Overview

Dataset statistics

Number of variables7
Number of observations30
Missing cells60
Missing cells (%)28.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory64.4 B

Variable types

Numeric1
Categorical1
Unsupported2
DateTime3

Dataset

Description샘플 데이터
Author경기도일자리재단
URLhttps://www.bigdata-region.kr/#/dataset/675bd300-27fb-46c6-b854-813d36c51db3

Alerts

일자리지원사업FAQ번호 is highly overall correlated with 일자리지원사업번호High correlation
일자리지원사업번호 is highly overall correlated with 일자리지원사업FAQ번호High correlation
일자리지원사업FAQ제목 has 30 (100.0%) missing valuesMissing
일자리지원사업FAQ내용 has 30 (100.0%) missing valuesMissing
일자리지원사업FAQ번호 has unique valuesUnique
일자리지원사업FAQ제목 is an unsupported type, check if it needs cleaning or further analysisUnsupported
일자리지원사업FAQ내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 14:16:49.702082
Analysis finished2023-12-10 14:16:50.659189
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자리지원사업FAQ번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.5
Minimum98
Maximum127
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:16:50.787979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum98
5-th percentile99.45
Q1105.25
median112.5
Q3119.75
95-th percentile125.55
Maximum127
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.078252519
Kurtosis-1.2
Mean112.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum3375
Variance77.5
MonotonicityStrictly increasing
2023-12-10T23:16:51.008039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
98 1
 
3.3%
114 1
 
3.3%
127 1
 
3.3%
126 1
 
3.3%
125 1
 
3.3%
124 1
 
3.3%
123 1
 
3.3%
122 1
 
3.3%
121 1
 
3.3%
120 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
98 1
3.3%
99 1
3.3%
100 1
3.3%
101 1
3.3%
102 1
3.3%
103 1
3.3%
104 1
3.3%
105 1
3.3%
106 1
3.3%
107 1
3.3%
ValueCountFrequency (%)
127 1
3.3%
126 1
3.3%
125 1
3.3%
124 1
3.3%
123 1
3.3%
122 1
3.3%
121 1
3.3%
120 1
3.3%
119 1
3.3%
118 1
3.3%

일자리지원사업번호
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
87
13 
97
7 
93
5 
117
3 
<NA>
2 

Length

Max length4
Median length2
Mean length2.2333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row87
2nd row87
3rd row87
4th row87
5th row87

Common Values

ValueCountFrequency (%)
87 13
43.3%
97 7
23.3%
93 5
 
16.7%
117 3
 
10.0%
<NA> 2
 
6.7%

Length

2023-12-10T23:16:51.308429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:16:51.519464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
87 13
43.3%
97 7
23.3%
93 5
 
16.7%
117 3
 
10.0%
na 2
 
6.7%

일자리지원사업FAQ제목
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

일자리지원사업FAQ내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

등록일시
Date

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2019-04-07 23:54:00
Maximum2019-05-30 20:32:00
2023-12-10T23:16:51.712792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:51.928347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

수정일시
Date

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2019-04-07 23:54:00
Maximum2019-06-19 10:18:00
2023-12-10T23:16:52.090736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:52.272675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

데이터기준일자
Date

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2019-04-07 00:00:00
Maximum2019-05-30 00:00:00
2023-12-10T23:16:52.441118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:16:52.613828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

Interactions

2023-12-10T23:16:49.985358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:16:52.744526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자리지원사업FAQ번호일자리지원사업번호등록일시수정일시데이터기준일자
일자리지원사업FAQ번호1.0000.9860.9780.9800.929
일자리지원사업번호0.9861.0001.0001.0000.935
등록일시0.9781.0001.0001.0001.000
수정일시0.9801.0001.0001.0001.000
데이터기준일자0.9290.9351.0001.0001.000
2023-12-10T23:16:52.906056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자리지원사업FAQ번호일자리지원사업번호
일자리지원사업FAQ번호1.0000.815
일자리지원사업번호0.8151.000

Missing values

2023-12-10T23:16:50.252219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:16:50.556030image/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

일자리지원사업FAQ번호일자리지원사업번호일자리지원사업FAQ제목일자리지원사업FAQ내용등록일시수정일시데이터기준일자
09887<NA><NA>2019-04-07 23:542019-04-07 23:542019-04-07
19987<NA><NA>2019-04-07 23:542019-04-07 23:542019-04-07
210087<NA><NA>2019-04-07 23:552019-04-07 23:552019-04-07
310187<NA><NA>2019-04-07 23:552019-04-07 23:552019-04-07
410287<NA><NA>2019-04-07 23:552019-04-07 23:552019-04-07
510387<NA><NA>2019-04-07 23:552019-04-07 23:552019-04-07
610487<NA><NA>2019-04-07 23:562019-04-07 23:562019-04-07
710587<NA><NA>2019-04-07 23:562019-04-07 23:562019-04-07
810687<NA><NA>2019-04-07 23:562019-04-26 10:352019-04-07
910787<NA><NA>2019-04-09 17:282019-04-16 22:082019-04-09
일자리지원사업FAQ번호일자리지원사업번호일자리지원사업FAQ제목일자리지원사업FAQ내용등록일시수정일시데이터기준일자
2011893<NA><NA>2019-04-18 21:012019-04-18 21:012019-04-18
2111993<NA><NA>2019-04-18 21:022019-04-18 21:022019-04-18
2212093<NA><NA>2019-04-18 21:032019-04-18 21:032019-04-18
2312193<NA><NA>2019-04-18 21:052019-04-18 21:052019-04-18
2412297<NA><NA>2019-04-19 09:192019-04-19 09:192019-04-19
2512397<NA><NA>2019-04-19 09:232019-05-03 16:202019-04-19
2612497<NA><NA>2019-04-19 09:282019-04-19 09:282019-04-19
27125117<NA><NA>2019-05-30 20:272019-06-19 10:182019-05-30
28126117<NA><NA>2019-05-30 20:312019-05-30 20:312019-05-30
29127117<NA><NA>2019-05-30 20:322019-05-30 20:322019-05-30