Overview

Dataset statistics

Number of variables4
Number of observations50
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory36.6 B

Variable types

Categorical1
Text1
Numeric2

Dataset

Description지난 1년간 구직활동 여부와 경로(공공취업지원기관, 인터넷 취업사이트 등) 자료입니다.* 공공취업지원기관(워크넷 등 포함)/ 인터넷 취업사이트/친척, 친구, 동료 등 주변 지인/ 해당기업(기관) 웹사이트/ 민간취업알선기관(인력사무소, 직업소개소 등)※ 2021년 수록 사회조사에서는 `지난 1주 구직활동 여부`로 조사하였으니 참고하여 주세요~
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15066308&srcSe=7661IVAWM27C61E190

Alerts

일하였음(2021년)_퍼센트 is highly overall correlated with 하지 않았음(2021년)_퍼센트High correlation
하지 않았음(2021년)_퍼센트 is highly overall correlated with 일하였음(2021년)_퍼센트High correlation
특성별(2) has unique valuesUnique
일하였음(2021년)_퍼센트 has 3 (6.0%) zerosZeros
하지 않았음(2021년)_퍼센트 has 5 (10.0%) zerosZeros

Reproduction

Analysis started2024-01-28 15:13:12.169985
Analysis finished2024-01-28 15:13:12.694215
Duration0.52 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
8 
월평균소득별
8 
연령별
6 
가구원수별
5 
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

2024-01-29T00:13:12.749743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:13:12.836087image/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
2024-01-29T00:13:13.005700image/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%
2024-01-29T00:13:13.272745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 33
 
13.4%
22
 
8.9%
만 15
 
6.1%
~ 11
 
4.5%
세 9
 
3.7%
원 8
 
3.3%
구 8
 
3.3%
미 8
 
3.3%
3 6
 
2.4%
인 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 (%)
만 15
 
10.6%
세 9
 
6.3%
원 8
 
5.6%
구 8
 
5.6%
미 8
 
5.6%
인 5
 
3.5%
이 5
 
3.5%
상 4
 
2.8%
기 4
 
2.8%
졸 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 (%)
만 15
 
10.6%
세 9
 
6.3%
원 8
 
5.6%
구 8
 
5.6%
미 8
 
5.6%
인 5
 
3.5%
이 5
 
3.5%
상 4
 
2.8%
기 4
 
2.8%
졸 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 (%)
만 15
 
10.6%
세 9
 
6.3%
원 8
 
5.6%
구 8
 
5.6%
미 8
 
5.6%
인 5
 
3.5%
이 5
 
3.5%
상 4
 
2.8%
기 4
 
2.8%
졸 4
 
2.8%
Other values (54) 72
50.7%

일하였음(2021년)_퍼센트
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct41
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.488
Minimum0
Maximum100
Zeros3
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-01-29T00:13:13.391963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.485
Q151.9
median57.45
Q366.375
95-th percentile100
Maximum100
Range100
Interquartile range (IQR)14.475

Descriptive statistics

Standard deviation24.211396
Coefficient of variation (CV)0.42861131
Kurtosis1.0659724
Mean56.488
Median Absolute Deviation (MAD)7.8
Skewness-0.62270042
Sum2824.4
Variance586.19169
MonotonicityNot monotonic
2024-01-29T00:13:13.500524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
100.0 5
 
10.0%
0.0 3
 
6.0%
55.5 3
 
6.0%
55.9 2
 
4.0%
61.7 1
 
2.0%
61.1 1
 
2.0%
62.4 1
 
2.0%
66.4 1
 
2.0%
64.2 1
 
2.0%
69.1 1
 
2.0%
Other values (31) 31
62.0%
ValueCountFrequency (%)
0.0 3
6.0%
3.3 1
 
2.0%
11.8 1
 
2.0%
19.5 1
 
2.0%
29.2 1
 
2.0%
39.9 1
 
2.0%
47.1 1
 
2.0%
47.8 1
 
2.0%
50.0 1
 
2.0%
51.0 1
 
2.0%
ValueCountFrequency (%)
100.0 5
10.0%
74.3 1
 
2.0%
73.9 1
 
2.0%
73.3 1
 
2.0%
72.3 1
 
2.0%
71.8 1
 
2.0%
69.1 1
 
2.0%
66.8 1
 
2.0%
66.4 1
 
2.0%
66.3 1
 
2.0%

하지 않았음(2021년)_퍼센트
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct41
Distinct (%)82.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.512
Minimum0
Maximum100
Zeros5
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-01-29T00:13:13.605438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q133.625
median42.55
Q348.1
95-th percentile98.515
Maximum100
Range100
Interquartile range (IQR)14.475

Descriptive statistics

Standard deviation24.211396
Coefficient of variation (CV)0.55643032
Kurtosis1.0659724
Mean43.512
Median Absolute Deviation (MAD)7.8
Skewness0.62270042
Sum2175.6
Variance586.19169
MonotonicityNot monotonic
2024-01-29T00:13:13.709732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0.0 5
 
10.0%
100.0 3
 
6.0%
44.5 3
 
6.0%
44.1 2
 
4.0%
38.3 1
 
2.0%
38.9 1
 
2.0%
37.6 1
 
2.0%
33.6 1
 
2.0%
35.8 1
 
2.0%
30.9 1
 
2.0%
Other values (31) 31
62.0%
ValueCountFrequency (%)
0.0 5
10.0%
25.7 1
 
2.0%
26.1 1
 
2.0%
26.7 1
 
2.0%
27.7 1
 
2.0%
28.2 1
 
2.0%
30.9 1
 
2.0%
33.2 1
 
2.0%
33.6 1
 
2.0%
33.7 1
 
2.0%
ValueCountFrequency (%)
100.0 3
6.0%
96.7 1
 
2.0%
88.2 1
 
2.0%
80.5 1
 
2.0%
70.8 1
 
2.0%
60.1 1
 
2.0%
52.9 1
 
2.0%
52.2 1
 
2.0%
50.0 1
 
2.0%
49.0 1
 
2.0%

Interactions

2024-01-29T00:13:12.464950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:13:12.323994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:13:12.526202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:13:12.403093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T00:13:13.781846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
특성별(1)특성별(2)일하였음(2021년)_퍼센트하지 않았음(2021년)_퍼센트
특성별(1)1.0001.0000.8210.834
특성별(2)1.0001.0001.0001.000
일하였음(2021년)_퍼센트0.8211.0001.0001.000
하지 않았음(2021년)_퍼센트0.8341.0001.0001.000
2024-01-29T00:13:13.852611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일하였음(2021년)_퍼센트하지 않았음(2021년)_퍼센트특성별(1)
일하였음(2021년)_퍼센트1.000-1.0000.393
하지 않았음(2021년)_퍼센트-1.0001.0000.408
특성별(1)0.3930.4081.000

Missing values

2024-01-29T00:13:12.603556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:13:12.667083image/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)일하였음(2021년)_퍼센트하지 않았음(2021년)_퍼센트
0군구별중구56.843.2
1군구별동구53.746.3
2군구별미추홀구55.544.5
3군구별연수구55.544.5
4군구별남동구51.848.2
5군구별부평구54.545.5
6군구별계양구66.333.7
7군구별서구61.438.6
8군구별강화군52.247.8
9군구별옹진군73.926.1
특성별(1)특성별(2)일하였음(2021년)_퍼센트하지 않았음(2021년)_퍼센트
40주거형태별연립/다세대주택58.141.9
41주거형태별기타65.634.4
42주거점유형태별자가55.944.1
43주거점유형태별전세61.838.2
44주거점유형태별월세 및 기타56.343.7
45가구원수별1인55.144.9
46가구원수별2인51.049.0
47가구원수별3인62.837.2
48가구원수별4인58.441.6
49가구원수별5인 이상50.050.0