Overview

Dataset statistics

Number of variables20
Number of observations728
Missing cells550
Missing cells (%)3.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory125.2 KiB
Average record size in memory176.2 B

Variable types

Numeric14
Categorical4
DateTime2

Dataset

Description부산광역시 상수도사업본부에서 상하수도 요금 계산 및 징수를 위해 운영하는 수용가정보시스템에 사용되는 복지사각지대 자료 제공 통계자료입니다.(자료제공년월, 자료회차, 전월 사용량 등)사용량의 단위는 톤입니다.
Author부산광역시 상수도사업본부
URLhttps://www.data.go.kr/data/15100343/fileData.do

Alerts

자료회차 has constant value ""Constant
자료접수기관코드 has constant value ""Constant
자료처리일자 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
자료제공년월 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 자료제공년월 and 1 other fieldsHigh correlation
전월사용량 is highly overall correlated with 3개월전사용량 and 4 other fieldsHigh correlation
2개월전사용량 is highly overall correlated with 4개월전사용량 and 4 other fieldsHigh correlation
3개월전사용량 is highly overall correlated with 전월사용량 and 4 other fieldsHigh correlation
4개월전사용량 is highly overall correlated with 2개월전사용량 and 4 other fieldsHigh correlation
5개월전사용량 is highly overall correlated with 전월사용량 and 4 other fieldsHigh correlation
6개월전사용량 is highly overall correlated with 2개월전사용량 and 4 other fieldsHigh correlation
7개월전사용량 is highly overall correlated with 전월사용량 and 4 other fieldsHigh correlation
8개월전사용량 is highly overall correlated with 2개월전사용량 and 4 other fieldsHigh correlation
9개월전사용량 is highly overall correlated with 전월사용량 and 4 other fieldsHigh correlation
10개월전사용량 is highly overall correlated with 2개월전사용량 and 4 other fieldsHigh correlation
11개월전사용량 is highly overall correlated with 전월사용량 and 4 other fieldsHigh correlation
12개월전사용량 is highly overall correlated with 2개월전사용량 and 4 other fieldsHigh correlation
정수종료일 has 550 (75.5%) missing valuesMissing
4개월전사용량 is highly skewed (γ1 = 25.14977004)Skewed
연번 has unique valuesUnique
전월사용량 has 620 (85.2%) zerosZeros
2개월전사용량 has 594 (81.6%) zerosZeros
3개월전사용량 has 587 (80.6%) zerosZeros
4개월전사용량 has 574 (78.8%) zerosZeros
5개월전사용량 has 572 (78.6%) zerosZeros
6개월전사용량 has 560 (76.9%) zerosZeros
7개월전사용량 has 546 (75.0%) zerosZeros
8개월전사용량 has 527 (72.4%) zerosZeros
9개월전사용량 has 524 (72.0%) zerosZeros
10개월전사용량 has 514 (70.6%) zerosZeros
11개월전사용량 has 515 (70.7%) zerosZeros
12개월전사용량 has 498 (68.4%) zerosZeros

Reproduction

Analysis started2024-03-14 11:33:56.443231
Analysis finished2024-03-14 11:34:48.252276
Duration51.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct728
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean364.5
Minimum1
Maximum728
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:48.430151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile37.35
Q1182.75
median364.5
Q3546.25
95-th percentile691.65
Maximum728
Range727
Interquartile range (IQR)363.5

Descriptive statistics

Standard deviation210.29979
Coefficient of variation (CV)0.57695415
Kurtosis-1.2
Mean364.5
Median Absolute Deviation (MAD)182
Skewness0
Sum265356
Variance44226
MonotonicityStrictly increasing
2024-03-14T20:34:48.689479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
480 1
 
0.1%
482 1
 
0.1%
483 1
 
0.1%
484 1
 
0.1%
485 1
 
0.1%
486 1
 
0.1%
487 1
 
0.1%
488 1
 
0.1%
489 1
 
0.1%
Other values (718) 718
98.6%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
728 1
0.1%
727 1
0.1%
726 1
0.1%
725 1
0.1%
724 1
0.1%
723 1
0.1%
722 1
0.1%
721 1
0.1%
720 1
0.1%
719 1
0.1%

자료제공년월
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-11
147 
2023-03
142 
2023-09
133 
2023-07
126 
2023-05
126 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09
2nd row2023-09
3rd row2023-09
4th row2023-09
5th row2023-09

Common Values

ValueCountFrequency (%)
2023-11 147
20.2%
2023-03 142
19.5%
2023-09 133
18.3%
2023-07 126
17.3%
2023-05 126
17.3%
2023-01 54
 
7.4%

Length

2024-03-14T20:34:49.043012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:34:49.398924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11 147
20.2%
2023-03 142
19.5%
2023-09 133
18.3%
2023-07 126
17.3%
2023-05 126
17.3%
2023-01 54
 
7.4%

자료회차
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
1
728 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 728
100.0%

Length

2024-03-14T20:34:49.696256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:34:49.864692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 728
100.0%

자료순번
Real number (ℝ)

Distinct147
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.149725
Minimum1
Maximum147
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:50.054020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q131
median62.5
Q399
95-th percentile129
Maximum147
Range146
Interquartile range (IQR)68

Descriptive statistics

Standard deviation39.612196
Coefficient of variation (CV)0.60801786
Kurtosis-1.1468636
Mean65.149725
Median Absolute Deviation (MAD)33.5
Skewness0.15058963
Sum47429
Variance1569.1261
MonotonicityNot monotonic
2024-03-14T20:34:50.315493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54 6
 
0.8%
20 6
 
0.8%
18 6
 
0.8%
17 6
 
0.8%
16 6
 
0.8%
15 6
 
0.8%
14 6
 
0.8%
13 6
 
0.8%
12 6
 
0.8%
11 6
 
0.8%
Other values (137) 668
91.8%
ValueCountFrequency (%)
1 6
0.8%
2 6
0.8%
3 6
0.8%
4 6
0.8%
5 6
0.8%
6 6
0.8%
7 6
0.8%
8 6
0.8%
9 6
0.8%
10 6
0.8%
ValueCountFrequency (%)
147 1
0.1%
146 1
0.1%
145 1
0.1%
144 1
0.1%
143 1
0.1%
142 2
0.3%
141 2
0.3%
140 2
0.3%
139 2
0.3%
138 2
0.3%

자료접수기관코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
6260095
728 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6260095
2nd row6260095
3rd row6260095
4th row6260095
5th row6260095

Common Values

ValueCountFrequency (%)
6260095 728
100.0%

Length

2024-03-14T20:34:50.561481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:34:50.820201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6260095 728
100.0%
Distinct197
Distinct (%)27.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
Minimum2022-12-01 00:00:00
Maximum2023-11-29 00:00:00
2024-03-14T20:34:51.004975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:51.249993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

정수종료일
Date

MISSING 

Distinct120
Distinct (%)67.4%
Missing550
Missing (%)75.5%
Memory size5.8 KiB
Minimum2022-12-05 00:00:00
Maximum2023-12-08 00:00:00
2024-03-14T20:34:51.492676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:51.735775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전월사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct66
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.197802
Minimum0
Maximum1838
Zeros620
Zeros (%)85.2%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:52.067498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile42.65
Maximum1838
Range1838
Interquartile range (IQR)0

Descriptive statistics

Standard deviation99.330977
Coefficient of variation (CV)6.5358778
Kurtosis178.92929
Mean15.197802
Median Absolute Deviation (MAD)0
Skewness11.849391
Sum11064
Variance9866.6431
MonotonicityNot monotonic
2024-03-14T20:34:52.323292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 620
85.2%
1 11
 
1.5%
4 6
 
0.8%
3 4
 
0.5%
6 4
 
0.5%
12 3
 
0.4%
5 3
 
0.4%
2 3
 
0.4%
48 2
 
0.3%
30 2
 
0.3%
Other values (56) 70
 
9.6%
ValueCountFrequency (%)
0 620
85.2%
1 11
 
1.5%
2 3
 
0.4%
3 4
 
0.5%
4 6
 
0.8%
5 3
 
0.4%
6 4
 
0.5%
7 2
 
0.3%
8 2
 
0.3%
9 2
 
0.3%
ValueCountFrequency (%)
1838 1
0.1%
990 1
0.1%
731 1
0.1%
637 1
0.1%
618 1
0.1%
550 2
0.3%
509 1
0.1%
451 1
0.1%
324 1
0.1%
278 1
0.1%

2개월전사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct60
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.502747
Minimum0
Maximum984
Zeros594
Zeros (%)81.6%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:52.590669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile28.3
Maximum984
Range984
Interquartile range (IQR)0

Descriptive statistics

Standard deviation65.687518
Coefficient of variation (CV)6.2543177
Kurtosis113.98375
Mean10.502747
Median Absolute Deviation (MAD)0
Skewness9.9725782
Sum7646
Variance4314.8501
MonotonicityNot monotonic
2024-03-14T20:34:52.971086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 594
81.6%
1 20
 
2.7%
3 12
 
1.6%
2 8
 
1.1%
10 5
 
0.7%
8 5
 
0.7%
9 4
 
0.5%
14 4
 
0.5%
7 4
 
0.5%
5 3
 
0.4%
Other values (50) 69
 
9.5%
ValueCountFrequency (%)
0 594
81.6%
1 20
 
2.7%
2 8
 
1.1%
3 12
 
1.6%
4 1
 
0.1%
5 3
 
0.4%
6 3
 
0.4%
7 4
 
0.5%
8 5
 
0.7%
9 4
 
0.5%
ValueCountFrequency (%)
984 1
0.1%
725 1
0.1%
659 1
0.1%
632 1
0.1%
418 1
0.1%
387 1
0.1%
380 1
0.1%
290 1
0.1%
283 1
0.1%
262 1
0.1%

3개월전사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct74
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.196429
Minimum0
Maximum1234
Zeros587
Zeros (%)80.6%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:53.309914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile63
Maximum1234
Range1234
Interquartile range (IQR)0

Descriptive statistics

Standard deviation87.611379
Coefficient of variation (CV)5.0947427
Kurtosis96.404736
Mean17.196429
Median Absolute Deviation (MAD)0
Skewness8.8722115
Sum12519
Variance7675.7537
MonotonicityNot monotonic
2024-03-14T20:34:53.569484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 587
80.6%
1 14
 
1.9%
2 8
 
1.1%
3 6
 
0.8%
5 5
 
0.7%
17 5
 
0.7%
6 3
 
0.4%
10 3
 
0.4%
4 3
 
0.4%
36 3
 
0.4%
Other values (64) 91
 
12.5%
ValueCountFrequency (%)
0 587
80.6%
1 14
 
1.9%
2 8
 
1.1%
3 6
 
0.8%
4 3
 
0.4%
5 5
 
0.7%
6 3
 
0.4%
8 2
 
0.3%
9 2
 
0.3%
10 3
 
0.4%
ValueCountFrequency (%)
1234 1
0.1%
1095 1
0.1%
703 1
0.1%
654 1
0.1%
587 1
0.1%
505 1
0.1%
459 1
0.1%
429 1
0.1%
383 1
0.1%
366 1
0.1%

4개월전사용량
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct66
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.684066
Minimum0
Maximum10764
Zeros574
Zeros (%)78.8%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:53.830146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile40
Maximum10764
Range10764
Interquartile range (IQR)0

Descriptive statistics

Standard deviation408.55259
Coefficient of variation (CV)14.243189
Kurtosis658.58226
Mean28.684066
Median Absolute Deviation (MAD)0
Skewness25.14977
Sum20882
Variance166915.22
MonotonicityNot monotonic
2024-03-14T20:34:54.083302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 574
78.8%
1 27
 
3.7%
3 9
 
1.2%
12 7
 
1.0%
4 6
 
0.8%
9 6
 
0.8%
10 6
 
0.8%
15 5
 
0.7%
2 4
 
0.5%
11 4
 
0.5%
Other values (56) 80
 
11.0%
ValueCountFrequency (%)
0 574
78.8%
1 27
 
3.7%
2 4
 
0.5%
3 9
 
1.2%
4 6
 
0.8%
5 1
 
0.1%
6 1
 
0.1%
7 3
 
0.4%
8 3
 
0.4%
9 6
 
0.8%
ValueCountFrequency (%)
10764 1
0.1%
1655 1
0.1%
890 1
0.1%
849 1
0.1%
674 1
0.1%
668 1
0.1%
447 1
0.1%
349 1
0.1%
281 1
0.1%
277 1
0.1%

5개월전사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct86
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.924451
Minimum0
Maximum863
Zeros572
Zeros (%)78.6%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:54.413639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile72.6
Maximum863
Range863
Interquartile range (IQR)0

Descriptive statistics

Standard deviation81.406082
Coefficient of variation (CV)4.5416222
Kurtosis58.559967
Mean17.924451
Median Absolute Deviation (MAD)0
Skewness7.1601098
Sum13049
Variance6626.9503
MonotonicityNot monotonic
2024-03-14T20:34:54.655798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 572
78.6%
1 18
 
2.5%
5 8
 
1.1%
2 6
 
0.8%
3 6
 
0.8%
20 4
 
0.5%
10 4
 
0.5%
14 4
 
0.5%
6 4
 
0.5%
12 3
 
0.4%
Other values (76) 99
 
13.6%
ValueCountFrequency (%)
0 572
78.6%
1 18
 
2.5%
2 6
 
0.8%
3 6
 
0.8%
4 2
 
0.3%
5 8
 
1.1%
6 4
 
0.5%
7 2
 
0.3%
8 2
 
0.3%
9 2
 
0.3%
ValueCountFrequency (%)
863 1
0.1%
809 1
0.1%
755 1
0.1%
745 2
0.3%
493 1
0.1%
475 1
0.1%
419 1
0.1%
356 1
0.1%
338 1
0.1%
325 1
0.1%

6개월전사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct76
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.913462
Minimum0
Maximum929
Zeros560
Zeros (%)76.9%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:55.096483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile55.65
Maximum929
Range929
Interquartile range (IQR)0

Descriptive statistics

Standard deviation66.319612
Coefficient of variation (CV)5.135696
Kurtosis101.11251
Mean12.913462
Median Absolute Deviation (MAD)0
Skewness9.3230275
Sum9401
Variance4398.291
MonotonicityNot monotonic
2024-03-14T20:34:55.338668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 560
76.9%
1 15
 
2.1%
2 14
 
1.9%
11 10
 
1.4%
10 8
 
1.1%
4 5
 
0.7%
9 5
 
0.7%
5 5
 
0.7%
6 5
 
0.7%
16 4
 
0.5%
Other values (66) 97
 
13.3%
ValueCountFrequency (%)
0 560
76.9%
1 15
 
2.1%
2 14
 
1.9%
3 3
 
0.4%
4 5
 
0.7%
5 5
 
0.7%
6 5
 
0.7%
7 1
 
0.1%
8 3
 
0.4%
9 5
 
0.7%
ValueCountFrequency (%)
929 1
0.1%
775 1
0.1%
711 1
0.1%
520 1
0.1%
458 1
0.1%
433 1
0.1%
380 1
0.1%
325 1
0.1%
270 1
0.1%
223 1
0.1%

7개월전사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct90
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.072802
Minimum0
Maximum859
Zeros546
Zeros (%)75.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:55.739261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.25
95-th percentile76.65
Maximum859
Range859
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation79.270844
Coefficient of variation (CV)4.1562243
Kurtosis47.297792
Mean19.072802
Median Absolute Deviation (MAD)0
Skewness6.4481451
Sum13885
Variance6283.8668
MonotonicityNot monotonic
2024-03-14T20:34:56.159344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 546
75.0%
1 15
 
2.1%
2 8
 
1.1%
6 7
 
1.0%
14 6
 
0.8%
17 6
 
0.8%
10 6
 
0.8%
16 6
 
0.8%
5 5
 
0.7%
3 5
 
0.7%
Other values (80) 118
 
16.2%
ValueCountFrequency (%)
0 546
75.0%
1 15
 
2.1%
2 8
 
1.1%
3 5
 
0.7%
4 3
 
0.4%
5 5
 
0.7%
6 7
 
1.0%
7 4
 
0.5%
8 4
 
0.5%
9 5
 
0.7%
ValueCountFrequency (%)
859 1
0.1%
719 1
0.1%
643 1
0.1%
618 1
0.1%
614 1
0.1%
499 1
0.1%
497 1
0.1%
460 1
0.1%
458 1
0.1%
450 1
0.1%

8개월전사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct76
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.315934
Minimum0
Maximum731
Zeros527
Zeros (%)72.4%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:56.557055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile56
Maximum731
Range731
Interquartile range (IQR)1

Descriptive statistics

Standard deviation65.327314
Coefficient of variation (CV)4.9059505
Kurtosis78.718167
Mean13.315934
Median Absolute Deviation (MAD)0
Skewness8.4426621
Sum9694
Variance4267.658
MonotonicityNot monotonic
2024-03-14T20:34:56.901870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 527
72.4%
1 27
 
3.7%
3 16
 
2.2%
8 11
 
1.5%
5 9
 
1.2%
4 8
 
1.1%
7 7
 
1.0%
2 7
 
1.0%
10 6
 
0.8%
12 4
 
0.5%
Other values (66) 106
 
14.6%
ValueCountFrequency (%)
0 527
72.4%
1 27
 
3.7%
2 7
 
1.0%
3 16
 
2.2%
4 8
 
1.1%
5 9
 
1.2%
6 4
 
0.5%
7 7
 
1.0%
8 11
 
1.5%
9 4
 
0.5%
ValueCountFrequency (%)
731 1
0.1%
728 1
0.1%
708 1
0.1%
612 1
0.1%
531 1
0.1%
523 1
0.1%
389 1
0.1%
347 1
0.1%
299 1
0.1%
274 1
0.1%

9개월전사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct88
Distinct (%)12.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.67033
Minimum0
Maximum750
Zeros524
Zeros (%)72.0%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:57.160081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile84.6
Maximum750
Range750
Interquartile range (IQR)3

Descriptive statistics

Standard deviation66.220931
Coefficient of variation (CV)3.7475775
Kurtosis51.174265
Mean17.67033
Median Absolute Deviation (MAD)0
Skewness6.4716366
Sum12864
Variance4385.2117
MonotonicityNot monotonic
2024-03-14T20:34:57.421546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 524
72.0%
1 16
 
2.2%
10 9
 
1.2%
6 9
 
1.2%
5 8
 
1.1%
13 7
 
1.0%
4 6
 
0.8%
3 6
 
0.8%
7 6
 
0.8%
28 5
 
0.7%
Other values (78) 132
 
18.1%
ValueCountFrequency (%)
0 524
72.0%
1 16
 
2.2%
2 2
 
0.3%
3 6
 
0.8%
4 6
 
0.8%
5 8
 
1.1%
6 9
 
1.2%
7 6
 
0.8%
8 4
 
0.5%
9 3
 
0.4%
ValueCountFrequency (%)
750 1
0.1%
639 1
0.1%
629 1
0.1%
516 1
0.1%
437 1
0.1%
372 1
0.1%
366 1
0.1%
329 1
0.1%
311 1
0.1%
283 1
0.1%

10개월전사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct86
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.06456
Minimum0
Maximum750
Zeros514
Zeros (%)70.6%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:57.678480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile60
Maximum750
Range750
Interquartile range (IQR)2

Descriptive statistics

Standard deviation72.074392
Coefficient of variation (CV)4.4865462
Kurtosis59.412528
Mean16.06456
Median Absolute Deviation (MAD)0
Skewness7.3241263
Sum11695
Variance5194.718
MonotonicityNot monotonic
2024-03-14T20:34:58.034803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 514
70.6%
1 23
 
3.2%
2 16
 
2.2%
6 12
 
1.6%
5 12
 
1.6%
3 7
 
1.0%
12 7
 
1.0%
4 7
 
1.0%
10 6
 
0.8%
16 5
 
0.7%
Other values (76) 119
 
16.3%
ValueCountFrequency (%)
0 514
70.6%
1 23
 
3.2%
2 16
 
2.2%
3 7
 
1.0%
4 7
 
1.0%
5 12
 
1.6%
6 12
 
1.6%
7 4
 
0.5%
8 5
 
0.7%
9 2
 
0.3%
ValueCountFrequency (%)
750 1
0.1%
728 1
0.1%
705 1
0.1%
624 1
0.1%
601 1
0.1%
483 1
0.1%
477 1
0.1%
459 1
0.1%
392 1
0.1%
342 1
0.1%

11개월전사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct89
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.729396
Minimum0
Maximum850
Zeros515
Zeros (%)70.7%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:58.308762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile93
Maximum850
Range850
Interquartile range (IQR)4

Descriptive statistics

Standard deviation72.559852
Coefficient of variation (CV)3.8741161
Kurtosis51.366627
Mean18.729396
Median Absolute Deviation (MAD)0
Skewness6.4945853
Sum13635
Variance5264.9322
MonotonicityNot monotonic
2024-03-14T20:34:58.551672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 515
70.7%
1 16
 
2.2%
5 9
 
1.2%
12 9
 
1.2%
3 8
 
1.1%
11 8
 
1.1%
7 7
 
1.0%
13 7
 
1.0%
2 6
 
0.8%
17 6
 
0.8%
Other values (79) 137
 
18.8%
ValueCountFrequency (%)
0 515
70.7%
1 16
 
2.2%
2 6
 
0.8%
3 8
 
1.1%
4 5
 
0.7%
5 9
 
1.2%
6 5
 
0.7%
7 7
 
1.0%
8 4
 
0.5%
9 6
 
0.8%
ValueCountFrequency (%)
850 1
0.1%
726 1
0.1%
608 1
0.1%
460 1
0.1%
451 1
0.1%
419 1
0.1%
412 1
0.1%
402 1
0.1%
395 1
0.1%
366 1
0.1%

12개월전사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct82
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.910714
Minimum0
Maximum1032
Zeros498
Zeros (%)68.4%
Negative0
Negative (%)0.0%
Memory size6.5 KiB
2024-03-14T20:34:58.802859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35
95-th percentile62.95
Maximum1032
Range1032
Interquartile range (IQR)5

Descriptive statistics

Standard deviation71.928296
Coefficient of variation (CV)4.8239336
Kurtosis103.16322
Mean14.910714
Median Absolute Deviation (MAD)0
Skewness9.4376837
Sum10855
Variance5173.6798
MonotonicityNot monotonic
2024-03-14T20:34:59.162409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 498
68.4%
1 15
 
2.1%
8 14
 
1.9%
3 13
 
1.8%
5 12
 
1.6%
6 10
 
1.4%
4 9
 
1.2%
9 8
 
1.1%
2 8
 
1.1%
12 7
 
1.0%
Other values (72) 134
 
18.4%
ValueCountFrequency (%)
0 498
68.4%
1 15
 
2.1%
2 8
 
1.1%
3 13
 
1.8%
4 9
 
1.2%
5 12
 
1.6%
6 10
 
1.4%
7 7
 
1.0%
8 14
 
1.9%
9 8
 
1.1%
ValueCountFrequency (%)
1032 1
0.1%
778 1
0.1%
729 1
0.1%
700 1
0.1%
584 1
0.1%
388 1
0.1%
366 1
0.1%
297 1
0.1%
291 1
0.1%
271 1
0.1%

자료처리일자
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
2023-12-13
147 
2023-04-13
142 
2023-10-13
133 
2023-08-13
126 
2023-06-13
126 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-13
2nd row2023-10-13
3rd row2023-10-13
4th row2023-10-13
5th row2023-10-13

Common Values

ValueCountFrequency (%)
2023-12-13 147
20.2%
2023-04-13 142
19.5%
2023-10-13 133
18.3%
2023-08-13 126
17.3%
2023-06-13 126
17.3%
2023-02-13 54
 
7.4%

Length

2024-03-14T20:34:59.393496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:34:59.599183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-13 147
20.2%
2023-04-13 142
19.5%
2023-10-13 133
18.3%
2023-08-13 126
17.3%
2023-06-13 126
17.3%
2023-02-13 54
 
7.4%

Interactions

2024-03-14T20:34:43.199193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:33:57.551706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:01.140760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:04.333988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:07.896288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:11.534086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:15.254287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:18.339274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:21.884435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:26.087390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:29.614339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:32.831947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:35.853825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:39.615967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:43.467185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:33:57.828640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:01.415871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:04.610451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:08.162331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:11.805574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:15.529381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:18.600899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:22.050606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:26.349002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:29.790123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:33.119286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:36.125947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:39.882108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:43.739726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:33:58.107710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:01.695917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:04.890506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:08.431601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:12.085612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:15.701854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:18.865394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:22.347894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:26.613708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:29.964027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:33.294134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:36.401364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:40.156055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:44.010546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:33:58.381007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:01.971112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:05.130483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:08.700917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:12.360916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:15.878397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:19.129424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:22.772951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:26.875461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:30.140016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:33.472568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:36.680189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:40.417773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:44.263013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:33:58.645316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:02.235643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:05.295279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:08.955440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:12.622621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:16.032036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:19.379057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:23.132267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:27.127853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:30.300778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:33.634042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:36.944418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:40.667984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:44.525062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:33:58.913485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:02.503659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:05.501466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:09.214401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:12.886744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:16.197195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:19.633204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:23.460415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:27.386132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:30.470123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:34.044150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:37.213218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:40.923913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:44.788434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:33:59.181102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:02.745141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:05.696373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:09.471361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:13.156085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:16.351449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:19.884390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:23.952067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:27.640106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:30.707792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:34.306228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:37.478543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:41.178794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:45.037642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:33:59.433391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:02.899780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:05.885757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:09.720742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:13.407314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:16.524642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:20.126799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:24.304243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:27.884119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:30.963821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:34.463675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:37.751953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:41.421790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:45.285283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:33:59.689839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:03.057286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:06.073411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:09.970034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:13.661267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:16.774587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:20.369901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:24.552545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:28.128172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:31.218413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:34.618331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:38.006902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:41.663177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:45.531078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:33:59.942237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:03.212095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:06.337285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:10.217648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:13.913412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:17.023069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:20.798077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:24.801746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:28.380350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:31.478190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:34.777324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:38.264656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:41.908633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:45.801379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:00.174628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:03.387673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:06.822919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:10.487770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:14.189420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:17.290400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:21.059508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:25.065743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:28.644803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:31.757282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:34.953319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:38.539715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:42.172374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:46.071927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:00.440721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:03.562450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:07.098099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:10.758565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:14.468548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:17.558695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:21.325201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:25.330257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:28.906952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:32.033306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:35.126870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:38.817124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:42.441164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:46.346257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:00.624140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:03.814456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:07.377446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:11.031458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:14.743185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:17.838482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:21.589546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:25.592963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:29.168567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:32.305194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:35.328663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:39.096025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:42.709561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:46.595861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:00.878635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:04.070373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:07.630964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:11.278058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:14.997056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:18.084190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:21.734334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:25.833824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:29.412645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:32.562830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:35.592174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:39.351889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:34:42.952108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T20:34:59.776393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번자료제공년월자료순번전월사용량2개월전사용량3개월전사용량4개월전사용량5개월전사용량6개월전사용량7개월전사용량8개월전사용량9개월전사용량10개월전사용량11개월전사용량12개월전사용량자료처리일자
연번1.0000.8960.7810.0730.0000.1110.0150.0000.0000.1100.0000.0000.0000.0310.0000.896
자료제공년월0.8961.0000.2410.1420.0960.1300.1600.0530.0480.1030.0870.0950.0000.0980.0851.000
자료순번0.7810.2411.0000.1930.1220.1770.0000.1190.1050.0000.0780.0000.0800.0000.0390.241
전월사용량0.0730.1420.1931.0000.7340.9070.0000.7760.8060.7810.7780.7210.5860.7270.6720.142
2개월전사용량0.0000.0960.1220.7341.0000.8660.0000.7770.8680.6450.7940.6510.6400.6960.8700.096
3개월전사용량0.1110.1300.1770.9070.8661.0000.0000.9340.7980.7640.7700.7740.6620.7640.8500.130
4개월전사용량0.0150.1600.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.160
5개월전사용량0.0000.0530.1190.7760.7770.9340.0001.0000.7620.7910.7200.7660.6500.7240.8450.053
6개월전사용량0.0000.0480.1050.8060.8680.7980.0000.7621.0000.8930.9680.9120.9210.9180.9120.048
7개월전사용량0.1100.1030.0000.7810.6450.7640.0000.7910.8931.0000.8140.9340.7430.9150.7650.103
8개월전사용량0.0000.0870.0780.7780.7940.7700.0000.7200.9680.8141.0000.8130.9430.8270.8840.087
9개월전사용량0.0000.0950.0000.7210.6510.7740.0000.7660.9120.9340.8131.0000.8270.9660.7960.095
10개월전사용량0.0000.0000.0800.5860.6400.6620.0000.6500.9210.7430.9430.8271.0000.8410.8660.000
11개월전사용량0.0310.0980.0000.7270.6960.7640.0000.7240.9180.9150.8270.9660.8411.0000.8250.098
12개월전사용량0.0000.0850.0390.6720.8700.8500.0000.8450.9120.7650.8840.7960.8660.8251.0000.085
자료처리일자0.8961.0000.2410.1420.0960.1300.1600.0530.0480.1030.0870.0950.0000.0980.0851.000
2024-03-14T20:35:00.067513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
자료처리일자자료제공년월
자료처리일자1.0001.000
자료제공년월1.0001.000
2024-03-14T20:35:00.349724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번자료순번전월사용량2개월전사용량3개월전사용량4개월전사용량5개월전사용량6개월전사용량7개월전사용량8개월전사용량9개월전사용량10개월전사용량11개월전사용량12개월전사용량자료제공년월자료처리일자
연번1.000-0.0730.0360.0200.0080.0450.0710.0310.013-0.0080.0210.0140.0590.0140.7480.748
자료순번-0.0731.0000.091-0.0390.038-0.0420.011-0.0100.065-0.0430.050-0.0690.047-0.0430.1290.129
전월사용량0.0360.0911.000-0.0370.745-0.0510.668-0.0630.642-0.1000.609-0.0990.594-0.1260.0520.052
2개월전사용량0.020-0.039-0.0371.000-0.0820.814-0.1060.751-0.1200.696-0.1340.666-0.1320.5990.0530.053
3개월전사용량0.0080.0380.745-0.0821.000-0.1050.807-0.1130.751-0.1500.700-0.1460.694-0.1570.0720.072
4개월전사용량0.045-0.042-0.0510.814-0.1051.000-0.1230.815-0.1390.750-0.1570.716-0.1430.6690.0670.067
5개월전사용량0.0710.0110.668-0.1060.807-0.1231.000-0.1230.817-0.1630.747-0.1720.729-0.1840.0290.029
6개월전사용량0.031-0.010-0.0630.751-0.1130.815-0.1231.000-0.1190.791-0.1450.735-0.1170.7030.0240.024
7개월전사용량0.0130.0650.642-0.1200.751-0.1390.817-0.1191.000-0.1690.838-0.1760.798-0.1870.0510.051
8개월전사용량-0.008-0.043-0.1000.696-0.1500.750-0.1630.791-0.1691.000-0.1560.821-0.1660.7280.0430.043
9개월전사용량0.0210.0500.609-0.1340.700-0.1570.747-0.1450.838-0.1561.000-0.1710.860-0.2010.0470.047
10개월전사용량0.014-0.069-0.0990.666-0.1460.716-0.1720.735-0.1760.821-0.1711.000-0.1880.8480.0000.000
11개월전사용량0.0590.0470.594-0.1320.694-0.1430.729-0.1170.798-0.1660.860-0.1881.000-0.1840.0480.048
12개월전사용량0.014-0.043-0.1260.599-0.1570.669-0.1840.703-0.1870.728-0.2010.848-0.1841.0000.0470.047
자료제공년월0.7480.1290.0520.0530.0720.0670.0290.0240.0510.0430.0470.0000.0480.0471.0001.000
자료처리일자0.7480.1290.0520.0530.0720.0670.0290.0240.0510.0430.0470.0000.0480.0471.0001.000

Missing values

2024-03-14T20:34:47.223824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T20:34:47.945336image/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

연번자료제공년월자료회차자료순번자료접수기관코드정수시작일정수종료일전월사용량2개월전사용량3개월전사용량4개월전사용량5개월전사용량6개월전사용량7개월전사용량8개월전사용량9개월전사용량10개월전사용량11개월전사용량12개월전사용량자료처리일자
012023-0915462600952023-08-25<NA>070401304506092023-10-13
122023-0915562600952023-08-25<NA>0000000000002023-10-13
232023-0915662600952023-08-25<NA>0000000000032023-10-13
342023-0915762600952023-08-252023-09-140000000000002023-10-13
452023-0915862600952023-08-25<NA>0000000000002023-10-13
562023-0915962600952023-08-25<NA>0000001000002023-10-13
672023-0916062600952023-08-25<NA>0000000010502023-10-13
782023-0916162600952023-08-25<NA>00000049903002602023-10-13
892023-0916262600952023-08-28<NA>00000058000002023-10-13
9102023-0916362600952023-08-28<NA>0000000000032023-10-13
연번자료제공년월자료회차자료순번자료접수기관코드정수시작일정수종료일전월사용량2개월전사용량3개월전사용량4개월전사용량5개월전사용량6개월전사용량7개월전사용량8개월전사용량9개월전사용량10개월전사용량11개월전사용량12개월전사용량자료처리일자
7187192023-07110262600952023-07-13<NA>401702102702302802023-08-13
7197202023-07110362600952023-07-17<NA>0000000000002023-08-13
7207212023-07110462600952023-07-17<NA>1006107007503303402023-08-13
7217222023-07110562600952023-07-172023-07-173403903503804404302023-08-13
7227232023-07110662600952023-07-18<NA>02000000010682023-08-13
7237242023-07110762600952023-07-182023-07-2101007060807082023-08-13
7247252023-07110862600952023-07-19<NA>0000000010102023-08-13
7257262023-07110962600952023-07-192023-07-208607906405805704602023-08-13
7267272023-07111062600952023-07-19<NA>0020101201301702023-08-13
7277282023-07111162600952023-07-19<NA>0000000000002023-08-13