Overview

Dataset statistics

Number of variables11
Number of observations48
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory100.8 B

Variable types

Text1
Numeric10

Dataset

Description공무원의 재직기간(5년미만, 33년이상, 40년 이상 등)에 따른 연령별 퇴직자 수 데이터로 18세 미만부터 시작됩니다.
URLhttps://www.data.go.kr/data/15053025/fileData.do

Alerts

계 is highly overall correlated with 25-30년미만 and 2 other fieldsHigh correlation
5년미만 is highly overall correlated with 5-10년미만 and 1 other fieldsHigh correlation
5-10년미만 is highly overall correlated with 5년미만 and 1 other fieldsHigh correlation
10-15년미만 is highly overall correlated with 5-10년미만 and 2 other fieldsHigh correlation
15-20년미만 is highly overall correlated with 10-15년미만 and 2 other fieldsHigh correlation
20-25년미만 is highly overall correlated with 10-15년미만 and 3 other fieldsHigh correlation
25-30년미만 is highly overall correlated with 계 and 4 other fieldsHigh correlation
30-33년이하 is highly overall correlated with 계 and 4 other fieldsHigh correlation
33년초과-40년미만 is highly overall correlated with 계 and 4 other fieldsHigh correlation
40년이상 is highly overall correlated with 30-33년이하 and 1 other fieldsHigh correlation
15-20년미만 has 1 (2.1%) missing valuesMissing
구분 has unique valuesUnique
5-10년미만 has 6 (12.5%) zerosZeros
10-15년미만 has 13 (27.1%) zerosZeros
15-20년미만 has 18 (37.5%) zerosZeros
20-25년미만 has 21 (43.8%) zerosZeros
25-30년미만 has 25 (52.1%) zerosZeros
30-33년이하 has 30 (62.5%) zerosZeros
33년초과-40년미만 has 33 (68.8%) zerosZeros
40년이상 has 40 (83.3%) zerosZeros

Reproduction

Analysis started2023-12-12 04:38:54.146797
Analysis finished2023-12-12 04:39:05.044710
Duration10.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2023-12-12T13:39:05.264189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.0833333
Min length3

Characters and Unicode

Total characters148
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)100.0%

Sample

1st row18세미만
2nd row19세
3rd row20세
4th row21세
5th row22세
ValueCountFrequency (%)
18세미만 1
 
2.1%
19세 1
 
2.1%
53세 1
 
2.1%
44세 1
 
2.1%
45세 1
 
2.1%
46세 1
 
2.1%
47세 1
 
2.1%
48세 1
 
2.1%
49세 1
 
2.1%
50세 1
 
2.1%
Other values (38) 38
79.2%
2023-12-12T13:39:05.992663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
세 48
32.4%
2 15
 
10.1%
3 15
 
10.1%
4 15
 
10.1%
5 15
 
10.1%
6 10
 
6.8%
1 7
 
4.7%
8 5
 
3.4%
9 5
 
3.4%
0 5
 
3.4%
Other values (5) 8
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96
64.9%
Other Letter 52
35.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
15.6%
3 15
15.6%
4 15
15.6%
5 15
15.6%
6 10
10.4%
1 7
7.3%
8 5
 
5.2%
9 5
 
5.2%
0 5
 
5.2%
7 4
 
4.2%
Other Letter
ValueCountFrequency (%)
세 48
92.3%
미 1
 
1.9%
만 1
 
1.9%
이 1
 
1.9%
상 1
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 96
64.9%
Hangul 52
35.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
15.6%
3 15
15.6%
4 15
15.6%
5 15
15.6%
6 10
10.4%
1 7
7.3%
8 5
 
5.2%
9 5
 
5.2%
0 5
 
5.2%
7 4
 
4.2%
Hangul
ValueCountFrequency (%)
세 48
92.3%
미 1
 
1.9%
만 1
 
1.9%
이 1
 
1.9%
상 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
64.9%
Hangul 52
35.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
세 48
92.3%
미 1
 
1.9%
만 1
 
1.9%
이 1
 
1.9%
상 1
 
1.9%
ASCII
ValueCountFrequency (%)
2 15
15.6%
3 15
15.6%
4 15
15.6%
5 15
15.6%
6 10
10.4%
1 7
7.3%
8 5
 
5.2%
9 5
 
5.2%
0 5
 
5.2%
7 4
 
4.2%

계
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1145.6875
Minimum1
Maximum16567
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T13:39:06.141750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.15
Q1532.75
median645.5
Q3979.25
95-th percentile2814.55
Maximum16567
Range16566
Interquartile range (IQR)446.5

Descriptive statistics

Standard deviation2376.8061
Coefficient of variation (CV)2.0745675
Kurtosis39.67925
Mean1145.6875
Median Absolute Deviation (MAD)296
Skewness6.0716653
Sum54993
Variance5649207.2
MonotonicityNot monotonic
2023-12-12T13:39:06.279877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
594 2
 
4.2%
532 2
 
4.2%
677 2
 
4.2%
596 1
 
2.1%
538 1
 
2.1%
590 1
 
2.1%
608 1
 
2.1%
710 1
 
2.1%
709 1
 
2.1%
715 1
 
2.1%
Other values (35) 35
72.9%
ValueCountFrequency (%)
1 1
2.1%
7 1
2.1%
8 1
2.1%
17 1
2.1%
39 1
2.1%
70 1
2.1%
84 1
2.1%
180 1
2.1%
344 1
2.1%
510 1
2.1%
ValueCountFrequency (%)
16567 1
2.1%
3266 1
2.1%
2971 1
2.1%
2524 1
2.1%
2104 1
2.1%
1499 1
2.1%
1401 1
2.1%
1349 1
2.1%
1140 1
2.1%
1111 1
2.1%

5년미만
Real number (ℝ)

HIGH CORRELATION 

Distinct47
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean277.52083
Minimum1
Maximum1055
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T13:39:06.436293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.15
Q1100
median224.5
Q3332
95-th percentile861.55
Maximum1055
Range1054
Interquartile range (IQR)232

Descriptive statistics

Standard deviation252.57634
Coefficient of variation (CV)0.91011669
Kurtosis1.8265975
Mean277.52083
Median Absolute Deviation (MAD)111.5
Skewness1.4939549
Sum13321
Variance63794.808
MonotonicityNot monotonic
2023-12-12T13:39:06.586888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
39 2
 
4.2%
1 1
 
2.1%
130 1
 
2.1%
240 1
 
2.1%
230 1
 
2.1%
227 1
 
2.1%
244 1
 
2.1%
210 1
 
2.1%
231 1
 
2.1%
222 1
 
2.1%
Other values (37) 37
77.1%
ValueCountFrequency (%)
1 1
2.1%
7 1
2.1%
8 1
2.1%
17 1
2.1%
39 2
4.2%
57 1
2.1%
68 1
2.1%
70 1
2.1%
77 1
2.1%
84 1
2.1%
ValueCountFrequency (%)
1055 1
2.1%
913 1
2.1%
892 1
2.1%
805 1
2.1%
689 1
2.1%
634 1
2.1%
573 1
2.1%
501 1
2.1%
468 1
2.1%
374 1
2.1%

5-10년미만
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.729167
Minimum0
Maximum209
Zeros6
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T13:39:06.724608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119.5
median51
Q392.5
95-th percentile171.2
Maximum209
Range209
Interquartile range (IQR)73

Descriptive statistics

Standard deviation55.242498
Coefficient of variation (CV)0.88065092
Kurtosis-0.03334088
Mean62.729167
Median Absolute Deviation (MAD)40.5
Skewness0.86019551
Sum3011
Variance3051.7336
MonotonicityNot monotonic
2023-12-12T13:39:06.896924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 6
 
12.5%
31 2
 
4.2%
85 2
 
4.2%
44 2
 
4.2%
30 1
 
2.1%
73 1
 
2.1%
55 1
 
2.1%
56 1
 
2.1%
62 1
 
2.1%
50 1
 
2.1%
Other values (30) 30
62.5%
ValueCountFrequency (%)
0 6
12.5%
4 1
 
2.1%
6 1
 
2.1%
7 1
 
2.1%
8 1
 
2.1%
9 1
 
2.1%
18 1
 
2.1%
20 1
 
2.1%
22 1
 
2.1%
23 1
 
2.1%
ValueCountFrequency (%)
209 1
2.1%
179 1
2.1%
174 1
2.1%
166 1
2.1%
144 1
2.1%
141 1
2.1%
138 1
2.1%
133 1
2.1%
114 1
2.1%
109 1
2.1%

10-15년미만
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.375
Minimum0
Maximum127
Zeros13
Zeros (%)27.1%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T13:39:07.085024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median21.5
Q350.25
95-th percentile101.75
Maximum127
Range127
Interquartile range (IQR)50.25

Descriptive statistics

Standard deviation35.680989
Coefficient of variation (CV)1.0379924
Kurtosis-0.11148155
Mean34.375
Median Absolute Deviation (MAD)21.5
Skewness0.93322236
Sum1650
Variance1273.133
MonotonicityNot monotonic
2023-12-12T13:39:07.255716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 13
27.1%
86 2
 
4.2%
37 2
 
4.2%
17 2
 
4.2%
6 2
 
4.2%
15 1
 
2.1%
9 1
 
2.1%
18 1
 
2.1%
20 1
 
2.1%
43 1
 
2.1%
Other values (22) 22
45.8%
ValueCountFrequency (%)
0 13
27.1%
4 1
 
2.1%
6 2
 
4.2%
9 1
 
2.1%
11 1
 
2.1%
15 1
 
2.1%
17 2
 
4.2%
18 1
 
2.1%
20 1
 
2.1%
21 1
 
2.1%
ValueCountFrequency (%)
127 1
2.1%
114 1
2.1%
107 1
2.1%
92 1
2.1%
86 2
4.2%
85 1
2.1%
84 1
2.1%
77 1
2.1%
71 1
2.1%
65 1
2.1%

15-20년미만
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct27
Distinct (%)57.4%
Missing1
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean30.425532
Minimum0
Maximum192
Zeros18
Zeros (%)37.5%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T13:39:07.439242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median12
Q345.5
95-th percentile104.9
Maximum192
Range192
Interquartile range (IQR)45.5

Descriptive statistics

Standard deviation41.788674
Coefficient of variation (CV)1.3734739
Kurtosis3.7597221
Mean30.425532
Median Absolute Deviation (MAD)12
Skewness1.8254375
Sum1430
Variance1746.2932
MonotonicityNot monotonic
2023-12-12T13:39:07.610583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 18
37.5%
8 2
 
4.2%
16 2
 
4.2%
31 2
 
4.2%
47 1
 
2.1%
35 1
 
2.1%
6 1
 
2.1%
192 1
 
2.1%
7 1
 
2.1%
12 1
 
2.1%
Other values (17) 17
35.4%
ValueCountFrequency (%)
0 18
37.5%
3 1
 
2.1%
6 1
 
2.1%
7 1
 
2.1%
8 2
 
4.2%
12 1
 
2.1%
16 2
 
4.2%
19 1
 
2.1%
22 1
 
2.1%
28 1
 
2.1%
ValueCountFrequency (%)
192 1
2.1%
116 1
2.1%
107 1
2.1%
100 1
2.1%
98 1
2.1%
88 1
2.1%
87 1
2.1%
73 1
2.1%
60 1
2.1%
58 1
2.1%

20-25년미만
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.75
Minimum0
Maximum342
Zeros21
Zeros (%)43.8%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T13:39:07.798294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11.5
Q364.25
95-th percentile137.5
Maximum342
Range342
Interquartile range (IQR)64.25

Descriptive statistics

Standard deviation63.923991
Coefficient of variation (CV)1.5311136
Kurtosis9.3540389
Mean41.75
Median Absolute Deviation (MAD)11.5
Skewness2.5923403
Sum2004
Variance4086.2766
MonotonicityNot monotonic
2023-12-12T13:39:07.959451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 21
43.8%
28 2
 
4.2%
48 2
 
4.2%
2 2
 
4.2%
89 1
 
2.1%
40 1
 
2.1%
64 1
 
2.1%
11 1
 
2.1%
342 1
 
2.1%
29 1
 
2.1%
Other values (15) 15
31.2%
ValueCountFrequency (%)
0 21
43.8%
2 2
 
4.2%
11 1
 
2.1%
12 1
 
2.1%
28 2
 
4.2%
29 1
 
2.1%
30 1
 
2.1%
34 1
 
2.1%
39 1
 
2.1%
40 1
 
2.1%
ValueCountFrequency (%)
342 1
2.1%
155 1
2.1%
141 1
2.1%
131 1
2.1%
130 1
2.1%
119 1
2.1%
112 1
2.1%
109 1
2.1%
89 1
2.1%
78 1
2.1%

25-30년미만
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.5625
Minimum0
Maximum1351
Zeros25
Zeros (%)52.1%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T13:39:08.106439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q392
95-th percentile170.65
Maximum1351
Range1351
Interquartile range (IQR)92

Descriptive statistics

Standard deviation198.31824
Coefficient of variation (CV)2.8925176
Kurtosis39.089347
Mean68.5625
Median Absolute Deviation (MAD)0
Skewness5.9918639
Sum3291
Variance39330.124
MonotonicityNot monotonic
2023-12-12T13:39:08.253230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 25
52.1%
64 2
 
4.2%
1 2
 
4.2%
115 1
 
2.1%
136 1
 
2.1%
3 1
 
2.1%
137 1
 
2.1%
41 1
 
2.1%
1351 1
 
2.1%
98 1
 
2.1%
Other values (12) 12
25.0%
ValueCountFrequency (%)
0 25
52.1%
1 2
 
4.2%
3 1
 
2.1%
4 1
 
2.1%
9 1
 
2.1%
36 1
 
2.1%
41 1
 
2.1%
64 2
 
4.2%
83 1
 
2.1%
90 1
 
2.1%
ValueCountFrequency (%)
1351 1
2.1%
180 1
2.1%
178 1
2.1%
157 1
2.1%
146 1
2.1%
137 1
2.1%
136 1
2.1%
134 1
2.1%
133 1
2.1%
130 1
2.1%

30-33년이하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean148.5625
Minimum0
Maximum2593
Zeros30
Zeros (%)62.5%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T13:39:08.397024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q377.25
95-th percentile622.7
Maximum2593
Range2593
Interquartile range (IQR)77.25

Descriptive statistics

Standard deviation408.91334
Coefficient of variation (CV)2.7524668
Kurtosis27.878238
Mean148.5625
Median Absolute Deviation (MAD)0
Skewness4.8692771
Sum7131
Variance167210.12
MonotonicityNot monotonic
2023-12-12T13:39:08.574909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 30
62.5%
598 2
 
4.2%
18 1
 
2.1%
458 1
 
2.1%
130 1
 
2.1%
7 1
 
2.1%
71 1
 
2.1%
190 1
 
2.1%
72 1
 
2.1%
2593 1
 
2.1%
Other values (8) 8
 
16.7%
ValueCountFrequency (%)
0 30
62.5%
1 1
 
2.1%
7 1
 
2.1%
18 1
 
2.1%
52 1
 
2.1%
71 1
 
2.1%
72 1
 
2.1%
93 1
 
2.1%
130 1
 
2.1%
152 1
 
2.1%
ValueCountFrequency (%)
2593 1
2.1%
647 1
2.1%
636 1
2.1%
598 2
4.2%
498 1
2.1%
458 1
2.1%
317 1
2.1%
190 1
2.1%
152 1
2.1%
130 1
2.1%

33년초과-40년미만
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean405.1875
Minimum0
Maximum10062
Zeros33
Zeros (%)68.8%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T13:39:08.749018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q329.5
95-th percentile1643.8
Maximum10062
Range10062
Interquartile range (IQR)29.5

Descriptive statistics

Standard deviation1503.1164
Coefficient of variation (CV)3.709681
Kurtosis38.057588
Mean405.1875
Median Absolute Deviation (MAD)0
Skewness5.9350066
Sum19449
Variance2259358.9
MonotonicityNot monotonic
2023-12-12T13:39:08.913836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 33
68.8%
2175 1
 
2.1%
348 1
 
2.1%
18 1
 
2.1%
601 1
 
2.1%
1655 1
 
2.1%
686 1
 
2.1%
10062 1
 
2.1%
1623 1
 
2.1%
4 1
 
2.1%
Other values (6) 6
 
12.5%
ValueCountFrequency (%)
0 33
68.8%
4 1
 
2.1%
17 1
 
2.1%
18 1
 
2.1%
64 1
 
2.1%
167 1
 
2.1%
311 1
 
2.1%
348 1
 
2.1%
572 1
 
2.1%
601 1
 
2.1%
ValueCountFrequency (%)
10062 1
2.1%
2175 1
2.1%
1655 1
2.1%
1623 1
2.1%
1146 1
2.1%
686 1
2.1%
601 1
2.1%
572 1
2.1%
348 1
2.1%
311 1
2.1%

40년이상
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.208333
Minimum0
Maximum1727
Zeros40
Zeros (%)83.3%
Negative0
Negative (%)0.0%
Memory size564.0 B
2023-12-12T13:39:09.039210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile426.8
Maximum1727
Range1727
Interquartile range (IQR)0

Descriptive statistics

Standard deviation299.13919
Coefficient of variation (CV)3.8744417
Kurtosis22.310125
Mean77.208333
Median Absolute Deviation (MAD)0
Skewness4.6226044
Sum3706
Variance89484.254
MonotonicityNot monotonic
2023-12-12T13:39:09.193667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 40
83.3%
13 1
 
2.1%
83 1
 
2.1%
1727 1
 
2.1%
185 1
 
2.1%
1074 1
 
2.1%
557 1
 
2.1%
1 1
 
2.1%
66 1
 
2.1%
ValueCountFrequency (%)
0 40
83.3%
1 1
 
2.1%
13 1
 
2.1%
66 1
 
2.1%
83 1
 
2.1%
185 1
 
2.1%
557 1
 
2.1%
1074 1
 
2.1%
1727 1
 
2.1%
ValueCountFrequency (%)
1727 1
 
2.1%
1074 1
 
2.1%
557 1
 
2.1%
185 1
 
2.1%
83 1
 
2.1%
66 1
 
2.1%
13 1
 
2.1%
1 1
 
2.1%
0 40
83.3%

Interactions

2023-12-12T13:39:03.675355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:54.479373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:55.550714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:56.630028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:57.527596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:58.505609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:59.848771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:00.994358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:02.035181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:02.771675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:03.774574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:54.580148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:55.667982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:56.715540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:57.612034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:58.633183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:59.961404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:01.106752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:02.111195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:02.845031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:03.865493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:54.661404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:55.788838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:56.798034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:57.725247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:58.744654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:00.069719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:01.225952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:02.179858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:02.927892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:03.964710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:54.737247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:55.901507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:56.876482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:57.808238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:58.848612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:00.183147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:01.348933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:02.257537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:03.044388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:04.069961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:54.823730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:56.019294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:56.967551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:57.906965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:58.939476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:00.301788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:01.452209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:02.333530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:03.127291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:04.183517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:54.953321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:56.159021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:57.062937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:58.004960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:59.049868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:00.407187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:01.546503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:02.411283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:03.217079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:04.299842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:55.067723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:56.259509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:57.152805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:58.124132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:59.142413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:00.529376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:01.660842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:02.493591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:03.309900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:04.390700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:55.183732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:56.349097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:57.259764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:58.250921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:59.533193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:00.652274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:01.771407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:02.566578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:03.415807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:04.485693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:55.272631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:56.429384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:57.359853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:58.329762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:59.643244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:00.763593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:01.861568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:02.630361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:03.503347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:04.599605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:55.365393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:56.536511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:57.444665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:58.412605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:38:59.738737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:00.870514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:01.942759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:02.699996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:03.583347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:39:09.292029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분계5년미만5-10년미만10-15년미만15-20년미만20-25년미만25-30년미만30-33년이하33년초과-40년미만40년이상
구분1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
계1.0001.0000.0000.2860.6110.7540.9410.9380.7381.0000.759
5년미만1.0000.0001.0000.8810.2130.0000.0000.0000.0000.0000.000
5-10년미만1.0000.2860.8811.0000.8880.4510.5020.3350.0000.1810.000
10-15년미만1.0000.6110.2130.8881.0000.7840.7170.6060.6210.3980.000
15-20년미만1.0000.7540.0000.4510.7841.0000.7810.9420.8660.8180.580
20-25년미만1.0000.9410.0000.5020.7170.7811.0000.9770.7880.7270.592
25-30년미만1.0000.9380.0000.3350.6060.9420.9771.0000.7120.6660.737
30-33년이하1.0000.7380.0000.0000.6210.8660.7880.7121.0000.9540.599
33년초과-40년미만1.0001.0000.0000.1810.3980.8180.7270.6660.9541.0000.690
40년이상1.0000.7590.0000.0000.0000.5800.5920.7370.5990.6901.000
2023-12-12T13:39:09.482644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
계5년미만5-10년미만10-15년미만15-20년미만20-25년미만25-30년미만30-33년이하33년초과-40년미만40년이상
계1.0000.1080.2190.1110.1970.3680.5770.6860.6990.483
5년미만0.1081.0000.7520.203-0.082-0.240-0.425-0.474-0.519-0.442
5-10년미만0.2190.7521.0000.6400.2830.049-0.180-0.278-0.316-0.220
10-15년미만0.1110.2030.6401.0000.8270.5500.2540.092-0.002-0.033
15-20년미만0.197-0.0820.2830.8271.0000.8410.5440.3260.2210.163
20-25년미만0.368-0.2400.0490.5500.8411.0000.8410.6050.4360.242
25-30년미만0.577-0.425-0.1800.2540.5440.8411.0000.9000.7870.461
30-33년이하0.686-0.474-0.2780.0920.3260.6050.9001.0000.9150.559
33년초과-40년미만0.699-0.519-0.316-0.0020.2210.4360.7870.9151.0000.747
40년이상0.483-0.442-0.220-0.0330.1630.2420.4610.5590.7471.000

Missing values

2023-12-12T13:39:04.771727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:39:04.973964image/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

구분계5년미만5-10년미만10-15년미만15-20년미만20-25년미만25-30년미만30-33년이하33년초과-40년미만40년이상
018세미만1100000000
119세7700000000
220세8800000000
321세171700000000
422세393900000000
523세707000000000
624세18017640000000
725세34433770000000
826세51050190000000
927세665634310000000
구분계5년미만5-10년미만10-15년미만15-20년미만20-25년미만25-30년미만30-33년이하33년초과-40년미만40년이상
3856세1499124181716391155985720
3957세21041042220123413063611460
4058세2524883418164490598162313
4159세297184201772998458217583
4260세16567129858619234213512593100621727
4361세1111683198114172686185
4462세3266772315316413719016551074
4563세1401576116286471601557
4664세843986<NA>237181
4765세이상9721324837354013613034866