Overview

Dataset statistics

Number of variables9
Number of observations4121
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory310.0 KiB
Average record size in memory77.0 B

Variable types

Text1
Categorical1
DateTime2
Numeric5

Dataset

Description경상북도 구미시 유수율제고블록시스템의 수도요금검침집계(소블록) 테이블 데이터로 소블록에 대한 월별 사용량 데이터를 제공합니다.
Author경상북도 구미시
URLhttps://www.data.go.kr/data/15049705/fileData.do

Alerts

당월사용량 is highly overall correlated with 확정사용량 and 3 other fieldsHigh correlation
확정사용량 is highly overall correlated with 당월사용량 and 3 other fieldsHigh correlation
가사용량 is highly overall correlated with 당월사용량 and 3 other fieldsHigh correlation
조정량 is highly overall correlated with 당월사용량 and 3 other fieldsHigh correlation
급수전수 is highly overall correlated with 당월사용량 and 3 other fieldsHigh correlation
당월사용량 has 263 (6.4%) zerosZeros
확정사용량 has 263 (6.4%) zerosZeros
가사용량 has 263 (6.4%) zerosZeros
조정량 has 263 (6.4%) zerosZeros

Reproduction

Analysis started2023-12-12 21:25:22.801074
Analysis finished2023-12-12 21:25:26.304014
Duration3.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

소블록명
Text

Distinct81
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
2023-12-13T06:25:26.538353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0497452
Min length3

Characters and Unicode

Total characters24931
Distinct characters23
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4F-1-1
2nd row4F-1-1
3rd row4F-1-2
4th row4F-1-2
5th row4F-1-3
ValueCountFrequency (%)
wh-1-1 100
 
2.4%
wh-4-2 93
 
2.3%
sp-6-4 85
 
2.1%
id-1-3 79
 
1.9%
sp-2-1 75
 
1.8%
ss-1-1 75
 
1.8%
sp-1-7 75
 
1.8%
sp-5-3 75
 
1.8%
sp-5-1 75
 
1.8%
sp-4-2 75
 
1.8%
Other values (68) 3314
80.4%
2023-12-13T06:25:27.020450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 8229
33.0%
1 3435
13.8%
S 2902
 
11.6%
P 2035
 
8.2%
2 1521
 
6.1%
4 1417
 
5.7%
H 1019
 
4.1%
W 867
 
3.5%
3 837
 
3.4%
5 614
 
2.5%
Other values (13) 2055
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8675
34.8%
Dash Punctuation 8229
33.0%
Uppercase Letter 7858
31.5%
Lowercase Letter 144
 
0.6%
Space Separator 25
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3435
39.6%
2 1521
17.5%
4 1417
16.3%
3 837
 
9.6%
5 614
 
7.1%
6 464
 
5.3%
7 181
 
2.1%
0 75
 
0.9%
8 75
 
0.9%
9 56
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
S 2902
36.9%
P 2035
25.9%
H 1019
 
13.0%
W 867
 
11.0%
D 336
 
4.3%
I 331
 
4.2%
F 280
 
3.6%
A 83
 
1.1%
B 5
 
0.1%
Lowercase Letter
ValueCountFrequency (%)
w 72
50.0%
h 72
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 8229
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16929
67.9%
Latin 8002
32.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 8229
48.6%
1 3435
20.3%
2 1521
 
9.0%
4 1417
 
8.4%
3 837
 
4.9%
5 614
 
3.6%
6 464
 
2.7%
7 181
 
1.1%
0 75
 
0.4%
8 75
 
0.4%
Other values (2) 81
 
0.5%
Latin
ValueCountFrequency (%)
S 2902
36.3%
P 2035
25.4%
H 1019
 
12.7%
W 867
 
10.8%
D 336
 
4.2%
I 331
 
4.1%
F 280
 
3.5%
A 83
 
1.0%
w 72
 
0.9%
h 72
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24931
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 8229
33.0%
1 3435
13.8%
S 2902
 
11.6%
P 2035
 
8.2%
2 1521
 
6.1%
4 1417
 
5.7%
H 1019
 
4.1%
W 867
 
3.5%
3 837
 
3.4%
5 614
 
2.5%
Other values (13) 2055
 
8.2%

업종
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
가정용
1743 
영업용
1741 
욕탕용
637 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가정용
2nd row영업용
3rd row가정용
4th row영업용
5th row가정용

Common Values

ValueCountFrequency (%)
가정용 1743
42.3%
영업용 1741
42.2%
욕탕용 637
 
15.5%

Length

2023-12-13T06:25:27.174680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:25:27.302183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가정용 1743
42.3%
영업용 1741
42.2%
욕탕용 637
 
15.5%

사용년월
Date

Distinct25
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
Minimum2019-03-01 00:00:00
Maximum2021-03-01 00:00:00
2023-12-13T06:25:27.435838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:27.572860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

납기년월
Date

Distinct25
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
Minimum2019-04-01 00:00:00
Maximum2021-04-01 00:00:00
2023-12-13T06:25:27.708117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:27.860740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)

당월사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3260
Distinct (%)79.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24716.167
Minimum0
Maximum438406
Zeros263
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2023-12-13T06:25:28.345541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1438
median9953
Q331392
95-th percentile94121
Maximum438406
Range438406
Interquartile range (IQR)30954

Descriptive statistics

Standard deviation42821.495
Coefficient of variation (CV)1.7325298
Kurtosis32.493618
Mean24716.167
Median Absolute Deviation (MAD)9895
Skewness4.6237911
Sum1.0185532 × 108
Variance1.8336804 × 109
MonotonicityNot monotonic
2023-12-13T06:25:28.505620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 263
 
6.4%
1 33
 
0.8%
3 19
 
0.5%
2 16
 
0.4%
5 14
 
0.3%
8 13
 
0.3%
39 13
 
0.3%
10 13
 
0.3%
4 13
 
0.3%
9 11
 
0.3%
Other values (3250) 3713
90.1%
ValueCountFrequency (%)
0 263
6.4%
1 33
 
0.8%
2 16
 
0.4%
3 19
 
0.5%
4 13
 
0.3%
5 14
 
0.3%
6 11
 
0.3%
7 10
 
0.2%
8 13
 
0.3%
9 11
 
0.3%
ValueCountFrequency (%)
438406 1
< 0.1%
436456 1
< 0.1%
435389 1
< 0.1%
432913 1
< 0.1%
432320 1
< 0.1%
425482 1
< 0.1%
420406 1
< 0.1%
407036 1
< 0.1%
396356 1
< 0.1%
394665 1
< 0.1%

확정사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3260
Distinct (%)79.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24716.167
Minimum0
Maximum438406
Zeros263
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2023-12-13T06:25:28.681417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1438
median9953
Q331392
95-th percentile94121
Maximum438406
Range438406
Interquartile range (IQR)30954

Descriptive statistics

Standard deviation42821.495
Coefficient of variation (CV)1.7325298
Kurtosis32.493618
Mean24716.167
Median Absolute Deviation (MAD)9895
Skewness4.6237911
Sum1.0185532 × 108
Variance1.8336804 × 109
MonotonicityNot monotonic
2023-12-13T06:25:28.873189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 263
 
6.4%
1 33
 
0.8%
3 19
 
0.5%
2 16
 
0.4%
5 14
 
0.3%
8 13
 
0.3%
39 13
 
0.3%
10 13
 
0.3%
4 13
 
0.3%
9 11
 
0.3%
Other values (3250) 3713
90.1%
ValueCountFrequency (%)
0 263
6.4%
1 33
 
0.8%
2 16
 
0.4%
3 19
 
0.5%
4 13
 
0.3%
5 14
 
0.3%
6 11
 
0.3%
7 10
 
0.2%
8 13
 
0.3%
9 11
 
0.3%
ValueCountFrequency (%)
438406 1
< 0.1%
436456 1
< 0.1%
435389 1
< 0.1%
432913 1
< 0.1%
432320 1
< 0.1%
425482 1
< 0.1%
420406 1
< 0.1%
407036 1
< 0.1%
396356 1
< 0.1%
394665 1
< 0.1%

가사용량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3254
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24900.129
Minimum0
Maximum492147
Zeros263
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2023-12-13T06:25:29.032028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1438
median9953
Q331262
95-th percentile94108
Maximum492147
Range492147
Interquartile range (IQR)30824

Descriptive statistics

Standard deviation44699.816
Coefficient of variation (CV)1.795164
Kurtosis39.81166
Mean24900.129
Median Absolute Deviation (MAD)9897
Skewness5.1455564
Sum1.0261343 × 108
Variance1.9980735 × 109
MonotonicityNot monotonic
2023-12-13T06:25:29.197660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 263
 
6.4%
1 33
 
0.8%
3 19
 
0.5%
2 16
 
0.4%
5 14
 
0.3%
39 13
 
0.3%
10 13
 
0.3%
4 13
 
0.3%
8 13
 
0.3%
9 11
 
0.3%
Other values (3244) 3713
90.1%
ValueCountFrequency (%)
0 263
6.4%
1 33
 
0.8%
2 16
 
0.4%
3 19
 
0.5%
4 13
 
0.3%
5 14
 
0.3%
6 11
 
0.3%
7 10
 
0.2%
8 13
 
0.3%
9 11
 
0.3%
ValueCountFrequency (%)
492147 1
< 0.1%
491648 1
< 0.1%
480494 1
< 0.1%
478630 1
< 0.1%
472356 1
< 0.1%
465977 1
< 0.1%
458160 1
< 0.1%
435841 1
< 0.1%
434270 1
< 0.1%
433473 1
< 0.1%

조정량
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3254
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24900.129
Minimum0
Maximum492147
Zeros263
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2023-12-13T06:25:29.370811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1438
median9953
Q331262
95-th percentile94108
Maximum492147
Range492147
Interquartile range (IQR)30824

Descriptive statistics

Standard deviation44699.816
Coefficient of variation (CV)1.795164
Kurtosis39.81166
Mean24900.129
Median Absolute Deviation (MAD)9897
Skewness5.1455564
Sum1.0261343 × 108
Variance1.9980735 × 109
MonotonicityNot monotonic
2023-12-13T06:25:29.526732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 263
 
6.4%
1 33
 
0.8%
3 19
 
0.5%
2 16
 
0.4%
5 14
 
0.3%
39 13
 
0.3%
10 13
 
0.3%
4 13
 
0.3%
8 13
 
0.3%
9 11
 
0.3%
Other values (3244) 3713
90.1%
ValueCountFrequency (%)
0 263
6.4%
1 33
 
0.8%
2 16
 
0.4%
3 19
 
0.5%
4 13
 
0.3%
5 14
 
0.3%
6 11
 
0.3%
7 10
 
0.2%
8 13
 
0.3%
9 11
 
0.3%
ValueCountFrequency (%)
492147 1
< 0.1%
491648 1
< 0.1%
480494 1
< 0.1%
478630 1
< 0.1%
472356 1
< 0.1%
465977 1
< 0.1%
458160 1
< 0.1%
435841 1
< 0.1%
434270 1
< 0.1%
433473 1
< 0.1%

급수전수
Real number (ℝ)

HIGH CORRELATION 

Distinct711
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean253.20529
Minimum1
Maximum1946
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.3 KiB
2023-12-13T06:25:29.695043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median149
Q3371
95-th percentile947
Maximum1946
Range1945
Interquartile range (IQR)364

Descriptive statistics

Standard deviation316.40254
Coefficient of variation (CV)1.249589
Kurtosis5.2313393
Mean253.20529
Median Absolute Deviation (MAD)146
Skewness2.0228213
Sum1043459
Variance100110.57
MonotonicityNot monotonic
2023-12-13T06:25:29.860830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 580
 
14.1%
2 195
 
4.7%
3 144
 
3.5%
4 61
 
1.5%
7 53
 
1.3%
5 39
 
0.9%
60 39
 
0.9%
64 32
 
0.8%
59 29
 
0.7%
92 25
 
0.6%
Other values (701) 2924
71.0%
ValueCountFrequency (%)
1 580
14.1%
2 195
 
4.7%
3 144
 
3.5%
4 61
 
1.5%
5 39
 
0.9%
6 7
 
0.2%
7 53
 
1.3%
8 8
 
0.2%
9 16
 
0.4%
10 3
 
0.1%
ValueCountFrequency (%)
1946 3
0.1%
1945 1
 
< 0.1%
1944 1
 
< 0.1%
1937 1
 
< 0.1%
1936 1
 
< 0.1%
1935 1
 
< 0.1%
1932 2
< 0.1%
1929 1
 
< 0.1%
1928 1
 
< 0.1%
1927 2
< 0.1%

Interactions

2023-12-13T06:25:25.404332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:23.405249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:23.888528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:24.378182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:24.895942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:25.515184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:23.483184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:23.977231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:24.491924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:25.004558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:25.625834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:23.561486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:24.069109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:24.586265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:25.099162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:25.766120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:23.648751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:24.180236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:24.679412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:25.197269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:25.908577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:23.768855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:24.271613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:24.782837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:25:25.298007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:25:29.982700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소블록명업종사용년월납기년월당월사용량확정사용량가사용량조정량급수전수
소블록명1.0000.5740.0000.0000.7820.7820.7730.7730.883
업종0.5741.0000.0000.0000.4200.4200.3930.3930.628
사용년월0.0000.0001.0001.0000.0000.0000.0000.0000.000
납기년월0.0000.0001.0001.0000.0000.0000.0000.0000.000
당월사용량0.7820.4200.0000.0001.0001.0000.9380.9380.518
확정사용량0.7820.4200.0000.0001.0001.0000.9380.9380.518
가사용량0.7730.3930.0000.0000.9380.9381.0001.0000.512
조정량0.7730.3930.0000.0000.9380.9381.0001.0000.512
급수전수0.8830.6280.0000.0000.5180.5180.5120.5121.000
2023-12-13T06:25:30.117053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
당월사용량확정사용량가사용량조정량급수전수업종
당월사용량1.0001.0001.0001.0000.6900.294
확정사용량1.0001.0001.0001.0000.6900.294
가사용량1.0001.0001.0001.0000.6900.288
조정량1.0001.0001.0001.0000.6900.288
급수전수0.6900.6900.6900.6901.0000.347
업종0.2940.2940.2880.2880.3471.000

Missing values

2023-12-13T06:25:26.071429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:25:26.236466image/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

소블록명업종사용년월납기년월당월사용량확정사용량가사용량조정량급수전수
04F-1-1가정용2019-03-012019-04-0113665813665813665813665857
14F-1-1영업용2019-03-012019-04-0194121941219410894108400
24F-1-2가정용2019-03-012019-04-0110415104151030610306923
34F-1-2영업용2019-03-012019-04-0126173261732617326173238
44F-1-3가정용2019-03-012019-04-017794779474627462492
54F-1-3영업용2019-03-012019-04-017887788778877887177
64F-1-4가정용2019-03-012019-04-0177782777827778277782640
74F-1-4영업용2019-03-012019-04-0128517285172851728517363
84F-1-5가정용2019-03-012019-04-01100224100224100224100224509
94F-1-5영업용2019-03-012019-04-0178745787457884578845673
소블록명업종사용년월납기년월당월사용량확정사용량가사용량조정량급수전수
4111SP-5-3욕탕용2021-03-012021-04-011121121121122
4112SP-6-1가정용2021-03-012021-04-0119954199541995419954371
4113SP-6-1영업용2021-03-012021-04-0111811118111179811798151
4114SP-6-1욕탕용2021-03-012021-04-0111251125112511251
4115SP-6-2가정용2021-03-012021-04-013784378437843784193
4116SP-6-2영업용2021-03-012021-04-01204520452045204546
4117SP-6-3가정용2021-03-012021-04-0177621776217762177621807
4118SP-6-3영업용2021-03-012021-04-0121810218102181021810393
4119SP-6-3욕탕용2021-03-012021-04-0100001
4120SP-6-4가정용2021-03-012021-04-011506521506521506521506521448