Overview

Dataset statistics

Number of variables3
Number of observations1672
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.6 KiB
Average record size in memory26.1 B

Variable types

DateTime1
Numeric2

Dataset

Description부산광역시해운대구_재정정보공개시스템_지출내역일자합계_20221219
Author부산광역시 해운대구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15050172

Alerts

지급일자(pay_cmd_ymd) has unique valuesUnique
지출액(expd_resol_amt) has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:13:54.635222
Analysis finished2023-12-10 16:13:55.499271
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지급일자(pay_cmd_ymd)
Date

UNIQUE 

Distinct1672
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size13.2 KiB
Minimum2016-01-05 00:00:00
Maximum2022-12-16 00:00:00
2023-12-11T01:13:55.611996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:13:55.806834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

세입회계연도(tax_accounting_year)
Real number (ℝ)

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.0036
Minimum2016
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.8 KiB
2023-12-11T01:13:55.948056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2016
Q12017
median2019
Q32021
95-th percentile2022
Maximum2022
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.000296
Coefficient of variation (CV)0.00099073424
Kurtosis-1.2486412
Mean2019.0036
Median Absolute Deviation (MAD)2
Skewness-0.012575168
Sum3375774
Variance4.001184
MonotonicityNot monotonic
2023-12-11T01:13:56.096422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2020 243
14.5%
2016 242
14.5%
2021 242
14.5%
2019 241
14.4%
2022 236
14.1%
2017 235
14.1%
2018 233
13.9%
ValueCountFrequency (%)
2016 242
14.5%
2017 235
14.1%
2018 233
13.9%
2019 241
14.4%
2020 243
14.5%
2021 242
14.5%
2022 236
14.1%
ValueCountFrequency (%)
2022 236
14.1%
2021 242
14.5%
2020 243
14.5%
2019 241
14.4%
2018 233
13.9%
2017 235
14.1%
2016 242
14.5%

지출액(expd_resol_amt)
Real number (ℝ)

UNIQUE 

Distinct1672
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6608975 × 109
Minimum-6.1547296 × 109
Maximum7.1536365 × 1010
Zeros0
Zeros (%)0.0%
Negative16
Negative (%)1.0%
Memory size14.8 KiB
2023-12-11T01:13:56.298812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-6.1547296 × 109
5-th percentile1.857718 × 108
Q14.9403858 × 108
median9.7087246 × 108
Q32.2765372 × 109
95-th percentile1.2384402 × 1010
Maximum7.1536365 × 1010
Range7.7691095 × 1010
Interquartile range (IQR)1.7824987 × 109

Descriptive statistics

Standard deviation4.6369551 × 109
Coefficient of variation (CV)1.7426282
Kurtosis40.792188
Mean2.6608975 × 109
Median Absolute Deviation (MAD)6.1222241 × 108
Skewness4.639145
Sum4.4490206 × 1012
Variance2.1501352 × 1019
MonotonicityNot monotonic
2023-12-11T01:13:56.529895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4400755140 1
 
0.1%
824252490 1
 
0.1%
632948720 1
 
0.1%
3150055740 1
 
0.1%
429112070 1
 
0.1%
912891790 1
 
0.1%
666019760 1
 
0.1%
1083486940 1
 
0.1%
218635970 1
 
0.1%
366525650 1
 
0.1%
Other values (1662) 1662
99.4%
ValueCountFrequency (%)
-6154729580 1
0.1%
-1844585530 1
0.1%
-928419520 1
0.1%
-238625910 1
0.1%
-28400000 1
0.1%
-25000000 1
0.1%
-19981370 1
0.1%
-4505880 1
0.1%
-2172460 1
0.1%
-1050000 1
0.1%
ValueCountFrequency (%)
71536365230 1
0.1%
48863781720 1
0.1%
38171586910 1
0.1%
32175771280 1
0.1%
30812346490 1
0.1%
25570675960 1
0.1%
23059274460 1
0.1%
22658957170 1
0.1%
20984828120 1
0.1%
20292005100 1
0.1%

Interactions

2023-12-11T01:13:55.024312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:13:54.744632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:13:55.166941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:13:54.873860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:13:56.682301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세입회계연도(tax_accounting_year)지출액(expd_resol_amt)
세입회계연도(tax_accounting_year)1.0000.120
지출액(expd_resol_amt)0.1201.000
2023-12-11T01:13:56.833167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세입회계연도(tax_accounting_year)지출액(expd_resol_amt)
세입회계연도(tax_accounting_year)1.0000.159
지출액(expd_resol_amt)0.1591.000

Missing values

2023-12-11T01:13:55.337559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:13:55.449054image/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

지급일자(pay_cmd_ymd)세입회계연도(tax_accounting_year)지출액(expd_resol_amt)
02016-12-3020164400755140
12016-12-2920162953440080
22016-12-2820162214580480
32016-12-2720161456042690
42016-12-262016768832460
52016-12-23201610976840810
62016-12-2220162928182460
72016-12-2120161270193590
82016-12-2020168994288450
92016-12-192016399323060
지급일자(pay_cmd_ymd)세입회계연도(tax_accounting_year)지출액(expd_resol_amt)
16622022-01-142022300873030
16632022-01-132022956471540
16642022-01-122022883632820
16652022-01-1120223083190320
16662022-01-102022102687860
16672022-01-07202210182091340
16682022-01-0620221796317120
16692022-01-052022298617920
16702022-01-0420221807280880
16712022-01-03202220048818470