gimi9 Pandas Profiling

Dataset statistics

Number of variables	12
Number of observations	35
Missing cells	72
Missing cells (%)	17.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	3.8 KiB
Average record size in memory	109.8 B

Variable types

Categorical	1
Numeric	10
DateTime	1

Dataset

Description	광주광역시 자치구(동,서,남,북,광산구)의 자동차 및 시설물에 대한 연도별 환경개선부담금 부과건수, 부과금액, 징수금액 등의 정보입니다.
Author	광주광역시
URL	https://www.data.go.kr/data/15054124/fileData.do

Alerts

`데이터기준일` has constant value ""	Constant
`부과년도` is highly overall correlated with `시설물징수금액(천원)`	High correlation
`합계부과건수` is highly overall correlated with `합계부과금액(천원)` and 8 other fields	High correlation
`합계부과금액(천원)` is highly overall correlated with `합계부과건수` and 8 other fields	High correlation
`합계징수금액(천원)` is highly overall correlated with `합계부과건수` and 7 other fields	High correlation
`시설물부과건수` is highly overall correlated with `합계부과건수` and 8 other fields	High correlation
`시설물부과금액(천원)` is highly overall correlated with `합계부과건수` and 8 other fields	High correlation
`시설물징수금액(천원)` is highly overall correlated with `부과년도` and 9 other fields	High correlation
`자동차부과건수` is highly overall correlated with `합계부과건수` and 8 other fields	High correlation
`자동차부과금액(천원)` is highly overall correlated with `합계부과건수` and 8 other fields	High correlation
`자동차징수금액(천원)` is highly overall correlated with `합계부과건수` and 8 other fields	High correlation
`구분` is highly overall correlated with `합계부과건수` and 7 other fields	High correlation
`시설물부과건수` has 25 (71.4%) missing values	Missing
`시설물부과금액(천원)` has 25 (71.4%) missing values	Missing
`시설물징수금액(천원)` has 22 (62.9%) missing values	Missing
`합계부과건수` has unique values	Unique
`합계부과금액(천원)` has unique values	Unique
`합계징수금액(천원)` has unique values	Unique
`자동차부과건수` has unique values	Unique
`자동차부과금액(천원)` has unique values	Unique
`자동차징수금액(천원)` has unique values	Unique

Reproduction

Analysis started	2023-12-12 08:25:06.995437
Analysis finished	2023-12-12 08:25:18.835144
Duration	11.84 seconds
Software version	ydata-profiling vv4.5.1
Download configuration	config.json

구분
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	14.3%
Missing	0
Missing (%)	0.0%
Memory size	412.0 B

광주광역시 동구	7
광주광역시 서구	7
광주광역시 남구	7
광주광역시 북구	7
광주광역시 광산구	7

Length

Max length	9
Median length	8
Mean length	8.2
Min length	8

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	광주광역시 동구
2nd row	광주광역시 동구
3rd row	광주광역시 동구
4th row	광주광역시 동구
5th row	광주광역시 동구

Common Values

Value	Count	Frequency (%)
광주광역시 동구	7	20.0%
광주광역시 서구	7	20.0%
광주광역시 남구	7	20.0%
광주광역시 북구	7	20.0%
광주광역시 광산구	7	20.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
광주광역시	35	50.0%
동구	7	10.0%
서구	7	10.0%
남구	7	10.0%
북구	7	10.0%
광산구	7	10.0%

부과년도
Real number (ℝ)

HIGH CORRELATION

Distinct	7
Distinct (%)	20.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2017

Minimum	2014
Maximum	2020
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	447.0 B

Quantile statistics

Minimum	2014
5-th percentile	2014
Q1	2015
median	2017
Q3	2019
95-th percentile	2020
Maximum	2020
Range	6
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.0291986
Coefficient of variation (CV)	0.0010060479
Kurtosis	-1.2556818
Mean	2017
Median Absolute Deviation (MAD)	2
Skewness	0
Sum	70595
Variance	4.1176471
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
2020	5	14.3%
2019	5	14.3%
2018	5	14.3%
2017	5	14.3%
2016	5	14.3%
2015	5	14.3%
2014	5	14.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2014	5	14.3%
2015	5	14.3%
2016	5	14.3%
2017	5	14.3%
2018	5	14.3%
2019	5	14.3%
2020	5	14.3%

Value	Count	Frequency (%)
2020	5	14.3%
2019	5	14.3%
2018	5	14.3%
2017	5	14.3%
2016	5	14.3%
2015	5	14.3%
2014	5	14.3%

합계부과건수
Real number (ℝ)

HIGH CORRELATION UNIQUE

Distinct	35
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	52845.943

Minimum	9773
Maximum	107835
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	447.0 B

Quantile statistics

Minimum	9773
5-th percentile	12223.6
Q1	29589
median	51810
Q3	72513.5
95-th percentile	102935.5
Maximum	107835
Range	98062
Interquartile range (IQR)	42924.5

Descriptive statistics

Standard deviation	28996.733
Coefficient of variation (CV)	0.5487031
Kurtosis	-0.96054518
Mean	52845.943
Median Absolute Deviation (MAD)	21538
Skewness	0.2489909
Sum	1849608
Variance	8.408105 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=35)

Value	Count	Frequency (%)
9773	1	2.9%
11112	1	2.9%
44712	1	2.9%
53437	1	2.9%
62170	1	2.9%
69440	1	2.9%
75954	1	2.9%
81859	1	2.9%
98223	1	2.9%
102478	1	2.9%
Other values (25)	25	71.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
9773	1	2.9%
11112	1	2.9%
12700	1	2.9%
13897	1	2.9%
15587	1	2.9%
21783	1	2.9%
22873	1	2.9%
23849	1	2.9%
27783	1	2.9%
31395	1	2.9%

Value	Count	Frequency (%)
107835	1	2.9%
104003	1	2.9%
102478	1	2.9%
98223	1	2.9%
88826	1	2.9%
81859	1	2.9%
80813	1	2.9%
75954	1	2.9%
73348	1	2.9%
71679	1	2.9%

합계부과금액(천원)
Real number (ℝ)

HIGH CORRELATION UNIQUE

Distinct	35
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3352208.5

Minimum	601043
Maximum	7102499
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	447.0 B

Quantile statistics

Minimum	601043
5-th percentile	735293.2
Q1	1740648.5
median	3016119
Q3	4617579.5
95-th percentile	6828812
Maximum	7102499
Range	6501456
Interquartile range (IQR)	2876931

Descriptive statistics

Standard deviation	1932636.6
Coefficient of variation (CV)	0.57652636
Kurtosis	-0.85011591
Mean	3352208.5
Median Absolute Deviation (MAD)	1521669
Skewness	0.38492722
Sum	1.173273 × 10⁸
Variance	3.7350842 × 10¹²
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=35)

Value	Count	Frequency (%)
601043	1	2.9%
678414	1	2.9%
2696148	1	2.9%
3477724	1	2.9%
3929657	1	2.9%
4280567	1	2.9%
4614184	1	2.9%
5052957	1	2.9%
6537660	1	2.9%
6745181	1	2.9%
Other values (25)	25	71.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
601043	1	2.9%
678414	1	2.9%
759670	1	2.9%
822508	1	2.9%
918284	1	2.9%
1467121	1	2.9%
1562373	1	2.9%
1624592	1	2.9%
1646635	1	2.9%
1834662	1	2.9%

Value	Count	Frequency (%)
7102499	1	2.9%
7023951	1	2.9%
6745181	1	2.9%
6537660	1	2.9%
5740281	1	2.9%
5206383	1	2.9%
5052957	1	2.9%
4855184	1	2.9%
4620975	1	2.9%
4614184	1	2.9%

합계징수금액(천원)
Real number (ℝ)

HIGH CORRELATION UNIQUE

Distinct	35
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2886192.9

Minimum	482036
Maximum	6563924
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	447.0 B

Quantile statistics

Minimum	482036
5-th percentile	576106.3
Q1	1412505
median	2594515
Q3	4107861
95-th percentile	6245514
Maximum	6563924
Range	6081888
Interquartile range (IQR)	2695356

Descriptive statistics

Standard deviation	1781812.8
Coefficient of variation (CV)	0.61735748
Kurtosis	-0.60552544
Mean	2886192.9
Median Absolute Deviation (MAD)	1312642
Skewness	0.55240083
Sum	1.0101675 × 10⁸
Variance	3.1748568 × 10¹²
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=35)

Value	Count	Frequency (%)
482036	1	2.9%
524244	1	2.9%
2489054	1	2.9%
2672157	1	2.9%
2957636	1	2.9%
3367690	1	2.9%
3931891	1	2.9%
4419604	1	2.9%
5923099	1	2.9%
6160842	1	2.9%
Other values (25)	25	71.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
482036	1	2.9%
524244	1	2.9%
598333	1	2.9%
649563	1	2.9%
736761	1	2.9%
1131619	1	2.9%
1281873	1	2.9%
1284894	1	2.9%
1325590	1	2.9%
1499420	1	2.9%

Value	Count	Frequency (%)
6563924	1	2.9%
6443082	1	2.9%
6160842	1	2.9%
5923099	1	2.9%
5130217	1	2.9%
4623239	1	2.9%
4419604	1	2.9%
4261067	1	2.9%
4154248	1	2.9%
4061474	1	2.9%

시설물부과건수
Real number (ℝ)

HIGH CORRELATION MISSING

Distinct	10
Distinct (%)	100.0%
Missing	25
Missing (%)	71.4%
Infinite	0
Infinite (%)	0.0%
Mean	7538.9

Minimum	3818
Maximum	10840
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	447.0 B

Quantile statistics

Minimum	3818
5-th percentile	3828.8
Q1	4798.25
median	9075.5
Q3	9266.5
95-th percentile	10762.15
Maximum	10840
Range	7022
Interquartile range (IQR)	4468.25

Descriptive statistics

Standard deviation	2861.1538
Coefficient of variation (CV)	0.37951873
Kurtosis	-1.9509501
Mean	7538.9
Median Absolute Deviation (MAD)	1678
Skewness	-0.3520347
Sum	75389
Variance	8186201
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
4795	1	2.9%
4808	1	2.9%
9168	1	2.9%
9169	1	2.9%
3818	1	2.9%
3842	1	2.9%
10840	1	2.9%
10667	1	2.9%
9299	1	2.9%
8983	1	2.9%
(Missing)	25	71.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
3818	1	2.9%
3842	1	2.9%
4795	1	2.9%
4808	1	2.9%
8983	1	2.9%
9168	1	2.9%
9169	1	2.9%
9299	1	2.9%
10667	1	2.9%
10840	1	2.9%

Value	Count	Frequency (%)
10840	1	2.9%
10667	1	2.9%
9299	1	2.9%
9169	1	2.9%
9168	1	2.9%
8983	1	2.9%
4808	1	2.9%
4795	1	2.9%
3842	1	2.9%
3818	1	2.9%

시설물부과금액(천원)
Real number (ℝ)

HIGH CORRELATION MISSING

Distinct	10
Distinct (%)	100.0%
Missing	25
Missing (%)	71.4%
Infinite	0
Infinite (%)	0.0%
Mean	803565.6

Minimum	353187
Maximum	1198276
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	447.0 B

Quantile statistics

Minimum	353187
5-th percentile	353703.6
Q1	561191.25
median	891813
Q3	1025782.5
95-th percentile	1182371.6
Maximum	1198276
Range	845089
Interquartile range (IQR)	464591.25

Descriptive statistics

Standard deviation	319129.23
Coefficient of variation (CV)	0.39714148
Kurtosis	-1.5152915
Mean	803565.6
Median Absolute Deviation (MAD)	288791.5
Skewness	-0.33212858
Sum	8035656
Variance	1.0184346 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
556104	1	2.9%
576453	1	2.9%
1024548	1	2.9%
1026194	1	2.9%
354335	1	2.9%
353187	1	2.9%
1162933	1	2.9%
1198276	1	2.9%
902102	1	2.9%
881524	1	2.9%
(Missing)	25	71.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
353187	1	2.9%
354335	1	2.9%
556104	1	2.9%
576453	1	2.9%
881524	1	2.9%
902102	1	2.9%
1024548	1	2.9%
1026194	1	2.9%
1162933	1	2.9%
1198276	1	2.9%

Value	Count	Frequency (%)
1198276	1	2.9%
1162933	1	2.9%
1026194	1	2.9%
1024548	1	2.9%
902102	1	2.9%
881524	1	2.9%
576453	1	2.9%
556104	1	2.9%
354335	1	2.9%
353187	1	2.9%

시설물징수금액(천원)
Real number (ℝ)

HIGH CORRELATION MISSING

Distinct	13
Distinct (%)	100.0%
Missing	22
Missing (%)	62.9%
Infinite	0
Infinite (%)	0.0%
Mean	604610.92

Minimum	12163
Maximum	1168606
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	447.0 B

Quantile statistics

Minimum	12163
5-th percentile	14434
Q1	343450
median	538761
Q3	1004549
95-th percentile	1141989.4
Maximum	1168606
Range	1156443
Interquartile range (IQR)	661099

Descriptive statistics

Standard deviation	431821.99
Coefficient of variation (CV)	0.71421468
Kurtosis	-1.5349874
Mean	604610.92
Median Absolute Deviation (MAD)	465788
Skewness	-0.18790503
Sum	7859942
Variance	1.8647023 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
12163	1	2.9%
15948	1	2.9%
24644	1	2.9%
527946	1	2.9%
538761	1	2.9%
1004549	1	2.9%
1012115	1	2.9%
343450	1	2.9%
343623	1	2.9%
1124245	1	2.9%
Other values (3)	3	8.6%
(Missing)	22	62.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
12163	1	2.9%
15948	1	2.9%
24644	1	2.9%
343450	1	2.9%
343623	1	2.9%
527946	1	2.9%
538761	1	2.9%
862645	1	2.9%
881247	1	2.9%
1004549	1	2.9%

Value	Count	Frequency (%)
1168606	1	2.9%
1124245	1	2.9%
1012115	1	2.9%
1004549	1	2.9%
881247	1	2.9%
862645	1	2.9%
538761	1	2.9%
527946	1	2.9%
343623	1	2.9%
343450	1	2.9%

자동차부과건수
Real number (ℝ)

HIGH CORRELATION UNIQUE

Distinct	35
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	50691.971

Minimum	9773
Maximum	98852
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	447.0 B

Quantile statistics

Minimum	9773
5-th percentile	12223.6
Q1	29589
median	51810
Q3	71394
95-th percentile	92678.9
Maximum	98852
Range	89079
Interquartile range (IQR)	41805

Descriptive statistics

Standard deviation	27202.681
Coefficient of variation (CV)	0.536627
Kurtosis	-1.1749139
Mean	50691.971
Median Absolute Deviation (MAD)	21538
Skewness	0.1070411
Sum	1774219
Variance	7.3998583 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=35)

Value	Count	Frequency (%)
9773	1	2.9%
11112	1	2.9%
40870	1	2.9%
53437	1	2.9%
62170	1	2.9%
69440	1	2.9%
75954	1	2.9%
81859	1	2.9%
87383	1	2.9%
91811	1	2.9%
Other values (25)	25	71.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
9773	1	2.9%
11112	1	2.9%
12700	1	2.9%
13897	1	2.9%
15587	1	2.9%
16988	1	2.9%
18065	1	2.9%
23849	1	2.9%
27783	1	2.9%
31395	1	2.9%

Value	Count	Frequency (%)
98852	1	2.9%
94704	1	2.9%
91811	1	2.9%
88826	1	2.9%
87383	1	2.9%
81859	1	2.9%
80813	1	2.9%
75954	1	2.9%
73348	1	2.9%
69440	1	2.9%

자동차부과금액(천원)
Real number (ℝ)

HIGH CORRELATION UNIQUE

Distinct	35
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3122618.4

Minimum	601043
Maximum	6220975
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	447.0 B

Quantile statistics

Minimum	601043
5-th percentile	735293.2
Q1	1729627
median	3016119
Q3	4603686
95-th percentile	5854751.4
Maximum	6220975
Range	5619932
Interquartile range (IQR)	2874059

Descriptive statistics

Standard deviation	1745750.9
Coefficient of variation (CV)	0.55906635
Kurtosis	-1.2018622
Mean	3122618.4
Median Absolute Deviation (MAD)	1548998
Skewness	0.18523215
Sum	1.0929164 × 10⁸
Variance	3.0476461 × 10¹²
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=35)

Value	Count	Frequency (%)
601043	1	2.9%
678414	1	2.9%
2342961	1	2.9%
3477724	1	2.9%
3929657	1	2.9%
4280567	1	2.9%
4614184	1	2.9%
5052957	1	2.9%
5374727	1	2.9%
5546905	1	2.9%
Other values (25)	25	71.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
601043	1	2.9%
678414	1	2.9%
759670	1	2.9%
822508	1	2.9%
918284	1	2.9%
1006269	1	2.9%
1070182	1	2.9%
1467121	1	2.9%
1624592	1	2.9%
1834662	1	2.9%

Value	Count	Frequency (%)
6220975	1	2.9%
6121849	1	2.9%
5740281	1	2.9%
5546905	1	2.9%
5374727	1	2.9%
5206383	1	2.9%
5052957	1	2.9%
4855184	1	2.9%
4614184	1	2.9%
4593188	1	2.9%

자동차징수금액(천원)
Real number (ℝ)

HIGH CORRELATION UNIQUE

Distinct	35
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2661623.1

Minimum	482036
Maximum	5701279
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	447.0 B

Quantile statistics

Minimum	482036
5-th percentile	567592.2
Q1	1392157
median	2594515
Q3	3799607.5
95-th percentile	5259702.4
Maximum	5701279
Range	5219243
Interquartile range (IQR)	2407450.5

Descriptive statistics

Standard deviation	1580500.4
Coefficient of variation (CV)	0.59381074
Kurtosis	-0.98706862
Mean	2661623.1
Median Absolute Deviation (MAD)	1309621
Skewness	0.32087167
Sum	93156809
Variance	2.4979815 × 10¹²
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=35)

Value	Count	Frequency (%)
482036	1	2.9%
524244	1	2.9%
2145431	1	2.9%
2672157	1	2.9%
2957636	1	2.9%
3367690	1	2.9%
3931891	1	2.9%
4419604	1	2.9%
4798854	1	2.9%
4992236	1	2.9%
Other values (25)	25	71.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
482036	1	2.9%
524244	1	2.9%
586170	1	2.9%
633615	1	2.9%
712117	1	2.9%
753927	1	2.9%
786829	1	2.9%
1131619	1	2.9%
1284894	1	2.9%
1499420	1	2.9%

Value	Count	Frequency (%)
5701279	1	2.9%
5561835	1	2.9%
5130217	1	2.9%
4992236	1	2.9%
4798854	1	2.9%
4623239	1	2.9%
4419604	1	2.9%
4061474	1	2.9%
3931891	1	2.9%
3667324	1	2.9%

데이터기준일
Date

CONSTANT

Distinct	1
Distinct (%)	2.9%
Missing	0
Missing (%)	0.0%
Memory size	412.0 B

Minimum	2021-09-08 00:00:00
Maximum	2021-09-08 00:00:00

Histogram

Histogram with fixed size bins (bins=1)

Phik (φk)
Auto

Heatmap
Table

	구분	부과년도	합계부과건수	합계부과금액(천원)	합계징수금액(천원)	시설물부과건수	시설물부과금액(천원)	시설물징수금액(천원)	자동차부과건수	자동차부과금액(천원)	자동차징수금액(천원)
구분	1.000	0.000	0.870	0.743	0.832	1.000	1.000	1.000	0.943	0.960	0.938
부과년도	0.000	1.000	0.000	0.000	0.000	NaN	NaN	0.000	0.000	0.000	0.000
합계부과건수	0.870	0.000	1.000	0.935	0.972	0.976	1.000	1.000	0.931	0.959	0.968
합계부과금액(천원)	0.743	0.000	0.935	1.000	0.940	0.976	1.000	1.000	0.801	0.869	0.907
합계징수금액(천원)	0.832	0.000	0.972	0.940	1.000	0.856	0.987	0.994	0.925	0.933	0.961
시설물부과건수	1.000	NaN	0.976	0.976	0.856	1.000	1.000	1.000	0.856	1.000	1.000
시설물부과금액(천원)	1.000	NaN	1.000	1.000	0.987	1.000	1.000	1.000	0.987	1.000	1.000
시설물징수금액(천원)	1.000	0.000	1.000	1.000	0.994	1.000	1.000	1.000	0.901	1.000	1.000
자동차부과건수	0.943	0.000	0.931	0.801	0.925	0.856	0.987	0.901	1.000	0.948	0.948
자동차부과금액(천원)	0.960	0.000	0.959	0.869	0.933	1.000	1.000	1.000	0.948	1.000	0.976
자동차징수금액(천원)	0.938	0.000	0.968	0.907	0.961	1.000	1.000	1.000	0.948	0.976	1.000

Heatmap
Table

	부과년도	합계부과건수	합계부과금액(천원)	합계징수금액(천원)	시설물부과건수	시설물부과금액(천원)	시설물징수금액(천원)	자동차부과건수	자동차부과금액(천원)	자동차징수금액(천원)	구분
부과년도	1.000	-0.380	-0.392	-0.434	0.035	-0.035	-0.623	-0.334	-0.303	-0.342	0.000
합계부과건수	-0.380	1.000	0.996	0.993	0.673	0.588	0.819	0.996	0.991	0.995	0.502
합계부과금액(천원)	-0.392	0.996	1.000	0.996	0.673	0.588	0.819	0.991	0.990	0.993	0.520
합계징수금액(천원)	-0.434	0.993	0.996	1.000	0.673	0.588	0.819	0.984	0.981	0.987	0.460
시설물부과건수	0.035	0.673	0.673	0.673	1.000	0.939	0.952	0.673	0.673	0.673	0.913
시설물부과금액(천원)	-0.035	0.588	0.588	0.588	0.939	1.000	0.988	0.588	0.588	0.588	1.000
시설물징수금액(천원)	-0.623	0.819	0.819	0.819	0.952	0.988	1.000	0.819	0.819	0.819	0.935
자동차부과건수	-0.334	0.996	0.991	0.984	0.673	0.588	0.819	1.000	0.998	0.998	0.618
자동차부과금액(천원)	-0.303	0.991	0.990	0.981	0.673	0.588	0.819	0.998	1.000	0.997	0.660
자동차징수금액(천원)	-0.342	0.995	0.993	0.987	0.673	0.588	0.819	0.998	0.997	1.000	0.607
구분	0.000	0.502	0.520	0.460	0.913	1.000	0.935	0.618	0.660	0.607	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows
Last rows

	구분	부과년도	합계부과건수	합계부과금액(천원)	합계징수금액(천원)	시설물부과건수	시설물부과금액(천원)	시설물징수금액(천원)	자동차부과건수	자동차부과금액(천원)	자동차징수금액(천원)	데이터기준일
0	광주광역시 동구	2020	9773	601043	482036	<NA>	<NA>	<NA>	9773	601043	482036	2021-09-08
1	광주광역시 동구	2019	11112	678414	524244	<NA>	<NA>	<NA>	11112	678414	524244	2021-09-08
2	광주광역시 동구	2018	12700	759670	598333	<NA>	<NA>	12163	12700	759670	586170	2021-09-08
3	광주광역시 동구	2017	13897	822508	649563	<NA>	<NA>	15948	13897	822508	633615	2021-09-08
4	광주광역시 동구	2016	15587	918284	736761	<NA>	<NA>	24644	15587	918284	712117	2021-09-08
5	광주광역시 동구	2015	21783	1562373	1281873	4795	556104	527946	16988	1006269	753927	2021-09-08
6	광주광역시 동구	2014	22873	1646635	1325590	4808	576453	538761	18065	1070182	786829	2021-09-08
7	광주광역시 서구	2020	33068	2057749	1658829	<NA>	<NA>	<NA>	33068	2057749	1658829	2021-09-08
8	광주광역시 서구	2019	40473	2461768	1891371	<NA>	<NA>	<NA>	40473	2461768	1891371	2021-09-08
9	광주광역시 서구	2018	45935	2712375	2173815	<NA>	<NA>	<NA>	45935	2712375	2173815	2021-09-08

	구분	부과년도	합계부과건수	합계부과금액(천원)	합계징수금액(천원)	시설물부과건수	시설물부과금액(천원)	시설물징수금액(천원)	자동차부과건수	자동차부과금액(천원)	자동차징수금액(천원)	데이터기준일
25	광주광역시 북구	2016	81859	5052957	4419604	<NA>	<NA>	<NA>	81859	5052957	4419604	2021-09-08
26	광주광역시 북구	2015	98223	6537660	5923099	10840	1162933	1124245	87383	5374727	4798854	2021-09-08
27	광주광역시 북구	2014	102478	6745181	6160842	10667	1198276	1168606	91811	5546905	4992236	2021-09-08
28	광주광역시 광산구	2020	64861	3983112	3305538	<NA>	<NA>	<NA>	64861	3983112	3305538	2021-09-08
29	광주광역시 광산구	2019	66778	4593188	3667324	<NA>	<NA>	<NA>	66778	4593188	3667324	2021-09-08
30	광주광역시 광산구	2018	73348	4855184	4061474	<NA>	<NA>	<NA>	73348	4855184	4061474	2021-09-08
31	광주광역시 광산구	2017	80813	5206383	4623239	<NA>	<NA>	<NA>	80813	5206383	4623239	2021-09-08
32	광주광역시 광산구	2016	88826	5740281	5130217	<NA>	<NA>	<NA>	88826	5740281	5130217	2021-09-08
33	광주광역시 광산구	2015	104003	7023951	6443082	9299	902102	881247	94704	6121849	5561835	2021-09-08
34	광주광역시 광산구	2014	107835	7102499	6563924	8983	881524	862645	98852	6220975	5701279	2021-09-08

Overview

Variables

Common Values

Length

Common Values (Plot)

Interactions

Correlations

Missing values

Sample