 1400
 
6.7%
기 987
 
4.7%
품 757
 
3.6%
및 572
 
2.7%
타 542
 
2.6%
리 516
 
2.5%
외 456
 
2.2%
금 422
 
2.0%
Other values (291) 11611
55.6%
Decimal Number
ValueCountFrequency (%)
2 688
28.1%
1 480
19.6%
3 414
16.9%
9 305
12.4%
0 208
 
8.5%
8 118
 
4.8%
5 115
 
4.7%
4 83
 
3.4%
6 23
 
0.9%
7 17
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 250
99.6%
. 1
 
0.4%
Space Separator
ValueCountFrequency (%)
672
100.0%
Open Punctuation
ValueCountFrequency (%)
( 455
100.0%
Close Punctuation
ValueCountFrequency (%)
) 452
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20869
83.0%
Common 4281
 
17.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1854
 
8.9%
제 1752
 
8.4%
조 1400
 
6.7%
기 987
 
4.7%
품 757
 
3.6%
및 572
 
2.7%
타 542
 
2.6%
리 516
 
2.5%
외 456
 
2.2%
금 422
 
2.0%
Other values (291) 11611
55.6%
Common
ValueCountFrequency (%)
2 688
16.1%
672
15.7%
1 480
11.2%
( 455
10.6%
) 452
10.6%
3 414
9.7%
9 305
7.1%
, 250
 
5.8%
0 208
 
4.9%
8 118
 
2.8%
Other values (5) 239
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20869
83.0%
ASCII 4281
 
17.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 1854
 
8.9%
제 1752
 
8.4%
조 1400
 
6.7%
기 987
 
4.7%
품 757
 
3.6%
및 572
 
2.7%
타 542
 
2.6%
리 516
 
2.5%
외 456
 
2.2%
금 422
 
2.0%
Other values (291) 11611
55.6%
ASCII
ValueCountFrequency (%)
2 688
16.1%
672
15.7%
1 480
11.2%
( 455
10.6%
) 452
10.6%
3 414
9.7%
9 305
7.1%
, 250
 
5.8%
0 208
 
4.9%
8 118
 
2.8%
Other values (5) 239
 
5.6%

종수
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.9 KiB
5
1192 
4
716 
3
 
67
2
 
31
1
 
12

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row4
3rd row5
4th row5
5th row2

Common Values

ValueCountFrequency (%)
5 1192
59.1%
4 716
35.5%
3 67
 
3.3%
2 31
 
1.5%
1 12
 
0.6%

Length

2023-12-11T09:50:40.261638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:50:40.354215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 1192
59.1%
4 716
35.5%
3 67
 
3.3%
2 31
 
1.5%
1 12
 
0.6%

신고일자
Text

Distinct1539
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Memory size15.9 KiB
2023-12-11T09:50:40.605904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9905847
Min length6

Characters and Unicode

Total characters20161
Distinct characters19
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1177 ?
Unique (%)58.3%

Sample

1st row1978-06-01
2nd row1979-08-10
3rd row1980-07-10
4th row1982-09-01
5th row1983-03-12
ValueCountFrequency (%)
2021-01-21 8
 
0.4%
2019-04-15 8
 
0.4%
2019-05-22 7
 
0.3%
2020-12-02 6
 
0.3%
2020-01-02 6
 
0.3%
2019-03-18 6
 
0.3%
2019-07-31 6
 
0.3%
2019-02-15 6
 
0.3%
2019-03-06 6
 
0.3%
2020-09-29 6
 
0.3%
Other values (1529) 1953
96.8%
2023-12-11T09:50:41.002059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5042
25.0%
- 4031
20.0%
2 3475
17.2%
1 3105
15.4%
9 1070
 
5.3%
3 665
 
3.3%
5 577
 
2.9%
7 574
 
2.8%
6 541
 
2.7%
8 540
 
2.7%
Other values (9) 541
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16117
79.9%
Dash Punctuation 4031
 
20.0%
Lowercase Letter 8
 
< 0.1%
Uppercase Letter 4
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5042
31.3%
2 3475
21.6%
1 3105
19.3%
9 1070
 
6.6%
3 665
 
4.1%
5 577
 
3.6%
7 574
 
3.6%
6 541
 
3.4%
8 540
 
3.4%
4 528
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
a 3
37.5%
r 2
25.0%
y 1
 
12.5%
o 1
 
12.5%
v 1
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
M 3
75.0%
N 1
 
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 4031
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20149
99.9%
Latin 12
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5042
25.0%
- 4031
20.0%
2 3475
17.2%
1 3105
15.4%
9 1070
 
5.3%
3 665
 
3.3%
5 577
 
2.9%
7 574
 
2.8%
6 541
 
2.7%
8 540
 
2.7%
Other values (2) 529
 
2.6%
Latin
ValueCountFrequency (%)
M 3
25.0%
a 3
25.0%
r 2
16.7%
y 1
 
8.3%
N 1
 
8.3%
o 1
 
8.3%
v 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20161
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5042
25.0%
- 4031
20.0%
2 3475
17.2%
1 3105
15.4%
9 1070
 
5.3%
3 665
 
3.3%
5 577
 
2.9%
7 574
 
2.8%
6 541
 
2.7%
8 540
 
2.7%
Other values (9) 541
 
2.7%

Interactions

2023-12-11T09:50:37.227520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:50:41.312428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번종수
순번1.0000.283
종수0.2831.000
2023-12-11T09:50:41.382726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번종수
순번1.0000.121
종수0.1211.000

Missing values

2023-12-11T09:50:37.387021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:50:37.490335image/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.
2023-12-11T09:50:37.577538image/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

순번업체명전화번호도로명주소업종종수신고일자
01㈜중일옥사이드055-345-9911경상남도 김해시 진영읍 김해대로 94-11기초무기화합물제조31978-06-01
12㈜씨앤엠055-330-5021경상남도 김해시 김해대로2635번길 29전동기및발전기제조업41979-08-10
23아세아식품055-323-9910경상남도 김해시 생림면 장재로520번안길 8식품제조51980-07-10
34진례산업㈜055-345-2600경상남도 김해시 진례면 서부로476번길 34스폰지제조업51982-09-01
45김해축협배합사료공장055-345-8844경상남도 김해시 한림면 고모로 775사료제조21983-03-12
56㈜제이케이유화055-329-4445경상남도 김해시 김해대로2579번길 36윤활유및그리스제조업41984-04-10
67한성기업㈜김해공장055-333-4676경상남도 김해시 삼안로 51음식료품제조시설41984-06-22
78한통아스콘㈜055-346-1100경상남도 김해시 한림면 안곡로 265아스콘제조업21999-06-21
89르노코리아자동차 김해정비사업소㈜055-333-2626경상남도 김해시 김해대로2635번길 6자동차종합수리업41986-01-25
910신광산업055-335-2481경상남도 김해시 김해대로2579번길 38-1플라스틱발포성형제품제조업41986-04-03
순번업체명전화번호도로명주소업종종수신고일자
20082009영남열처리055-342-2747경상남도 김해시 한림면 병동산단로 68금속열처리업52021-08-09
20092010더클래스<NA>경상남도 김해시 분성로627번길 53-57치약, 비누 및 기타세제제조업 외 152021-08-10
20102011아시아페인트(주)<NA>경상남도 김해시 진영읍 본산리 309-21,22일반용도료 및 관련제품제조업52021-08-13
20112012동성산업<NA>경상남도 김해시 주촌면 서부로1409번길 108선박구성부분품제조업42021-08-25
20122013㈜케이에스중장비055-724-2357경상남도 김해시 생림면 장재로520번길 55그외자동차용신품부품제조업42021-08-26
20132014씨에스종합건설주식회사055-313-0484경상남도 김해시 장유동 산 57-15건설업52021-08-30
20142015창인토건㈜<NA>경상남도 김해시 장유동 산 76-1번지 외 1필지건설업52021-08-30
20152016원테크<NA>경상남도 김해시 생림면 사촌리 산39 외 1공장건립을위한개발행위52021-08-30
20162017주식회사 리드엔텍055-343-3602경상남도 김해시 한림면 김해대로1402번길 36금속류해체및선별업42021-08-27
20172018주식회사 한해그린텍<NA>경상남도 김해시 주촌면 서부로1541번안길 50-34폐기물처리업52021-08-18