Overview

Dataset statistics

Number of variables3
Number of observations105
Missing cells18
Missing cells (%)5.7%
Duplicate rows1
Duplicate rows (%)1.0%
Total size in memory2.8 KiB
Average record size in memory27.3 B

Variable types

DateTime1
Numeric2

Dataset

Description한국잡월드 홈페이지에 신규가입한 월별 가입자 현황자료입니다. 각 월을 기준으로 분류된 자료로 누적 자료 및 해당 월 가입자를 데이터로 제공합니다.
URLhttps://www.data.go.kr/data/15051974/fileData.do

Alerts

Dataset has 1 (1.0%) duplicate rowsDuplicates
신규가입수 is highly overall correlated with 신규가입누계High correlation
신규가입누계 is highly overall correlated with 신규가입수High correlation
기준일 has 6 (5.7%) missing valuesMissing
신규가입수 has 6 (5.7%) missing valuesMissing
신규가입누계 has 6 (5.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 10:40:47.576756
Analysis finished2023-12-12 10:40:48.422183
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준일
Date

MISSING 

Distinct99
Distinct (%)100.0%
Missing6
Missing (%)5.7%
Memory size972.0 B
Minimum2012-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-12T19:40:48.501121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:40:48.654638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

신규가입수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct99
Distinct (%)100.0%
Missing6
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean25427.283
Minimum126
Maximum384731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T19:40:48.799818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126
5-th percentile1278.2
Q16479.5
median13673
Q324013
95-th percentile38820.2
Maximum384731
Range384605
Interquartile range (IQR)17533.5

Descriptive statistics

Standard deviation59825.588
Coefficient of variation (CV)2.3528109
Kurtosis28.069803
Mean25427.283
Median Absolute Deviation (MAD)9439
Skewness5.3248953
Sum2517301
Variance3.579101 × 109
MonotonicityNot monotonic
2023-12-12T19:40:48.935216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6611 1
 
1.0%
2705 1
 
1.0%
2205 1
 
1.0%
126 1
 
1.0%
3319 1
 
1.0%
1901 1
 
1.0%
819 1
 
1.0%
1399 1
 
1.0%
833 1
 
1.0%
875 1
 
1.0%
Other values (89) 89
84.8%
(Missing) 6
 
5.7%
ValueCountFrequency (%)
126 1
1.0%
579 1
1.0%
819 1
1.0%
833 1
1.0%
875 1
1.0%
1323 1
1.0%
1399 1
1.0%
1901 1
1.0%
1909 1
1.0%
2075 1
1.0%
ValueCountFrequency (%)
384731 1
1.0%
349632 1
1.0%
334080 1
1.0%
41406 1
1.0%
39479 1
1.0%
38747 1
1.0%
38231 1
1.0%
36620 1
1.0%
34481 1
1.0%
32802 1
1.0%

신규가입누계
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct99
Distinct (%)100.0%
Missing6
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean1943241.9
Minimum349632
Maximum2515557
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T19:40:49.111334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum349632
5-th percentile1132963.3
Q11609634.5
median2092301
Q32337082.5
95-th percentile2445916.5
Maximum2515557
Range2165925
Interquartile range (IQR)727448

Descriptive statistics

Standard deviation471779.52
Coefficient of variation (CV)0.24277961
Kurtosis0.134265
Mean1943241.9
Median Absolute Deviation (MAD)274125
Skewness-0.89280913
Sum1.9238095 × 108
Variance2.2257592 × 1011
MonotonicityStrictly increasing
2023-12-12T19:40:49.261275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2319017 1
 
1.0%
2336793 1
 
1.0%
2334088 1
 
1.0%
2331883 1
 
1.0%
2331757 1
 
1.0%
2328438 1
 
1.0%
2326537 1
 
1.0%
2325718 1
 
1.0%
2324319 1
 
1.0%
2323486 1
 
1.0%
Other values (89) 89
84.8%
(Missing) 6
 
5.7%
ValueCountFrequency (%)
349632 1
1.0%
734363 1
1.0%
1068443 1
1.0%
1086947 1
1.0%
1098091 1
1.0%
1136838 1
1.0%
1165095 1
1.0%
1191084 1
1.0%
1202747 1
1.0%
1231552 1
1.0%
ValueCountFrequency (%)
2515557 1
1.0%
2505344 1
1.0%
2495828 1
1.0%
2478363 1
1.0%
2461878 1
1.0%
2444143 1
1.0%
2430906 1
1.0%
2414920 1
1.0%
2402991 1
1.0%
2394558 1
1.0%

Interactions

2023-12-12T19:40:47.913936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:40:47.681975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:40:48.037357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:40:47.803109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:40:49.356100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일신규가입수신규가입누계
기준일1.0001.0001.000
신규가입수1.0001.0000.901
신규가입누계1.0000.9011.000
2023-12-12T19:40:49.445425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신규가입수신규가입누계
신규가입수1.000-0.664
신규가입누계-0.6641.000

Missing values

2023-12-12T19:40:48.185678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:40:48.270063image/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.
2023-12-12T19:40:48.360443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

기준일신규가입수신규가입누계
02012-12-31349632349632
12013-12-31384731734363
22014-12-313340801068443
32015-01-31185041086947
42015-02-28111441098091
52015-03-31387471136838
62015-04-30282571165095
72015-05-31259891191084
82015-06-30116631202747
92015-07-31288051231552
기준일신규가입수신규가입누계
952022-09-30164852478363
962022-10-31174652495828
972022-11-3095162505344
982022-12-31102132515557
99<NA><NA><NA>
100<NA><NA><NA>
101<NA><NA><NA>
102<NA><NA><NA>
103<NA><NA><NA>
104<NA><NA><NA>

Duplicate rows

Most frequently occurring

기준일신규가입수신규가입누계# duplicates
0<NA><NA><NA>6