Overview

Dataset statistics

Number of variables16
Number of observations1189
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory160.4 KiB
Average record size in memory138.1 B

Variable types

Numeric7
Categorical9

Dataset

Description국민연금 가입현황입니다. 법정동, 시군구명, 읍면동명, 성별, 나이, 가입자종별, 가입내역구간인원수, 평균납부금액, 평균가입기간, 평균예산연금금액 등의 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=130

Alerts

시구명 has constant value ""Constant
수집년도 has constant value ""Constant
수집월 has constant value ""Constant
성별코드 is highly overall correlated with 성별명High correlation
가입자종별코드 is highly overall correlated with 평균예상연금금액 and 1 other fieldsHigh correlation
가입자종별명 is highly overall correlated with 평균예상연금금액 and 1 other fieldsHigh correlation
성별명 is highly overall correlated with 성별코드High correlation
번호 is highly overall correlated with 법정동코드 and 1 other fieldsHigh correlation
법정동코드 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
나이코드 is highly overall correlated with 평균납부금액 and 2 other fieldsHigh correlation
평균납부금액 is highly overall correlated with 나이코드 and 1 other fieldsHigh correlation
평균가입기간 is highly overall correlated with 나이코드 and 1 other fieldsHigh correlation
평균예상연금금액 is highly overall correlated with 가입자종별코드 and 1 other fieldsHigh correlation
읍면동명 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
나이명 is highly overall correlated with 나이코드High correlation
번호 has unique valuesUnique
평균납부금액 has unique valuesUnique

Reproduction

Analysis started2024-01-09 23:17:49.265423
Analysis finished2024-01-09 23:17:54.544632
Duration5.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1189
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean595
Minimum1
Maximum1189
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-01-10T08:17:54.606383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile60.4
Q1298
median595
Q3892
95-th percentile1129.6
Maximum1189
Range1188
Interquartile range (IQR)594

Descriptive statistics

Standard deviation343.37904
Coefficient of variation (CV)0.57710763
Kurtosis-1.2
Mean595
Median Absolute Deviation (MAD)297
Skewness0
Sum707455
Variance117909.17
MonotonicityStrictly increasing
2024-01-10T08:17:54.725167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
800 1
 
0.1%
798 1
 
0.1%
797 1
 
0.1%
796 1
 
0.1%
795 1
 
0.1%
794 1
 
0.1%
793 1
 
0.1%
792 1
 
0.1%
791 1
 
0.1%
Other values (1179) 1179
99.2%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1189 1
0.1%
1188 1
0.1%
1187 1
0.1%
1186 1
0.1%
1185 1
0.1%
1184 1
0.1%
1183 1
0.1%
1182 1
0.1%
1181 1
0.1%
1180 1
0.1%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4131106 × 109
Minimum4.4131101 × 109
Maximum4.4131111 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-01-10T08:17:54.827999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.4131101 × 109
5-th percentile4.4131102 × 109
Q14.4131103 × 109
median4.4131107 × 109
Q34.4131109 × 109
95-th percentile4.413111 × 109
Maximum4.4131111 × 109
Range1000
Interquartile range (IQR)600

Descriptive statistics

Standard deviation285.45204
Coefficient of variation (CV)6.468273 × 10-8
Kurtosis-1.1928573
Mean4.4131106 × 109
Median Absolute Deviation (MAD)200
Skewness-0.18867367
Sum5.2471885 × 1012
Variance81482.869
MonotonicityIncreasing
2024-01-10T08:17:54.917873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
4413110800 176
14.8%
4413110900 170
14.3%
4413110700 168
14.1%
4413110300 165
13.9%
4413110500 132
11.1%
4413110200 103
8.7%
4413111000 88
7.4%
4413110400 62
 
5.2%
4413111100 55
 
4.6%
4413110100 42
 
3.5%
ValueCountFrequency (%)
4413110100 42
 
3.5%
4413110200 103
8.7%
4413110300 165
13.9%
4413110400 62
 
5.2%
4413110500 132
11.1%
4413110600 28
 
2.4%
4413110700 168
14.1%
4413110800 176
14.8%
4413110900 170
14.3%
4413111000 88
7.4%
ValueCountFrequency (%)
4413111100 55
 
4.6%
4413111000 88
7.4%
4413110900 170
14.3%
4413110800 176
14.8%
4413110700 168
14.1%
4413110600 28
 
2.4%
4413110500 132
11.1%
4413110400 62
 
5.2%
4413110300 165
13.9%
4413110200 103
8.7%

시구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
천안시 동남구
1189 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row천안시 동남구
2nd row천안시 동남구
3rd row천안시 동남구
4th row천안시 동남구
5th row천안시 동남구

Common Values

ValueCountFrequency (%)
천안시 동남구 1189
100.0%

Length

2024-01-10T08:17:55.011751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:17:55.086402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
천안시 1189
50.0%
동남구 1189
50.0%

읍면동명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
구성동
176 
청수동
170 
원성동
168 
문화동
165 
영성동
132 
Other values (6)
378 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구성동 176
14.8%
청수동 170
14.3%
원성동 168
14.1%
문화동 165
13.9%
영성동 132
11.1%
성황동 103
8.7%
삼룡동 88
7.4%
사직동 62
 
5.2%
청당동 55
 
4.6%
대흥동 42
 
3.5%

Length

2024-01-10T08:17:55.173302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
구성동 176
14.8%
청수동 170
14.3%
원성동 168
14.1%
문화동 165
13.9%
영성동 132
11.1%
성황동 103
8.7%
삼룡동 88
7.4%
사직동 62
 
5.2%
청당동 55
 
4.6%
대흥동 42
 
3.5%

성별코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
M
624 
F
565 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowM
3rd rowF
4th rowM
5th rowM

Common Values

ValueCountFrequency (%)
M 624
52.5%
F 565
47.5%

Length

2024-01-10T08:17:55.277418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:17:55.367532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 624
52.5%
f 565
47.5%

성별명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
남자
624 
여자
565 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남자
2nd row남자
3rd row여자
4th row남자
5th row남자

Common Values

ValueCountFrequency (%)
남자 624
52.5%
여자 565
47.5%

Length

2024-01-10T08:17:55.466897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:17:55.546723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남자 624
52.5%
여자 565
47.5%

나이코드
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.030278
Minimum18
Maximum59
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-01-10T08:17:55.637389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile21
Q129
median40
Q351
95-th percentile58
Maximum59
Range41
Interquartile range (IQR)22

Descriptive statistics

Standard deviation11.984379
Coefficient of variation (CV)0.29938287
Kurtosis-1.2876369
Mean40.030278
Median Absolute Deviation (MAD)11
Skewness-0.066027892
Sum47596
Variance143.62535
MonotonicityNot monotonic
2024-01-10T08:17:55.753458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
56 39
 
3.3%
55 37
 
3.1%
58 36
 
3.0%
54 36
 
3.0%
52 36
 
3.0%
29 35
 
2.9%
57 35
 
2.9%
31 35
 
2.9%
53 35
 
2.9%
49 33
 
2.8%
Other values (32) 832
70.0%
ValueCountFrequency (%)
18 4
 
0.3%
19 17
1.4%
20 21
1.8%
21 21
1.8%
22 26
2.2%
23 25
2.1%
24 27
2.3%
25 32
2.7%
26 33
2.8%
27 33
2.8%
ValueCountFrequency (%)
59 29
2.4%
58 36
3.0%
57 35
2.9%
56 39
3.3%
55 37
3.1%
54 36
3.0%
53 35
2.9%
52 36
3.0%
51 32
2.7%
50 32
2.7%

나이명
Categorical

HIGH CORRELATION 

Distinct42
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
56세
 
39
55세
 
37
58세
 
36
54세
 
36
52세
 
36
Other values (37)
1005 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row25세
2nd row25세
3rd row26세
4th row26세
5th row27세

Common Values

ValueCountFrequency (%)
56세 39
 
3.3%
55세 37
 
3.1%
58세 36
 
3.0%
54세 36
 
3.0%
52세 36
 
3.0%
29세 35
 
2.9%
57세 35
 
2.9%
31세 35
 
2.9%
53세 35
 
2.9%
26세 33
 
2.8%
Other values (32) 832
70.0%

Length

2024-01-10T08:17:55.874541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
56세 39
 
3.3%
55세 37
 
3.1%
58세 36
 
3.0%
54세 36
 
3.0%
52세 36
 
3.0%
29세 35
 
2.9%
57세 35
 
2.9%
31세 35
 
2.9%
53세 35
 
2.9%
49세 33
 
2.8%
Other values (32) 832
70.0%

가입자종별코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
0
626 
1
536 
5
 
27

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 626
52.6%
1 536
45.1%
5 27
 
2.3%

Length

2024-01-10T08:17:55.994868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:17:56.095826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 626
52.6%
1 536
45.1%
5 27
 
2.3%

가입자종별명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
사업장
626 
지역
536 
임의가입
 
27

Length

Max length4
Median length3
Mean length2.5719092
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사업장
2nd row지역
3rd row사업장
4th row지역
5th row지역

Common Values

ValueCountFrequency (%)
사업장 626
52.6%
지역 536
45.1%
임의가입 27
 
2.3%

Length

2024-01-10T08:17:56.217578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:17:56.315172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사업장 626
52.6%
지역 536
45.1%
임의가입 27
 
2.3%

가입내역구간인원수
Real number (ℝ)

Distinct85
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.079899
Minimum3
Maximum189
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-01-10T08:17:56.406187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q15
median11
Q327
95-th percentile54.6
Maximum189
Range186
Interquartile range (IQR)22

Descriptive statistics

Standard deviation20.222945
Coefficient of variation (CV)1.0599084
Kurtosis9.9826258
Mean19.079899
Median Absolute Deviation (MAD)7
Skewness2.4077191
Sum22686
Variance408.96752
MonotonicityNot monotonic
2024-01-10T08:17:56.523956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 161
 
13.5%
4 100
 
8.4%
5 83
 
7.0%
6 74
 
6.2%
7 48
 
4.0%
9 40
 
3.4%
11 38
 
3.2%
10 38
 
3.2%
8 36
 
3.0%
12 32
 
2.7%
Other values (75) 539
45.3%
ValueCountFrequency (%)
3 161
13.5%
4 100
8.4%
5 83
7.0%
6 74
6.2%
7 48
 
4.0%
8 36
 
3.0%
9 40
 
3.4%
10 38
 
3.2%
11 38
 
3.2%
12 32
 
2.7%
ValueCountFrequency (%)
189 1
0.1%
162 1
0.1%
141 1
0.1%
133 1
0.1%
127 1
0.1%
124 1
0.1%
114 1
0.1%
109 1
0.1%
100 1
0.1%
99 2
0.2%

평균납부금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1189
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16478139
Minimum46900
Maximum72261208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-01-10T08:17:56.652046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46900
5-th percentile1308052
Q16128208
median12546037
Q323126528
95-th percentile47266719
Maximum72261208
Range72214308
Interquartile range (IQR)16998320

Descriptive statistics

Standard deviation13836750
Coefficient of variation (CV)0.83970346
Kurtosis1.558138
Mean16478139
Median Absolute Deviation (MAD)7581076
Skewness1.3348388
Sum1.9592507 × 1010
Variance1.9145566 × 1014
MonotonicityNot monotonic
2024-01-10T08:17:56.774050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5204057 1
 
0.1%
6294606 1
 
0.1%
23435452 1
 
0.1%
43004011 1
 
0.1%
13285604 1
 
0.1%
12546037 1
 
0.1%
23986913 1
 
0.1%
37779978 1
 
0.1%
11014529 1
 
0.1%
17085453 1
 
0.1%
Other values (1179) 1179
99.2%
ValueCountFrequency (%)
46900 1
0.1%
47260 1
0.1%
142465 1
0.1%
148047 1
0.1%
236400 1
0.1%
245204 1
0.1%
340920 1
0.1%
377520 1
0.1%
437187 1
0.1%
454302 1
0.1%
ValueCountFrequency (%)
72261208 1
0.1%
68114791 1
0.1%
66431017 1
0.1%
65337591 1
0.1%
64669480 1
0.1%
63538224 1
0.1%
62383257 1
0.1%
62301364 1
0.1%
62122321 1
0.1%
60961465 1
0.1%

평균가입기간
Real number (ℝ)

HIGH CORRELATION 

Distinct249
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.224558
Minimum1
Maximum326
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-01-10T08:17:56.893072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q139
median88
Q3141
95-th percentile220
Maximum326
Range325
Interquartile range (IQR)102

Descriptive statistics

Standard deviation66.369686
Coefficient of variation (CV)0.6897375
Kurtosis-0.16438741
Mean96.224558
Median Absolute Deviation (MAD)50
Skewness0.63657138
Sum114411
Variance4404.9352
MonotonicityNot monotonic
2024-01-10T08:17:57.009352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 14
 
1.2%
102 13
 
1.1%
7 13
 
1.1%
8 13
 
1.1%
16 13
 
1.1%
20 11
 
0.9%
32 11
 
0.9%
11 11
 
0.9%
39 11
 
0.9%
30 10
 
0.8%
Other values (239) 1069
89.9%
ValueCountFrequency (%)
1 3
 
0.3%
2 2
 
0.2%
3 5
 
0.4%
4 5
 
0.4%
5 7
0.6%
6 8
0.7%
7 13
1.1%
8 13
1.1%
9 7
0.6%
10 8
0.7%
ValueCountFrequency (%)
326 1
0.1%
313 1
0.1%
306 1
0.1%
291 1
0.1%
285 1
0.1%
279 1
0.1%
278 2
0.2%
277 1
0.1%
275 1
0.1%
271 2
0.2%

평균예상연금금액
Real number (ℝ)

HIGH CORRELATION 

Distinct1159
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean762720.25
Minimum191333
Maximum1397000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.6 KiB
2024-01-10T08:17:57.367276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191333
5-th percentile338200
Q1563105
median714667
Q31002000
95-th percentile1165370.6
Maximum1397000
Range1205667
Interquartile range (IQR)438895

Descriptive statistics

Standard deviation262684.98
Coefficient of variation (CV)0.34440541
Kurtosis-0.98637745
Mean762720.25
Median Absolute Deviation (MAD)218333
Skewness0.085759048
Sum9.0687437 × 108
Variance6.9003399 × 1010
MonotonicityNot monotonic
2024-01-10T08:17:57.503479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1144000 2
 
0.2%
707000 2
 
0.2%
582000 2
 
0.2%
337000 2
 
0.2%
664000 2
 
0.2%
665500 2
 
0.2%
667667 2
 
0.2%
715333 2
 
0.2%
478000 2
 
0.2%
583167 2
 
0.2%
Other values (1149) 1169
98.3%
ValueCountFrequency (%)
191333 1
0.1%
222500 1
0.1%
242000 1
0.1%
243000 1
0.1%
244333 1
0.1%
250750 1
0.1%
252750 1
0.1%
254333 1
0.1%
257500 1
0.1%
257667 1
0.1%
ValueCountFrequency (%)
1397000 1
0.1%
1368000 1
0.1%
1367333 1
0.1%
1359667 1
0.1%
1357679 1
0.1%
1349192 1
0.1%
1332617 1
0.1%
1330429 1
0.1%
1319718 1
0.1%
1313243 1
0.1%

수집년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
2023
1189 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 1189
100.0%

Length

2024-01-10T08:17:57.619370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:17:57.696123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 1189
100.0%

수집월
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.4 KiB
12
1189 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12
2nd row12
3rd row12
4th row12
5th row12

Common Values

ValueCountFrequency (%)
12 1189
100.0%

Length

2024-01-10T08:17:57.783546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:17:57.861100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
12 1189
100.0%

Interactions

2024-01-10T08:17:53.688788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:50.059077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:50.602077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:51.165558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:51.721249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:52.299177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:53.109243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:53.769903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:50.135043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:50.682989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:51.255809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:51.803879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:52.378261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:53.191479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:53.845566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:50.207469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:50.752828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:51.334997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:51.882148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:52.456638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:53.273886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:53.924321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:50.280642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:50.830505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:51.406720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:51.962622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:52.530736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:53.360358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:54.008092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:50.359766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:50.911857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:51.484955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:52.047778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:52.619873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:53.442042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:54.095394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:50.443078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:50.993654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:51.567828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:52.133168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:52.943923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:53.527595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:54.177073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:50.518748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:51.070790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:51.643708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:52.212592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:53.023957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:17:53.604317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T08:17:57.917465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호법정동코드읍면동명성별코드성별명나이코드나이명가입자종별코드가입자종별명가입내역구간인원수평균납부금액평균가입기간평균예상연금금액
번호1.0000.9780.9300.0470.0470.4700.2530.1640.1640.5300.3200.3340.332
법정동코드0.9781.0001.0000.0910.0910.3000.0000.1880.1880.6420.3250.3200.354
읍면동명0.9301.0001.0000.1000.1000.2280.0000.1900.1900.5120.2390.2350.272
성별코드0.0470.0910.1001.0001.0000.0000.0000.0810.0810.1540.4320.3380.416
성별명0.0470.0910.1001.0001.0000.0000.0000.0810.0810.1540.4320.3380.416
나이코드0.4700.3000.2280.0000.0001.0001.0000.1930.1930.2420.6700.7800.657
나이명0.2530.0000.0000.0000.0001.0001.0000.0000.0000.0000.6000.7190.590
가입자종별코드0.1640.1880.1900.0810.0810.1930.0001.0001.0000.3240.5290.3850.718
가입자종별명0.1640.1880.1900.0810.0810.1930.0001.0001.0000.3240.5290.3850.718
가입내역구간인원수0.5300.6420.5120.1540.1540.2420.0000.3240.3241.0000.3740.3660.356
평균납부금액0.3200.3250.2390.4320.4320.6700.6000.5290.5290.3741.0000.9200.719
평균가입기간0.3340.3200.2350.3380.3380.7800.7190.3850.3850.3660.9201.0000.655
평균예상연금금액0.3320.3540.2720.4160.4160.6570.5900.7180.7180.3560.7190.6551.000
2024-01-10T08:17:58.038153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별코드가입자종별코드나이명읍면동명가입자종별명성별명
성별코드1.0000.1330.0000.0950.1330.998
가입자종별코드0.1331.0000.0000.1121.0000.133
나이명0.0000.0001.0000.0000.0000.000
읍면동명0.0950.1120.0001.0000.1120.095
가입자종별명0.1331.0000.0000.1121.0000.133
성별명0.9980.1330.0000.0950.1331.000
2024-01-10T08:17:58.159360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호법정동코드나이코드가입내역구간인원수평균납부금액평균가입기간평균예상연금금액읍면동명성별코드성별명나이명가입자종별코드가입자종별명
번호1.0000.993-0.0470.3740.0220.0370.0940.7470.0360.0360.0890.0980.098
법정동코드0.9931.000-0.1570.359-0.047-0.0520.1461.0000.0870.0870.0000.1150.115
나이코드-0.047-0.1571.000-0.0250.6160.792-0.4730.0990.0000.0000.9860.1160.116
가입내역구간인원수0.3740.359-0.0251.0000.2170.1660.2720.2470.1180.1180.0000.2040.204
평균납부금액0.022-0.0470.6160.2171.0000.9380.3170.1030.3310.3310.2490.3730.373
평균가입기간0.037-0.0520.7920.1660.9381.0000.0680.1010.2580.2580.3350.2510.251
평균예상연금금액0.0940.146-0.4730.2720.3170.0681.0000.1190.3200.3200.2440.5780.578
읍면동명0.7471.0000.0990.2470.1030.1010.1191.0000.0950.0950.0000.1120.112
성별코드0.0360.0870.0000.1180.3310.2580.3200.0951.0000.9980.0000.1330.133
성별명0.0360.0870.0000.1180.3310.2580.3200.0950.9981.0000.0000.1330.133
나이명0.0890.0000.9860.0000.2490.3350.2440.0000.0000.0001.0000.0000.000
가입자종별코드0.0980.1150.1160.2040.3730.2510.5780.1120.1330.1330.0001.0001.000
가입자종별명0.0980.1150.1160.2040.3730.2510.5780.1120.1330.1330.0001.0001.000

Missing values

2024-01-10T08:17:54.306832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T08:17:54.478020image/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

번호법정동코드시구명읍면동명성별코드성별명나이코드나이명가입자종별코드가입자종별명가입내역구간인원수평균납부금액평균가입기간평균예상연금금액수집년도수집월
014413110100천안시 동남구대흥동M남자2525세0사업장35204057291049000202312
124413110100천안시 동남구대흥동M남자2525세1지역3616854032743000202312
234413110100천안시 동남구대흥동F여자2626세0사업장3601722749975000202312
344413110100천안시 동남구대흥동M남자2626세1지역3229455020705000202312
454413110100천안시 동남구대흥동M남자2727세1지역4342833518670750202312
564413110100천안시 동남구대흥동M남자2828세0사업장39155910441081667202312
674413110100천안시 동남구대흥동M남자2929세0사업장3854971044852667202312
784413110100천안시 동남구대흥동M남자3030세0사업장411979920441046000202312
894413110100천안시 동남구대흥동M남자3131세0사업장316632520761174667202312
9104413110100천안시 동남구대흥동M남자3131세1지역3517508338612000202312
번호법정동코드시구명읍면동명성별코드성별명나이코드나이명가입자종별코드가입자종별명가입내역구간인원수평균납부금액평균가입기간평균예상연금금액수집년도수집월
117911804413111100천안시 동남구청당동M남자2929세1지역48295689019636083202312
118011814413111100천안시 동남구청당동F여자2929세1지역53603199234668660202312
118111824413111100천안시 동남구청당동M남자3030세0사업장16215267699621120525202312
118211834413111100천안시 동남구청당동F여자3030세0사업장11417418235781083860202312
118311844413111100천안시 동남구청당동M남자3030세1지역41531252137654146202312
118411854413111100천안시 동남구청당동F여자3030세1지역49618406742661796202312
118511864413111100천안시 동남구청당동M남자3131세0사업장18917661425731118254202312
118611874413111100천안시 동남구청당동F여자3131세0사업장14117773461851035667202312
118711884413111100천안시 동남구청당동M남자3131세1지역34601648236628676202312
118811894413111100천안시 동남구청당동F여자3131세1지역53504283140651340202312