Overview

Dataset statistics

Number of variables5
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory48.3 B

Variable types

Numeric3
Text2

Dataset

Description전북특별자치도 여성기업 현황 데이터입니다. 업종코드(C10, C11 등), 업종(식료품, 음료 등) 업체수, 종사자수 등의 항목 데이터를 제공합니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15089301/fileData.do

Alerts

업체수 is highly overall correlated with 종사자수High correlation
종사자수 is highly overall correlated with 업체수High correlation
연번 has unique valuesUnique
업종코드 has unique valuesUnique
업종 has unique valuesUnique
종사자수 has unique valuesUnique
업체수 has 1 (4.0%) zerosZeros
종사자수 has 1 (4.0%) zerosZeros

Reproduction

Analysis started2024-04-17 13:03:43.368871
Analysis finished2024-04-17 13:03:44.179421
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-17T22:03:44.225065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q17
median13
Q319
95-th percentile23.8
Maximum25
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.3598007
Coefficient of variation (CV)0.56613852
Kurtosis-1.2
Mean13
Median Absolute Deviation (MAD)6
Skewness0
Sum325
Variance54.166667
MonotonicityStrictly increasing
2024-04-17T22:03:44.315322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 1
 
4.0%
2 1
 
4.0%
25 1
 
4.0%
24 1
 
4.0%
23 1
 
4.0%
22 1
 
4.0%
21 1
 
4.0%
20 1
 
4.0%
19 1
 
4.0%
18 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1 1
4.0%
2 1
4.0%
3 1
4.0%
4 1
4.0%
5 1
4.0%
6 1
4.0%
7 1
4.0%
8 1
4.0%
9 1
4.0%
10 1
4.0%
ValueCountFrequency (%)
25 1
4.0%
24 1
4.0%
23 1
4.0%
22 1
4.0%
21 1
4.0%
20 1
4.0%
19 1
4.0%
18 1
4.0%
17 1
4.0%
16 1
4.0%

업종코드
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-04-17T22:03:44.466708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters75
Distinct characters11
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

Unique25 ?
Unique (%)100.0%

Sample

1st rowC10
2nd rowC11
3rd rowC12
4th rowC13
5th rowC14
ValueCountFrequency (%)
c10 1
 
4.0%
c23 1
 
4.0%
c33 1
 
4.0%
c32 1
 
4.0%
c31 1
 
4.0%
c30 1
 
4.0%
c29 1
 
4.0%
c28 1
 
4.0%
c27 1
 
4.0%
c26 1
 
4.0%
Other values (15) 15
60.0%
2024-04-17T22:03:44.713757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
C 25
33.3%
1 13
17.3%
2 13
17.3%
3 8
 
10.7%
0 3
 
4.0%
4 3
 
4.0%
5 2
 
2.7%
6 2
 
2.7%
7 2
 
2.7%
8 2
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 50
66.7%
Uppercase Letter 25
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
26.0%
2 13
26.0%
3 8
16.0%
0 3
 
6.0%
4 3
 
6.0%
5 2
 
4.0%
6 2
 
4.0%
7 2
 
4.0%
8 2
 
4.0%
9 2
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
C 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 50
66.7%
Latin 25
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
26.0%
2 13
26.0%
3 8
16.0%
0 3
 
6.0%
4 3
 
6.0%
5 2
 
4.0%
6 2
 
4.0%
7 2
 
4.0%
8 2
 
4.0%
9 2
 
4.0%
Latin
ValueCountFrequency (%)
C 25
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 25
33.3%
1 13
17.3%
2 13
17.3%
3 8
 
10.7%
0 3
 
4.0%
4 3
 
4.0%
5 2
 
2.7%
6 2
 
2.7%
7 2
 
2.7%
8 2
 
2.7%

업종
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-04-17T22:03:44.891561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length15
Mean length10.96
Min length2

Characters and Unicode

Total characters274
Distinct characters93
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

Unique25 ?
Unique (%)100.0%

Sample

1st row식료품
2nd row음료
3rd row담배 제조업
4th row섬유제품(의복 제외)
5th row의복, 의복액세서리 및 모피제품
ValueCountFrequency (%)
및 15
 
20.0%
제외 3
 
4.0%
가구 2
 
2.7%
기계 2
 
2.7%
기타 2
 
2.7%
식료품 1
 
1.3%
통신장비 1
 
1.3%
비금속 1
 
1.3%
광물제품 1
 
1.3%
1차 1
 
1.3%
Other values (46) 46
61.3%
2024-04-17T22:03:45.151330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50
 
18.2%
제 17
 
6.2%
및 15
 
5.5%
품 15
 
5.5%
기 10
 
3.6%
, 9
 
3.3%
의 7
 
2.6%
비 6
 
2.2%
가 6
 
2.2%
장 5
 
1.8%
Other values (83) 134
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 206
75.2%
Space Separator 50
 
18.2%
Other Punctuation 9
 
3.3%
Open Punctuation 4
 
1.5%
Close Punctuation 4
 
1.5%
Decimal Number 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 17
 
8.3%
및 15
 
7.3%
품 15
 
7.3%
기 10
 
4.9%
의 7
 
3.4%
비 6
 
2.9%
가 6
 
2.9%
장 5
 
2.4%
료 4
 
1.9%
계 4
 
1.9%
Other values (78) 117
56.8%
Space Separator
ValueCountFrequency (%)
50
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 206
75.2%
Common 68
 
24.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 17
 
8.3%
및 15
 
7.3%
품 15
 
7.3%
기 10
 
4.9%
의 7
 
3.4%
비 6
 
2.9%
가 6
 
2.9%
장 5
 
2.4%
료 4
 
1.9%
계 4
 
1.9%
Other values (78) 117
56.8%
Common
ValueCountFrequency (%)
50
73.5%
, 9
 
13.2%
( 4
 
5.9%
) 4
 
5.9%
1 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 206
75.2%
ASCII 68
 
24.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50
73.5%
, 9
 
13.2%
( 4
 
5.9%
) 4
 
5.9%
1 1
 
1.5%
Hangul
ValueCountFrequency (%)
제 17
 
8.3%
및 15
 
7.3%
품 15
 
7.3%
기 10
 
4.9%
의 7
 
3.4%
비 6
 
2.9%
가 6
 
2.9%
장 5
 
2.4%
료 4
 
1.9%
계 4
 
1.9%
Other values (78) 117
56.8%

업체수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.2
Minimum0
Maximum430
Zeros1
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-17T22:03:45.246818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q115
median38
Q384
95-th percentile163.4
Maximum430
Range430
Interquartile range (IQR)69

Descriptive statistics

Standard deviation87.519046
Coefficient of variation (CV)1.4070586
Kurtosis13.520181
Mean62.2
Median Absolute Deviation (MAD)31
Skewness3.3669993
Sum1555
Variance7659.5833
MonotonicityNot monotonic
2024-04-17T22:03:45.343599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
59 3
 
12.0%
2 2
 
8.0%
38 2
 
8.0%
430 1
 
4.0%
37 1
 
4.0%
5 1
 
4.0%
86 1
 
4.0%
26 1
 
4.0%
7 1
 
4.0%
92 1
 
4.0%
Other values (11) 11
44.0%
ValueCountFrequency (%)
0 1
4.0%
2 2
8.0%
3 1
4.0%
5 1
4.0%
7 1
4.0%
15 1
4.0%
21 1
4.0%
26 1
4.0%
27 1
4.0%
28 1
4.0%
ValueCountFrequency (%)
430 1
 
4.0%
176 1
 
4.0%
113 1
 
4.0%
92 1
 
4.0%
88 1
 
4.0%
86 1
 
4.0%
84 1
 
4.0%
60 1
 
4.0%
59 3
12.0%
38 2
8.0%

종사자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean463.4
Minimum0
Maximum2452
Zeros1
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-04-17T22:03:45.437679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q197
median330
Q3568
95-th percentile1219.4
Maximum2452
Range2452
Interquartile range (IQR)471

Descriptive statistics

Standard deviation558.7278
Coefficient of variation (CV)1.2057138
Kurtosis5.766393
Mean463.4
Median Absolute Deviation (MAD)238
Skewness2.1430491
Sum11585
Variance312176.75
MonotonicityNot monotonic
2024-04-17T22:03:45.532094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2452 1
 
4.0%
185 1
 
4.0%
20 1
 
4.0%
485 1
 
4.0%
103 1
 
4.0%
33 1
 
4.0%
816 1
 
4.0%
568 1
 
4.0%
1091 1
 
4.0%
359 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
0 1
4.0%
2 1
4.0%
12 1
4.0%
15 1
4.0%
20 1
4.0%
33 1
4.0%
97 1
4.0%
103 1
4.0%
105 1
4.0%
185 1
4.0%
ValueCountFrequency (%)
2452 1
4.0%
1235 1
4.0%
1157 1
4.0%
1091 1
4.0%
816 1
4.0%
803 1
4.0%
568 1
4.0%
485 1
4.0%
423 1
4.0%
398 1
4.0%

Interactions

2024-04-17T22:03:43.889631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:03:43.521313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:03:43.717912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:03:43.949837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:03:43.588469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:03:43.776711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:03:44.005575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:03:43.647375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T22:03:43.832735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T22:03:45.604626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종코드업종업체수종사자수
연번1.0001.0001.0000.6420.000
업종코드1.0001.0001.0001.0001.000
업종1.0001.0001.0001.0001.000
업체수0.6421.0001.0001.0000.848
종사자수0.0001.0001.0000.8481.000
2024-04-17T22:03:45.697546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업체수종사자수
연번1.0000.0440.107
업체수0.0441.0000.962
종사자수0.1070.9621.000

Missing values

2024-04-17T22:03:44.081642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T22:03:44.150734image/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

연번업종코드업종업체수종사자수
01C10식료품4302452
12C11음료27185
23C12담배 제조업00
34C13섬유제품(의복 제외)60398
45C14의복, 의복액세서리 및 모피제품59397
56C15가죽, 가방 및 신발22
67C16목재 및 나무제품(가구제외)38223
78C17펄프, 종이 및 종이제품38276
89C18인쇄 및 기록매체 복제업28105
910C19코크스, 연탄 및 석유정유제품315
연번업종코드업종업체수종사자수
1516C25금속가공제품(기계 및 가구 제외)1761157
1617C26전자부품, 컴퓨터, 영상, 음향 및 통신장비37330
1718C27의료, 정밀, 광학기기 및 시계21359
1819C28전기장비881091
1920C29기타 기계 및 장비92568
2021C30자동차 및 트레일러59816
2122C31기타 운송장비733
2223C32가구26103
2324C33기타제품86485
2425C34산업용 기계 및 장비수리업520