Overview

Dataset statistics

Number of variables10
Number of observations30
Missing cells42
Missing cells (%)14.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory86.4 B

Variable types

Numeric2
Text4
Categorical3
DateTime1

Dataset

Description샘플 데이터
Author경기도일자리재단
URLhttps://www.bigdata-region.kr/#/dataset/7d5e4b4a-e484-4023-9f6b-ab2c63f9a513

Alerts

근무형태명 has constant value ""Constant
청년시리즈신청번호 is highly overall correlated with 제조업표기명High correlation
제조업표기명 is highly overall correlated with 청년시리즈신청번호High correlation
사업장등록지역명 has 17 (56.7%) missing valuesMissing
업종명 has 25 (83.3%) missing valuesMissing
청년시리즈신청번호 has unique valuesUnique
기업명 has unique valuesUnique
실근무지역우편번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 14:22:34.336980
Analysis finished2023-12-10 14:22:35.502994
Duration1.17 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

청년시리즈신청번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.966667
Minimum43
Maximum95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:22:35.566908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43
5-th percentile44.45
Q155.25
median68.5
Q384
95-th percentile93.1
Maximum95
Range52
Interquartile range (IQR)28.75

Descriptive statistics

Standard deviation16.740377
Coefficient of variation (CV)0.24273142
Kurtosis-1.3782704
Mean68.966667
Median Absolute Deviation (MAD)14
Skewness0.013054939
Sum2069
Variance280.24023
MonotonicityStrictly increasing
2023-12-10T23:22:35.682999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
43 1
 
3.3%
75 1
 
3.3%
95 1
 
3.3%
94 1
 
3.3%
92 1
 
3.3%
91 1
 
3.3%
89 1
 
3.3%
87 1
 
3.3%
86 1
 
3.3%
85 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
43 1
3.3%
44 1
3.3%
45 1
3.3%
47 1
3.3%
50 1
3.3%
51 1
3.3%
54 1
3.3%
55 1
3.3%
56 1
3.3%
57 1
3.3%
ValueCountFrequency (%)
95 1
3.3%
94 1
3.3%
92 1
3.3%
91 1
3.3%
89 1
3.3%
87 1
3.3%
86 1
3.3%
85 1
3.3%
81 1
3.3%
79 1
3.3%

기업명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:22:35.866082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length6.3
Min length2

Characters and Unicode

Total characters189
Distinct characters89
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row진우산전
2nd row유양특수산업
3rd row(주)알이랑
4th row백웅
5th row주식회사 한맥아이피에스
ValueCountFrequency (%)
주식회사 3
 
8.8%
진우산전 1
 
2.9%
래피드컴 1
 
2.9%
켐텍 1
 
2.9%
주 1
 
2.9%
이노프라 1
 
2.9%
주)태성산업 1
 
2.9%
영우화인텍 1
 
2.9%
주)비앤엠 1
 
2.9%
태준아그로텍 1
 
2.9%
Other values (22) 22
64.7%
2023-12-10T23:22:36.168409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 17
 
9.0%
) 14
 
7.4%
( 14
 
7.4%
스 6
 
3.2%
업 6
 
3.2%
에 5
 
2.6%
텍 5
 
2.6%
이 5
 
2.6%
산 5
 
2.6%
4
 
2.1%
Other values (79) 108
57.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 157
83.1%
Close Punctuation 14
 
7.4%
Open Punctuation 14
 
7.4%
Space Separator 4
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 17
 
10.8%
스 6
 
3.8%
업 6
 
3.8%
에 5
 
3.2%
텍 5
 
3.2%
이 5
 
3.2%
산 5
 
3.2%
식 3
 
1.9%
회 3
 
1.9%
태 3
 
1.9%
Other values (76) 99
63.1%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 157
83.1%
Common 32
 
16.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 17
 
10.8%
스 6
 
3.8%
업 6
 
3.8%
에 5
 
3.2%
텍 5
 
3.2%
이 5
 
3.2%
산 5
 
3.2%
식 3
 
1.9%
회 3
 
1.9%
태 3
 
1.9%
Other values (76) 99
63.1%
Common
ValueCountFrequency (%)
) 14
43.8%
( 14
43.8%
4
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 157
83.1%
ASCII 32
 
16.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 17
 
10.8%
스 6
 
3.8%
업 6
 
3.8%
에 5
 
3.2%
텍 5
 
3.2%
이 5
 
3.2%
산 5
 
3.2%
식 3
 
1.9%
회 3
 
1.9%
태 3
 
1.9%
Other values (76) 99
63.1%
ASCII
ValueCountFrequency (%)
) 14
43.8%
( 14
43.8%
4
 
12.5%

기업규모명
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
소기업
11 
<NA>
10 
중기업
9 

Length

Max length4
Median length3
Mean length3.3333333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중기업
2nd row소기업
3rd row<NA>
4th row소기업
5th row<NA>

Common Values

ValueCountFrequency (%)
소기업 11
36.7%
<NA> 10
33.3%
중기업 9
30.0%

Length

2023-12-10T23:22:36.302035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:22:36.396649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소기업 11
36.7%
na 10
33.3%
중기업 9
30.0%

사업장등록지역명
Text

MISSING 

Distinct13
Distinct (%)100.0%
Missing17
Missing (%)56.7%
Memory size372.0 B
2023-12-10T23:22:36.575303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length31
Mean length23
Min length12

Characters and Unicode

Total characters299
Distinct characters91
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

Unique13 ?
Unique (%)100.0%

Sample

1st row서울 강남구 신사동 539-10번지 진우빌딩 7층; 9층
2nd row경기 화성시 팔탄면 율암리 65-8번지
3rd row경기 화성시 향남읍 하길리 1406-15번지
4th row주식회사 한맥아이피에스
5th row경기 수원시 권선구 세류2동 1129-4번지
ValueCountFrequency (%)
경기 8
 
12.3%
경기도 3
 
4.6%
평택시 2
 
3.1%
주식회사 2
 
3.1%
화성시 2
 
3.1%
모곡동 1
 
1.5%
441-9번지 1
 
1.5%
시흥시 1
 
1.5%
정왕1동 1
 
1.5%
205-607번지 1
 
1.5%
Other values (43) 43
66.2%
2023-12-10T23:22:36.905180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
 
17.4%
시 13
 
4.3%
기 11
 
3.7%
경 11
 
3.7%
1 10
 
3.3%
- 9
 
3.0%
지 9
 
3.0%
번 9
 
3.0%
동 7
 
2.3%
3 7
 
2.3%
Other values (81) 161
53.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 175
58.5%
Decimal Number 58
 
19.4%
Space Separator 52
 
17.4%
Dash Punctuation 9
 
3.0%
Other Punctuation 3
 
1.0%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 13
 
7.4%
기 11
 
6.3%
경 11
 
6.3%
지 9
 
5.1%
번 9
 
5.1%
동 7
 
4.0%
사 5
 
2.9%
리 4
 
2.3%
남 4
 
2.3%
화 4
 
2.3%
Other values (66) 98
56.0%
Decimal Number
ValueCountFrequency (%)
1 10
17.2%
3 7
12.1%
0 7
12.1%
6 6
10.3%
9 6
10.3%
5 6
10.3%
7 5
8.6%
4 5
8.6%
2 5
8.6%
8 1
 
1.7%
Space Separator
ValueCountFrequency (%)
52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Punctuation
ValueCountFrequency (%)
; 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 175
58.5%
Common 124
41.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 13
 
7.4%
기 11
 
6.3%
경 11
 
6.3%
지 9
 
5.1%
번 9
 
5.1%
동 7
 
4.0%
사 5
 
2.9%
리 4
 
2.3%
남 4
 
2.3%
화 4
 
2.3%
Other values (66) 98
56.0%
Common
ValueCountFrequency (%)
52
41.9%
1 10
 
8.1%
- 9
 
7.3%
3 7
 
5.6%
0 7
 
5.6%
6 6
 
4.8%
9 6
 
4.8%
5 6
 
4.8%
7 5
 
4.0%
4 5
 
4.0%
Other values (5) 11
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 175
58.5%
ASCII 124
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
41.9%
1 10
 
8.1%
- 9
 
7.3%
3 7
 
5.6%
0 7
 
5.6%
6 6
 
4.8%
9 6
 
4.8%
5 6
 
4.8%
7 5
 
4.0%
4 5
 
4.0%
Other values (5) 11
 
8.9%
Hangul
ValueCountFrequency (%)
시 13
 
7.4%
기 11
 
6.3%
경 11
 
6.3%
지 9
 
5.1%
번 9
 
5.1%
동 7
 
4.0%
사 5
 
2.9%
리 4
 
2.3%
남 4
 
2.3%
화 4
 
2.3%
Other values (66) 98
56.0%

실근무지역우편번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15144.7
Minimum10881
Maximum18608
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:22:37.041514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10881
5-th percentile11138.85
Q113210
median15114.5
Q317697.25
95-th percentile18553.7
Maximum18608
Range7727
Interquartile range (IQR)4487.25

Descriptive statistics

Standard deviation2629.2013
Coefficient of variation (CV)0.17360537
Kurtosis-1.3776349
Mean15144.7
Median Absolute Deviation (MAD)2407.5
Skewness-0.16045747
Sum454341
Variance6912699.3
MonotonicityNot monotonic
2023-12-10T23:22:37.158028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
11157 1
 
3.3%
16648 1
 
3.3%
10881 1
 
3.3%
17843 1
 
3.3%
17554 1
 
3.3%
14055 1
 
3.3%
18326 1
 
3.3%
11124 1
 
3.3%
13219 1
 
3.3%
13207 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
10881 1
3.3%
11124 1
3.3%
11157 1
3.3%
11413 1
3.3%
11757 1
3.3%
12073 1
3.3%
12739 1
3.3%
13207 1
3.3%
13219 1
3.3%
13516 1
3.3%
ValueCountFrequency (%)
18608 1
3.3%
18578 1
3.3%
18524 1
3.3%
18516 1
3.3%
18326 1
3.3%
17974 1
3.3%
17843 1
3.3%
17745 1
3.3%
17554 1
3.3%
17307 1
3.3%

사업자등록번호
Text

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:22:37.328516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters360
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

Unique14 ?
Unique (%)46.7%

Sample

1st row105-**-*****
2nd row136-**-*****
3rd row125-**-*****
4th row214-**-*****
5th row113-**-*****
ValueCountFrequency (%)
125 4
 
13.3%
126 3
 
10.0%
123 3
 
10.0%
127 2
 
6.7%
214 2
 
6.7%
135 2
 
6.7%
648 1
 
3.3%
105 1
 
3.3%
124 1
 
3.3%
143 1
 
3.3%
Other values (10) 10
33.3%
2023-12-10T23:22:37.613871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 210
58.3%
- 60
 
16.7%
1 31
 
8.6%
2 18
 
5.0%
3 11
 
3.1%
5 8
 
2.2%
4 7
 
1.9%
6 5
 
1.4%
0 3
 
0.8%
8 3
 
0.8%
Other values (2) 4
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 210
58.3%
Decimal Number 90
25.0%
Dash Punctuation 60
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 31
34.4%
2 18
20.0%
3 11
 
12.2%
5 8
 
8.9%
4 7
 
7.8%
6 5
 
5.6%
0 3
 
3.3%
8 3
 
3.3%
7 2
 
2.2%
9 2
 
2.2%
Other Punctuation
ValueCountFrequency (%)
* 210
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 360
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 210
58.3%
- 60
 
16.7%
1 31
 
8.6%
2 18
 
5.0%
3 11
 
3.1%
5 8
 
2.2%
4 7
 
1.9%
6 5
 
1.4%
0 3
 
0.8%
8 3
 
0.8%
Other values (2) 4
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 210
58.3%
- 60
 
16.7%
1 31
 
8.6%
2 18
 
5.0%
3 11
 
3.1%
5 8
 
2.2%
4 7
 
1.9%
6 5
 
1.4%
0 3
 
0.8%
8 3
 
0.8%
Other values (2) 4
 
1.1%

제조업표기명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
제조업
26 
비제조
4 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제조업 26
86.7%
비제조 4
 
13.3%

Length

2023-12-10T23:22:37.740245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:22:37.832155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제조업 26
86.7%
비제조 4
 
13.3%

업종명
Text

MISSING 

Distinct4
Distinct (%)80.0%
Missing25
Missing (%)83.3%
Memory size372.0 B
2023-12-10T23:22:37.983311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length3
Mean length7
Min length3

Characters and Unicode

Total characters35
Distinct characters21
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row운수업
2nd row도매 및 소매업
3rd row예술 스포츠 및 여가관련 서비스업
4th row건설업
5th row운수업
ValueCountFrequency (%)
운수업 2
18.2%
및 2
18.2%
도매 1
9.1%
소매업 1
9.1%
예술 1
9.1%
스포츠 1
9.1%
여가관련 1
9.1%
서비스업 1
9.1%
건설업 1
9.1%
2023-12-10T23:22:38.252506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
17.1%
업 5
14.3%
운 2
 
5.7%
수 2
 
5.7%
및 2
 
5.7%
스 2
 
5.7%
매 2
 
5.7%
소 1
 
2.9%
예 1
 
2.9%
술 1
 
2.9%
Other values (11) 11
31.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 29
82.9%
Space Separator 6
 
17.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 5
17.2%
운 2
 
6.9%
수 2
 
6.9%
및 2
 
6.9%
스 2
 
6.9%
매 2
 
6.9%
소 1
 
3.4%
예 1
 
3.4%
술 1
 
3.4%
도 1
 
3.4%
Other values (10) 10
34.5%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29
82.9%
Common 6
 
17.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 5
17.2%
운 2
 
6.9%
수 2
 
6.9%
및 2
 
6.9%
스 2
 
6.9%
매 2
 
6.9%
소 1
 
3.4%
예 1
 
3.4%
술 1
 
3.4%
도 1
 
3.4%
Other values (10) 10
34.5%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29
82.9%
ASCII 6
 
17.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
100.0%
Hangul
ValueCountFrequency (%)
업 5
17.2%
운 2
 
6.9%
수 2
 
6.9%
및 2
 
6.9%
스 2
 
6.9%
매 2
 
6.9%
소 1
 
3.4%
예 1
 
3.4%
술 1
 
3.4%
도 1
 
3.4%
Other values (10) 10
34.5%

근무형태명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
상용직
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상용직 30
100.0%

Length

2023-12-10T23:22:38.379897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:22:38.482449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상용직 30
100.0%

데이터기준일자
Date

Distinct9
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2018-01-22 00:00:00
Maximum2018-01-31 00:00:00
2023-12-10T23:22:38.612038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:22:38.736472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

Interactions

2023-12-10T23:22:34.900549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:22:34.722881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:22:34.990112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:22:34.800496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:22:38.833225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
청년시리즈신청번호기업명기업규모명사업장등록지역명실근무지역우편번호사업자등록번호제조업표기명업종명데이터기준일자
청년시리즈신청번호1.0001.0000.2721.0000.5210.0000.7820.0000.000
기업명1.0001.0001.0001.0001.0001.0001.0001.0001.000
기업규모명0.2721.0001.0001.0000.6420.3500.0000.0000.000
사업장등록지역명1.0001.0001.0001.0001.0001.0001.0000.0001.000
실근무지역우편번호0.5211.0000.6421.0001.0000.6650.6611.0000.132
사업자등록번호0.0001.0000.3501.0000.6651.0000.8331.0000.858
제조업표기명0.7821.0000.0001.0000.6610.8331.0000.0000.000
업종명0.0001.0000.0000.0001.0001.0000.0001.0001.000
데이터기준일자0.0001.0000.0001.0000.1320.8580.0001.0001.000
2023-12-10T23:22:38.953157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기업규모명제조업표기명
기업규모명1.0000.000
제조업표기명0.0001.000
2023-12-10T23:22:39.039989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
청년시리즈신청번호실근무지역우편번호기업규모명제조업표기명
청년시리즈신청번호1.000-0.0390.1570.516
실근무지역우편번호-0.0391.0000.4060.438
기업규모명0.1570.4061.0000.000
제조업표기명0.5160.4380.0001.000

Missing values

2023-12-10T23:22:35.182441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:22:35.340171image/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.
2023-12-10T23:22:35.443095image/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

청년시리즈신청번호기업명기업규모명사업장등록지역명실근무지역우편번호사업자등록번호제조업표기명업종명근무형태명데이터기준일자
043진우산전중기업서울 강남구 신사동 539-10번지 진우빌딩 7층; 9층11157105-**-*****제조업<NA>상용직2018-01-26
144유양특수산업소기업경기 화성시 팔탄면 율암리 65-8번지18524136-**-*****제조업<NA>상용직2018-01-25
245(주)알이랑<NA><NA>17974125-**-*****제조업<NA>상용직2018-01-23
347백웅소기업경기 화성시 향남읍 하길리 1406-15번지18608214-**-*****제조업<NA>상용직2018-01-27
450주식회사 한맥아이피에스<NA>주식회사 한맥아이피에스13516113-**-*****제조업<NA>상용직2018-01-22
551(주)동신테크<NA><NA>14519130-**-*****제조업<NA>상용직2018-01-29
654태형기업(주)중기업<NA>11413219-**-*****제조업<NA>상용직2018-01-27
755카스맥시스템소기업경기 수원시 권선구 세류2동 1129-4번지16657129-**-*****비제조운수업상용직2018-01-22
856삼양<NA>경기 남양주시 진접읍 연평리 219번지12073528-**-*****비제조도매 및 소매업상용직2018-01-26
957(주)동일프린텍소기업<NA>12739126-**-*****비제조예술 스포츠 및 여가관련 서비스업상용직2018-01-22
청년시리즈신청번호기업명기업규모명사업장등록지역명실근무지역우편번호사업자등록번호제조업표기명업종명근무형태명데이터기준일자
2079대원산업<NA>경기 하남시 천현동 456-1번지17307126-**-*****제조업<NA>상용직2018-01-26
2181(주)혜창소기업<NA>15809123-**-*****제조업<NA>상용직2018-01-22
2285(주)밝은세상소기업<NA>13207126-**-*****제조업<NA>상용직2018-01-22
2386태준아그로텍<NA><NA>13219214-**-*****제조업<NA>상용직2018-01-31
2487(주)비앤엠<NA>경기도 포천시 화현면 문암동길 3311124127-**-*****제조업<NA>상용직2018-01-22
2589영우화인텍소기업<NA>18326124-**-*****제조업<NA>상용직2018-01-22
2691(주)태성산업중기업<NA>14055123-**-*****제조업<NA>상용직2018-01-29
2792이노프라중기업경기 안성시 원곡면 성은리 332-9번지17554125-**-*****제조업<NA>상용직2018-01-22
2894(주) 켐텍소기업경기도 평택시 세교산단로 50-3; 주식회사 켐텍 (세교동)17843125-**-*****제조업<NA>상용직2018-01-26
2995(주)한국학술정보중기업<NA>10881111-**-*****제조업<NA>상용직2018-01-22