Overview

Dataset statistics

Number of variables20
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory181.9 B

Variable types

Categorical1
Text1
Numeric18

Dataset

Description창업기업의 업력별, 창업기업의 업종별, 창업기업의 기업형태별, 창업기업의 성별, 창업기업의 연령별 인력구성 정보(2020년 창업기업실태조사 통계자료)
URLhttps://www.data.go.kr/data/15049004/fileData.do

Alerts

경영관리 전체인원 is highly overall correlated with 기능생산 전체인원High correlation
경영관리 전체인원(남성) is highly overall correlated with 경영관리 전체인원(여성)High correlation
경영관리 전체인원(여성) is highly overall correlated with 경영관리 전체인원(남성)High correlation
연구개발 전체인원 is highly overall correlated with 일반사무 전체인원 High correlation
연구개발 전체인원(남성) is highly overall correlated with 연구개발 전체인원(여성) and 1 other fieldsHigh correlation
연구개발 전체인원(여성) is highly overall correlated with 연구개발 전체인원(남성) and 1 other fieldsHigh correlation
일반사무 전체인원 is highly overall correlated with 연구개발 전체인원High correlation
일반사무 전체인원(남성) is highly overall correlated with 일반사무 전체인원(여성) and 2 other fieldsHigh correlation
일반사무 전체인원(여성) is highly overall correlated with 일반사무 전체인원(남성) and 1 other fieldsHigh correlation
기능생산 전체인원 is highly overall correlated with 경영관리 전체인원 and 2 other fieldsHigh correlation
기능생산 전체인원(남성) is highly overall correlated with 기능생산 전체인원 and 1 other fieldsHigh correlation
기능생산 전체인원(여성) is highly overall correlated with 기능생산 전체인원 and 1 other fieldsHigh correlation
영업판매 전체인원(남성) is highly overall correlated with 연구개발 전체인원(남성) and 1 other fieldsHigh correlation
영업판매 전체인원(여성) is highly overall correlated with 연구개발 전체인원(여성) and 1 other fieldsHigh correlation
단순노무 전체인원 is highly overall correlated with 일반사무 전체인원(여성) and 2 other fieldsHigh correlation
단순노무 전체인원(남성) is highly overall correlated with 일반사무 전체인원(남성) and 2 other fieldsHigh correlation
단순노무 전체인원(여성) is highly overall correlated with 일반사무 전체인원(남성) and 2 other fieldsHigh correlation
구분별(2) has unique valuesUnique
기능생산 전체인원(남성) has unique valuesUnique
기능생산 전체인원(여성) has unique valuesUnique
단순노무 전체인원(남성) has unique valuesUnique
단순노무 전체인원(여성) has unique valuesUnique
경영관리 전체인원(여성) has 1 (2.9%) zerosZeros
연구개발 전체인원 has 1 (2.9%) zerosZeros
연구개발 전체인원(남성) has 3 (8.8%) zerosZeros
연구개발 전체인원(여성) has 4 (11.8%) zerosZeros
일반사무 전체인원 has 1 (2.9%) zerosZeros
일반사무 전체인원(남성) has 2 (5.9%) zerosZeros
일반사무 전체인원(여성) has 1 (2.9%) zerosZeros
기능생산 전체인원(여성) has 1 (2.9%) zerosZeros
영업판매 전체인원 has 1 (2.9%) zerosZeros
영업판매 전체인원(남성) has 1 (2.9%) zerosZeros
영업판매 전체인원(여성) has 3 (8.8%) zerosZeros
단순노무 전체인원(남성) has 1 (2.9%) zerosZeros

Reproduction

Analysis started2023-12-12 06:13:54.034352
Analysis finished2023-12-12 06:14:27.062750
Duration33.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분별(1)
Categorical

Distinct5
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size404.0 B
업종
18 
업력
창업자 연령
기업형태
창업자 성별

Length

Max length6
Median length2
Mean length2.9411765
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
업종 18
52.9%
업력 7
 
20.6%
창업자 연령 5
 
14.7%
기업형태 2
 
5.9%
창업자 성별 2
 
5.9%

Length

2023-12-12T15:14:27.120850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:14:27.211407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
업종 18
43.9%
업력 7
 
17.1%
창업자 7
 
17.1%
연령 5
 
12.2%
기업형태 2
 
4.9%
성별 2
 
4.9%

구분별(2)
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-12T15:14:27.372731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length7.1764706
Min length2

Characters and Unicode

Total characters244
Distinct characters88
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

Unique34 ?
Unique (%)100.0%

Sample

1st row1년
2nd row2년
3rd row3년
4th row4년
5th row5년
ValueCountFrequency (%)
12
 
15.0%
서비스업 6
 
7.5%
개인 2
 
2.5%
1년 1
 
1.2%
예술 1
 
1.2%
50대 1
 
1.2%
40대 1
 
1.2%
30대 1
 
1.2%
20대 1
 
1.2%
이하 1
 
1.2%
Other values (53) 53
66.2%
2023-12-12T15:14:27.653745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
18.9%
23
 
9.4%
12
 
4.9%
, 8
 
3.3%
8
 
3.3%
7
 
2.9%
6
 
2.5%
6
 
2.5%
6
 
2.5%
6
 
2.5%
Other values (78) 116
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 173
70.9%
Space Separator 46
 
18.9%
Decimal Number 17
 
7.0%
Other Punctuation 8
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
23
 
13.3%
12
 
6.9%
8
 
4.6%
7
 
4.0%
6
 
3.5%
6
 
3.5%
6
 
3.5%
6
 
3.5%
4
 
2.3%
3
 
1.7%
Other values (68) 92
53.2%
Decimal Number
ValueCountFrequency (%)
0 5
29.4%
6 2
 
11.8%
5 2
 
11.8%
4 2
 
11.8%
3 2
 
11.8%
2 2
 
11.8%
1 1
 
5.9%
7 1
 
5.9%
Space Separator
ValueCountFrequency (%)
46
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 173
70.9%
Common 71
29.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
23
 
13.3%
12
 
6.9%
8
 
4.6%
7
 
4.0%
6
 
3.5%
6
 
3.5%
6
 
3.5%
6
 
3.5%
4
 
2.3%
3
 
1.7%
Other values (68) 92
53.2%
Common
ValueCountFrequency (%)
46
64.8%
, 8
 
11.3%
0 5
 
7.0%
6 2
 
2.8%
5 2
 
2.8%
4 2
 
2.8%
3 2
 
2.8%
2 2
 
2.8%
1 1
 
1.4%
7 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 173
70.9%
ASCII 71
29.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
64.8%
, 8
 
11.3%
0 5
 
7.0%
6 2
 
2.8%
5 2
 
2.8%
4 2
 
2.8%
3 2
 
2.8%
2 2
 
2.8%
1 1
 
1.4%
7 1
 
1.4%
Hangul
ValueCountFrequency (%)
23
 
13.3%
12
 
6.9%
8
 
4.6%
7
 
4.0%
6
 
3.5%
6
 
3.5%
6
 
3.5%
6
 
3.5%
4
 
2.3%
3
 
1.7%
Other values (68) 92
53.2%

경영관리 전체인원
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.844118
Minimum24.8
Maximum53.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:27.754138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24.8
5-th percentile27.725
Q133.1
median36.35
Q340.225
95-th percentile46.58
Maximum53.5
Range28.7
Interquartile range (IQR)7.125

Descriptive statistics

Standard deviation6.3171336
Coefficient of variation (CV)0.17145569
Kurtosis0.35642495
Mean36.844118
Median Absolute Deviation (MAD)3.8
Skewness0.40578229
Sum1252.7
Variance39.906176
MonotonicityNot monotonic
2023-12-12T15:14:27.842939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
29.1 2
 
5.9%
38.6 2
 
5.9%
31.1 2
 
5.9%
42.2 1
 
2.9%
40.3 1
 
2.9%
39.1 1
 
2.9%
26.1 1
 
2.9%
53.5 1
 
2.9%
40.0 1
 
2.9%
39.8 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
24.8 1
2.9%
26.1 1
2.9%
28.6 1
2.9%
29.1 2
5.9%
31.1 2
5.9%
32.0 1
2.9%
32.8 1
2.9%
34.0 1
2.9%
34.2 1
2.9%
34.4 1
2.9%
ValueCountFrequency (%)
53.5 1
2.9%
48.4 1
2.9%
45.6 1
2.9%
45.3 1
2.9%
43.6 1
2.9%
42.6 1
2.9%
42.2 1
2.9%
41.2 1
2.9%
40.3 1
2.9%
40.0 1
2.9%

경영관리 전체인원(남성)
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.770588
Minimum39.2
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:27.941961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39.2
5-th percentile56.115
Q176.225
median78
Q380.7
95-th percentile90.12
Maximum100
Range60.8
Interquartile range (IQR)4.475

Descriptive statistics

Standard deviation11.604167
Coefficient of variation (CV)0.15115381
Kurtosis4.4462367
Mean76.770588
Median Absolute Deviation (MAD)2.7
Skewness-1.6064398
Sum2610.2
Variance134.65668
MonotonicityNot monotonic
2023-12-12T15:14:28.039782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
80.7 2
 
5.9%
77.8 2
 
5.9%
78.0 2
 
5.9%
76.2 1
 
2.9%
79.6 1
 
2.9%
76.3 1
 
2.9%
89.0 1
 
2.9%
65.0 1
 
2.9%
79.9 1
 
2.9%
76.6 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
39.2 1
2.9%
42.4 1
2.9%
63.5 1
2.9%
64.9 1
2.9%
65.0 1
2.9%
72.4 1
2.9%
73.0 1
2.9%
74.7 1
2.9%
76.2 1
2.9%
76.3 1
2.9%
ValueCountFrequency (%)
100.0 1
2.9%
92.2 1
2.9%
89.0 1
2.9%
88.5 1
2.9%
85.7 1
2.9%
84.2 1
2.9%
83.2 1
2.9%
81.8 1
2.9%
80.7 2
5.9%
80.3 1
2.9%

경영관리 전체인원(여성)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.229412
Minimum0
Maximum60.8
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:28.134860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9.88
Q119.3
median22
Q323.775
95-th percentile43.885
Maximum60.8
Range60.8
Interquartile range (IQR)4.475

Descriptive statistics

Standard deviation11.604167
Coefficient of variation (CV)0.4995463
Kurtosis4.4462367
Mean23.229412
Median Absolute Deviation (MAD)2.7
Skewness1.6064398
Sum789.8
Variance134.65668
MonotonicityNot monotonic
2023-12-12T15:14:28.231033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
19.3 2
 
5.9%
22.2 2
 
5.9%
22.0 2
 
5.9%
23.8 1
 
2.9%
20.4 1
 
2.9%
23.7 1
 
2.9%
11.0 1
 
2.9%
35.0 1
 
2.9%
20.1 1
 
2.9%
23.4 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
0.0 1
2.9%
7.8 1
2.9%
11.0 1
2.9%
11.5 1
2.9%
14.3 1
2.9%
15.8 1
2.9%
16.8 1
2.9%
18.2 1
2.9%
19.3 2
5.9%
19.7 1
2.9%
ValueCountFrequency (%)
60.8 1
2.9%
57.6 1
2.9%
36.5 1
2.9%
35.1 1
2.9%
35.0 1
2.9%
27.6 1
2.9%
27.0 1
2.9%
25.3 1
2.9%
23.8 1
2.9%
23.7 1
2.9%

연구개발 전체인원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1176471
Minimum0
Maximum16.5
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:28.324033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.665
Q11.875
median3.85
Q34.925
95-th percentile9.6
Maximum16.5
Range16.5
Interquartile range (IQR)3.05

Descriptive statistics

Standard deviation3.3356178
Coefficient of variation (CV)0.8100786
Kurtosis4.6437055
Mean4.1176471
Median Absolute Deviation (MAD)1.8
Skewness1.7945043
Sum140
Variance11.126346
MonotonicityNot monotonic
2023-12-12T15:14:28.426729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
9.6 2
 
5.9%
4.1 2
 
5.9%
1.8 2
 
5.9%
4.7 2
 
5.9%
2.2 2
 
5.9%
7.9 1
 
2.9%
4.6 1
 
2.9%
5.8 1
 
2.9%
2.3 1
 
2.9%
0.7 1
 
2.9%
Other values (19) 19
55.9%
ValueCountFrequency (%)
0.0 1
2.9%
0.6 1
2.9%
0.7 1
2.9%
0.8 1
2.9%
1.0 1
2.9%
1.1 1
2.9%
1.5 1
2.9%
1.8 2
5.9%
2.1 1
2.9%
2.2 2
5.9%
ValueCountFrequency (%)
16.5 1
2.9%
9.6 2
5.9%
8.7 1
2.9%
7.9 1
2.9%
5.9 1
2.9%
5.8 1
2.9%
5.7 1
2.9%
5.0 1
2.9%
4.7 2
5.9%
4.6 1
2.9%

연구개발 전체인원(남성)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.773529
Minimum0
Maximum100
Zeros3
Zeros (%)8.8%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:28.533143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q131.275
median68.45
Q381.1
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)49.825

Descriptive statistics

Standard deviation31.875766
Coefficient of variation (CV)0.55173651
Kurtosis-1.0259251
Mean57.773529
Median Absolute Deviation (MAD)22.25
Skewness-0.4877481
Sum1964.3
Variance1016.0644
MonotonicityNot monotonic
2023-12-12T15:14:28.633523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
100.0 3
 
8.8%
0.0 3
 
8.8%
21.5 1
 
2.9%
34.0 1
 
2.9%
91.5 1
 
2.9%
75.3 1
 
2.9%
46.8 1
 
2.9%
37.3 1
 
2.9%
32.1 1
 
2.9%
61.0 1
 
2.9%
Other values (20) 20
58.8%
ValueCountFrequency (%)
0.0 3
8.8%
4.2 1
 
2.9%
21.3 1
 
2.9%
21.5 1
 
2.9%
25.5 1
 
2.9%
30.0 1
 
2.9%
31.0 1
 
2.9%
32.1 1
 
2.9%
34.0 1
 
2.9%
37.3 1
 
2.9%
ValueCountFrequency (%)
100.0 3
8.8%
91.5 1
 
2.9%
91.3 1
 
2.9%
90.0 1
 
2.9%
89.1 1
 
2.9%
87.6 1
 
2.9%
81.4 1
 
2.9%
80.2 1
 
2.9%
77.3 1
 
2.9%
76.3 1
 
2.9%

연구개발 전체인원(여성)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.285294
Minimum0
Maximum100
Zeros4
Zeros (%)11.8%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:28.728961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113.95
median27.9
Q367.425
95-th percentile97.27
Maximum100
Range100
Interquartile range (IQR)53.475

Descriptive statistics

Standard deviation30.984504
Coefficient of variation (CV)0.7887049
Kurtosis-0.89916473
Mean39.285294
Median Absolute Deviation (MAD)19.3
Skewness0.54434939
Sum1335.7
Variance960.03947
MonotonicityNot monotonic
2023-12-12T15:14:28.822513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.0 4
 
11.8%
100.0 2
 
5.9%
78.5 1
 
2.9%
66.0 1
 
2.9%
8.5 1
 
2.9%
24.7 1
 
2.9%
53.2 1
 
2.9%
62.7 1
 
2.9%
67.9 1
 
2.9%
39.0 1
 
2.9%
Other values (20) 20
58.8%
ValueCountFrequency (%)
0.0 4
11.8%
8.5 1
 
2.9%
8.7 1
 
2.9%
10.0 1
 
2.9%
10.9 1
 
2.9%
12.4 1
 
2.9%
18.6 1
 
2.9%
19.8 1
 
2.9%
22.7 1
 
2.9%
23.7 1
 
2.9%
ValueCountFrequency (%)
100.0 2
5.9%
95.8 1
2.9%
78.7 1
2.9%
78.5 1
2.9%
74.5 1
2.9%
70.0 1
2.9%
69.0 1
2.9%
67.9 1
2.9%
66.0 1
2.9%
62.7 1
2.9%

일반사무 전체인원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.176471
Minimum0
Maximum32.1
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:29.199911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.905
Q112.025
median14.7
Q316.45
95-th percentile21.01
Maximum32.1
Range32.1
Interquartile range (IQR)4.425

Descriptive statistics

Standard deviation5.8077304
Coefficient of variation (CV)0.40967393
Kurtosis2.5241058
Mean14.176471
Median Absolute Deviation (MAD)2.15
Skewness0.10241735
Sum482
Variance33.729733
MonotonicityNot monotonic
2023-12-12T15:14:29.318312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
16.3 3
 
8.8%
14.6 2
 
5.9%
13.9 2
 
5.9%
14.3 2
 
5.9%
21.4 1
 
2.9%
17.1 1
 
2.9%
13.0 1
 
2.9%
9.8 1
 
2.9%
15.8 1
 
2.9%
15.4 1
 
2.9%
Other values (19) 19
55.9%
ValueCountFrequency (%)
0.0 1
2.9%
2.8 1
2.9%
4.5 1
2.9%
6.7 1
2.9%
7.3 1
2.9%
9.1 1
2.9%
9.8 1
2.9%
11.8 1
2.9%
11.9 1
2.9%
12.4 1
2.9%
ValueCountFrequency (%)
32.1 1
 
2.9%
21.4 1
 
2.9%
20.8 1
 
2.9%
19.6 1
 
2.9%
19.3 1
 
2.9%
17.1 1
 
2.9%
17.0 1
 
2.9%
16.7 1
 
2.9%
16.5 1
 
2.9%
16.3 3
8.8%

일반사무 전체인원(남성)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.385294
Minimum0
Maximum86.5
Zeros2
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:29.437733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.9
Q126.525
median36.25
Q341.325
95-th percentile56.29
Maximum86.5
Range86.5
Interquartile range (IQR)14.8

Descriptive statistics

Standard deviation16.772906
Coefficient of variation (CV)0.48779301
Kurtosis2.2097443
Mean34.385294
Median Absolute Deviation (MAD)7.05
Skewness0.35089752
Sum1169.1
Variance281.33038
MonotonicityNot monotonic
2023-12-12T15:14:29.614263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
30.9 2
 
5.9%
23.4 2
 
5.9%
0.0 2
 
5.9%
36.8 1
 
2.9%
29.0 1
 
2.9%
6.0 1
 
2.9%
55.1 1
 
2.9%
19.1 1
 
2.9%
45.9 1
 
2.9%
38.7 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
0.0 2
5.9%
6.0 1
2.9%
10.5 1
2.9%
19.1 1
2.9%
23.4 2
5.9%
23.6 1
2.9%
25.7 1
2.9%
29.0 1
2.9%
29.1 1
2.9%
29.4 1
2.9%
ValueCountFrequency (%)
86.5 1
2.9%
58.5 1
2.9%
55.1 1
2.9%
54.1 1
2.9%
46.1 1
2.9%
45.9 1
2.9%
43.2 1
2.9%
43.1 1
2.9%
41.4 1
2.9%
41.1 1
2.9%

일반사무 전체인원(여성)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.673529
Minimum0
Maximum100
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:29.769880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile31.7
Q157.325
median62.95
Q370.975
95-th percentile91.075
Maximum100
Range100
Interquartile range (IQR)13.65

Descriptive statistics

Standard deviation19.158609
Coefficient of variation (CV)0.30568901
Kurtosis3.5461457
Mean62.673529
Median Absolute Deviation (MAD)7.8
Skewness-1.2216832
Sum2130.9
Variance367.05231
MonotonicityNot monotonic
2023-12-12T15:14:29.889161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
69.1 2
 
5.9%
76.6 2
 
5.9%
63.2 1
 
2.9%
61.3 1
 
2.9%
94.0 1
 
2.9%
44.9 1
 
2.9%
100.0 1
 
2.9%
80.9 1
 
2.9%
54.1 1
 
2.9%
64.3 1
 
2.9%
Other values (22) 22
64.7%
ValueCountFrequency (%)
0.0 1
2.9%
13.5 1
2.9%
41.5 1
2.9%
44.9 1
2.9%
45.9 1
2.9%
53.9 1
2.9%
54.1 1
2.9%
56.8 1
2.9%
56.9 1
2.9%
58.6 1
2.9%
ValueCountFrequency (%)
100.0 1
2.9%
94.0 1
2.9%
89.5 1
2.9%
80.9 1
2.9%
76.6 2
5.9%
76.4 1
2.9%
74.3 1
2.9%
71.0 1
2.9%
70.9 1
2.9%
70.6 1
2.9%

기능생산 전체인원
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.432353
Minimum4.2
Maximum58.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:30.007561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.2
5-th percentile5.88
Q114.35
median19.45
Q323.575
95-th percentile37.405
Maximum58.1
Range53.9
Interquartile range (IQR)9.225

Descriptive statistics

Standard deviation10.705697
Coefficient of variation (CV)0.52395812
Kurtosis3.6969732
Mean20.432353
Median Absolute Deviation (MAD)5.05
Skewness1.4696453
Sum694.7
Variance114.61195
MonotonicityNot monotonic
2023-12-12T15:14:30.138860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
20.5 2
 
5.9%
35.2 2
 
5.9%
14.3 1
 
2.9%
21.6 1
 
2.9%
5.1 1
 
2.9%
8.7 1
 
2.9%
18.3 1
 
2.9%
13.0 1
 
2.9%
24.0 1
 
2.9%
20.7 1
 
2.9%
Other values (22) 22
64.7%
ValueCountFrequency (%)
4.2 1
2.9%
5.1 1
2.9%
6.3 1
2.9%
8.7 1
2.9%
11.5 1
2.9%
12.4 1
2.9%
13.0 1
2.9%
13.5 1
2.9%
14.3 1
2.9%
14.5 1
2.9%
ValueCountFrequency (%)
58.1 1
2.9%
41.5 1
2.9%
35.2 2
5.9%
30.7 1
2.9%
28.3 1
2.9%
26.3 1
2.9%
24.8 1
2.9%
24.0 1
2.9%
22.3 1
2.9%
21.6 1
2.9%

기능생산 전체인원(남성)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79.773529
Minimum42.6
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:30.297507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum42.6
5-th percentile63.705
Q174.325
median80.7
Q386.25
95-th percentile96.755
Maximum100
Range57.4
Interquartile range (IQR)11.925

Descriptive statistics

Standard deviation11.499758
Coefficient of variation (CV)0.14415506
Kurtosis2.3719371
Mean79.773529
Median Absolute Deviation (MAD)6
Skewness-0.92543233
Sum2712.3
Variance132.24443
MonotonicityNot monotonic
2023-12-12T15:14:30.466067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
80.3 1
 
2.9%
82.1 1
 
2.9%
85.4 1
 
2.9%
86.3 1
 
2.9%
70.0 1
 
2.9%
56.1 1
 
2.9%
79.2 1
 
2.9%
75.2 1
 
2.9%
82.3 1
 
2.9%
86.1 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
42.6 1
2.9%
56.1 1
2.9%
67.8 1
2.9%
70.0 1
2.9%
70.4 1
2.9%
70.5 1
2.9%
71.0 1
2.9%
73.4 1
2.9%
74.2 1
2.9%
74.7 1
2.9%
ValueCountFrequency (%)
100.0 1
2.9%
97.6 1
2.9%
96.3 1
2.9%
96.0 1
2.9%
90.5 1
2.9%
89.6 1
2.9%
87.6 1
2.9%
86.7 1
2.9%
86.3 1
2.9%
86.1 1
2.9%

기능생산 전체인원(여성)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.226471
Minimum0
Maximum57.4
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:30.690092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3.245
Q113.75
median19.3
Q325.675
95-th percentile36.295
Maximum57.4
Range57.4
Interquartile range (IQR)11.925

Descriptive statistics

Standard deviation11.499758
Coefficient of variation (CV)0.5685499
Kurtosis2.3719371
Mean20.226471
Median Absolute Deviation (MAD)6
Skewness0.92543233
Sum687.7
Variance132.24443
MonotonicityNot monotonic
2023-12-12T15:14:30.901158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
19.7 1
 
2.9%
17.9 1
 
2.9%
14.6 1
 
2.9%
13.7 1
 
2.9%
30.0 1
 
2.9%
43.9 1
 
2.9%
20.8 1
 
2.9%
24.8 1
 
2.9%
17.7 1
 
2.9%
13.9 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
0.0 1
2.9%
2.4 1
2.9%
3.7 1
2.9%
4.0 1
2.9%
9.5 1
2.9%
10.4 1
2.9%
12.4 1
2.9%
13.3 1
2.9%
13.7 1
2.9%
13.9 1
2.9%
ValueCountFrequency (%)
57.4 1
2.9%
43.9 1
2.9%
32.2 1
2.9%
30.0 1
2.9%
29.6 1
2.9%
29.5 1
2.9%
29.0 1
2.9%
26.6 1
2.9%
25.8 1
2.9%
25.3 1
2.9%

영업판매 전체인원
Real number (ℝ)

ZEROS 

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.9882353
Minimum0
Maximum20.8
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:31.090416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.19
Q13.95
median6.6
Q37.9
95-th percentile18.16
Maximum20.8
Range20.8
Interquartile range (IQR)3.95

Descriptive statistics

Standard deviation4.8536625
Coefficient of variation (CV)0.69454766
Kurtosis2.0683084
Mean6.9882353
Median Absolute Deviation (MAD)2.1
Skewness1.3846012
Sum237.6
Variance23.558039
MonotonicityNot monotonic
2023-12-12T15:14:31.255436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
6.6 3
 
8.8%
7.9 2
 
5.9%
4.5 2
 
5.9%
3.2 1
 
2.9%
2.7 1
 
2.9%
6.4 1
 
2.9%
7.0 1
 
2.9%
7.2 1
 
2.9%
3.1 1
 
2.9%
7.3 1
 
2.9%
Other values (20) 20
58.8%
ValueCountFrequency (%)
0.0 1
2.9%
0.8 1
2.9%
1.4 1
2.9%
1.7 1
2.9%
2.7 1
2.9%
3.0 1
2.9%
3.1 1
2.9%
3.2 1
2.9%
3.8 1
2.9%
4.4 1
2.9%
ValueCountFrequency (%)
20.8 1
2.9%
19.2 1
2.9%
17.6 1
2.9%
14.7 1
2.9%
10.0 1
2.9%
9.6 1
2.9%
8.5 1
2.9%
8.1 1
2.9%
7.9 2
5.9%
7.4 1
2.9%

영업판매 전체인원(남성)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.117647
Minimum0
Maximum100
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:31.428463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile31.115
Q148.6
median61.3
Q373.75
95-th percentile95.775
Maximum100
Range100
Interquartile range (IQR)25.15

Descriptive statistics

Standard deviation20.489724
Coefficient of variation (CV)0.3408271
Kurtosis1.2865033
Mean60.117647
Median Absolute Deviation (MAD)13.15
Skewness-0.39176418
Sum2044
Variance419.82877
MonotonicityNot monotonic
2023-12-12T15:14:31.612493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
100.0 2
 
5.9%
65.2 2
 
5.9%
48.5 1
 
2.9%
30.4 1
 
2.9%
46.8 1
 
2.9%
76.1 1
 
2.9%
51.9 1
 
2.9%
63.4 1
 
2.9%
62.6 1
 
2.9%
51.6 1
 
2.9%
Other values (22) 22
64.7%
ValueCountFrequency (%)
0.0 1
2.9%
30.4 1
2.9%
31.5 1
2.9%
34.9 1
2.9%
41.2 1
2.9%
41.6 1
2.9%
46.8 1
2.9%
47.8 1
2.9%
48.5 1
2.9%
48.9 1
2.9%
ValueCountFrequency (%)
100.0 2
5.9%
93.5 1
2.9%
80.4 1
2.9%
78.9 1
2.9%
78.5 1
2.9%
78.0 1
2.9%
76.1 1
2.9%
75.7 1
2.9%
67.9 1
2.9%
66.7 1
2.9%

영업판매 전체인원(여성)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.941176
Minimum0
Maximum69.6
Zeros3
Zeros (%)8.8%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:31.775248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q124
median37
Q350.425
95-th percentile66.29
Maximum69.6
Range69.6
Interquartile range (IQR)26.425

Descriptive statistics

Standard deviation18.697514
Coefficient of variation (CV)0.5061429
Kurtosis-0.25669076
Mean36.941176
Median Absolute Deviation (MAD)13.6
Skewness-0.36145175
Sum1256
Variance349.59704
MonotonicityNot monotonic
2023-12-12T15:14:31.950243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.0 3
 
8.8%
34.8 2
 
5.9%
51.5 1
 
2.9%
69.6 1
 
2.9%
53.2 1
 
2.9%
23.9 1
 
2.9%
48.1 1
 
2.9%
36.6 1
 
2.9%
37.4 1
 
2.9%
48.4 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
0.0 3
8.8%
6.5 1
 
2.9%
19.6 1
 
2.9%
21.1 1
 
2.9%
21.5 1
 
2.9%
22.0 1
 
2.9%
23.9 1
 
2.9%
24.3 1
 
2.9%
32.1 1
 
2.9%
33.3 1
 
2.9%
ValueCountFrequency (%)
69.6 1
2.9%
68.5 1
2.9%
65.1 1
2.9%
58.8 1
2.9%
58.4 1
2.9%
53.2 1
2.9%
52.2 1
2.9%
51.5 1
2.9%
51.1 1
2.9%
48.4 1
2.9%

단순노무 전체인원
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.429412
Minimum6.7
Maximum36.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:32.114090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.7
5-th percentile6.765
Q113.45
median15.2
Q320.925
95-th percentile32.95
Maximum36.6
Range29.9
Interquartile range (IQR)7.475

Descriptive statistics

Standard deviation7.4381706
Coefficient of variation (CV)0.4267597
Kurtosis0.77927763
Mean17.429412
Median Absolute Deviation (MAD)3.55
Skewness0.94279435
Sum592.6
Variance55.326381
MonotonicityNot monotonic
2023-12-12T15:14:32.279122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
6.7 2
 
5.9%
15.0 2
 
5.9%
15.2 2
 
5.9%
14.0 1
 
2.9%
31.9 1
 
2.9%
11.0 1
 
2.9%
34.9 1
 
2.9%
20.5 1
 
2.9%
13.8 1
 
2.9%
17.6 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
6.7 2
5.9%
6.8 1
2.9%
7.9 1
2.9%
11.0 1
2.9%
11.6 1
2.9%
12.2 1
2.9%
13.0 1
2.9%
13.4 1
2.9%
13.6 1
2.9%
13.8 1
2.9%
ValueCountFrequency (%)
36.6 1
2.9%
34.9 1
2.9%
31.9 1
2.9%
27.8 1
2.9%
24.9 1
2.9%
24.3 1
2.9%
22.7 1
2.9%
21.5 1
2.9%
21.0 1
2.9%
20.7 1
2.9%

단순노무 전체인원(남성)
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.311765
Minimum0
Maximum58.4
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:32.436427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7.335
Q119.125
median35.45
Q342.95
95-th percentile55.735
Maximum58.4
Range58.4
Interquartile range (IQR)23.825

Descriptive statistics

Standard deviation15.812476
Coefficient of variation (CV)0.4893721
Kurtosis-0.72782703
Mean32.311765
Median Absolute Deviation (MAD)10.35
Skewness-0.26203489
Sum1098.6
Variance250.0344
MonotonicityNot monotonic
2023-12-12T15:14:32.601997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
17.0 1
 
2.9%
40.7 1
 
2.9%
49.9 1
 
2.9%
10.7 1
 
2.9%
12.2 1
 
2.9%
43.7 1
 
2.9%
4.8 1
 
2.9%
20.7 1
 
2.9%
35.5 1
 
2.9%
34.3 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
0.0 1
2.9%
4.8 1
2.9%
8.7 1
2.9%
10.2 1
2.9%
10.7 1
2.9%
12.2 1
2.9%
17.0 1
2.9%
18.4 1
2.9%
18.6 1
2.9%
20.7 1
2.9%
ValueCountFrequency (%)
58.4 1
2.9%
57.1 1
2.9%
55.0 1
2.9%
54.9 1
2.9%
51.3 1
2.9%
49.9 1
2.9%
45.2 1
2.9%
44.0 1
2.9%
43.7 1
2.9%
40.7 1
2.9%

단순노무 전체인원(여성)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.688235
Minimum41.6
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T15:14:32.790927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41.6
5-th percentile44.265
Q157.05
median64.55
Q380.875
95-th percentile92.665
Maximum100
Range58.4
Interquartile range (IQR)23.825

Descriptive statistics

Standard deviation15.812476
Coefficient of variation (CV)0.23360745
Kurtosis-0.72782703
Mean67.688235
Median Absolute Deviation (MAD)10.35
Skewness0.26203489
Sum2301.4
Variance250.0344
MonotonicityNot monotonic
2023-12-12T15:14:32.946615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
83.0 1
 
2.9%
59.3 1
 
2.9%
50.1 1
 
2.9%
89.3 1
 
2.9%
87.8 1
 
2.9%
56.3 1
 
2.9%
95.2 1
 
2.9%
79.3 1
 
2.9%
64.5 1
 
2.9%
65.7 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
41.6 1
2.9%
42.9 1
2.9%
45.0 1
2.9%
45.1 1
2.9%
48.7 1
2.9%
50.1 1
2.9%
54.8 1
2.9%
56.0 1
2.9%
56.3 1
2.9%
59.3 1
2.9%
ValueCountFrequency (%)
100.0 1
2.9%
95.2 1
2.9%
91.3 1
2.9%
89.8 1
2.9%
89.3 1
2.9%
87.8 1
2.9%
83.0 1
2.9%
81.6 1
2.9%
81.4 1
2.9%
79.3 1
2.9%

Interactions

2023-12-12T15:14:25.561994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:54.867217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:56.572216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:58.854132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:00.528352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:02.503294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:04.277129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:06.391727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:08.443076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:09.798462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:11.450584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:13.258460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:14.877681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:16.792304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:18.560553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:20.380551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:22.278202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:23.931326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:25.631679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:54.966563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:56.662018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:58.960941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:00.615496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:02.591424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:04.389922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:06.473858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:08.521358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:09.869046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:11.536840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:13.332743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:14.979774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:16.889718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:18.639727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:20.492601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:22.373503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:24.017109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:25.697971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:55.063258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:56.770399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:59.073955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:00.724353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:02.676803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:04.493072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:06.576993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:08.599458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:09.965914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:11.628066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:13.413020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:15.088301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:16.982805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:18.760472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:20.611585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:22.456202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:24.098228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:25.765756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:55.170434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:56.864800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:59.164021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:00.873022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:02.779600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:04.598353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:06.672704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:08.675814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:10.056498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:11.748310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:13.489428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:15.197989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:17.074193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:18.851581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:20.711185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:22.546117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:24.170780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:25.834306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:55.283322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:56.959975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:59.254218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:00.975706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:02.875050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:04.713095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:06.774590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:08.754134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:10.141400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:11.835715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:13.586069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:15.303560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:17.156550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:18.946965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:20.831027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:22.626435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:24.259374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:25.900059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:55.376124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:57.062567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:59.349585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:01.082492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:02.975041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:04.807022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:06.857094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:08.828730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:10.235244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:12.266703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:13.672240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:15.386465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:17.247349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:19.033294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:20.927486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:22.699814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:24.335531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:25.965312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:55.472885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:57.167696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:59.430569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:01.192611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:03.068529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:04.895947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:06.954330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:08.901898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:10.330227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:12.338224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:13.754729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:15.491457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:17.328310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:19.111382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:21.017766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:22.794989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:24.415168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:26.031110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:55.555332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:57.300576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:59.519580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:01.334851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:03.164224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:05.028342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:07.054092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:08.984271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:10.437988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:12.415348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:13.832095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:15.604210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:17.405297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:19.228384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:21.132075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:22.884936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:24.496336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:26.093583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:55.657530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:57.418003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:59.609838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:01.424315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:03.264157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:05.143234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:07.189782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:09.057041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:10.519472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:12.482264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:13.901917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:15.712816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:17.466435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:19.342276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:21.233642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:22.977107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:24.576233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:26.156171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:55.769943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:57.540502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:59.690094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:01.545533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:03.337247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:05.270658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:07.328238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:09.133639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:10.619743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:12.558559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:13.982702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:15.818069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:17.535475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:19.452329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:21.332726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:23.071176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:24.869032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:26.222195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:55.850211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:57.675086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:59.765656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:01.651773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:03.420440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:05.372027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:07.475260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:09.210362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:10.727572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:12.636852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:14.099669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:15.910864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:17.606050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:19.565473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:21.428018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:23.154094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:24.931237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:26.288145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:55.978515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:57.786172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:59.853690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:01.783701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:03.525132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:05.808632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:07.625494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:09.280304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:10.837441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:12.720590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:14.204602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:16.012790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:17.677769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:19.678521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:21.537720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:23.244212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:25.003350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:26.355747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:56.057452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:57.891025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:59.956968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:01.882028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:03.613164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:05.909481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:07.870828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:09.353834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:10.922470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:12.798218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:14.281048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:16.123596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:17.761690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:19.779983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:21.650311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:23.329798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:25.088394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:26.415968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:56.147937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:58.002049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:00.062653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:01.977355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:03.731658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:05.984250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:08.027052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:09.431470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:11.000657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:12.862640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:14.356083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:16.239735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:17.838097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:19.872989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:21.734382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:23.407456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:25.168285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:26.478689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:56.227987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:58.114064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:00.173208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:02.083886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:03.816171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:06.062300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:08.115014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:09.507669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:11.082055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:12.933830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:14.433487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:16.358492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:17.923995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:19.971751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:21.826819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:23.488057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:25.242618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:26.544588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:56.327282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:58.231217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:00.277001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:02.192834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:03.954630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:06.145455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:08.209325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:09.590429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:11.166240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:13.015291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:14.521269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:16.488239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:18.011252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:20.064290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:21.940093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:23.593059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:25.339232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:26.607852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:56.413140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:58.326828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:00.357290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:02.300361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:04.057234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:06.225808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:08.282623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:09.658120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:11.249293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:13.104719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:14.616964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:16.598919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:18.395083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:20.160377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:22.035067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:23.705566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:25.417371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:26.675552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:56.494823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:13:58.435017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:00.440915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:02.407462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:04.170897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:06.310025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:08.357405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:09.729119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:11.365891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:13.182097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:14.782819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:16.699900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:18.466760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:20.266964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:22.166468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:23.818194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:14:25.489576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:14:33.072704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분별(1)구분별(2)경영관리 전체인원경영관리 전체인원(남성)경영관리 전체인원(여성)연구개발 전체인원연구개발 전체인원(남성)연구개발 전체인원(여성)일반사무 전체인원일반사무 전체인원(남성)일반사무 전체인원(여성)기능생산 전체인원기능생산 전체인원(남성)기능생산 전체인원(여성)영업판매 전체인원영업판매 전체인원(남성)영업판매 전체인원(여성)단순노무 전체인원단순노무 전체인원(남성)단순노무 전체인원(여성)
구분별(1)1.0001.0000.0000.0000.0000.0000.6010.5970.0000.0270.0000.0000.0000.0000.0000.0000.5200.0000.4800.480
구분별(2)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
경영관리 전체인원0.0001.0001.0000.4820.4820.0000.0000.0000.4770.3930.4000.3380.7470.7470.3080.3150.6320.5790.1970.197
경영관리 전체인원(남성)0.0001.0000.4821.0001.0000.0000.2040.0000.6890.8600.8680.8330.5330.5330.8710.7880.2360.6440.7000.700
경영관리 전체인원(여성)0.0001.0000.4821.0001.0000.0000.2040.0000.6890.8600.8680.8330.5330.5330.8710.7880.2360.6440.7000.700
연구개발 전체인원0.0001.0000.0000.0000.0001.0000.0000.2850.2150.0000.0000.0000.0000.0000.2970.0000.1850.6320.1670.167
연구개발 전체인원(남성)0.6011.0000.0000.2040.2040.0001.0001.0000.0000.0000.1330.0000.5210.5210.1540.4010.4570.4870.5300.530
연구개발 전체인원(여성)0.5971.0000.0000.0000.0000.2851.0001.0000.0000.0000.0000.0000.5910.5910.2370.2610.6400.5700.5870.587
일반사무 전체인원0.0001.0000.4770.6890.6890.2150.0000.0001.0000.8510.8810.8570.0000.0000.6110.6770.5110.5260.6870.687
일반사무 전체인원(남성)0.0271.0000.3930.8600.8600.0000.0000.0000.8511.0000.9720.7740.3750.3750.8420.6100.0000.3470.6490.649
일반사무 전체인원(여성)0.0001.0000.4000.8680.8680.0000.1330.0000.8810.9721.0000.8720.6770.6770.7160.8300.2220.4340.7250.725
기능생산 전체인원0.0001.0000.3380.8330.8330.0000.0000.0000.8570.7740.8721.0000.5060.5060.6790.8440.2640.1510.3240.324
기능생산 전체인원(남성)0.0001.0000.7470.5330.5330.0000.5210.5910.0000.3750.6770.5061.0001.0000.5050.6710.5500.4080.0000.000
기능생산 전체인원(여성)0.0001.0000.7470.5330.5330.0000.5210.5910.0000.3750.6770.5061.0001.0000.5050.6710.5500.4080.0000.000
영업판매 전체인원0.0001.0000.3080.8710.8710.2970.1540.2370.6110.8420.7160.6790.5050.5051.0000.4660.0000.6190.5410.541
영업판매 전체인원(남성)0.0001.0000.3150.7880.7880.0000.4010.2610.6770.6100.8300.8440.6710.6710.4661.0000.9560.6440.6300.630
영업판매 전체인원(여성)0.5201.0000.6320.2360.2360.1850.4570.6400.5110.0000.2220.2640.5500.5500.0000.9561.0000.6350.5700.570
단순노무 전체인원0.0001.0000.5790.6440.6440.6320.4870.5700.5260.3470.4340.1510.4080.4080.6190.6440.6351.0000.7570.757
단순노무 전체인원(남성)0.4801.0000.1970.7000.7000.1670.5300.5870.6870.6490.7250.3240.0000.0000.5410.6300.5700.7571.0001.000
단순노무 전체인원(여성)0.4801.0000.1970.7000.7000.1670.5300.5870.6870.6490.7250.3240.0000.0000.5410.6300.5700.7571.0001.000
2023-12-12T15:14:33.274050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경영관리 전체인원경영관리 전체인원(남성)경영관리 전체인원(여성)연구개발 전체인원연구개발 전체인원(남성)연구개발 전체인원(여성)일반사무 전체인원일반사무 전체인원(남성)일반사무 전체인원(여성)기능생산 전체인원기능생산 전체인원(남성)기능생산 전체인원(여성)영업판매 전체인원영업판매 전체인원(남성)영업판매 전체인원(여성)단순노무 전체인원단순노무 전체인원(남성)단순노무 전체인원(여성)구분별(1)
경영관리 전체인원1.000-0.2390.2390.010-0.0970.165-0.169-0.0480.124-0.510-0.2110.2110.175-0.4050.483-0.047-0.1500.1500.000
경영관리 전체인원(남성)-0.2391.000-1.0000.1140.122-0.279-0.0990.314-0.4820.3670.323-0.323-0.1200.199-0.366-0.1460.278-0.2780.000
경영관리 전체인원(여성)0.239-1.0001.000-0.114-0.1220.2790.099-0.3140.482-0.367-0.3230.3230.120-0.1990.3660.146-0.2780.2780.000
연구개발 전체인원0.0100.114-0.1141.000-0.0200.1820.5130.221-0.050-0.256-0.1710.171-0.024-0.0830.252-0.0790.204-0.2040.000
연구개발 전체인원(남성)-0.0970.122-0.122-0.0201.000-0.853-0.0950.457-0.3000.319-0.0740.0740.1500.561-0.409-0.3140.459-0.4590.392
연구개발 전체인원(여성)0.165-0.2790.2790.182-0.8531.0000.263-0.3050.461-0.473-0.0870.0870.005-0.4040.5600.442-0.2990.2990.375
일반사무 전체인원-0.169-0.0990.0990.513-0.0950.2631.0000.0080.163-0.148-0.0760.076-0.244-0.1420.313-0.0460.207-0.2070.000
일반사무 전체인원(남성)-0.0480.314-0.3140.2210.457-0.3050.0081.000-0.8340.1620.137-0.1370.4710.233-0.072-0.3830.531-0.5310.000
일반사무 전체인원(여성)0.124-0.4820.482-0.050-0.3000.4610.163-0.8341.000-0.330-0.3050.305-0.300-0.0660.2330.519-0.3600.3600.000
기능생산 전체인원-0.5100.367-0.367-0.2560.319-0.473-0.1480.162-0.3301.0000.554-0.554-0.2190.316-0.484-0.4880.405-0.4050.000
기능생산 전체인원(남성)-0.2110.323-0.323-0.171-0.074-0.087-0.0760.137-0.3050.5541.000-1.000-0.227-0.067-0.102-0.2320.281-0.2810.000
기능생산 전체인원(여성)0.211-0.3230.3230.1710.0740.0870.076-0.1370.305-0.554-1.0001.0000.2270.0670.1020.232-0.2810.2810.000
영업판매 전체인원0.175-0.1200.120-0.0240.1500.005-0.2440.471-0.300-0.219-0.2270.2271.0000.1430.022-0.0940.127-0.1270.000
영업판매 전체인원(남성)-0.4050.199-0.199-0.0830.561-0.404-0.1420.233-0.0660.316-0.0670.0670.1431.000-0.839-0.0570.278-0.2780.000
영업판매 전체인원(여성)0.483-0.3660.3660.252-0.4090.5600.313-0.0720.233-0.484-0.1020.1020.022-0.8391.0000.193-0.1120.1120.297
단순노무 전체인원-0.047-0.1460.146-0.079-0.3140.442-0.046-0.3830.519-0.488-0.2320.232-0.094-0.0570.1931.000-0.5450.5450.000
단순노무 전체인원(남성)-0.1500.278-0.2780.2040.459-0.2990.2070.531-0.3600.4050.281-0.2810.1270.278-0.112-0.5451.000-1.0000.176
단순노무 전체인원(여성)0.150-0.2780.278-0.204-0.4590.299-0.207-0.5310.360-0.405-0.2810.281-0.127-0.2780.1120.545-1.0001.0000.176
구분별(1)0.0000.0000.0000.0000.3920.3750.0000.0000.0000.0000.0000.0000.0000.0000.2970.0000.1760.1761.000

Missing values

2023-12-12T15:14:26.781017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:14:26.986819image/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

구분별(1)구분별(2)경영관리 전체인원경영관리 전체인원(남성)경영관리 전체인원(여성)연구개발 전체인원연구개발 전체인원(남성)연구개발 전체인원(여성)일반사무 전체인원일반사무 전체인원(남성)일반사무 전체인원(여성)기능생산 전체인원기능생산 전체인원(남성)기능생산 전체인원(여성)영업판매 전체인원영업판매 전체인원(남성)영업판매 전체인원(여성)단순노무 전체인원단순노무 전체인원(남성)단순노무 전체인원(여성)
0업력1년42.280.719.35.921.578.516.736.863.214.380.319.73.251.648.417.617.083.0
1업력2년41.278.022.03.874.026.012.434.965.119.271.029.08.166.733.315.329.470.6
2업력3년36.681.818.22.177.322.711.930.969.120.581.019.07.967.932.121.030.369.7
3업력4년34.664.935.13.455.944.117.030.969.128.390.59.54.557.842.212.239.960.1
4업력5년34.477.822.28.789.110.916.340.859.219.085.514.56.554.245.815.136.263.8
5업력6년34.779.320.74.265.634.416.139.260.820.267.832.29.647.852.215.044.056.0
6업력7년32.079.720.34.171.328.719.646.153.920.580.419.68.565.234.815.238.062.0
7업종농업, 임업 및 어업35.676.923.13.976.323.77.323.476.635.282.617.44.478.521.513.651.348.7
8업종광업24.892.27.81.8100.00.04.586.513.541.596.33.720.8100.00.06.758.441.6
9업종제조업29.184.215.85.790.010.013.958.541.535.276.024.04.578.921.111.654.945.1
구분별(1)구분별(2)경영관리 전체인원경영관리 전체인원(남성)경영관리 전체인원(여성)연구개발 전체인원연구개발 전체인원(남성)연구개발 전체인원(여성)일반사무 전체인원일반사무 전체인원(남성)일반사무 전체인원(여성)기능생산 전체인원기능생산 전체인원(남성)기능생산 전체인원(여성)영업판매 전체인원영업판매 전체인원(남성)영업판매 전체인원(여성)단순노무 전체인원단순노무 전체인원(남성)단순노무 전체인원(여성)
24업종수리 및 기타 개인 서비스업40.074.725.31.0100.00.02.80.0100.018.379.220.83.0100.00.034.94.895.2
25기업형태개인39.876.623.44.431.069.015.619.180.913.075.224.86.651.948.120.520.779.3
26기업형태법인35.377.822.24.780.219.815.445.954.124.082.117.96.863.436.613.840.759.3
27창업자 성별남성36.980.319.75.065.134.915.838.761.321.682.317.76.662.637.414.035.564.5
28창업자 성별여성36.165.035.02.761.039.014.329.071.015.270.529.57.348.551.524.324.575.5
29창업자 연령20대 이하29.189.011.00.732.167.99.835.764.320.774.225.83.180.419.636.68.791.3
30창업자 연령30대45.378.022.02.337.362.713.032.667.413.575.324.77.241.258.818.736.363.7
31창업자 연령40대38.676.323.75.846.853.216.329.470.617.773.426.66.664.935.115.030.469.6
32창업자 연령50대34.276.223.84.775.324.717.143.156.922.383.416.67.063.636.414.635.964.1
33창업자 연령60대 이상32.879.620.44.691.58.513.941.158.926.386.713.36.457.942.115.931.468.6