Overview

Dataset statistics

Number of variables7
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory64.9 B

Variable types

Categorical1
Text1
Numeric5

Dataset

Description창업기업의 사업장 입지 현황별 업력, 창업기업의 사업장 입지 현황별 업종, 창업기업의 사업장 입지 현황별 기업형태, 창업기업의 사업장 입지 현황별 성별, 창업기업의 사업장 입지 현황별 연령 현황
URLhttps://www.data.go.kr/data/15037552/fileData.do

Alerts

대학 및 연구기관 is highly overall correlated with 산업단지High correlation
산업단지 is highly overall correlated with 대학 및 연구기관 and 1 other fieldsHigh correlation
일반상업지역 is highly overall correlated with 기타지역High correlation
일반주택지역 is highly overall correlated with 산업단지High correlation
기타지역 is highly overall correlated with 일반상업지역High correlation
구분별(2) has unique valuesUnique
대학 및 연구기관 has 10 (29.4%) zerosZeros
산업단지 has 1 (2.9%) zerosZeros

Reproduction

Analysis started2023-12-12 04:19:44.894528
Analysis finished2023-12-12 04:19:48.254185
Duration3.36 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
7 
창업자 연령
5 
기업형태
2 
창업자 성별
2 

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

2023-12-12T13:19:48.336862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:19:48.461728image/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
2023-12-12T13:19:48.732901image/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 (%)
및 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%
2023-12-12T13:19:49.220411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
18.9%
업 23
 
9.4%
및 12
 
4.9%
, 8
 
3.3%
스 8
 
3.3%
년 7
 
2.9%
기 6
 
2.5%
비 6
 
2.5%
대 6
 
2.5%
서 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 (%)
업 23
 
13.3%
및 12
 
6.9%
스 8
 
4.6%
년 7
 
4.0%
기 6
 
3.5%
비 6
 
3.5%
대 6
 
3.5%
서 6
 
3.5%
수 4
 
2.3%
사 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 (%)
업 23
 
13.3%
및 12
 
6.9%
스 8
 
4.6%
년 7
 
4.0%
기 6
 
3.5%
비 6
 
3.5%
대 6
 
3.5%
서 6
 
3.5%
수 4
 
2.3%
사 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 (%)
업 23
 
13.3%
및 12
 
6.9%
스 8
 
4.6%
년 7
 
4.0%
기 6
 
3.5%
비 6
 
3.5%
대 6
 
3.5%
서 6
 
3.5%
수 4
 
2.3%
사 3
 
1.7%
Other values (68) 92
53.2%

대학 및 연구기관
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0294118
Minimum0
Maximum8.3
Zeros10
Zeros (%)29.4%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:19:49.398332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.5
Q31.075
95-th percentile3.735
Maximum8.3
Range8.3
Interquartile range (IQR)1.075

Descriptive statistics

Standard deviation1.74643
Coefficient of variation (CV)1.696532
Kurtosis10.948998
Mean1.0294118
Median Absolute Deviation (MAD)0.5
Skewness3.2079097
Sum35
Variance3.0500178
MonotonicityNot monotonic
2023-12-12T13:19:49.578460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 10
29.4%
0.4 5
14.7%
0.6 3
 
8.8%
1.1 2
 
5.9%
1.0 2
 
5.9%
8.3 1
 
2.9%
0.9 1
 
2.9%
0.3 1
 
2.9%
2.3 1
 
2.9%
1.2 1
 
2.9%
Other values (7) 7
20.6%
ValueCountFrequency (%)
0.0 10
29.4%
0.2 1
 
2.9%
0.3 1
 
2.9%
0.4 5
14.7%
0.6 3
 
8.8%
0.7 1
 
2.9%
0.8 1
 
2.9%
0.9 1
 
2.9%
1.0 2
 
5.9%
1.1 2
 
5.9%
ValueCountFrequency (%)
8.3 1
2.9%
6.4 1
2.9%
2.3 1
2.9%
2.2 1
2.9%
2.0 1
2.9%
1.7 1
2.9%
1.2 1
2.9%
1.1 2
5.9%
1.0 2
5.9%
0.9 1
2.9%

산업단지
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6088235
Minimum0
Maximum29.8
Zeros1
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:19:49.707494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.3
Q14.1
median5.6
Q37.85
95-th percentile26.205
Maximum29.8
Range29.8
Interquartile range (IQR)3.75

Descriptive statistics

Standard deviation7.6846312
Coefficient of variation (CV)1.0099631
Kurtosis2.9239927
Mean7.6088235
Median Absolute Deviation (MAD)2
Skewness1.9185246
Sum258.7
Variance59.053556
MonotonicityNot monotonic
2023-12-12T13:19:49.830014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
4.7 2
 
5.9%
6.6 2
 
5.9%
0.3 2
 
5.9%
8.2 1
 
2.9%
4.4 1
 
2.9%
7.1 1
 
2.9%
0.0 1
 
2.9%
1.3 1
 
2.9%
2.0 1
 
2.9%
6.9 1
 
2.9%
Other values (21) 21
61.8%
ValueCountFrequency (%)
0.0 1
2.9%
0.3 2
5.9%
0.7 1
2.9%
1.3 1
2.9%
2.0 1
2.9%
2.4 1
2.9%
3.2 1
2.9%
4.0 1
2.9%
4.4 1
2.9%
4.5 1
2.9%
ValueCountFrequency (%)
29.8 1
2.9%
26.4 1
2.9%
26.1 1
2.9%
25.2 1
2.9%
13.0 1
2.9%
9.2 1
2.9%
8.5 1
2.9%
8.2 1
2.9%
8.1 1
2.9%
7.1 1
2.9%

일반상업지역
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.158824
Minimum7.2
Maximum78.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:19:50.001980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.2
5-th percentile16.735
Q137.25
median44.45
Q346.95
95-th percentile59.255
Maximum78.4
Range71.2
Interquartile range (IQR)9.7

Descriptive statistics

Standard deviation13.400432
Coefficient of variation (CV)0.31785594
Kurtosis1.9541678
Mean42.158824
Median Absolute Deviation (MAD)4.7
Skewness-0.31831014
Sum1433.4
Variance179.57159
MonotonicityNot monotonic
2023-12-12T13:19:50.469462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
37.1 2
 
5.9%
39.1 1
 
2.9%
43.3 1
 
2.9%
61.4 1
 
2.9%
51.8 1
 
2.9%
32.1 1
 
2.9%
58.1 1
 
2.9%
40.4 1
 
2.9%
47.0 1
 
2.9%
44.4 1
 
2.9%
Other values (23) 23
67.6%
ValueCountFrequency (%)
7.2 1
2.9%
12.9 1
2.9%
18.8 1
2.9%
26.8 1
2.9%
27.1 1
2.9%
32.1 1
2.9%
34.7 1
2.9%
37.1 2
5.9%
37.7 1
2.9%
39.1 1
2.9%
ValueCountFrequency (%)
78.4 1
2.9%
61.4 1
2.9%
58.1 1
2.9%
56.7 1
2.9%
54.6 1
2.9%
51.8 1
2.9%
48.2 1
2.9%
48.0 1
2.9%
47.0 1
2.9%
46.8 1
2.9%

일반주택지역
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.95
Minimum7.9
Maximum61.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:19:50.650409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7.9
5-th percentile13.765
Q125.75
median34.15
Q339.275
95-th percentile49.135
Maximum61.2
Range53.3
Interquartile range (IQR)13.525

Descriptive statistics

Standard deviation11.967817
Coefficient of variation (CV)0.36321143
Kurtosis-0.011690619
Mean32.95
Median Absolute Deviation (MAD)6.4
Skewness-0.13512547
Sum1120.3
Variance143.22864
MonotonicityNot monotonic
2023-12-12T13:19:50.777921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
31.5 2
 
5.9%
40.8 1
 
2.9%
33.5 1
 
2.9%
61.2 1
 
2.9%
49.2 1
 
2.9%
36.7 1
 
2.9%
49.1 1
 
2.9%
38.9 1
 
2.9%
25.0 1
 
2.9%
41.1 1
 
2.9%
Other values (23) 23
67.6%
ValueCountFrequency (%)
7.9 1
2.9%
11.1 1
2.9%
15.2 1
2.9%
15.5 1
2.9%
18.2 1
2.9%
18.3 1
2.9%
20.6 1
2.9%
20.9 1
2.9%
25.0 1
2.9%
28.0 1
2.9%
ValueCountFrequency (%)
61.2 1
2.9%
49.2 1
2.9%
49.1 1
2.9%
49.0 1
2.9%
46.6 1
2.9%
41.8 1
2.9%
41.1 1
2.9%
40.8 1
2.9%
39.4 1
2.9%
38.9 1
2.9%

기타지역
Real number (ℝ)

HIGH CORRELATION 

Distinct32
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.264706
Minimum3.9
Maximum62.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T13:19:50.928925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.9
5-th percentile6.595
Q18.825
median12.9
Q314.775
95-th percentile44.595
Maximum62.7
Range58.8
Interquartile range (IQR)5.95

Descriptive statistics

Standard deviation13.145385
Coefficient of variation (CV)0.80821534
Kurtosis5.4296176
Mean16.264706
Median Absolute Deviation (MAD)3.05
Skewness2.3744174
Sum553
Variance172.80114
MonotonicityNot monotonic
2023-12-12T13:19:51.108126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
13.5 2
 
5.9%
14.0 2
 
5.9%
10.8 1
 
2.9%
13.0 1
 
2.9%
6.4 1
 
2.9%
8.4 1
 
2.9%
6.7 1
 
2.9%
3.9 1
 
2.9%
8.6 1
 
2.9%
12.8 1
 
2.9%
Other values (22) 22
64.7%
ValueCountFrequency (%)
3.9 1
2.9%
6.4 1
2.9%
6.7 1
2.9%
7.2 1
2.9%
7.6 1
2.9%
8.1 1
2.9%
8.2 1
2.9%
8.4 1
2.9%
8.6 1
2.9%
9.5 1
2.9%
ValueCountFrequency (%)
62.7 1
2.9%
53.5 1
2.9%
39.8 1
2.9%
36.9 1
2.9%
29.4 1
2.9%
17.3 1
2.9%
17.2 1
2.9%
15.5 1
2.9%
15.0 1
2.9%
14.1 1
2.9%

Interactions

2023-12-12T13:19:47.454860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:45.233713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:45.825297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:46.430897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:46.961477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:47.589334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:45.333408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:45.953544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:46.535703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:47.056283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:47.702789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:45.463760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:46.088529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:46.644254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:47.141240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:47.795676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:45.608604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:46.210135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:46.767262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:47.232057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:47.909616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:45.719177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:46.312003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:46.863164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:47.332462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:19:51.214522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분별(1)구분별(2)대학 및 연구기관산업단지일반상업지역일반주택지역기타지역
구분별(1)1.0001.0000.0000.4560.0000.4450.000
구분별(2)1.0001.0001.0001.0001.0001.0001.000
대학 및 연구기관0.0001.0001.0000.5860.4570.5570.000
산업단지0.4561.0000.5861.0000.7070.7320.809
일반상업지역0.0001.0000.4570.7071.0000.8650.852
일반주택지역0.4451.0000.5570.7320.8651.0000.574
기타지역0.0001.0000.0000.8090.8520.5741.000
2023-12-12T13:19:51.347711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대학 및 연구기관산업단지일반상업지역일반주택지역기타지역구분별(1)
대학 및 연구기관1.0000.6020.194-0.3450.0510.000
산업단지0.6021.000-0.187-0.7090.4730.294
일반상업지역0.194-0.1871.000-0.111-0.6310.000
일반주택지역-0.345-0.709-0.1111.000-0.3770.241
기타지역0.0510.473-0.631-0.3771.0000.000
구분별(1)0.0000.2940.0000.2410.0001.000

Missing values

2023-12-12T13:19:48.064864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:19:48.205715image/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)대학 및 연구기관산업단지일반상업지역일반주택지역기타지역
0업력1년1.18.239.140.810.8
1업력2년0.64.844.438.012.2
2업력3년0.85.541.438.314.1
3업력4년0.74.746.834.113.6
4업력5년1.15.848.231.513.4
5업력6년0.44.748.031.415.5
6업력7년0.48.145.332.214.0
7업종농업, 임업 및 어업0.09.212.915.262.7
8업종광업1.729.87.27.953.5
9업종제조업2.225.234.720.617.3
구분별(1)구분별(2)대학 및 연구기관산업단지일반상업지역일반주택지역기타지역
24업종수리 및 기타 개인 서비스업0.02.040.449.18.6
25기업형태개인0.44.443.338.913.0
26기업형태법인2.313.047.025.012.8
27창업자 성별남성1.06.943.633.515.0
28창업자 성별여성0.44.544.541.19.5
29창업자 연령20대 이하0.33.245.936.614.0
30창업자 연령30대0.45.044.939.410.2
31창업자 연령40대1.06.545.635.411.5
32창업자 연령50대0.96.145.234.213.5
33창업자 연령60대 이상0.66.637.138.517.2