Overview

Dataset statistics

Number of variables6
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory55.2 B

Variable types

Numeric5
Categorical1

Dataset

Description신분별 군인 및 군무원 정원(만 명 단위) 정보입니다. 신분별 군인 및 군무원 정원(만 명 단위) 정보입니다. 신분별 군인 및 군무원 정원(만 명 단위) 정보입니다.
Author국방부
URLhttps://www.data.go.kr/data/15060494/fileData.do

Alerts

장교 is highly overall correlated with 부사관 and 2 other fieldsHigh correlation
부사관 is highly overall correlated with 장교 and 2 other fieldsHigh correlation
병 is highly overall correlated with 장교 and 1 other fieldsHigh correlation
군무원 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 장교 and 2 other fieldsHigh correlation
장교 has 12 (20.0%) zerosZeros
부사관 has 12 (20.0%) zerosZeros
병 has 12 (20.0%) zerosZeros

Reproduction

Analysis started2023-12-12 19:31:56.787695
Analysis finished2023-12-12 19:31:59.463876
Duration2.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

Distinct12
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.5
Minimum2010
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T04:31:59.520169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2010
5-th percentile2010
Q12012.75
median2015.5
Q32018.25
95-th percentile2021
Maximum2021
Range11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.4811843
Coefficient of variation (CV)0.0017272063
Kurtosis-1.2175447
Mean2015.5
Median Absolute Deviation (MAD)3
Skewness0
Sum120930
Variance12.118644
MonotonicityIncreasing
2023-12-13T04:31:59.629184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2010 5
8.3%
2011 5
8.3%
2012 5
8.3%
2013 5
8.3%
2014 5
8.3%
2015 5
8.3%
2016 5
8.3%
2017 5
8.3%
2018 5
8.3%
2019 5
8.3%
Other values (2) 10
16.7%
ValueCountFrequency (%)
2010 5
8.3%
2011 5
8.3%
2012 5
8.3%
2013 5
8.3%
2014 5
8.3%
2015 5
8.3%
2016 5
8.3%
2017 5
8.3%
2018 5
8.3%
2019 5
8.3%
ValueCountFrequency (%)
2021 5
8.3%
2020 5
8.3%
2019 5
8.3%
2018 5
8.3%
2017 5
8.3%
2016 5
8.3%
2015 5
8.3%
2014 5
8.3%
2013 5
8.3%
2012 5
8.3%

구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size612.0 B
육군
12 
해군
12 
해병대
12 
공군
12 
기타
12 

Length

Max length3
Median length2
Mean length2.2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row육군
2nd row해군
3rd row해병대
4th row공군
5th row기타

Common Values

ValueCountFrequency (%)
육군 12
20.0%
해군 12
20.0%
해병대 12
20.0%
공군 12
20.0%
기타 12
20.0%

Length

2023-12-13T04:31:59.742449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:31:59.842147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
육군 12
20.0%
해군 12
20.0%
해병대 12
20.0%
공군 12
20.0%
기타 12
20.0%

장교
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4233333
Minimum0
Maximum5.2
Zeros12
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T04:31:59.940422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2
median0.7
Q31.2
95-th percentile5.105
Maximum5.2
Range5.2
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.8886249
Coefficient of variation (CV)1.3269027
Kurtosis0.14788749
Mean1.4233333
Median Absolute Deviation (MAD)0.5
Skewness1.3747256
Sum85.4
Variance3.566904
MonotonicityNot monotonic
2023-12-13T04:32:00.045717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.7 12
20.0%
0.2 12
20.0%
0.0 12
20.0%
1.1 8
13.3%
5.1 6
10.0%
1.2 4
 
6.7%
5.2 3
 
5.0%
4.9 2
 
3.3%
5.0 1
 
1.7%
ValueCountFrequency (%)
0.0 12
20.0%
0.2 12
20.0%
0.7 12
20.0%
1.1 8
13.3%
1.2 4
 
6.7%
4.9 2
 
3.3%
5.0 1
 
1.7%
5.1 6
10.0%
5.2 3
 
5.0%
ValueCountFrequency (%)
5.2 3
 
5.0%
5.1 6
10.0%
5.0 1
 
1.7%
4.9 2
 
3.3%
1.2 4
 
6.7%
1.1 8
13.3%
0.7 12
20.0%
0.2 12
20.0%
0.0 12
20.0%

부사관
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)28.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4216667
Minimum0
Maximum8.6
Zeros12
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T04:32:00.144981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.6
median1.8
Q31.9
95-th percentile8.4
Maximum8.6
Range8.6
Interquartile range (IQR)1.3

Descriptive statistics

Standard deviation2.8302897
Coefficient of variation (CV)1.1687363
Kurtosis0.18373896
Mean2.4216667
Median Absolute Deviation (MAD)1.2
Skewness1.3189421
Sum145.3
Variance8.0105395
MonotonicityNot monotonic
2023-12-13T04:32:00.241868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 12
20.0%
1.9 11
18.3%
0.6 8
13.3%
1.8 6
10.0%
1.7 5
8.3%
8.4 3
 
5.0%
7.0 2
 
3.3%
0.5 2
 
3.3%
2.0 2
 
3.3%
0.7 2
 
3.3%
Other values (7) 7
11.7%
ValueCountFrequency (%)
0.0 12
20.0%
0.5 2
 
3.3%
0.6 8
13.3%
0.7 2
 
3.3%
1.7 5
8.3%
1.8 6
10.0%
1.9 11
18.3%
2.0 2
 
3.3%
7.0 2
 
3.3%
7.2 1
 
1.7%
ValueCountFrequency (%)
8.6 1
 
1.7%
8.4 3
5.0%
8.2 1
 
1.7%
8.0 1
 
1.7%
7.7 1
 
1.7%
7.6 1
 
1.7%
7.4 1
 
1.7%
7.2 1
 
1.7%
7.0 2
3.3%
2.0 2
3.3%

병
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3983333
Minimum0
Maximum39.8
Zeros12
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T04:32:00.353879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.675
median2
Q33.5
95-th percentile37.63
Maximum39.8
Range39.8
Interquartile range (IQR)1.825

Descriptive statistics

Standard deviation13.50108
Coefficient of variation (CV)1.6075903
Kurtosis0.66037994
Mean8.3983333
Median Absolute Deviation (MAD)1.5
Skewness1.5801922
Sum503.9
Variance182.27915
MonotonicityNot monotonic
2023-12-13T04:32:00.473145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 12
20.0%
3.5 9
15.0%
1.7 9
15.0%
2.0 6
10.0%
2.1 5
8.3%
3.4 2
 
3.3%
1.6 2
 
3.3%
39.8 1
 
1.7%
31.0 1
 
1.7%
3.3 1
 
1.7%
Other values (12) 12
20.0%
ValueCountFrequency (%)
0.0 12
20.0%
1.5 1
 
1.7%
1.6 2
 
3.3%
1.7 9
15.0%
1.9 1
 
1.7%
2.0 6
10.0%
2.1 5
8.3%
3.3 1
 
1.7%
3.4 2
 
3.3%
3.5 9
15.0%
ValueCountFrequency (%)
39.8 1
1.7%
39.3 1
1.7%
38.2 1
1.7%
37.6 1
1.7%
36.9 1
1.7%
36.6 1
1.7%
35.9 1
1.7%
35.0 1
1.7%
32.9 1
1.7%
31.0 1
1.7%

군무원
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.57
Minimum0.1
Maximum2.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size672.0 B
2023-12-13T04:32:00.595493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.1
Q10.4
median0.4
Q30.625
95-th percentile1.215
Maximum2.2
Range2.1
Interquartile range (IQR)0.225

Descriptive statistics

Standard deviation0.45110035
Coefficient of variation (CV)0.79140412
Kurtosis2.3335133
Mean0.57
Median Absolute Deviation (MAD)0.1
Skewness1.5109045
Sum34.2
Variance0.20349153
MonotonicityNot monotonic
2023-12-13T04:32:00.707216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0.4 21
35.0%
0.1 12
20.0%
0.5 11
18.3%
1.2 9
15.0%
0.7 2
 
3.3%
0.6 1
 
1.7%
1.5 1
 
1.7%
1.8 1
 
1.7%
2.2 1
 
1.7%
0.8 1
 
1.7%
ValueCountFrequency (%)
0.1 12
20.0%
0.4 21
35.0%
0.5 11
18.3%
0.6 1
 
1.7%
0.7 2
 
3.3%
0.8 1
 
1.7%
1.2 9
15.0%
1.5 1
 
1.7%
1.8 1
 
1.7%
2.2 1
 
1.7%
ValueCountFrequency (%)
2.2 1
 
1.7%
1.8 1
 
1.7%
1.5 1
 
1.7%
1.2 9
15.0%
0.8 1
 
1.7%
0.7 2
 
3.3%
0.6 1
 
1.7%
0.5 11
18.3%
0.4 21
35.0%
0.1 12
20.0%

Interactions

2023-12-13T04:31:58.829637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:56.985818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:57.402826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:57.868721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:58.281461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:58.915802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:57.067727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:57.506775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:57.954867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:58.379580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:58.998250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:57.145877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:57.588997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:58.035749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:58.481692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:59.072962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:57.223907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:57.664924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:58.107840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:58.611654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:59.175067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:57.320262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:57.791095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:58.201069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:31:58.723164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:32:00.787876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도구분장교부사관병군무원
연도1.0000.0000.0000.0000.0000.000
구분0.0001.0001.0000.9640.8170.834
장교0.0001.0001.0000.8710.6070.930
부사관0.0000.9640.8711.0000.9260.774
병0.0000.8170.6070.9261.0000.910
군무원0.0000.8340.9300.7740.9101.000
2023-12-13T04:32:00.884400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도장교부사관병군무원구분
연도1.000-0.0040.111-0.1040.1220.000
장교-0.0041.0000.9760.8860.3960.991
부사관0.1110.9761.0000.8550.4000.731
병-0.1040.8860.8551.0000.2320.442
군무원0.1220.3960.4000.2321.0000.690
구분0.0000.9910.7310.4420.6901.000

Missing values

2023-12-13T04:31:59.296004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:31:59.417777image/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

연도구분장교부사관병군무원
02010육군5.27.039.81.2
12010해군0.71.81.70.4
22010해병대0.20.52.00.1
32010공군1.11.93.50.4
42010기타0.00.00.00.5
52011육군5.27.039.31.2
62011해군0.71.81.70.4
72011해병대0.20.52.00.1
82011공군1.11.93.50.4
92011기타0.00.00.00.5
연도구분장교부사관병군무원
502020육군4.98.428.61.8
512020해군0.71.81.60.4
522020해병대0.20.72.00.1
532020공군1.22.03.40.5
542020기타0.00.00.00.7
552021육군4.98.626.12.2
562021해군0.71.91.50.4
572021해병대0.20.71.90.1
582021공군1.22.03.30.5
592021기타0.00.00.00.8