Overview

Dataset statistics

Number of variables3
Number of observations4556
Missing cells211
Missing cells (%)1.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory115.8 KiB
Average record size in memory26.0 B

Variable types

Numeric2
Categorical1

Dataset

Description- 시도별 실업률 정보를 제공합니다. - 실업률은 경제활동인구(취업자+실업자)에서 실업자가 차지하는 비율을 의미합니다. - 2017년부터 충청남도에서 세종특별자치시를 분리하였기 때문에 충청남도의 전년동월대비 비교시 주의가 필요합니다. - 데이터 제공처: KOSIS 국가통계포털
Author제주특별자치도 미래성장과
URLhttps://www.jejudatahub.net/data/view/data/885

Alerts

실업률 has 211 (4.6%) missing valuesMissing

Reproduction

Analysis started2023-12-11 20:16:30.277831
Analysis finished2023-12-11 20:16:30.814557
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준 연월
Real number (ℝ)

Distinct268
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201014.72
Minimum199906
Maximum202109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size40.2 KiB
2023-12-12T05:16:30.877469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum199906
5-th percentile200007
Q1200478.75
median201007.5
Q3201602.25
95-th percentile202008
Maximum202109
Range2203
Interquartile range (IQR)1123.5

Descriptive statistics

Standard deviation645.59745
Coefficient of variation (CV)0.0032116924
Kurtosis-1.1944176
Mean201014.72
Median Absolute Deviation (MAD)595
Skewness-0.0010941504
Sum9.1582308 × 108
Variance416796.07
MonotonicityNot monotonic
2023-12-12T05:16:30.992725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
199906 17
 
0.4%
201411 17
 
0.4%
201309 17
 
0.4%
201310 17
 
0.4%
201311 17
 
0.4%
201312 17
 
0.4%
201401 17
 
0.4%
201402 17
 
0.4%
201403 17
 
0.4%
201404 17
 
0.4%
Other values (258) 4386
96.3%
ValueCountFrequency (%)
199906 17
0.4%
199907 17
0.4%
199908 17
0.4%
199909 17
0.4%
199910 17
0.4%
199911 17
0.4%
199912 17
0.4%
200001 17
0.4%
200002 17
0.4%
200003 17
0.4%
ValueCountFrequency (%)
202109 17
0.4%
202108 17
0.4%
202107 17
0.4%
202106 17
0.4%
202105 17
0.4%
202104 17
0.4%
202103 17
0.4%
202102 17
0.4%
202101 17
0.4%
202012 17
0.4%

시도
Categorical

Distinct17
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size35.7 KiB
서울특별시
 
268
부산광역시
 
268
대구광역시
 
268
인천광역시
 
268
광주광역시
 
268
Other values (12)
3216 

Length

Max length7
Median length5
Mean length4.4117647
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 268
 
5.9%
부산광역시 268
 
5.9%
대구광역시 268
 
5.9%
인천광역시 268
 
5.9%
광주광역시 268
 
5.9%
대전광역시 268
 
5.9%
울산광역시 268
 
5.9%
세종특별자치시 268
 
5.9%
경기도 268
 
5.9%
강원도 268
 
5.9%
Other values (7) 1876
41.2%

Length

2023-12-12T05:16:31.107605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 268
 
5.9%
강원도 268
 
5.9%
경상남도 268
 
5.9%
경상북도 268
 
5.9%
전라남도 268
 
5.9%
전라북도 268
 
5.9%
충청남도 268
 
5.9%
충청북도 268
 
5.9%
경기도 268
 
5.9%
부산광역시 268
 
5.9%
Other values (7) 1876
41.2%

실업률
Real number (ℝ)

MISSING 

Distinct79
Distinct (%)1.8%
Missing211
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean3.3158803
Minimum0.8
Maximum10.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size40.2 KiB
2023-12-12T05:16:31.229742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.8
5-th percentile1.7
Q12.4
median3.2
Q34.1
95-th percentile5.2
Maximum10.5
Range9.7
Interquartile range (IQR)1.7

Descriptive statistics

Standard deviation1.1829226
Coefficient of variation (CV)0.35674465
Kurtosis1.4936695
Mean3.3158803
Median Absolute Deviation (MAD)0.8
Skewness0.80349445
Sum14407.5
Variance1.3993058
MonotonicityNot monotonic
2023-12-12T05:16:31.347328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.7 159
 
3.5%
2.5 156
 
3.4%
2.4 154
 
3.4%
2.3 154
 
3.4%
2.6 147
 
3.2%
4.0 135
 
3.0%
2.2 134
 
2.9%
2.1 134
 
2.9%
3.0 132
 
2.9%
2.7 129
 
2.8%
Other values (69) 2911
63.9%
(Missing) 211
 
4.6%
ValueCountFrequency (%)
0.8 4
 
0.1%
0.9 1
 
< 0.1%
1.0 1
 
< 0.1%
1.1 13
 
0.3%
1.2 15
 
0.3%
1.3 26
 
0.6%
1.4 23
 
0.5%
1.5 46
1.0%
1.6 72
1.6%
1.7 75
1.6%
ValueCountFrequency (%)
10.5 1
 
< 0.1%
10.3 1
 
< 0.1%
9.4 1
 
< 0.1%
9.2 1
 
< 0.1%
8.8 2
< 0.1%
8.7 3
0.1%
8.4 1
 
< 0.1%
8.1 3
0.1%
8.0 1
 
< 0.1%
7.9 1
 
< 0.1%

Interactions

2023-12-12T05:16:30.572167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:16:30.415951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:16:30.646070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:16:30.491996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T05:16:31.665579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준 연월시도실업률
기준 연월1.0000.0000.410
시도0.0001.0000.577
실업률0.4100.5771.000
2023-12-12T05:16:31.729725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준 연월실업률시도
기준 연월1.000-0.0570.000
실업률-0.0571.0000.267
시도0.0000.2671.000

Missing values

2023-12-12T05:16:30.730205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T05:16:30.788685image/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

기준 연월시도실업률
0199906서울특별시7.1
1199907서울특별시7.6
2199908서울특별시6.8
3199909서울특별시5.6
4199910서울특별시5.8
5199911서울특별시5.4
6199912서울특별시5.9
7200001서울특별시6.7
8200002서울특별시6.5
9200003서울특별시5.9
기준 연월시도실업률
4546202012제주도2.3
4547202101제주도5.2
4548202102제주도3.9
4549202103제주도2.9
4550202104제주도3.9
4551202105제주도3.0
4552202106제주도3.2
4553202107제주도3.6
4554202108제주도1.9
4555202109제주도2.3