Overview

Dataset statistics

Number of variables14
Number of observations253
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.8 KiB
Average record size in memory124.5 B

Variable types

DateTime2
Numeric11
Categorical1

Dataset

Description사립학교교직원연금공단 대여 상환 수납 현황과 관련된 데이터로 처리일자,수납일자,정기상환건수,정기상환금액,개인정기상환건수,개인정기상환금액,일시상환건수,일시상환금액,개인일시상환건수,개인일시상환금액,부분상환건수,부분상환금액,정산고지선납건수,정산고지선납금액 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15081267/fileData.do

Alerts

정기상환건수 is highly overall correlated with 정기상환금액 and 2 other fieldsHigh correlation
정기상환금액 is highly overall correlated with 정기상환건수High correlation
개인정기상환건수 is highly overall correlated with 개인정기상환금액High correlation
개인정기상환금액 is highly overall correlated with 개인정기상환건수High correlation
일시상환건수 is highly overall correlated with 정기상환건수 and 3 other fieldsHigh correlation
일시상환금액 is highly overall correlated with 일시상환건수 and 2 other fieldsHigh correlation
개인일시상환건수 is highly overall correlated with 개인일시상환금액High correlation
개인일시상환금액 is highly overall correlated with 개인일시상환건수High correlation
부분상환건수 is highly overall correlated with 정기상환건수 and 3 other fieldsHigh correlation
부분상환금액 is highly overall correlated with 일시상환건수 and 2 other fieldsHigh correlation
정산고지선납건수 is highly imbalanced (64.4%)Imbalance
수납일자 has unique valuesUnique
정기상환건수 has 7 (2.8%) zerosZeros
정기상환금액 has 7 (2.8%) zerosZeros
개인정기상환건수 has 16 (6.3%) zerosZeros
개인정기상환금액 has 17 (6.7%) zerosZeros
일시상환건수 has 5 (2.0%) zerosZeros
일시상환금액 has 5 (2.0%) zerosZeros
개인일시상환건수 has 180 (71.1%) zerosZeros
개인일시상환금액 has 180 (71.1%) zerosZeros
정산고지선납금액 has 218 (86.2%) zerosZeros

Reproduction

Analysis started2023-12-12 14:46:10.325739
Analysis finished2023-12-12 14:46:24.003898
Duration13.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct225
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2022-01-04 00:00:00
Maximum2022-12-30 00:00:00
2023-12-12T23:46:24.112645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:24.265118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수납일자
Date

UNIQUE 

Distinct253
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum2022-01-02 00:00:00
Maximum2022-12-29 00:00:00
2023-12-12T23:46:24.437924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:24.598497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

정기상환건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct149
Distinct (%)58.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean174.18972
Minimum0
Maximum1335
Zeros7
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T23:46:24.760572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q114
median45
Q3144
95-th percentile801.6
Maximum1335
Range1335
Interquartile range (IQR)130

Descriptive statistics

Standard deviation310.46747
Coefficient of variation (CV)1.7823524
Kurtosis6.1434648
Mean174.18972
Median Absolute Deviation (MAD)37
Skewness2.5888235
Sum44070
Variance96390.051
MonotonicityNot monotonic
2023-12-12T23:46:24.934381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 11
 
4.3%
9 7
 
2.8%
0 7
 
2.8%
15 7
 
2.8%
4 5
 
2.0%
48 5
 
2.0%
20 5
 
2.0%
10 5
 
2.0%
12 5
 
2.0%
7 5
 
2.0%
Other values (139) 191
75.5%
ValueCountFrequency (%)
0 7
2.8%
1 2
 
0.8%
2 1
 
0.4%
3 2
 
0.8%
4 5
2.0%
5 2
 
0.8%
6 4
 
1.6%
7 5
2.0%
8 11
4.3%
9 7
2.8%
ValueCountFrequency (%)
1335 1
0.4%
1322 1
0.4%
1317 1
0.4%
1315 1
0.4%
1312 1
0.4%
1310 1
0.4%
1308 1
0.4%
1307 1
0.4%
1303 1
0.4%
1298 1
0.4%

정기상환금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct247
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4762741 × 109
Minimum0
Maximum9.5848786 × 109
Zeros7
Zeros (%)2.8%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T23:46:25.118145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1371236
Q111750070
median1.6224562 × 108
Q31.2749201 × 109
95-th percentile8.709796 × 109
Maximum9.5848786 × 109
Range9.5848786 × 109
Interquartile range (IQR)1.26317 × 109

Descriptive statistics

Standard deviation2.6841644 × 109
Coefficient of variation (CV)1.8182019
Kurtosis2.487632
Mean1.4762741 × 109
Median Absolute Deviation (MAD)1.5811008 × 108
Skewness1.9647165
Sum3.7349735 × 1011
Variance7.2047387 × 1018
MonotonicityNot monotonic
2023-12-12T23:46:25.300456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7
 
2.8%
100780910 1
 
0.4%
41660470 1
 
0.4%
1707218690 1
 
0.4%
673506510 1
 
0.4%
266260320 1
 
0.4%
5257928022 1
 
0.4%
756236300 1
 
0.4%
195105450 1
 
0.4%
8974325710 1
 
0.4%
Other values (237) 237
93.7%
ValueCountFrequency (%)
0 7
2.8%
345550 1
 
0.4%
495140 1
 
0.4%
540780 1
 
0.4%
749410 1
 
0.4%
1326220 1
 
0.4%
1354940 1
 
0.4%
1382100 1
 
0.4%
1451550 1
 
0.4%
1586530 1
 
0.4%
ValueCountFrequency (%)
9584878616 1
0.4%
9488827432 1
0.4%
9305378482 1
0.4%
9233126583 1
0.4%
9160701740 1
0.4%
9098119740 1
0.4%
9010492156 1
0.4%
8974325710 1
0.4%
8937387233 1
0.4%
8912176348 1
0.4%

개인정기상환건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct49
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.699605
Minimum0
Maximum129
Zeros16
Zeros (%)6.3%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T23:46:25.456040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median10
Q316
95-th percentile45.4
Maximum129
Range129
Interquartile range (IQR)11

Descriptive statistics

Standard deviation22.099089
Coefficient of variation (CV)1.4076207
Kurtosis13.811236
Mean15.699605
Median Absolute Deviation (MAD)6
Skewness3.5276792
Sum3972
Variance488.36972
MonotonicityNot monotonic
2023-12-12T23:46:25.618074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
10 19
 
7.5%
8 17
 
6.7%
0 16
 
6.3%
4 15
 
5.9%
1 14
 
5.5%
7 13
 
5.1%
11 12
 
4.7%
9 11
 
4.3%
15 11
 
4.3%
5 10
 
4.0%
Other values (39) 115
45.5%
ValueCountFrequency (%)
0 16
6.3%
1 14
5.5%
2 9
3.6%
3 8
3.2%
4 15
5.9%
5 10
4.0%
6 7
2.8%
7 13
5.1%
8 17
6.7%
9 11
4.3%
ValueCountFrequency (%)
129 1
0.4%
128 2
0.8%
126 1
0.4%
123 1
0.4%
114 1
0.4%
98 2
0.8%
75 1
0.4%
73 1
0.4%
67 1
0.4%
53 1
0.4%

개인정기상환금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct237
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5022912.6
Minimum0
Maximum32475960
Zeros17
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T23:46:25.756845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11253700
median3512500
Q36460790
95-th percentile15852136
Maximum32475960
Range32475960
Interquartile range (IQR)5207090

Descriptive statistics

Standard deviation5611666.8
Coefficient of variation (CV)1.1172137
Kurtosis5.4862069
Mean5022912.6
Median Absolute Deviation (MAD)2554170
Skewness2.1474832
Sum1.2707969 × 109
Variance3.1490804 × 1013
MonotonicityNot monotonic
2023-12-12T23:46:25.916975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17
 
6.7%
1273010 1
 
0.4%
11675510 1
 
0.4%
2345510 1
 
0.4%
2745890 1
 
0.4%
12746900 1
 
0.4%
9036200 1
 
0.4%
1322070 1
 
0.4%
18726110 1
 
0.4%
395360 1
 
0.4%
Other values (227) 227
89.7%
ValueCountFrequency (%)
0 17
6.7%
5280 1
 
0.4%
28600 1
 
0.4%
76490 1
 
0.4%
104380 1
 
0.4%
117770 1
 
0.4%
117970 1
 
0.4%
118060 1
 
0.4%
134180 1
 
0.4%
134340 1
 
0.4%
ValueCountFrequency (%)
32475960 1
0.4%
28867390 1
0.4%
26629470 1
0.4%
25369960 1
0.4%
25339590 1
0.4%
24986010 1
0.4%
24422840 1
0.4%
19650090 1
0.4%
18853630 1
0.4%
18726110 1
0.4%

일시상환건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct114
Distinct (%)45.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean103.27668
Minimum0
Maximum443
Zeros5
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T23:46:26.095781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile49
Q177
median100
Q3121
95-th percentile169.6
Maximum443
Range443
Interquartile range (IQR)44

Descriptive statistics

Standard deviation44.788508
Coefficient of variation (CV)0.43367494
Kurtosis14.720382
Mean103.27668
Median Absolute Deviation (MAD)22
Skewness2.2399834
Sum26129
Variance2006.0104
MonotonicityNot monotonic
2023-12-12T23:46:26.228722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
87 7
 
2.8%
71 7
 
2.8%
109 6
 
2.4%
110 5
 
2.0%
86 5
 
2.0%
0 5
 
2.0%
111 5
 
2.0%
92 5
 
2.0%
72 4
 
1.6%
113 4
 
1.6%
Other values (104) 200
79.1%
ValueCountFrequency (%)
0 5
2.0%
2 1
 
0.4%
7 1
 
0.4%
33 1
 
0.4%
43 1
 
0.4%
47 2
 
0.8%
48 1
 
0.4%
49 2
 
0.8%
51 1
 
0.4%
54 2
 
0.8%
ValueCountFrequency (%)
443 1
0.4%
323 1
0.4%
209 1
0.4%
207 1
0.4%
203 1
0.4%
202 1
0.4%
199 1
0.4%
198 2
0.8%
192 1
0.4%
191 1
0.4%

일시상환금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct249
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2838385 × 109
Minimum0
Maximum1.5510821 × 1010
Zeros5
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T23:46:26.364847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.9883313 × 108
Q18.9466591 × 108
median1.1854054 × 109
Q31.483008 × 109
95-th percentile2.2428028 × 109
Maximum1.5510821 × 1010
Range1.5510821 × 1010
Interquartile range (IQR)5.8834212 × 108

Descriptive statistics

Standard deviation1.0331169 × 109
Coefficient of variation (CV)0.80470942
Kurtosis143.43949
Mean1.2838385 × 109
Median Absolute Deviation (MAD)2.9494968 × 108
Skewness10.516181
Sum3.2481114 × 1011
Variance1.0673306 × 1018
MonotonicityNot monotonic
2023-12-12T23:46:26.808014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5
 
2.0%
1615405440 1
 
0.4%
805551720 1
 
0.4%
1351851670 1
 
0.4%
1011204700 1
 
0.4%
812589120 1
 
0.4%
812477230 1
 
0.4%
1269620720 1
 
0.4%
1450819700 1
 
0.4%
1084152950 1
 
0.4%
Other values (239) 239
94.5%
ValueCountFrequency (%)
0 5
2.0%
9280000 1
 
0.4%
316560570 1
 
0.4%
439158070 1
 
0.4%
459697310 1
 
0.4%
514256950 1
 
0.4%
568723472 1
 
0.4%
571033180 1
 
0.4%
585069770 1
 
0.4%
608008700 1
 
0.4%
ValueCountFrequency (%)
15510821240 1
0.4%
3573666440 1
0.4%
3121438970 1
0.4%
2780178840 1
0.4%
2739678800 1
0.4%
2642082760 1
0.4%
2572405880 1
0.4%
2562023250 1
0.4%
2453058899 1
0.4%
2423352220 1
0.4%

개인일시상환건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.51778656
Minimum0
Maximum14
Zeros180
Zeros (%)71.1%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T23:46:26.921337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum14
Range14
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.3586436
Coefficient of variation (CV)2.6239454
Kurtosis57.766261
Mean0.51778656
Median Absolute Deviation (MAD)0
Skewness6.6272324
Sum131
Variance1.8459125
MonotonicityNot monotonic
2023-12-12T23:46:27.025306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 180
71.1%
1 45
 
17.8%
2 20
 
7.9%
3 4
 
1.6%
4 2
 
0.8%
14 1
 
0.4%
12 1
 
0.4%
ValueCountFrequency (%)
0 180
71.1%
1 45
 
17.8%
2 20
 
7.9%
3 4
 
1.6%
4 2
 
0.8%
12 1
 
0.4%
14 1
 
0.4%
ValueCountFrequency (%)
14 1
 
0.4%
12 1
 
0.4%
4 2
 
0.8%
3 4
 
1.6%
2 20
 
7.9%
1 45
 
17.8%
0 180
71.1%

개인일시상환금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct74
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean825117.26
Minimum0
Maximum40958120
Zeros180
Zeros (%)71.1%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T23:46:27.192582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q352173
95-th percentile4492478
Maximum40958120
Range40958120
Interquartile range (IQR)52173

Descriptive statistics

Standard deviation3568474.9
Coefficient of variation (CV)4.3248094
Kurtosis71.272109
Mean825117.26
Median Absolute Deviation (MAD)0
Skewness7.6144444
Sum2.0875467 × 108
Variance1.2734013 × 1013
MonotonicityNot monotonic
2023-12-12T23:46:27.357972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 180
71.1%
14420 1
 
0.4%
883770 1
 
0.4%
209150 1
 
0.4%
28490 1
 
0.4%
420140 1
 
0.4%
1208560 1
 
0.4%
11280 1
 
0.4%
21529490 1
 
0.4%
6975780 1
 
0.4%
Other values (64) 64
 
25.3%
ValueCountFrequency (%)
0 180
71.1%
90 1
 
0.4%
1340 1
 
0.4%
1750 1
 
0.4%
11280 1
 
0.4%
14420 1
 
0.4%
16410 1
 
0.4%
28490 1
 
0.4%
49250 1
 
0.4%
51490 1
 
0.4%
ValueCountFrequency (%)
40958120 1
0.4%
21529490 1
0.4%
17717110 1
0.4%
16054080 1
0.4%
14217610 1
0.4%
11707340 1
0.4%
7290210 1
0.4%
6975780 1
0.4%
5664620 1
0.4%
5458170 1
0.4%

부분상환건수
Real number (ℝ)

HIGH CORRELATION 

Distinct120
Distinct (%)47.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.79447
Minimum0
Maximum410
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T23:46:27.518897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile61.6
Q186
median105
Q3136
95-th percentile206.8
Maximum410
Range410
Interquartile range (IQR)50

Descriptive statistics

Standard deviation48.853901
Coefficient of variation (CV)0.42557714
Kurtosis5.577379
Mean114.79447
Median Absolute Deviation (MAD)24
Skewness1.3514109
Sum29043
Variance2386.7036
MonotonicityNot monotonic
2023-12-12T23:46:27.666322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98 6
 
2.4%
95 6
 
2.4%
88 5
 
2.0%
102 5
 
2.0%
87 5
 
2.0%
109 5
 
2.0%
116 5
 
2.0%
112 4
 
1.6%
125 4
 
1.6%
97 4
 
1.6%
Other values (110) 204
80.6%
ValueCountFrequency (%)
0 1
 
0.4%
1 3
1.2%
3 2
0.8%
19 1
 
0.4%
48 1
 
0.4%
54 1
 
0.4%
55 1
 
0.4%
58 2
0.8%
61 1
 
0.4%
62 1
 
0.4%
ValueCountFrequency (%)
410 1
0.4%
269 1
0.4%
263 1
0.4%
252 1
0.4%
242 1
0.4%
241 1
0.4%
231 1
0.4%
220 1
0.4%
216 2
0.8%
212 1
0.4%

부분상환금액
Real number (ℝ)

HIGH CORRELATION 

Distinct252
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.5757787 × 108
Minimum0
Maximum2.2062706 × 109
Zeros1
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T23:46:27.845922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.4871 × 108
Q14.1763 × 108
median5.30247 × 108
Q36.5248 × 108
95-th percentile9.68754 × 108
Maximum2.2062706 × 109
Range2.2062706 × 109
Interquartile range (IQR)2.3485 × 108

Descriptive statistics

Standard deviation2.5747597 × 108
Coefficient of variation (CV)0.4617758
Kurtosis9.9056801
Mean5.5757787 × 108
Median Absolute Deviation (MAD)1.16003 × 108
Skewness2.0718073
Sum1.410672 × 1011
Variance6.6293875 × 1016
MonotonicityNot monotonic
2023-12-12T23:46:28.067119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
372700000 2
 
0.8%
945740000 1
 
0.4%
723261960 1
 
0.4%
614990000 1
 
0.4%
322705081 1
 
0.4%
371070000 1
 
0.4%
600898500 1
 
0.4%
541948500 1
 
0.4%
712234000 1
 
0.4%
617800000 1
 
0.4%
Other values (242) 242
95.7%
ValueCountFrequency (%)
0 1
0.4%
10 1
0.4%
2600000 1
0.4%
19680000 1
0.4%
24000000 1
0.4%
27200000 1
0.4%
139040000 1
0.4%
195550000 1
0.4%
208840000 1
0.4%
219665540 1
0.4%
ValueCountFrequency (%)
2206270590 1
0.4%
1904193390 1
0.4%
1489430000 1
0.4%
1418570000 1
0.4%
1383825750 1
0.4%
1183823010 1
0.4%
1152169650 1
0.4%
1090627450 1
0.4%
1082480000 1
0.4%
1035520000 1
0.4%

정산고지선납건수
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
0
218 
1
26 
2
 
8
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 218
86.2%
1 26
 
10.3%
2 8
 
3.2%
3 1
 
0.4%

Length

2023-12-12T23:46:28.216529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:46:28.319952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 218
86.2%
1 26
 
10.3%
2 8
 
3.2%
3 1
 
0.4%

정산고지선납금액
Real number (ℝ)

ZEROS 

Distinct36
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean218816.92
Minimum0
Maximum9959508
Zeros218
Zeros (%)86.2%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T23:46:28.445056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile816684
Maximum9959508
Range9959508
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1139954.4
Coefficient of variation (CV)5.2096263
Kurtosis45.88268
Mean218816.92
Median Absolute Deviation (MAD)0
Skewness6.6099167
Sum55360681
Variance1.299496 × 1012
MonotonicityNot monotonic
2023-12-12T23:46:28.593222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 218
86.2%
3700 1
 
0.4%
420 1
 
0.4%
180060 1
 
0.4%
91642 1
 
0.4%
8596699 1
 
0.4%
60170 1
 
0.4%
1129888 1
 
0.4%
7649840 1
 
0.4%
99989 1
 
0.4%
Other values (26) 26
 
10.3%
ValueCountFrequency (%)
0 218
86.2%
420 1
 
0.4%
810 1
 
0.4%
920 1
 
0.4%
1100 1
 
0.4%
1700 1
 
0.4%
3700 1
 
0.4%
9332 1
 
0.4%
12799 1
 
0.4%
14430 1
 
0.4%
ValueCountFrequency (%)
9959508 1
0.4%
8596699 1
0.4%
7649840 1
0.4%
7452850 1
0.4%
5027470 1
0.4%
2524120 1
0.4%
2506670 1
0.4%
1957130 1
0.4%
1657799 1
0.4%
1579060 1
0.4%

Interactions

2023-12-12T23:46:22.464186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:10.794501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:11.961472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:13.128312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:14.311456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:15.662977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:16.560787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:17.733744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:18.951499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:19.987185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:21.394752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:22.568322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:10.922597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:12.077735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:13.245953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:14.433928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:15.749721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:16.668245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:17.827485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:19.072388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:20.093437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:21.486704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:22.682143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:11.039817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:12.199666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:13.343351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:14.537002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:15.828400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:16.777354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:17.928602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:19.154351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:20.187727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:21.573973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:22.793962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:11.130785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:12.297533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:13.480135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:14.945326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:15.905016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:16.873404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:18.067738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:19.242011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:20.282708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:21.674739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:22.908093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:11.232979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:12.393585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:13.580580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:15.043572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:15.984337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:16.973531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:18.175393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:19.334430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:20.383675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:21.785484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:22.983972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:11.342835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:12.488714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:13.696319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:15.147998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:16.059840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:17.109632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:18.283417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:19.439701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:20.472383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:21.871617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:23.091121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:11.450804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:12.614400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:13.829040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:15.248506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:16.156033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:17.210959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:18.419911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:19.555657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:20.591701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:21.976763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:23.218729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:11.566956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:12.716128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:13.959721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:15.337237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:16.239193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:17.322004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:18.532085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:19.657466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:20.689105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:22.103078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:23.312175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:11.673737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:12.796614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:14.049266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:15.415505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:16.306996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:17.447465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:18.629944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:19.730458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:20.790741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:22.184685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:23.393380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:11.763521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:12.909965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:14.134302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:15.502699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:16.374475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:17.539086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:18.736432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:19.809545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:20.892983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:22.279660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:23.490217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:11.849680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:13.002604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:14.214917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:15.576514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:16.467903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:17.637843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:18.847236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:19.891632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:20.975759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:46:22.374584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:46:28.746760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정기상환건수정기상환금액개인정기상환건수개인정기상환금액일시상환건수일시상환금액개인일시상환건수개인일시상환금액부분상환건수부분상환금액정산고지선납건수정산고지선납금액
정기상환건수1.0000.8050.6840.5340.4090.3180.3680.3410.5200.6140.2420.136
정기상환금액0.8051.0000.4390.5050.1410.0000.2120.2840.6740.0000.2790.261
개인정기상환건수0.6840.4391.0000.8620.0000.0000.0000.0000.0000.0000.0000.000
개인정기상환금액0.5340.5050.8621.0000.0000.0000.0000.0000.0000.0000.0000.000
일시상환건수0.4090.1410.0000.0001.0000.8560.2250.0000.8540.9170.1450.000
일시상환금액0.3180.0000.0000.0000.8561.0000.0000.0000.8320.8690.2810.179
개인일시상환건수0.3680.2120.0000.0000.2250.0001.0000.7960.4130.5150.2790.188
개인일시상환금액0.3410.2840.0000.0000.0000.0000.7961.0000.1900.2390.2530.000
부분상환건수0.5200.6740.0000.0000.8540.8320.4130.1901.0000.8680.4080.000
부분상환금액0.6140.0000.0000.0000.9170.8690.5150.2390.8681.0000.1560.000
정산고지선납건수0.2420.2790.0000.0000.1450.2810.2790.2530.4080.1561.0000.544
정산고지선납금액0.1360.2610.0000.0000.0000.1790.1880.0000.0000.0000.5441.000
2023-12-12T23:46:28.945977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정기상환건수정기상환금액개인정기상환건수개인정기상환금액일시상환건수일시상환금액개인일시상환건수개인일시상환금액부분상환건수부분상환금액정산고지선납금액정산고지선납건수
정기상환건수1.0000.8940.3820.3100.5060.3960.0830.0920.6310.3550.1750.155
정기상환금액0.8941.0000.4550.4220.3830.2820.1120.1220.4910.2340.1520.126
개인정기상환건수0.3820.4551.0000.8680.1350.0900.0810.0890.2370.1760.0880.000
개인정기상환금액0.3100.4220.8681.0000.0710.0630.1160.1170.1550.1070.0910.000
일시상환건수0.5060.3830.1350.0711.0000.8090.001-0.0080.7810.7450.1140.099
일시상환금액0.3960.2820.0900.0630.8091.0000.0560.0570.5960.6050.0980.113
개인일시상환건수0.0830.1120.0810.1160.0010.0561.0000.9840.0580.0340.1200.230
개인일시상환금액0.0920.1220.0890.117-0.0080.0570.9841.0000.0560.0340.1160.175
부분상환건수0.6310.4910.2370.1550.7810.5960.0580.0561.0000.8020.1590.192
부분상환금액0.3550.2340.1760.1070.7450.6050.0340.0340.8021.0000.1450.099
정산고지선납금액0.1750.1520.0880.0910.1140.0980.1200.1160.1590.1451.0000.404
정산고지선납건수0.1550.1260.0000.0000.0990.1130.2300.1750.1920.0990.4041.000

Missing values

2023-12-12T23:46:23.639926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:46:23.893153image/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

처리일자수납일자정기상환건수정기상환금액개인정기상환건수개인정기상환금액일시상환건수일시상환금액개인일시상환건수개인일시상환금액부분상환건수부분상환금액정산고지선납건수정산고지선납금액
02022-01-042022-01-03148100780910317259014816154054400017294574000000
12022-01-052022-01-0420120352400012813320786310010960357000000
22022-01-062022-01-05953215502107762077888097970008846937000000
32022-01-072022-01-02000029280000000000
42022-01-072022-01-06354078053111092001011141791634008054641000000
52022-01-102022-01-078370415904494870931196969965007348618000000
62022-01-122022-01-10749672101231277701161353109260009552005584000
72022-01-132022-01-1112714616035688240681025661160154581706228937000000
82022-01-142022-01-12213262205875900861185405350123286506646205000000
92022-01-172022-01-1383965563023676230781431123560005426628000000
처리일자수납일자정기상환건수정기상환금액개인정기상환건수개인정기상환금액일시상환건수일시상환금액개인일시상환건수개인일시상환금액부분상환건수부분상환금액정산고지선납건수정산고지선납금액
2432022-12-192022-12-1612898649490874103376300741012076520291605014043803000000
2442022-12-212022-12-198230223856603011029610811243499960009538352600000
2452022-12-212022-12-201762551775240381478410071753299130110360209342939000000
2462022-12-222022-12-21281239517908284245065571033180008435965086400
2472022-12-232022-12-2234180118010620592805767785470014317205819555000000
2482022-12-282022-12-23631556761084521796807081841578054111857015661567369000
2492022-12-282022-12-26271913954090321349561087875978799283989014048895000011579060
2502022-12-282022-12-27141127492012021790413076848188780113458011745926950000
2512022-12-292022-12-2841282103469224218069770731081850390009833556000000
2522022-12-302022-12-2946130023560102009110139208424463000184100116000000