Overview

Dataset statistics

Number of variables33
Number of observations500
Missing cells186
Missing cells (%)1.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory144.7 KiB
Average record size in memory296.3 B

Variable types

Numeric25
Text1
Categorical7

Dataset

Description샘플 데이터
AuthorKCB(코리아크레딧뷰로)
URLhttps://bigdata.seoul.go.kr/data/selectSampleData.do?sample_data_seq=322

Alerts

평균_체크카드_할부이용금액(3개월)(CHK_INSTL_M3_AMT) has constant value ""Constant
평균_보유주택건수(HOUS_HLD_CNT) is highly imbalanced (58.6%)Imbalance
경형_승용차_보유자_수(CAR_SZ01_CNT) is highly imbalanced (69.6%)Imbalance
소형_승용차_보유자_수(CAR_SZ02_CNT) is highly imbalanced (88.2%)Imbalance
준중형_승용차_보유자_수(CAR_SZ03_CNT) is highly imbalanced (70.9%)Imbalance
수입_승용차_보유자_수(CAR_FRGN_CNT) is highly imbalanced (72.5%)Imbalance
평균_증빙_연소득(AVG_ICM1) has 186 (37.2%) missing valuesMissing
평균_예금여력금액1(AVG_LN_P1) is highly skewed (γ1 = 22.33846131)Skewed
급여소득자_수(MDL4_CNT) has 22 (4.4%) zerosZeros
자영업자_수(MDL5_CNT) has 184 (36.8%) zerosZeros
기타(무직,주부,학생등)수(MDL9_CNT) has 10 (2.0%) zerosZeros
평균_예금여력금액2(AVG_LN_P2) has 25 (5.0%) zerosZeros
신용대출_보유자_수(CRDT_LN_CNT) has 99 (19.8%) zerosZeros
주택담보대출_보유자_수(HOUS_LN_CNT) has 208 (41.6%) zerosZeros
평균_신용대출_대출잔액(CRDT_LN_BAL) has 95 (19.0%) zerosZeros
평균_주택담보대출_대출잔액(HOUS_LN_BAL) has 219 (43.8%) zerosZeros
평균_신용카드_총이용금액(3개월)(SIN_TOT_M3_AMT) has 25 (5.0%) zerosZeros
평균_신용카드_일시불이용금액(3개월)(SIN_FUL_M3_AMT) has 22 (4.4%) zerosZeros
평균_신용카드_할부이용금액(3개월)(SIN_INSTL_M3_AMT) has 34 (6.8%) zerosZeros
평균_신용카드_해외이용금액(3개월)(SIN_ABRD_M3_AMT) has 179 (35.8%) zerosZeros
평균_체크카드_총이용금액(3개월)(CHK_TOT_M3_AMT) has 15 (3.0%) zerosZeros
평균_체크카드_일시불이용금액(3개월)(CHK_FUL_M3_AMT) has 17 (3.4%) zerosZeros
평균_체크카드_해외이용금액(3개월)(CHK_ABRD_M3_AMT) has 326 (65.2%) zerosZeros
자가거주자_수(ONHS_CNT) has 235 (47.0%) zerosZeros
중형_승용차_보유자_수(CAR_SZ04_CNT) has 384 (76.8%) zerosZeros
대형_승용차_보유자_수(CAR_SZ05_CNT) has 378 (75.6%) zerosZeros
국산_승용차_보유자_수(CAR_DMST_CNT) has 283 (56.6%) zerosZeros

Reproduction

Analysis started2023-12-10 14:50:25.273888
Analysis finished2023-12-10 14:50:25.611548
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

데이터기준년월(BS_YR_MON)
Real number (ℝ)

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201841.22
Minimum201803
Maximum201906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:25.672512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201803
5-th percentile201803
Q1201806
median201812
Q3201903
95-th percentile201906
Maximum201906
Range103
Interquartile range (IQR)97

Descriptive statistics

Standard deviation46.186414
Coefficient of variation (CV)0.00022882548
Kurtosis-1.5803658
Mean201841.22
Median Absolute Deviation (MAD)6
Skewness0.6407852
Sum1.0092061 × 108
Variance2133.1848
MonotonicityNot monotonic
2023-12-10T23:50:25.821144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
201809 96
19.2%
201906 89
17.8%
201806 88
17.6%
201903 84
16.8%
201812 78
15.6%
201803 65
13.0%
ValueCountFrequency (%)
201803 65
13.0%
201806 88
17.6%
201809 96
19.2%
201812 78
15.6%
201903 84
16.8%
201906 89
17.8%
ValueCountFrequency (%)
201906 89
17.8%
201903 84
16.8%
201812 78
15.6%
201809 96
19.2%
201806 88
17.6%
201803 65
13.0%

서울시_블럭ID(BLK_CD)
Text

Distinct324
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-10T23:50:26.143738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.678
Min length2

Characters and Unicode

Total characters2839
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique209 ?
Unique (%)41.8%

Sample

1st row2*2*9*
2nd row2*3*7*
3rd row2*2*4*
4th row6*5*9
5th row3*3*4*
ValueCountFrequency (%)
2*2*3 7
 
1.4%
2*1*9 6
 
1.2%
2*5*0 6
 
1.2%
2*2*1 6
 
1.2%
2*7*9 6
 
1.2%
2*1*3 5
 
1.0%
1*2*6 5
 
1.0%
2*0*3 5
 
1.0%
2*7*8 5
 
1.0%
2*1*8 5
 
1.0%
Other values (253) 444
88.8%
2023-12-10T23:50:26.660883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 1350
47.6%
2 345
 
12.2%
1 238
 
8.4%
3 186
 
6.6%
4 151
 
5.3%
5 104
 
3.7%
9 99
 
3.5%
7 97
 
3.4%
0 96
 
3.4%
6 94
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1489
52.4%
Other Punctuation 1350
47.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 345
23.2%
1 238
16.0%
3 186
12.5%
4 151
10.1%
5 104
 
7.0%
9 99
 
6.6%
7 97
 
6.5%
0 96
 
6.4%
6 94
 
6.3%
8 79
 
5.3%
Other Punctuation
ValueCountFrequency (%)
* 1350
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2839
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 1350
47.6%
2 345
 
12.2%
1 238
 
8.4%
3 186
 
6.6%
4 151
 
5.3%
5 104
 
3.7%
9 99
 
3.5%
7 97
 
3.4%
0 96
 
3.4%
6 94
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2839
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 1350
47.6%
2 345
 
12.2%
1 238
 
8.4%
3 186
 
6.6%
4 151
 
5.3%
5 104
 
3.7%
9 99
 
3.5%
7 97
 
3.4%
0 96
 
3.4%
6 94
 
3.3%

성별(GENDER)
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2
264 
1
236 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 264
52.8%
1 236
47.2%

Length

2023-12-10T23:50:26.805946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:50:26.913928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 264
52.8%
1 236
47.2%

연령대(AGE)
Real number (ℝ)

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.282
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:27.022125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7088934
Coefficient of variation (CV)0.39908767
Kurtosis-1.0595473
Mean4.282
Median Absolute Deviation (MAD)1
Skewness-0.011706726
Sum2141
Variance2.9203166
MonotonicityNot monotonic
2023-12-10T23:50:27.199738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
5 96
19.2%
4 94
18.8%
2 87
17.4%
6 74
14.8%
3 73
14.6%
7 62
12.4%
1 14
 
2.8%
ValueCountFrequency (%)
1 14
 
2.8%
2 87
17.4%
3 73
14.6%
4 94
18.8%
5 96
19.2%
6 74
14.8%
7 62
12.4%
ValueCountFrequency (%)
7 62
12.4%
6 74
14.8%
5 96
19.2%
4 94
18.8%
3 73
14.6%
2 87
17.4%
1 14
 
2.8%

거주자_수(CUST_CNT)
Real number (ℝ)

Distinct52
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.054
Minimum6
Maximum371
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:27.382564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile6
Q18.75
median13
Q320
95-th percentile38.05
Maximum371
Range365
Interquartile range (IQR)11.25

Descriptive statistics

Standard deviation20.886157
Coefficient of variation (CV)1.2247072
Kurtosis172.27536
Mean17.054
Median Absolute Deviation (MAD)5
Skewness11.098958
Sum8527
Variance436.23155
MonotonicityNot monotonic
2023-12-10T23:50:27.600713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 46
 
9.2%
6 41
 
8.2%
9 39
 
7.8%
7 38
 
7.6%
10 37
 
7.4%
15 24
 
4.8%
11 24
 
4.8%
14 23
 
4.6%
13 23
 
4.6%
12 22
 
4.4%
Other values (42) 183
36.6%
ValueCountFrequency (%)
6 41
8.2%
7 38
7.6%
8 46
9.2%
9 39
7.8%
10 37
7.4%
11 24
4.8%
12 22
4.4%
13 23
4.6%
14 23
4.6%
15 24
4.8%
ValueCountFrequency (%)
371 1
0.2%
175 1
0.2%
108 1
0.2%
74 1
0.2%
72 1
0.2%
70 1
0.2%
68 1
0.2%
65 1
0.2%
63 1
0.2%
61 1
0.2%

급여소득자_수(MDL4_CNT)
Real number (ℝ)

ZEROS 

Distinct32
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3
Minimum0
Maximum39
Zeros22
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:27.802850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median6
Q310
95-th percentile19
Maximum39
Range39
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.179188
Coefficient of variation (CV)0.84646411
Kurtosis4.3544809
Mean7.3
Median Absolute Deviation (MAD)3
Skewness1.8031447
Sum3650
Variance38.182365
MonotonicityNot monotonic
2023-12-10T23:50:27.984494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
4 55
11.0%
6 53
10.6%
5 47
 
9.4%
3 46
 
9.2%
2 44
 
8.8%
7 31
 
6.2%
1 28
 
5.6%
8 25
 
5.0%
11 24
 
4.8%
0 22
 
4.4%
Other values (22) 125
25.0%
ValueCountFrequency (%)
0 22
 
4.4%
1 28
5.6%
2 44
8.8%
3 46
9.2%
4 55
11.0%
5 47
9.4%
6 53
10.6%
7 31
6.2%
8 25
5.0%
9 13
 
2.6%
ValueCountFrequency (%)
39 1
 
0.2%
35 1
 
0.2%
34 1
 
0.2%
33 1
 
0.2%
31 3
0.6%
30 1
 
0.2%
27 3
0.6%
24 3
0.6%
23 3
0.6%
22 1
 
0.2%

자영업자_수(MDL5_CNT)
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.694
Minimum0
Maximum18
Zeros184
Zeros (%)36.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:28.164659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile6
Maximum18
Range18
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.186762
Coefficient of variation (CV)1.2908866
Kurtosis9.7799534
Mean1.694
Median Absolute Deviation (MAD)1
Skewness2.4359247
Sum847
Variance4.7819279
MonotonicityNot monotonic
2023-12-10T23:50:28.334299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 184
36.8%
1 114
22.8%
2 83
16.6%
3 49
 
9.8%
4 23
 
4.6%
6 18
 
3.6%
7 10
 
2.0%
5 9
 
1.8%
8 3
 
0.6%
10 3
 
0.6%
Other values (3) 4
 
0.8%
ValueCountFrequency (%)
0 184
36.8%
1 114
22.8%
2 83
16.6%
3 49
 
9.8%
4 23
 
4.6%
5 9
 
1.8%
6 18
 
3.6%
7 10
 
2.0%
8 3
 
0.6%
9 2
 
0.4%
ValueCountFrequency (%)
18 1
 
0.2%
15 1
 
0.2%
10 3
 
0.6%
9 2
 
0.4%
8 3
 
0.6%
7 10
 
2.0%
6 18
 
3.6%
5 9
 
1.8%
4 23
4.6%
3 49
9.8%

기타(무직,주부,학생등)수(MDL9_CNT)
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.524
Minimum0
Maximum184
Zeros10
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:28.491329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median5
Q38
95-th percentile15
Maximum184
Range184
Interquartile range (IQR)5

Descriptive statistics

Standard deviation9.1411457
Coefficient of variation (CV)1.4011566
Kurtosis285.58803
Mean6.524
Median Absolute Deviation (MAD)2
Skewness14.904482
Sum3262
Variance83.560545
MonotonicityNot monotonic
2023-12-10T23:50:28.677262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
4 61
12.2%
5 59
11.8%
3 59
11.8%
2 48
9.6%
6 48
9.6%
7 37
7.4%
1 32
6.4%
8 31
6.2%
9 28
 
5.6%
11 22
 
4.4%
Other values (17) 75
15.0%
ValueCountFrequency (%)
0 10
 
2.0%
1 32
6.4%
2 48
9.6%
3 59
11.8%
4 61
12.2%
5 59
11.8%
6 48
9.6%
7 37
7.4%
8 31
6.2%
9 28
5.6%
ValueCountFrequency (%)
184 1
 
0.2%
29 2
0.4%
26 2
0.4%
25 1
 
0.2%
22 1
 
0.2%
21 2
0.4%
20 2
0.4%
19 1
 
0.2%
18 3
0.6%
17 4
0.8%

평균_증빙_연소득(AVG_ICM1)
Real number (ℝ)

MISSING 

Distinct311
Distinct (%)99.0%
Missing186
Missing (%)37.2%
Infinite0
Infinite (%)0.0%
Mean47277.513
Minimum10970
Maximum474700
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:28.839033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10970
5-th percentile15756.5
Q125670
median37835
Q355367.5
95-th percentile105391.4
Maximum474700
Range463730
Interquartile range (IQR)29697.5

Descriptive statistics

Standard deviation39934.901
Coefficient of variation (CV)0.84469124
Kurtosis45.886184
Mean47277.513
Median Absolute Deviation (MAD)13660
Skewness5.3068245
Sum14845139
Variance1.5947963 × 109
MonotonicityNot monotonic
2023-12-10T23:50:29.007704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26620 2
 
0.4%
38045 2
 
0.4%
15600 2
 
0.4%
47563 1
 
0.2%
26047 1
 
0.2%
23365 1
 
0.2%
34545 1
 
0.2%
30000 1
 
0.2%
69203 1
 
0.2%
72755 1
 
0.2%
Other values (301) 301
60.2%
(Missing) 186
37.2%
ValueCountFrequency (%)
10970 1
0.2%
11260 1
0.2%
11440 1
0.2%
11840 1
0.2%
12000 1
0.2%
12200 1
0.2%
12770 1
0.2%
13410 1
0.2%
13900 1
0.2%
13930 1
0.2%
ValueCountFrequency (%)
474700 1
0.2%
264700 1
0.2%
239804 1
0.2%
201543 1
0.2%
147615 1
0.2%
145690 1
0.2%
141990 1
0.2%
128633 1
0.2%
122975 1
0.2%
121876 1
0.2%

평균_결정_연소득(AVG_ICM2)
Real number (ℝ)

Distinct480
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32084.988
Minimum12111
Maximum247606
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:29.199546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12111
5-th percentile17097.3
Q122770
median28424
Q335630.25
95-th percentile57396.45
Maximum247606
Range235495
Interquartile range (IQR)12860.25

Descriptive statistics

Standard deviation17659.513
Coefficient of variation (CV)0.55039801
Kurtosis48.244823
Mean32084.988
Median Absolute Deviation (MAD)6424
Skewness5.1052151
Sum16042494
Variance3.1185842 × 108
MonotonicityNot monotonic
2023-12-10T23:50:29.443609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22000 4
 
0.8%
28000 2
 
0.4%
13000 2
 
0.4%
26857 2
 
0.4%
23667 2
 
0.4%
18250 2
 
0.4%
14714 2
 
0.4%
13250 2
 
0.4%
22667 2
 
0.4%
24000 2
 
0.4%
Other values (470) 478
95.6%
ValueCountFrequency (%)
12111 1
0.2%
12167 1
0.2%
13000 2
0.4%
13077 1
0.2%
13100 1
0.2%
13143 2
0.4%
13167 1
0.2%
13200 1
0.2%
13250 2
0.4%
13308 1
0.2%
ValueCountFrequency (%)
247606 1
0.2%
129550 1
0.2%
117191 1
0.2%
111918 1
0.2%
104297 1
0.2%
99646 1
0.2%
87315 1
0.2%
84534 1
0.2%
82160 1
0.2%
80543 1
0.2%

평균_예금여력금액1(AVG_LN_P1)
Real number (ℝ)

SKEWED 

Distinct497
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63107.72
Minimum2012
Maximum22195799
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:29.652879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile8169.25
Q111853.25
median15067
Q319081.75
95-th percentile31638.5
Maximum22195799
Range22193787
Interquartile range (IQR)7228.5

Descriptive statistics

Standard deviation992117.53
Coefficient of variation (CV)15.721017
Kurtosis499.33128
Mean63107.72
Median Absolute Deviation (MAD)3544
Skewness22.338461
Sum31553860
Variance9.842972 × 1011
MonotonicityNot monotonic
2023-12-10T23:50:29.832072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16239 2
 
0.4%
10822 2
 
0.4%
16332 2
 
0.4%
18514 1
 
0.2%
10199 1
 
0.2%
13246 1
 
0.2%
97032 1
 
0.2%
27529 1
 
0.2%
10378 1
 
0.2%
11551 1
 
0.2%
Other values (487) 487
97.4%
ValueCountFrequency (%)
2012 1
0.2%
4602 1
0.2%
5052 1
0.2%
5599 1
0.2%
5899 1
0.2%
5976 1
0.2%
6039 1
0.2%
6130 1
0.2%
6186 1
0.2%
6541 1
0.2%
ValueCountFrequency (%)
22195799 1
0.2%
345744 1
0.2%
312669 1
0.2%
266774 1
0.2%
205201 1
0.2%
97032 1
0.2%
72566 1
0.2%
58588 1
0.2%
55371 1
0.2%
52478 1
0.2%

평균_예금여력금액2(AVG_LN_P2)
Real number (ℝ)

ZEROS 

Distinct469
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9451.156
Minimum0
Maximum67186
Zeros25
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:30.025096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile212.8
Q13752
median7007.5
Q312698
95-th percentile25195.05
Maximum67186
Range67186
Interquartile range (IQR)8946

Descriptive statistics

Standard deviation8644.0144
Coefficient of variation (CV)0.91459864
Kurtosis8.6459701
Mean9451.156
Median Absolute Deviation (MAD)3853
Skewness2.3020909
Sum4725578
Variance74718985
MonotonicityNot monotonic
2023-12-10T23:50:30.188298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25
 
5.0%
5857 2
 
0.4%
6851 2
 
0.4%
6269 2
 
0.4%
2000 2
 
0.4%
16331 2
 
0.4%
4948 2
 
0.4%
14141 2
 
0.4%
5838 1
 
0.2%
11230 1
 
0.2%
Other values (459) 459
91.8%
ValueCountFrequency (%)
0 25
5.0%
224 1
 
0.2%
692 1
 
0.2%
695 1
 
0.2%
893 1
 
0.2%
939 1
 
0.2%
992 1
 
0.2%
996 1
 
0.2%
997 1
 
0.2%
1044 1
 
0.2%
ValueCountFrequency (%)
67186 1
0.2%
62222 1
0.2%
50771 1
0.2%
49215 1
0.2%
41566 1
0.2%
40603 1
0.2%
37049 1
0.2%
36754 1
0.2%
35606 1
0.2%
35460 1
0.2%

신용대출_보유자_수(CRDT_LN_CNT)
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.282
Minimum0
Maximum100
Zeros99
Zeros (%)19.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:30.382753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile9
Maximum100
Range100
Interquartile range (IQR)3

Descriptive statistics

Standard deviation5.411566
Coefficient of variation (CV)1.6488623
Kurtosis205.0385
Mean3.282
Median Absolute Deviation (MAD)2
Skewness11.877112
Sum1641
Variance29.285046
MonotonicityNot monotonic
2023-12-10T23:50:30.526001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 99
19.8%
1 90
18.0%
2 79
15.8%
3 71
14.2%
4 42
8.4%
6 33
 
6.6%
5 24
 
4.8%
7 19
 
3.8%
9 11
 
2.2%
8 9
 
1.8%
Other values (10) 23
 
4.6%
ValueCountFrequency (%)
0 99
19.8%
1 90
18.0%
2 79
15.8%
3 71
14.2%
4 42
8.4%
5 24
 
4.8%
6 33
 
6.6%
7 19
 
3.8%
8 9
 
1.8%
9 11
 
2.2%
ValueCountFrequency (%)
100 1
 
0.2%
22 1
 
0.2%
21 1
 
0.2%
18 2
 
0.4%
17 1
 
0.2%
14 1
 
0.2%
13 1
 
0.2%
12 6
1.2%
11 5
1.0%
10 4
0.8%

주택담보대출_보유자_수(HOUS_LN_CNT)
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.53
Minimum0
Maximum14
Zeros208
Zeros (%)41.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:30.653371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile6
Maximum14
Range14
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.0585371
Coefficient of variation (CV)1.3454491
Kurtosis5.2536918
Mean1.53
Median Absolute Deviation (MAD)1
Skewness2.0155671
Sum765
Variance4.2375752
MonotonicityNot monotonic
2023-12-10T23:50:30.790681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 208
41.6%
1 122
24.4%
2 59
 
11.8%
3 38
 
7.6%
5 24
 
4.8%
4 22
 
4.4%
6 13
 
2.6%
8 4
 
0.8%
9 4
 
0.8%
7 3
 
0.6%
Other values (2) 3
 
0.6%
ValueCountFrequency (%)
0 208
41.6%
1 122
24.4%
2 59
 
11.8%
3 38
 
7.6%
4 22
 
4.4%
5 24
 
4.8%
6 13
 
2.6%
7 3
 
0.6%
8 4
 
0.8%
9 4
 
0.8%
ValueCountFrequency (%)
14 1
 
0.2%
11 2
 
0.4%
9 4
 
0.8%
8 4
 
0.8%
7 3
 
0.6%
6 13
 
2.6%
5 24
4.8%
4 22
 
4.4%
3 38
7.6%
2 59
11.8%

평균_신용대출_대출잔액(CRDT_LN_BAL)
Real number (ℝ)

ZEROS 

Distinct401
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18553.712
Minimum0
Maximum258038
Zeros95
Zeros (%)19.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:30.957603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13360.5
median12058
Q324154.75
95-th percentile62003.95
Maximum258038
Range258038
Interquartile range (IQR)20794.25

Descriptive statistics

Standard deviation23397.969
Coefficient of variation (CV)1.2610937
Kurtosis24.458247
Mean18553.712
Median Absolute Deviation (MAD)9880.5
Skewness3.557273
Sum9276856
Variance5.4746497 × 108
MonotonicityNot monotonic
2023-12-10T23:50:31.123293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 95
 
19.0%
10000 3
 
0.6%
15064 2
 
0.4%
6000 2
 
0.4%
8000 2
 
0.4%
30383 1
 
0.2%
36122 1
 
0.2%
4444 1
 
0.2%
574 1
 
0.2%
22379 1
 
0.2%
Other values (391) 391
78.2%
ValueCountFrequency (%)
0 95
19.0%
2 1
 
0.2%
250 1
 
0.2%
315 1
 
0.2%
574 1
 
0.2%
652 1
 
0.2%
800 1
 
0.2%
849 1
 
0.2%
1000 1
 
0.2%
1133 1
 
0.2%
ValueCountFrequency (%)
258038 1
0.2%
126012 1
0.2%
124914 1
0.2%
119076 1
0.2%
117115 1
0.2%
105214 1
0.2%
93114 1
0.2%
89782 1
0.2%
87938 1
0.2%
79634 1
0.2%

평균_주택담보대출_대출잔액(HOUS_LN_BAL)
Real number (ℝ)

ZEROS 

Distinct277
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85799.846
Minimum0
Maximum1550000
Zeros219
Zeros (%)43.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:31.318395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median35122.5
Q3127450.5
95-th percentile295235.95
Maximum1550000
Range1550000
Interquartile range (IQR)127450.5

Descriptive statistics

Standard deviation146203.13
Coefficient of variation (CV)1.7040023
Kurtosis37.697824
Mean85799.846
Median Absolute Deviation (MAD)35122.5
Skewness4.8446505
Sum42899923
Variance2.1375356 × 1010
MonotonicityNot monotonic
2023-12-10T23:50:31.528934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 219
43.8%
30000 3
 
0.6%
50000 2
 
0.4%
10000 2
 
0.4%
65000 2
 
0.4%
266915 1
 
0.2%
59028 1
 
0.2%
79888 1
 
0.2%
465434 1
 
0.2%
48716 1
 
0.2%
Other values (267) 267
53.4%
ValueCountFrequency (%)
0 219
43.8%
2704 1
 
0.2%
8803 1
 
0.2%
10000 2
 
0.4%
14050 1
 
0.2%
14925 1
 
0.2%
17649 1
 
0.2%
18000 1
 
0.2%
18763 1
 
0.2%
19100 1
 
0.2%
ValueCountFrequency (%)
1550000 1
0.2%
1460000 1
0.2%
831883 1
0.2%
737980 1
0.2%
650000 1
0.2%
621156 1
0.2%
619671 1
0.2%
554400 1
0.2%
540980 1
0.2%
500389 1
0.2%

평균_신용카드_총이용금액(3개월)(SIN_TOT_M3_AMT)
Real number (ℝ)

ZEROS 

Distinct462
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3133.986
Minimum0
Maximum54056
Zeros25
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:32.097683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile36.1
Q11170
median2353
Q34114.5
95-th percentile8038.7
Maximum54056
Range54056
Interquartile range (IQR)2944.5

Descriptive statistics

Standard deviation3646.0542
Coefficient of variation (CV)1.163392
Kurtosis79.335407
Mean3133.986
Median Absolute Deviation (MAD)1327.5
Skewness6.6534487
Sum1566993
Variance13293712
MonotonicityNot monotonic
2023-12-10T23:50:32.356036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25
 
5.0%
2076 2
 
0.4%
1288 2
 
0.4%
1576 2
 
0.4%
2470 2
 
0.4%
2170 2
 
0.4%
4448 2
 
0.4%
3155 2
 
0.4%
2715 2
 
0.4%
980 2
 
0.4%
Other values (452) 457
91.4%
ValueCountFrequency (%)
0 25
5.0%
38 1
 
0.2%
80 1
 
0.2%
98 1
 
0.2%
110 1
 
0.2%
121 1
 
0.2%
142 1
 
0.2%
214 1
 
0.2%
224 1
 
0.2%
240 1
 
0.2%
ValueCountFrequency (%)
54056 1
0.2%
24988 1
0.2%
18877 1
0.2%
16853 1
0.2%
14751 1
0.2%
14257 1
0.2%
14249 1
0.2%
13821 1
0.2%
13420 1
0.2%
13371 1
0.2%

평균_신용카드_일시불이용금액(3개월)(SIN_FUL_M3_AMT)
Real number (ℝ)

ZEROS 

Distinct450
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2422.36
Minimum0
Maximum21762
Zeros22
Zeros (%)4.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:32.535562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile42.75
Q1874.75
median1808.5
Q33124.25
95-th percentile7436.5
Maximum21762
Range21762
Interquartile range (IQR)2249.5

Descriptive statistics

Standard deviation2571.369
Coefficient of variation (CV)1.061514
Kurtosis13.367323
Mean2422.36
Median Absolute Deviation (MAD)1065
Skewness2.9426769
Sum1211180
Variance6611938.5
MonotonicityNot monotonic
2023-12-10T23:50:32.713368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22
 
4.4%
1935 3
 
0.6%
1602 3
 
0.6%
756 2
 
0.4%
1871 2
 
0.4%
1246 2
 
0.4%
1356 2
 
0.4%
2451 2
 
0.4%
919 2
 
0.4%
602 2
 
0.4%
Other values (440) 458
91.6%
ValueCountFrequency (%)
0 22
4.4%
3 1
 
0.2%
13 1
 
0.2%
19 1
 
0.2%
44 1
 
0.2%
98 1
 
0.2%
106 1
 
0.2%
109 1
 
0.2%
121 1
 
0.2%
124 1
 
0.2%
ValueCountFrequency (%)
21762 1
0.2%
19174 1
0.2%
16852 1
0.2%
12543 1
0.2%
12528 1
0.2%
12403 1
0.2%
12273 1
0.2%
11613 1
0.2%
11501 1
0.2%
11468 1
0.2%

평균_신용카드_할부이용금액(3개월)(SIN_INSTL_M3_AMT)
Real number (ℝ)

ZEROS 

Distinct391
Distinct (%)78.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean630.982
Minimum0
Maximum10611
Zeros34
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:32.914710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1176.25
median447
Q3834.25
95-th percentile1723.85
Maximum10611
Range10611
Interquartile range (IQR)658

Descriptive statistics

Standard deviation802.34487
Coefficient of variation (CV)1.2715812
Kurtosis53.306383
Mean630.982
Median Absolute Deviation (MAD)306.5
Skewness5.5087842
Sum315491
Variance643757.28
MonotonicityNot monotonic
2023-12-10T23:50:33.149923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34
 
6.8%
442 4
 
0.8%
594 3
 
0.6%
247 3
 
0.6%
387 3
 
0.6%
693 3
 
0.6%
95 3
 
0.6%
180 3
 
0.6%
1143 2
 
0.4%
622 2
 
0.4%
Other values (381) 440
88.0%
ValueCountFrequency (%)
0 34
6.8%
7 1
 
0.2%
9 2
 
0.4%
16 1
 
0.2%
21 1
 
0.2%
23 2
 
0.4%
25 1
 
0.2%
27 1
 
0.2%
28 2
 
0.4%
33 1
 
0.2%
ValueCountFrequency (%)
10611 1
0.2%
5599 1
0.2%
4495 1
0.2%
4487 1
0.2%
4179 1
0.2%
3834 1
0.2%
3616 1
0.2%
3346 1
0.2%
2755 1
0.2%
2402 1
0.2%

평균_신용카드_해외이용금액(3개월)(SIN_ABRD_M3_AMT)
Real number (ℝ)

ZEROS 

Distinct183
Distinct (%)36.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.962
Minimum0
Maximum2001
Zeros179
Zeros (%)35.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:33.360792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median16
Q387
95-th percentile399.75
Maximum2001
Range2001
Interquartile range (IQR)87

Descriptive statistics

Standard deviation205.91911
Coefficient of variation (CV)2.2391761
Kurtosis31.701892
Mean91.962
Median Absolute Deviation (MAD)16
Skewness4.9000712
Sum45981
Variance42402.682
MonotonicityNot monotonic
2023-12-10T23:50:33.555976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 179
35.8%
4 9
 
1.8%
6 9
 
1.8%
5 8
 
1.6%
9 8
 
1.6%
2 8
 
1.6%
49 5
 
1.0%
8 5
 
1.0%
15 5
 
1.0%
33 5
 
1.0%
Other values (173) 259
51.8%
ValueCountFrequency (%)
0 179
35.8%
1 3
 
0.6%
2 8
 
1.6%
3 4
 
0.8%
4 9
 
1.8%
5 8
 
1.6%
6 9
 
1.8%
7 2
 
0.4%
8 5
 
1.0%
9 8
 
1.6%
ValueCountFrequency (%)
2001 1
0.2%
1735 1
0.2%
1447 1
0.2%
1390 1
0.2%
1187 1
0.2%
984 1
0.2%
878 1
0.2%
811 1
0.2%
773 1
0.2%
751 1
0.2%

평균_체크카드_총이용금액(3개월)(CHK_TOT_M3_AMT)
Real number (ℝ)

ZEROS 

Distinct428
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean763.038
Minimum0
Maximum29015
Zeros15
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:33.772038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile21.95
Q1248
median571
Q31050.5
95-th percentile1809.6
Maximum29015
Range29015
Interquartile range (IQR)802.5

Descriptive statistics

Standard deviation1388.6359
Coefficient of variation (CV)1.8198778
Kurtosis344.60404
Mean763.038
Median Absolute Deviation (MAD)377.5
Skewness16.998951
Sum381519
Variance1928309.7
MonotonicityNot monotonic
2023-12-10T23:50:33.978026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15
 
3.0%
869 3
 
0.6%
513 3
 
0.6%
24 3
 
0.6%
105 3
 
0.6%
1209 3
 
0.6%
66 3
 
0.6%
457 3
 
0.6%
699 3
 
0.6%
600 3
 
0.6%
Other values (418) 458
91.6%
ValueCountFrequency (%)
0 15
3.0%
1 1
 
0.2%
4 1
 
0.2%
6 1
 
0.2%
12 1
 
0.2%
13 1
 
0.2%
15 1
 
0.2%
18 2
 
0.4%
19 1
 
0.2%
21 1
 
0.2%
ValueCountFrequency (%)
29015 1
0.2%
3345 1
0.2%
3250 1
0.2%
2712 1
0.2%
2397 1
0.2%
2365 1
0.2%
2357 1
0.2%
2209 1
0.2%
2185 1
0.2%
2180 1
0.2%

평균_체크카드_일시불이용금액(3개월)(CHK_FUL_M3_AMT)
Real number (ℝ)

ZEROS 

Distinct417
Distinct (%)83.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean726.27
Minimum0
Maximum12980
Zeros17
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:34.211076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.8
Q1217.75
median560.5
Q3992.5
95-th percentile1772.2
Maximum12980
Range12980
Interquartile range (IQR)774.75

Descriptive statistics

Standard deviation857.14876
Coefficient of variation (CV)1.1802067
Kurtosis87.274538
Mean726.27
Median Absolute Deviation (MAD)378.5
Skewness6.9662802
Sum363135
Variance734703.99
MonotonicityNot monotonic
2023-12-10T23:50:34.438181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17
 
3.4%
21 4
 
0.8%
555 3
 
0.6%
166 3
 
0.6%
212 3
 
0.6%
651 3
 
0.6%
534 3
 
0.6%
520 3
 
0.6%
28 3
 
0.6%
122 2
 
0.4%
Other values (407) 456
91.2%
ValueCountFrequency (%)
0 17
3.4%
1 1
 
0.2%
2 1
 
0.2%
3 1
 
0.2%
4 1
 
0.2%
6 1
 
0.2%
7 2
 
0.4%
10 1
 
0.2%
14 1
 
0.2%
18 1
 
0.2%
ValueCountFrequency (%)
12980 1
0.2%
6127 1
0.2%
4818 1
0.2%
4414 1
0.2%
2886 1
0.2%
2628 1
0.2%
2600 1
0.2%
2551 1
0.2%
2411 1
0.2%
2320 1
0.2%

평균_체크카드_할부이용금액(3개월)(CHK_INSTL_M3_AMT)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
500 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 500
100.0%

Length

2023-12-10T23:50:34.629900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:50:34.755099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 500
100.0%

평균_체크카드_해외이용금액(3개월)(CHK_ABRD_M3_AMT)
Real number (ℝ)

ZEROS 

Distinct77
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.314
Minimum0
Maximum983
Zeros326
Zeros (%)65.2%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:34.923033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile79.05
Maximum983
Range983
Interquartile range (IQR)6

Descriptive statistics

Standard deviation62.132248
Coefficient of variation (CV)3.8085232
Kurtosis127.49487
Mean16.314
Median Absolute Deviation (MAD)0
Skewness9.6479942
Sum8157
Variance3860.4162
MonotonicityNot monotonic
2023-12-10T23:50:35.142883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 326
65.2%
1 13
 
2.6%
2 11
 
2.2%
3 7
 
1.4%
5 7
 
1.4%
6 7
 
1.4%
4 6
 
1.2%
11 6
 
1.2%
17 5
 
1.0%
22 4
 
0.8%
Other values (67) 108
 
21.6%
ValueCountFrequency (%)
0 326
65.2%
1 13
 
2.6%
2 11
 
2.2%
3 7
 
1.4%
4 6
 
1.2%
5 7
 
1.4%
6 7
 
1.4%
7 2
 
0.4%
8 4
 
0.8%
9 3
 
0.6%
ValueCountFrequency (%)
983 1
0.2%
480 1
0.2%
383 1
0.2%
311 1
0.2%
243 1
0.2%
242 1
0.2%
238 1
0.2%
216 1
0.2%
214 1
0.2%
210 1
0.2%

평균_보유주택건수(HOUS_HLD_CNT)
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
353 
1
141 
2
 
4
3
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
0 353
70.6%
1 141
 
28.2%
2 4
 
0.8%
3 1
 
0.2%
4 1
 
0.2%

Length

2023-12-10T23:50:35.307804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:50:35.456171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 353
70.6%
1 141
 
28.2%
2 4
 
0.8%
3 1
 
0.2%
4 1
 
0.2%

자가거주자_수(ONHS_CNT)
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.054
Minimum0
Maximum40
Zeros235
Zeros (%)47.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:35.621277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile8
Maximum40
Range40
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.6217839
Coefficient of variation (CV)1.7632833
Kurtosis37.039818
Mean2.054
Median Absolute Deviation (MAD)1
Skewness4.7228486
Sum1027
Variance13.117319
MonotonicityNot monotonic
2023-12-10T23:50:35.817849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 235
47.0%
1 71
 
14.2%
2 51
 
10.2%
3 42
 
8.4%
4 31
 
6.2%
6 19
 
3.8%
5 13
 
2.6%
7 11
 
2.2%
8 7
 
1.4%
10 4
 
0.8%
Other values (7) 16
 
3.2%
ValueCountFrequency (%)
0 235
47.0%
1 71
 
14.2%
2 51
 
10.2%
3 42
 
8.4%
4 31
 
6.2%
5 13
 
2.6%
6 19
 
3.8%
7 11
 
2.2%
8 7
 
1.4%
9 3
 
0.6%
ValueCountFrequency (%)
40 1
 
0.2%
34 1
 
0.2%
17 1
 
0.2%
15 3
 
0.6%
14 4
 
0.8%
11 3
 
0.6%
10 4
 
0.8%
9 3
 
0.6%
8 7
1.4%
7 11
2.2%

경형_승용차_보유자_수(CAR_SZ01_CNT)
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
454 
1
 
42
2
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 454
90.8%
1 42
 
8.4%
2 4
 
0.8%

Length

2023-12-10T23:50:36.060488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:50:36.219324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 454
90.8%
1 42
 
8.4%
2 4
 
0.8%

소형_승용차_보유자_수(CAR_SZ02_CNT)
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
492 
1
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 492
98.4%
1 8
 
1.6%

Length

2023-12-10T23:50:36.371820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:50:36.517054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 492
98.4%
1 8
 
1.6%

준중형_승용차_보유자_수(CAR_SZ03_CNT)
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
430 
1
62 
2
 
5
3
 
2
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 430
86.0%
1 62
 
12.4%
2 5
 
1.0%
3 2
 
0.4%
4 1
 
0.2%

Length

2023-12-10T23:50:36.670878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:50:36.807467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 430
86.0%
1 62
 
12.4%
2 5
 
1.0%
3 2
 
0.4%
4 1
 
0.2%

중형_승용차_보유자_수(CAR_SZ04_CNT)
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.326
Minimum0
Maximum5
Zeros384
Zeros (%)76.8%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:36.938157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.71326116
Coefficient of variation (CV)2.1879177
Kurtosis11.46467
Mean0.326
Median Absolute Deviation (MAD)0
Skewness2.9909235
Sum163
Variance0.50874148
MonotonicityNot monotonic
2023-12-10T23:50:37.108608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 384
76.8%
1 86
 
17.2%
2 19
 
3.8%
3 7
 
1.4%
4 2
 
0.4%
5 2
 
0.4%
ValueCountFrequency (%)
0 384
76.8%
1 86
 
17.2%
2 19
 
3.8%
3 7
 
1.4%
4 2
 
0.4%
5 2
 
0.4%
ValueCountFrequency (%)
5 2
 
0.4%
4 2
 
0.4%
3 7
 
1.4%
2 19
 
3.8%
1 86
 
17.2%
0 384
76.8%

대형_승용차_보유자_수(CAR_SZ05_CNT)
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.356
Minimum0
Maximum5
Zeros378
Zeros (%)75.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:37.263474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.73915946
Coefficient of variation (CV)2.0762906
Kurtosis7.5216667
Mean0.356
Median Absolute Deviation (MAD)0
Skewness2.5522583
Sum178
Variance0.54635671
MonotonicityNot monotonic
2023-12-10T23:50:37.435692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 378
75.6%
1 84
 
16.8%
2 24
 
4.8%
3 11
 
2.2%
4 2
 
0.4%
5 1
 
0.2%
ValueCountFrequency (%)
0 378
75.6%
1 84
 
16.8%
2 24
 
4.8%
3 11
 
2.2%
4 2
 
0.4%
5 1
 
0.2%
ValueCountFrequency (%)
5 1
 
0.2%
4 2
 
0.4%
3 11
 
2.2%
2 24
 
4.8%
1 84
 
16.8%
0 378
75.6%

국산_승용차_보유자_수(CAR_DMST_CNT)
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.788
Minimum0
Maximum7
Zeros283
Zeros (%)56.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:50:37.602762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2074651
Coefficient of variation (CV)1.5323161
Kurtosis4.7901504
Mean0.788
Median Absolute Deviation (MAD)0
Skewness2.0520832
Sum394
Variance1.4579719
MonotonicityNot monotonic
2023-12-10T23:50:37.792855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 283
56.6%
1 123
24.6%
2 49
 
9.8%
3 24
 
4.8%
4 10
 
2.0%
5 6
 
1.2%
6 4
 
0.8%
7 1
 
0.2%
ValueCountFrequency (%)
0 283
56.6%
1 123
24.6%
2 49
 
9.8%
3 24
 
4.8%
4 10
 
2.0%
5 6
 
1.2%
6 4
 
0.8%
7 1
 
0.2%
ValueCountFrequency (%)
7 1
 
0.2%
6 4
 
0.8%
5 6
 
1.2%
4 10
 
2.0%
3 24
 
4.8%
2 49
 
9.8%
1 123
24.6%
0 283
56.6%

수입_승용차_보유자_수(CAR_FRGN_CNT)
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
0
448 
1
45 
2
 
6
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 448
89.6%
1 45
 
9.0%
2 6
 
1.2%
3 1
 
0.2%

Length

2023-12-10T23:50:38.014906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:50:38.161851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 448
89.6%
1 45
 
9.0%
2 6
 
1.2%
3 1
 
0.2%

Sample

데이터기준년월(BS_YR_MON)서울시_블럭ID(BLK_CD)성별(GENDER)연령대(AGE)거주자_수(CUST_CNT)급여소득자_수(MDL4_CNT)자영업자_수(MDL5_CNT)기타(무직,주부,학생등)수(MDL9_CNT)평균_증빙_연소득(AVG_ICM1)평균_결정_연소득(AVG_ICM2)평균_예금여력금액1(AVG_LN_P1)평균_예금여력금액2(AVG_LN_P2)신용대출_보유자_수(CRDT_LN_CNT)주택담보대출_보유자_수(HOUS_LN_CNT)평균_신용대출_대출잔액(CRDT_LN_BAL)평균_주택담보대출_대출잔액(HOUS_LN_BAL)평균_신용카드_총이용금액(3개월)(SIN_TOT_M3_AMT)평균_신용카드_일시불이용금액(3개월)(SIN_FUL_M3_AMT)평균_신용카드_할부이용금액(3개월)(SIN_INSTL_M3_AMT)평균_신용카드_해외이용금액(3개월)(SIN_ABRD_M3_AMT)평균_체크카드_총이용금액(3개월)(CHK_TOT_M3_AMT)평균_체크카드_일시불이용금액(3개월)(CHK_FUL_M3_AMT)평균_체크카드_할부이용금액(3개월)(CHK_INSTL_M3_AMT)평균_체크카드_해외이용금액(3개월)(CHK_ABRD_M3_AMT)평균_보유주택건수(HOUS_HLD_CNT)자가거주자_수(ONHS_CNT)경형_승용차_보유자_수(CAR_SZ01_CNT)소형_승용차_보유자_수(CAR_SZ02_CNT)준중형_승용차_보유자_수(CAR_SZ03_CNT)중형_승용차_보유자_수(CAR_SZ04_CNT)대형_승용차_보유자_수(CAR_SZ05_CNT)국산_승용차_보유자_수(CAR_DMST_CNT)수입_승용차_보유자_수(CAR_FRGN_CNT)
02018122*2*9*2516151<NA>37750115511567830303832401505269154940708692300010001020
12019032*3*7*2218508<NA>525541365123252431935216052959001610205305010000010000
22018062*2*4*15141102<NA>1314314250104330015357075921089640239712401030001001
32019066*5*91181226<NA>410681361548630170070597033835058344641400040000110
42018033*3*4*15272021802521826302135310114263038871264137563401108300110000000
52018033*4*8*262511429158283432586285913262000300006108915331074083300000000000
62018061*5*723181522<NA>2677819186229721038590121281397828623191361372164080100000200
72018063*4*3*2612504201543200001125589364369117810924621290933183813200110000000
82018094*4*6*1512129723002211819852299171422230133010671277112628100101000001
92018031*0*6151378864250305001227789990027802765001692118844066200134000020000
데이터기준년월(BS_YR_MON)서울시_블럭ID(BLK_CD)성별(GENDER)연령대(AGE)거주자_수(CUST_CNT)급여소득자_수(MDL4_CNT)자영업자_수(MDL5_CNT)기타(무직,주부,학생등)수(MDL9_CNT)평균_증빙_연소득(AVG_ICM1)평균_결정_연소득(AVG_ICM2)평균_예금여력금액1(AVG_LN_P1)평균_예금여력금액2(AVG_LN_P2)신용대출_보유자_수(CRDT_LN_CNT)주택담보대출_보유자_수(HOUS_LN_CNT)평균_신용대출_대출잔액(CRDT_LN_BAL)평균_주택담보대출_대출잔액(HOUS_LN_BAL)평균_신용카드_총이용금액(3개월)(SIN_TOT_M3_AMT)평균_신용카드_일시불이용금액(3개월)(SIN_FUL_M3_AMT)평균_신용카드_할부이용금액(3개월)(SIN_INSTL_M3_AMT)평균_신용카드_해외이용금액(3개월)(SIN_ABRD_M3_AMT)평균_체크카드_총이용금액(3개월)(CHK_TOT_M3_AMT)평균_체크카드_일시불이용금액(3개월)(CHK_FUL_M3_AMT)평균_체크카드_할부이용금액(3개월)(CHK_INSTL_M3_AMT)평균_체크카드_해외이용금액(3개월)(CHK_ABRD_M3_AMT)평균_보유주택건수(HOUS_HLD_CNT)자가거주자_수(ONHS_CNT)경형_승용차_보유자_수(CAR_SZ01_CNT)소형_승용차_보유자_수(CAR_SZ02_CNT)준중형_승용차_보유자_수(CAR_SZ03_CNT)중형_승용차_보유자_수(CAR_SZ04_CNT)대형_승용차_보유자_수(CAR_SZ05_CNT)국산_승용차_보유자_수(CAR_DMST_CNT)수입_승용차_보유자_수(CAR_FRGN_CNT)
4902018122*2*1*2214506<NA>3191012463474800466948755528175294172201156173200000010000
4912019033*5*7*1638827<NA>43734180786993322065015003646527705495898584800020000000
4922018032*1*7*1610711010111339012183150032580380186219220303583300134001000000
4932019064*5*0*2712406<NA>268577283733004570430000218484058451670810243110001130
4942018122*0*3*2511417<NA>1825013147932702105214203000104113074069120826011030000000
4952018092*1*3*123735126620356181325680430125000206636501727997674616189702100000200
4962019062*8*3*268305<NA>21135192084970002159888774921706018775857803100000020
4972019061*5*5*2596234501719857117801997921000006113019123681052028001000000
4982018061*6*412133134049428871147275462223634595400100954407540218250110000000000
4992018091*4*32722823<NA>5407126545541505698616432648040118154070052101001010