Overview

Dataset statistics

Number of variables13
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory122.3 B

Variable types

Numeric12
Categorical1

Dataset

Description사립학교교직원연금공단 신규 사학연금 가입자 현황(연도별 성별 나이별)과 관련된 데이터로 연도별 성별 나이별 신규 사학연금 가입자 수 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15102544/fileData.do

Alerts

연도 is highly overall correlated with 합계 and 6 other fieldsHigh correlation
합계 is highly overall correlated with 연도 and 6 other fieldsHigh correlation
신규가입자수 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
신규가입자수남계 is highly overall correlated with 연도 and 2 other fieldsHigh correlation
신규가입자수여계 is highly overall correlated with 연도 and 5 other fieldsHigh correlation
신규가입자수10대 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
신규가입자수20대 is highly overall correlated with 연도 and 4 other fieldsHigh correlation
신규가입자수30대 is highly overall correlated with 연도 and 5 other fieldsHigh correlation
신규가입자수40대 is highly overall correlated with 신규가입자수50대 and 1 other fieldsHigh correlation
신규가입자수50대 is highly overall correlated with 신규가입자수40대 and 1 other fieldsHigh correlation
신규가입자수60대 is highly overall correlated with 신규가입자수40대 and 1 other fieldsHigh correlation
신규가입자수70대 is highly overall correlated with 신규가입자수80대High correlation
신규가입자수80대 is highly overall correlated with 신규가입자수70대High correlation
연도 has unique valuesUnique
합계 has unique valuesUnique
신규가입자수 has unique valuesUnique
신규가입자수남계 has unique valuesUnique
신규가입자수여계 has unique valuesUnique
신규가입자수20대 has unique valuesUnique
신규가입자수30대 has unique valuesUnique
신규가입자수40대 has unique valuesUnique
신규가입자수50대 has unique valuesUnique
신규가입자수60대 has unique valuesUnique
신규가입자수70대 has 6 (24.0%) zerosZeros

Reproduction

Analysis started2023-12-12 18:23:36.161728
Analysis finished2023-12-12 18:23:53.315590
Duration17.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2010
Minimum1998
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T03:23:53.379387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1998
5-th percentile1999.2
Q12004
median2010
Q32016
95-th percentile2020.8
Maximum2022
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.3598007
Coefficient of variation (CV)0.0036615924
Kurtosis-1.2
Mean2010
Median Absolute Deviation (MAD)6
Skewness0
Sum50250
Variance54.166667
MonotonicityStrictly increasing
2023-12-13T03:23:53.509403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1998 1
 
4.0%
1999 1
 
4.0%
2022 1
 
4.0%
2021 1
 
4.0%
2020 1
 
4.0%
2019 1
 
4.0%
2018 1
 
4.0%
2017 1
 
4.0%
2016 1
 
4.0%
2015 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1998 1
4.0%
1999 1
4.0%
2000 1
4.0%
2001 1
4.0%
2002 1
4.0%
2003 1
4.0%
2004 1
4.0%
2005 1
4.0%
2006 1
4.0%
2007 1
4.0%
ValueCountFrequency (%)
2022 1
4.0%
2021 1
4.0%
2020 1
4.0%
2019 1
4.0%
2018 1
4.0%
2017 1
4.0%
2016 1
4.0%
2015 1
4.0%
2014 1
4.0%
2013 1
4.0%

합계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean267472.24
Minimum206278
Maximum333231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T03:23:53.627536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum206278
5-th percentile208303.8
Q1229926
median267481
Q3313156
95-th percentile329830.4
Maximum333231
Range126953
Interquartile range (IQR)83230

Descriptive statistics

Standard deviation42506.35
Coefficient of variation (CV)0.15891873
Kurtosis-1.2648007
Mean267472.24
Median Absolute Deviation (MAD)42127
Skewness0.16140107
Sum6686806
Variance1.8067898 × 109
MonotonicityNot monotonic
2023-12-13T03:23:53.791698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
206278 1
 
4.0%
207664 1
 
4.0%
333231 1
 
4.0%
330322 1
 
4.0%
327864 1
 
4.0%
323697 1
 
4.0%
320326 1
 
4.0%
317602 1
 
4.0%
313156 1
 
4.0%
282467 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
206278 1
4.0%
207664 1
4.0%
210863 1
4.0%
216361 1
4.0%
220874 1
4.0%
225354 1
4.0%
229926 1
4.0%
236726 1
4.0%
245520 1
4.0%
250652 1
4.0%
ValueCountFrequency (%)
333231 1
4.0%
330322 1
4.0%
327864 1
4.0%
323697 1
4.0%
320326 1
4.0%
317602 1
4.0%
313156 1
4.0%
282467 1
4.0%
280721 1
4.0%
276959 1
4.0%

신규가입자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29193.44
Minimum19891
Maximum53413
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T03:23:53.920926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19891
5-th percentile24417.4
Q125942
median28093
Q330683
95-th percentile33092.6
Maximum53413
Range33522
Interquartile range (IQR)4741

Descriptive statistics

Standard deviation5913.1359
Coefficient of variation (CV)0.20255016
Kurtosis12.06865
Mean29193.44
Median Absolute Deviation (MAD)2360
Skewness2.8825056
Sum729836
Variance34965176
MonotonicityNot monotonic
2023-12-13T03:23:54.378904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
19891 1
 
4.0%
24122 1
 
4.0%
31954 1
 
4.0%
30683 1
 
4.0%
32555 1
 
4.0%
33227 1
 
4.0%
32100 1
 
4.0%
30623 1
 
4.0%
53413 1
 
4.0%
25599 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
19891 1
4.0%
24122 1
4.0%
25599 1
4.0%
25669 1
4.0%
25733 1
4.0%
25941 1
4.0%
25942 1
4.0%
25993 1
4.0%
26292 1
4.0%
27326 1
4.0%
ValueCountFrequency (%)
53413 1
4.0%
33227 1
4.0%
32555 1
4.0%
32100 1
4.0%
31954 1
4.0%
30687 1
4.0%
30683 1
4.0%
30623 1
4.0%
30398 1
4.0%
30316 1
4.0%

신규가입자수남계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10134.24
Minimum7582
Maximum14758
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T03:23:54.515847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7582
5-th percentile8028.8
Q19124
median9464
Q311499
95-th percentile12318
Maximum14758
Range7176
Interquartile range (IQR)2375

Descriptive statistics

Standard deviation1746.8562
Coefficient of variation (CV)0.1723717
Kurtosis0.26763883
Mean10134.24
Median Absolute Deviation (MAD)1088
Skewness0.77754569
Sum253356
Variance3051506.6
MonotonicityNot monotonic
2023-12-13T03:23:54.651610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
11832 1
 
4.0%
12355 1
 
4.0%
9205 1
 
4.0%
9432 1
 
4.0%
9898 1
 
4.0%
9202 1
 
4.0%
8579 1
 
4.0%
8530 1
 
4.0%
14758 1
 
4.0%
7582 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
7582 1
4.0%
7965 1
4.0%
8284 1
4.0%
8376 1
4.0%
8530 1
4.0%
8579 1
4.0%
9124 1
4.0%
9202 1
4.0%
9205 1
4.0%
9331 1
4.0%
ValueCountFrequency (%)
14758 1
4.0%
12355 1
4.0%
12170 1
4.0%
12104 1
4.0%
11832 1
4.0%
11739 1
4.0%
11499 1
4.0%
11485 1
4.0%
11478 1
4.0%
9950 1
4.0%

신규가입자수여계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19059.2
Minimum8059
Maximum38655
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T03:23:54.804189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8059
5-th percentile12191.4
Q116027
median18517
Q321251
95-th percentile23924.2
Maximum38655
Range30596
Interquartile range (IQR)5224

Descriptive statistics

Standard deviation5587.134
Coefficient of variation (CV)0.2931463
Kurtosis5.8301066
Mean19059.2
Median Absolute Deviation (MAD)2690
Skewness1.4928349
Sum476480
Variance31216066
MonotonicityNot monotonic
2023-12-13T03:23:54.958467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
8059 1
 
4.0%
11767 1
 
4.0%
22749 1
 
4.0%
21251 1
 
4.0%
22657 1
 
4.0%
24025 1
 
4.0%
23521 1
 
4.0%
22093 1
 
4.0%
38655 1
 
4.0%
18017 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
8059 1
4.0%
11767 1
4.0%
13889 1
4.0%
14255 1
4.0%
14456 1
4.0%
15827 1
4.0%
16027 1
4.0%
17566 1
4.0%
17704 1
4.0%
18008 1
4.0%
ValueCountFrequency (%)
38655 1
4.0%
24025 1
4.0%
23521 1
4.0%
22749 1
4.0%
22657 1
4.0%
22093 1
4.0%
21251 1
4.0%
20985 1
4.0%
20834 1
4.0%
20006 1
4.0%

신규가입자수10대
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56
Minimum8
Maximum184
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T03:23:55.100909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile9.4
Q119
median35
Q353
95-th percentile178.2
Maximum184
Range176
Interquartile range (IQR)34

Descriptive statistics

Standard deviation57.874865
Coefficient of variation (CV)1.0334797
Kurtosis0.55308012
Mean56
Median Absolute Deviation (MAD)18
Skewness1.4192539
Sum1400
Variance3349.5
MonotonicityNot monotonic
2023-12-13T03:23:55.220551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
24 2
 
8.0%
179 1
 
4.0%
23 1
 
4.0%
14 1
 
4.0%
9 1
 
4.0%
37 1
 
4.0%
16 1
 
4.0%
19 1
 
4.0%
35 1
 
4.0%
11 1
 
4.0%
Other values (14) 14
56.0%
ValueCountFrequency (%)
8 1
4.0%
9 1
4.0%
11 1
4.0%
12 1
4.0%
14 1
4.0%
16 1
4.0%
19 1
4.0%
22 1
4.0%
23 1
4.0%
24 2
8.0%
ValueCountFrequency (%)
184 1
4.0%
179 1
4.0%
175 1
4.0%
147 1
4.0%
132 1
4.0%
81 1
4.0%
53 1
4.0%
47 1
4.0%
44 1
4.0%
42 1
4.0%

신규가입자수20대
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17204.96
Minimum9305
Maximum23633
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T03:23:55.392440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9305
5-th percentile13425.8
Q115078
median18269
Q319446
95-th percentile21156.2
Maximum23633
Range14328
Interquartile range (IQR)4368

Descriptive statistics

Standard deviation3175.9196
Coefficient of variation (CV)0.18459326
Kurtosis0.24448856
Mean17204.96
Median Absolute Deviation (MAD)2251
Skewness-0.35114293
Sum430124
Variance10086466
MonotonicityNot monotonic
2023-12-13T03:23:55.548653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
9305 1
 
4.0%
13348 1
 
4.0%
20525 1
 
4.0%
19240 1
 
4.0%
19620 1
 
4.0%
21314 1
 
4.0%
20431 1
 
4.0%
18320 1
 
4.0%
23633 1
 
4.0%
14314 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
9305 1
4.0%
13348 1
4.0%
13737 1
4.0%
13841 1
4.0%
14091 1
4.0%
14314 1
4.0%
15078 1
4.0%
15126 1
4.0%
15356 1
4.0%
16018 1
4.0%
ValueCountFrequency (%)
23633 1
4.0%
21314 1
4.0%
20525 1
4.0%
20431 1
4.0%
19679 1
4.0%
19620 1
4.0%
19446 1
4.0%
19240 1
4.0%
18813 1
4.0%
18370 1
4.0%

신규가입자수30대
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7304.4
Minimum5860
Maximum17648
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T03:23:55.703992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5860
5-th percentile6207.6
Q16528
median6873
Q37290
95-th percentile7738.8
Maximum17648
Range11788
Interquartile range (IQR)762

Descriptive statistics

Standard deviation2209.623
Coefficient of variation (CV)0.30250575
Kurtosis22.31114
Mean7304.4
Median Absolute Deviation (MAD)417
Skewness4.6050066
Sum182610
Variance4882433.9
MonotonicityNot monotonic
2023-12-13T03:23:55.859898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
5860 1
 
4.0%
6191 1
 
4.0%
7271 1
 
4.0%
6906 1
 
4.0%
7802 1
 
4.0%
7400 1
 
4.0%
7346 1
 
4.0%
7455 1
 
4.0%
17648 1
 
4.0%
6565 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
5860 1
4.0%
6191 1
4.0%
6274 1
4.0%
6280 1
4.0%
6309 1
4.0%
6445 1
4.0%
6528 1
4.0%
6565 1
4.0%
6698 1
4.0%
6740 1
4.0%
ValueCountFrequency (%)
17648 1
4.0%
7802 1
4.0%
7486 1
4.0%
7455 1
4.0%
7400 1
4.0%
7346 1
4.0%
7290 1
4.0%
7271 1
4.0%
7261 1
4.0%
7185 1
4.0%

신규가입자수40대
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3137.4
Minimum1970
Maximum8180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T03:23:56.003966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1970
5-th percentile2250.2
Q12798
median2955
Q33216
95-th percentile3767.8
Maximum8180
Range6210
Interquartile range (IQR)418

Descriptive statistics

Standard deviation1122.519
Coefficient of variation (CV)0.35778637
Kurtosis18.499258
Mean3137.4
Median Absolute Deviation (MAD)187
Skewness4.0102149
Sum78435
Variance1260048.8
MonotonicityNot monotonic
2023-12-13T03:23:56.162019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3003 1
 
4.0%
2819 1
 
4.0%
2798 1
 
4.0%
2917 1
 
4.0%
3220 1
 
4.0%
2980 1
 
4.0%
2877 1
 
4.0%
3257 1
 
4.0%
8180 1
 
4.0%
3109 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1970 1
4.0%
2230 1
4.0%
2331 1
4.0%
2554 1
4.0%
2616 1
4.0%
2783 1
4.0%
2798 1
4.0%
2819 1
4.0%
2850 1
4.0%
2877 1
4.0%
ValueCountFrequency (%)
8180 1
4.0%
3855 1
4.0%
3419 1
4.0%
3400 1
4.0%
3257 1
4.0%
3220 1
4.0%
3216 1
4.0%
3142 1
4.0%
3109 1
4.0%
3025 1
4.0%

신규가입자수50대
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1284.56
Minimum647
Maximum3665
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T03:23:56.312710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum647
5-th percentile695.2
Q11018
median1248
Q31386
95-th percentile1589
Maximum3665
Range3018
Interquartile range (IQR)368

Descriptive statistics

Standard deviation564.33752
Coefficient of variation (CV)0.4393236
Kurtosis13.775013
Mean1284.56
Median Absolute Deviation (MAD)188
Skewness3.2126611
Sum32114
Variance318476.84
MonotonicityNot monotonic
2023-12-13T03:23:56.449560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1191 1
 
4.0%
1411 1
 
4.0%
1150 1
 
4.0%
1311 1
 
4.0%
1591 1
 
4.0%
1306 1
 
4.0%
1248 1
 
4.0%
1384 1
 
4.0%
3665 1
 
4.0%
1369 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
647 1
4.0%
665 1
4.0%
816 1
4.0%
831 1
4.0%
889 1
4.0%
1011 1
4.0%
1018 1
4.0%
1060 1
4.0%
1061 1
4.0%
1150 1
4.0%
ValueCountFrequency (%)
3665 1
4.0%
1591 1
4.0%
1581 1
4.0%
1517 1
4.0%
1493 1
4.0%
1411 1
4.0%
1386 1
4.0%
1384 1
4.0%
1369 1
4.0%
1311 1
4.0%

신규가입자수60대
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean198.56
Minimum110
Maximum345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T03:23:56.609297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110
5-th percentile120.2
Q1157
median188
Q3229
95-th percentile299.6
Maximum345
Range235
Interquartile range (IQR)72

Descriptive statistics

Standard deviation57.115439
Coefficient of variation (CV)0.28764826
Kurtosis0.69039486
Mean198.56
Median Absolute Deviation (MAD)35
Skewness0.82644515
Sum4964
Variance3262.1733
MonotonicityNot monotonic
2023-12-13T03:23:56.784730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
345 1
 
4.0%
218 1
 
4.0%
196 1
 
4.0%
300 1
 
4.0%
298 1
 
4.0%
190 1
 
4.0%
182 1
 
4.0%
188 1
 
4.0%
242 1
 
4.0%
223 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
110 1
4.0%
117 1
4.0%
133 1
4.0%
145 1
4.0%
153 1
4.0%
155 1
4.0%
157 1
4.0%
169 1
4.0%
174 1
4.0%
176 1
4.0%
ValueCountFrequency (%)
345 1
4.0%
300 1
4.0%
298 1
4.0%
242 1
4.0%
233 1
4.0%
232 1
4.0%
229 1
4.0%
223 1
4.0%
219 1
4.0%
218 1
4.0%

신규가입자수70대
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct12
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.08
Minimum0
Maximum30
Zeros6
Zeros (%)24.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-13T03:23:56.955245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median7
Q38
95-th percentile17.2
Maximum30
Range30
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.7386942
Coefficient of variation (CV)0.95179297
Kurtosis4.6191235
Mean7.08
Median Absolute Deviation (MAD)3
Skewness1.7198704
Sum177
Variance45.41
MonotonicityNot monotonic
2023-12-13T03:23:57.108808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 6
24.0%
8 5
20.0%
7 3
12.0%
3 2
 
8.0%
6 2
 
8.0%
30 1
 
4.0%
4 1
 
4.0%
13 1
 
4.0%
18 1
 
4.0%
9 1
 
4.0%
Other values (2) 2
 
8.0%
ValueCountFrequency (%)
0 6
24.0%
3 2
 
8.0%
4 1
 
4.0%
6 2
 
8.0%
7 3
12.0%
8 5
20.0%
9 1
 
4.0%
10 1
 
4.0%
13 1
 
4.0%
14 1
 
4.0%
ValueCountFrequency (%)
30 1
 
4.0%
18 1
 
4.0%
14 1
 
4.0%
13 1
 
4.0%
10 1
 
4.0%
9 1
 
4.0%
8 5
20.0%
7 3
12.0%
6 2
 
8.0%
4 1
 
4.0%

신규가입자수80대
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
0
18 
2
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 18
72.0%
2 3
 
12.0%
1 3
 
12.0%
3 1
 
4.0%

Length

2023-12-13T03:23:57.295115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:23:57.426423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18
72.0%
2 3
 
12.0%
1 3
 
12.0%
3 1
 
4.0%

Interactions

2023-12-13T03:23:51.615178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:36.510783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:37.421480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:38.732488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:40.063207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:41.941671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:43.199416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:44.519069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:45.985493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:47.367409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:49.012283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:50.323171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:51.709832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:36.575618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:37.500063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:38.838746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:40.173742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:42.046992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:43.311476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:44.623845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:46.093982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:47.466620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:49.113604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:50.407917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:51.811868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:36.661556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:37.602795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:38.940249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:40.297779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:42.147756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:43.406390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:44.751686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:46.195126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:47.916002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:49.222347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:50.496396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:51.928254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:36.745982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:37.699503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:39.037328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:40.754281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:42.250570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:43.503452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:44.895619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:46.305366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:48.032139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:49.335362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:50.615804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:52.058536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:36.818187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:37.803300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:39.144768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:40.882135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:42.356869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:43.606570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:45.036259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:46.415780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:48.146546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:49.454247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:50.714349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:52.165330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:36.893193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:37.902090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:39.273224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:40.998199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:42.460484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:43.714172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:45.149212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:46.549447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:48.254870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:49.565360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:50.823241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:52.270191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:36.973123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:37.997921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:39.402530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:41.129607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:42.555407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:43.822574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:45.289304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:46.671906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:48.377841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:49.688193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:50.920500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:52.425517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:37.047192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:38.096198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:39.509223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:41.253175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:42.669545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:43.946787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:45.413577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:46.791026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:48.475020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:49.806300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:51.024760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:52.531346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:37.119354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:38.191432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:39.620881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:41.403681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:42.770617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:44.064834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:45.522650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:46.904880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:48.577380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:49.906901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:51.124267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:52.636198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:37.194082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:38.297120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:39.735004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:41.559864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:42.879367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:44.181061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:45.647086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:47.023207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:48.687200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:50.000084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:51.271146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:52.748069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:37.269721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:38.408043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:39.844906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:41.705159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:42.980384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:44.295229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:45.775143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:47.142712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:48.821522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:50.110344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:51.390646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:52.861017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:37.346122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:38.547280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:39.942484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:41.827279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:43.090194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:44.400016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:45.892610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:47.261998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:48.910462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:50.226066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:23:51.493487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:23:57.549905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도합계신규가입자수신규가입자수남계신규가입자수여계신규가입자수10대신규가입자수20대신규가입자수30대신규가입자수40대신규가입자수50대신규가입자수60대신규가입자수70대신규가입자수80대
연도1.0000.8690.7400.8300.8910.6630.6800.2230.6630.7090.7100.6380.590
합계0.8691.0000.7640.7510.7690.6940.7500.7240.7680.4880.6220.5670.514
신규가입자수0.7400.7641.0000.7580.8770.5010.9590.8070.7230.6540.7430.6820.000
신규가입자수남계0.8300.7510.7581.0000.8160.3030.8010.7910.7220.7150.7090.6800.000
신규가입자수여계0.8910.7690.8770.8161.0000.6840.8700.9800.5910.5750.5950.5360.000
신규가입자수10대0.6630.6940.5010.3030.6841.0000.6500.1010.3410.0970.4870.5650.421
신규가입자수20대0.6800.7500.9590.8010.8700.6501.0000.8360.7820.6770.7020.4420.000
신규가입자수30대0.2230.7240.8070.7910.9800.1010.8361.0000.7220.7080.5230.5720.000
신규가입자수40대0.6630.7680.7230.7220.5910.3410.7820.7221.0000.9510.0000.4610.245
신규가입자수50대0.7090.4880.6540.7150.5750.0970.6770.7080.9511.0000.5220.4040.000
신규가입자수60대0.7100.6220.7430.7090.5950.4870.7020.5230.0000.5221.0000.4100.000
신규가입자수70대0.6380.5670.6820.6800.5360.5650.4420.5720.4610.4040.4101.0000.774
신규가입자수80대0.5900.5140.0000.0000.0000.4210.0000.0000.2450.0000.0000.7741.000
2023-12-13T03:23:57.753106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도합계신규가입자수신규가입자수남계신규가입자수여계신규가입자수10대신규가입자수20대신규가입자수30대신규가입자수40대신규가입자수50대신규가입자수60대신규가입자수70대신규가입자수80대
연도1.0000.9990.667-0.6120.843-0.8240.6120.7430.1800.3620.401-0.3530.339
합계0.9991.0000.675-0.6050.850-0.8210.6220.7490.1750.3530.391-0.3550.314
신규가입자수0.6670.6751.0000.0010.913-0.3100.9180.7830.0810.1260.029-0.3900.000
신규가입자수남계-0.612-0.6050.0011.000-0.3020.722-0.024-0.2230.052-0.033-0.1180.0340.000
신규가입자수여계0.8430.8500.913-0.3021.000-0.5490.9020.7720.0070.1190.105-0.3250.000
신규가입자수10대-0.824-0.821-0.3100.722-0.5491.000-0.253-0.527-0.140-0.340-0.3810.0820.253
신규가입자수20대0.6120.6220.918-0.0240.902-0.2531.0000.602-0.194-0.155-0.158-0.3210.000
신규가입자수30대0.7430.7490.783-0.2230.772-0.5270.6021.0000.4220.4820.255-0.2890.000
신규가입자수40대0.1800.1750.0810.0520.007-0.140-0.1940.4221.0000.8560.613-0.0810.237
신규가입자수50대0.3620.3530.126-0.0330.119-0.340-0.1550.4820.8561.0000.788-0.2100.000
신규가입자수60대0.4010.3910.029-0.1180.105-0.381-0.1580.2550.6130.7881.000-0.1390.000
신규가입자수70대-0.353-0.355-0.3900.034-0.3250.082-0.321-0.289-0.081-0.210-0.1391.0000.614
신규가입자수80대0.3390.3140.0000.0000.0000.2530.0000.0000.2370.0000.0000.6141.000

Missing values

2023-12-13T03:23:53.026998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:23:53.238814image/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

연도합계신규가입자수신규가입자수남계신규가입자수여계신규가입자수10대신규가입자수20대신규가입자수30대신규가입자수40대신규가입자수50대신규가입자수60대신규가입자수70대신규가입자수80대
0199820627819891118328059179930558603003119134580
119992076642412212355117671321334861912819141121830
220002108632599312104138891751512667742783101111770
320012163612573311478142551841507862802955106116960
420022208742594111485144561471535663092929101817660
520032253542732611499158278116157652831421206180302
62004229926277661173916027421601868433400130715330
72005236726306871217018517441778772613855151721940
8200624552028651995018701471837067402554816110131
920072506522739291241826853183066274197064713381
연도합계신규가입자수신규가입자수남계신규가입자수여계신규가입자수10대신규가입자수20대신규가입자수30대신규가입자수40대신규가입자수50대신규가입자수60대신규가입자수70대신규가입자수80대
15201327695926292828418008241373772903419158123380
1620142807212566979651770481384168733216149322981
17201528246725599758218017111431465653109136922380
18201631315653413147583865535236331764881803665242100
19201731760230623853022093191832074553257138418800
20201832032632100857923521162043173462877124818200
21201932369733227920224025372131474002980130619000
22202032786432555989822657241962078023220159129800
2320213303223068394322125191924069062917131130000
24202233323131954920522749142052572712798115019600