Overview

Dataset statistics

Number of variables11
Number of observations50
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory99.6 B

Variable types

Categorical1
Text1
Numeric9

Dataset

Description창업의사 및 창업계획 관련(창업 의사 및 계획, 군구별 성별, 연령별, 학력별, 직업별, 월평균소득별) 정보입니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15066400&srcSe=7661IVAWM27C61E190

Alerts

창업의향 있음 is highly overall correlated with 창업의향 없음 and 6 other fieldsHigh correlation
창업의향 없음 is highly overall correlated with 창업의향 있음 and 6 other fieldsHigh correlation
창업계획기간(1년 이내) is highly overall correlated with 창업의향 있음 and 4 other fieldsHigh correlation
창업계획기간(1년_3년 이내) is highly overall correlated with 창업의향 있음 and 4 other fieldsHigh correlation
창업계획기간(3년_5년 이내) is highly overall correlated with 창업의향 있음 and 5 other fieldsHigh correlation
창업계획기간(5년 이후) is highly overall correlated with 창업의향 있음 and 5 other fieldsHigh correlation
창업계획기간(창업할 의향은 있으나 구체적인 계획은 없음) is highly overall correlated with 창업의향 있음 and 6 other fieldsHigh correlation
창업계획기간(창업할 의향이 없음) is highly overall correlated with 창업의향 있음 and 5 other fieldsHigh correlation
창업계획기간(이미 창업을 하였음) is highly overall correlated with 창업계획기간(창업할 의향이 없음)High correlation
특성별(2) has unique valuesUnique
창업계획기간(1년 이내) has 2 (4.0%) zerosZeros
창업계획기간(1년_3년 이내) has 1 (2.0%) zerosZeros
창업계획기간(3년_5년 이내) has 1 (2.0%) zerosZeros
창업계획기간(5년 이후) has 4 (8.0%) zerosZeros
창업계획기간(창업할 의향은 있으나 구체적인 계획은 없음) has 1 (2.0%) zerosZeros

Reproduction

Analysis started2024-03-18 02:18:09.828701
Analysis finished2024-03-18 02:18:17.250524
Duration7.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

특성별(1)
Categorical

Distinct9
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
군구별
10 
직업별
월평균소득별
연령별
가구원수별
Other values (4)
13 

Length

Max length7
Median length3
Mean length4.04
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군구별 10
20.0%
직업별 8
16.0%
월평균소득별 8
16.0%
연령별 6
12.0%
가구원수별 5
10.0%
학력별 4
 
8.0%
주거형태별 4
 
8.0%
주거점유형태별 3
 
6.0%
성별 2
 
4.0%

Length

2024-03-18T11:18:17.313974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:18:17.412684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군구별 10
20.0%
직업별 8
16.0%
월평균소득별 8
16.0%
연령별 6
12.0%
가구원수별 5
10.0%
학력별 4
 
8.0%
주거형태별 4
 
8.0%
주거점유형태별 3
 
6.0%
성별 2
 
4.0%

특성별(2)
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-18T11:18:17.596662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length7.5
Mean length4.92
Min length2

Characters and Unicode

Total characters246
Distinct characters76
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)100.0%

Sample

1st row중구
2nd row동구
3rd row미추홀구
4th row연수구
5th row남동구
ValueCountFrequency (%)
미만 7
 
9.7%
5
 
6.9%
이상 3
 
4.2%
기타 2
 
2.8%
중구 1
 
1.4%
기능노무 1
 
1.4%
4인 1
 
1.4%
학생 1
 
1.4%
주부 1
 
1.4%
무직/기타 1
 
1.4%
Other values (49) 49
68.1%
2024-03-18T11:18:17.864057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33
 
13.4%
22
 
8.9%
15
 
6.1%
~ 11
 
4.5%
9
 
3.7%
8
 
3.3%
8
 
3.3%
8
 
3.3%
3 6
 
2.4%
5
 
2.0%
Other values (66) 121
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 142
57.7%
Decimal Number 69
28.0%
Space Separator 22
 
8.9%
Math Symbol 11
 
4.5%
Other Punctuation 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
15
 
10.6%
9
 
6.3%
8
 
5.6%
8
 
5.6%
8
 
5.6%
5
 
3.5%
5
 
3.5%
4
 
2.8%
4
 
2.8%
4
 
2.8%
Other values (54) 72
50.7%
Decimal Number
ValueCountFrequency (%)
0 33
47.8%
3 6
 
8.7%
9 5
 
7.2%
5 5
 
7.2%
4 5
 
7.2%
2 5
 
7.2%
1 5
 
7.2%
6 3
 
4.3%
7 2
 
2.9%
Space Separator
ValueCountFrequency (%)
22
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 142
57.7%
Common 104
42.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
15
 
10.6%
9
 
6.3%
8
 
5.6%
8
 
5.6%
8
 
5.6%
5
 
3.5%
5
 
3.5%
4
 
2.8%
4
 
2.8%
4
 
2.8%
Other values (54) 72
50.7%
Common
ValueCountFrequency (%)
0 33
31.7%
22
21.2%
~ 11
 
10.6%
3 6
 
5.8%
9 5
 
4.8%
5 5
 
4.8%
4 5
 
4.8%
2 5
 
4.8%
1 5
 
4.8%
6 3
 
2.9%
Other values (2) 4
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 142
57.7%
ASCII 104
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 33
31.7%
22
21.2%
~ 11
 
10.6%
3 6
 
5.8%
9 5
 
4.8%
5 5
 
4.8%
4 5
 
4.8%
2 5
 
4.8%
1 5
 
4.8%
6 3
 
2.9%
Other values (2) 4
 
3.8%
Hangul
ValueCountFrequency (%)
15
 
10.6%
9
 
6.3%
8
 
5.6%
8
 
5.6%
8
 
5.6%
5
 
3.5%
5
 
3.5%
4
 
2.8%
4
 
2.8%
4
 
2.8%
Other values (54) 72
50.7%

창업의향 있음
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.534
Minimum0.6
Maximum16.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:18:17.970206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile1.875
Q15.85
median9.05
Q310.9
95-th percentile14.175
Maximum16.3
Range15.7
Interquartile range (IQR)5.05

Descriptive statistics

Standard deviation3.7082154
Coefficient of variation (CV)0.43452254
Kurtosis-0.23163653
Mean8.534
Median Absolute Deviation (MAD)2.05
Skewness-0.25461839
Sum426.7
Variance13.750861
MonotonicityNot monotonic
2024-03-18T11:18:18.076330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
11.1 3
 
6.0%
4.6 3
 
6.0%
10.7 3
 
6.0%
10.9 2
 
4.0%
8.0 2
 
4.0%
2.7 2
 
4.0%
7.8 2
 
4.0%
6.3 1
 
2.0%
4.5 1
 
2.0%
11.7 1
 
2.0%
Other values (30) 30
60.0%
ValueCountFrequency (%)
0.6 1
 
2.0%
0.9 1
 
2.0%
1.2 1
 
2.0%
2.7 2
4.0%
3.5 1
 
2.0%
4.5 1
 
2.0%
4.6 3
6.0%
5.3 1
 
2.0%
5.5 1
 
2.0%
5.7 1
 
2.0%
ValueCountFrequency (%)
16.3 1
 
2.0%
15.7 1
 
2.0%
14.4 1
 
2.0%
13.9 1
 
2.0%
13.4 1
 
2.0%
13.1 1
 
2.0%
11.7 1
 
2.0%
11.3 1
 
2.0%
11.2 1
 
2.0%
11.1 3
6.0%

창업의향 없음
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.466
Minimum83.7
Maximum99.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:18:18.187876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum83.7
5-th percentile85.825
Q189.1
median90.95
Q394.15
95-th percentile98.125
Maximum99.4
Range15.7
Interquartile range (IQR)5.05

Descriptive statistics

Standard deviation3.7082154
Coefficient of variation (CV)0.040542009
Kurtosis-0.23163653
Mean91.466
Median Absolute Deviation (MAD)2.05
Skewness0.25461839
Sum4573.3
Variance13.750861
MonotonicityNot monotonic
2024-03-18T11:18:18.293725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
88.9 3
 
6.0%
95.4 3
 
6.0%
89.3 3
 
6.0%
89.1 2
 
4.0%
92.0 2
 
4.0%
97.3 2
 
4.0%
92.2 2
 
4.0%
93.7 1
 
2.0%
95.5 1
 
2.0%
88.3 1
 
2.0%
Other values (30) 30
60.0%
ValueCountFrequency (%)
83.7 1
 
2.0%
84.3 1
 
2.0%
85.6 1
 
2.0%
86.1 1
 
2.0%
86.6 1
 
2.0%
86.9 1
 
2.0%
88.3 1
 
2.0%
88.7 1
 
2.0%
88.8 1
 
2.0%
88.9 3
6.0%
ValueCountFrequency (%)
99.4 1
 
2.0%
99.1 1
 
2.0%
98.8 1
 
2.0%
97.3 2
4.0%
96.5 1
 
2.0%
95.5 1
 
2.0%
95.4 3
6.0%
94.7 1
 
2.0%
94.5 1
 
2.0%
94.3 1
 
2.0%

창업계획기간(1년 이내)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.62
Minimum0
Maximum1.6
Zeros2
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:18:18.522606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.145
Q10.4
median0.6
Q30.8
95-th percentile1.11
Maximum1.6
Range1.6
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.33258419
Coefficient of variation (CV)0.53642612
Kurtosis1.0260399
Mean0.62
Median Absolute Deviation (MAD)0.2
Skewness0.65668803
Sum31
Variance0.11061224
MonotonicityNot monotonic
2024-03-18T11:18:18.648521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0.6 7
14.0%
0.4 6
12.0%
0.9 6
12.0%
0.5 6
12.0%
0.3 5
10.0%
0.7 5
10.0%
0.8 4
8.0%
1.0 3
6.0%
0.0 2
 
4.0%
0.2 2
 
4.0%
Other values (4) 4
8.0%
ValueCountFrequency (%)
0.0 2
 
4.0%
0.1 1
 
2.0%
0.2 2
 
4.0%
0.3 5
10.0%
0.4 6
12.0%
0.5 6
12.0%
0.6 7
14.0%
0.7 5
10.0%
0.8 4
8.0%
0.9 6
12.0%
ValueCountFrequency (%)
1.6 1
 
2.0%
1.5 1
 
2.0%
1.2 1
 
2.0%
1.0 3
6.0%
0.9 6
12.0%
0.8 4
8.0%
0.7 5
10.0%
0.6 7
14.0%
0.5 6
12.0%
0.4 6
12.0%

창업계획기간(1년_3년 이내)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.876
Minimum0
Maximum2.2
Zeros1
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:18:18.751634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.2
Q10.525
median0.9
Q31.1
95-th percentile1.555
Maximum2.2
Range2.2
Interquartile range (IQR)0.575

Descriptive statistics

Standard deviation0.4547078
Coefficient of variation (CV)0.51907283
Kurtosis0.21824356
Mean0.876
Median Absolute Deviation (MAD)0.3
Skewness0.20172853
Sum43.8
Variance0.20675918
MonotonicityNot monotonic
2024-03-18T11:18:18.833429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
1.1 6
12.0%
1.0 5
10.0%
1.3 5
10.0%
0.7 5
10.0%
0.9 5
10.0%
0.2 4
8.0%
0.5 4
8.0%
0.8 3
 
6.0%
0.3 3
 
6.0%
1.4 2
 
4.0%
Other values (7) 8
16.0%
ValueCountFrequency (%)
0.0 1
 
2.0%
0.1 1
 
2.0%
0.2 4
8.0%
0.3 3
6.0%
0.5 4
8.0%
0.6 1
 
2.0%
0.7 5
10.0%
0.8 3
6.0%
0.9 5
10.0%
1.0 5
10.0%
ValueCountFrequency (%)
2.2 1
 
2.0%
1.6 2
 
4.0%
1.5 1
 
2.0%
1.4 2
 
4.0%
1.3 5
10.0%
1.2 1
 
2.0%
1.1 6
12.0%
1.0 5
10.0%
0.9 5
10.0%
0.8 3
6.0%

창업계획기간(3년_5년 이내)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.936
Minimum0
Maximum2.4
Zeros1
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:18:18.917879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.2
Q10.7
median0.9
Q31.2
95-th percentile1.765
Maximum2.4
Range2.4
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.48687257
Coefficient of variation (CV)0.520163
Kurtosis0.75677625
Mean0.936
Median Absolute Deviation (MAD)0.2
Skewness0.47693222
Sum46.8
Variance0.2370449
MonotonicityNot monotonic
2024-03-18T11:18:19.006175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.8 8
16.0%
1.0 5
10.0%
0.7 5
10.0%
0.9 4
 
8.0%
0.3 4
 
8.0%
1.1 4
 
8.0%
1.3 4
 
8.0%
1.6 2
 
4.0%
1.9 2
 
4.0%
1.4 2
 
4.0%
Other values (8) 10
20.0%
ValueCountFrequency (%)
0.0 1
 
2.0%
0.1 1
 
2.0%
0.2 2
 
4.0%
0.3 4
8.0%
0.4 1
 
2.0%
0.5 1
 
2.0%
0.7 5
10.0%
0.8 8
16.0%
0.9 4
8.0%
1.0 5
10.0%
ValueCountFrequency (%)
2.4 1
 
2.0%
1.9 2
 
4.0%
1.6 2
 
4.0%
1.5 1
 
2.0%
1.4 2
 
4.0%
1.3 4
8.0%
1.2 2
 
4.0%
1.1 4
8.0%
1.0 5
10.0%
0.9 4
8.0%

창업계획기간(5년 이후)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.796
Minimum0
Maximum1.9
Zeros4
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:18:19.093871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.525
median0.7
Q31.1
95-th percentile1.5
Maximum1.9
Range1.9
Interquartile range (IQR)0.575

Descriptive statistics

Standard deviation0.46333309
Coefficient of variation (CV)0.58207674
Kurtosis-0.36580616
Mean0.796
Median Absolute Deviation (MAD)0.3
Skewness0.23813816
Sum39.8
Variance0.21467755
MonotonicityNot monotonic
2024-03-18T11:18:19.199497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.6 9
18.0%
1.1 5
10.0%
0.8 4
8.0%
0.7 4
8.0%
1.5 4
8.0%
0.0 4
8.0%
1.0 4
8.0%
0.5 3
 
6.0%
0.4 2
 
4.0%
1.3 2
 
4.0%
Other values (8) 9
18.0%
ValueCountFrequency (%)
0.0 4
8.0%
0.1 1
 
2.0%
0.2 1
 
2.0%
0.3 2
 
4.0%
0.4 2
 
4.0%
0.5 3
 
6.0%
0.6 9
18.0%
0.7 4
8.0%
0.8 4
8.0%
0.9 1
 
2.0%
ValueCountFrequency (%)
1.9 1
 
2.0%
1.7 1
 
2.0%
1.5 4
8.0%
1.4 1
 
2.0%
1.3 2
 
4.0%
1.2 1
 
2.0%
1.1 5
10.0%
1.0 4
8.0%
0.9 1
 
2.0%
0.8 4
8.0%
Distinct40
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.292
Minimum0
Maximum9.9
Zeros1
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:18:19.300954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.79
Q13.575
median5.8
Q36.875
95-th percentile9.065
Maximum9.9
Range9.9
Interquartile range (IQR)3.3

Descriptive statistics

Standard deviation2.4416321
Coefficient of variation (CV)0.46138173
Kurtosis-0.40359471
Mean5.292
Median Absolute Deviation (MAD)1.45
Skewness-0.28736921
Sum264.6
Variance5.9615673
MonotonicityNot monotonic
2024-03-18T11:18:19.461545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
7.4 2
 
4.0%
6.8 2
 
4.0%
6.6 2
 
4.0%
7.2 2
 
4.0%
6.3 2
 
4.0%
9.9 2
 
4.0%
3.5 2
 
4.0%
6.2 2
 
4.0%
5.1 2
 
4.0%
7.1 2
 
4.0%
Other values (30) 30
60.0%
ValueCountFrequency (%)
0.0 1
2.0%
0.5 1
2.0%
0.7 1
2.0%
0.9 1
2.0%
1.6 1
2.0%
1.8 1
2.0%
2.4 1
2.0%
2.5 1
2.0%
3.0 1
2.0%
3.2 1
2.0%
ValueCountFrequency (%)
9.9 2
4.0%
9.2 1
2.0%
8.9 1
2.0%
8.7 1
2.0%
8.0 1
2.0%
7.4 2
4.0%
7.2 2
4.0%
7.1 2
4.0%
6.9 1
2.0%
6.8 2
4.0%

창업계획기간(창업할 의향이 없음)
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.778
Minimum62.3
Maximum94.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:18:19.578700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum62.3
5-th percentile73.65
Q177.925
median81.65
Q385.65
95-th percentile92.09
Maximum94.1
Range31.8
Interquartile range (IQR)7.725

Descriptive statistics

Standard deviation6.0872999
Coefficient of variation (CV)0.074436889
Kurtosis1.403227
Mean81.778
Median Absolute Deviation (MAD)3.9
Skewness-0.46755802
Sum4088.9
Variance37.05522
MonotonicityNot monotonic
2024-03-18T11:18:19.683619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
88.2 2
 
4.0%
81.3 2
 
4.0%
76.7 2
 
4.0%
77.6 1
 
2.0%
74.2 1
 
2.0%
91.1 1
 
2.0%
93.4 1
 
2.0%
84.9 1
 
2.0%
81.9 1
 
2.0%
81.5 1
 
2.0%
Other values (37) 37
74.0%
ValueCountFrequency (%)
62.3 1
2.0%
67.7 1
2.0%
73.2 1
2.0%
74.2 1
2.0%
75.7 1
2.0%
76.3 1
2.0%
76.7 2
4.0%
77.0 1
2.0%
77.1 1
2.0%
77.5 1
2.0%
ValueCountFrequency (%)
94.1 1
2.0%
93.4 1
2.0%
92.9 1
2.0%
91.1 1
2.0%
88.9 1
2.0%
88.7 1
2.0%
88.2 2
4.0%
87.7 1
2.0%
86.6 1
2.0%
86.3 1
2.0%

창업계획기간(이미 창업을 하였음)
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.692
Minimum0.6
Maximum26.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-18T11:18:19.795605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile1.725
Q17.3
median9.5
Q311.7
95-th percentile18.145
Maximum26.6
Range26
Interquartile range (IQR)4.4

Descriptive statistics

Standard deviation4.8282265
Coefficient of variation (CV)0.49816617
Kurtosis3.2105861
Mean9.692
Median Absolute Deviation (MAD)2.25
Skewness1.1113735
Sum484.6
Variance23.311771
MonotonicityNot monotonic
2024-03-18T11:18:19.907120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
7.3 2
 
4.0%
10.0 2
 
4.0%
9.4 2
 
4.0%
12.5 2
 
4.0%
9.6 2
 
4.0%
11.9 2
 
4.0%
6.9 2
 
4.0%
11.4 2
 
4.0%
0.6 1
 
2.0%
1.0 1
 
2.0%
Other values (32) 32
64.0%
ValueCountFrequency (%)
0.6 1
2.0%
1.0 1
2.0%
1.5 1
2.0%
2.0 1
2.0%
3.6 1
2.0%
5.5 1
2.0%
5.6 1
2.0%
6.2 1
2.0%
6.4 1
2.0%
6.9 2
4.0%
ValueCountFrequency (%)
26.6 1
2.0%
23.3 1
2.0%
19.0 1
2.0%
17.1 1
2.0%
14.9 1
2.0%
13.4 1
2.0%
12.5 2
4.0%
12.2 1
2.0%
12.1 1
2.0%
11.9 2
4.0%

Interactions

2024-03-18T11:18:15.992223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:10.141787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:10.857164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:11.513481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.501514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:13.104555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:13.754012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:14.571355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:15.322024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:16.159198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:10.225251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:10.932357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:11.597895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.570350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:13.174860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:13.830850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:14.664539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:15.414426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:16.331444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:10.320042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:11.005555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:11.701517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.641441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:13.248370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:13.972291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:14.753672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:15.507037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:16.410834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:10.412763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:11.091140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.061138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.728039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:13.321250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:14.097445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:14.859591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:15.581443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:16.474029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:10.493368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:11.158635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.125940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.786943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:13.384243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:14.165870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:14.948251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:15.644861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:16.755236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:10.573234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:11.226581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.195425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.847826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:13.450900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:14.236271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:15.014139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:15.717869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:16.822199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:10.649132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:11.303622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.272248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.915736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:13.538933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:14.314323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:15.088430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:15.788397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:16.886979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:10.716869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:11.373154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.340981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.978383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:13.605543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:14.382276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:15.155613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:15.853086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:16.951533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:10.786135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:11.445076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:12.420195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:13.042969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:13.687294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:14.477311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:15.240353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:18:15.921355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T11:18:19.985364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특성별(1)특성별(2)창업의향 있음창업의향 없음창업계획기간(1년 이내)창업계획기간(1년_3년 이내)창업계획기간(3년_5년 이내)창업계획기간(5년 이후)창업계획기간(창업할 의향은 있으나 구체적인 계획은 없음)창업계획기간(창업할 의향이 없음)창업계획기간(이미 창업을 하였음)
특성별(1)1.0001.0000.0000.0000.5820.4640.0000.0000.0000.0000.104
특성별(2)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
창업의향 있음0.0001.0001.0001.0000.5340.6900.6920.8660.9420.5700.585
창업의향 없음0.0001.0001.0001.0000.5340.6900.6920.8660.9420.5700.585
창업계획기간(1년 이내)0.5821.0000.5340.5341.0000.6720.5950.6080.4470.3650.000
창업계획기간(1년_3년 이내)0.4641.0000.6900.6900.6721.0000.7260.5060.7100.5100.416
창업계획기간(3년_5년 이내)0.0001.0000.6920.6920.5950.7261.0000.5910.5840.2980.558
창업계획기간(5년 이후)0.0001.0000.8660.8660.6080.5060.5911.0000.7100.5210.000
창업계획기간(창업할 의향은 있으나 구체적인 계획은 없음)0.0001.0000.9420.9420.4470.7100.5840.7101.0000.5380.435
창업계획기간(창업할 의향이 없음)0.0001.0000.5700.5700.3650.5100.2980.5210.5381.0000.852
창업계획기간(이미 창업을 하였음)0.1041.0000.5850.5850.0000.4160.5580.0000.4350.8521.000
2024-03-18T11:18:20.100773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
창업의향 있음창업의향 없음창업계획기간(1년 이내)창업계획기간(1년_3년 이내)창업계획기간(3년_5년 이내)창업계획기간(5년 이후)창업계획기간(창업할 의향은 있으나 구체적인 계획은 없음)창업계획기간(창업할 의향이 없음)창업계획기간(이미 창업을 하였음)특성별(1)
창업의향 있음1.000-1.0000.6980.6700.7500.8450.945-0.6990.0790.000
창업의향 없음-1.0001.000-0.698-0.670-0.750-0.845-0.9450.699-0.0790.000
창업계획기간(1년 이내)0.698-0.6981.0000.6350.4370.5260.599-0.413-0.0640.076
창업계획기간(1년_3년 이내)0.670-0.6700.6351.0000.5770.4840.514-0.404-0.0410.111
창업계획기간(3년_5년 이내)0.750-0.7500.4370.5771.0000.6930.637-0.5460.0590.000
창업계획기간(5년 이후)0.845-0.8450.5260.4840.6931.0000.766-0.553-0.0030.000
창업계획기간(창업할 의향은 있으나 구체적인 계획은 없음)0.945-0.9450.5990.5140.6370.7661.000-0.6810.1040.000
창업계획기간(창업할 의향이 없음)-0.6990.699-0.413-0.404-0.546-0.553-0.6811.000-0.7040.000
창업계획기간(이미 창업을 하였음)0.079-0.079-0.064-0.0410.059-0.0030.104-0.7041.0000.000
특성별(1)0.0000.0000.0760.1110.0000.0000.0000.0000.0001.000

Missing values

2024-03-18T11:18:17.040272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T11:18:17.193130image/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

특성별(1)특성별(2)창업의향 있음창업의향 없음창업계획기간(1년 이내)창업계획기간(1년_3년 이내)창업계획기간(3년_5년 이내)창업계획기간(5년 이후)창업계획기간(창업할 의향은 있으나 구체적인 계획은 없음)창업계획기간(창업할 의향이 없음)창업계획기간(이미 창업을 하였음)
0군구별중구2.797.30.01.40.40.30.788.29.1
1군구별동구9.890.20.41.21.10.66.780.89.4
2군구별미추홀구4.695.40.30.20.30.73.286.68.8
3군구별연수구5.594.50.10.20.50.24.682.711.8
4군구별남동구7.892.20.60.71.00.35.284.47.8
5군구별부평구15.784.30.92.21.91.59.277.96.4
6군구별계양구4.695.40.50.30.70.62.583.012.5
7군구별서구16.383.71.61.61.41.79.973.210.5
8군구별강화군1.298.80.30.10.20.00.588.210.6
9군구별옹진군0.699.40.30.20.20.00.082.317.1
특성별(1)특성별(2)창업의향 있음창업의향 없음창업계획기간(1년 이내)창업계획기간(1년_3년 이내)창업계획기간(3년_5년 이내)창업계획기간(5년 이후)창업계획기간(창업할 의향은 있으나 구체적인 계획은 없음)창업계획기간(창업할 의향이 없음)창업계획기간(이미 창업을 하였음)
40주거형태별연립/다세대주택7.892.20.50.91.01.14.384.87.3
41주거형태별기타10.289.81.01.32.41.04.476.313.4
42주거점유형태별자가8.391.70.60.80.80.65.681.310.4
43주거점유형태별전세11.388.71.21.11.11.56.381.37.4
44주거점유형태별월세 및 기타11.288.80.61.61.91.06.081.87.0
45가구원수별1인6.993.10.40.70.81.13.885.97.3
46가구원수별2인6.393.70.50.81.00.63.486.17.6
47가구원수별3인9.390.70.90.70.80.66.381.09.7
48가구원수별4인11.788.30.71.31.30.97.477.610.7
49가구원수별5인 이상11.188.90.71.30.71.37.177.511.4