Overview

Dataset statistics

Number of variables17
Number of observations200
Missing cells0
Missing cells (%)0.0%
Duplicate rows10
Duplicate rows (%)5.0%
Total size in memory29.8 KiB
Average record size in memory152.7 B

Variable types

Categorical3
Numeric14

Alerts

집계기준년도 has constant value ""Constant
Dataset has 10 (5.0%) duplicate rowsDuplicates
교통지출금액 is highly overall correlated with 통신지출금액 and 11 other fieldsHigh correlation
통신지출금액 is highly overall correlated with 교통지출금액 and 11 other fieldsHigh correlation
오락문화지출금액 is highly overall correlated with 교통지출금액 and 11 other fieldsHigh correlation
교육지출금액 is highly overall correlated with 교통지출금액 and 11 other fieldsHigh correlation
음식숙박지출금액 is highly overall correlated with 교통지출금액 and 11 other fieldsHigh correlation
기타상품서비스지출금액 is highly overall correlated with 교통지출금액 and 11 other fieldsHigh correlation
비소비지출지출금액 is highly overall correlated with 교통지출금액 and 11 other fieldsHigh correlation
집계영역코드 is highly overall correlated with 집계영역구분코드High correlation
식료품음료수지출금액 is highly overall correlated with 교통지출금액 and 11 other fieldsHigh correlation
주류담배지출금액 is highly overall correlated with 교통지출금액 and 11 other fieldsHigh correlation
의류신발지출금액 is highly overall correlated with 교통지출금액 and 11 other fieldsHigh correlation
주거비수도비광열비지출금액 is highly overall correlated with 교통지출금액 and 11 other fieldsHigh correlation
가정용품가사서비스지출금액 is highly overall correlated with 교통지출금액 and 11 other fieldsHigh correlation
보건지출금액 is highly overall correlated with 교통지출금액 and 11 other fieldsHigh correlation
집계영역구분코드 is highly overall correlated with 집계영역코드High correlation

Reproduction

Analysis started2023-12-10 06:47:48.585729
Analysis finished2023-12-10 06:48:11.158478
Duration22.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계영역구분코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2
79 
3
65 
1
54 
6
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row3
4th row1
5th row3

Common Values

ValueCountFrequency (%)
2 79
39.5%
3 65
32.5%
1 54
27.0%
6 2
 
1.0%

Length

2023-12-10T15:48:11.227789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:48:11.330312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 79
39.5%
3 65
32.5%
1 54
27.0%
6 2
 
1.0%

집계기준년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2021
200 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021
2nd row2021
3rd row2021
4th row2021
5th row2021

Common Values

ValueCountFrequency (%)
2021 200
100.0%

Length

2023-12-10T15:48:11.438887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:48:11.562845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021 200
100.0%

교통지출금액
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89593614
Minimum125170
Maximum9.1427991 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:11.658029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum125170
5-th percentile249142.4
Q11250058.5
median4971152.5
Q393031763
95-th percentile4.71502 × 108
Maximum9.1427991 × 108
Range9.1415474 × 108
Interquartile range (IQR)91781704

Descriptive statistics

Standard deviation1.6740579 × 108
Coefficient of variation (CV)1.8685014
Kurtosis7.5734701
Mean89593614
Median Absolute Deviation (MAD)4776961.5
Skewness2.6395823
Sum1.7918723 × 1010
Variance2.8024699 × 1016
MonotonicityNot monotonic
2023-12-10T15:48:11.829277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
598682 4
 
2.0%
125170 4
 
2.0%
194191 3
 
1.5%
92625800 3
 
1.5%
625850 2
 
1.0%
1627210 2
 
1.0%
171052 2
 
1.0%
3501855 2
 
1.0%
185501940 2
 
1.0%
339582 2
 
1.0%
Other values (157) 174
87.0%
ValueCountFrequency (%)
125170 4
2.0%
171052 2
1.0%
194191 3
1.5%
226388 1
 
0.5%
250340 2
1.0%
273164 1
 
0.5%
282985 1
 
0.5%
339582 2
1.0%
342104 1
 
0.5%
375510 1
 
0.5%
ValueCountFrequency (%)
914279908 1
0.5%
888941625 1
0.5%
828111570 1
0.5%
628479280 1
0.5%
607418955 1
0.5%
599680510 1
0.5%
532385425 1
0.5%
483309970 2
1.0%
478999950 1
0.5%
471107366 1
0.5%

통신지출금액
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37921783
Minimum40744
Maximum4.463085 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:11.987633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40744
5-th percentile100447.4
Q1519486
median2391119.5
Q339272900
95-th percentile2.0615026 × 108
Maximum4.463085 × 108
Range4.4626776 × 108
Interquartile range (IQR)38753414

Descriptive statistics

Standard deviation75904147
Coefficient of variation (CV)2.0015975
Kurtosis9.529702
Mean37921783
Median Absolute Deviation (MAD)2290165.5
Skewness2.9668974
Sum7.5843567 × 109
Variance5.7614396 × 1015
MonotonicityNot monotonic
2023-12-10T15:48:12.141013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
353339 4
 
2.0%
40744 4
 
2.0%
61746 3
 
1.5%
30150560 3
 
1.5%
203720 2
 
1.0%
529672 2
 
1.0%
100954 2
 
1.0%
1376235 2
 
1.0%
60382608 2
 
1.0%
155280 2
 
1.0%
Other values (157) 174
87.0%
ValueCountFrequency (%)
40744 4
2.0%
61746 3
1.5%
81488 2
1.0%
90822 1
 
0.5%
100954 2
1.0%
103520 1
 
0.5%
122232 1
 
0.5%
129400 1
 
0.5%
136233 2
1.0%
155280 2
1.0%
ValueCountFrequency (%)
446308500 1
0.5%
415767720 1
0.5%
315538880 1
0.5%
304965180 1
0.5%
303981234 1
0.5%
301079960 1
0.5%
267293300 1
0.5%
242654120 2
1.0%
240490200 1
0.5%
204342900 1
0.5%

오락문화지출금액
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47141294
Minimum57577
Maximum4.9220313 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:12.311679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum57577
5-th percentile122088
Q1716803.5
median3695434.5
Q359846466
95-th percentile2.2745933 × 108
Maximum4.9220313 × 108
Range4.9214555 × 108
Interquartile range (IQR)59129662

Descriptive statistics

Standard deviation84586905
Coefficient of variation (CV)1.7943272
Kurtosis7.618578
Mean47141294
Median Absolute Deviation (MAD)3469987
Skewness2.5823871
Sum9.4282589 × 109
Variance7.1549445 × 1015
MonotonicityNot monotonic
2023-12-10T15:48:12.468392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
427308 4
 
2.0%
57577 4
 
2.0%
86703 3
 
1.5%
42606980 3
 
1.5%
287885 2
 
1.0%
748501 2
 
1.0%
122088 2
 
1.0%
3052266 2
 
1.0%
85329114 2
 
1.0%
288354 2
 
1.0%
Other values (157) 174
87.0%
ValueCountFrequency (%)
57577 4
2.0%
86703 3
1.5%
115154 2
1.0%
122088 2
1.0%
147058 1
 
0.5%
172731 1
 
0.5%
192236 1
 
0.5%
220587 2
1.0%
230308 1
 
0.5%
240295 1
 
0.5%
ValueCountFrequency (%)
492203126 1
0.5%
438885150 1
0.5%
408852348 1
0.5%
310290592 1
0.5%
299892762 1
0.5%
296072164 1
0.5%
262847470 1
0.5%
238618108 2
1.0%
236490180 1
0.5%
226984023 2
1.0%

교육지출금액
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42711841
Minimum5504
Maximum3.5520458 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:12.658898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5504
5-th percentile28842
Q1609426
median2454665
Q366526302
95-th percentile2.0714204 × 108
Maximum3.5520458 × 108
Range3.5519907 × 108
Interquartile range (IQR)65916876

Descriptive statistics

Standard deviation74572555
Coefficient of variation (CV)1.7459457
Kurtosis3.2350446
Mean42711841
Median Absolute Deviation (MAD)2390681
Skewness1.9389722
Sum8.5423682 × 109
Variance5.5610659 × 1015
MonotonicityNot monotonic
2023-12-10T15:48:12.801106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1218329 4
 
2.0%
130534 4
 
2.0%
28842 3
 
1.5%
96595160 3
 
1.5%
652670 2
 
1.0%
1696942 2
 
1.0%
348094 2
 
1.0%
825741 2
 
1.0%
193451388 2
 
1.0%
8256 2
 
1.0%
Other values (157) 174
87.0%
ValueCountFrequency (%)
5504 1
 
0.5%
6880 1
 
0.5%
8256 2
1.0%
9632 1
 
0.5%
11008 1
 
0.5%
17888 1
 
0.5%
19264 1
 
0.5%
28842 3
1.5%
30272 2
1.0%
31648 1
 
0.5%
ValueCountFrequency (%)
355204575 1
0.5%
330898014 1
0.5%
317636994 1
0.5%
251128656 1
0.5%
242713341 1
0.5%
239662719 1
0.5%
239621202 1
0.5%
212731335 1
0.5%
210248776 1
0.5%
207638071 1
0.5%

음식숙박지출금액
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean90511345
Minimum109531
Maximum9.3722062 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:12.957294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum109531
5-th percentile245246
Q11314372
median5983616.5
Q399125555
95-th percentile4.3290298 × 108
Maximum9.3722062 × 108
Range9.3711109 × 108
Interquartile range (IQR)97811183

Descriptive statistics

Standard deviation1.6995875 × 108
Coefficient of variation (CV)1.8777618
Kurtosis7.9335945
Mean90511345
Median Absolute Deviation (MAD)5692937.5
Skewness2.7021757
Sum1.8102269 × 1010
Variance2.8885976 × 1016
MonotonicityNot monotonic
2023-12-10T15:48:13.113198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
858361 4
 
2.0%
109531 4
 
2.0%
165879 3
 
1.5%
81052940 3
 
1.5%
547655 2
 
1.0%
1423903 2
 
1.0%
245246 2
 
1.0%
3611244 2
 
1.0%
162324942 2
 
1.0%
387432 2
 
1.0%
Other values (157) 174
87.0%
ValueCountFrequency (%)
109531 4
2.0%
165879 3
1.5%
219062 2
1.0%
245246 2
1.0%
258288 1
 
0.5%
258498 1
 
0.5%
322860 1
 
0.5%
328593 1
 
0.5%
387432 2
1.0%
387747 2
1.0%
ValueCountFrequency (%)
937220625 1
0.5%
873086850 1
0.5%
865192806 1
0.5%
662612400 1
0.5%
640408275 1
0.5%
632249550 1
0.5%
561299625 1
0.5%
509558850 2
1.0%
505014750 1
0.5%
429107625 1
0.5%

기타상품서비스지출금액
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61834247
Minimum66318
Maximum6.017088 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:13.289274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66318
5-th percentile138550
Q1881046
median4738916
Q372091512
95-th percentile3.1115531 × 108
Maximum6.017088 × 108
Range6.0164248 × 108
Interquartile range (IQR)71210466

Descriptive statistics

Standard deviation1.1258168 × 108
Coefficient of variation (CV)1.8207011
Kurtosis7.1553884
Mean61834247
Median Absolute Deviation (MAD)4467263.5
Skewness2.5581462
Sum1.2366849 × 1010
Variance1.2674636 × 1016
MonotonicityNot monotonic
2023-12-10T15:48:13.457478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
484925 4
 
2.0%
66318 4
 
2.0%
127975 3
 
1.5%
49075320 3
 
1.5%
331590 2
 
1.0%
862134 2
 
1.0%
138550 2
 
1.0%
1638546 2
 
1.0%
98283276 2
 
1.0%
433764 2
 
1.0%
Other values (157) 174
87.0%
ValueCountFrequency (%)
66318 4
2.0%
127975 3
1.5%
132636 2
1.0%
138550 2
1.0%
177470 1
 
0.5%
198954 1
 
0.5%
265272 1
 
0.5%
266205 2
1.0%
277100 1
 
0.5%
289176 1
 
0.5%
ValueCountFrequency (%)
601708800 1
0.5%
593992090 1
0.5%
560534016 1
0.5%
425406464 1
0.5%
411151104 1
0.5%
405913088 1
0.5%
360362240 1
0.5%
327143936 2
1.0%
324226560 1
0.5%
310467350 1
0.5%

비소비지출지출금액
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2753833 × 108
Minimum255066
Maximum2.3486009 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:13.606077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum255066
5-th percentile581283
Q13094389
median15582560
Q32.7978096 × 108
95-th percentile1.2660965 × 109
Maximum2.3486009 × 109
Range2.3483459 × 109
Interquartile range (IQR)2.7668657 × 108

Descriptive statistics

Standard deviation4.2304194 × 108
Coefficient of variation (CV)1.8592118
Kurtosis7.3245822
Mean2.2753833 × 108
Median Absolute Deviation (MAD)14920454
Skewness2.6282496
Sum4.5507666 × 1010
Variance1.7896449 × 1017
MonotonicityNot monotonic
2023-12-10T15:48:13.761405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1940708 4
 
2.0%
255066 4
 
2.0%
581283 3
 
1.5%
188748840 3
 
1.5%
1275330 2
 
1.0%
3315858 2
 
1.0%
554488 2
 
1.0%
7039221 2
 
1.0%
378007812 2
 
1.0%
1114392 2
 
1.0%
Other values (157) 174
87.0%
ValueCountFrequency (%)
255066 4
2.0%
510132 2
1.0%
554488 2
1.0%
555844 1
 
0.5%
581283 3
1.5%
742928 1
 
0.5%
765198 1
 
0.5%
833766 2
1.0%
928660 1
 
0.5%
1020264 1
 
0.5%
ValueCountFrequency (%)
2348600925 1
0.5%
2187886746 1
0.5%
1860409868 1
0.5%
1660454384 1
0.5%
1604812599 1
0.5%
1584367478 1
0.5%
1410192558 1
0.5%
1406572565 1
0.5%
1276914266 2
1.0%
1265527110 1
0.5%

집계영역코드
Real number (ℝ)

HIGH CORRELATION 

Distinct158
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6293645 × 1011
Minimum213
Maximum1.1230801 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:13.896378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum213
5-th percentile15545.95
Q1282889.5
median11500611
Q31.1090743 × 1012
95-th percentile1.123068 × 1012
Maximum1.1230801 × 1012
Range1.1230801 × 1012
Interquartile range (IQR)1.109074 × 1012

Descriptive statistics

Standard deviation5.2435955 × 1011
Coefficient of variation (CV)1.4447696
Kurtosis-1.4473292
Mean3.6293645 × 1011
Median Absolute Deviation (MAD)11280262
Skewness0.75304312
Sum7.2587291 × 1013
Variance2.7495294 × 1023
MonotonicityNot monotonic
2023-12-10T15:48:14.070531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11305534 5
 
2.5%
11680700 5
 
2.5%
11500540 4
 
2.0%
11500530 3
 
1.5%
11305645 3
 
1.5%
11305615 3
 
1.5%
11305660 3
 
1.5%
11500611 3
 
1.5%
11500615 3
 
1.5%
11680655 2
 
1.0%
Other values (148) 166
83.0%
ValueCountFrequency (%)
213 1
0.5%
1708 1
0.5%
4281 1
0.5%
4775 1
0.5%
13608 1
0.5%
14897 1
0.5%
15032 1
0.5%
15168 1
0.5%
15172 1
0.5%
15279 1
0.5%
ValueCountFrequency (%)
1123080060002 1
0.5%
1123080020012 1
0.5%
1123077050003 1
0.5%
1123077050001 1
0.5%
1123077020002 1
0.5%
1123076020001 1
0.5%
1123075010002 1
0.5%
1123072010011 1
0.5%
1123071030015 1
0.5%
1123068020003 1
0.5%
Distinct7
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
초등자녀가구
39 
중고등 자녀가구
36 
신혼 및 영유아 자녀가구
34 
노인부부가구
33 
성인자녀 및 부모부양가구
31 
Other values (2)
27 

Length

Max length13
Median length8
Mean length8.365
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중고등 자녀가구
2nd row노인부부가구
3rd row중고등 자녀가구
4th row중고등 자녀가구
5th row노인부부가구

Common Values

ValueCountFrequency (%)
초등자녀가구 39
19.5%
중고등 자녀가구 36
18.0%
신혼 및 영유아 자녀가구 34
17.0%
노인부부가구 33
16.5%
성인자녀 및 부모부양가구 31
15.5%
일반가구 23
11.5%
1인가구 4
 
2.0%

Length

2023-12-10T15:48:14.224660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:48:14.344704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
자녀가구 70
17.5%
65
16.2%
초등자녀가구 39
9.8%
중고등 36
9.0%
신혼 34
8.5%
영유아 34
8.5%
노인부부가구 33
8.2%
성인자녀 31
7.8%
부모부양가구 31
7.8%
일반가구 23
 
5.8%

식료품음료수지출금액
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0284772 × 108
Minimum116722
Maximum1.0430714 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:14.778687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum116722
5-th percentile233423
Q11508175.5
median8122737
Q31.2367749 × 108
95-th percentile4.8179555 × 108
Maximum1.0430714 × 109
Range1.0429547 × 109
Interquartile range (IQR)1.2216931 × 108

Descriptive statistics

Standard deviation1.8582098 × 108
Coefficient of variation (CV)1.8067583
Kurtosis7.043938
Mean1.0284772 × 108
Median Absolute Deviation (MAD)7564578.5
Skewness2.5401854
Sum2.0569544 × 1010
Variance3.4529436 × 1016
MonotonicityNot monotonic
2023-12-10T15:48:14.919688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
815584 4
 
2.0%
116722 4
 
2.0%
194609 3
 
1.5%
86374280 3
 
1.5%
583610 2
 
1.0%
1517386 2
 
1.0%
233024 2
 
1.0%
2595831 2
 
1.0%
172982004 2
 
1.0%
1049418 2
 
1.0%
Other values (157) 174
87.0%
ValueCountFrequency (%)
116722 4
2.0%
194609 3
1.5%
227776 1
 
0.5%
233024 2
1.0%
233444 2
1.0%
341664 2
1.0%
350166 1
 
0.5%
466048 1
 
0.5%
466888 1
 
0.5%
569440 1
 
0.5%
ValueCountFrequency (%)
1043071425 1
0.5%
971694306 1
0.5%
762366272 1
0.5%
737448624 1
0.5%
712736739 1
0.5%
703656558 1
0.5%
624693465 1
0.5%
567109026 2
1.0%
562051710 1
0.5%
477571545 1
0.5%

주류담배지출금액
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9135534.1
Minimum11479
Maximum86479786
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:15.093812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11479
5-th percentile22958
Q1128718
median668493
Q310401062
95-th percentile46407409
Maximum86479786
Range86468307
Interquartile range (IQR)10272344

Descriptive statistics

Standard deviation16414004
Coefficient of variation (CV)1.7967208
Kurtosis6.7335266
Mean9135534.1
Median Absolute Deviation (MAD)630928.5
Skewness2.5016015
Sum1.8271068 × 109
Variance2.6941954 × 1014
MonotonicityNot monotonic
2023-12-10T15:48:15.248745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
62097 4
 
2.0%
11479 4
 
2.0%
22746 3
 
1.5%
8494460 3
 
1.5%
57395 2
 
1.0%
149227 2
 
1.0%
17742 2
 
1.0%
478275 2
 
1.0%
17011878 2
 
1.0%
54558 2
 
1.0%
Other values (157) 174
87.0%
ValueCountFrequency (%)
11479 4
2.0%
17742 2
1.0%
22746 3
1.5%
22958 2
1.0%
25838 1
 
0.5%
34437 1
 
0.5%
35484 1
 
0.5%
36372 1
 
0.5%
38757 2
1.0%
45465 1
 
0.5%
ValueCountFrequency (%)
86479786 1
0.5%
86085450 1
0.5%
80194644 1
0.5%
60862176 1
0.5%
58822686 1
0.5%
58073292 1
0.5%
55181796 1
0.5%
51556410 1
0.5%
46803924 2
1.0%
46386540 1
0.5%

의류신발지출금액
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41969299
Minimum49625
Maximum4.342206 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:15.415449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum49625
5-th percentile111928.4
Q1595500
median3139534
Q345964999
95-th percentile2.0056685 × 108
Maximum4.342206 × 108
Range4.3417098 × 108
Interquartile range (IQR)45369499

Descriptive statistics

Standard deviation78648612
Coefficient of variation (CV)1.8739558
Kurtosis7.9281262
Mean41969299
Median Absolute Deviation (MAD)2981828.5
Skewness2.7030801
Sum8.3938599 × 109
Variance6.1856041 × 1015
MonotonicityNot monotonic
2023-12-10T15:48:15.598729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
391916 4
 
2.0%
49625 4
 
2.0%
78522 3
 
1.5%
36722500 3
 
1.5%
248125 2
 
1.0%
645125 2
 
1.0%
111976 2
 
1.0%
4313190 2
 
1.0%
73544250 2
 
1.0%
166536 2
 
1.0%
Other values (157) 174
87.0%
ValueCountFrequency (%)
49625 4
2.0%
78522 3
1.5%
99250 2
1.0%
111024 1
 
0.5%
111976 2
1.0%
119076 1
 
0.5%
138780 1
 
0.5%
148875 1
 
0.5%
166536 2
1.0%
178614 2
1.0%
ValueCountFrequency (%)
434220600 1
0.5%
404506992 1
0.5%
398547372 1
0.5%
306992768 1
0.5%
296705448 1
0.5%
292925456 1
0.5%
260053880 1
0.5%
236082032 2
1.0%
233976720 1
0.5%
198808440 1
0.5%

주거비수도비광열비지출금액
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68376290
Minimum90856
Maximum6.569937 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:15.791934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum90856
5-th percentile181407.4
Q11128715.5
median4949973
Q388019580
95-th percentile3.2789961 × 108
Maximum6.569937 × 108
Range6.5690284 × 108
Interquartile range (IQR)86890864

Descriptive statistics

Standard deviation1.2055919 × 108
Coefficient of variation (CV)1.7631724
Kurtosis6.807001
Mean68376290
Median Absolute Deviation (MAD)4686543
Skewness2.4887238
Sum1.3675258 × 1010
Variance1.4534518 × 1016
MonotonicityNot monotonic
2023-12-10T15:48:15.947207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
580440 4
 
2.0%
90856 4
 
2.0%
134594 3
 
1.5%
67233440 3
 
1.5%
454280 2
 
1.0%
1181128 2
 
1.0%
165840 2
 
1.0%
3014214 2
 
1.0%
134648592 2
 
1.0%
547194 2
 
1.0%
Other values (157) 174
87.0%
ValueCountFrequency (%)
90856 4
2.0%
134594 3
1.5%
165840 2
1.0%
175620 1
 
0.5%
181712 2
1.0%
263430 2
1.0%
272568 1
 
0.5%
331680 1
 
0.5%
363424 1
 
0.5%
364796 1
 
0.5%
ValueCountFrequency (%)
656993700 1
0.5%
612035784 1
0.5%
587800140 1
0.5%
464492736 1
0.5%
448927596 1
0.5%
443208312 1
0.5%
393472260 1
0.5%
357201864 2
1.0%
354016440 1
0.5%
326525044 1
0.5%

가정용품가사서비스지출금액
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35247342
Minimum40418
Maximum3.876964 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:16.146265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40418
5-th percentile80836
Q1500460
median2840173.5
Q337696712
95-th percentile1.6204243 × 108
Maximum3.876964 × 108
Range3.8765598 × 108
Interquartile range (IQR)37196252

Descriptive statistics

Standard deviation62101925
Coefficient of variation (CV)1.7618896
Kurtosis7.3025037
Mean35247342
Median Absolute Deviation (MAD)2648160
Skewness2.4568208
Sum7.0494683 × 109
Variance3.8566491 × 1015
MonotonicityNot monotonic
2023-12-10T15:48:16.325161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
234766 4
 
2.0%
40418 4
 
2.0%
62325 3
 
1.5%
29909320 3
 
1.5%
202090 2
 
1.0%
525434 2
 
1.0%
67076 2
 
1.0%
806820 2
 
1.0%
59899476 2
 
1.0%
366474 2
 
1.0%
Other values (157) 174
87.0%
ValueCountFrequency (%)
40418 4
2.0%
62325 3
1.5%
67076 2
1.0%
80836 2
1.0%
115834 1
 
0.5%
121254 1
 
0.5%
134152 1
 
0.5%
161672 1
 
0.5%
173751 2
1.0%
186975 1
 
0.5%
ValueCountFrequency (%)
387696398 1
0.5%
298041150 1
0.5%
277646268 1
0.5%
210714272 1
0.5%
203653242 1
0.5%
201058724 1
0.5%
178789779 2
1.0%
178496270 1
0.5%
162042428 2
1.0%
160597380 1
0.5%

보건지출금액
Real number (ℝ)

HIGH CORRELATION 

Distinct167
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60562449
Minimum55959
Maximum6.2539455 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:48:16.495882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum55959
5-th percentile121838
Q1819724
median4687177.5
Q367124616
95-th percentile2.9210901 × 108
Maximum6.2539455 × 108
Range6.2533859 × 108
Interquartile range (IQR)66304892

Descriptive statistics

Standard deviation1.1184641 × 108
Coefficient of variation (CV)1.8467947
Kurtosis7.1691234
Mean60562449
Median Absolute Deviation (MAD)4425442
Skewness2.5761575
Sum1.211249 × 1010
Variance1.250962 × 1016
MonotonicityNot monotonic
2023-12-10T15:48:16.640769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
426433 4
 
2.0%
55959 4
 
2.0%
119434 3
 
1.5%
41409660 3
 
1.5%
279795 2
 
1.0%
727467 2
 
1.0%
121838 2
 
1.0%
1783110 2
 
1.0%
82931238 2
 
1.0%
598494 2
 
1.0%
Other values (157) 174
87.0%
ValueCountFrequency (%)
55959 4
2.0%
111918 2
1.0%
119434 3
1.5%
121838 2
1.0%
142438 1
 
0.5%
167877 1
 
0.5%
213657 2
1.0%
223836 1
 
0.5%
243676 1
 
0.5%
279795 2
1.0%
ValueCountFrequency (%)
625394550 1
0.5%
582598956 1
0.5%
476739986 1
0.5%
442152224 1
0.5%
427335714 1
0.5%
421891508 1
0.5%
374547590 1
0.5%
340021676 2
1.0%
336989460 1
0.5%
289746884 1
0.5%

Interactions

2023-12-10T15:48:09.144770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:49.630538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:51.026808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:52.412945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:53.768584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:55.395376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:57.062318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:58.504435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:59.823808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:01.317058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:02.684684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:04.397774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:06.157831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:07.731669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:09.234488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:49.742688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:51.105268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:52.507672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:53.873485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:55.498060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:57.168440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:58.589038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:59.911228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:01.405883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:03.067408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:04.501999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:06.302702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:07.825014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:09.322235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:49.828715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:51.212662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:52.609626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:53.978163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:55.584678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:57.265612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:58.684541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:59.993852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:01.484919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:03.159071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:04.611914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:06.418864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:07.912049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:09.411773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:49.913734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:51.302505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:52.713708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:54.077338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:55.674278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:57.370426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:58.786373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:00.106453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:01.578233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:03.267910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:04.737152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:06.531789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:08.008536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:09.514580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:50.033261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:51.410635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:52.828455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:54.188010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:55.774879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:57.481889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:58.887750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:00.230283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:01.694698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:03.377882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:04.849462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:06.642372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:08.100636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:09.605739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:50.129253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:51.486380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:52.920016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:54.286661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:55.882962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:57.573358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:58.971487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:00.329932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:01.796084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:03.473785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:04.970335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:06.733744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:08.189236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:09.983106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:50.219751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:51.580520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:53.010395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:54.424685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:55.987938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:57.674636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:59.070217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:00.448572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:01.913075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:03.577240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:05.108147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:06.859956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:08.306069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:10.055935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:50.308671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:51.687251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:53.101018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:54.559866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:56.060895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:57.761044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:59.153675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:00.579216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:01.994367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:03.662277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:05.210090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:06.950450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:08.386890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:10.166130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:50.396990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:51.779560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:53.207282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:54.688329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:56.441533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:57.884465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:59.243515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:00.681428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:02.094913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:03.750084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:05.340640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:07.036743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:08.500739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:10.252783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:50.487024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:51.875286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:53.296491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:54.805793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:56.553817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:57.996674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:59.343892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:00.762637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:02.191773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:03.846590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:05.493946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:07.135540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:08.605063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:10.328265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:50.575104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:51.973312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:53.397405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:54.900907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:56.646017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:58.108020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:59.453864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:00.872138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:02.291054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:03.943949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:05.623695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:07.242177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:08.686200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:10.429980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:50.672094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:52.065011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:53.486249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:55.017311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:56.738639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:58.196540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:59.537748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:00.962632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:02.389829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:04.057225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:05.743694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:07.334993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:08.786429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:10.535460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:50.771351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:52.165481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:53.573855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:55.162938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:56.841699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:58.295297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:59.624337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:01.081819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:02.486847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:04.169995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:05.865547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:07.482339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:08.911319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:10.633681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:50.912776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:52.281480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:53.673799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:55.286281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:56.965800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:58.407840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:47:59.715221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:01.209435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:02.597197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:04.295781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:06.016952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:07.622728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:48:09.022666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T15:48:16.768474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집계영역구분코드교통지출금액통신지출금액오락문화지출금액교육지출금액음식숙박지출금액기타상품서비스지출금액비소비지출지출금액집계영역코드가구생애주기명식료품음료수지출금액주류담배지출금액의류신발지출금액주거비수도비광열비지출금액가정용품가사서비스지출금액보건지출금액
집계영역구분코드1.0000.7320.5000.5790.6050.5620.5680.5411.0000.1660.5740.5950.5620.6280.6990.549
교통지출금액0.7321.0000.9320.9390.8910.9520.9600.9090.5170.3970.9080.9480.9550.9460.9750.908
통신지출금액0.5000.9321.0000.9760.9170.9910.9880.9910.3450.4050.9880.9850.9910.9550.9140.990
오락문화지출금액0.5790.9390.9761.0000.8960.9790.9820.9730.3970.3670.9730.9800.9760.9370.9600.971
교육지출금액0.6050.8910.9170.8961.0000.9210.9160.8980.5180.3860.8960.9040.9210.9820.8980.902
음식숙박지출금액0.5620.9520.9910.9790.9211.0000.9960.9840.3840.3680.9870.9941.0000.9740.9070.987
기타상품서비스지출금액0.5680.9600.9880.9820.9160.9961.0000.9800.3970.3810.9830.9940.9960.9640.9240.986
비소비지출지출금액0.5410.9090.9910.9730.8980.9840.9801.0000.3690.4110.9900.9910.9830.9400.9090.992
집계영역코드1.0000.5170.3450.3970.5180.3840.3970.3691.0000.0690.4090.3960.3840.5570.4920.384
가구생애주기명0.1660.3970.4050.3670.3860.3680.3810.4110.0691.0000.3520.3850.3650.3510.3610.383
식료품음료수지출금액0.5740.9080.9880.9730.8960.9870.9830.9900.4090.3521.0000.9820.9880.9640.9360.999
주류담배지출금액0.5950.9480.9850.9800.9040.9940.9940.9910.3960.3850.9821.0000.9930.9510.9000.981
의류신발지출금액0.5620.9550.9910.9760.9211.0000.9960.9830.3840.3650.9880.9931.0000.9740.9030.988
주거비수도비광열비지출금액0.6280.9460.9550.9370.9820.9740.9640.9400.5570.3510.9640.9510.9741.0000.9490.972
가정용품가사서비스지출금액0.6990.9750.9140.9600.8980.9070.9240.9090.4920.3610.9360.9000.9030.9491.0000.938
보건지출금액0.5490.9080.9900.9710.9020.9870.9860.9920.3840.3830.9990.9810.9880.9720.9381.000
2023-12-10T15:48:16.967835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집계영역구분코드가구생애주기명
집계영역구분코드1.0000.113
가구생애주기명0.1131.000
2023-12-10T15:48:17.083108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
교통지출금액통신지출금액오락문화지출금액교육지출금액음식숙박지출금액기타상품서비스지출금액비소비지출지출금액집계영역코드식료품음료수지출금액주류담배지출금액의류신발지출금액주거비수도비광열비지출금액가정용품가사서비스지출금액보건지출금액집계영역구분코드가구생애주기명
교통지출금액1.0000.9940.9930.8710.9960.9900.9940.1670.9770.9950.9940.9880.9800.9780.4000.224
통신지출금액0.9941.0000.9960.8780.9990.9920.9970.1560.9830.9920.9980.9910.9800.9830.3410.229
오락문화지출금액0.9930.9961.0000.8480.9970.9970.9960.1670.9890.9970.9960.9970.9900.9900.4080.205
교육지출금액0.8710.8780.8481.0000.8790.8280.8570.0980.7990.8320.8800.8260.7920.7920.4030.206
음식숙박지출금액0.9960.9990.9970.8791.0000.9930.9970.1620.9820.9930.9980.9910.9810.9820.3940.205
기타상품서비스지출금액0.9900.9920.9970.8280.9931.0000.9960.1740.9950.9970.9890.9980.9960.9960.3980.215
비소비지출지출금액0.9940.9970.9960.8570.9970.9961.0000.1760.9880.9960.9950.9940.9850.9890.3760.234
집계영역코드0.1670.1560.1670.0980.1620.1740.1761.0000.1820.1770.1590.1820.1760.1760.9950.071
식료품음료수지출금액0.9770.9830.9890.7990.9820.9950.9880.1821.0000.9900.9770.9970.9950.9990.4040.196
주류담배지출금액0.9950.9920.9970.8320.9930.9970.9960.1770.9901.0000.9920.9960.9910.9910.4220.216
의류신발지출금액0.9940.9980.9960.8800.9980.9890.9950.1590.9770.9921.0000.9890.9760.9780.3940.203
주거비수도비광열비지출금액0.9880.9910.9970.8260.9910.9980.9940.1820.9970.9960.9891.0000.9950.9960.4250.186
가정용품가사서비스지출금액0.9800.9800.9900.7920.9810.9960.9850.1760.9950.9910.9760.9951.0000.9960.3730.205
보건지출금액0.9780.9830.9900.7920.9820.9960.9890.1760.9990.9910.9780.9960.9961.0000.3820.216
집계영역구분코드0.4000.3410.4080.4030.3940.3980.3760.9950.4040.4220.3940.4250.3730.3821.0000.113
가구생애주기명0.2240.2290.2050.2060.2050.2150.2340.0710.1960.2160.2030.1860.2050.2160.1131.000

Missing values

2023-12-10T15:48:10.773962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T15:48:11.057562image/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

집계영역구분코드집계기준년도교통지출금액통신지출금액오락문화지출금액교육지출금액음식숙박지출금액기타상품서비스지출금액비소비지출지출금액집계영역코드가구생애주기명식료품음료수지출금액주류담배지출금액의류신발지출금액주거비수도비광열비지출금액가정용품가사서비스지출금액보건지출금액
0120215986823533394273081218329858361484925194070816159중고등 자녀가구81558462097391916580440234766426433
13202118677018540401585947454082130876238570261291561116069020009노인부부가구5771799300069915948300956720156073291717
23202129934101766695213654060916454291805242462597035401123058020003중고등 자녀가구40779203104851959580290220011738302132165
3120215131563028623662641044282735738415650166346415560중고등 자녀가구69907253226335928497520201228365514
43202119242988799201634006467842195448245799663148881109075020023노인부부가구5946702309162943704310076620766863391466
52202192625800301505604260698096595160810529404907532018874884011680700초등자녀가구86374280849446036722500672334402990932041409660
612021150204048892869092415664081314372795816306079217374초등자녀가구14006641377485955001090272485016671508
72202190247570293764244151301794115014789718514781527818390258611500630초등자녀가구84156562827635935779625655071762914137840346439
822021483309970242654120238618108193121694509558850327143936127691426611500520성인자녀 및 부모부양가구56710902646803924236082032357201864162042428340021676
9120216829102270553676452372556462454436751389610265803신혼 및 영유아 자녀가구56944064595297690439050289585356095
집계영역구분코드집계기준년도교통지출금액통신지출금액오락문화지출금액교육지출금액음식숙박지출금액기타상품서비스지출금액비소비지출지출금액집계영역코드가구생애주기명식료품음료수지출금액주류담배지출금액의류신발지출금액주거비수도비광열비지출금액가정용품가사서비스지출금액보건지출금액
1901202140974613623322058714235338774726620583376633502신혼 및 영유아 자녀가구34166438757178614263430173751213657
1911202159868235333942730812183298583614849251940708266641중고등 자녀가구81558462097391916580440234766426433
1921202147997952409820236973819179095060475324889612681151220829성인자녀 및 부모부양가구56320114648142344552354740416092583376786
1933202112451345693601057298302721420584159046840861041116067020041노인부부가구3847866200046610632200637813437382194478
194320216671028393720647614321357566695645945403450216250321123058030001중고등 자녀가구90879366919384367064646776026159644751682
195220212058424665450769190518305725217583174135653506161599811680750일반가구206285542411076832333214266964660645012660004
19612021587730295080290172234846619650397824155279433535성인자녀 및 부모부양가구68963456916287088434376197052413484
1973202111754600590160058034404696920123930007956480310558801123075010002성인자녀 및 부모부양가구1379268011383205741760868752039410408269680
198120214097460136233022058701423530387747026620508337660220205신혼 및 영유아 자녀가구34166403875701786140263430017375102136570
1991202151315630286236626410442827357384156501663464275563중고등 자녀가구69907253226335928497520201228365514

Duplicate rows

Most frequently occurring

집계영역구분코드집계기준년도교통지출금액통신지출금액오락문화지출금액교육지출금액음식숙박지출금액기타상품서비스지출금액비소비지출지출금액집계영역코드가구생애주기명식료품음료수지출금액주류담배지출금액의류신발지출금액주거비수도비광열비지출금액가정용품가사서비스지출금액보건지출금액# duplicates
22202192625800301505604260698096595160810529404907532018874884011680700초등자녀가구863742808494460367225006723344029909320414096603
022021350185513762353052266825741361124416385467039221115005401인가구25958314782754313190301421480682017831102
12202167341460219202723097642670227292589276783567908413722550811305535초등자녀가구627964366175702266982504888052821744884301059422
3220211132788503687332052107185118133270991255556001779023083473011500590초등자녀가구10563341010388495449106258222468036578290506428952
42202118550194060382608853291141934513881623249429828327637800781211500611초등자녀가구172982004170118787354425013464859259899476829312382
522021191487964636662221030876586652630218120709812440647038964664411305645신혼 및 영유아 자녀가구159670976181124388347227612310962081199634998490382
622021276578550919572751488962259608827526172922517968837556279205011305534신혼 및 영유아 자녀가구230623200261609751205644501778152501172819251442184752
72202142162863414018375722698402314648123739899166327392494585794521411500615신혼 및 영유아 자녀가구351572256398809531837938062710694701787897792198530532
822021483309970242654120238618108193121694509558850327143936127691426611500520성인자녀 및 부모부양가구567109026468039242360820323572018641620424283400216762
93202129934101766695213654060916454291805242462597035401123058020003중고등 자녀가구407792031048519595802902200117383021321652